ExMove: An open-source toolkit for processing and exploring animal-tracking data in R.

Ongoing technological advances have led to a rapid increase in the number, type and scope of animal-tracking studies. In response, many software tools have been developed to analyse animal movement data. These tools generally focus on movement modelling, but the steps required to clean raw data files from different tracking devices have been largely ignored. Such pre-processing steps are often time-consuming and involve a steep learning curve but are crucial for the creation of high-quality, standardised and shareable data. Moreover, decisions made at this early stage can substantially influence subsequent analyses, and in the current age of reproducibility crisis, the transparency of this process is vital. Here we present an open-access, reproducible toolkit written in the programming language R for processing raw data files into a single cleaned data set for analyses and upload to online tracking databases (found here: https://github.com/ExMove/ExMove). The toolkit comprises well-documented and flexible code to facilitate data processing and user understanding, both of which can increase user confidence and improve the uptake of sharing open and reproducible code. Additionally, we provide an overview website (found here: https://exmove.github.io/) and a Shiny app to help users visualise tracking data and assist with parameter determination during data cleaning. The toolkit is generalisable to different data formats and device types, uses modern 'tidy coding' practices, and relies on a few well-maintained packages. Among these, we perform spatial manipulations using the package sf. Overall, by collating all required steps from data collection to archiving on open access databases into a single, robust pipeline, our toolkit provides a valuable resource for anyone conducting animal movement analyses and represents an important step towards increased standardisation and reproducibility in animal movement ecology.

Scaling up ocean conservation through recognition of key biodiversity areas in the Southern Ocean from multispecies tracking data.

Biodiversity is critical for maintaining ecosystem function but is threatened by increasing anthropogenic pressures. In the Southern Ocean, a highly biologically productive region containing many endemic species, proactive management is urgently needed to mitigate increasing pressures from fishing, climate change, and tourism. Site-based conservation is one important tool for managing the negative impacts of human activities on ecosystems. The Key Biodiversity Area (KBA) Standard is a standardized framework used to define sites vital for the persistence of global biodiversity based on criteria and quantitative thresholds. We used tracking data from 14 species of Antarctic and subantarctic seabirds and pinnipeds from the publicly available Retrospective Analysis of Antarctic Tracking Data (RAATD) data set to define KBAs for a diverse suite of marine predators. We used track2kba, an R package that supports identification of KBAs from telemetry data through identification of highly used habitat areas and estimates of local abundance within sites. We compared abundance estimates at each site with thresholds for KBA criteria A1, B1, and D1 (related to globally threatened species, individual geographically restricted species, and demographic aggregations, respectively). We identified 30 potential KBAs for 13 species distributed throughout the Southern Ocean that were vital for each individual species, population, and life-history stage for which they were determined. These areas were identified as highly used by these populations based on observational data and complement the ongoing habitat modeling and bioregionalization work that has been used to prioritize conservation areas in this region. Although further work is needed to identify potential KBAs based on additional current and future data sets, we highlight the benefits of utilizing KBAs as part of a holistic approach to marine conservation, given their significant value as a global conservation tool.

Ampliación de la conservación oceánica por medio del reconocimiento de áreas importantes de biodiversidad en el Océano Antártico a partir de datos de rastreo de varias especies Resumen La biodiversidad es fundamental para mantener la función de los ecosistemas, pero está amenazada por las crecientes presiones antropogénicas. En el Océano Antártico, una región con mucha producción biológica que contiene numerosas especies endémicas, se necesita urgentemente una gestión proactiva para mitigar las crecientes presiones de la pesca, el cambio climático y el turismo. La conservación basada en el sitio es una herramienta importante para gestionar los efectos negativos de las actividades humanas en los ecosistemas. El Estándar de Áreas Clave para la Biodiversidad (ACB) es un marco estandarizado que se utiliza para definir lugares vitales para la persistencia de la biodiversidad mundial con base en criterios y umbrales cuantitativos. Usamos datos del seguimiento de 14 especies de aves marinas y pinnípedos antárticos y sub­antárticos del conjunto de datos públicos Retrospective Analysis of Antarctic Tracking Data (RAATD) para definir las ACB de un conjunto diverso de depredadores marinos. Utilizamos track2kba, un paquete de R que permite la identificación de ACB a partir de datos telemétricos mediante la identificación de áreas de hábitat altamente utilizadas y estimaciones de abundancia local dentro de los sitios. Comparamos las estimaciones de abundancia en cada lugar con los umbrales de los criterios A1, B1 y D1 de las ACB (relacionados con especies amenazadas a nivel mundial, especies individuales restringidas geográficamente y agregaciones demográficas, respectivamente). Identificamos 30 ACB potenciales para 13 especies distribuidas por todo el Océano Antártico que eran vitales para cada especie individual, población y etapa del ciclo biológico para las que se determinaron. Estas áreas fueron identificadas como muy utilizadas por estas poblaciones con base a datos observacionales y complementan el trabajo en curso de modelos del hábitat y biorregionalización que se ha utilizado para priorizar las áreas de conservación en esta región. Aunque es necesario seguir trabajando para identificar posibles ACB basadas en conjuntos de datos adicionales actuales y futuros, destacamos los beneficios de utilizar las ACB como parte de un enfoque holístico de la conservación marina, dado su importante valor como herramienta de conservación global.

