0000000000684461

AUTHOR

Wei Song

showing 4 related works from this author

Criminal networks analysis in missing data scenarios through graph distances

2021

Data collected in criminal investigations may suffer from issues like: (i) incompleteness, due to the covert nature of criminal organizations; (ii) incorrectness, caused by either unintentional data collection errors or intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyze nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data, and to determine which network type is most affected by it. The networks are firstly pruned using two specific m…

Euclidean distanceData collectionComputer scienceNode (networking)Law enforcementGraph (abstract data type)Adjacency listData miningMissing datacomputer.software_genreCriminal investigationcomputerCrimRxiv
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Disrupting resilient criminal networks through data analysis: The case of Sicilian Mafia

2020

Compared to other types of social networks, criminal networks present hard challenges, due to their strong resilience to disruption, which poses severe hurdles to law-enforcement agencies. Herein, we borrow methods and tools from Social Network Analysis to (i) unveil the structure of Sicilian Mafia gangs, based on two real-world datasets, and (ii) gain insights as to how to efficiently disrupt them. Mafia networks have peculiar features, due to the links distribution and strength, which makes them very different from other social networks, and extremely robust to exogenous perturbations. Analysts are also faced with the difficulty in collecting reliable datasets that accurately describe the…

FOS: Computer and information sciencesEconomicsComputer science0211 other engineering and technologiesSocial SciencesCriminology02 engineering and technologycomputer.software_genreSocial NetworkingSociologyStatistics - Machine LearningCentralityCriminals; Humans; Sicily; Social NetworkingSicilySocial network analysisHuman CapitalMultidisciplinarySettore INF/01 - InformaticaQ05 social sciencesRComputer Science - Social and Information NetworksPoliceProfessionsSocial NetworksMedicineCrimeNetwork AnalysisResearch ArticleNetwork analysisComputer and Information SciencesScienceMachine Learning (stat.ML)Computer securityNetwork ResilienceHuman capitalBetweenness centralityHumansResilience (network)0505 lawBlock (data storage)Social and Information Networks (cs.SI)021110 strategic defence & security studiesSocial networkbusiness.industryNode (networking)CriminalsCommunicationsPeople and Places050501 criminologyPopulation GroupingsCentralitybusinesscomputer
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Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

2016

Seuls les 100 premiers auteurs dont les auteurs INRA ont été entrés dans la notice. La liste complète des auteurs et de leurs affiliations est accessible sur la publication.; International audience; In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues…

[SDV]Life Sciences [q-bio]autophagosomeReview Articleddc:616.07stressstreLC3MESH: AnimalsSettore MED/49 - Scienze Tecniche Dietetiche ApplicateSettore BIO/06 - Anatomia Comparata E Citologiachaperone-mediated autophagyComputingMilieux_MISCELLANEOUSSettore BIO/11Pharmacology. TherapySettore BIO/13standards [Biological Assay]autolysosomeMESH: Autophagy*/physiologylysosomemethods [Biological Assay]Biological AssaySettore BIO/17 - ISTOLOGIAErratumHumanBiochemistry & Molecular BiologySettore BIO/06physiology [Autophagy]Chaperonemediated autophagy[SDV.BC]Life Sciences [q-bio]/Cellular BiologyNOautophagy guidelines molecular biology ultrastructureautolysosome; autophagosome; chaperone-mediated autophagy; flux; LC3; lysosome; macroautophagy; phagophore; stress; vacuoleMESH: Biological Assay/methodsMESH: Computer Simulationddc:570Autolysosome Autophagosome Chaperonemediated autophagy Flux LC3 Lysosome Macroautophagy Phagophore Stress VacuoleAutophagyAnimalsHumansComputer SimulationSettore BIO/10ddc:612BiologyphagophoreMESH: HumansvacuoleAnimalLC3; autolysosome; autophagosome; chaperone-mediated autophagy; flux; lysosome; macroautophagy; phagophore; stress; vacuole; Animals; Biological Assay; Computer Simulation; Humans; Autophagy0601 Biochemistry And Cell BiologyfluxmacroautophagyMESH: Biological Assay/standards*Human medicineLC3; autolysosome; autophagosome; chaperone-mediated autophagy; flux; lysosome; macroautophagy; phagophore; stress; vacuole
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Erratum

2016

Author(s): Klionsky, DJ; Abdelmohsen, K; Abe, A; Abedin, MJ; Abeliovich, H; Arozena, AA; Adachi, H; Adams, CM; Adams, PD; Adeli, K; Adhihetty, PJ; Adler, SG; Agam, G; Agarwal, R; Aghi, MK; Agnello, M; Agostinis, P; Aguilar, PV; Aguirre-Ghiso, J; Airoldi, EM; Ait-Si-Ali, S; Akematsu, T; Akporiaye, ET; Al-Rubeai, M; Albaiceta, GM; Albanese, C; Albani, D; Albert, ML; Aldudo, J; Algul, H; Alirezaei, M; Alloza, I; Almasan, A; Almonte-Beceril, M; Alnemri, ES; Alonso, C; Altan-Bonnet, N; Altieri, DC; Alvarez, S; Alvarez-Erviti, L; Alves, S; Amadoro, G; Amano, A; Amantini, C; Ambrosio, S; Amelio, I; Amer, AO; Amessou, M; Amon, A; An, Z; Anania, FA; Andersen, SU; Andley, UP; Andreadi, CK; Andrieu-Ab…

0301 basic medicineSettore BIO/06biologyCell Biology[SDV.BC]Life Sciences [q-bio]/Cellular Biologybiology.organism_classificationCell biologyInterpretation (model theory)03 medical and health sciencesArama030104 developmental biologyMolecular BiologyHumanitiesComputingMilieux_MISCELLANEOUS
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