The European Virus Archive goes global: A growing resource for research

The European Virus Archive (EVA) was created in 2008 with funding from the FP7-EU Infrastructure Programme, in response to the need for a coordinated and readily accessible collection of viruses that could be made available to academia, public health organisations and industry. Within three years, it developed from a consortium of nine European laboratories to encompass associated partners in Africa, Russia, China, Turkey, Germany and Italy. In 2014, the H2020 Research and Innovation Framework Programme (INFRAS projects) provided support for the transformation of the EVA from a European to a global organization (EVAg). The EVAg now operates as a non-profit consortium, with 26 partners and 20 associated partners from 21 EU and non-EU countries. In this paper, we outline the structure, management and goals of the EVAg, to bring to the attention of researchers the wealth of products it can provide and to illustrate how end-users can gain access to these resources. Organisations or individuals who would like to be considered as contributors are invited to contact the EVAg coordinator, Jean-Louis Romette, at [email protected]

An integer linear programming model for fair multitarget tracking in cooperative multirobot systems

Cooperative Multi-Robot Observation of Multiple Moving Targets (CMOMMT) denotes a class of problems in which a set of autonomous mobile robots equipped with limited-range sensors keep under observation a (possibly larger) set of mobile targets. In the existing literature, it is common to let the robots cooperatively plan their motion in order to maximize the average targets’ detection rate, defined as the percentage of mission steps in which a target is observed by at least one robot. We present a novel optimization model for CMOMMT scenarios which features fairness of observation among different targets as an additional objective. The proposed integer linear formulation exploits available knowledge about the expected motion patterns of the targets, represented as a probabilistic occupancy maps estimated in a Bayesian framework. An empirical analysis of the model is performed in simulation, considering multiple scenarios to study the effects of the amount of robots and of the prediction accuracy for the mobility of the targets. Both centralized and distributed implementations are presented and compared to each other evaluating the impact of multi-hop communications and limited information sharing. The proposed solutions are also compared to two algorithms selected from the literature. The model is finally validated on a real team of ground robots in a limited set of scenarios

Facial Surgery in the Era of SARS-CoV-2 and Beyond: Challenges, Considerations, and Initiatives

The SARS-CoV-2 pandemic resulted in the implementation of healthcare practice regulations and restrictions across the United States. To facilitate safe patient management practices for facial plastic and reconstructive surgeons, appropriate guidelines and recommendations should be followed. Guidelines and recommendations should include a synthesis of the best evidence available from public health authorities and respected members in the surgery community. This review contains evidence-based suggestions that prioritize the safety of healthcare professionals and patients to help guide facial and reconstructive surgeons toward safe patient management. © 2020 The Authors. Published by Wolters Kluwer Health, Inc.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The European Virus Archive goes global: A growing resource for research

The European Virus Archive (EVA) was created in 2008 with funding from the FP7-EU Infrastructure Programme, in response to the need for a coordinated and readily accessible collection of viruses that could be made available to academia, public health organisations and industry. Within three years, it developed from a consortium of nine European laboratories to encompass associated partners in Africa, Russia, China, Turkey, Germany and Italy. In 2014, the H2020 Research and Innovation Framework Programme (INFRAS projects) provided support for the transformation of the EVA from a European to a global organization (EVAg). The EVAg now operates as a non-pro fi t consortium, with 26 partners and 20 associated partners from 21 EU and non-EU countries. In this paper, we outline the structure, management and goals of the EVAg, to bring to the attention of researchers the wealth of products it can provide and to illustrate how end-users can gain access to these re- sources. Organisations or individuals who would like to be considered as contributors are invited to contact the EVAg coordinator, Jean-Louis Romette, at [email protected] Reviewe