Lévy Flight Model of Gaze Trajectories to Assist in ADHD Diagnoses.

The precise mathematical description of gaze patterns remains a topic of ongoing debate, impacting the practical analysis of eye-tracking data. In this context, we present evidence supporting the appropriateness of a Lévy flight description for eye-gaze trajectories, emphasizing its beneficial scale-invariant properties. Our study focuses on utilizing these properties to aid in diagnosing Attention-Deficit and Hyperactivity Disorder (ADHD) in children, in conjunction with standard cognitive tests. Using this method, we found that the distribution of the characteristic exponent of Lévy flights statistically is different in children with ADHD. Furthermore, we observed that these children deviate from a strategy that is considered optimal for searching processes, in contrast to non-ADHD children. We focused on the case where both eye-tracking data and data from a cognitive test are present and show that the study of gaze patterns in children with ADHD can help in identifying this condition. Since eye-tracking data can be gathered during cognitive tests without needing extra time-consuming specific tasks, we argue that it is in a prime position to provide assistance in the arduous task of diagnosing ADHD.

Connectivity between countries established by landbirds and raptors migrating along the African-Eurasian flyway.

The conservation of long-distance migratory birds requires coordination between the multiple countries connected by the movements of these species. The recent expansion of tracking studies is shedding new light on these movements, but much of this information is fragmented and inaccessible to conservation practitioners and policy makers. We synthesized current knowledge on the connectivity established between countries by landbirds and raptors migrating along the African-Eurasian flyway. We reviewed tracking studies to compile migration records for 1229 individual birds, from which we derived 544 migratory links, each link corresponding to a species' connection between a breeding country in Europe and a nonbreeding country in sub-Saharan Africa. We used these migratory links to analyze trends in knowledge over time and spatial patterns of connectivity per country (across species), per species (across countries), and at the flyway scale (across all countries and all species). The number of tracking studies available increased steadily since 2010 (particularly for landbirds), but the coverage of existing tracking data was highly incomplete. An average of 7.5% of migratory landbird species and 14.6% of raptor species were tracked per country. More data existed from central and western European countries, and it was biased toward larger bodied species. We provide species- and country-level syntheses of the migratory links we identified from the reviewed studies, involving 123 populations of 43 species, migrating between 28 European and 43 African countries. Several countries (e.g., Spain, Poland, Ethiopia, Democratic Republic of Congo) are strategic priorities for future tracking studies to complement existing data, particularly on landbirds. Despite the limitations in existing tracking data, our data and results can inform discussions under 2 key policy instruments at the flyway scale: the African-Eurasian Migratory Landbirds Action Plan and the Memorandum of Understanding on the Conservation of Migratory Birds of Prey in Africa and Eurasia.

