Explore the vast range of titles available.

Do the movements of animals, including humans, follow patterns that can be described quantitatively by simple laws of motion? If so, then why? These questions have attracted the attention of scientists in many disciplines, and stimulated debates ranging from ecological matters to queries such as 'how can there be free will if one follows a law of motion?' This is the first book on this rapidly evolving subject, introducing random searches and foraging in a way that can be understood by readers without a previous background on the subject. It reviews theory as well as experiment, addresses open problems and perspectives, and discusses applications ranging from the colonization of Madagascar by Austronesians to the diffusion of genetically modified crops. The book will interest physicists working in the field of anomalous diffusion and movement ecology as well as ecologists already familiar with the concepts and methods of statistical physics.

1.Animals move to interact with the environment in order to find food resources and cover.Intrinsic characteristics affecting feeding and antipredatory strategies likely shape variation inmovement patterns and home range formation between individuals, populations and species.2.Browsing herbivores selectively forage on patchily distributed resources in areas with morecanopy cover, whereas mixed feeders and grazers feed on more open grasslands and tend toaggregate as an antipredatory strategy. We therefore predicted that at small temporal scales,browsers will show greater net displacements (i.e. typical of searching patterns) than mixedfeeders or grazers; but at larger temporal scales, we expect the opposite pattern, since gregari-ous species will need to use larger areas to feed the whole herd. We also predicted that thefeeding/antipredatory strategy will determine the behavioural responses to other environmentalfactors.3.To test this, we compared spatial movement patterns at multiple scales (from 20-minintervals to annual home ranges) of three sympatric, similar-sized, alpine ungulates which dif-fer in their feeding/antipredatory strategy: roe deer (solitary browsers), mouflon (gregariousgrazers) and chamois (intermediate feeders in smaller groups). We used location data fromGPS-collared females of the three species in the French Alps.4.As predicted, we found that multi-scale spatial patterns depended on the feeding/antipreda-tory strategy. Browsers foraged within smaller range areas, searching back and forth. Mixedfeeders and, especially, grazers covered larger areas, presumably to satisfy herd needs. Thefeeding/antipredatory strategies also determined the interspecific variability in behaviouralresponses to factors such as maternal status, weather, habitat type or human disturbance,supporting our hypothesis.5.Exploring interspecific variability, we showed how movement behaviour and home rangeformation vary substantially, even among species within the same guild. This mechanism mightbe important to maintain intra-guild multi-species associations and increase biodiversity,through contributing to niche segregation and, thus, coexistence.

The simultaneous classification of the three most basic eye-movement patterns is known as the ternary eye-movement classification problem (3EMCP). Dynamic, interactive real-time applications that must instantly adjust or respond to certain eye behaviors would highly benefit from accurate, robust, fast, and low-latency classification methods. Recent developments based on 1D-CNN-BiLSTM and TCN architectures have demonstrated to be more accurate and robust than previous solutions, but solely considering offline applications. In this paper, we propose a TCN classifier for the 3EMCP, adapted to online applications, that does not require look-ahead buffers. We introduce a new lightweight preprocessing technique that allows the TCN to make real-time predictions at about 500 Hz with low latency using commodity hardware. We evaluate the TCN performance against other two deep neural models: a CNN-LSTM and a CNN-BiLSTM, also adapted to online classification. Furthermore, we compare the performance of the deep neural models against a lightweight real-time Bayesian classifier (I-BDT). Our results, considering two publicly available datasets, show that the proposed TCN model consistently outperforms other methods for all classes. The results also show that, though it is possible to achieve reasonable accuracy levels with zero-length look ahead, the performance of all methods improve with the use of look-ahead information. The codebase, pre-trained models, and datasets are available at https://github.com/elmadjian/OEMC.

Identifying neuromuscular screening factors for anterior cruciate ligament (ACL) injury is a critical step toward large-scale deployment of effective ACL injury-prevention programs. The Landing Error Scoring System (LESS) is a valid and reliable clinical assessment of jump-landing biomechanics. To investigate the ability of the LESS to identify individuals at risk for ACL injury in an elite-youth soccer population. Cohort study. Field-based functional movement screening performed at soccer practice facilities. A total of 829 elite-youth soccer athletes (348 boys, 481 girls; age = 13.9 ± 1.8 years, age range = 11 to 18 years), of whom 25% (n = 207) were less than 13 years of age. Baseline preseason testing for all participants consisted of a jump-landing task (3 trials). Participants were followed prospectively throughout their soccer seasons for diagnosis of ACL injuries (1217 athlete-seasons of follow-up). Landings were scored for \"errors\" in technique using the LESS. We used receiver operator characteristic curves to determine a cutpoint on the LESS. Sensitivity and specificity of the LESS in predicting ACL injury were assessed. Seven participants sustained ACL injuries during the follow-up period; the mechanism of injury was noncontact or indirect contact for all injuries. Uninjured participants had lower LESS scores (4.43 ± 1.71) than injured participants (6.24 ± 1.75; t1215 = -2.784, P = .005). The receiver operator characteristic curve analyses suggested that 5 was the optimal cutpoint for the LESS, generating a sensitivity of 86% and a specificity of 64%. Despite sample-size limitations, the LESS showed potential as a screening tool to determine ACL injury risk in elite-youth soccer athletes.

