Existing systems for wildlife monitoring focus either on acquiring the location of animals via GPS or detecting their proximity via wireless communication; the integration of the two, remarkably increasing the biological value of the data gathered, is hitherto unexplored. We offer this integration as our first contribution, embodied by our WILDSCOPE system whose key functionality is georeferenced proximity detection of an animal to others or to landmarks. However, to be truly useful to biologists, the in-field monitoring system must be complemented by two key elements, largely neglected by the literature and constituting our other contributions: i) a model exposing the tradeoffs between accuracy and lifetime, enabling biologists to determine the configuration best suited to their needs, a task complicated by the rich set of on-board devices (GPS, low-power radio, GSM modem) whose activation depends strongly on the biological questions and target species at hand; ii) a validation in controlled experiments that, by eliciting the relationship between proximity detection, the distance at which it reliably occurs, and the location acquisition, provides the cornerstone for the biologists' analysis of wildlife behavior. We test WILDSCOPE in real-world experimental setups and deployments with different degrees of control, ascertaining the platform accuracy w.r.t. ground truth and comparing against a commercial proximity logger.

BackgroundRandomized clinical trials (RCTs) about Ezetimibe's efficacy on patient-oriented outcomes have given discordant results. The aim of this study was to determine the net effect of Ezetimibe and of the widely marketed combination, Ezetimibe+simvastatin, on mortality and morbidity outcomes.Methods and FindingsWe searched for RCT on Ezetimibe using MEDLINE, CCTR, EMBASE, ClinicalTrials.gov databases up to December 2013, Merck and Novartis online registers, and personal communications. Two authors independently selected trials fulfilling these criteria: RCTs comparing Ezetimibe±statin or another lipid-lowering drug against placebo, or against the same lipid-lowering drug at the same dosage, with a follow-up at least 24 weeks and one or more of these outcomes: all-cause mortality, cardiovascular (CV) mortality, stroke, myocardial infarction (MI), cancer, serious adverse events (SAEs); we assessed the risk of bias using the Cochrane checklist. We extracted the data for major clinical events as a dichotomous measure, with the patient the unit of analysis. Pooled analysis was done with random and fixed effect based models. Trials comparing Ezetimibe plus a lipid-lowering drug against the same lipidlowering drug representing the net effect of Ezetimibe, showed a nonsignificant tendency toward damage for cancer, MI, stroke and SAEs. Ezetimibe+simvastatin vs. simvastatin alone showed a stronger tendency towards a higher risk for all-cause death (2.52; 0.65-9.74), CV death (3.04; 0.48-19.21), non-CV death (3.03; 0.12-73.50), MI (1.91; 0.42-8.70), stroke (2.38; 0.46-12.35), cancer (RR 11.11; 0.62-198.29), and SAEs (1.45; 0.95-2.23). Limitations include small numbers of events and inadequate power of the pooling. Trials comparing Ezetimibe+simvastatin vs placebo showed non-significant effects: MI (0.81; 0.66-1.00 p = 0.051), all-cause death (1.02; 0.95-1.09), CV death (0.91; 0.80-1.04), non-CV death (108; 0.99-1.18), stroke (0.86; 0.72-1.04), cancer (1.18; 0.80-1.74), SAEs (1.01; 0.96-1.06).ConclusionsEzetimibe±simvastatin had inconsistent effects on important outcomes. No firm conclusions are possible, but findings indicative of damage suggest much more selective use of Ezetimibe±simvastatin.

