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Abstract Deciding when to depart on long‐distance, sometimes global, movements can be especially important for flying species. Adverse weather conditions can affect energetic flight costs and navigational ability. While departure timings and conditions have been well‐studied for migratory flights to and from the breeding range, few studies have focussed on flights within the non‐breeding season. Yet in some cases, overwintering ranges can be large enough that ecological barriers, and a lack of resting sites en route, may resist movement, especially in unfavorable environmental conditions. Understanding the conditions that will enable or prohibit flights within an overwintering range is particularly relevant in light of climate change, whereby increases in extreme weather events may reduce the connectivity of sites. We tracked 495 (n = 251 in 2019; n = 244 in 2020) overwintering red knots (Calidris canutus islandica) in the Dutch Wadden Sea and investigated how many departed towards the UK (on westward relocation flights), which requires flying over the North Sea. For those that departed, we used a resource selection model to determine the effect of environmental conditions on the timing of relocation flights. Specifically, we investigated the effects of wind, rain, atmospheric pressure, cloud cover, and migratory timing relative to sunset and tidal cycle, which have all been shown to be crucial to migratory departure conditions. Approximately 37% (2019) and 36% (2020) of tagged red knots departed on westward relocation flights, indicating differences between individuals' space use within the overwintering range. Red knots selected for departures between 1 and 2.5 h after sunset, approximately 4 h before high tide, with tailwinds and little cloud cover. However, rainfall and changes in atmospheric pressure appear unimportant. Our study reveals environmental conditions that are important for relocation flights across an ecological barrier, indicating potential consequences of climate change on connectivity.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site's data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare.

Abstract Tracking animal movement is important for understanding how animals interact with their (changing) environment, and crucial for predicting and explaining how animals are affected by anthropogenic activities. The Wadden Sea is a UNESCO World Heritage Site and a region of global importance for millions of shorebirds. Due to climate change and anthropogenic activity, understanding and predicting movement and space-use in areas like the Wadden Sea is increasingly important. Monitoring and predicting animal movement, however, requires high-resolution tracking of many individuals. While high-resolution tracking has been made possible through GPS, trade-offs between tag weight and battery life limit its use to larger species. Here, we introduce WATLAS (the Wadden Sea deployment of the ATLAS tracking system) capable of monitoring the movements of hundreds of (small) birds simultaneously in the Dutch Wadden Sea. WATLAS employs an array of receiver stations that can detect and localize small, low-cost tags at fine spatial (metres) and temporal resolution (seconds). From 2017 to 2021, we tracked red knots, sanderlings, bar-tailed godwits, and common terns. We use parts of these data to give four use-cases revealing its performance and demonstrating how WATLAS can be used to study numerous aspects of animal behaviour, such as, space-use (both intra- and inter-specific), among-individual variation, and social networks across levels of organization: from individuals, to species, to populations, and even communities. After describing the WATLAS system, we first illustrate space-use of red knots across the study area and how the tidal environment affects their movement. Secondly, we show large among-individual differences in distances travelled per day, and thirdly illustrate how high-throughput WATLAS data allows calculating a proximity-based social network. Finally, we demonstrate that using WATLAS to monitor multiple species can reveal differential space use. For example, despite sanderlings and red knots roosting together, they foraged in different areas of the mudflats. The high-resolution tracking data collected by WATLAS offers many possibilities for research into the drivers of bird movement in the Wadden Sea. WATLAS could provide a tool for impact assessment, and thus aid nature conservation and management of the globally important Wadden Sea ecosystem.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

This music score was submitted for the Kaleidoscope 2020 Call for Scores, an open access collaboration with the UCLA Music Library.

