Carrel name: keyword-node-cord Creating study carrel named keyword-node-cord Initializing database file: cache/cord-000196-lkoyrv3s.json key: cord-000196-lkoyrv3s authors: Salathé, Marcel; Jones, James H. title: Dynamics and Control of Diseases in Networks with Community Structure date: 2010-04-08 journal: PLoS Comput Biol DOI: 10.1371/journal.pcbi.1000736 sha: doc_id: 196 cord_uid: lkoyrv3s file: cache/cord-010739-28qfmj9x.json key: cord-010739-28qfmj9x authors: Sherborne, N.; Blyuss, K. B.; Kiss, I. Z. title: Bursting endemic bubbles in an adaptive network date: 2018-04-09 journal: nan DOI: 10.1103/physreve.97.042306 sha: doc_id: 10739 cord_uid: 28qfmj9x file: cache/cord-017590-w5copp1z.json key: cord-017590-w5copp1z authors: Fresnadillo, María J.; García, Enrique; García, José E.; Martín, Ángel; Rodríguez, Gerardo title: A SIS Epidemiological Model Based on Cellular Automata on Graphs date: 2009 journal: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living DOI: 10.1007/978-3-642-02481-8_160 sha: doc_id: 17590 cord_uid: w5copp1z file: cache/cord-016196-ub4mgqxb.json key: cord-016196-ub4mgqxb authors: Wang, Cheng; Zhang, Qing; Gan, Jianping title: Study on Efficient Complex Network Model date: 2012-11-20 journal: Proceedings of the 2nd International Conference on Green Communications and Networks 2012 (GCN 2012): Volume 5 DOI: 10.1007/978-3-642-35398-7_20 sha: doc_id: 16196 cord_uid: ub4mgqxb file: cache/cord-010727-fiukemh3.json key: cord-010727-fiukemh3 authors: Holme, Petter title: Three faces of node importance in network epidemiology: Exact results for small graphs date: 2017-12-05 journal: Phys Rev E DOI: 10.1103/physreve.96.062305 sha: doc_id: 10727 cord_uid: fiukemh3 file: cache/cord-024504-p2vxnn9z.json key: cord-024504-p2vxnn9z authors: Lyu, Tianshu; Sun, Fei; Zhang, Yan title: Node Conductance: A Scalable Node Centrality Measure on Big Networks date: 2020-04-17 journal: Advances in Knowledge Discovery and Data Mining DOI: 10.1007/978-3-030-47436-2_40 sha: doc_id: 24504 cord_uid: p2vxnn9z file: cache/cord-017062-dkw2sugl.json key: cord-017062-dkw2sugl authors: Singh, Indu; Swami, Rajan; Khan, Wahid; Sistla, Ramakrishna title: Delivery Systems for Lymphatic Targeting date: 2013-10-08 journal: Focal Controlled Drug Delivery DOI: 10.1007/978-1-4614-9434-8_20 sha: doc_id: 17062 cord_uid: dkw2sugl file: cache/cord-005090-l676wo9t.json key: cord-005090-l676wo9t authors: Gao, Chao; Liu, Jiming; Zhong, Ning title: Network immunization and virus propagation in email networks: experimental evaluation and analysis date: 2010-07-14 journal: Knowl Inf Syst DOI: 10.1007/s10115-010-0321-0 sha: doc_id: 5090 cord_uid: l676wo9t file: cache/cord-014845-odnlt6fr.json key: cord-014845-odnlt6fr authors: Wu, Jia; Chen, Zhigang title: Reducing Energy Consumption and Overhead Based on Mobile Health in Big Data Opportunistic Networks date: 2016-08-13 journal: Wirel Pers Commun DOI: 10.1007/s11277-016-3610-4 sha: doc_id: 14845 cord_uid: odnlt6fr file: cache/cord-027451-ztx9fsbg.json key: cord-027451-ztx9fsbg authors: De Chiara, Davide; Chinnici, Marta; Kor, Ah-Lian title: Data Mining for Big Dataset-Related Thermal Analysis of High Performance Computing (HPC) Data Center date: 2020-05-25 journal: Computational Science - ICCS 2020 DOI: 10.1007/978-3-030-50436-6_27 sha: doc_id: 27451 cord_uid: ztx9fsbg file: cache/cord-024499-14jlk5tv.json key: cord-024499-14jlk5tv authors: Balalau, Oana; Goyal, Sagar title: SubRank: Subgraph Embeddings via a Subgraph Proximity Measure date: 2020-04-17 journal: Advances in Knowledge Discovery and Data Mining DOI: 10.1007/978-3-030-47426-3_38 sha: doc_id: 24499 cord_uid: 14jlk5tv file: cache/cord-034545-onj7zpi1.json key: cord-034545-onj7zpi1 authors: Abuelkhail, Abdulrahman; Baroudi, Uthman; Raad, Muhammad; Sheltami, Tarek title: Internet of things for healthcare monitoring applications based on RFID clustering scheme date: 2020-11-03 journal: Wireless Netw DOI: 10.1007/s11276-020-02482-1 sha: doc_id: 34545 cord_uid: onj7zpi1 file: cache/cord-199630-2lmwnfda.json key: cord-199630-2lmwnfda authors: Ray, Sumanta; Lall, Snehalika; Mukhopadhyay, Anirban; Bandyopadhyay, Sanghamitra; Schonhuth, Alexander title: Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs date: 2020-07-05 journal: nan DOI: nan sha: doc_id: 199630 cord_uid: 2lmwnfda file: cache/cord-155475-is3su3ga.json key: cord-155475-is3su3ga authors: Kalogeratos, Argyris; Mannelli, Stefano Sarao title: Winning the competition: enhancing counter-contagion in SIS-like epidemic processes date: 2020-06-24 journal: nan DOI: nan sha: doc_id: 155475 cord_uid: is3su3ga file: cache/cord-102935-cx3elpb8.json key: cord-102935-cx3elpb8 authors: Hassani-Pak, Keywan; Singh, Ajit; Brandizi, Marco; Hearnshaw, Joseph; Amberkar, Sandeep; Phillips, Andrew L.; Doonan, John H.; Rawlings, Chris title: KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species date: 2020-04-24 journal: bioRxiv DOI: 10.1101/2020.04.02.017004 sha: doc_id: 102935 cord_uid: cx3elpb8 file: cache/cord-034824-eelqmzdx.json key: cord-034824-eelqmzdx authors: Guo, Chungu; Yang, Liangwei; Chen, Xiao; Chen, Duanbing; Gao, Hui; Ma, Jing title: Influential Nodes Identification in Complex Networks via Information Entropy date: 2020-02-21 journal: Entropy (Basel) DOI: 10.3390/e22020242 sha: doc_id: 34824 cord_uid: eelqmzdx file: cache/cord-010751-fgk05n3z.json key: cord-010751-fgk05n3z authors: Holme, Petter title: Objective measures for sentinel surveillance in network epidemiology date: 2018-08-15 journal: nan DOI: 10.1103/physreve.98.022313 sha: doc_id: 10751 cord_uid: fgk05n3z file: cache/cord-119522-2ua8218z.json key: cord-119522-2ua8218z authors: Reddy, C. Rajashekar; Mukku, T.; Dwivedi, A.; Rout, A.; Chaudhari, S.; Vemuri, K.; Rajan, K. S.; Hussain, A. M. title: Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors date: 2020-05-12 journal: nan DOI: nan sha: doc_id: 119522 cord_uid: 2ua8218z file: cache/cord-028688-5uzl1jpu.json key: cord-028688-5uzl1jpu authors: Li, Peisen; Wang, Guoyin; Hu, Jun; Li, Yun title: Multi-granularity Complex Network Representation Learning date: 2020-06-10 journal: Rough Sets DOI: 10.1007/978-3-030-52705-1_18 sha: doc_id: 28688 cord_uid: 5uzl1jpu file: cache/cord-322890-w78tftva.json key: cord-322890-w78tftva authors: Suran, Jantra Ngosuwan; Wyre, Nicole Rene title: IMAGING FINDINGS IN 14 DOMESTIC FERRETS (MUSTELA PUTORIUS FURO) WITH LYMPHOMA date: 2013-06-06 journal: Vet Radiol Ultrasound DOI: 10.1111/vru.12068 sha: doc_id: 322890 cord_uid: w78tftva file: cache/cord-269711-tw5armh8.json key: cord-269711-tw5armh8 authors: Ma, Junling; van den Driessche, P.; Willeboordse, Frederick H. title: The importance of contact network topology for the success of vaccination strategies date: 2013-05-21 journal: Journal of Theoretical Biology DOI: 10.1016/j.jtbi.2013.01.006 sha: doc_id: 269711 cord_uid: tw5armh8 file: cache/cord-284186-zf1w8ksm.json key: cord-284186-zf1w8ksm authors: Suran, J. N.; Latney, L. V.; Wyre, N. R. title: Radiographic and ultrasonographic findings of the spleen and abdominal lymph nodes in healthy domestic ferrets date: 2017-04-17 journal: J Small Anim Pract DOI: 10.1111/jsap.12680 sha: doc_id: 284186 cord_uid: zf1w8ksm file: cache/cord-020885-f667icyt.json key: cord-020885-f667icyt authors: Sharma, Ujjwal; Rudinac, Stevan; Worring, Marcel; Demmers, Joris; van Dolen, Willemijn title: Semantic Path-Based Learning for Review Volume Prediction date: 2020-03-17 journal: Advances in Information Retrieval DOI: 10.1007/978-3-030-45439-5_54 sha: doc_id: 20885 cord_uid: f667icyt file: cache/cord-168862-3tj63eve.json key: cord-168862-3tj63eve authors: Porter, Mason A. title: Nonlinearity + Networks: A 2020 Vision date: 2019-11-09 journal: nan DOI: nan sha: doc_id: 168862 cord_uid: 3tj63eve file: cache/cord-328875-fgeudou6.json key: cord-328875-fgeudou6 authors: Leung, Alexander K. C.; Davies, H. Dele title: Cervical lymphadenitis: Etiology, diagnosis, and management date: 2009-04-18 journal: Curr Infect Dis Rep DOI: 10.1007/s11908-009-0028-0 sha: doc_id: 328875 cord_uid: fgeudou6 file: cache/cord-024437-r5wnz7rq.json key: cord-024437-r5wnz7rq authors: Wang, Yubin; Zhang, Zhenyu; Liu, Tingwen; Guo, Li title: SLGAT: Soft Labels Guided Graph Attention Networks date: 2020-04-17 journal: Advances in Knowledge Discovery and Data Mining DOI: 10.1007/978-3-030-47426-3_40 sha: doc_id: 24437 cord_uid: r5wnz7rq file: cache/cord-196353-p05a8zjy.json key: cord-196353-p05a8zjy authors: Backhausz, 'Agnes; Bogn'ar, Edit title: Virus spread and voter model on random graphs with multiple type nodes date: 2020-02-17 journal: nan DOI: nan sha: doc_id: 196353 cord_uid: p05a8zjy file: cache/cord-026306-mkmrninv.json key: cord-026306-mkmrninv authors: Lepskiy, Alexander; Meshcheryakova, Natalia title: Belief Functions for the Importance Assessment in Multiplex Networks date: 2020-05-15 journal: Information Processing and Management of Uncertainty in Knowledge-Based Systems DOI: 10.1007/978-3-030-50143-3_22 sha: doc_id: 26306 cord_uid: mkmrninv file: cache/cord-007415-d57zqixs.json key: cord-007415-d57zqixs authors: da Fontoura Costa, Luciano; Sporns, Olaf; Antiqueira, Lucas; das Graças Volpe Nunes, Maria; Oliveira, Osvaldo N. title: Correlations between structure and random walk dynamics in directed complex networks date: 2007-07-30 journal: Appl Phys Lett DOI: 10.1063/1.2766683 sha: doc_id: 7415 cord_uid: d57zqixs file: cache/cord-248848-p7jv79ae.json key: cord-248848-p7jv79ae authors: Lee, Kookjin; Parish, Eric J. title: Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems date: 2020-10-28 journal: nan DOI: nan sha: doc_id: 248848 cord_uid: p7jv79ae file: cache/cord-355393-ot7hztyk.json key: cord-355393-ot7hztyk authors: Yuan, Peiyan; Tang, Shaojie title: Community-based immunization in opportunistic social networks date: 2015-02-15 journal: Physica A: Statistical Mechanics and its Applications DOI: 10.1016/j.physa.2014.10.087 sha: doc_id: 355393 cord_uid: ot7hztyk file: cache/cord-102394-vk4ag44m.json key: cord-102394-vk4ag44m authors: Zhang, Hai-Feng; Xie, Jia-Rong; Chen, Han-Shuang; Liu, Can; Small, Michael title: Impact of asymptomatic infection on coupled disease-behavior dynamics in complex networks date: 2016-08-14 journal: nan DOI: 10.1209/0295-5075/114/38004 sha: doc_id: 102394 cord_uid: vk4ag44m file: cache/cord-322746-28igib4l.json key: cord-322746-28igib4l authors: Gosche, John R.; Vick, Laura title: Acute, subacute, and chronic cervical lymphadenitis in children date: 2007-06-06 journal: Semin Pediatr Surg DOI: 10.1053/j.sempedsurg.2006.02.007 sha: doc_id: 322746 cord_uid: 28igib4l file: cache/cord-306727-2c1m04je.json key: cord-306727-2c1m04je authors: Pandey, Prateek; Litoriya, Ratnesh title: Promoting Trustless Computation Through Blockchain Technology date: 2020-05-20 journal: Natl Acad Sci Lett DOI: 10.1007/s40009-020-00978-0 sha: doc_id: 306727 cord_uid: 2c1m04je file: cache/cord-102588-vpu5w9wh.json key: cord-102588-vpu5w9wh authors: Le, Trang T.; Moore, Jason H. title: treeheatr: an R package for interpretable decision tree visualizations date: 2020-07-10 journal: bioRxiv DOI: 10.1101/2020.07.10.196352 sha: doc_id: 102588 cord_uid: vpu5w9wh file: cache/cord-028660-hi35xvni.json key: cord-028660-hi35xvni authors: Chen, Jie; Li, Yang; Zhao, Shu; Wang, Xiangyang; Zhang, Yanping title: Three-Way Decisions Community Detection Model Based on Weighted Graph Representation date: 2020-06-10 journal: Rough Sets DOI: 10.1007/978-3-030-52705-1_11 sha: doc_id: 28660 cord_uid: hi35xvni file: cache/cord-027178-tqj8jgem.json key: cord-027178-tqj8jgem authors: Tian, Changbo; Zhang, Yongzheng; Yin, Tao title: Modeling of Anti-tracking Network Based on Convex-Polytope Topology date: 2020-06-15 journal: Computational Science - ICCS 2020 DOI: 10.1007/978-3-030-50417-5_32 sha: doc_id: 27178 cord_uid: tqj8jgem file: cache/cord-319291-6l688krc.json key: cord-319291-6l688krc authors: Hung, Chun-Min; Huang, Yueh-Min; Chang, Ming-Shi title: Alignment using genetic programming with causal trees for identification of protein functions date: 2006-09-01 journal: Nonlinear Anal Theory Methods Appl DOI: 10.1016/j.na.2005.09.048 sha: doc_id: 319291 cord_uid: 6l688krc file: cache/cord-276178-0hrs1w7r.json key: cord-276178-0hrs1w7r authors: Bangotra, Deep Kumar; Singh, Yashwant; Selwal, Arvind; Kumar, Nagesh; Singh, Pradeep Kumar; Hong, Wei-Chiang title: An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare date: 2020-07-13 journal: Sensors (Basel) DOI: 10.3390/s20143887 sha: doc_id: 276178 cord_uid: 0hrs1w7r file: cache/cord-285350-64mzmiv3.json key: cord-285350-64mzmiv3 authors: Bhagatkar, Nikita; Dolas, Kapil; Ghosh, R. K.; Das, Sajal K. title: An integrated P2P framework for E-learning date: 2020-06-29 journal: Peer Peer Netw Appl DOI: 10.1007/s12083-020-00919-0 sha: doc_id: 285350 cord_uid: 64mzmiv3 file: cache/cord-125089-1lfmqzmc.json key: cord-125089-1lfmqzmc authors: Chandrasekhar, Arun G.; Goldsmith-Pinkham, Paul; Jackson, Matthew O.; Thau, Samuel title: Interacting Regional Policies in Containing a Disease date: 2020-08-24 journal: nan DOI: nan sha: doc_id: 125089 cord_uid: 1lfmqzmc file: cache/cord-349724-yq4dphmb.json key: cord-349724-yq4dphmb authors: Santos, Hugo; Alencar, Derian; Meneguette, Rodolfo; Rosário, Denis; Nobre, Jéferson; Both, Cristiano; Cerqueira, Eduardo; Braun, Torsten title: A Multi-Tier Fog Content Orchestrator Mechanism with Quality of Experience Support date: 2020-05-06 journal: nan DOI: 10.1016/j.comnet.2020.107288 sha: doc_id: 349724 cord_uid: yq4dphmb file: cache/cord-022561-rv5j1201.json key: cord-022561-rv5j1201 authors: Boes, Katie M.; Durham, Amy C. title: Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System date: 2017-02-17 journal: Pathologic Basis of Veterinary Disease DOI: 10.1016/b978-0-323-35775-3.00013-8 sha: doc_id: 22561 cord_uid: rv5j1201 Reading metadata file and updating bibliogrpahics === updating bibliographic database Building study carrel named keyword-node-cord === file2bib.sh === id: cord-017590-w5copp1z author: Fresnadillo, María J. title: A SIS Epidemiological Model Based on Cellular Automata on Graphs date: 2009 pages: extension: .txt txt: ./txt/cord-017590-w5copp1z.txt cache: ./cache/cord-017590-w5copp1z.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-017590-w5copp1z.txt' === file2bib.sh === id: cord-102935-cx3elpb8 author: Hassani-Pak, Keywan title: KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species date: 2020-04-24 pages: extension: .txt txt: ./txt/cord-102935-cx3elpb8.txt cache: ./cache/cord-102935-cx3elpb8.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-102935-cx3elpb8.txt' === file2bib.sh === id: cord-155475-is3su3ga author: Kalogeratos, Argyris title: Winning the competition: enhancing counter-contagion in SIS-like epidemic processes date: 2020-06-24 pages: extension: .txt txt: ./txt/cord-155475-is3su3ga.txt cache: ./cache/cord-155475-is3su3ga.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-155475-is3su3ga.txt' === file2bib.sh === id: cord-016196-ub4mgqxb author: Wang, Cheng title: Study on Efficient Complex Network Model date: 2012-11-20 pages: extension: .txt txt: ./txt/cord-016196-ub4mgqxb.txt cache: ./cache/cord-016196-ub4mgqxb.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-016196-ub4mgqxb.txt' === file2bib.sh === id: cord-010739-28qfmj9x author: Sherborne, N. title: Bursting endemic bubbles in an adaptive network date: 2018-04-09 pages: extension: .txt txt: ./txt/cord-010739-28qfmj9x.txt cache: ./cache/cord-010739-28qfmj9x.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-010739-28qfmj9x.txt' === file2bib.sh === id: cord-024499-14jlk5tv author: Balalau, Oana title: SubRank: Subgraph Embeddings via a Subgraph Proximity Measure date: 2020-04-17 pages: extension: .txt txt: ./txt/cord-024499-14jlk5tv.txt cache: ./cache/cord-024499-14jlk5tv.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-024499-14jlk5tv.txt' === file2bib.sh === id: cord-119522-2ua8218z author: Reddy, C. Rajashekar title: Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors date: 2020-05-12 pages: extension: .txt txt: ./txt/cord-119522-2ua8218z.txt cache: ./cache/cord-119522-2ua8218z.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-119522-2ua8218z.txt' === file2bib.sh === id: cord-007415-d57zqixs author: da Fontoura Costa, Luciano title: Correlations between structure and random walk dynamics in directed complex networks date: 2007-07-30 pages: extension: .txt txt: ./txt/cord-007415-d57zqixs.txt cache: ./cache/cord-007415-d57zqixs.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-007415-d57zqixs.txt' === file2bib.sh === id: cord-024504-p2vxnn9z author: Lyu, Tianshu title: Node Conductance: A Scalable Node Centrality Measure on Big Networks date: 2020-04-17 pages: extension: .txt txt: ./txt/cord-024504-p2vxnn9z.txt cache: ./cache/cord-024504-p2vxnn9z.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-024504-p2vxnn9z.txt' === file2bib.sh === id: cord-102588-vpu5w9wh author: Le, Trang T. title: treeheatr: an R package for interpretable decision tree visualizations date: 2020-07-10 pages: extension: .txt txt: ./txt/cord-102588-vpu5w9wh.txt cache: ./cache/cord-102588-vpu5w9wh.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-102588-vpu5w9wh.txt' === file2bib.sh === id: cord-010727-fiukemh3 author: Holme, Petter title: Three faces of node importance in network epidemiology: Exact results for small graphs date: 2017-12-05 pages: extension: .txt txt: ./txt/cord-010727-fiukemh3.txt cache: ./cache/cord-010727-fiukemh3.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-010727-fiukemh3.txt' === file2bib.sh === id: cord-306727-2c1m04je author: Pandey, Prateek title: Promoting Trustless Computation Through Blockchain Technology date: 2020-05-20 pages: extension: .txt txt: ./txt/cord-306727-2c1m04je.txt cache: ./cache/cord-306727-2c1m04je.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-306727-2c1m04je.txt' === file2bib.sh === id: cord-028660-hi35xvni author: Chen, Jie title: Three-Way Decisions Community Detection Model Based on Weighted Graph Representation date: 2020-06-10 pages: extension: .txt txt: ./txt/cord-028660-hi35xvni.txt cache: ./cache/cord-028660-hi35xvni.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-028660-hi35xvni.txt' === file2bib.sh === id: cord-026306-mkmrninv author: Lepskiy, Alexander title: Belief Functions for the Importance Assessment in Multiplex Networks date: 2020-05-15 pages: extension: .txt txt: ./txt/cord-026306-mkmrninv.txt cache: ./cache/cord-026306-mkmrninv.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-026306-mkmrninv.txt' === file2bib.sh === id: cord-024437-r5wnz7rq author: Wang, Yubin title: SLGAT: Soft Labels Guided Graph Attention Networks date: 2020-04-17 pages: extension: .txt txt: ./txt/cord-024437-r5wnz7rq.txt cache: ./cache/cord-024437-r5wnz7rq.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-024437-r5wnz7rq.txt' === file2bib.sh === id: cord-102394-vk4ag44m author: Zhang, Hai-Feng title: Impact of asymptomatic infection on coupled disease-behavior dynamics in complex networks date: 2016-08-14 pages: extension: .txt txt: ./txt/cord-102394-vk4ag44m.txt cache: ./cache/cord-102394-vk4ag44m.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-102394-vk4ag44m.txt' === file2bib.sh === id: cord-328875-fgeudou6 author: Leung, Alexander K. C. title: Cervical lymphadenitis: Etiology, diagnosis, and management date: 2009-04-18 pages: extension: .txt txt: ./txt/cord-328875-fgeudou6.txt cache: ./cache/cord-328875-fgeudou6.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-328875-fgeudou6.txt' === file2bib.sh === id: cord-020885-f667icyt author: Sharma, Ujjwal title: Semantic Path-Based Learning for Review Volume Prediction date: 2020-03-17 pages: extension: .txt txt: ./txt/cord-020885-f667icyt.txt cache: ./cache/cord-020885-f667icyt.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-020885-f667icyt.txt' === file2bib.sh === id: cord-014845-odnlt6fr author: Wu, Jia title: Reducing Energy Consumption and Overhead Based on Mobile Health in Big Data Opportunistic Networks date: 2016-08-13 pages: extension: .txt txt: ./txt/cord-014845-odnlt6fr.txt cache: ./cache/cord-014845-odnlt6fr.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-014845-odnlt6fr.txt' === file2bib.sh === id: cord-027451-ztx9fsbg author: De Chiara, Davide title: Data Mining for Big Dataset-Related Thermal Analysis of High Performance Computing (HPC) Data Center date: 2020-05-25 pages: extension: .txt txt: ./txt/cord-027451-ztx9fsbg.txt cache: ./cache/cord-027451-ztx9fsbg.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-027451-ztx9fsbg.txt' === file2bib.sh === id: cord-027178-tqj8jgem author: Tian, Changbo title: Modeling of Anti-tracking Network Based on Convex-Polytope Topology date: 2020-06-15 pages: extension: .txt txt: ./txt/cord-027178-tqj8jgem.txt cache: ./cache/cord-027178-tqj8jgem.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-027178-tqj8jgem.txt' === file2bib.sh === id: cord-028688-5uzl1jpu author: Li, Peisen title: Multi-granularity Complex Network Representation Learning date: 2020-06-10 pages: extension: .txt txt: ./txt/cord-028688-5uzl1jpu.txt cache: ./cache/cord-028688-5uzl1jpu.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-028688-5uzl1jpu.txt' === file2bib.sh === id: cord-034824-eelqmzdx author: Guo, Chungu title: Influential Nodes Identification in Complex Networks via Information Entropy date: 2020-02-21 pages: extension: .txt txt: ./txt/cord-034824-eelqmzdx.txt cache: ./cache/cord-034824-eelqmzdx.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-034824-eelqmzdx.txt' === file2bib.sh === id: cord-322746-28igib4l author: Gosche, John R. title: Acute, subacute, and chronic cervical lymphadenitis in children date: 2007-06-06 pages: extension: .txt txt: ./txt/cord-322746-28igib4l.txt cache: ./cache/cord-322746-28igib4l.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-322746-28igib4l.txt' === file2bib.sh === id: cord-199630-2lmwnfda author: Ray, Sumanta title: Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs date: 2020-07-05 pages: extension: .txt txt: ./txt/cord-199630-2lmwnfda.txt cache: ./cache/cord-199630-2lmwnfda.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-199630-2lmwnfda.txt' === file2bib.sh === id: cord-010751-fgk05n3z author: Holme, Petter title: Objective measures for sentinel surveillance in network epidemiology date: 2018-08-15 pages: extension: .txt txt: ./txt/cord-010751-fgk05n3z.txt cache: ./cache/cord-010751-fgk05n3z.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-010751-fgk05n3z.txt' === file2bib.sh === id: cord-284186-zf1w8ksm author: Suran, J. N. title: Radiographic and ultrasonographic findings of the spleen and abdominal lymph nodes in healthy domestic ferrets date: 2017-04-17 pages: extension: .txt txt: ./txt/cord-284186-zf1w8ksm.txt cache: ./cache/cord-284186-zf1w8ksm.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-284186-zf1w8ksm.txt' === file2bib.sh === id: cord-269711-tw5armh8 author: Ma, Junling title: The importance of contact network topology for the success of vaccination strategies date: 2013-05-21 pages: extension: .txt txt: ./txt/cord-269711-tw5armh8.txt cache: ./cache/cord-269711-tw5armh8.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-269711-tw5armh8.txt' === file2bib.sh === id: cord-355393-ot7hztyk author: Yuan, Peiyan title: Community-based immunization in opportunistic social networks date: 2015-02-15 pages: extension: .txt txt: ./txt/cord-355393-ot7hztyk.txt cache: ./cache/cord-355393-ot7hztyk.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-355393-ot7hztyk.txt' === file2bib.sh === id: cord-322890-w78tftva author: Suran, Jantra Ngosuwan title: IMAGING FINDINGS IN 14 DOMESTIC FERRETS (MUSTELA PUTORIUS FURO) WITH LYMPHOMA date: 2013-06-06 pages: extension: .txt txt: ./txt/cord-322890-w78tftva.txt cache: ./cache/cord-322890-w78tftva.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-322890-w78tftva.txt' === file2bib.sh === id: cord-000196-lkoyrv3s author: Salathé, Marcel title: Dynamics and Control of Diseases in Networks with Community Structure date: 2010-04-08 pages: extension: .txt txt: ./txt/cord-000196-lkoyrv3s.txt cache: ./cache/cord-000196-lkoyrv3s.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-000196-lkoyrv3s.txt' === file2bib.sh === id: cord-248848-p7jv79ae author: Lee, Kookjin title: Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems date: 2020-10-28 pages: extension: .txt txt: ./txt/cord-248848-p7jv79ae.txt cache: ./cache/cord-248848-p7jv79ae.