Conectividad entre países establecida por aves terrestres y rapaces que migran a través del corredor aéreo africano-euroasiático Resumen La conservación de las aves que migran grandes distancias requiere de una coordinación entre los varios países conectados por los movimientos de estas especies. La expansión reciente de los estudios de rastreo está descubriendo novedades en estos movimientos, aunque gran parte de esta información está fragmentada y es inaccesible para quienes practican y elaboran las políticas de conservación. Sintetizamos el conocimiento actual sobre la conectividad establecida entre países por las aves terrestres y rapaces que migran a través del corredor aéreo africano-euroasiático. Revisamos los estudios de rastreo para compilar los registros migratorios de 1229 aves, de los cuales derivamos 544 conexiones migratorias, con cada conexión correspondiendo a la conexión que tiene una especie entre un país europeo en donde se reproduce con un país de la África subsahariana en donde no se reproduce. Usamos estas conexiones migratorias para analizar las tendencias informativas en patrones espaciales y temporales de conectividad por país (en todas las especies), por especie (en todos los países) y a escala del corredor aéreo (en todas las especies y en todos los países). El número de estudios de rastreo disponibles incrementó gradualmente a partir de 2010 (particularmente para las aves terrestres), pero la cobertura de los datos de rastreo existentes estaba incompleta. Se rastreó en promedio 7.5% de especies de aves terrestres migratorias y 14.6% de aves rapaces por país. Existían más datos de los países del centro y oeste de Europa, los cuales estaban sesgados hacia las especies de mayor tamaño. Proporcionamos varias síntesis a nivel de especie y país de las conexiones migratorias que identificamos a partir de la revisión de estudios, las cuales involucran a 123 poblaciones de 43 especies que migran entre 28 países europeos y 43 países africanos. Varios países, como España, Polonia, Etiopía y la República Democrática del Congo son prioridades estratégicas para complementar los datos existentes en los siguientes estudios de rastreo, en especial para las aves terrestres. A pesar de las limitaciones que tienen los datos de rastreo existentes, nuestros datos y resultados pueden orientar las discusiones con dos instrumentos claves para las políticas: el Plan de Acción de las Aves Terrestres Migratorias Africanas-Euroasiáticas y el Memorando de Entendimiento sobre la Conservación de las Aves Rapaces Migratorias de África y Eurasia.

A Re-evaluation of Online Pornography Use in Germany: A Combination of Web Tracking and Survey Data Analysis.

Several researchers have questioned the reliability of pornography research's findings. Following a recent call to use more reliable data sources, we conducted two analyses to investigate patterns and predictors of online pornography use (OPU). Our analyses were based on data from a large-scale German online web tracking panel (N = 3018) gathered from June 2018 to June 2019. The study we present here has two parts: In the first part, we looked at group differences (gender and age) in tracked OPU. Overall, this part's results confirm questionnaire-based research findings regarding sex and age differences. In the second part of our study, we combined the web tracking data with data from an online survey which was answered by a subset of the tracking participants (n = 1315) to assess the relevance of various predictors of OPU that have been identified in previous research. Again, our results mostly echoed previous findings based on self-reports. Online pornography was used more by males and younger individuals, while relationship status, sexist attitudes, and social dominance orientation were not associated with OPU. However, we did find differences in OPU between members of different religious communities. Our study confirms some critical findings on OPU from previous questionnaire-based research while extending existing research by providing a more fine-grained analysis of usage patterns based on web tracking data.

Attitude Towards Deposit Limits and Relationship with Their Account-Based Data Among a Sample of German Online Slots Players.

Social responsibility and duty of care have become major cornerstones for gambling operators. This has led to the introduction of many different responsible gambling tools such as limit-setting, mandatory play breaks, and personalized messaging. In the present study, the authors were given access to two secondary datasets provided by a German online slots game operator. The first dataset was from an online survey carried out by the gambling operator among 1000 of its players concerning their attitude towards deposit limits as well as self-reported problem gambling. In addition to the survey responses, the authors were given access to a second dataset of account-based data concerning each customer's wagers, wins, monetary deposits, and monetary withdrawals. These datasets were then combined. The majority of players had a positive attitude towards the maximum deposit monthly deposit limit which was introduced by the German State Treaty on Gambling in 2021. Players who disagreed with the maximum monthly deposit limit, deposited significantly more money in the 30 days prior to answering the survey questions compared to players who agreed with the monthly deposit limit. The tracking data found only 7.6% of players had deposited the maximum amount of money allowed in one month. However, 60.5% of players in the survey data said that they did so. Players who said that they continued to gamble after reaching the deposit limit wagered and deposited significantly more money in the 30 days prior to the survey compared to players who said they stopped gambling after reaching the deposit limit. Two-fifths of players said they continued to gamble after reaching the monthly deposit limit (42%). The majority of the players said they chose a personal deposit limit because it helped them to better control their gambling expenditure. A quarter of the players reported gambling problems using the Brief Biosocial Gambling Screen (27%). Self-reported problem gambling was not correlated with depositing, wagering or any other player tracking metric.