Aims: Poor sleep is highly prevalent in young people and increases risk of mental health difficulties, yet access to sleep interventions remains limited. This paper evaluates the use of a sleep intervention delivered by non‐expert practitioners in a secondary care youth mental health service. Method: Assistant psychologists were trained to deliver a six‐session 1:1 cognitive‐behavioural sleep intervention adapted for use with young people with mental health difficulties. A within‐subject design assessed clinical outcomes relating to sleep (Insomnia Severity Index), psychological distress and personal goals (Goal Based Outcome Measures) at four time points. Results: High referral, intervention take‐up (82.82%) and completion (70%) rates were reported, together with high baseline levels of insomnia (Insomnia Severity Index mean 20.47, SD 3.68) and poor sleep efficiency (56.36%, SD 17.23). Fifty‐six young people (average age 19.2 years, SD 3.25) were included in the outcome analysis. Statistically and clinically significant improvements were seen across all outcome measures, with 68% no longer meeting clinical threshold (ISI ≥15) for insomnia at endpoint. Conclusions: This study demonstrates exceptionally high levels of clinical need and engagement with a sleep intervention adapted specifically for young people with mental health difficulties. Whilst limited by the uncontrolled design, large improvements in insomnia and psychological distress support its effectiveness and utility in clinical settings. More robust implementation and evaluation is warranted in broader youth mental health services to promote earlier access. [ABSTRACT FROM AUTHOR]

Memories about the spatial environment, such as the locations of foraging patches, are expected to affect how individuals move around the landscape. However, individuals differ in the ability to remember spatial locations (spatial cognitive ability) and evidence is growing that these inter-individual differences influence a range of fitness proxies. Yet empirical evaluations directly linking inter-individual variation in spatial cognitive ability and the development and structure of movement paths are lacking. We assessed the performance of young pheasants (Phasianus colchicus) on a spatial cognition task before releasing them into a novel, rural landscape and tracking their movements. We quantified changes in the straightness and speed of their transitory paths over one month. Birds with better performances on the task initially made slower transitory paths than poor performers but by the end of the month, there was no difference in speed. In general, birds increased the straightness of their path over time, indicating improved efficiency independent of speed, but this was not related to performance on the cognitive task. We suggest that initial slow movements may facilitate more detailed information gathering by better performers and indicates a potential link between an individual's spatial cognitive ability and their movement behaviour.

Individuals likely vary in how quickly they learn, how many different associations they may be able to maintain, and how long they can remember previously learned associations. However, it is unclear whether capacities for these cognitive processes are consistent within individuals, or whether individual performance differs when presented with novel variants of tasks, or across tasks that assess different cognitive abilities. We investigate associative learning and long-term reference memory in young (3-8 week-old) pheasants (Phasianus colchicus) using a series of visual binary discrimination problems that were presented at different intervals of time. Birds were sequentially presented with five novel color pairs, where they could learn that one color of each pair was consistently rewarded. After experiencing these learning trials, subjects were re-tested on each discrimination problem, but at different intervals (0-27 days), to assess their memory. Subjects’ learning performance improved within 50 trials of each discrimination problem. We found no differences in performance between final learning sessions and initial memory sessions across the different time intervals, suggesting that pheasants retained the previously learned associations of multiple color pairs over at least a 27-day interval. Moreover, proactive interference did not impede their ability to recall subsequently learned color contingencies. Although individual learning and memory performance correlated positively, we found no evidence that individuals’ performances were consistent across task variants. Our findings illuminate capacities for associative learning and long-term reference memory in pheasants.

The relationship between neuronal density and verbal memory in left and right hippocampal subfields was investigated in patients who underwent surgery for alleviation of temporal lobe epilepsy. The surgery consisted of unilateral partial removal of the hippocampus along with the anterior temporal lobe and amygdala. Study 1 looked at post-surgical explicit versus implicit verbal memory for lists of words while Study 2 looked at pre- and post-surgical explicit memory for word pairs. Left subfield CA1 appeared to be the most consistently involved in explicit and implicit memory. The results of the two studies confirm presence of hemispheric asymmetry in verbal memory. The notion that hippocampal control of memory is most apparent in post-surgical performance is discussed.