Movement Patterns Research Articles

A wavelength analyzer using laser self-mixing interferometry

In this paper, we propose a simple yet effective method to measure the operating wavelength of a laser using laser self-mixing interferometry (SMI). Analyzing the self-mixing interference signals acquired from external objects with known motion patterns allows us to deduce the laser's operating wavelength. To validate the accuracy of our method further, we constructed a laser self-mixing linear motion sensing system. This system captured the self-mixing interference signals generated as external targets moved at a uniform linear velocity under various laser wavelengths. By conducting FFT analysis, we obtained the signal frequency, which was then converted from laser Doppler frequency to optical frequency, ultimately determining the laser's wavelength. Our experiment specifically focused on analyzing the impact of frequency doubling on the results, discussing its causes and potential solutions. Numerical analysis indicates that the laser's working wavelength parameter is precisely measured from external targets moving at a uniform speed of 0.4 to 2.4 mm/s. Additionally, the experimental results show a absolute error of less than 1.230 nm and an relative error of less than 0.12 %. In conclusion, our experimental, simulation, and theoretical analysis results mutually validate each other, confirming the accuracy and practicality of the measurement method.

Determining the coordinates of unmanned aerial vehicles

The purpose of the work was to develop a method for determining unmanned aerial vehicles’ (UAVs) coordinates, trajectory and parameters of their spatial movements by means of kinematic projection. The paper analyses the use of technologies for determining coordinates and spatial movements of aircraft trajectories. The principle of the kinematic scheme of fixing moving objects by means of orthogonal and kinematic design has been developed. The principle scheme of determining UAV coordinates by kinematic projection was studied. The theoretical mathematical dependencies of the determination and calculations of the coordinates of spatial movements of unmanned aerial vehicles have been practically verified. The main object of research in this work was the theory of kinematic design as a means of graphically displaying the patterns of spatial movements of objects. The subject of the study was the specific features of searching and recording the trajectories of spatial movements of unmanned aerial vehicles in order to determine the coordinates of their instantaneous location in space. In the process of conducting theoretical and experimental research, methods and techniques of physical and mathematical modelling of fast-moving processes and mathematical statistics of analysis and classification of their results were used. The basis of the experimental study was the theory of mapping coordinates and trajectories of spatial movements of moving objects by means of graphic geometry when combining classical orthogonal design with dynamic features of kinematic design. For an objective assessment of the results of the theoretical and experimental study of the dynamics of objects moving in space, the classical theory of research planning with a mathematical apparatus for processing their results was used. Graphical models of UAV coordinate fixation were made with the use of computer technology and the AutoCAD graphic editor software.

A multi-agent motion simulation method for emergency scenario deduction

Simulating crowd motion in emergency scenarios remains a challenge in computer graphics due to crowd heterogeneity and environmental complexity. However, existing crowd simulation methods homogenize the agent model and simplify target selection and motion navigation of emergency crowds. To address these problems, we propose a multi-agent motion simulation method for emergency scenario deduction. First, we propose a multi-agent model to simulate crowd heterogeneity. This model includes a personality-based heterogeneous agent model and an agent perception model that considers vision, hearing, and familiarity with the environment. Second, we propose a target selection strategy based on the motion patterns of actual pedestrians. This strategy employs mathematical models and our agent perception model to guide agents in selecting appropriate targets. Finally, we propose a global navigation algorithm that combines random sampling with heuristic search methods. Concurrently, we use our multi-agent model to adjust the agent’s local motion planning to deduce the motion states of emergency crowds naturally. Experimental results validate that our method can realistically and reasonably simulate crowd motion in emergency scenarios.

Psychometric properties of the modified reaching performance scale in persons with multiple sclerosis