Estimating Player Positions from Padel High-Angle Videos: Accuracy Comparison of Recent Computer Vision Methods.

The estimation of player positions is key for performance analysis in sport. In this paper, we focus on image-based, single-angle, player position estimation in padel. Unlike tennis, the primary camera view in professional padel videos follows a de facto standard, consisting of a high-angle shot at about 7.6 m above the court floor. This camera angle reduces the occlusion impact of the mesh that stands over the glass walls, and offers a convenient view for judging the depth of the ball and the player positions and poses. We evaluate and compare the accuracy of state-of-the-art computer vision methods on a large set of images from both amateur videos and publicly available videos from the major international padel circuit. The methods we analyze include object detection, image segmentation and pose estimation techniques, all of them based on deep convolutional neural networks. We report accuracy and average precision with respect to manually-annotated video frames. The best results are obtained by top-down pose estimation methods, which offer a detection rate of 99.8% and a RMSE below 5 and 12 cm for horizontal/vertical court-space coordinates (deviations from predicted and ground-truth player positions). These results demonstrate the suitability of pose estimation methods based on deep convolutional neural networks for estimating player positions from single-angle padel videos. Immediate applications of this work include the player and team analysis of the large collection of publicly available videos from international circuits, as well as an inexpensive method to get player positional data in amateur padel clubs.

Automatic Visual Attention Detection for Mobile Eye Tracking Using Pre-Trained Computer Vision Models and Human Gaze.

Processing visual stimuli in a scene is essential for the human brain to make situation-aware decisions. These stimuli, which are prevalent subjects of diagnostic eye tracking studies, are commonly encoded as rectangular areas of interest (AOIs) per frame. Because it is a tedious manual annotation task, the automatic detection and annotation of visual attention to AOIs can accelerate and objectify eye tracking research, in particular for mobile eye tracking with egocentric video feeds. In this work, we implement two methods to automatically detect visual attention to AOIs using pre-trained deep learning models for image classification and object detection. Furthermore, we develop an evaluation framework based on the VISUS dataset and well-known performance metrics from the field of activity recognition. We systematically evaluate our methods within this framework, discuss potentials and limitations, and propose ways to improve the performance of future automatic visual attention detection methods.

The "Hockey" Assist Makes the Difference-Validation of a Defensive Disruptiveness Model to Evaluate Passing Sequences in Elite Soccer.

With the growing availability of position data in sports, spatiotemporal analysis in soccer is a topic of rising interest. The aim of this study is to validate a performance indicator, namely D-Def, measuring passing effectiveness. D-Def calculates the change of the teams' centroid, centroids of formation lines (e.g., defensive line), teams' surface area, and teams' spread in the following three seconds after a pass and therefore results in a measure of disruption of the opponents' defense following a pass. While this measure was introduced earlier, in this study we aim to prove the usefulness to evaluate attacking sequences. In this study, 258 games of Dutch Eredivisie season 2018/19 were included, resulting in 13,094 attacks. D-Def, pass length, pass velocity, and pass angle of the last four passes of each attack were calculated and compared between successful and unsuccessful attacks. D-Def showed higher values for passes of successful compared to unsuccessful attacks (0.001 < p ≤ 0.029, 0.06 ≤ d ≤ 0.23). This difference showed the highest effects sizes in the penultimate pass (d = 0.23) and the maximal D-Def value of an attack (d = 0.23). Passing length (0.001 < p ≤ 0.236, 0.08 ≤ d ≤ 0.17) and passing velocity (0.001 < p ≤ 0.690, -0.09 ≤ d ≤ 0.12) showed inconsistent results in discriminating between successful and unsuccessful attacks. The results indicate that D-Def is a useful indicator for the measurement of pass effectiveness in attacking sequences, highlighting that successful attacks are connected to disruptive passing. Within successful attacks, at least one high disruptive action (pass with D-Def > 28) needs to be present. In addition, the penultimate pass ("hockey assist") of an attack seems crucial in characterizing successful attacks.

Navigating through the r packages for movement.