Background:In animal ecology, inter-individual encounters are often investigated using automated proximity loggers. However, data acquired are typically spatially implicit, i.e. the question 'Where did the contact occur?' remains unanswered. To resolve this issue, recent advancements in Wireless Sensor Network technology have facilitated the geo-referencing of animal contacts. Among these, WildScope devices integrate GPS-based telemetry within fully distributed networks, allowing contact-triggered GPS location acquisition. In this way, the ecological context in which contacts occur can be assessed. We evaluated the performance of WildScope in close-to-real settings, whilst controlling for movement of loggers and obstacles, performing field trials that simulated: (1) different scenarios of encounters between individuals (mobile-mobile contacts) and (2) patterns of individual focal resource use (mobilefixed contacts). Each scenario involved one to three mobile and two fixed loggers and was replicated at two different radio transmission powers. For each scenario, we performed and repeated a script of actions that corresponded to expected contact events and contact-triggered GPS locations. By comparing expected and observed events, we obtained the success rate of: (1) contact detection and (2) contact-triggered GPS location acquisition. We modelled these in dependence on radio power and number of loggers by means of generalized linear mixed models. Results:Overall we found a high success rate of both contact detection (88-87%: power 3 and 7) and contacttriggered GPS location acquisition (85-97%: power 3 and 7). The majority of errors in contact detection were false negatives (66-69%: power 3 and 7). Number of loggers was positively correlated with contact success rate, whereas radio power had little effect on either variable. Conclusions:Our work provides an easily repeatable approach for exploring the potential and testing the performance of WildScope GPS-based geo-referencing proximity loggers, for studying both animal-to-animal encounters and animal use of focal resources. However, our finding that success rate did not equal 100%, and in particular that false negatives represent a non-negligible proportion, suggests that validation of proximity loggers should be undertaken in close-to-real settings prior to field deployment, as stochastic events affecting radio connectivity (e.g. obstacles, movement) can bias proximity patterns in real-life scenarios.

Policy makers have implemented multiple non-pharmaceutical strategies to mitigate the COVID-19 worldwide crisis. Interventions had the aim of reducing close proximity interactions, which drive the spread of the disease. A deeper knowledge of human physical interactions has revealed necessary, especially in all settings involving children, whose education and gathering activities should be preserved. Despite their relevance, almost no data are available on close proximity contacts among children in schools or other educational settings during the pandemic.Contact data are usually gathered via Bluetooth, which nonetheless offers a low temporal and spatial resolution. Recently, ultra-wideband (UWB) radios emerged as a more accurate alternative that nonetheless exhibits a significantly higher energy consumption, limiting in-field studies. In this paper, we leverage a novel approach, embodied by the Janus system that combines these radios by exploiting their complementary benefits. The very accurate proximity data gathered in-field by Janus, once augmented with several metadata, unlocks unprecedented levels of information, enabling the development of novel multi-level risk analyses.By means of this technology, we have collected real contact data of children and educators in three summer camps during summer 2020 in the province of Trento, Italy. The wide variety of performed daily activities induced multiple individual behaviors, allowing a rich investigation of social environments from the contagion risk perspective. We consider risk based on duration and proximity of contacts and classify interactions according to different risk levels. We can then evaluate the summer camps’ organization, observe the effect of partition in small groups, or social bubbles, and identify the organized activities that mitigate the riskier behaviors.Overall, we offer an insight into the educator-child and child-child social interactions during the pandemic, thus providing a valuable tool for schools, summer camps, and policy makers to (re)structure educational activities safely.

Proximity detection is at the core of several mobile and ubiquitous computing applications. These include reactive use cases, e.g., alerting individuals of hazards or interaction opportunities, and others concerned only with logging proximity data, e.g., for offline analysis and modeling. Common approaches rely on Bluetooth Low Energy (BLE) or ultra-wideband (UWB) radios. Nevertheless, these strike opposite tradeoffs between the accuracy of distance estimates quantifying proximity and the energy efficiency affecting system lifetime, effectively forcing a choice between the two and ultimately constraining applicability. Janus reconciles these dimensions in a dual-radio protocol enabling accurate and energy-efficient proximity detection, where the energy-savvy BLE is exploited to discover devices and coordinate their distance measurements, acquired via the energy-hungry UWB. A model supports domain experts in configuring Janus for their use cases with predictable performance. The latency, reliability, and accuracy of Janus are evaluated experimentally, including realistic scenarios endowed with the mm-level ground truth provided by a motion capture system. Energy measurements show that Janus achieves weeks to months of autonomous operation, depending on the use case configuration. Finally, several large-scale campaigns exemplify its practical usefulness in real-world contexts.