BackgroundA valid and reliable assessment tool to describe the quality of the movement pattern of reaching can provide valuable insights into motor performance deficits in persons with MS (pwMS). The Reaching Performance Scale, developed for stroke, is a promising scale to assess movement patterns in pwMS. However, psychometric properties of the scale are lacking in pwMS. ObjectivesFirstly, to investigate the content validity of the modified Reaching Performance Scale for application in patients with MS (mRPS). Secondly, to investigate the psychometric properties (within- and between-session reliability and concurrent validity) of the mRPS for pwMS. MethodsForty-five pwMS (mean EDSS 6.6 pt, IQR 6–7.5) executed the mRPS that rates the quality of movement patterns and compensations during reach to grasp tasks. The content validity was determined by an expert panel based on observations of subjects performing the RPS. The reliability was based on five repetitions within one day, and between two days. For the concurrent validity, outcome measures at two levels of the International Classification of Functioning were correlated with the mRPS: Body Structure and Function level: Fugl-Meyer Assessment of the Upper Limb (FMA-UL), maximal isometric hand grip strength (HGS; Activity level: Action Research Arm Test (ARAT), Box and Blocks Test (BBT), Nine Hole Peg Test (NHPT) and Trunk Impairment Scale 2.0 (TIS 2.0) as well as perceived performance by the Manual Ability Measure-36 (MAM-36). ResultsScale modifications were made only on the ratings of the trunk displacement subscale. The mRPS had excellent agreement scores for within-session reliability (range of Kappa between 0.85 and 0.98) and moderate-to-excellent agreement scores for between-session reliability (K: 0.66–1.00). Regarding validity, the mRPS was highly correlated with the ARAT (rho=0.74, p < 0.001), followed by moderate correlations with trunk performance (TIS 2.0, rho= 0.61, p < 0.001), hand function (BBT: rho=0.64, p < 0.001; NHPT: rho=-0.61, p < 0.001) and perceived performance (MAM36 rho= 0.53, p < 0.001). ConclusionThe mRPS is a reliable measurement tool to describe the movement pattern quality and motor compensations used during reaching in pwMS. Concerning concurrent validity, the mRPS is partially related to other measures of upper limb and trunk performance.

Long-term co-occurrence and gregariousness in the migratory common stingray using network analysis

Aggregations and social interactions play an important role in the movement ecology of many animals, including elasmobranchs. Several of these species have shown the capability of carrying out complex social behaviours, and the importance of sociality in this taxon is being realized. Although it is a growing field of study in the case of these organisms, these processes still need to be better understood, especially to support management and conservation policies. In this study, a long-term acoustic telemetry data set collected on Dasyatis pastinaca in a coastal marine protected area was analysed. A co-occurrence network analysis was done to investigate preferential associations among individuals, revealing non-random associations among them. The analysis revealed a few strong and consistent associations that were maintained across inter-migratory periods, as this species performs seasonal migrations to a nearby estuary, suggesting temporal stability of the observed associations. Moreover, individuals had similar average positions and a generally high overlap of space use in both periods, indicating some level of site fidelity to the fully protected area. Groups of up to 64% of tagged individuals were co-detected at a same receiver, particularly in the western side of the array. Despite our limited sample size, likely underestimating associations, these results show that in addition to their large-scale movement pattern, D. pastinaca is likely to also present active partner preference and spatial structure at a finer spatial scale. The nature of such results is relevant to support the protection of these species.

Mussels with luggage: the influence of artificially attached “backpack” devices on mussel movement behavior

BackgroundFreshwater mussels are important keystone and indicator species of aquatic ecosystems. Recent advances in sensor technology facilitate applications to individually track mussels and to record and monitor their behavior and physiology. These approaches require the attachment of sensor devices as “backpacks” to the outer shell surface. The interpretation of such data makes it necessary to understand the influence of these attachments on the horizontal and vertical movement behaviors of freshwater mussels. Over a series of mesocosm experiments, this study systematically investigated the effects of three size- and wiring-specific variants of artificially attached backpacks on the horizontal and vertical movement behavior of Anodonta anatina.ResultsAcross all experiments, equipping mussels with backpacks did not result in a significant influence on horizontal movement for any of the backpack variants. In contrast to this finding, the big backpacks with a high ratio between backpack volume and mussel length resulted in a significantly negative effect on vertical movement, indicating a potential for adverse effects of such devices on mussels, especially in natural settings.ConclusionsThe findings of this study show that assessing the effects of attached devices on mussels requires a species-specific evaluation of potential impacts on the endpoints of interest. Especially for vertical movement patterns, selection of the smallest available devices appears mandatory.