The advent of miniaturized biologging devices has provided ecologists with unprecedented opportunities to record animal movement across scales, and led to the collection of ever-increasing quantities of tracking data. In parallel, sophisticated tools have been developed to process, visualize and analyse tracking data; however, many of these tools have proliferated in isolation, making it challenging for users to select the most appropriate method for the question in hand. Indeed, within the r software alone, we listed 58 packages created to deal with tracking data or 'tracking packages'. Here, we reviewed and described each tracking package based on a workflow centred around tracking data (i.e. spatio-temporal locations (x, y, t)), broken down into three stages: pre-processing, post-processing and analysis, the latter consisting of data visualization, track description, path reconstruction, behavioural pattern identification, space use characterization, trajectory simulation and others. Supporting documentation is key to render a package accessible for users. Based on a user survey, we reviewed the quality of packages' documentation and identified 11 packages with good or excellent documentation. Links between packages were assessed through a network graph analysis. Although a large group of packages showed some degree of connectivity (either depending on functions or suggesting the use of another tracking package), one third of the packages worked in isolation, reflecting a fragmentation in the r movement-ecology programming community. Finally, we provide recommendations for users when choosing packages, and for developers to maximize the usefulness of their contribution and strengthen the links within the programming community.

Modeling Early Gambling Behavior Using Indicators from Online Lottery Gambling Tracking Data: Longitudinal Analysis.

BACKGROUND: Individuals who gamble online may be at risk of gambling excessively, but internet gambling also provides a unique opportunity to monitor gambling behavior in real environments which may allow intervention for those who encounter difficulties. OBJECTIVE: The objective of this study was to model the early gambling trajectories of individuals who play online lottery. METHODS: Anonymized gambling-related records of the initial 6 months of 1152 clients of the French national lottery who created their internet gambling accounts between September 2015 and February 2016 were analyzed using a two-step approach that combined growth mixture modeling and latent class analysis. The analysis was based upon behavior indicators of gambling activity (money wagered and number of gambling days) and indicators of gambling problems (breadth of involvement and chasing). Profiles were described based upon the probabilities of following the trajectories that were identified for the four indicators, and upon several covariates (age, gender, deposits, type of play, net losses, voluntary self-exclusion, and Playscan classification-a responsible gambling tool that provides each player with a risk assessment: green for low risk, orange for medium risk and red for high risk). Net losses, voluntary self-exclusion, and Playscan classification were used as external verification of problem gambling. RESULTS: We identified 5 distinct profiles of online lottery gambling. Classes 1 (56.8%), 2 (14.8%) and 3 (13.9%) were characterized by low to medium gambling activity and low values for markers of problem gambling. They displayed low net losses, did not use the voluntary self-exclusion measure, and were classified predominantly with green Playscan tags (range 90%-98%). Class 4 (9.7%) was characterized by medium to high gambling activity, played a higher breadth of game types (range 1-6), and had zero to few chasing episodes. They had high net losses but were classified with green (66%) or orange (25%) Playscan tags and did not use the voluntary self-exclusion measure. Class 5 (4.8%) was characterized by medium to very high gambling activity, played a higher breadth of game types (range 1-17), and had a high number of chasing episodes (range 0-5). They experienced the highest net losses, the highest proportion of orange (32%) and red (39%) tags within the Playscan classification system and represented the only class in which voluntary self-exclusion was present. CONCLUSIONS: Classes 1, 2, 3 may be considered to represent recreational gambling. Class 4 had higher gambling activity and higher breadth of involvement and may be representative of players at risk for future gambling problems. Class 5 stood out in terms of much higher gambling activity and breadth of involvement, and the presence of chasing behavior. Individuals in classes 4 and 5 may benefit from early preventive measures.

The importance of sample size in marine megafauna tagging studies.

Telemetry is a key, widely used tool to understand marine megafauna distribution, habitat use, behavior, and physiology; however, a critical question remains: "How many animals should be tracked to acquire meaningful data sets?" This question has wide-ranging implications including considerations of statistical power, animal ethics, logistics, and cost. While power analyses can inform sample sizes needed for statistical significance, they require some initial data inputs that are often unavailable. To inform the planning of telemetry and biologging studies of marine megafauna where few or no data are available or where resources are limited, we reviewed the types of information that have been obtained in previously published studies using different sample sizes. We considered sample sizes from one to >100 individuals and synthesized empirical findings, detailing the information that can be gathered with increasing sample sizes. We complement this review with simulations, using real data, to show the impact of sample size when trying to address various research questions in movement ecology of marine megafauna. We also highlight the value of collaborative, synthetic studies to enhance sample sizes and broaden the range, scale, and scope of questions that can be answered.

