Planning UAV Activities for Efficient User Coverage in Disaster Areas

Climate changes brought about by global warming as well as man-made environmental changes are often the cause of sever natural disasters. ICT, which is itself responsible for global warming due to its high carbon footprint, can play a role in alleviating the consequences of such hazards by providing reliable, resilient means of communication during a disaster crisis. In this paper, we explore the provision of wireless coverage through UAVs (Unmanned Aerial Vehicles) to complement, or replace, the traditional communication infrastructure. The use of UAVs is indeed crucial in emergency scenarios, as they allow for the quick and easy deployment of micro and pico cellular base stations where needed. We characterize the movements of UAVs and define an optimization problem to determine the best UAV coverage that maximizes the user throughput, while maintaining fairness across the different parts of the geographical area that has been affected by the disaster. To evaluate our strategy, we simulate a flooding in San Francisco and the car traffic resulting from people seeking safety on higher ground

Navigational style influences eye movement pattern during exploration and learning of an environmental map

During navigation people may adopt three different spatial styles (i.e., Landmark, Route, and Survey). Landmark style (LS) people are able to recall familiar landmarks but cannot combine them with directional information; Route style (RS) people connect landmarks to each other using egocentric information about direction; Survey style (SS) people use a map-like representation of the environment. SS individuals generally navigate better than LS and RS people. Fifty-one college students (20 LS; 17 RS, and 14 SS) took part in the experiment. The spatial cognitive style (SCS) was assessed by means of the SCS test; participants then had to learn a schematic map of a city, and after 5 min had to recall the path depicted on it. During the learning and delayed recall phases, eye-movements were recorded. Our intent was to investigate whether there is a peculiar way to explore an environmental map related to the individual's spatial style. Results support the presence of differences in the strategy used by the three spatial styles for learning the path and its delayed recall. Specifically, LS individuals produced a greater number of fixations of short duration, while the opposite eye movement pattern characterized SS individuals. Moreover, SS individuals showed a more spread and comprehensive explorative pattern of the map, while LS individuals focused their exploration on the path and related targets. RS individuals showed a pattern of exploration at a level of proficiency between LS and SS individuals. We discuss the clinical and anatomical implications of our data

Selection of protein conformations for structure-based polypharmacology studies

Several drugs exert their therapeutic effect through the modulation of multiple targets. Structure-based approaches hold great promise for identifying compounds with the desired polypharmacological profiles. These methods use knowledge of the protein binding sites to identify stereoelectronically complementary ligands. The selection of the most suitable protein conformations to be used in the design process is vital, especially for multitarget drug design in which the same ligand has to be accommodated in multiple binding pockets. Herein, we focus on currently available techniques for the selection of the most suitable protein conformations for multitarget drug design, compare the potential advantages and limitations of each method, and comment on how their combination could help in polypharmacology drug design

Correspondence

We read with interest the article by Touzé et al. entitled ‘Retinal vascular abnormalities in children with Neurofibromatosis type 1’. The Authors assessed clinical retinal microvascular abnormalities (RVAs) characteristics in a large series of children affected by NF1 on near-infrared imaging. The overall prevalence of RVAs was 37.1% in accordance with the results of Moramarco et al. This is notable as vascular tortuosity is a phenotype reported with variable appearance and frequency in clinical studies as opposed to corkscrew pattern, for whom an excellent interobserver agreement was observe

Stochastic Optimization of Service Provision with Selfish Users

We develop a computationally efficient technique to solve a fairly general distributed service provision problem with selfish users and imperfect information. In particular, in a context in which the service capacity of the existing infrastructure can be partially adapted to the user load by activating just some of the service units, we aim at finding the configuration of active service units that achieves the best trade-off between maintenance (e.g.\ energetic) costs for the provider and user satisfaction. The core of our technique resides in the implementation of a belief-propagation (BP) algorithm to evaluate the cost configurations. Numerical results confirm the effectiveness of our approach.Comment: paper presented at NETSTAT Workshop, Budapest - June 201

Drug Repurposing and Polypharmacology to Fight SARS-CoV-2 Through Inhibition of the Main Protease

The outbreak of a new coronavirus (SARS-CoV-2), which is responsible for the COVID-19 disease and is spreading rapidly around the world, urgently requires effective therapeutic treatments. In this context, drug repurposing represents a valuable strategy, as it enables accelerating the identification of drug candidates with already known safety profiles, possibly aiding in the late stages of clinical evaluation. Moreover, therapeutic treatments based on drugs with beneficial multi-target activities (polypharmacology) may show an increased antiviral activity or help to counteract severe complications concurrently affecting COVID-19 patients. In this study, we present the results of a computational drug repurposing campaign that aimed at identifying potential inhibitors of the main protease (Mpro) of the SARS-CoV-2. The performed in silico screening allowed the identification of 22 candidates with putative SARS-CoV-2 Mpro inhibitory activity. Interestingly, some of the identified compounds have recently entered clinical trials for COVID-19 treatment, albeit not being assayed for their SARS-CoV-2 antiviral activity. Some candidates present a polypharmacology profile that may be beneficial for COVID-19 treatment and, to the best of our knowledge, have never been considered in clinical trials. For each repurposed compound, its therapeutic relevance and potential beneficial polypharmacological effects that may arise due to its original therapeutic indication are thoroughly discussed

Decentering visual arts history from local knowledge

En este artículo partimos de dos experiencias de investigación en el desarrollo de la cursada de Historia del Arte 7 que, por las condiciones coyunturales definidas por la pandemia en el año 2021, se situaron en dos localidades de la provincia de Buenos Aires: General Pinto y Chivilcoy. A partir de las mismas me pregunto sobre la posibilidad de provocar descentramientos epistemológicos al interior de la disciplina, pero también geográficos que reactualicen el sentido de la idea de Nación en tanto una construcción que incorpore estas prácticas y saberes otros aún no historiados por la Historia del Arte canónica.This article focuses on two investigation experiences during the development of Art History 7 classes in the COVID 19 pandemic context. The investigations were developed in two small towns from the province of Buenos Aires: General Pinto and Chivilcoy. This article discusses possibilities not only of epistemic decentralization in the apprenticeship, but possibilities of geographical decentralization too, in order to actualize the meaning of the nation concept as a construction comprehending these kind of practices and knowledge, as well as others not contemplated by canonic Art History.Facultad de Arte

Mining and modelling temporal dynamics of followers' engagement on online social networks

A relevant fraction of human interactions occurs on online social networks. In this context, the freshness of content plays an important role, with content popularity rapidly vanishing over time. We therefore investigate how influencers' generated content (i.e., posts) attracts interactions, measured by the number of likes or reactions. We analyse the activity of influencers and followers over more than 5 years, focusing on two popular social networks: Facebook and Instagram, including more than 13 billion interactions and about 4 million posts. We investigate the influencers' and followers' behaviour over time, characterising the arrival process of interactions during the lifetime of posts, which are typically short-lived. After finding the factors playing a crucial role in the post popularity dynamics, we propose an analytical model for the user interactions. We tune the parameters of the model based on the past behaviour observed for each given influencer, discovering that fitted parameters are pretty similar across different influencers and social networks. We validate our model using experimental data and effectively apply the model to perform early prediction of post popularity, showing considerable improvements over a simpler baseline