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-248848-p7jv79ae.txt' === file2bib.sh === id: cord-196353-p05a8zjy author: Backhausz, 'Agnes title: Virus spread and voter model on random graphs with multiple type nodes date: 2020-02-17 pages: extension: .txt txt: ./txt/cord-196353-p05a8zjy.txt cache: ./cache/cord-196353-p05a8zjy.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 2 resourceName b'cord-196353-p05a8zjy.txt' === file2bib.sh === id: cord-005090-l676wo9t author: Gao, Chao title: Network immunization and virus propagation in email networks: experimental evaluation and analysis date: 2010-07-14 pages: extension: .txt txt: ./txt/cord-005090-l676wo9t.txt cache: ./cache/cord-005090-l676wo9t.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-005090-l676wo9t.txt' === file2bib.sh === id: cord-349724-yq4dphmb author: Santos, Hugo title: A Multi-Tier Fog Content Orchestrator Mechanism with Quality of Experience Support date: 2020-05-06 pages: extension: .txt txt: ./txt/cord-349724-yq4dphmb.txt cache: ./cache/cord-349724-yq4dphmb.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-349724-yq4dphmb.txt' === file2bib.sh === id: cord-034545-onj7zpi1 author: Abuelkhail, Abdulrahman title: Internet of things for healthcare monitoring applications based on RFID clustering scheme date: 2020-11-03 pages: extension: .txt txt: ./txt/cord-034545-onj7zpi1.txt cache: ./cache/cord-034545-onj7zpi1.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-034545-onj7zpi1.txt' === file2bib.sh === id: cord-125089-1lfmqzmc author: Chandrasekhar, Arun G. title: Interacting Regional Policies in Containing a Disease date: 2020-08-24 pages: extension: .txt txt: ./txt/cord-125089-1lfmqzmc.txt cache: ./cache/cord-125089-1lfmqzmc.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-125089-1lfmqzmc.txt' === file2bib.sh === id: cord-276178-0hrs1w7r author: Bangotra, Deep Kumar title: An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare date: 2020-07-13 pages: extension: .txt txt: ./txt/cord-276178-0hrs1w7r.txt cache: ./cache/cord-276178-0hrs1w7r.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-276178-0hrs1w7r.txt' === file2bib.sh === id: cord-319291-6l688krc author: Hung, Chun-Min title: Alignment using genetic programming with causal trees for identification of protein functions date: 2006-09-01 pages: extension: .txt txt: ./txt/cord-319291-6l688krc.txt cache: ./cache/cord-319291-6l688krc.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-319291-6l688krc.txt' === file2bib.sh === id: cord-017062-dkw2sugl author: Singh, Indu title: Delivery Systems for Lymphatic Targeting date: 2013-10-08 pages: extension: .txt txt: ./txt/cord-017062-dkw2sugl.txt cache: ./cache/cord-017062-dkw2sugl.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-017062-dkw2sugl.txt' === file2bib.sh === id: cord-285350-64mzmiv3 author: Bhagatkar, Nikita title: An integrated P2P framework for E-learning date: 2020-06-29 pages: extension: .txt txt: ./txt/cord-285350-64mzmiv3.txt cache: ./cache/cord-285350-64mzmiv3.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 4 resourceName b'cord-285350-64mzmiv3.txt' === file2bib.sh === id: cord-168862-3tj63eve author: Porter, Mason A. title: Nonlinearity + Networks: A 2020 Vision date: 2019-11-09 pages: extension: .txt txt: ./txt/cord-168862-3tj63eve.txt cache: ./cache/cord-168862-3tj63eve.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 3 resourceName b'cord-168862-3tj63eve.txt' === file2bib.sh === id: cord-022561-rv5j1201 author: Boes, Katie M. title: Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System date: 2017-02-17 pages: extension: .txt txt: ./txt/cord-022561-rv5j1201.txt cache: ./cache/cord-022561-rv5j1201.txt Content-Encoding UTF-8 Content-Type text/plain; charset=UTF-8 X-Parsed-By ['org.apache.tika.parser.DefaultParser', 'org.apache.tika.parser.csv.TextAndCSVParser'] X-TIKA:content_handler ToTextContentHandler X-TIKA:embedded_depth 0 X-TIKA:parse_time_millis 5 resourceName b'cord-022561-rv5j1201.txt' Que is empty; done keyword-node-cord === reduce.pl bib === id = cord-000196-lkoyrv3s author = Salathé, Marcel title = Dynamics and Control of Diseases in Networks with Community Structure date = 2010-04-08 pages = extension = .txt mime = text/plain words = 6817 sentences = 322 flesch = 51 summary = Running standard susceptible-infected-resistant (SIR) epidemic simulations (see Methods) on these networks, we find that the average epidemic size, epidemic duration and the peak prevalence of the epidemic are strongly affected by a change in community structure connectivity that is independent of the overall degree distribution of the full network ( Figure 1 ). While infections are most likely to spread along the shortest paths between any two nodes, the cumulative contribution of other paths can still be important [40] : immunization strategies based on random walk centrality result in the lowest number of infected cases at low vaccination coverage (Figure 4b and 4c ). In practice, identifying immunization targets may be impossible using such algorithms, because the structure of the contact network relevant for the spread of a directly transmissible disease is generally not known. cache = ./cache/cord-000196-lkoyrv3s.txt txt = ./txt/cord-000196-lkoyrv3s.txt === reduce.pl bib === id = cord-017590-w5copp1z author = Fresnadillo, María J. title = A SIS Epidemiological Model Based on Cellular Automata on Graphs date = 2009 pages = extension = .txt mime = text/plain words = 2757 sentences = 169 flesch = 61 summary = The main goal of this work is to introduce a new SIS epidemic model based on a particular type of finite state machines called cellular automata on graphs. The state of each cell stands for the fraction of the susceptible and infected individuals of the cell at a particular time step and the evolution of these classes is given in terms of a local transition function. The model introduced in this paper deals with SIS epidemic diseases (for example the group of those responsible for the common cold), that is, the population is divided into susceptible individuals (S) and infected individuals (I). The main goal of this work is to introduce a new SIS model to simulate the spread of a general epidemic based on cellular automata on graph. Nevertheless, in this paper we will consider a more efficient topology to model an epidemic disease, which is given by an undirected graph where its nodes stand for the cells of the cellular automata. cache = ./cache/cord-017590-w5copp1z.txt txt = ./txt/cord-017590-w5copp1z.txt === reduce.pl bib === id = cord-010739-28qfmj9x author = Sherborne, N. title = Bursting endemic bubbles in an adaptive network date = 2018-04-09 pages = extension = .txt mime = text/plain words = 3350 sentences = 178 flesch = 55 summary = Adaptive network models that account for both epidemic and behavioral change have found oscillations, but in an extremely narrow region of the parameter space, which contrasts with intuition and available data. In this paper we propose a simple susceptible-infected-susceptible epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space. [13] showed that cutting links between susceptible and infected individuals can lead to epidemic reemergence, with long periods of low disease prevalence punctuated by large outbreaks. Figure 2 (d) illustrates this behavior both in simulation and in the meanfield model (4) , showing how after the initial outbreak each new wave of infection is preceded by the recovery of network connectivity. Furthermore, since rewiring nodes choose their new neighbors uniformly at random from all available susceptible nodes, the initial network topology itself is transient, as shown in Fig. 4 , and, as a result, over time our model becomes more relevant. cache = ./cache/cord-010739-28qfmj9x.txt txt = ./txt/cord-010739-28qfmj9x.txt === reduce.pl bib === id = cord-016196-ub4mgqxb author = Wang, Cheng title = Study on Efficient Complex Network Model date = 2012-11-20 pages = extension = .txt mime = text/plain words = 2486 sentences = 92 flesch = 51 summary = This paper summarizes the relevant research of the complex network systematically based on Statistical Property, Structural Model, and Dynamical Behavior. An important discover in the complex network researching is that the average path length of the most of the large-scale real networks is much less than our imagine, which we call ''Small-world Effect''. Paul Erdös and Alfred Rényi discovered a complete random network model in the late 50s twentieth century, it is made of any two nodes which connected with probability p in the graph made of N nodes, its average degree is \k [ ¼ pðN À 1Þ % PN; the average path length l : ln N= lnð\k [ Þ; the convergence factor C ¼ P; when the value of N is very large, the distribution of the node degree approximately equals poisson distribution. However, the regular network has aggregation, but its average shortest path length is larger, random graph has the opposite property, having small-world and less convergence factor. cache = ./cache/cord-016196-ub4mgqxb.txt txt = ./txt/cord-016196-ub4mgqxb.txt === reduce.pl bib === id = cord-010727-fiukemh3 author = Holme, Petter title = Three faces of node importance in network epidemiology: Exact results for small graphs date = 2017-12-05 pages = extension = .txt mime = text/plain words = 4712 sentences = 279 flesch = 63 summary = We investigate three aspects of the importance of nodes with respect to susceptible-infectious-removed (SIR) disease dynamics: influence maximization (the expected outbreak size given a set of seed nodes), the effect of vaccination (how much deleting nodes would reduce the expected outbreak size), and sentinel surveillance (how early an outbreak could be detected with sensors at a set of nodes). [13] is a bit different from ours-they call important nodes for vaccination "blockers" and important nodes for influence maximization "spreaders".) * holme@cns.pi.titech.ac.jp We will proceed by discussing our setup in greater detail: our implementation of the SIR model, how to analyze the three aspects of importance, network centrality measures that we need for our analysis, and our results, including the smallest networks where different nodes come out as most important. This is the smallest graph where the most important single node (n = 1) is different for influence maximization, vaccination, and sentinel surveillance. cache = ./cache/cord-010727-fiukemh3.txt txt = ./txt/cord-010727-fiukemh3.txt === reduce.pl bib === id = cord-017062-dkw2sugl author = Singh, Indu title = Delivery Systems for Lymphatic Targeting date = 2013-10-08 pages = extension = .txt mime = text/plain words = 9733 sentences = 491 flesch = 39 summary = The major purpose of lymphatic targeting is to provide an effective anticancer chemotherapy to prevent the metastasis of cancer cells by accumulating the drug in the regional lymph node. Hydrophilic multiwalled carbon nanotubes (MWNTs) coated with magnetic nanoparticles (MN-MWNTs) have emerged as an effective delivery system for lymphatic targeting following subcutaneous injection of these particles into the left footpad of Sprague Dawley rats; the left popliteal lymph nodes were dyed black. In vivo study, about eight times lymph node uptake of LyP-1-NPs was seen in metastasis than that of NPs, indicated LyP-1-NP as a promising carrier for targetspecifi c drug delivery to lymphatic metastatic tumours [ 129 ] . To improve carrier retention in lymph nodes, a new method of increasing lymphatic uptake of subcutaneously injected liposome utilises the high-affi nity ligands biotin and avidin. cache = ./cache/cord-017062-dkw2sugl.txt txt = ./txt/cord-017062-dkw2sugl.txt === reduce.pl bib === id = cord-024504-p2vxnn9z author = Lyu, Tianshu title = Node Conductance: A Scalable Node Centrality Measure on Big Networks date = 2020-04-17 pages = extension = .txt mime = text/plain words = 4036 sentences = 277 flesch = 63 summary = Moreover, with the help of node embedding techniques, Node Conductance is able to be approximately calculated on big networks effectively and efficiently. Thorough experiments present the differences between existing centralities and Node Conductance, its outstanding ability of detecting influential nodes on both static and dynamic network, and its superior efficiency compared with other global centralities. Random walk, which Node Conductance is based on, is also an effective sampling strategy to capture node neighborhood in the recent network embedding studies [10, 21] . We visualize the special case, football network, in order to have an intuitive sense of the properties of Degree, Betweenness, and Node Conductance (other centralities are presented in the Supplementary Material). Comparing with the existing global centralities, Node Conductance computed by DeepWalk is much more scalable and capable to be performed on big datasets. We also rethink the widely used network representation model, DeepWalk, and calculate Node Conductance approximately by the dot product of the input and output vectors. cache = ./cache/cord-024504-p2vxnn9z.txt txt = ./txt/cord-024504-p2vxnn9z.txt === reduce.pl bib === id = cord-199630-2lmwnfda author = Ray, Sumanta title = Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs date = 2020-07-05 pages = extension = .txt mime = text/plain words = 6389 sentences = 379 flesch = 53 summary = Therefore, host-(1) We link existing high-quality, long-term curated and refined, large scale drug/protein -protein interaction data with (2) molecular interaction data on SARS-CoV-2 itself, raised only a handful of weeks ago, (3) exploit the resulting overarching network using most advanced, AI boosted techniques (4) for repurposing drugs in the fight against SARS-CoV-2 (5) in the frame of HDT based strategies. As for (3)-(5), we will highlight interactions between SARS-Cov-2-host protein and human proteins important for the virus to persist using most advanced deep learning techniques that cater to exploiting network data. As per our simulation study, a large fraction, if not the vast majority of the predictions establish true, hence actionable interactions between drugs on the one hand and SARS-CoV-2 associated human proteins (hence of use in HDT) on the other hand. cache = ./cache/cord-199630-2lmwnfda.txt txt = ./txt/cord-199630-2lmwnfda.txt === reduce.pl bib === id = cord-024499-14jlk5tv author = Balalau, Oana title = SubRank: Subgraph Embeddings via a Subgraph Proximity Measure date = 2020-04-17 pages = extension = .txt mime = text/plain words = 3741 sentences = 265 flesch = 63 summary = We show that our subgraph embeddings are comprehensive and achieve competitive performance on three important data mining tasks: community detection, link prediction, and cascade growth prediction. A cascade graph is sampled for a set of random walks, which are given as input to a gated neural network to predict the future size of the cascade. In [3] , the authors propose an inductive framework for computing graph embeddings, based on training an attention network to predict a graph proximity measure, such as graph edit distance. Given a graph G = (V, E) and set of subgraphs of G, S = {S 1 , S 2 , · · · , S k }, we learn their representations as dense vectors, i.e. as embeddings. cache = ./cache/cord-024499-14jlk5tv.txt txt = ./txt/cord-024499-14jlk5tv.txt === reduce.pl bib === id = cord-005090-l676wo9t author = Gao, Chao title = Network immunization and virus propagation in email networks: experimental evaluation and analysis date = 2010-07-14 pages = extension = .txt mime = text/plain words = 8030 sentences = 495 flesch = 58 summary = For example, computer scientists focus on algorithms and the computational complexities of strategies, i.e. how to quickly search a short path from one "seed" node to a targeted node just based on local information, and then effectively and efficiently restrain virus propagation [42] . Section 4 describes the experiments which are performed to compare different immunization strategies with the measurements of the immunization efficiency, the cost and the robustness in both synthetic networks (including a synthetic community-based network) and two real email networks (the Enron and a university email network), and analyze the effects of network structures and human dynamics on virus propagation. It is readily to observe the microscopic process of worm propagating through this model, and uncover the effects of different factors (e.g. the power-law exponent, human dynamics and the average path length of the network) on virus propagation and immunization strategies. cache = ./cache/cord-005090-l676wo9t.txt txt = ./txt/cord-005090-l676wo9t.txt === reduce.pl bib === id = cord-155475-is3su3ga author = Kalogeratos, Argyris title = Winning the competition: enhancing counter-contagion in SIS-like epidemic processes date = 2020-06-24 pages = extension = .txt mime = text/plain words = 2821 sentences = 181 flesch = 60 summary = Motivated by social epidemics, we apply this method to a generic continuous-time SIS-like diffusion model where we allow for: i) arbitrary node transition rate functions that describe the dynamics of propagation depending on the network state, and ii) competition between the healthy (positive) and infected (negative) states, which are both diffusive at the same time, yet mutually exclusive on each node. Among them, the Largest Reduction in Infectious Edges (LRIE) [9] results to be the optimal greedy algorithm for resource allocation under limitations in the resource budget, in the N -intertwined Susceptible-Infected-Susceptible (SIS) epidemic model. In this study, we propose the Generalized Largest Reduction in Infectious Edges (gLRIE) strategy, which is adapted for the diffusion competition of recurrent epidemics, as well as nonlinearity and saturation of the functions of node transition rates. cache = ./cache/cord-155475-is3su3ga.txt txt = ./txt/cord-155475-is3su3ga.txt === reduce.pl bib === id = cord-014845-odnlt6fr author = Wu, Jia title = Reducing Energy Consumption and Overhead Based on Mobile Health in Big Data Opportunistic Networks date = 2016-08-13 pages = extension = .txt mime = text/plain words = 5394 sentences = 405 flesch = 64 summary = title: Reducing Energy Consumption and Overhead Based on Mobile Health in Big Data Opportunistic Networks This algorithm can reduce energy consumption and overhead, then improve deliver ratio in big data communication. Compare with Spray and Wait algorithm, Binary spray and wait algorithm in opportunistic networks, this algorithm acquires good results by reduce energy consumption, overhead and deliver ratio. This algorithm can judge routing request and predict data data packets and then can overhead, energy consumption and deliver ratio in transmission. From what has been discussed above, ADTRA needs to solve energy consumption, overhead and deliver ratio when the algorithm is applied of big data environment. In wireless communication, if doctors or hospitals send all pictures to patients, many network resource must be wasted, especially in big data environment, mass of people join in transmission, there are no enough space storing effective information. cache = ./cache/cord-014845-odnlt6fr.txt txt = ./txt/cord-014845-odnlt6fr.txt === reduce.pl bib === id = cord-034824-eelqmzdx author = Guo, Chungu title = Influential Nodes Identification in Complex Networks via Information Entropy date = 2020-02-21 pages = extension = .txt mime = text/plain words = 5770 sentences = 397 flesch = 55 summary = In this paper, we propose the EnRenew algorithm aimed to identify a set of influential nodes via information entropy. Compared with the best state-of-the-art benchmark methods, the performance of proposed algorithm improved by 21.1%, 7.0%, 30.0%, 5.0%, 2.5%, and 9.0% in final affected scale on CEnew, Email, Hamster, Router, Condmat, and Amazon network, respectively, under the Susceptible-Infected-Recovered (SIR) simulation model. The impressive results on the SIR simulation model shed light on new method of node mining in complex networks for information spreading and epidemic prevention. defined the problem of identifying a set of influential spreaders in complex networks as influence maximization problem [57] , and they used hill-climbing based greedy algorithm that is within 63% of optimal in several models. Besides, to make the algorithm practically more useful, we provide EnRenew's source code and all the experiments details on https://github.com/YangLiangwei/Influential-nodes-identification-in-complex-networksvia-information-entropy, and researchers can download it freely for their convenience. cache = ./cache/cord-034824-eelqmzdx.txt txt = ./txt/cord-034824-eelqmzdx.txt === reduce.pl bib === id = cord-034545-onj7zpi1 author = Abuelkhail, Abdulrahman title = Internet of things for healthcare monitoring applications based on RFID clustering scheme date = 2020-11-03 pages = extension = .txt mime = text/plain words = 7772 sentences = 433 flesch = 62 summary = The mathematical model optimizes the following objective functions: (1) minimizing the total distance between CHs and CMs to improve positioning accuracy; and (2) minimizing the number of clusters which reduces the signal transmission traffic Feature 6 (F-6): two level security is obtained by when a node writes data to its RFID tag, the data is signed with a signature, which is a hash value, the obtained hash is encrypted with a AES 128 bits shared key cache = ./cache/cord-034545-onj7zpi1.txt txt = ./txt/cord-034545-onj7zpi1.txt === reduce.pl bib === id = cord-027451-ztx9fsbg author = De Chiara, Davide title = Data Mining for Big Dataset-Related Thermal Analysis of High Performance Computing (HPC) Data Center date = 2020-05-25 pages = extension = .txt mime = text/plain words = 5758 sentences = 326 flesch = 51 summary = This work presents an algorithm that clusters hotspots with the goal of reducing a data centre's large thermal-gradient due to uneven distribution of server dissipated waste heat followed by increasing cooling effectiveness. Thermal-aware schedulers adopt different thermal-aware approaches (e.g. system-level for work placements [16] ; execute 'hot' jobs on 'cold' compute nodes; predictive model for job schedule selection [17] ; ranked node queue based on thermal characteristics of rack layouts and optimisation (e.g. optimal setpoints for workload distribution and supply temperature of the cooling system). Analysis conducted are as follows: hotspots localisation; users categorisations based on submitted jobs to CRESCO6 cluster; compute nodes categorisation based on thermal behaviour of internal and surrounding air temperatures due to workload related waste heat dissipation. Data collected are related to: relevant parameters for each node (e.g. inlet air temperature, internal temperature of each node, energy consumption of CPU, RAM, memory, etc…); environmental parameters (e.g. air temperatures and humidity in both the hot and cold aisles); cooling system related parameters (e.g. fan speed); and finally, individual users who submit their jobs to cluster node. cache = ./cache/cord-027451-ztx9fsbg.txt txt = ./txt/cord-027451-ztx9fsbg.txt === reduce.pl bib === id = cord-102935-cx3elpb8 author = Hassani-Pak, Keywan title = KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species date = 2020-04-24 pages = extension = .txt mime = text/plain words = 2172 sentences = 119 flesch = 60 summary = Here we report the main design principles behind KnetMiner and provide use cases for mining public datasets to identify unknown links between traits such grain colour and pre-harvest sprouting in Triticum aestivum, as well as, an evidence-based approach to identify candidate genes under an Arabidopsis thaliana petal size QTL. KnetMiner is the first open-source gene discovery platform that can leverage genome-scale knowledge graphs, generate evidence-based biological networks and be deployed for any species with a sequenced genome. Even when 38 the task of gathering information is complete, it is demanding to assemble a coherent view of how 39 each piece of evidence might come together to "tell a story" about the biology that can explain how 40 multiple genes might be implicated in a complex trait or disease. cache = ./cache/cord-102935-cx3elpb8.txt txt = ./txt/cord-102935-cx3elpb8.txt === reduce.pl bib === id = cord-010751-fgk05n3z author = Holme, Petter title = Objective measures for sentinel surveillance in network epidemiology date = 2018-08-15 pages = extension = .txt mime = text/plain words = 5591 sentences = 332 flesch = 64 summary = Then problem