Utilizing machine learning to analyze trunk movement patterns in women with postpartum low back pain

This paper presents an analysis of trunk movement in women with postnatal low back pain using machine learning techniques. The study aims to identify the most important features related to low back pain and to develop accurate models for predicting low back pain. Machine learning approaches showed promise for analyzing biomechanical factors related to postnatal low back pain (LBP). This study applied regression and classification algorithms to the trunk movement proposed dataset from 100 postpartum women, 50 with LBP and 50 without. The Optimized optuna Regressor achieved the best regression performance with a mean squared error (MSE) of 0.000273, mean absolute error (MAE) of 0.0039, and R2 score of 0.9968. In classification, the Basic CNN and Random Forest Classifier both attained near-perfect accuracy of 1.0, the area under the receiver operating characteristic curve (AUC) of 1.0, precision of 1.0, recall of 1.0, and F1-score of 1.0, outperforming other models. Key predictive features included pain (correlation of -0.732 with flexion range of motion), range of motion measures (flexion and extension correlation of 0.662), and average movements (correlation of 0.957 with flexion). Feature selection consistently identified pain, flexion, extension, lateral flexion, and average movement as influential across methods. While limited to this initial dataset and constrained by generalizability, machine learning offered quantitative insight. Models accurately regressed (MSE < 0.01, R2 > 0.95) and classified (accuracy > 0.94) trunk biomechanics distinguishing LBP. Incorporating additional demographic, clinical, and patient-reported factors may enhance individualized risk prediction and treatment personalization. This preliminary application of advanced analytics supported machine learning's potential utility for both LBP risk determination and outcome improvement. This study provides valuable insights into the use of machine learning techniques for analyzing trunk movement in women with postnatal low back pain and can potentially inform the development of more effective treatments.Trial registration: The trial was designed as an observational and cross-section study. The study was approved by the Ethical Committee in Deraya University, Faculty of Pharmacy, (No: 10/2023). According to the ethical standards of the Declaration of Helsinki. This study complies with the principles of human research. Each patient signed a written consent form after being given a thorough description of the trial. The study was conducted at the outpatient clinic from February 2023 till June 30, 2023.

Machine learning-based bee recognition and tracking for advancing insect behavior research

The study of insect behavior, particularly that of honey bees, has a broad scope and significance. Tracking bee flying patterns grants much helpful information about bee behavior. However, tracking a small yet fast-moving object, such as a bee, is difficult. Hence, we present artificial intelligence, machine-learning-based bee recognition, and tracking systems to assist the researcher in studying the bee’s behavior. To develop a machine learning system, a labeled database is required for model training. To address this, we implemented an automated system for analyzing and labeling bee videos. This labeled database served as the foundation for two distinct bee-tracking solutions. The first solution (planar bee tracking system) tracked individual bees in closed mazes using a neural network. The second solution (spatial bee tracking system) utilized a neural network and a tracking algorithm to identify and track flying bees in open environments. Both systems tackle the challenge of tracking small-bodied creatures with rapid and diverse movement patterns. Although we applied these systems to entomological cognition research in this paper, their relevance extends to general insect research and developing tracking solutions for small organisms with swift movements. We present the complete architecture and detailed methodologies to facilitate the utilization of these models in future research endeavors. Our approach is a simple and inexpensive method that contributes to the growing number of image-analysis tools used for tracking animal movement, with future potential applications under less sterile field conditions. The tools presented in this paper could assist the study of movement ecology, specifically in insects, by providing accurate movement specifications. Following the movement of pollinators or natural enemies, for example, greatly contributes to the study of pollination or biological control, respectively, in natural and agro-ecosystems.

РАЗРАБОТКА МОБИЛЬНОГО КОЛЕСНОГО РОБОТА ДЛЯ ДОСТАВКИ ПОСЫЛОК

The study objective is to develop approaches to the design of a mobile wheeled robot for transporting small-sized goods, operating autonomously without the participation of a human operator. At the same time, the main task is to develop a mathematical model of a wheeled robot that takes into account the moments of rolling friction and sliding of the driving wheels on the support surface, and which allows to study the starting operation modes of the electromechanical drive of a mobile device. The increase in the speed of the mobile robot is achieved by minimizing the acceleration time to the required speed values through the use of a 2-stage algorithm for changing the control voltage. The development of a mathematical model of a robotic system is carried out on the basis of methods of analytical mechanics and the theory of automatic control. Using the Laplace transforms, an analytical solution of differential equations describing the dynamics of a mobile robot is obtained. Numerical solution of the obtained equations is carried out in Mathcad interface. The novelty of the work consists in obtaining time dependencies for the speed and current in the circuit of the electric motor of the mobile robot wheeled drive and finding out the basic patterns of movement at its launch. The results of the conducted research can be used in the development of motion control systems for mobile robots with feedback, ensuring the stabilization of a set value of the movement speed in steady-state modes. Conclusions: a mathematical model of a mobile robotic system is developed, the starting modes of its operation and the method of combined motion control are studied, the speed of a mobile wheeled device is increased when moving along a given trajectory.