ContextDispersal is a crucial process for species persistence under natural and disturbed landscapes. The effectiveness of stepping stones as a connectivity strategy for increasing dispersal success depends on landscape structure and animal behaviour, such as the perceptual range.ObjectivesWe quantify the relative contribution of stepping stones (small fragments and scattered trees) to dispersal success considering interactions with perceptual range, habitat amount and configuration.MethodsWe develop an individual-based model (IBM) to simulate the dispersal movement of small mammals. The model is parametrized using empirical estimates of perceptual range and movement properties (turning angles and steps length). Simulations are implemented in landscapes with varying gradients of habitat amount and clumpiness, with and without the presence of stepping stones.ResultsSmall patches and scattered trees combined, or only scattered trees, have a positive effect on dispersal. Meanwhile, the presence of only small patches has negative effects on dispersal. Habitat amount positively influences dispersal, which decreases abruptly when the habitat amount is less than 20%. This threshold disappears in the presence of stepping stones. In landscapes with intermediate levels of habitat amount, landscape fragmentation (low clumpiness) has a positive effect on dispersal success.ConclusionsStepping stones, especially scattered trees, are a fundamental connectivity strategy for the conservation of small non-flying vertebrates in human-modified landscapes, particularly landscapes with less than 20% of habitat amount. However, small patches stepping stones may act as ecological traps leading the individuals to dead-ends. Their effectiveness in improving dispersal depends on both landscape structure and perceptual range.

Modern movement tracking technologies enable acquisition of high quality data about movements of the players and the ball in the course of a football match. However, there is a big difference between the raw data and the insights into team behaviors that analysts would like to gain. To enable such insights, it is necessary first to establish relationships between the concepts characterizing behaviors and what can be extracted from data. This task is challenging since the concepts are not strictly defined. We propose a computational approach to detecting and quantifying the relationships of pressure emerging during a game. Pressure is exerted by defending players upon the ball and the opponents. Pressing behavior of a team consists of multiple instances of pressure exerted by the team members. The extracted pressure relationships can be analyzed in detailed and summarized forms with the use of static and dynamic visualizations and interactive query tools. To support examination of team tactics in different situations, we have designed and implemented a novel interactive visual tool “time mask”. It enables selection of multiple disjoint time intervals in which given conditions are fulfilled. Thus, it is possible to select game situations according to ball possession, ball distance to the goal, time that has passed since the last ball possession change or remaining time before the next change, density of players’ positions, or various other conditions. In response to a query, the analyst receives visual and statistical summaries of the set of selected situations and can thus perform joint analysis of these situations. We give examples of applying the proposed combination of computational, visual, and interactive techniques to real data from games in the German Bundesliga, where the teams actively used pressing in their defense tactics.

Virtual reality (VR) technology has gained popularity across various fields; however, its use often induces cybersickness, characterized by symptoms such as dizziness, nausea, and eye strain. This study investigated the differences in cybersickness levels and head movement patterns under three distinct VR viewing conditions: dynamic VR (DVR), static VR (SVR), and a control condition (CON) using a simulator. Thirty healthy adults participated, and their head movements were recorded using the Meta Quest 2 VR headset and analyzed using Python. The Virtual Reality Sickness Questionnaire (VRSQ) assessed subjective cybersickness levels. The results revealed that the SVR condition induced the highest VRSQ scores (M = 58.057), indicating the most severe cybersickness symptoms, while the DVR condition elicited significantly higher values in head movement variables, particularly in the coefficient of variation (CV) and integral values of head position along the vertical axis, and mean velocity (p < 0.05). These findings suggest that VR content characteristics directly influence users’ head movement patterns, closely related to cybersickness occurrence and severity. This study highlights the importance of analyzing head movement patterns in cybersickness research and provides insights for VR content design.