of optimizing sentinel surveillance in networks is to identify the nodes to probe such that an emerging disease outbreak can be discovered early or reliably. Furthermore, we do not find one type of network structure that predicts the objective measures, i.e., that depends both on the data set and the SIR parameter values. Finally, if the objective is to stop the disease as early as possible, it makes sense to measure the time to extinction or detection (infection of a sentinel) [13] . Just as for the case of static networks, τ (t x , f d ) is always nonpositive, meaning the time to detection or extinction ranks the nodes in a way positively correlated with the frequency of detection. In Fig. 4 , we show the correlation between our three objective measures and the structural descriptors as a function of β for the Office data set. cache = ./cache/cord-010751-fgk05n3z.txt txt = ./txt/cord-010751-fgk05n3z.txt === reduce.pl bib === id = cord-119522-2ua8218z author = Reddy, C. Rajashekar title = Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors date = 2020-05-12 pages = extension = .txt mime = text/plain words = 3573 sentences = 211 flesch = 62 summary = This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes. For this, total nine low-cost IoT nodes monitoring particulate matter (PM), which is one of the most dominant pollutants, are deployed in a small educational campus in Indian city of Hyderabad. This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes in Indian urban conditions. For spatial interpolation, inverse distance weighing (IDW) scheme is used on these nodes for the data collected before and during the bursting of firecrackers on the main night of Diwali (one of the most popular festivals in India) to show the variability pattern in a small campus, hot spot detection and need for a dense deployment to provide better local pollution indicators. cache = ./cache/cord-119522-2ua8218z.txt txt = ./txt/cord-119522-2ua8218z.txt === reduce.pl bib === id = cord-028688-5uzl1jpu author = Li, Peisen title = Multi-granularity Complex Network Representation Learning date = 2020-06-10 pages = extension = .txt mime = text/plain words = 4539 sentences = 277 flesch = 46 summary = In this paper, we propose a multi-granularity complex network representation learning model (MNRL), which integrates topological structure and additional information at the same time, and presents these fused information learning into the same granularity semantic space that through fine-to-coarse to refine the complex network. A series of deep learning-based network representation methods were then proposed to further solve the problems of global topological structure preservation and high-order nonlinearity of data, and increased efficiency. So these location attributes and activity information are inherently indecomposable and interdependence with the suspect, making the two nodes recognize at a finer granularity based on the additional information and relationship structure that the low-dimensional representation vectors learned have certain similarities. To better characterize multiple granularity complex networks and solve the problem of nodes with potential associations that cannot be processed through the relationship structure alone, we refine the granularity to additional attributes, and designed an information fusion method, which are defined as follows: cache = ./cache/cord-028688-5uzl1jpu.txt txt = ./txt/cord-028688-5uzl1jpu.txt === reduce.pl bib === id = cord-322890-w78tftva author = Suran, Jantra Ngosuwan title = IMAGING FINDINGS IN 14 DOMESTIC FERRETS (MUSTELA PUTORIUS FURO) WITH LYMPHOMA date = 2013-06-06 pages = extension = .txt mime = text/plain words = 6858 sentences = 414 flesch = 46 summary = Radiographs, CT, MRI, static ultrasound images, and when available, ultrasound cine loops were retrospectively evaluated, and abnormal findings were recorded by J.N.S. The imaging reports generated by a board-certified veterinary radiologist at the time the study was performed were also reviewed. Cytology of the right renal mass in the first ferret was not performed; however, the patient received chemotherapy for the treatment of lymphoma, confirmed from aspiration and biopsy of an enlarged lymph node, and the mass was seen to decrease in size during follow-up studies (Fig. 5) . Concurrent abdominal imaging findings considered incidental to the diagnosed lymphoma included renal cysts (8) , cystic lymph nodes (7), adrenomegaly in ferrets with diagnosed adrenal disease (5), and pancreatic nodules in ferrets diagnosed with insulinoma (2). Additional radiographic findings in this ferret included splenomegaly, hepatomegaly, and abdominal masses consistent with enlarged lymph nodes. cache = ./cache/cord-322890-w78tftva.txt txt = ./txt/cord-322890-w78tftva.txt === reduce.pl bib === id = cord-269711-tw5armh8 author = Ma, Junling title = The importance of contact network topology for the success of vaccination strategies date = 2013-05-21 pages = extension = .txt mime = text/plain words = 7036 sentences = 417 flesch = 60 summary = Abstract The effects of a number of vaccination strategies on the spread of an SIR type disease are numerically investigated for several common network topologies including random, scale-free, small world, and meta-random networks. These strategies, namely, prioritized, random, follow links and contact tracing, are compared across networks using extensive simulations with disease parameters relevant for viruses such as pandemic influenza H1N1/09. (2006) compared the efficacy of contact tracing on random and scale-free networks and found that for transmission rates greater than a certain threshold, the final epidemic size is smaller on a scale-free network than on a corresponding random network, while they considered the effects of degree correlations in Kiss et al. We investigate numerically whether network topologies affect the effectiveness of vaccination strategies started with a delay after the disease is widespread; for example, a 40 day delay as in the second wave of the 2009 influenza pandemic in British Columbia, Canada (Office of the Provincial Health Officer, 2010). cache = ./cache/cord-269711-tw5armh8.txt txt = ./txt/cord-269711-tw5armh8.txt === reduce.pl bib === id = cord-284186-zf1w8ksm author = Suran, J. N. title = Radiographic and ultrasonographic findings of the spleen and abdominal lymph nodes in healthy domestic ferrets date = 2017-04-17 pages = extension = .txt mime = text/plain words = 6084 sentences = 351 flesch = 53 summary = The goal of this prospective, cross-sectional study was to describe the characteristics of the spleen and abdominal lymph nodes on radiographs and with ultrasound in a sample of clientowned, clinically healthy domestic ferrets ( Mustela putorius furo ). For the calculation of sample sizes, the standard deviations of previously reported measurements of abdominal viscera in clinically healthy ferrets were compared, including gross renal measurements (1·25, 1·5 mm), ultrasonographic adrenal thickness (0·5, 0·6 mm) and ultrasonographic jejunal lymph node thickness (1·39, 2.0 mm) (O ' Brien et al . The results presented in this study provide the most comprehensive evaluation of the spleen and abdominal lymph nodes with radiographs and ultrasound in clinically healthy ferrets to date. Based on the results of this study, the jejunal, pancreaticoduodenal, hepatic and caudal mesenteric lymph nodes can be routinely detected with ultrasound in most ferrets. cache = ./cache/cord-284186-zf1w8ksm.txt txt = ./txt/cord-284186-zf1w8ksm.txt === reduce.pl bib === id = cord-168862-3tj63eve author = Porter, Mason A. title = Nonlinearity + Networks: A 2020 Vision date = 2019-11-09 pages = extension = .txt mime = text/plain words = 11845 sentences = 667 flesch = 50 summary = However, recent uses of the term "network" have focused increasingly on connectivity patterns that are more general than graphs [98] : a network's nodes and/or edges (or their associated weights) can change in time [70, 72] (see Section 3), nodes and edges can include annotations [26] , a network can include multiple types of edges and/or multiple types of nodes [90, 140] , it can have associated dynamical processes [142] (see Sections 3, 4, and 5) , it can include memory [152] , connections can occur between an arbitrary number of entities [127, 131] (see Section 6) , and so on. Following a long line of research in sociology [37] , two important ingredients in the study of networks are examining (1) the importances ("centralities") of nodes, edges, and other small network structures and the relationship of measures of importance to dynamical processes on networks and (2) the large-scale organization of networks [121, 193] . cache = ./cache/cord-168862-3tj63eve.txt txt = ./txt/cord-168862-3tj63eve.txt === reduce.pl bib === id = cord-020885-f667icyt author = Sharma, Ujjwal title = Semantic Path-Based Learning for Review Volume Prediction date = 2020-03-17 pages = extension = .txt mime = text/plain words = 4026 sentences = 245 flesch = 48 summary = In this work, we present an approach that uses semantically meaningful, bimodal random walks on real-world heterogeneous networks to extract correlations between nodes and bring together nodes with shared or similar attributes. In this work, -We propose a novel method that incorporates restaurants and their attributes into a multimodal graph and extracts multiple, bimodal low dimensional representations for restaurants based on available paths through shared visual, textual, geographical and categorical features. In this section, we discuss prior work that leverages graph-based structures for extracting information from multiple modalities, focussing on the auto-captioning task that introduced such methods. For each of these sub-networks, we perform random walks and use a variant of the heterogeneous skip-gram objective introduced in [6] to generate low-dimensional bimodal embeddings. Our attention-based model combines separately learned bimodal embeddings using a late-fusion setup for predicting the review volume of the restaurants. cache = ./cache/cord-020885-f667icyt.txt txt = ./txt/cord-020885-f667icyt.txt === reduce.pl bib === id = cord-328875-fgeudou6 author = Leung, Alexander K. C. title = Cervical lymphadenitis: Etiology, diagnosis, and management date = 2009-04-18 pages = extension = .txt mime = text/plain words = 3893 sentences = 235 flesch = 39 summary = Acute bilateral cervical lymphadenitis is usually caused by a viral upper respiratory tract infection or streptococcal pharyngitis. Generalized lymphadenopathy is often caused by a viral infection, and less frequently by malignancies, collagen vascular diseases, and medications. Offending organisms usually fi rst infect the upper respiratory tract, anterior nares, oral cavity, or skin in the head and neck area before spreading to the cervical lymph nodes. Bartonella henselae (cat-scratch disease), nontuberculosis mycobacteria (eg, Mycobacterium avium-intracellulare, Mycobacterium scrofulaceum ), and Mycobacterium tuberculosis ("scrofula") are important causes of subacute or chronic cervical lymphadenopathy [ 8 ] . Kikuchi-Fujimoto disease (histocytic necrotizing lymphadenitis) is a benign cause of lymph node enlargement, usually in the posterior cervical triangle [ 9 ] . Acute bilateral cervical lymphadenitis is usually caused by a viral upper respiratory tract infection or pharyngitis due to S. cache = ./cache/cord-328875-fgeudou6.txt txt = ./txt/cord-328875-fgeudou6.txt === reduce.pl bib === id = cord-196353-p05a8zjy author = Backhausz, 'Agnes title = Virus spread and voter model on random graphs with multiple type nodes date = 2020-02-17 pages = extension = .txt mime = text/plain words = 7550 sentences = 429 flesch = 62 summary = The two processes can be connected by the following idea: We can see virus spread as a special case of the voter model with two different opinions (healthy and infected), but only one of the opinions (infected) can be transmitted, while any individuals with infected opinion switch to healthy opinion after a period of time. We examined the virus spread with vaccination and the voter model on random graphs of different structures, where in some cases the nodes of the graph corresponding to the individuals of the network are divided into groups representing significantly distinct properties for the process. To study the result on the discretized model, we generated 5 random graphs with N = 10000 nodes for each graph structure, and run the process 20 times on a random graph with independent In case of most of the structures we can derive rather different outcomes on the same graph with different initial values concerning the peak of the virus. cache = ./cache/cord-196353-p05a8zjy.txt txt = ./txt/cord-196353-p05a8zjy.txt === reduce.pl bib === id = cord-024437-r5wnz7rq author = Wang, Yubin title = SLGAT: Soft Labels Guided Graph Attention Networks date = 2020-04-17 pages = extension = .txt mime = text/plain words = 3501 sentences = 243 flesch = 53 summary = In this paper, we propose a soft labels guided graph attention network (SLGAT) to improve the performance of node representation learning by leveraging generated pseudo labels. Graph attention networks (GAT) [23] , which is one of the most representative GCNs, learns the weights for neighborhood aggregation via self-attention mechanism [22] and achieves promising performance on semi-supervised node classification problem. In this paper, we propose soft labels guided attention networks (SLGAT) for semi-supervised node representation learning. First, SLGAT aggregates the features of neighbors using convolutional networks and predicts soft labels for each node based on the learned embeddings. The weights for neighborhood aggregation learned by a feedforward neural network based on both label information of central nodes and features of neighboring nodes, which can lead to learning more discriminative node representations for classification. Unlike the prior graph attention networks [23, 28] , we use label information as guidance to learn the weights of neighboring nodes for feature aggregation. cache = ./cache/cord-024437-r5wnz7rq.txt txt = ./txt/cord-024437-r5wnz7rq.txt === reduce.pl bib === id = cord-026306-mkmrninv author = Lepskiy, Alexander title = Belief Functions for the Importance Assessment in Multiplex Networks date = 2020-05-15 pages = extension = .txt mime = text/plain words = 4133 sentences = 274 flesch = 61 summary = The measures use the combination of "high", "low" and "(high, low)" probabilities of the influence based on weighted and unweighted degrees of nodes via Dempster's rule. Secondly, one can aggregate connections between pairs of nodes to obtain monoplex network and then apply centrality measures to a new weighted graph. In this Section we describe a graph model with one layer of interaction as well as the construction of centrality measure based on a mass function for a network. Additionally, if we consider a 1-neighborhood of nodes in multiplex acyclic graphs with two layers then the following propositions concerning the aggregated interaction centrality value can be proved. We apply Dempster-Shafer theory in order to reveal key elements in undirected weighted graphs as well as to aggregate interactions between nodes into the total ranking. If nodes cooperate with each other on different levels of interactions then we apply a combination rule to mass functions obtained for different layers of a multiplex structure. cache = ./cache/cord-026306-mkmrninv.txt txt = ./txt/cord-026306-mkmrninv.txt === reduce.pl bib === id = cord-248848-p7jv79ae author = Lee, Kookjin title = Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems date = 2020-10-28 pages = extension = .txt mime = text/plain words = 6965 sentences = 424 flesch = 53 summary = We emphasize that our approach is closely related to [63] , where neural networks are trained to approximate the action of the first-order time-integration scheme applied to latent dynamics and, at each time step, the neural networks take a set of problem-specific parameters as well as reduced state as an input. PNODEs still can learn multiple trajectories, which are characterized by the ODE parameters, even if the same initial states are given for different ODE parameters, which is not achievable with NODEs. Furthermore, the proposed framework is significantly simpler than the common neural network settings for NODEs when they are used to learn latent dynamics: the sequence-to-sequence architectures as in [9, 61, 74, 45, 46] , which require that a (part of) sequence is fed into the encoder network to produce a context vector, which is then fed into the NODE decoder network as an initial condition. cache = ./cache/cord-248848-p7jv79ae.txt txt = ./txt/cord-248848-p7jv79ae.txt === reduce.pl bib === id = cord-007415-d57zqixs author = da Fontoura Costa, Luciano title = Correlations between structure and random walk dynamics in directed complex networks date = 2007-07-30 pages = extension = .txt mime = text/plain words = 2202 sentences = 124 flesch = 58 summary = They establish the necessary conditions for networks to be topologically and dynamically fully correlated (e.g., word adjacency and airport networks), and show that in this case Zipf's law is a consequence of the match between structure and dynamics. They establish the necessary conditions for networks to be topologically and dynamically fully correlated ͑e.g., word adjacency and airport networks͒, and show that in this case Zipf's law is a consequence of the match between structure and dynamics. 2766683͔ We address the relationship between structure and dynamics in complex networks by taking the steady-state distribution of the frequency of visits to nodes-a dynamical feature-obtained by performing random walks 1 along the networks. In addition to providing a modeling approach intrinsically compatible with dynamics involving successive visits to nodes by a single or multiple agents, such as is the case with world wide web ͑WWW͒ navigation, text writing, and transportation systems, random walks are directly related to diffusion. cache = ./cache/cord-007415-d57zqixs.txt txt = ./txt/cord-007415-d57zqixs.txt === reduce.pl bib === id = cord-355393-ot7hztyk author = Yuan, Peiyan title = Community-based immunization in opportunistic social networks date = 2015-02-15 pages = extension = .txt mime = text/plain words = 5983 sentences = 467 flesch = 66 summary = More interestingly, we find that high local importance but non-central nodes play a big role in epidemic spreading process, removing them improves the immunization efficiency by 25% to 150% at different scenarios. To this end, we investigate the evolution of community structure in opportunistic social networks, and analyze the effect of community-based immunization strategy on epidemic spreading. We observe that the most efficient immunization strategy on epidemic spreading is to remove nodes with high local importance in communities. Although many random mobility models, such as Random Walk and Random Way Point, have been widely used in opportunistic social networks for evaluating routing performance or even the epidemic dynamics [30, 31] , they cannot reflect the main features of human mobility, including the truncated power-law flights and pause-times, the heterogeneously bounded mobility areas of different nodes, etc. cache = ./cache/cord-355393-ot7hztyk.txt txt = ./txt/cord-355393-ot7hztyk.txt === reduce.pl bib === id = cord-102394-vk4ag44m author = Zhang, Hai-Feng title = Impact of asymptomatic infection on coupled disease-behavior dynamics in complex networks date = 2016-08-14 pages = extension = .txt mime = text/plain words = 3220 sentences = 204 flesch = 59 summary = The analytic results emph{quantitatively} describe the influence of different factors, such as asymptomatic infection, the awareness rate, the network structure, and so forth, on the epidemic thresholds. Since the manner of the diffusion of awareness is quite different from the mechanism of epidemic spreading, the coupled disease-behavior interaction models in multiplex networks were also investigated [18] [19] [20] . Therefore, the SAUIR model is an irreversible process but the SAUIS model is a reversible process, which yields different theoretical methods to deal with their epidemic thresholds and the results. For our SAUIR model, on one hand, the epidemic threshold is very difficult or impossible to obtain by solving the meanfield based differential equations; on the other hand, in Ref. Near the epidemic threshold, the number of infected nodes is very few, indicating that the value of θ is a very small too. Then the epidemic thresholds for the improved SIS model and SIR model were obtained by using different theoretical methods. cache = ./cache/cord-102394-vk4ag44m.txt txt = ./txt/cord-102394-vk4ag44m.txt === reduce.pl bib === id = cord-322746-28igib4l author = Gosche, John R. title = Acute, subacute, and chronic cervical lymphadenitis in children date = 2007-06-06 pages = extension = .txt mime = text/plain words = 4721 sentences = 276 flesch = 33 summary = Involvement of superficial or deep cervical lymph nodes is also frequently indicative of the site of entry since superficial nodal enlargement usually reflects invasion through an epithelial surface (eg, buccal mucosa, skin, scalp), whereas deep nodal enlargement results from an infectious process involving more central structures (eg, middle ear, posterior pharynx). Finally, serologic testing for human immunodeficiency virus (HIV) should be considered in any patient with at-risk behaviors, generalized lymphadenitis, and unusual or recurrent infections caused by opportunistic organisms. Plain radiographs are seldom necessary in patients with acute cervical lymphadenitis, but may occasionally document the primary site of an infection (eg, pneumonia, sinusitis, or dental caries). 8 Acute viral associated cervical lymphadenitis typically develops following an upper respiratory tract infection. 