Visual analysis of oceanic data for marine ecosystems

We present a data visualization approach that allows users to interactively analyse sequential movement patterns and automatically extract rules for marine animal behaviour. This enhances the ability of oceanic experts to understand marine ecosystems. Traditional time-series analysis, basic statistical methods, and single-view visualizations often fail to capture the intricate spatial and temporal dynamics of marine ecosystems. Our visual analytics approach, that leverages sequential pattern mining and rule mining techniques, integrates SPMF's Vertical Mining of Maximal Sequential Patterns (VMSP) algorithm and T-Rule Growth algorithm to efficiently extract and visualize movement patterns and behavioural rules of marine animals. The system also incorporates automated pre-processing to clean and prepare large datasets, reducing the time and effort required for manual handling. The visualization presents oceanic data from detection stations, allowing researchers to discover patterns in the movements of marine species. Our interface also provides geographical visualization of selected patterns or rules and helps users to navigate and find the relevant information. Key principles of our model include multi-view visualizations that provide comprehensive insights by displaying data from various perspectives simultaneously, and geo-spatial time-varying data visualization that captures and represents the dynamic movements of marine species. This approach allows domain experts to interactively explore and analyse sequential patterns and rules, enhancing their ability to make informed decisions. Additionally, feedback received, and insights gained from specialized professionals was used to determine if this approach would be a beneficial complement to existing practice.

Commuting-driven competition between transmission chains shapes seasonal influenza virus epidemics in the United States.

Despite intensive study, much remains unknown about the dynamics of seasonal influenza virus epidemic establishment and spread in the United States (US) each season. By reconstructing transmission lineages from seasonal influenza virus genomes collected in the US from 2014 to 2023, we show that most epidemics consisted of multiple distinct transmission lineages. Spread of these lineages exhibited strong spatiotemporal hierarchies and lineage size was correlated with timing of lineage establishment in the US. Mechanistic epidemic simulations suggest that mobility-driven competition between lineages determined the extent of individual lineages' geographical spread. Based on phylogeographic analyses and epidemic simulations, lineage-specific movement patterns were dominated by human commuting behavior. These results suggest that given the locations of early-season epidemic sparks, the topology of inter-state human mobility yields repeatable patterns of which influenza viruses will circulate where, but the importance of short-term processes limits predictability of regional and national epidemics.

Adherence to Short-Duration Treatment (3HP) for Latent Tuberculosis among International Migrants in Manaus, Amazonas: Evaluation of the Efficacy of Different Treatment Modalities.

Migration, a multifaceted phenomenon, has a significant impact on health. Migrants perform similar movement patterns within their country of origin, in transit, and in the country of destination, thus making it difficult to monitor TB treatment throughout the journey. The objective was to compare the effectiveness of different treatment modalities in adherence to the short-term regimen for LTBI (3HP) among international migrants and refugees. This is a quasi-experimental study conducted in Manaus-AM. The study population was made up of international migrants. The certification and monitoring of medication intake employed three strategies: self-administration (SA), directly observed conventional therapy (DOT), and Video Telemonitoring System for Tuberculosis Treatment (VDOT). The VDOT group and SA group exhibited the lowest rate of treatment dropout or interruption at 16.1%, followed by the DOT group at 23.1%. The results suggest that the most effective strategy for ensuring adherence among migrants and refugees was VDOT (OR_adj 0.26; CI 0.7-0.94), suggesting that migrants may be more likely to adhere to and complete their treatment. The results show that relying on different treatment strategies, adapted to the individuals' needs and risk factors, is a viable and effective way of providing person-centered TB care.

Investigating Expert-Rater Agreement and Inter/Intra-Rater Reliability of Two Fundamental Movement Skills for the Locomotor Subscale of the FG-COMPASS.