Prediction of the service life of surgical instruments from the surgical instrument management system log using radio frequency identification.

BACKGROUND: Bar code- or radio frequency identification (RFID)-based medical instrument management systems have gradually been introduced in the field of surgical medicine for the individual management and identification of instruments. We hypothesized that individual management of instruments using RFID tags can provide previously unavailable information, particularly the precise service life of an instrument. Such information can be used to prevent medical accidents caused by surgical instrument failure. This study aimed to predict the precise service life of instruments by analyzing the data available in instrument management systems. METHODS: We evaluated the repair history of instruments and the usage count until failure and then analyzed the data by the following three methods: the distribution of the instrument usage count was determined, an instrument failure probability model was generated through logistic regression analysis, and survival analysis was performed to predict instrument failure. RESULTS: The usage count followed a normal distribution. Analysis showed that instruments were not used uniformly during surgery. In addition, the Kaplan-Meier curves plotted for five types of instruments showed significant differences in the cumulative survival rate of different instruments. CONCLUSIONS: The usage history of instruments obtained with RFID tags or bar codes can be used to predict the probability of instrument failure. This prediction is significant for determining the service life of an instrument. Implementation of the developed model in instrument management systems can help prevent accidents due to instrument failure. Knowledge of the instrument service life will also help in developing a purchase plan for instruments to minimize wastage.

High-throughput behavioral assay to investigate seizure sensitivity in zebrafish implicates ZFHX3 in epilepsy.

Epilepsy, which affects ∼1% of the population, is caused by abnormal synchronous neural activity in the central nervous system (CNS). While there is a significant genetic contribution to epilepsy, the underlying causes for the majority of genetic cases remain unknown. The NIH Undiagnosed Diseases Project (UDP) utilized exome sequencing to identify genetic variants in patients affected by various conditions with undefined etiology, including epilepsy. Confirming the functional relevance of the candidate genes identified by exome sequencing in a timely manner is crucial to translating exome data into clinically useful information. To this end, we developed a high throughput version of a seizure-sensitivity assay in zebrafish (Danio rerio) to rapidly evaluate candidate genes found by exome sequencing. We developed open access software, Studying Epilepsy In Zebrafish using R (SEIZR), to efficiently analyze the data. SEIZR was validated by disrupting function of a known epilepsy gene, prickle 1. Next, using SEIZR, we analyzed a candidate gene from the UDP screen (Zinc Finger Homeobox 3, ZFHX3), and showed that reduced ZFHX3 function in zebrafish results in a significant hyperactive response to the convulsant drug pentylenetetrazol (PTZ). We find that ZFHX3 shows strong expression in the CNS during neurogenesis including in the pallium, thalamus, tegmentum, reticular formation, and medulla oblongata - all regions which have roles in motor control and coordination. Our findings in the zebrafish confirm human ZFHX3 is a strong candidate for further neurological studies. We offer SEIZR to other researchers as a tool to rapidly and efficiently analyze large behavioral data sets.

Correcting for missing and irregular data in home-range estimation.

Home-range estimation is an important application of animal tracking data that is frequently complicated by autocorrelation, sampling irregularity, and small effective sample sizes. We introduce a novel, optimal weighting method that accounts for temporal sampling bias in autocorrelated tracking data. This method corrects for irregular and missing data, such that oversampled times are downweighted and undersampled times are upweighted to minimize error in the home-range estimate. We also introduce computationally efficient algorithms that make this method feasible with large data sets. Generally speaking, there are three situations where weight optimization improves the accuracy of home-range estimates: with marine data, where the sampling schedule is highly irregular, with duty cycled data, where the sampling schedule changes during the observation period, and when a small number of home-range crossings are observed, making the beginning and end times more independent and informative than the intermediate times. Using both simulated data and empirical examples including reef manta ray, Mongolian gazelle, and African buffalo, optimal weighting is shown to reduce the error and increase the spatial resolution of home-range estimates. With a conveniently packaged and computationally efficient software implementation, this method broadens the array of data sets with which accurate space-use assessments can be made.

A shot taxonomy in the era of tracking data in professional tennis.