11 Bilateral, acute cervical lymphadenitis associated with a viral upper respiratory tract infection rarely requires additional diagnostic testing or specific therapy. cache = ./cache/cord-322746-28igib4l.txt txt = ./txt/cord-322746-28igib4l.txt === reduce.pl bib === id = cord-306727-2c1m04je author = Pandey, Prateek title = Promoting Trustless Computation Through Blockchain Technology date = 2020-05-20 pages = extension = .txt mime = text/plain words = 2629 sentences = 128 flesch = 55 summary = The paper explains the blockchain technology and a variety of its implementation through five different use cases in the field of drug supply chain, health insurance, land record management, courier services, and immigration records. Therefore, virtually all the use cases, from money transaction to mushroom supply chain, and from agricultural commodity market place to electronic health records (EHR) are a potential client for blockchain technology. In this article, the authors propose the use of Blockchain in five different use cases, namely drug supply chain, health insurance, land record management, courier services, and immigration records. Therefore, Drug supply, health insurance, and land records blockchains are implemented over the Ethereum network, whereas immigration and courier blockchains are implemented on hyper ledger fabric. While implementing the private Blockchain for immigration records and courier tracking, we observe the performance of the built network in terms of throughput, which is the number of transactions written in the ledger per second. cache = ./cache/cord-306727-2c1m04je.txt txt = ./txt/cord-306727-2c1m04je.txt === reduce.pl bib === id = cord-102588-vpu5w9wh author = Le, Trang T. title = treeheatr: an R package for interpretable decision tree visualizations date = 2020-07-10 pages = extension = .txt mime = text/plain words = 2389 sentences = 124 flesch = 51 summary = Summary treeheatr is an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. Implemented in an easily installed package with a detailed vignette, treeheatr can be a useful teaching tool to enhance students' understanding of a simple decision tree model before diving into more complex tree-based machine learning methods. We have developed the treeheatr package to incorporate the functionality of ggparty but also utilize the leaf node space to display the data as a heatmap, a popular visualization that uncovers groups of samples and features in a dataset (Wilkinson and Friendly, 2009, Galili,T. The following lines of code compute and visualize the conditional decision tree along with the heatmap containing features that are important for constructing this model ( Fig. 1) : When the first argument x is a data.frame object representing the dataset instead of the decision tree, treeheatr automatically computes a conditional tree with default parameters for visualization. cache = ./cache/cord-102588-vpu5w9wh.txt txt = ./txt/cord-102588-vpu5w9wh.txt === reduce.pl bib === id = cord-028660-hi35xvni author = Chen, Jie title = Three-Way Decisions Community Detection Model Based on Weighted Graph Representation date = 2020-06-10 pages = extension = .txt mime = text/plain words = 3633 sentences = 246 flesch = 56 summary = Community detection algorithm based on three-way decisions (TWD) forms a multi-layered community structure by hierarchical clustering and then selects a suitable layer as the community detection result. Therefore, in this paper, we propose a method for three-way decisions community detection based on weighted graph representation (WGR-TWD). In this paper, we propose a three-way decisions community detection model based on weighted graph representation (WGR-TWD). The graph representation can well transform the global structure of the network into vector representation and make the two nodes in the boundary region that appear in the same community more similar by using the weight. (1) We use weighted graph representation to obtain the global structure information of the network to guide the processing of the boundary region, which gets a better three-way decisions community detection method. In this paper, we propose a method for three-way decisions community detection based on weighted graph representation. cache = ./cache/cord-028660-hi35xvni.txt txt = ./txt/cord-028660-hi35xvni.txt === reduce.pl bib === id = cord-319291-6l688krc author = Hung, Chun-Min title = Alignment using genetic programming with causal trees for identification of protein functions date = 2006-09-01 pages = extension = .txt mime = text/plain words = 8941 sentences = 632 flesch = 52 summary = Particularly, the model has three characteristics: (i) it is a hybrid evolutionary model with multiple fitness functions that uses genetic programming to predict protein functions on a distantly related protein family, (ii) it incorporates modified robust point matching to accurately compare all feature points using the moment invariant and thin-plate spline theorems, and (iii) the hierarchical homologies holding up a novel protein sequence in the form of a causal tree can effectively demonstrate the relationship between proteins. The hybrid model, namely Alignment using Genetic programming with Causal Tree (AGCT), is a heuristic evolutionary method that contains three basic components: (i) genetic programming with innerexchanged individual strategy, (ii) causal trees [4, 28, 31] with probabilistic reasoning, and (iii) construction of hierarchical homologies with local block-to-block alignment using the methods of moment invariant and robust points matching (RPM) [24] . cache = ./cache/cord-319291-6l688krc.txt txt = ./txt/cord-319291-6l688krc.txt === reduce.pl bib === id = cord-027178-tqj8jgem author = Tian, Changbo title = Modeling of Anti-tracking Network Based on Convex-Polytope Topology date = 2020-06-15 pages = extension = .txt mime = text/plain words = 4301 sentences = 274 flesch = 62 summary = From the aspects of network stability, network resilience and destroy-resistance, we propose the convex-polytope topology (CPT) applied in the anti-tracking network. From the experimental results, CPT has better robustness, resilience and destroy-resistance confronted with dynamically changed topology, and performs better in the efficiency of network self-optimization. Especially, for the P2P-based anti-tracking network which takes the advantage of the wide distribution of nodes for tracking-resistant communication, it is important to keep a stable, secure and destroy-resistant topology structure. But the convex-polytope structure still has some extreme cases shown in Fig. 2 which may pose a potential threat on the structure stability and communication efficiency of anti-tracking network because of the key nodes. According to the properties of CPT, we can achieve the self-optimization of anti-tracking network to balance the distribution of nodes' connectivity. For each network constructed by CPT, NN and DHT, we randomly remove p percent of nodes and count the time requirement of network self-optimization as the metric. cache = ./cache/cord-027178-tqj8jgem.txt txt = ./txt/cord-027178-tqj8jgem.txt === reduce.pl bib === id = cord-276178-0hrs1w7r author = Bangotra, Deep Kumar title = An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare date = 2020-07-13 pages = extension = .txt mime = text/plain words = 9221 sentences = 567 flesch = 59 summary = In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The problem of energy efficiency during the routing of data packets from source to target in case of IoToriented WSN is significantly addressed by another network-based routing protocol known as GreeDi [6] . The problem of energy efficiency during the routing of data packets from source to target in case of IoT-oriented WSN is significantly addressed by another network-based routing protocol known as GreeDi [6] . The proposed method of relay node selection using IOP could be understood by considering an example of WSN shown in Figure 2 and using the naïve Baye's algorithm on the generic data available in Table 4 , to find the optimal path in terms of energy efficiency and reliability from source node S to destination node D. cache = ./cache/cord-276178-0hrs1w7r.txt txt = ./txt/cord-276178-0hrs1w7r.txt === reduce.pl bib === id = cord-285350-64mzmiv3 author = Bhagatkar, Nikita title = An integrated P2P framework for E-learning date = 2020-06-29 pages = extension = .txt mime = text/plain words = 11383 sentences = 728 flesch = 68 summary = The focus of this paper is to design and develop a Peer-to-Peer Presentation System (P2P-PS) that supports E-learning through live media streaming coupled with a P2P shared whiteboard. In current situation of pandemic outbreak of COVID-19, our P2P-PS may, in fact, be an ideal complementary system for offloading pressure on Zoom on WebEx. To organize the stored contents, we used an efficient implementation of Distributed Hash Table ( DHT) based on de Bruijn graphs. -It incorporates an efficient DHT-based sharing and searching of media and document files, which is implemented using de Bruijn graph-based overlays. We use a de Bruijn graph-based overlay for implementing distributed hash table (DHT) organization for stored Fig. 2 Overall system architecture of P2P-PS materials. The bootstrap server randomly selects a set of required number of active peers from the entire active peer list and returns the same to the requesting node. cache = ./cache/cord-285350-64mzmiv3.txt txt = ./txt/cord-285350-64mzmiv3.txt === reduce.pl bib === id = cord-125089-1lfmqzmc author = Chandrasekhar, Arun G. title = Interacting Regional Policies in Containing a Disease date = 2020-08-24 pages = extension = .txt mime = text/plain words = 8625 sentences = 569 flesch = 64 summary = We show that a regional quarantine policy's effectiveness depends upon whether (i) the network of interactions satisfies a balanced-growth condition, (ii) infections have a short delay in detection, and (iii) the government has control over and knowledge of the necessary parts of the network (no leakage of behaviors). As these conditions generally fail to be satisfied, especially when interactions cross borders, we show that substantial improvements are possible if governments are proactive: triggering quarantines in reaction to neighbors' infection rates, in some cases even before infections are detected internally. In the SI (Theorem 1) we prove that, with no delays in detection and no leakage, a (k, x)regional policy halts infection among all nodes beyond distance k +1 from i 0 with probability approaching 1 (as the population grows) if and only if the network satisfies growth-balance. Given that real-world networks have short average distances between nodes [32], non-trivial delays in detection allow the disease to escape a regional quarantine. cache = ./cache/cord-125089-1lfmqzmc.txt txt = ./txt/cord-125089-1lfmqzmc.txt === reduce.pl bib === id = cord-349724-yq4dphmb author = Santos, Hugo title = A Multi-Tier Fog Content Orchestrator Mechanism with Quality of Experience Support date = 2020-05-06 pages = extension = .txt mime = text/plain words = 7209 sentences = 369 flesch = 57 summary = For the analysis phase, the Fog4Video collects information about available bandwidth, delay, stall duration, number of stall events, and monetary cost from the network, user client, and fog node. Based on our analysis of the state-of-the-art, we conclude that VoD services deployed in a multi-tier fog architecture improve the QoE by efficiently orchestrating fog nodes resources, while reducing delay and amount of data uploading/downloading to the cloud in a cost efficient fashion. Based on such architecture, Fog4Video classifies the connectivity and resources of each available fog node into a multi-criteria rank, where it considers the AHP method to assign different degrees of importance for each criterion to provide better QoE for each user. Based on these values, Fog4Video implemented in the Orchestrator considers network, fog node, and user information to perform real-time content orchestration, i.e., it chooses an appropriate Streaming Unit from a given tier for the client to download the video. cache = ./cache/cord-349724-yq4dphmb.txt txt = ./txt/cord-349724-yq4dphmb.txt === reduce.pl bib === id = cord-022561-rv5j1201 author = Boes, Katie M. title = Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System date = 2017-02-17 pages = extension = .txt mime = text/plain words = 52276 sentences = 2784 flesch = 39 summary = Mechanisms contributing to glucocorticoid-mediated neutrophilia include the following: • Increased release of mature neutrophils from the bone marrow storage pool • Decreased margination of neutrophils within the vasculature, with a resulting increase in the circulating pool • Decreased migration of neutrophils from the bloodstream into tissues The magnitude of neutrophilia tends to be species dependent, with dogs having the most pronounced response (up to 35,000 cells/µL) and in decreasing order of responsiveness, cats (30,000 cells/µL), horses (20,000 cells/µL), and cattle (15,000 cells/µL) having less marked responses. As a result, animals with Chédiak-Higashi 746.e1 CHAPTER 13 Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System von Willebrand disease (vWD) is the most common canine hereditary bleeding disorder and has also been described in many other domestic species. cache = ./cache/cord-022561-rv5j1201.txt txt = ./txt/cord-022561-rv5j1201.txt ===== Reducing email addresses cord-010727-fiukemh3 cord-010739-28qfmj9x cord-010751-fgk05n3z cord-102588-vpu5w9wh Creating transaction Updating adr table ===== Reducing keywords cord-000196-lkoyrv3s cord-010739-28qfmj9x cord-017590-w5copp1z cord-016196-ub4mgqxb cord-010727-fiukemh3 cord-024504-p2vxnn9z cord-017062-dkw2sugl cord-005090-l676wo9t cord-014845-odnlt6fr cord-027451-ztx9fsbg cord-024499-14jlk5tv cord-034545-onj7zpi1 cord-199630-2lmwnfda cord-155475-is3su3ga cord-102935-cx3elpb8 cord-034824-eelqmzdx cord-119522-2ua8218z cord-010751-fgk05n3z cord-028688-5uzl1jpu cord-322890-w78tftva cord-269711-tw5armh8 cord-284186-zf1w8ksm cord-020885-f667icyt cord-168862-3tj63eve cord-328875-fgeudou6 cord-196353-p05a8zjy cord-024437-r5wnz7rq cord-026306-mkmrninv cord-007415-d57zqixs cord-248848-p7jv79ae cord-355393-ot7hztyk cord-102394-vk4ag44m cord-322746-28igib4l cord-306727-2c1m04je cord-102588-vpu5w9wh cord-028660-hi35xvni cord-319291-6l688krc cord-027178-tqj8jgem cord-276178-0hrs1w7r cord-285350-64mzmiv3 cord-125089-1lfmqzmc cord-022561-rv5j1201 cord-349724-yq4dphmb Creating transaction Updating wrd table ===== Reducing urls cord-010727-fiukemh3 cord-102935-cx3elpb8 cord-034824-eelqmzdx cord-199630-2lmwnfda cord-168862-3tj63eve cord-024437-r5wnz7rq cord-102588-vpu5w9wh cord-285350-64mzmiv3 Creating transaction Updating url table ===== Reducing named entities cord-000196-lkoyrv3s cord-016196-ub4mgqxb cord-024504-p2vxnn9z cord-010739-28qfmj9x cord-010727-fiukemh3 cord-017590-w5copp1z cord-005090-l676wo9t cord-017062-dkw2sugl cord-027451-ztx9fsbg cord-014845-odnlt6fr cord-024499-14jlk5tv cord-034545-onj7zpi1 cord-199630-2lmwnfda cord-155475-is3su3ga cord-102935-cx3elpb8 cord-034824-eelqmzdx cord-010751-fgk05n3z cord-119522-2ua8218z cord-322890-w78tftva cord-028688-5uzl1jpu cord-269711-tw5armh8 cord-284186-zf1w8ksm cord-020885-f667icyt cord-168862-3tj63eve cord-328875-fgeudou6 cord-196353-p05a8zjy cord-026306-mkmrninv cord-007415-d57zqixs cord-248848-p7jv79ae cord-355393-ot7hztyk cord-102394-vk4ag44m cord-322746-28igib4l cord-306727-2c1m04je cord-102588-vpu5w9wh cord-319291-6l688krc cord-028660-hi35xvni cord-027178-tqj8jgem cord-276178-0hrs1w7r cord-285350-64mzmiv3 cord-125089-1lfmqzmc cord-349724-yq4dphmb cord-024437-r5wnz7rq cord-022561-rv5j1201 Creating transaction Updating ent table ===== Reducing parts of speech cord-017590-w5copp1z cord-010739-28qfmj9x cord-016196-ub4mgqxb cord-010727-fiukemh3 cord-000196-lkoyrv3s cord-024504-p2vxnn9z cord-024499-14jlk5tv cord-102935-cx3elpb8 cord-014845-odnlt6fr cord-027451-ztx9fsbg cord-005090-l676wo9t cord-155475-is3su3ga cord-017062-dkw2sugl cord-034545-onj7zpi1 cord-199630-2lmwnfda cord-034824-eelqmzdx cord-010751-fgk05n3z cord-119522-2ua8218z cord-028688-5uzl1jpu cord-322890-w78tftva cord-269711-tw5armh8 cord-284186-zf1w8ksm cord-020885-f667icyt cord-328875-fgeudou6 cord-024437-r5wnz7rq cord-196353-p05a8zjy cord-026306-mkmrninv cord-007415-d57zqixs cord-102394-vk4ag44m cord-306727-2c1m04je cord-102588-vpu5w9wh cord-322746-28igib4l cord-028660-hi35xvni cord-355393-ot7hztyk cord-248848-p7jv79ae cord-168862-3tj63eve cord-027178-tqj8jgem cord-319291-6l688krc cord-349724-yq4dphmb cord-276178-0hrs1w7r cord-125089-1lfmqzmc cord-285350-64mzmiv3 cord-022561-rv5j1201 Creating transaction Updating pos table Building ./etc/reader.txt cord-022561-rv5j1201 cord-276178-0hrs1w7r cord-017062-dkw2sugl cord-022561-rv5j1201 cord-017062-dkw2sugl cord-284186-zf1w8ksm number of items: 43 sum of words: 284,065 average size in words: 6,606 average readability score: 55 nouns: nodes; node; network; networks; data; model; lymph; time; number; disease; graph; cells; information; structure; degree; blood; community; system; results; cell; energy; algorithm; epidemic; lymphoma; infection; probability; dynamics; ferrets; spleen; method; function; models; size; process; case; rate; distribution; lymphocytes; edges; transmission; individuals; graphs; virus; marrow; strategy; value; vaccination; cases; dogs; example verbs: used; based; shown; include; see; proposed; follows; consider; given; caused; increasing; reduce; compared; occurs; infected; provided; learned; represents; found; result; made; spread; identify; described; selecting; performed; becoming; denoted; take; set; affecting; study; known; obtain; defines; chosen; contains; detected; connected; associated; presented; decreases; targeted; receiving; developed; required; generating; send; reported; compute adjectives: different; random; large; small; important; many; new; high; complex; infectious; splenic; social; initial; red; lymphoid; infected; low; multiple; common; lymphatic; average; local; susceptible; similar; first; cervical; specific; acute; normal; single; human; higher; several; effective; available; possible; clinical; various; chronic; real; total; non; secondary; efficient; central; multi; primary; opportunistic; potential; better adverbs: also; however; often; well; therefore; usually; respectively; first; randomly; even; especially; finally; commonly; typically; still; directly; generally; moreover; frequently; less; hence; highly; approximately; significantly; particularly; later; rather; relatively; previously; mainly; always; next; furthermore; easily; otherwise; widely; instead; grossly; now; namely; recently; much; additionally; just; fully; specifically; initially; almost; likely; together pronouns: we; it; i; its; their; they; our; them; one; itself; us; he; his; u; themselves; she; your; you; my; her; ourselves; me; 's; theirs; s; mine; getuserfromsubmittedjob_in_lsf; cord-014845-odnlt6fr proper nouns: Fig; •; T; RFID; Eq; S; Table; i; C; CPT; Node; SIR; SARS; N; M; K; E; Fog4Video; A; Conductance; IoT; EnRenew; L; D; Figure; VoD; B; WSN; Network; F; Networks; DC; −; PageRank; ADTRA; sha; DeepWalk; System; COVID-19; Sect; SIS; ID; CoV-2; α; DOI; |; II; DHT; Bruijn; W keywords: node; network; model; protein; lymphoma; lymph; graph; ferret; drug; community; cervical; wsn; unit; tree; time; temperature; target; tag; table; system; strategy; state; spleen; slgat; sir; sars; rfid; red; policy; pm2.5; peer; patient; parameter; p2p; mri; measure; marrow; lymphoid; lymphocyte; lymphatic; lymphadenopathy; lymphadenitis; liposome; kuramoto; information; individual; host; gene; function; fog4video one topic; one dimension: nodes file(s): https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851561/ titles(s): Dynamics and Control of Diseases in Networks with Community Structure three topics; one dimension: nodes; may; nodes file(s): https://arxiv.org/pdf/1911.03805v1.pdf, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158316/, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7607371/ titles(s): Nonlinearity + Networks: A 2020 Vision | Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System | Internet of things for healthcare monitoring applications based on RFID clustering scheme five topics; three dimensions: nodes node network; may cells blood; nodes node network; nodes node lymph; ferrets lymph nodes file(s): https://www.sciencedirect.com/science/article/pii/S0362546X05009028, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158316/, https://doi.org/10.3390/s20143887, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121534/, https://doi.org/10.1111/vru.12068 titles(s): Alignment using genetic programming with causal trees for identification of protein functions | Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System | An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare | Delivery Systems for Lymphatic Targeting | IMAGING FINDINGS IN 14 DOMESTIC FERRETS (MUSTELA PUTORIUS FURO) WITH LYMPHOMA Type: cord title: keyword-node-cord date: 2021-05-25 time: 15:42 username: emorgan patron: Eric Morgan email: emorgan@nd.edu input: keywords:node ==== make-pages.sh htm files ==== make-pages.sh complex files ==== make-pages.sh named enities ==== making bibliographics id: cord-034545-onj7zpi1 author: Abuelkhail, Abdulrahman title: Internet of things for healthcare monitoring applications based on RFID clustering scheme date: 2020-11-03 words: 7772 sentences: 433 pages: flesch: 62 cache: ./cache/cord-034545-onj7zpi1.txt txt: ./txt/cord-034545-onj7zpi1.txt summary: The mathematical model optimizes the following objective functions: (1) minimizing the total distance between CHs and CMs to improve positioning accuracy; and (2) minimizing the number of clusters which reduces the signal transmission traffic Feature 6 (F-6): two level security is obtained by when a node writes data to its RFID tag, the data is signed with a signature, which is a hash value, the obtained hash is encrypted with a AES 128 bits shared key abstract: COVID-19 surprised the whole world by its quick and sudden spread. Coronavirus pushes all community sectors: government, industry, academia, and nonprofit organizations to take forward steps to stop and control this pandemic. It is evident that IT-based solutions are urgent. This study is a small step in this direction, where health information is monitored and collected continuously. In this work, we build a network of smart nodes where each node comprises a Radio-Frequency Identification (RFID) tag, reduced function RFID reader (RFRR), and sensors. The smart nodes are grouped in clusters, which are constructed periodically. The RFRR reader of the clusterhead collects data from its members, and once it is close to the primary reader, it conveys its data and so on. This approach reduces the primary RFID reader’s burden by receiving data from the clusterheads only instead of reading every tag when they pass by its vicinity. Besides, this mechanism reduces the channel access congestion; thus, it reduces the interference significantly. Furthermore, to protect the exchanged data from potential attacks, two levels of security algorithms, including an AES 128 bit with hashing, have been implemented. The proposed scheme has been validated via mathematical modeling using Integer programming, simulation, and prototype experimentation. The proposed technique shows low data delivery losses and a significant drop in transmission delay compared to contemporary approaches. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7607371/ doi: 10.1007/s11276-020-02482-1 id: cord-196353-p05a8zjy author: Backhausz, ''Agnes title: Virus spread and voter model on random graphs with multiple type nodes date: 2020-02-17 words: 7550 sentences: 429 pages: flesch: 62 cache: ./cache/cord-196353-p05a8zjy.txt txt: ./txt/cord-196353-p05a8zjy.txt summary: The two processes can be connected by the following idea: We can see virus spread as a special case of the voter model with two different opinions (healthy and infected), but only one of the opinions (infected) can be transmitted, while any individuals with infected opinion switch to healthy opinion after a period of time. We examined the virus spread with vaccination and the voter model on random graphs of different structures, where in some cases the nodes of the graph corresponding to the individuals of the network are divided into groups representing significantly distinct properties for the process. To study the result on the discretized model, we generated 5 random graphs with N = 10000 nodes for each graph structure, and run the process 20 times on a random graph with independent In case of most of the structures we can derive rather different outcomes on the same graph with different initial values concerning the peak of the virus. abstract: When modelling epidemics or spread of information on online social networks, it is crucial to include not just the density of the connections through which infections can be transmitted, but also the variability of susceptibility. Different people have different chance to be infected by a disease (due to age or general health conditions), or, in case of opinions, ones are easier to be convinced by others, or stronger at sharing their opinions. The goal of this work is to examine the effect of multiple types of nodes on various random graphs such as ErdH{o}s--R'enyi random graphs, preferential attachment random graphs and geometric random graphs. We used two models for the dynamics: SEIR model with vaccination and a version of voter model for exchanging opinions. In the first case, among others, various vaccination strategies are compared to each other, while in the second case we studied sevaral initial configurations to find the key positions where the most effective nodes should be placed to disseminate opinions. url: https://arxiv.org/pdf/2002.06926v1.pdf doi: nan id: cord-024499-14jlk5tv author: Balalau, Oana title: SubRank: Subgraph Embeddings via a Subgraph Proximity Measure date: 2020-04-17 words: 3741 sentences: 265 pages: flesch: 63 cache: ./cache/cord-024499-14jlk5tv.txt txt: ./txt/cord-024499-14jlk5tv.txt summary: We show that our subgraph embeddings are comprehensive and achieve competitive performance on three important data mining tasks: community detection, link prediction, and cascade growth prediction. A cascade graph is sampled for a set of random walks, which are given as input to a gated neural network to predict the future size of the cascade. In [3] , the authors propose an inductive framework for computing graph embeddings, based on training an attention network to predict a graph proximity measure, such as graph edit distance. Given a graph G = (V, E) and set of subgraphs of G, S = {S 1 , S 2 , · · · , S k }, we learn their representations as dense vectors, i.e. as embeddings. abstract: Representation learning for graph data has gained a lot of attention in recent years. However, state-of-the-art research is focused mostly on node embeddings, with little effort dedicated to the closely related task of computing subgraph embeddings. Subgraph embeddings have many applications, such as community detection, cascade prediction, and question answering. In this work, we propose a subgraph to subgraph proximity measure as a building block for a subgraph embedding framework. Experiments on real-world datasets show that our approach, SubRank, outperforms state-of-the-art methods on several important data mining tasks. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206259/ doi: 10.1007/978-3-030-47426-3_38 id: cord-276178-0hrs1w7r author: Bangotra, Deep Kumar title: An Intelligent Opportunistic Routing Algorithm for Wireless Sensor Networks and Its Application Towards e-Healthcare date: 2020-07-13 words: 9221 sentences: 567 pages: flesch: 59 cache: ./cache/cord-276178-0hrs1w7r.txt txt: ./txt/cord-276178-0hrs1w7r.txt summary: In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The problem of energy efficiency during the routing of data packets from source to target in case of IoToriented WSN is significantly addressed by another network-based routing protocol known as GreeDi [6] . The problem of energy efficiency during the routing of data packets from source to target in case of IoT-oriented WSN is significantly addressed by another network-based routing protocol known as GreeDi [6] . The proposed method of relay node selection using IOP could be understood by considering an example of WSN shown in Figure 2 and using the naïve Baye''s algorithm on the generic data available in Table 4 , to find the optimal path in terms of energy efficiency and reliability from source node S to destination node D. abstract: The lifetime of a node in wireless sensor networks (WSN) is directly responsible for the longevity of the wireless network. The routing of packets is the most energy-consuming activity for a sensor node. Thus, finding an energy-efficient routing strategy for transmission of packets becomes of utmost importance. The opportunistic routing (OR) protocol is one of the new routing protocol that promises reliability and energy efficiency during transmission of packets in wireless sensor networks (WSN). In this paper, we propose an intelligent opportunistic routing protocol (IOP) using a machine learning technique, to select a relay node from the list of potential forwarder nodes to achieve energy efficiency and reliability in the network. The proposed approach might have applications including e-healthcare services. As the proposed method might achieve reliability in the network because it can connect several healthcare network devices in a better way and good healthcare services might be offered. In addition to this, the proposed method saves energy, therefore, it helps the remote patient to connect with healthcare services for a longer duration with the integration of IoT services. url: https://doi.org/10.3390/s20143887 doi: 10.3390/s20143887 id: cord-285350-64mzmiv3 author: Bhagatkar, Nikita title: An integrated P2P framework for E-learning date: 2020-06-29 words: 11383 sentences: 728 pages: flesch: 68 cache: ./cache/cord-285350-64mzmiv3.txt txt: ./txt/cord-285350-64mzmiv3.txt summary: The focus of this paper is to design and develop a Peer-to-Peer Presentation System (P2P-PS) that supports E-learning through live media streaming coupled with a P2P shared whiteboard. In current situation of pandemic outbreak of COVID-19, our P2P-PS may, in fact, be an ideal complementary system for offloading pressure on Zoom on WebEx. To organize the stored contents, we used an efficient implementation of Distributed Hash Table ( DHT) based on de Bruijn graphs. -It incorporates an efficient DHT-based sharing and searching of media and document files, which is implemented using de Bruijn graph-based overlays. We use a de Bruijn graph-based overlay for implementing distributed hash table (DHT) organization for stored Fig. 2 Overall system architecture of P2P-PS materials. The bootstrap server randomly selects a set of required number of active peers from the entire active peer list and returns the same to the requesting node. abstract: The focus of this paper is to design and develop a Peer-to-Peer Presentation System (P2P-PS) that supports E-learning through live media streaming coupled with a P2P shared whiteboard. The participants use the “ask doubt” feature to raise and resolve doubts during a session of ongoing presentation. The proposed P2P-PS system preserves causality between ask doubt and its resolution while disseminating them to all the participants. A buffered approach is employed to enhance the performance of P2P shared whiteboard, which may be used either in tandem with live media streaming or in standalone mode. The proposed system further extends P2P interactions on stored contents (files) built on top of a P2P file sharing and searching module with additional features. The added features allow the creation of mash-up presentations with annotations, posts, comments on audio, video, and PDF files as well as a discussion forum. We have implemented the P2P file sharing and searching system on the de Bruijn graph-based overlay for low latency. Extensive experiments were carried out on Emulab to validate the P2P-PS system using 200 physical nodes. url: https://doi.org/10.1007/s12083-020-00919-0 doi: 10.1007/s12083-020-00919-0 id: cord-022561-rv5j1201 author: Boes, Katie M. title: Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System date: 2017-02-17 words: 52276 sentences: 2784 pages: flesch: 39 cache: ./cache/cord-022561-rv5j1201.txt txt: ./txt/cord-022561-rv5j1201.txt summary: Mechanisms contributing to glucocorticoid-mediated neutrophilia include the following: • Increased release of mature neutrophils from the bone marrow storage pool • Decreased margination of neutrophils within the vasculature, with a resulting increase in the circulating pool • Decreased migration of neutrophils from the bloodstream into tissues The magnitude of neutrophilia tends to be species dependent, with dogs having the most pronounced response (up to 35,000 cells/µL) and in decreasing order of responsiveness, cats (30,000 cells/µL), horses (20,000 cells/µL), and cattle (15,000 cells/µL) having less marked responses. As a result, animals with Chédiak-Higashi 746.e1 CHAPTER 13 Bone Marrow, Blood Cells, and the Lymphoid/Lymphatic System von Willebrand disease (vWD) is the most common canine hereditary bleeding disorder and has also been described in many other domestic species. abstract: nan url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7158316/ doi: 10.1016/b978-0-323-35775-3.00013-8 id: cord-125089-1lfmqzmc author: Chandrasekhar, Arun G. title: Interacting Regional Policies in Containing a Disease date: 2020-08-24 words: 8625 sentences: 569 pages: flesch: 64 cache: ./cache/cord-125089-1lfmqzmc.txt txt: ./txt/cord-125089-1lfmqzmc.txt summary: We show that a regional quarantine policy''s effectiveness depends upon whether (i) the network of interactions satisfies a balanced-growth condition, (ii) infections have a short delay in detection, and (iii) the government has control over and knowledge of the necessary parts of the network (no leakage of behaviors). As these conditions generally fail to be satisfied, especially when interactions cross borders, we show that substantial improvements are possible if governments are proactive: triggering quarantines in reaction to neighbors'' infection rates, in some cases even before infections are detected internally. In the SI (Theorem 1) we prove that, with no delays in detection and no leakage, a (k, x)regional policy halts infection among all nodes beyond distance k +1 from i 0 with probability approaching 1 (as the population grows) if and only if the network satisfies growth-balance. Given that real-world networks have short average distances between nodes [32], non-trivial delays in detection allow the disease to escape a regional quarantine. abstract: Regional quarantine policies, in which a portion of a population surrounding infections are locked down, are an important tool to contain disease. However, jurisdictional governments -- such as cities, counties, states, and countries -- act with minimal coordination across borders. We show that a regional quarantine policy's effectiveness depends upon whether (i) the network of interactions satisfies a balanced-growth condition, (ii) infections have a short delay in detection, and (iii) the government has control over and knowledge of the necessary parts of the network (no leakage of behaviors). As these conditions generally fail to be satisfied, especially when interactions cross borders, we show that substantial improvements are possible if governments are proactive: triggering quarantines in reaction to neighbors' infection rates, in some cases even before infections are detected internally. We also show that even a few lax governments -- those that wait for nontrivial internal infection rates before quarantining -- impose substantial costs on the whole system. Our results illustrate the importance of understanding contagion across policy borders and offer a starting point in designing proactive policies for decentralized jurisdictions. url: https://arxiv.org/pdf/2008.10745v3.pdf doi: nan id: cord-028660-hi35xvni author: Chen, Jie title: Three-Way Decisions Community Detection Model Based on Weighted Graph Representation date: 2020-06-10 words: 3633 sentences: 246 pages: flesch: 56 cache: ./cache/cord-028660-hi35xvni.txt txt: ./txt/cord-028660-hi35xvni.txt summary: Community detection algorithm based on three-way decisions (TWD) forms a multi-layered community structure by hierarchical clustering and then selects a suitable layer as the community detection result. Therefore, in this paper, we propose a method for three-way decisions community detection based on weighted graph representation (WGR-TWD). In this paper, we propose a three-way decisions community detection model based on weighted graph representation (WGR-TWD). The graph representation can well transform the global structure of the network into vector representation and make the two nodes in the boundary region that appear in the same community more similar by using the weight. (1) We use weighted graph representation to obtain the global structure information of the network to guide the processing of the boundary region, which gets a better three-way decisions community detection method. In this paper, we propose a method for three-way decisions community detection based on weighted graph representation. abstract: Community detection is of great significance to the study of complex networks. Community detection algorithm based on three-way decisions (TWD) forms a multi-layered community structure by hierarchical clustering and then selects a suitable layer as the community detection result. However, this layer usually contains overlapping communities. Based on the idea of TWD, we define the overlapping part in the communities as boundary region (BND), and the non-overlapping part as positive region (POS) or negative region (NEG). How to correctly divide the nodes in the BND into the POS or NEG is a challenge for three-way decisions community detection. The general methods to deal with boundary region are modularity increment and similarity calculation. But these methods only take advantage of the local features of the network, without considering the information of the divided communities and the similarity of the global structure. Therefore, in this paper, we propose a method for three-way decisions community detection based on weighted graph representation (WGR-TWD). The weighted graph representation (WGR) can well transform the global structure into vector representation and make the two nodes in the boundary region more similar by using frequency of appearing in the same community as the weight. Firstly, the multi-layered community structure is constructed by hierarchical clustering. The target layer is selected according to the extended modularity value of each layer. Secondly, all nodes are converted into vectors by WGR. Finally, the nodes in the BND are divided into the POS or NEG based on cosine similarity. Experiments on real-world networks demonstrate that WGR-TWD is effective for community detection in networks compared with the state-of-the-art algorithms. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338166/ doi: 10.1007/978-3-030-52705-1_11 id: cord-027451-ztx9fsbg author: De Chiara, Davide title: Data Mining for Big Dataset-Related Thermal Analysis of High Performance Computing (HPC) Data Center date: 2020-05-25 words: 5758 sentences: 326 pages: flesch: 51 cache: ./cache/cord-027451-ztx9fsbg.txt txt: ./txt/cord-027451-ztx9fsbg.txt summary: This work presents an algorithm that clusters hotspots with the goal of reducing a data centre''s large thermal-gradient due to uneven distribution of server dissipated waste heat followed by increasing cooling effectiveness. Thermal-aware schedulers adopt different thermal-aware approaches (e.g. system-level for work placements [16] ; execute ''hot'' jobs on ''cold'' compute nodes; predictive model for job schedule selection [17] ; ranked node queue based on thermal characteristics of rack layouts and optimisation (e.g. optimal setpoints for workload distribution and supply temperature of the cooling system). Analysis conducted are as follows: hotspots localisation; users categorisations based on submitted jobs to CRESCO6 cluster; compute nodes categorisation based on thermal behaviour of internal and surrounding air temperatures due to workload related waste heat dissipation. Data collected are related to: relevant parameters for each node (e.g. inlet air temperature, internal temperature of each node, energy consumption of CPU, RAM, memory, etc…); environmental parameters (e.g. air temperatures and humidity in both the hot and cold aisles); cooling system related parameters (e.g. fan speed); and finally, individual users who submit their jobs to cluster node. abstract: Greening of Data Centers could be achieved through energy savings in two significant areas, namely: compute systems and cooling systems. A reliable cooling system is necessary to produce a persistent flow of cold air to cool the servers due to increasing computational load demand. Servers’ dissipated heat effects a strain on the cooling systems. Consequently, it is necessary to identify hotspots that frequently occur in the server zones. This is facilitated through the application of data mining techniques to an available big dataset for thermal characteristics of High-Performance Computing ENEA Data Center, namely Cresco 6. This work presents an algorithm that clusters hotspots with the goal of reducing a data centre’s large thermal-gradient due to uneven distribution of server dissipated waste heat followed by increasing cooling effectiveness. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304773/ doi: 10.1007/978-3-030-50436-6_27 id: cord-017590-w5copp1z author: Fresnadillo, María J. title: A SIS Epidemiological Model Based on Cellular Automata on Graphs date: 2009 words: 2757 sentences: 169 pages: flesch: 61 cache: ./cache/cord-017590-w5copp1z.txt txt: ./txt/cord-017590-w5copp1z.txt summary: The main goal of this work is to introduce a new SIS epidemic model based on a particular type of finite state machines called cellular automata on graphs. The state of each cell stands for the fraction of the susceptible and infected individuals of the cell at a particular time step and the evolution of these classes is given in terms of a local transition function. The model introduced in this paper deals with SIS epidemic diseases (for example the group of those responsible for the common cold), that is, the population is divided into susceptible individuals (S) and infected individuals (I). The main goal of this work is to introduce a new SIS model to simulate the spread of a general epidemic based on cellular automata on graph. Nevertheless, in this paper we will consider a more efficient topology to model an epidemic disease, which is given by an undirected graph where its nodes stand for the cells of the cellular automata. abstract: The main goal of this work is to introduce a new SIS epidemic model based on a particular type of finite state machines called cellular automata on graphs. The state of each cell stands for the fraction of the susceptible and infected individuals of the cell at a particular time step and the evolution of these classes is given in terms of a local transition function. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7122184/ doi: 10.1007/978-3-642-02481-8_160 id: cord-005090-l676wo9t author: Gao, Chao title: Network immunization and virus propagation in email networks: experimental evaluation and analysis date: 2010-07-14 words: 8030 sentences: 495 pages: flesch: 58 cache: ./cache/cord-005090-l676wo9t.txt txt: ./txt/cord-005090-l676wo9t.txt summary: For example, computer scientists focus on algorithms and the computational complexities of strategies, i.e. how to quickly search a short path from one "seed" node to a targeted node just based on local information, and then effectively and efficiently restrain virus propagation [42] . Section 4 describes the experiments which are performed to compare different immunization strategies with the measurements of the immunization efficiency, the cost and the robustness in both synthetic networks (including a synthetic community-based network) and two real email networks (the Enron and a university email network), and analyze the effects of network structures and human dynamics on virus propagation. It is readily to observe the microscopic process of worm propagating through this model, and uncover the effects of different factors (e.g. the power-law exponent, human dynamics and the average path length of the network) on virus propagation and immunization strategies. abstract: Network immunization strategies have emerged as possible solutions to the challenges of virus propagation. In this paper, an existing interactive model is introduced and then improved in order to better characterize the way a virus spreads in email networks with different topologies. The model is used to demonstrate the effects of a number of key factors, notably nodes’ degree and betweenness. Experiments are then performed to examine how the structure of a network and human dynamics affects virus propagation. The experimental results have revealed that a virus spreads in two distinct phases and shown that the most efficient immunization strategy is the node-betweenness strategy. Moreover, those results have also explained why old virus can survive in networks nowadays from the aspects of human dynamics. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7088328/ doi: 10.1007/s10115-010-0321-0 id: cord-322746-28igib4l author: Gosche, John R. title: Acute, subacute, and chronic cervical lymphadenitis in children date: 2007-06-06 words: 4721 sentences: 276 pages: flesch: 33 cache: ./cache/cord-322746-28igib4l.txt txt: ./txt/cord-322746-28igib4l.txt summary: Involvement of superficial or deep cervical lymph nodes is also frequently indicative of the site of entry since superficial nodal enlargement usually reflects invasion through an epithelial surface (eg, buccal mucosa, skin, scalp), whereas deep nodal enlargement results from an infectious process involving more central structures (eg, middle ear, posterior pharynx). Finally, serologic testing for human immunodeficiency virus (HIV) should be considered in any patient with at-risk behaviors, generalized lymphadenitis, and unusual or recurrent infections caused by opportunistic organisms. Plain radiographs are seldom necessary in patients with acute cervical lymphadenitis, but may occasionally document the primary site of an infection (eg, pneumonia, sinusitis, or dental caries). 8 Acute viral associated cervical lymphadenitis typically develops following an upper respiratory tract infection. 11 Bilateral, acute cervical lymphadenitis associated with a viral upper respiratory tract infection rarely requires additional diagnostic testing or specific therapy. abstract: Lymphadenopathy refers to any disease process involving lymph nodes that are abnormal in size and consistency. Lymphadenitis specifically refers to lymphadenopathies that are caused by inflammatory processes. Cervical lymphadenopathy is a common problem in the pediatric age group and is largely inflammatory and infectious in etiology. Although most patients are treated successfully by their primary care physician, surgical consultation is frequently required for patients who fail to respond to initial therapy or for those in whom there is an index of suspicion for a neoplastic process. This article addresses current approaches to the diagnosis and management of cervical lymphadenitis in children. url: https://www.ncbi.nlm.nih.gov/pubmed/16616313/ doi: 10.1053/j.sempedsurg.2006.02.007 id: cord-034824-eelqmzdx author: Guo, Chungu title: Influential Nodes Identification in Complex Networks via Information Entropy date: 2020-02-21 words: 5770 sentences: 397 pages: flesch: 55 cache: ./cache/cord-034824-eelqmzdx.txt txt: ./txt/cord-034824-eelqmzdx.txt summary: In this paper, we propose the EnRenew algorithm aimed to identify a set of influential nodes via information entropy. Compared with the best state-of-the-art benchmark methods, the performance of proposed algorithm improved by 21.1%, 7.0%, 30.0%, 5.0%, 2.5%, and 9.0% in final affected scale on CEnew, Email, Hamster, Router, Condmat, and Amazon network, respectively, under the Susceptible-Infected-Recovered (SIR) simulation model. The impressive results on the SIR simulation model shed light on new method of node mining in complex networks for information spreading and epidemic prevention. defined the problem of identifying a set of influential spreaders in complex networks as influence maximization problem [57] , and they used hill-climbing based greedy algorithm that is within 63% of optimal in several models. Besides, to make the algorithm practically more useful, we provide EnRenew''s source code and all the experiments details on https://github.com/YangLiangwei/Influential-nodes-identification-in-complex-networksvia-information-entropy, and researchers can download it freely for their convenience. abstract: Identifying a set of influential nodes is an important topic in complex networks which plays a crucial role in many applications, such as market advertising, rumor controlling, and predicting valuable scientific publications. In regard to this, researchers have developed algorithms from simple degree methods to all kinds of sophisticated approaches. However, a more robust and practical algorithm is required for the task. In this paper, we propose the EnRenew algorithm aimed to identify a set of influential nodes via information entropy. Firstly, the information entropy of each node is calculated as initial spreading ability. Then, select the node with the largest information entropy and renovate its l-length reachable nodes’ spreading ability by an attenuation factor, repeat this process until specific number of influential nodes are selected. Compared with the best state-of-the-art benchmark methods, the performance of proposed algorithm improved by 21.1%, 7.0%, 30.0%, 5.0%, 2.5%, and 9.0% in final affected scale on CEnew, Email, Hamster, Router, Condmat, and Amazon network, respectively, under the Susceptible-Infected-Recovered (SIR) simulation model. The proposed algorithm measures the importance of nodes based on information entropy and selects a group of important nodes through dynamic update strategy. The impressive results on the SIR simulation model shed light on new method of node mining in complex networks for information spreading and epidemic prevention. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516697/ doi: 10.3390/e22020242 id: cord-102935-cx3elpb8 author: Hassani-Pak, Keywan title: KnetMiner: a comprehensive approach for supporting evidence-based gene discovery and complex trait analysis across species date: 2020-04-24 words: 2172 sentences: 119 pages: flesch: 60 cache: ./cache/cord-102935-cx3elpb8.txt txt: ./txt/cord-102935-cx3elpb8.txt summary: Here we report the main design principles behind KnetMiner and provide use cases for mining public datasets to identify unknown links between traits such grain colour and pre-harvest sprouting in Triticum aestivum, as well as, an evidence-based approach to identify candidate genes under an Arabidopsis thaliana petal size QTL. KnetMiner is the first open-source gene discovery platform that can leverage genome-scale knowledge graphs, generate evidence-based biological networks and be deployed for any species with a sequenced genome. Even when 38 the task of gathering information is complete, it is demanding to assemble a coherent view of how 39 each piece of evidence might come together to "tell a story" about the biology that can explain how 40 multiple genes might be implicated in a complex trait or disease. abstract: Generating new ideas and scientific hypotheses is often the result of extensive literature and database reviews, overlaid with scientists’ own novel data and a creative process of making connections that were not made before. We have developed a comprehensive approach to guide this technically challenging data integration task and to make knowledge discovery and hypotheses generation easier for plant and crop researchers. KnetMiner can digest large volumes of scientific literature and biological research to find and visualise links between the genetic and biological properties of complex traits and diseases. Here we report the main design principles behind KnetMiner and provide use cases for mining public datasets to identify unknown links between traits such grain colour and pre-harvest sprouting in Triticum aestivum, as well as, an evidence-based approach to identify candidate genes under an Arabidopsis thaliana petal size QTL. We have developed KnetMiner knowledge graphs and applications for a range of species including plants, crops and pathogens. KnetMiner is the first open-source gene discovery platform that can leverage genome-scale knowledge graphs, generate evidence-based biological networks and be deployed for any species with a sequenced genome. KnetMiner is available at http://knetminer.org. url: https://doi.org/10.1101/2020.04.02.017004 doi: 10.1101/2020.04.02.017004 id: cord-010727-fiukemh3 author: Holme, Petter title: Three faces of node importance in network epidemiology: Exact results for small graphs date: 2017-12-05 words: 4712 sentences: 279 pages: flesch: 63 cache: ./cache/cord-010727-fiukemh3.txt txt: ./txt/cord-010727-fiukemh3.txt summary: We investigate three aspects of the importance of nodes with respect to susceptible-infectious-removed (SIR) disease dynamics: influence maximization (the expected outbreak size given a set of seed nodes), the effect of vaccination (how much deleting nodes would reduce the expected outbreak size), and sentinel surveillance (how early an outbreak could be detected with sensors at a set of nodes). [13] is a bit different from ours-they call important nodes for vaccination "blockers" and important nodes for influence maximization "spreaders".) * holme@cns.pi.titech.ac.jp We will proceed by discussing our setup in greater detail: our implementation of the SIR model, how to analyze the three aspects of importance, network centrality measures that we need for our analysis, and our results, including the smallest networks where different nodes come out as most important. This is the smallest graph where the most important single node (n = 1) is different for influence maximization, vaccination, and sentinel surveillance. abstract: We investigate three aspects of the importance of nodes with respect to susceptible-infectious-removed (SIR) disease dynamics: influence maximization (the expected outbreak size given a set of seed nodes), the effect of vaccination (how much deleting nodes would reduce the expected outbreak size), and sentinel surveillance (how early an outbreak could be detected with sensors at a set of nodes). We calculate the exact expressions of these quantities, as functions of the SIR parameters, for all connected graphs of three to seven nodes. We obtain the smallest graphs where the optimal node sets are not overlapping. We find that (i) node separation is more important than centrality for more than one active node, (ii) vaccination and influence maximization are the most different aspects of importance, and (iii) the three aspects are more similar when the infection rate is low. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217518/ doi: 10.1103/physreve.96.062305 id: cord-010751-fgk05n3z author: Holme, Petter title: Objective measures for sentinel surveillance in network epidemiology date: 2018-08-15 words: 5591 sentences: 332 pages: flesch: 64 cache: ./cache/cord-010751-fgk05n3z.txt txt: ./txt/cord-010751-fgk05n3z.txt summary: Then problem of optimizing sentinel surveillance in networks is to identify the nodes to probe such that an emerging disease outbreak can be discovered early or reliably. Furthermore, we do not find one type of network structure that predicts the objective measures, i.e., that depends both on the data set and the SIR parameter values. Finally, if the objective is to stop the disease as early as possible, it makes sense to measure the time to extinction or detection (infection of a sentinel) [13] . Just as for the case of static networks, τ (t x , f d ) is always nonpositive, meaning the time to detection or extinction ranks the nodes in a way positively correlated with the frequency of detection. In Fig. 4 , we show the correlation between our three objective measures and the structural descriptors as a function of β for the Office data set. abstract: Assume one has the capability of determining whether a node in a network is infectious or not by probing it. Then problem of optimizing sentinel surveillance in networks is to identify the nodes to probe such that an emerging disease outbreak can be discovered early or reliably. Whether the emphasis should be on early or reliable detection depends on the scenario in question. We investigate three objective measures from the literature quantifying the performance of nodes in sentinel surveillance: the time to detection or extinction, the time to detection, and the frequency of detection. As a basis for the comparison, we use the susceptible-infectious-recovered model on static and temporal networks of human contacts. We show that, for some regions of parameter space, the three objective measures can rank the nodes very differently. This means sentinel surveillance is a class of problems, and solutions need to chose an objective measure for the particular scenario in question. As opposed to other problems in network epidemiology, we draw similar conclusions from the static and temporal networks. Furthermore, we do not find one type of network structure that predicts the objective measures, i.e., that depends both on the data set and the SIR parameter values. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217546/ doi: 10.1103/physreve.98.022313 id: cord-319291-6l688krc author: Hung, Chun-Min title: Alignment using genetic programming with causal trees for identification of protein functions date: 2006-09-01 words: 8941 sentences: 632 pages: flesch: 52 cache: ./cache/cord-319291-6l688krc.txt txt: ./txt/cord-319291-6l688krc.txt summary: Particularly, the model has three characteristics: (i) it is a hybrid evolutionary model with multiple fitness functions that uses genetic programming to predict protein functions on a distantly related protein family, (ii) it incorporates modified robust point matching to accurately compare all feature points using the moment invariant and thin-plate spline theorems, and (iii) the hierarchical homologies holding up a novel protein sequence in the form of a causal tree can effectively demonstrate the relationship between proteins. The hybrid model, namely Alignment using Genetic programming with Causal Tree (AGCT), is a heuristic evolutionary method that contains three basic components: (i) genetic programming with innerexchanged individual strategy, (ii) causal trees [4, 28, 31] with probabilistic reasoning, and (iii) construction of hierarchical homologies with local block-to-block alignment using the methods of moment invariant and robust points matching (RPM) [24] . abstract: A hybrid evolutionary model is used to propose a hierarchical homology of protein sequences to identify protein functions systematically. The proposed model offers considerable potentials, considering the inconsistency of existing methods for predicting novel proteins. Because some novel proteins might align without meaningful conserved domains, maximizing the score of sequence alignment is not the best criterion for predicting protein functions. This work presents a decision model that can minimize the cost of making a decision for predicting protein functions using the hierarchical homologies. Particularly, the model has three characteristics: (i) it is a hybrid evolutionary model with multiple fitness functions that uses genetic programming to predict protein functions on a distantly related protein family, (ii) it incorporates modified robust point matching to accurately compare all feature points using the moment invariant and thin-plate spline theorems, and (iii) the hierarchical homologies holding up a novel protein sequence in the form of a causal tree can effectively demonstrate the relationship between proteins. This work describes the comparisons of nucleocapsid proteins from the putative polyprotein SARS virus and other coronaviruses in other hosts using the model. url: https://www.sciencedirect.com/science/article/pii/S0362546X05009028 doi: 10.1016/j.na.2005.09.048 id: cord-155475-is3su3ga author: Kalogeratos, Argyris title: Winning the competition: enhancing counter-contagion in SIS-like epidemic processes date: 2020-06-24 words: 2821 sentences: 181 pages: flesch: 60 cache: ./cache/cord-155475-is3su3ga.txt txt: ./txt/cord-155475-is3su3ga.txt summary: Motivated by social epidemics, we apply this method to a generic continuous-time SIS-like diffusion model where we allow for: i) arbitrary node transition rate functions that describe the dynamics of propagation depending on the network state, and ii) competition between the healthy (positive) and infected (negative) states, which are both diffusive at the same time, yet mutually exclusive on each node. Among them, the Largest Reduction in Infectious Edges (LRIE) [9] results to be the optimal greedy algorithm for resource allocation under limitations in the resource budget, in the N -intertwined Susceptible-Infected-Susceptible (SIS) epidemic model. In this study, we propose the Generalized Largest Reduction in Infectious Edges (gLRIE) strategy, which is adapted for the diffusion competition of recurrent epidemics, as well as nonlinearity and saturation of the functions of node transition rates. abstract: In this paper we consider the epidemic competition between two generic diffusion processes, where each competing side is represented by a different state of a stochastic process. For this setting, we present the Generalized Largest Reduction in Infectious Edges (gLRIE) dynamic resource allocation strategy to advantage the preferred state against the other. Motivated by social epidemics, we apply this method to a generic continuous-time SIS-like diffusion model where we allow for: i) arbitrary node transition rate functions that describe the dynamics of propagation depending on the network state, and ii) competition between the healthy (positive) and infected (negative) states, which are both diffusive at the same time, yet mutually exclusive on each node. Finally we use simulations to compare empirically the proposed gLRIE against competitive approaches from literature. url: https://arxiv.org/pdf/2006.13395v1.pdf doi: nan id: cord-102588-vpu5w9wh author: Le, Trang T. title: treeheatr: an R package for interpretable decision tree visualizations date: 2020-07-10 words: 2389 sentences: 124 pages: flesch: 51 cache: ./cache/cord-102588-vpu5w9wh.txt txt: ./txt/cord-102588-vpu5w9wh.txt summary: Summary treeheatr is an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree''s leaf nodes. Implemented in an easily installed package with a detailed vignette, treeheatr can be a useful teaching tool to enhance students'' understanding of a simple decision tree model before diving into more complex tree-based machine learning methods. We have developed the treeheatr package to incorporate the functionality of ggparty but also utilize the leaf node space to display the data as a heatmap, a popular visualization that uncovers groups of samples and features in a dataset (Wilkinson and Friendly, 2009, Galili,T. The following lines of code compute and visualize the conditional decision tree along with the heatmap containing features that are important for constructing this model ( Fig. 1) : When the first argument x is a data.frame object representing the dataset instead of the decision tree, treeheatr automatically computes a conditional tree with default parameters for visualization. abstract: Summary treeheatr is an R package for creating interpretable decision tree visualizations with the data represented as a heatmap at the tree’s leaf nodes. The integrated presentation of the tree structure along with an overview of the data efficiently illustrates how the tree nodes split up the feature space and how well the tree model performs. This visualization can also be examined in depth to uncover the correlation structure in the data and importance of each feature in predicting the outcome. Implemented in an easily installed package with a detailed vignette, treeheatr can be a useful teaching tool to enhance students’ understanding of a simple decision tree model before diving into more complex tree-based machine learning methods. Availability The treeheatr package is freely available under the permissive MIT license at https://trang1618.github.io/treeheatr and https://cran.r-project.org/package=treeheatr. It comes with a detailed vignette that is automatically built with GitHub Actions continuous integration. Contact ttle@pennmedicine.upenn.edu url: https://doi.org/10.1101/2020.07.10.196352 doi: 10.1101/2020.07.10.196352 id: cord-248848-p7jv79ae author: Lee, Kookjin title: Parameterized Neural Ordinary Differential Equations: Applications to Computational Physics Problems date: 2020-10-28 words: 6965 sentences: 424 pages: flesch: 53 cache: ./cache/cord-248848-p7jv79ae.txt txt: ./txt/cord-248848-p7jv79ae.txt summary: We emphasize that our approach is closely related to [63] , where neural networks are trained to approximate the action of the first-order time-integration scheme applied to latent dynamics and, at each time step, the neural networks take a set of problem-specific parameters as well as reduced state as an input. PNODEs still can learn multiple trajectories, which are characterized by the ODE parameters, even if the same initial states are given for different ODE parameters, which is not achievable with NODEs. Furthermore, the proposed framework is significantly simpler than the common neural network settings for NODEs when they are used to learn latent dynamics: the sequence-to-sequence architectures as in [9, 61, 74, 45, 46] , which require that a (part of) sequence is fed into the encoder network to produce a context vector, which is then fed into the NODE decoder network as an initial condition. abstract: This work proposes an extension of neural ordinary differential equations (NODEs) by introducing an additional set of ODE input parameters to NODEs. This extension allows NODEs to learn multiple dynamics specified by the input parameter instances. Our extension is inspired by the concept of parameterized ordinary differential equations, which are widely investigated in computational science and engineering contexts, where characteristics of the governing equations vary over the input parameters. We apply the proposed parameterized NODEs (PNODEs) for learning latent dynamics of complex dynamical processes that arise in computational physics, which is an essential component for enabling rapid numerical simulations for time-critical physics applications. For this, we propose an encoder-decoder-type framework, which models latent dynamics as PNODEs. We demonstrate the effectiveness of PNODEs with important benchmark problems from computational physics. url: https://arxiv.org/pdf/2010.14685v1.pdf doi: nan id: cord-026306-mkmrninv author: Lepskiy, Alexander title: Belief Functions for the Importance Assessment in Multiplex Networks date: 2020-05-15 words: 4133 sentences: 274 pages: flesch: 61 cache: ./cache/cord-026306-mkmrninv.txt txt: ./txt/cord-026306-mkmrninv.txt summary: The measures use the combination of "high", "low" and "(high, low)" probabilities of the influence based on weighted and unweighted degrees of nodes via Dempster''s rule. Secondly, one can aggregate connections between pairs of nodes to obtain monoplex network and then apply centrality measures to a new weighted graph. In this Section we describe a graph model with one layer of interaction as well as the construction of centrality measure based on a mass function for a network. Additionally, if we consider a 1-neighborhood of nodes in multiplex acyclic graphs with two layers then the following propositions concerning the aggregated interaction centrality value can be proved. We apply Dempster-Shafer theory in order to reveal key elements in undirected weighted graphs as well as to aggregate interactions between nodes into the total ranking. If nodes cooperate with each other on different levels of interactions then we apply a combination rule to mass functions obtained for different layers of a multiplex structure. abstract: We apply Dempster-Shafer theory in order to reveal important elements in undirected weighted networks. We estimate cooperation of each node with different groups of vertices that surround it via construction of belief functions. The obtained intensities of cooperation are further redistributed over all elements of a particular group of nodes that results in pignistic probabilities of node-to-node interactions. Finally, pairwise interactions can be aggregated into the centrality vector that ranks nodes with respect to derived values. We also adapt the proposed model to multiplex networks. In this type of networks nodes can be differently connected with each other on several levels of interaction. Various combination rules help to analyze such systems as a single entity, that has many advantages in the study of complex systems. In particular, Dempster rule takes into account the inconsistency in initial data that has an impact on the final centrality ranking. We also provide a numerical example that illustrates the distinctive features of the proposed model. Additionally, we establish analytical relations between a proposed measure and classical centrality measures for particular graph configurations. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274755/ doi: 10.1007/978-3-030-50143-3_22 id: cord-328875-fgeudou6 author: Leung, Alexander K. C. title: Cervical lymphadenitis: Etiology, diagnosis, and management date: 2009-04-18 words: 3893 sentences: 235 pages: flesch: 39 cache: ./cache/cord-328875-fgeudou6.txt txt: ./txt/cord-328875-fgeudou6.txt summary: Acute bilateral cervical lymphadenitis is usually caused by a viral upper respiratory tract infection or streptococcal pharyngitis. Generalized lymphadenopathy is often caused by a viral infection, and less frequently by malignancies, collagen vascular diseases, and medications. Offending organisms usually fi rst infect the upper respiratory tract, anterior nares, oral cavity, or skin in the head and neck area before spreading to the cervical lymph nodes. Bartonella henselae (cat-scratch disease), nontuberculosis mycobacteria (eg, Mycobacterium avium-intracellulare, Mycobacterium scrofulaceum ), and Mycobacterium tuberculosis ("scrofula") are important causes of subacute or chronic cervical lymphadenopathy [ 8 ] . Kikuchi-Fujimoto disease (histocytic necrotizing lymphadenitis) is a benign cause of lymph node enlargement, usually in the posterior cervical triangle [ 9 ] . Acute bilateral cervical lymphadenitis is usually caused by a viral upper respiratory tract infection or pharyngitis due to S. abstract: Cervical lymphadenopathy is a common problem in children. The condition most commonly represents a transient response to a benign local or generalized infection. Acute bilateral cervical lymphadenitis is usually caused by a viral upper respiratory tract infection or streptococcal pharyngitis. Acute unilateral cervical lymphadenitis is caused by streptococcal or staphylococcal infection in 40% to 80% of cases. Common causes of subacute or chronic lymphadenitis include cat-scratch disease and mycobacterial infection. Generalized lymphadenopathy is often caused by a viral infection, and less frequently by malignancies, collagen vascular diseases, and medications. Laboratory tests are not necessary in most children with cervical lymphadenopathy. Most cases of cervical lymphadenitis are self-limited and require no treatment. The treatment of acute bacterial cervical lymphadenitis without a known primary source should provide adequate coverage for both Staphylococcus aureus and Streptococcus pyogenes. url: https://www.ncbi.nlm.nih.gov/pubmed/19366560/ doi: 10.1007/s11908-009-0028-0 id: cord-028688-5uzl1jpu author: Li, Peisen title: Multi-granularity Complex Network Representation Learning date: 2020-06-10 words: 4539 sentences: 277 pages: flesch: 46 cache: ./cache/cord-028688-5uzl1jpu.txt txt: ./txt/cord-028688-5uzl1jpu.txt summary: In this paper, we propose a multi-granularity complex network representation learning model (MNRL), which integrates topological structure and additional information at the same time, and presents these fused information learning into the same granularity semantic space that through fine-to-coarse to refine the complex network. A series of deep learning-based network representation methods were then proposed to further solve the problems of global topological structure preservation and high-order nonlinearity of data, and increased efficiency. So these location attributes and activity information are inherently indecomposable and interdependence with the suspect, making the two nodes recognize at a finer granularity based on the additional information and relationship structure that the low-dimensional representation vectors learned have certain similarities. To better characterize multiple granularity complex networks and solve the problem of nodes with potential associations that cannot be processed through the relationship structure alone, we refine the granularity to additional attributes, and designed an information fusion method, which are defined as follows: abstract: Network representation learning aims to learn the low dimensional vector of the nodes in a network while maintaining the inherent properties of the original information. Existing algorithms focus on the single coarse-grained topology of nodes or text information alone, which cannot describe complex information networks. However, node structure and attribution are interdependent, indecomposable. Therefore, it is essential to learn the representation of node based on both the topological structure and node additional attributes. In this paper, we propose a multi-granularity complex network representation learning model (MNRL), which integrates topological structure and additional information at the same time, and presents these fused information learning into the same granularity semantic space that through fine-to-coarse to refine the complex network. Experiments show that our method can not only capture indecomposable multi-granularity information, but also retain various potential similarities of both topology and node attributes. It has achieved effective results in the downstream work of node classification and the link prediction on real-world datasets. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338194/ doi: 10.1007/978-3-030-52705-1_18 id: cord-024504-p2vxnn9z author: Lyu, Tianshu title: Node Conductance: A Scalable Node Centrality Measure on Big Networks date: 2020-04-17 words: 4036 sentences: 277 pages: flesch: 63 cache: ./cache/cord-024504-p2vxnn9z.txt txt: ./txt/cord-024504-p2vxnn9z.txt summary: Moreover, with the help of node embedding techniques, Node Conductance is able to be approximately calculated on big networks effectively and efficiently. Thorough experiments present the differences between existing centralities and Node Conductance, its outstanding ability of detecting influential nodes on both static and dynamic network, and its superior efficiency compared with other global centralities. Random walk, which Node Conductance is based on, is also an effective sampling strategy to capture node neighborhood in the recent network embedding studies [10, 21] . We visualize the special case, football network, in order to have an intuitive sense of the properties of Degree, Betweenness, and Node Conductance (other centralities are presented in the Supplementary Material). Comparing with the existing global centralities, Node Conductance computed by DeepWalk is much more scalable and capable to be performed on big datasets. We also rethink the widely used network representation model, DeepWalk, and calculate Node Conductance approximately by the dot product of the input and output vectors. abstract: Node centralities such as Degree and Betweenness help detecting influential nodes from local or global view. Existing global centrality measures suffer from the high computational complexity and unrealistic assumptions, limiting their applications on real-world applications. In this paper, we propose a new centrality measure, Node Conductance, to effectively detect spanning structural hole nodes and predict the formation of new edges. Node Conductance is the sum of the probability that node i is revisited at r-th step, where r is an integer between 1 and infinity. Moreover, with the help of node embedding techniques, Node Conductance is able to be approximately calculated on big networks effectively and efficiently. Thorough experiments present the differences between existing centralities and Node Conductance, its outstanding ability of detecting influential nodes on both static and dynamic network, and its superior efficiency compared with other global centralities. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this chapter (10.1007/978-3-030-47436-2_40) contains supplementary material, which is available to authorized users. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206264/ doi: 10.1007/978-3-030-47436-2_40 id: cord-269711-tw5armh8 author: Ma, Junling title: The importance of contact network topology for the success of vaccination strategies date: 2013-05-21 words: 7036 sentences: 417 pages: flesch: 60 cache: ./cache/cord-269711-tw5armh8.txt txt: ./txt/cord-269711-tw5armh8.txt summary: Abstract The effects of a number of vaccination strategies on the spread of an SIR type disease are numerically investigated for several common network topologies including random, scale-free, small world, and meta-random networks. These strategies, namely, prioritized, random, follow links and contact tracing, are compared across networks using extensive simulations with disease parameters relevant for viruses such as pandemic influenza H1N1/09. (2006) compared the efficacy of contact tracing on random and scale-free networks and found that for transmission rates greater than a certain threshold, the final epidemic size is smaller on a scale-free network than on a corresponding random network, while they considered the effects of degree correlations in Kiss et al. We investigate numerically whether network topologies affect the effectiveness of vaccination strategies started with a delay after the disease is widespread; for example, a 40 day delay as in the second wave of the 2009 influenza pandemic in British Columbia, Canada (Office of the Provincial Health Officer, 2010). abstract: Abstract The effects of a number of vaccination strategies on the spread of an SIR type disease are numerically investigated for several common network topologies including random, scale-free, small world, and meta-random networks. These strategies, namely, prioritized, random, follow links and contact tracing, are compared across networks using extensive simulations with disease parameters relevant for viruses such as pandemic influenza H1N1/09. Two scenarios for a network SIR model are considered. First, a model with a given transmission rate is studied. Second, a model with a given initial growth rate is considered, because the initial growth rate is commonly used to impute the transmission rate from incidence curves and to predict the course of an epidemic. Since a vaccine may not be readily available for a new virus, the case of a delay in the start of vaccination is also considered in addition to the case of no delay. It is found that network topology can have a larger impact on the spread of the disease than the choice of vaccination strategy. Simulations also show that the network structure has a large effect on both the course of an epidemic and the determination of the transmission rate from the initial growth rate. The effect of delay in the vaccination start time varies tremendously with network topology. Results show that, without the knowledge of network topology, predictions on the peak and the final size of an epidemic cannot be made solely based on the initial exponential growth rate or transmission rate. This demonstrates the importance of understanding the topology of realistic contact networks when evaluating vaccination strategies. url: https://www.ncbi.nlm.nih.gov/pubmed/23376579/ doi: 10.1016/j.jtbi.2013.01.006 id: cord-306727-2c1m04je author: Pandey, Prateek title: Promoting Trustless Computation Through Blockchain Technology date: 2020-05-20 words: 2629 sentences: 128 pages: flesch: 55 cache: ./cache/cord-306727-2c1m04je.txt txt: ./txt/cord-306727-2c1m04je.txt summary: The paper explains the blockchain technology and a variety of its implementation through five different use cases in the field of drug supply chain, health insurance, land record management, courier services, and immigration records. Therefore, virtually all the use cases, from money transaction to mushroom supply chain, and from agricultural commodity market place to electronic health records (EHR) are a potential client for blockchain technology. In this article, the authors propose the use of Blockchain in five different use cases, namely drug supply chain, health insurance, land record management, courier services, and immigration records. Therefore, Drug supply, health insurance, and land records blockchains are implemented over the Ethereum network, whereas immigration and courier blockchains are implemented on hyper ledger fabric. While implementing the private Blockchain for immigration records and courier tracking, we observe the performance of the built network in terms of throughput, which is the number of transactions written in the ledger per second. abstract: Records, irrespective of their nature (whether electronic or paper-based), are vulnerable to fraud. People's hard-earned money, their personal information, identity, and health are at a higher risk than ever due to the misuse of technology in doing forgery. However, the technology can also be used as an answer to counteracting against fraudulence prevalent in affairs from every walk of life. This short paper attempts to present the blockchain technology as a solution to overcome the menace of forgery by promoting trustless computing in business transactions. The paper explains the blockchain technology and a variety of its implementation through five different use cases in the field of drug supply chain, health insurance, land record management, courier services, and immigration records. The immigration blockchain is also proposed as a solution to check pandemic like the coronavirus (COVID-19) effectively. The implementation of the Blockchain is performed using a locally built IBM’s hyper-ledger fabric-based platform, and Ethereum public platform. The results are encouraging enough to substitute existing business operations using Blockchain-based solutions. url: https://www.ncbi.nlm.nih.gov/pubmed/32836612/ doi: 10.1007/s40009-020-00978-0 id: cord-168862-3tj63eve author: Porter, Mason A. title: Nonlinearity + Networks: A 2020 Vision date: 2019-11-09 words: 11845 sentences: 667 pages: flesch: 50 cache: ./cache/cord-168862-3tj63eve.txt txt: ./txt/cord-168862-3tj63eve.txt summary: However, recent uses of the term "network" have focused increasingly on connectivity patterns that are more general than graphs [98] : a network''s nodes and/or edges (or their associated weights) can change in time [70, 72] (see Section 3), nodes and edges can include annotations [26] , a network can include multiple types of edges and/or multiple types of nodes [90, 140] , it can have associated dynamical processes [142] (see Sections 3, 4, and 5) , it can include memory [152] , connections can occur between an arbitrary number of entities [127, 131] (see Section 6) , and so on. Following a long line of research in sociology [37] , two important ingredients in the study of networks are examining (1) the importances ("centralities") of nodes, edges, and other small network structures and the relationship of measures of importance to dynamical processes on networks and (2) the large-scale organization of networks [121, 193] . abstract: I briefly survey several fascinating topics in networks and nonlinearity. I highlight a few methods and ideas, including several of personal interest, that I anticipate to be especially important during the next several years. These topics include temporal networks (in which the entities and/or their interactions change in time), stochastic and deterministic dynamical processes on networks, adaptive networks (in which a dynamical process on a network is coupled to dynamics of network structure), and network structure and dynamics that include"higher-order"interactions (which involve three or more entities in a network). I draw examples from a variety of scenarios, including contagion dynamics, opinion models, waves, and coupled oscillators. url: https://arxiv.org/pdf/1911.03805v1.pdf doi: nan id: cord-199630-2lmwnfda author: Ray, Sumanta title: Predicting potential drug targets and repurposable drugs for COVID-19 via a deep generative model for graphs date: 2020-07-05 words: 6389 sentences: 379 pages: flesch: 53 cache: ./cache/cord-199630-2lmwnfda.txt txt: ./txt/cord-199630-2lmwnfda.txt summary: Therefore, host-(1) We link existing high-quality, long-term curated and refined, large scale drug/protein -protein interaction data with (2) molecular interaction data on SARS-CoV-2 itself, raised only a handful of weeks ago, (3) exploit the resulting overarching network using most advanced, AI boosted techniques (4) for repurposing drugs in the fight against SARS-CoV-2 (5) in the frame of HDT based strategies. As for (3)-(5), we will highlight interactions between SARS-Cov-2-host protein and human proteins important for the virus to persist using most advanced deep learning techniques that cater to exploiting network data. As per our simulation study, a large fraction, if not the vast majority of the predictions establish true, hence actionable interactions between drugs on the one hand and SARS-CoV-2 associated human proteins (hence of use in HDT) on the other hand. abstract: Coronavirus Disease 2019 (COVID-19) has been creating a worldwide pandemic situation. Repurposing drugs, already shown to be free of harmful side effects, for the treatment of COVID-19 patients is an important option in launching novel therapeutic strategies. Therefore, reliable molecule interaction data are a crucial basis, where drug-/protein-protein interaction networks establish invaluable, year-long carefully curated data resources. However, these resources have not yet been systematically exploited using high-performance artificial intelligence approaches. Here, we combine three networks, two of which are year-long curated, and one of which, on SARS-CoV-2-human host-virus protein interactions, was published only most recently (30th of April 2020), raising a novel network that puts drugs, human and virus proteins into mutual context. We apply Variational Graph AutoEncoders (VGAEs), representing most advanced deep learning based methodology for the analysis of data that are subject to network constraints. Reliable simulations confirm that we operate at utmost accuracy in terms of predicting missing links. We then predict hitherto unknown links between drugs and human proteins against which virus proteins preferably bind. The corresponding therapeutic agents present splendid starting points for exploring novel host-directed therapy (HDT) options. url: https://arxiv.org/pdf/2007.02338v1.pdf doi: nan id: cord-119522-2ua8218z author: Reddy, C. Rajashekar title: Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors date: 2020-05-12 words: 3573 sentences: 211 pages: flesch: 62 cache: ./cache/cord-119522-2ua8218z.txt txt: ./txt/cord-119522-2ua8218z.txt summary: This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes. For this, total nine low-cost IoT nodes monitoring particulate matter (PM), which is one of the most dominant pollutants, are deployed in a small educational campus in Indian city of Hyderabad. This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes in Indian urban conditions. For spatial interpolation, inverse distance weighing (IDW) scheme is used on these nodes for the data collected before and during the bursting of firecrackers on the main night of Diwali (one of the most popular festivals in India) to show the variability pattern in a small campus, hot spot detection and need for a dense deployment to provide better local pollution indicators. abstract: Current air pollution monitoring systems are bulky and expensive resulting in a very sparse deployment. In addition, the data from these monitoring stations may not be easily accessible. This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes. For this, total nine low-cost IoT nodes monitoring particulate matter (PM), which is one of the most dominant pollutants, are deployed in a small educational campus in Indian city of Hyderabad. Out of these, eight IoT nodes were developed at IIIT-H while one was bought off the shelf. A web based dashboard website is developed to easily monitor the real-time PM values. The data is collected from these nodes for more than five months. Different analyses such as correlation and spatial interpolation are done on the data to understand efficacy of dense deployment in better understanding the spatial variability and time-dependent changes to the local pollution indicators. url: https://arxiv.org/pdf/2005.05936v1.pdf doi: nan id: cord-000196-lkoyrv3s author: Salathé, Marcel title: Dynamics and Control of Diseases in Networks with Community Structure date: 2010-04-08 words: 6817 sentences: 322 pages: flesch: 51 cache: ./cache/cord-000196-lkoyrv3s.txt txt: ./txt/cord-000196-lkoyrv3s.txt summary: Running standard susceptible-infected-resistant (SIR) epidemic simulations (see Methods) on these networks, we find that the average epidemic size, epidemic duration and the peak prevalence of the epidemic are strongly affected by a change in community structure connectivity that is independent of the overall degree distribution of the full network ( Figure 1 ). While infections are most likely to spread along the shortest paths between any two nodes, the cumulative contribution of other paths can still be important [40] : immunization strategies based on random walk centrality result in the lowest number of infected cases at low vaccination coverage (Figure 4b and 4c ). In practice, identifying immunization targets may be impossible using such algorithms, because the structure of the contact network relevant for the spread of a directly transmissible disease is generally not known. abstract: The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2851561/ doi: 10.1371/journal.pcbi.1000736 id: cord-349724-yq4dphmb author: Santos, Hugo title: A Multi-Tier Fog Content Orchestrator Mechanism with Quality of Experience Support date: 2020-05-06 words: 7209 sentences: 369 pages: flesch: 57 cache: ./cache/cord-349724-yq4dphmb.txt txt: ./txt/cord-349724-yq4dphmb.txt summary: For the analysis phase, the Fog4Video collects information about available bandwidth, delay, stall duration, number of stall events, and monetary cost from the network, user client, and fog node. Based on our analysis of the state-of-the-art, we conclude that VoD services deployed in a multi-tier fog architecture improve the QoE by efficiently orchestrating fog nodes resources, while reducing delay and amount of data uploading/downloading to the cloud in a cost efficient fashion. Based on such architecture, Fog4Video classifies the connectivity and resources of each available fog node into a multi-criteria rank, where it considers the AHP method to assign different degrees of importance for each criterion to provide better QoE for each user. Based on these values, Fog4Video implemented in the Orchestrator considers network, fog node, and user information to perform real-time content orchestration, i.e., it chooses an appropriate Streaming Unit from a given tier for the client to download the video. abstract: Abstract Video-on-Demand (VoD) services create a demand for content orchestrator mechanisms to support Quality of Experience (QoE). Fog computing brings benefits for enhancing the QoE for VoD services by caching the content closer to the user in a multi-tier fog architecture, considering their available resources to improve QoE. In this context, it is mandatory to consider network, fog node, and user metrics to choose an appropriate fog node to distribute videos with QoE support properly. In this article, we introduce a content orchestrator mechanism, called of Fog4Video, which chooses an appropriate fog node to download video content. The mechanism considers the available bandwidth, delay, and cost, besides the QoE metrics for VoD, namely number of stalls and stalls duration, to deploy VoD services in the opportune fog node. Decision-making acknowledges periodical reports of QoE from the clients to assess the video streaming from each fog node. These values serve as inputs for a real-time Analytic Hierarchy Process method to compute the influence factor for each parameter and compute the QoE improvement potential of the fog node. Fog4Video is executed in fog nodes organized in multiple tiers, having different characteristics to provide VoD services. Simulation results demonstrate that Fog4Video transmits adapted videos with 30% higher QoE and reduced monetary cost up to 24% than other content request mechanisms. url: https://www.sciencedirect.com/science/article/pii/S1389128620304448?v=s5 doi: 10.1016/j.comnet.2020.107288 id: cord-020885-f667icyt author: Sharma, Ujjwal title: Semantic Path-Based Learning for Review Volume Prediction date: 2020-03-17 words: 4026 sentences: 245 pages: flesch: 48 cache: ./cache/cord-020885-f667icyt.txt txt: ./txt/cord-020885-f667icyt.txt summary: In this work, we present an approach that uses semantically meaningful, bimodal random walks on real-world heterogeneous networks to extract correlations between nodes and bring together nodes with shared or similar attributes. In this work, -We propose a novel method that incorporates restaurants and their attributes into a multimodal graph and extracts multiple, bimodal low dimensional representations for restaurants based on available paths through shared visual, textual, geographical and categorical features. In this section, we discuss prior work that leverages graph-based structures for extracting information from multiple modalities, focussing on the auto-captioning task that introduced such methods. For each of these sub-networks, we perform random walks and use a variant of the heterogeneous skip-gram objective introduced in [6] to generate low-dimensional bimodal embeddings. Our attention-based model combines separately learned bimodal embeddings using a late-fusion setup for predicting the review volume of the restaurants. abstract: Graphs offer a natural abstraction for modeling complex real-world systems where entities are represented as nodes and edges encode relations between them. In such networks, entities may share common or similar attributes and may be connected by paths through multiple attribute modalities. In this work, we present an approach that uses semantically meaningful, bimodal random walks on real-world heterogeneous networks to extract correlations between nodes and bring together nodes with shared or similar attributes. An attention-based mechanism is used to combine multiple attribute-specific representations in a late fusion setup. We focus on a real-world network formed by restaurants and their shared attributes and evaluate performance on predicting the number of reviews a restaurant receives, a strong proxy for popularity. Our results demonstrate the rich expressiveness of such representations in predicting review volume and the ability of an attention-based model to selectively combine individual representations for maximum predictive power on the chosen downstream task. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148205/ doi: 10.1007/978-3-030-45439-5_54 id: cord-010739-28qfmj9x author: Sherborne, N. title: Bursting endemic bubbles in an adaptive network date: 2018-04-09 words: 3350 sentences: 178 pages: flesch: 55 cache: ./cache/cord-010739-28qfmj9x.txt txt: ./txt/cord-010739-28qfmj9x.txt summary: Adaptive network models that account for both epidemic and behavioral change have found oscillations, but in an extremely narrow region of the parameter space, which contrasts with intuition and available data. In this paper we propose a simple susceptible-infected-susceptible epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space. [13] showed that cutting links between susceptible and infected individuals can lead to epidemic reemergence, with long periods of low disease prevalence punctuated by large outbreaks. Figure 2 (d) illustrates this behavior both in simulation and in the meanfield model (4) , showing how after the initial outbreak each new wave of infection is preceded by the recovery of network connectivity. Furthermore, since rewiring nodes choose their new neighbors uniformly at random from all available susceptible nodes, the initial network topology itself is transient, as shown in Fig. 4 , and, as a result, over time our model becomes more relevant. abstract: The spread of an infectious disease is known to change people's behavior, which in turn affects the spread of disease. Adaptive network models that account for both epidemic and behavioral change have found oscillations, but in an extremely narrow region of the parameter space, which contrasts with intuition and available data. In this paper we propose a simple susceptible-infected-susceptible epidemic model on an adaptive network with time-delayed rewiring, and show that oscillatory solutions are now present in a wide region of the parameter space. Altering the transmission or rewiring rates reveals the presence of an endemic bubble—an enclosed region of the parameter space where oscillations are observed. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217531/ doi: 10.1103/physreve.97.042306 id: cord-017062-dkw2sugl author: Singh, Indu title: Delivery Systems for Lymphatic Targeting date: 2013-10-08 words: 9733 sentences: 491 pages: flesch: 39 cache: ./cache/cord-017062-dkw2sugl.txt txt: ./txt/cord-017062-dkw2sugl.txt summary: The major purpose of lymphatic targeting is to provide an effective anticancer chemotherapy to prevent the metastasis of cancer cells by accumulating the drug in the regional lymph node. Hydrophilic multiwalled carbon nanotubes (MWNTs) coated with magnetic nanoparticles (MN-MWNTs) have emerged as an effective delivery system for lymphatic targeting following subcutaneous injection of these particles into the left footpad of Sprague Dawley rats; the left popliteal lymph nodes were dyed black. In vivo study, about eight times lymph node uptake of LyP-1-NPs was seen in metastasis than that of NPs, indicated LyP-1-NP as a promising carrier for targetspecifi c drug delivery to lymphatic metastatic tumours [ 129 ] . To improve carrier retention in lymph nodes, a new method of increasing lymphatic uptake of subcutaneously injected liposome utilises the high-affi nity ligands biotin and avidin. abstract: The lymphatic system has a critical role in the immune system’s recognition and response to disease, and it is an additional circulatory system throughout the entire body. Most solid cancers primarily spread from the main site via the tumour’s surrounding lymphatics before haematological dissemination. Targeting drugs to lymphatic system is quite complicated because of its intricate physiology. Therefore, it tends to be an important target for developing novel therapeutics. Currently, nanocarriers have encouraged the lymphatic targeting, but still there are challenges of locating drugs and bioactives to specific sites, maintaining desired action and crossing all the physiological barriers. Lymphatic therapy using drug-encapsulated colloidal carriers especially liposomes and solid lipid nanoparticles emerges as a new technology to provide better penetration into the lymphatics where residual disease exists. Optimising the proper procedure, selecting the proper delivery route and target area and making use of surface engineering tool, better carrier for lymphotropic system can be achieved. Thus, new methods of delivering drugs and other carriers to lymph nodes are currently under investigation. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7121534/ doi: 10.1007/978-1-4614-9434-8_20 id: cord-284186-zf1w8ksm author: Suran, J. N. title: Radiographic and ultrasonographic findings of the spleen and abdominal lymph nodes in healthy domestic ferrets date: 2017-04-17 words: 6084 sentences: 351 pages: flesch: 53 cache: ./cache/cord-284186-zf1w8ksm.txt txt: ./txt/cord-284186-zf1w8ksm.txt summary: The goal of this prospective, cross-sectional study was to describe the characteristics of the spleen and abdominal lymph nodes on radiographs and with ultrasound in a sample of clientowned, clinically healthy domestic ferrets ( Mustela putorius furo ). For the calculation of sample sizes, the standard deviations of previously reported measurements of abdominal viscera in clinically healthy ferrets were compared, including gross renal measurements (1·25, 1·5 mm), ultrasonographic adrenal thickness (0·5, 0·6 mm) and ultrasonographic jejunal lymph node thickness (1·39, 2.0 mm) (O '' Brien et al . The results presented in this study provide the most comprehensive evaluation of the spleen and abdominal lymph nodes with radiographs and ultrasound in clinically healthy ferrets to date. Based on the results of this study, the jejunal, pancreaticoduodenal, hepatic and caudal mesenteric lymph nodes can be routinely detected with ultrasound in most ferrets. abstract: OBJECTIVE: To describe the radiographic and ultrasonographic characteristics of the spleen and abdominal lymph nodes in clinically healthy ferrets. MATERIALS AND METHODS: Fifty‐five clinically healthy ferrets were prospectively recruited for this cross‐sectional study. Three‐view whole body radiographs and abdominal ultrasonography were performed on awake (23 out of 55) or sedated (32 out of 55) ferrets. On radiographs splenic and abdominal lymph node visibility was assessed. Splenic thickness and echogenicity and lymph node length, thickness, echogenicity, number and presence of cyst‐like changes were recorded. RESULTS: The spleen was radiographically detectable in all ferrets. On ultrasound the spleen was hyperechoic to the liver (55 out of 55) and mildly hyperechoic (28 out of 55), isoechoic (15 out of 55) or mildly hypoechoic (12 out of 55) to the renal cortices. Mean splenic thickness was 11.80 ±0.34 mm. Lymph nodes were radiographically discernible in 28 out of 55 ferrets and included caudal mesenteric and sublumbar nodes. An average of 9 ±2 lymph nodes (mean± standard deviation; mode 10) were identified in each ferret using ultrasound. A single large jejunal lymph node was identified in all ferrets and had a mean thickness of 5.28 ± 1.66 mm. For other lymph nodes the mean thickness measurements plus one standard deviation were less than 4.4 mm (95% confidence interval: ≤ 3.72 mm). CLINICAL SIGNIFICANCE: The information provided in this study may act as a baseline for evaluation of the spleen and lymph nodes in ferrets. url: https://www.ncbi.nlm.nih.gov/pubmed/28414856/ doi: 10.1111/jsap.12680 id: cord-322890-w78tftva author: Suran, Jantra Ngosuwan title: IMAGING FINDINGS IN 14 DOMESTIC FERRETS (MUSTELA PUTORIUS FURO) WITH LYMPHOMA date: 2013-06-06 words: 6858 sentences: 414 pages: flesch: 46 cache: ./cache/cord-322890-w78tftva.txt txt: ./txt/cord-322890-w78tftva.txt summary: Radiographs, CT, MRI, static ultrasound images, and when available, ultrasound cine loops were retrospectively evaluated, and abnormal findings were recorded by J.N.S. The imaging reports generated by a board-certified veterinary radiologist at the time the study was performed were also reviewed. Cytology of the right renal mass in the first ferret was not performed; however, the patient received chemotherapy for the treatment of lymphoma, confirmed from aspiration and biopsy of an enlarged lymph node, and the mass was seen to decrease in size during follow-up studies (Fig. 5) . Concurrent abdominal imaging findings considered incidental to the diagnosed lymphoma included renal cysts (8) , cystic lymph nodes (7), adrenomegaly in ferrets with diagnosed adrenal disease (5), and pancreatic nodules in ferrets diagnosed with insulinoma (2). Additional radiographic findings in this ferret included splenomegaly, hepatomegaly, and abdominal masses consistent with enlarged lymph nodes. abstract: Lymphoma is the most common malignant neoplasia in domestic ferrets, Mustela putorius furo. However, imaging findings in ferrets with lymphoma have primarily been described in single case reports. The purpose of this retrospective study was to describe imaging findings in a group of ferrets with confirmed lymphoma. Medical records were searched between 2002 and 2012. A total of 14 ferrets were included. Radiographs (n = 12), ultrasound (n = 14), computed tomography (CT; n = 1), and magnetic resonance imaging (MRI; n = 1) images were available for review. Median age at the time of diagnosis was 5.2 years (range 3.25–7.6 years). Clinical signs were predominantly nonspecific (8/14). The time between the first imaging study and lymphoma diagnosis was 1 day or less in most ferrets (12). Imaging lesions were predominantly detected in the abdomen, and most frequently included intra‐abdominal lymphadenopathy (12/14), splenomegaly (8/14), and peritoneal effusion (11/14). Lymphadenopathy and mass lesions were typically hypoechoic on ultrasound. Mild peritoneal effusion was the only detected abnormality in two ferrets. Mild pleural effusion was the most common thoracic abnormality (3/12). Expansile lytic lesions were present in the vertebrae of two ferrets with T3‐L3 myelopathy and the femur in a ferret with lameness. Hyperattenuating, enhancing masses with secondary spinal cord compression were associated with vertebral lysis in CT images of one ferret. The MRI study in one ferret with myelopathy was inconclusive. Findings indicated that imaging characteristics of lymphoma in ferrets are similar to those previously reported in dogs, cats, and humans. url: https://doi.org/10.1111/vru.12068 doi: 10.1111/vru.12068 id: cord-027178-tqj8jgem author: Tian, Changbo title: Modeling of Anti-tracking Network Based on Convex-Polytope Topology date: 2020-06-15 words: 4301 sentences: 274 pages: flesch: 62 cache: ./cache/cord-027178-tqj8jgem.txt txt: ./txt/cord-027178-tqj8jgem.txt summary: From the aspects of network stability, network resilience and destroy-resistance, we propose the convex-polytope topology (CPT) applied in the anti-tracking network. From the experimental results, CPT has better robustness, resilience and destroy-resistance confronted with dynamically changed topology, and performs better in the efficiency of network self-optimization. Especially, for the P2P-based anti-tracking network which takes the advantage of the wide distribution of nodes for tracking-resistant communication, it is important to keep a stable, secure and destroy-resistant topology structure. But the convex-polytope structure still has some extreme cases shown in Fig. 2 which may pose a potential threat on the structure stability and communication efficiency of anti-tracking network because of the key nodes. According to the properties of CPT, we can achieve the self-optimization of anti-tracking network to balance the distribution of nodes'' connectivity. For each network constructed by CPT, NN and DHT, we randomly remove p percent of nodes and count the time requirement of network self-optimization as the metric. abstract: Anti-tracking network plays an important role in protection of network users’ identities and communication privacy. Confronted with the frequent network attacks or infiltration to anti-tracking network, a robust and destroy-resistant network topology is an important prerequisite to maintain the stability and security of anti-tracking network. From the aspects of network stability, network resilience and destroy-resistance, we propose the convex-polytope topology (CPT) applied in the anti-tracking network. CPT has three main advantages: (1) CPT can easily avoid the threat of key nodes and cut vertices to network structure; (2) Even the nodes could randomly join in or quit the network, CPT can easily keep the network topology in stable structure without the global view of network; (3) CPT can easily achieve the self-optimization of network topology. Anti-tracking network based on CPT can achieve the self-maintenance and self-optimization of its network topology. We compare CPT with other methods of topology optimization. From the experimental results, CPT has better robustness, resilience and destroy-resistance confronted with dynamically changed topology, and performs better in the efficiency of network self-optimization. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302821/ doi: 10.1007/978-3-030-50417-5_32 id: cord-016196-ub4mgqxb author: Wang, Cheng title: Study on Efficient Complex Network Model date: 2012-11-20 words: 2486 sentences: 92 pages: flesch: 51 cache: ./cache/cord-016196-ub4mgqxb.txt txt: ./txt/cord-016196-ub4mgqxb.txt summary: This paper summarizes the relevant research of the complex network systematically based on Statistical Property, Structural Model, and Dynamical Behavior. An important discover in the complex network researching is that the average path length of the most of the large-scale real networks is much less than our imagine, which we call ''''Small-world Effect''''. Paul Erdös and Alfred Rényi discovered a complete random network model in the late 50s twentieth century, it is made of any two nodes which connected with probability p in the graph made of N nodes, its average degree is \k [ ¼ pðN À 1Þ % PN; the average path length l : ln N= lnð\k [ Þ; the convergence factor C ¼ P; when the value of N is very large, the distribution of the node degree approximately equals poisson distribution. However, the regular network has aggregation, but its average shortest path length is larger, random graph has the opposite property, having small-world and less convergence factor. abstract: This paper summarizes the relevant research of the complex network systematically based on Statistical Property, Structural Model, and Dynamical Behavior. Moreover, it emphatically introduces the application of the complex network in the economic system. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7120410/ doi: 10.1007/978-3-642-35398-7_20 id: cord-024437-r5wnz7rq author: Wang, Yubin title: SLGAT: Soft Labels Guided Graph Attention Networks date: 2020-04-17 words: 3501 sentences: 243 pages: flesch: 53 cache: ./cache/cord-024437-r5wnz7rq.txt txt: ./txt/cord-024437-r5wnz7rq.txt summary: In this paper, we propose a soft labels guided graph attention network (SLGAT) to improve the performance of node representation learning by leveraging generated pseudo labels. Graph attention networks (GAT) [23] , which is one of the most representative GCNs, learns the weights for neighborhood aggregation via self-attention mechanism [22] and achieves promising performance on semi-supervised node classification problem. In this paper, we propose soft labels guided attention networks (SLGAT) for semi-supervised node representation learning. First, SLGAT aggregates the features of neighbors using convolutional networks and predicts soft labels for each node based on the learned embeddings. The weights for neighborhood aggregation learned by a feedforward neural network based on both label information of central nodes and features of neighboring nodes, which can lead to learning more discriminative node representations for classification. Unlike the prior graph attention networks [23, 28] , we use label information as guidance to learn the weights of neighboring nodes for feature aggregation. abstract: Graph convolutional neural networks have been widely studied for semi-supervised classification on graph-structured data in recent years. They usually learn node representations by transforming, propagating, aggregating node features and minimizing the prediction loss on labeled nodes. However, the pseudo labels generated on unlabeled nodes are usually overlooked during the learning process. In this paper, we propose a soft labels guided graph attention network (SLGAT) to improve the performance of node representation learning by leveraging generated pseudo labels. Unlike the prior graph attention networks, our SLGAT uses soft labels as guidance to learn different weights for neighboring nodes, which allows SLGAT to pay more attention to the features closely related to the central node labels during the feature aggregation process. We further propose a self-training based optimization method to train SLGAT on both labeled and pseudo labeled nodes. Specifically, we first pre-train SLGAT on labeled nodes and generate pseudo labels for unlabeled nodes. Next, for each iteration, we train SLGAT on the combination of labeled and pseudo labeled nodes, and then generate new pseudo labels for further training. Experimental results on semi-supervised node classification show that SLGAT achieves state-of-the-art performance. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206162/ doi: 10.1007/978-3-030-47426-3_40 id: cord-014845-odnlt6fr author: Wu, Jia title: Reducing Energy Consumption and Overhead Based on Mobile Health in Big Data Opportunistic Networks date: 2016-08-13 words: 5394 sentences: 405 pages: flesch: 64 cache: ./cache/cord-014845-odnlt6fr.txt txt: ./txt/cord-014845-odnlt6fr.txt summary: title: Reducing Energy Consumption and Overhead Based on Mobile Health in Big Data Opportunistic Networks This algorithm can reduce energy consumption and overhead, then improve deliver ratio in big data communication. Compare with Spray and Wait algorithm, Binary spray and wait algorithm in opportunistic networks, this algorithm acquires good results by reduce energy consumption, overhead and deliver ratio. This algorithm can judge routing request and predict data data packets and then can overhead, energy consumption and deliver ratio in transmission. From what has been discussed above, ADTRA needs to solve energy consumption, overhead and deliver ratio when the algorithm is applied of big data environment. In wireless communication, if doctors or hospitals send all pictures to patients, many network resource must be wasted, especially in big data environment, mass of people join in transmission, there are no enough space storing effective information. abstract: A great number of people and non-equalizing medical resources, in developing countries, have become a serious contradiction. Not only does it affects the person’s life, but also causes serious epidemic contagious, because patients can not get help with hospital on time. With the development of wireless communication network, patient may get medical information by wireless network device. It can alleviate contradictions between patients and medical resources. But in developing countries, population quantity is a big data. How to solve data packets in wireless communication network is a big problem when researchers face huge population. In order to solve some problems in big data communication, this paper founds availability data transmission routing algorithm. This algorithm can reduce energy consumption and overhead, then improve deliver ratio in big data communication. Compare with Spray and Wait algorithm, Binary spray and wait algorithm in opportunistic networks, this algorithm acquires good results by reduce energy consumption, overhead and deliver ratio. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7088852/ doi: 10.1007/s11277-016-3610-4 id: cord-355393-ot7hztyk author: Yuan, Peiyan title: Community-based immunization in opportunistic social networks date: 2015-02-15 words: 5983 sentences: 467 pages: flesch: 66 cache: ./cache/cord-355393-ot7hztyk.txt txt: ./txt/cord-355393-ot7hztyk.txt summary: More interestingly, we find that high local importance but non-central nodes play a big role in epidemic spreading process, removing them improves the immunization efficiency by 25% to 150% at different scenarios. To this end, we investigate the evolution of community structure in opportunistic social networks, and analyze the effect of community-based immunization strategy on epidemic spreading. We observe that the most efficient immunization strategy on epidemic spreading is to remove nodes with high local importance in communities. Although many random mobility models, such as Random Walk and Random Way Point, have been widely used in opportunistic social networks for evaluating routing performance or even the epidemic dynamics [30, 31] , they cannot reflect the main features of human mobility, including the truncated power-law flights and pause-times, the heterogeneously bounded mobility areas of different nodes, etc. abstract: Abstract Immunizing important nodes has been shown to be an effective solution to suppress the epidemic spreading. Most studies focus on the globally important nodes in a network, but neglect the locally important nodes in different communities. We claim that given the temporal community feature of opportunistic social networks (OSN), this strategy has a biased understanding of the epidemic dynamics, leading us to conjecture that it is not “the more central, the better” for the implementation of control strategy. In this paper, we track the evolution of community structure and study the effect of community-based immunization strategy on epidemic spreading. We first break the OSN traces down into different communities, and find that the community structure helps to delay the outbreak of epidemic. We then evaluate the local importance of nodes in communities, and show that immunizing nodes with high local importance can remarkably suppress the epidemic. More interestingly, we find that high local importance but non-central nodes play a big role in epidemic spreading process, removing them improves the immunization efficiency by 25% to 150% at different scenarios. url: https://www.sciencedirect.com/science/article/pii/S037843711400942X doi: 10.1016/j.physa.2014.10.087 id: cord-102394-vk4ag44m author: Zhang, Hai-Feng title: Impact of asymptomatic infection on coupled disease-behavior dynamics in complex networks date: 2016-08-14 words: 3220 sentences: 204 pages: flesch: 59 cache: ./cache/cord-102394-vk4ag44m.txt txt: ./txt/cord-102394-vk4ag44m.txt summary: The analytic results emph{quantitatively} describe the influence of different factors, such as asymptomatic infection, the awareness rate, the network structure, and so forth, on the epidemic thresholds. Since the manner of the diffusion of awareness is quite different from the mechanism of epidemic spreading, the coupled disease-behavior interaction models in multiplex networks were also investigated [18] [19] [20] . Therefore, the SAUIR model is an irreversible process but the SAUIS model is a reversible process, which yields different theoretical methods to deal with their epidemic thresholds and the results. For our SAUIR model, on one hand, the epidemic threshold is very difficult or impossible to obtain by solving the meanfield based differential equations; on the other hand, in Ref. Near the epidemic threshold, the number of infected nodes is very few, indicating that the value of θ is a very small too. Then the epidemic thresholds for the improved SIS model and SIR model were obtained by using different theoretical methods. abstract: Studies on how to model the interplay between diseases and behavioral responses (so-called coupled disease-behavior interaction) have attracted increasing attention. Owing to the lack of obvious clinical evidence of diseases, or the incomplete information related to the disease, the risks of infection cannot be perceived and may lead to inappropriate behavioral responses. Therefore, how to quantitatively analyze the impacts of asymptomatic infection on the interplay between diseases and behavioral responses is of particular importance. In this Letter, under the complex network framework, we study the coupled disease-behavior interaction model by dividing infectious individuals into two states: U-state (without evident clinical symptoms, labelled as U) and I-state (with evident clinical symptoms, labelled as I). A susceptible individual can be infected by U- or I-nodes, however, since the U-nodes cannot be easily observed, susceptible individuals take behavioral responses emph{only} when they contact I-nodes. The mechanism is considered in the improved Susceptible-Infected-Susceptible (SIS) model and the improved Susceptible-Infected-Recovered (SIR) model, respectively. Then, one of the most concerned problems in spreading dynamics: the epidemic thresholds for the two models are given by two methods. The analytic results emph{quantitatively} describe the influence of different factors, such as asymptomatic infection, the awareness rate, the network structure, and so forth, on the epidemic thresholds. Moreover, because of the irreversible process of the SIR model, the suppression effect of the improved SIR model is weaker than the improved SIS model. url: https://arxiv.org/pdf/1608.04049v1.pdf doi: 10.1209/0295-5075/114/38004 id: cord-007415-d57zqixs author: da Fontoura Costa, Luciano title: Correlations between structure and random walk dynamics in directed complex networks date: 2007-07-30 words: 2202 sentences: 124 pages: flesch: 58 cache: ./cache/cord-007415-d57zqixs.txt txt: ./txt/cord-007415-d57zqixs.txt summary: They establish the necessary conditions for networks to be topologically and dynamically fully correlated (e.g., word adjacency and airport networks), and show that in this case Zipf''s law is a consequence of the match between structure and dynamics. They establish the necessary conditions for networks to be topologically and dynamically fully correlated ͑e.g., word adjacency and airport networks͒, and show that in this case Zipf''s law is a consequence of the match between structure and dynamics. 2766683͔ We address the relationship between structure and dynamics in complex networks by taking the steady-state distribution of the frequency of visits to nodes-a dynamical feature-obtained by performing random walks 1 along the networks. In addition to providing a modeling approach intrinsically compatible with dynamics involving successive visits to nodes by a single or multiple agents, such as is the case with world wide web ͑WWW͒ navigation, text writing, and transportation systems, random walks are directly related to diffusion. abstract: In this letter the authors discuss the relationship between structure and random walk dynamics in directed complex networks, with an emphasis on identifying whether a topological hub is also a dynamical hub. They establish the necessary conditions for networks to be topologically and dynamically fully correlated (e.g., word adjacency and airport networks), and show that in this case Zipf’s law is a consequence of the match between structure and dynamics. They also show that real-world neuronal networks and the world wide web are not fully correlated, implying that their more intensely connected nodes are not necessarily highly active. url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7112555/ doi: 10.1063/1.2766683 ==== make-pages.sh questions [ERIC WAS HERE] ==== make-pages.sh search /data-disk/reader-compute/reader-cord/bin/make-pages.sh: line 77: /data-disk/reader-compute/reader-cord/tmp/search.htm: No such file or directory Traceback (most recent call last): File "/data-disk/reader-compute/reader-cord/bin/tsv2htm-search.py", line 51, in with open( TEMPLATE, 'r' ) as handle : htm = handle.read() FileNotFoundError: [Errno 2] No such file or directory: '/data-disk/reader-compute/reader-cord/tmp/search.htm' ==== make-pages.sh topic modeling corpus Zipping study carrel