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A longitudinal network analysis of social dynamics in rooks corvus frugilegus： repeated group modifications do not affect social network in captive rooks

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Current Zoology 2017年第5期63卷 379-388页

作者： Palmyre H. BOUCHERIE sebastian sosa Cristian PASQUARETTA Valerie DUFOUR Institut Pluridisciplinaire Hubert Curien University of Strasbourg 23 rue Becquerel 67087 Strasbourg France Centre National de la Recherche Scientifique UMR 7178 67087 Strasbourg France Formerly affiliated with Grupo de Conducta Adaptativa e Interacci6n Psychology Faculty University of Barcelona 08035 Barcelona Spain

Numerous studies have investigated the remarkable variation of social features and the resulting structures across species. Indeed, relationships are dynamic and vary in time according to various factors such as environmental conditions or individuals attributes. However, few studies have investigated the processes that stabilize the structures within a given species, and the behavioral mechanisms that ensure their coherence and continuity across time. Here, we used a dynamic actor-based model, RSiena, to investigate the consistency of the temporal dynamic of relationships of a group of captive rooks facing recurrent modifications in group composition (i.e., the loss and introduction of individuals). We found that changes in relationships (i.e., formation and removal) followed consistent patterns regardless of group composition and sex-ratio. Rooks preferentially interacted with paired congeners (i.e., unpopular attachment) and were more likely to form relationships with individuals bonded to a current social partner (i.e., “friends of friends”, or triadic closure). The sex of individuals had no effect on the dynamic of relationships. This robust behavioral mechanisms formed the basis of inter-connected networks, composed of sub-structures of individuals emerging from the enmeshment of dyadic and triadic motifs. Overall, the present study reveals crucial aspects of the behavioral mechanisms shaping rooks social structure, suggesting that rooks live in a well-integrated society, going far beyond the unique monogamous pair-bond.

关键词：社会网络乌鸦网络分析饲养修改行为机制人际关系组成关系

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Exploiting Deep Learning Techniques for Colon Polyp Segmentation

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Computers, Materials & Continua 2021年第5期67卷 1629-1644页

作者： Daniel Sierra-sosa sebastian Patino-Barrientos Begonya Garcia-Zapirain Cristian Castillo-Oleam Adel Elmaghraby Department of Computer Science and Engineering University of LouisvilleLouisvilleKYUSA Centro de Computacion Cientifica Apolo at Universidad EAFIT MedelinColombia eVida Research Group University of DeustoBilbaoSpain

As colon cancer is among the top causes of death, there is a growinginterest in developing improved techniques for the early detection of colonpolyps. Given the close relation between colon polyps and colon cancer,their detection helps avoid cancer cases. The increment in the availability ofcolorectal screening tests and the number of colonoscopies have increasedthe burden on the medical personnel. In this article, the application of deeplearning techniques for the detection and segmentation of colon polyps incolonoscopies is presented. Four techniques were implemented and evaluated:Mask-RCNN, PANet, Cascade R-CNN and Hybrid Task Cascade (HTC).These were trained and tested using CVC-Colon database, ETIS-LARIBPolyp, and a proprietary dataset. Three experiments were conducted to assessthe techniques performance: (1) Training and testing using each databaseindependently, (2) Mergingd the databases and testing on each database independently using a merged test set, and (3) Training on each dataset and testingon the merged test set. In our experiments, PANet architecture has the bestperformance in Polyp detection, and HTC was the most accurate to segmentthem. This approach allows us to employ Deep Learning techniques to assisthealthcare professionals in the medical diagnosis for colon cancer. It is anticipated that this approach can be part of a framework for a semi-automatedpolyp detection in colonoscopies.

关键词： Colon polyps deep learning image segmentation

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