Summary 1. Decreasing rate of migration in several species as a consequence of climate change and anthropic pressure, together with increasing evidence of space-use strategies intermediate between residency and complete migration, are very strong motivations to evaluate migration occurrence and features in animal populations. 2. The main goal of this paper was to perform a relative comparison between methods for identifying and charact erizing migration at the individual and population level on the basis of animal location data. 3. We classified 104 yearly individual trajectories from five populations of three deer species as migratory or non-migratory, by means of three methods: seasonal home range overlap, spatio-temporal separation of seasonal clusters and the Net Squared Displacement (NSD) method. For migr atory cases, we also measured timing and distance of migration and resi- dence time on the summer range. Finally, we comp ared the classification in migration cases across methods and populations. 4. All methods consistently identified migration at the population level, that is, they coherently dis- tinguished between complete or almost complete migr atory populations and partially migratory populations. Ho wever, in the latter case, methods co heren tly classified only about 50% of the sin- gle cases, that is they classified differently at the individual-animal level. We therefore infer that the compariso n of methods may help point to ‘less-stereo typed ’ cases in the residency -to-migration continuum. For ca ses consistently classified by all methods, no signifi cant differences were found in migration distance, or residence time on summer ranges. Timing of migration estimated by NSD was ea rlier than by the other two methods, both for spring and autumn migrations. 5. We suggest three steps to identify improper inferences from migration data and to enhance understanding of intermedia te space-use strategies. We recommend (i) classifying migration behaviours using more than one method, (ii) performing sensitivity analysis on method parame- ters to identify the extent of the differences and (iii) investigating inconsistently classified cases as these may often be ecologically interest ing (i.e. less-stereotyped migratory behaviours). adehabitat, hom e range overlap, movement patterns, Net Squared Displacement, red deer, reindeer, residence behaviour, roe deer, spatial clusters

New radar satellites provide global coverage and the possibility of long-term, regular frequency (days-weeks) surface displacement measurements through the application of high precision multi-temporal InSAR (Synthetic Aperture Radar Interferometry) techniques. This represents an excellent opportunity to investigate and improve our understanding of the behavior of extremely slow landslides, as well as of the long- to short-term controls of their activity. In urban settings, such landslides deserve special attention, as their cumulative movements can cause significant socio-economic damage. Here, we re-examine the case of a long-lived, deep-seated landslide in the Apennine Mountains (Italy) which was urbanized between the late 1970s and early 2000s. The case provides a rare opportunity to highlight the benefits of the integrated analysis of long-term (several years) borehole inclinometer measurements with 15 years of multi-temporal InSAR displacement data. We present evidence of the landslide composite nature and asymmetry, and draw attention to the recent period of accelerated movement that coincided with the foot failure event. This helps constraining the interpretation of the borehole and InSAR data and demonstrating the predominantly rotational landslide mechanism. We show how a detailed analysis of sparse inclinometer and more spatially continuous InSAR measurements, when combined with local rainfall records, can reveal long- to short-term patterns of temporal variability in landslide motions and allow anticipating the consequences of future landslide activity.

Rugby union is a high intensity intermittent sport, typically analysed via set time periods or rolling average methods. This study reports the demands of international rugby union via global positioning system (GPS) metrics expressed as mean ball in play (BiP), maximum BiP (max BiP), and whole match outputs. Single cohort cross sectional study involving 22 international players, categorised as forwards and backs. A total of 88 GPS files from eight international test matches were collected during 2016. An Opta sportscode timeline was integrated into the GPS software to split the data into BiP periods. Metres per min (mmin−1), high metabolic load per min (HML), accelerations per min (Acc), high speed running per min (HSR), and collisions per min (Coll) were expressed relative to BiP periods and over the whole match (>60min). Whole match metrics were significantly lower than all BiP metrics (p<0.001). Mean and max BiP HML, (p<0.01) and HSR (p<0.05) were significantly higher for backs versus forwards, whereas Coll were significantly higher for forwards (p<0.001). In plays lasting 61s or greater, max BiP mmin−1 were higher for backs. Max BiP mmin−1, HML, HSR and Coll were all time dependant (p<0.05) showing that both movement metrics and collision demands differ as length of play continues. This study uses a novel method of accurately assessing the BiP demands of rugby union. It also reports typical and maximal demands of international rugby union that can be used by practitioners and scientists to target training of worst-case scenario’s equivalent to international intensity. Backs covered greater distances at higher speeds and demonstrated higher HML, in general play as well as ‘worst case scenarios’; conversely forwards perform a higher number of collisions.