Shots are an essential part of the language of tennis yet little is known about the distinct types of shots in the professional game. In this study, we build a taxonomy of shots for elite tennis players using tracking data from multiple years of men's and women's matches at the Australian Open. Our taxonomy is constructed using model-based multi-stage functional data clustering, an unsupervised machine learning approach. Among 270,023 men's and 178,136 women's shots, we found 13 distinct types of serves to both the Ad and Deuce court for male players and 17 and 15 types to the Ad and Deuce for female players. More variety was found among serve returns and rally shots compared to the serve; with less variety on the backhand than forehand. There was also more overlap in the physical characteristics of groundstroke shots between male and female players than on serve. Shot type was strongly associated with winning points and shots in the highest speed and lowest net clearance categories tended to be the most effective. This data-driven dictionary of shots provides a framework for analysis of elite player performance, characterizing playing style, and designing more representative practice.

The Relationship Between Structural Game Characteristics and Gambling Behavior: A Population-Level Study.

The aim of this study was to examine the relationship between the structural characteristics and gambling behavior among video lottery terminal (VLT) gamblers. The study was ecological valid, because the data consisted of actual gambling behavior registered in the participants natural gambling environment without intrusion by researchers. Online behavioral tracking data from Multix, an eight game video lottery terminal, were supplied by Norsk-Tipping (the state owned gambling company in Norway). The sample comprised the entire population of Multix gamblers (N = 31,109) who had gambled in January 2010. The individual number of bets made across games was defined as the dependent variable, reward characteristics of a game (i.e., payback percentage, hit frequency, size of winnings and size of jackpot) and bet characteristics of a game (i.e., range of betting options and availability of advanced betting options) served as the independent variables. Control variables were age and gender. Two separate cross-classified multilevel random intercepts models were used to analyze the relationship between bets made, reward characteristics and bet characteristics, where the number of bets was nested within both individuals and within games. The results show that the number of bets is positively associated with payback percentage, hit frequency, being female and age, and negatively associated with size of wins and range of available betting options. In summary, the results show that the reward characteristics and betting options explained 27% and 15% of the variance in the number of bets made, respectively. It is concluded that structural game characteristics affect gambling behavior. Implications of responsible gambling are discussed.

Understanding the potential of taxi sharing: The case of Chengdu.

The emergence of taxi sharing enhances urban transport efficiency and reduces carbon emissions. Using GPS tracking data from taxis in Chengdu, China, this study first outlines conditions for identifying shareable taxi orders based on their origins and destinations. We then develop a three-phase computational model to optimize matches among all potential shareable orders, calculating the shareable mileage and the proportion of original mileage that could be shared. Our comprehensive temporal and spatial analysis reveal a significant market for taxi sharing in Chengdu, with higher potential on workdays than non-workdays and four distinct demand peaks throughout the day. The morning peak on workdays and the night peak on non-workdays are particularly pronounced. Most shareable orders originate within major city districts. We find a positive correlation between the potential of taxi sharing and average traffic speed, and negative correlations with order volume, regional economic development, and population density. Functional zones related to Enterprises, Motorcycle Services, and Transportation Services exhibit significantly higher sharing potential. Compared to traditional taxi operations, taxi sharing significantly reduces total travel mileage. This quantitative analysis offers insights into the potential demand for taxi sharing among urban residents and may help government authorities optimize taxi resources for the sustainable development of urban transport.

Geometric framework for statistical analysis of eye tracking heat maps, with application to a tobacco waterpipe study.

Health warning labels have been found to increase awareness of the harmful effects of tobacco products. An eye tracking study was conducted to determine the optimal placement and type of a health warning label on tobacco waterpipes. Participants viewed images that contained one of (1) four waterpipes, (2) three different types of warning labels, (3) placed in three locations. Typically, statistical analysis of eye tracking data is conducted based on summary statistics such as total dwell time, duration score, and number of visits to an area of interest. However, these summary statistics fail to capture the complete variability in a participant's eye movement. Instead, we propose to estimate heat maps defined on the entire image domain using the raw two-dimensional coordinates of eye movement via kernel density estimation. For statistical analysis of heat maps, we adopt the Fisher-Rao Riemannian geometric framework, which enables computationally efficient comparisons of heat maps, statistical summarization and exploration of variability in a sample of heat maps, and metric-based hierarchical clustering. We apply this framework to eye tracking data from the tobacco waterpipe study and comment on the results in the context of the optimal placement and type of health warning labels on tobacco waterpipes.