The Furtado-Gallagher Children Observational Movement Pattern Assessment System (FG-COMPASS) is an observational tool using sequential decisions to assess fundamental movement skill proficiency. The current version of the test has three locomotor and five manipulative skills. Adding two more locomotor skills to the assessment tool enriches its scope, enabling a more comprehensive and nuanced evaluation of individual movement skills. We assessed expert-non-expert rater agreement and inter/intra non-expert rater reliability of two new scales for the locomotor subscale. We divided this study into two parts. In Part I, we filmed 60 children aged 5-10years old who performed gallop and vertical jump skills. A motor behavior expert then classified the videotapes using our newly created rating scales. Next, we selected eight videos for training purposes and 24 videos for testing purposes. In Part II, 30 undergraduate students underwent rater training. Rating data were analyzed using weighted kappa (Kw) and the intra-class correlation coefficient (ICC), and these indices showed 'very good' agreement between the expert and the non-expert raters for vertical jump (Kw = .96) and gallop (Kw = .89). The ICC expert to non-expert rater values for vertical jump and gallop were .98 and .94, respectively; and mean kappa values for inter-rater reliability between non-experts were considered 'very good' for vertical jump (MKw = .92) and 'good' for gallop (MKw = .78). The ICC inter-rater values were .98 and .95 (considered 'excellent') for vertical jump and gallop, respectively; and the kappa intra-rater values were .96 and .85, respectively, with intra-rater ICC values .98 and .92. Thus, the proposed rating scales were reliable for assessing vertical jump and gallop. Future studies should focus on criterion-related validity and reliability evidence from live performances.

The movement pattern changes of population following a disaster: Example of the Aegean Sea earthquake of October 2020

Unexpected seismic events can have a significant impact on our daily lives. Examining post-disaster population movement patterns contributes to disaster response and recovery operations. While most studies analyze population movement or displacement data, only a few examine multi-level movement patterns and consider public transportation demand. This paper aims to analyze changes in movement patterns following a major earthquake that severely affected İzmir in Türkiye, mainly using movement data from the Data for Good platform of Meta. According to the findings, on the first day following the earthquake, those traveling within İzmir considered the areas least damaged to be safer, despite the higher seismic intensity. The timeframe alignment between aftershock activity and the number of people traveling within İzmir suggests the routine movement pattern within the city was regained as the aftershocks decreased day by day. Unlike intra-city travel routines, there was an increase in the number of people moving to summer houses, located far from the center of İzmir. By November 2, 2020, three days after the earthquake, intra-city movements reached a new normal, as confirmed by public transportation use. However, intra-city travel patterns were impacted for approximately one month. This study reveals key findings from the evaluation of post-earthquake movements to improve disaster management decision making and aid crisis response and recovery operations.

Development of a cloud-based IoT system for livestock health monitoring using AWS and python

The agriculture industry is currently facing significant challenges in effectively monitoring the health of livestock. Traditional methods of health monitoring are often labor-intensive, inefficient, and insufficiently responsive to the needs of modern farming. As the number of IoT devices in agriculture proliferates, issues of scalability and computational load have become prominent, necessitating efficient and scalable solutions. This research introduces a cloud-based architecture aimed at enhancing livestock health monitoring. This system is designed to track critical health indicators such as movement patterns, body temperature, and heart rate, utilizing AWS for robust data handling and Python for data processing and real-time analytics. The proposed system incorporates Narrow Band IoT (Nb IoT) technology, which is optimized for low-bandwidth, long-range communication, making it suitable for rural and remote farming locations. The architecture's scalability allows for the effective management of varying numbers of IoT devices, which is essential for adapting to changing herd sizes and farm scales. Preliminary experiments conducted to assess the system's performance have demonstrated its durability and effectiveness, indicating a successful integration of AWS IoT Cloud services with the deployed IoT devices. Furthermore, the study explores the implementation of predictive analytics to facilitate proactive health management in livestock. By predicting potential health issues before they become apparent, the system can offer significant improvements in animal welfare and farm efficiency. The integration of cloud computing and IoT not only meets the growing technological needs of modern agriculture but also sets a new benchmark in the development of sustainable farming practices. The findings from this research could have broad implications for the future of livestock management, potentially leading to widespread adoption of technology-driven health monitoring systems in agriculture. This would help in optimizing the health management of livestock globally, thereby enhancing productivity and sustainability in the agricultural sector.

Development of a pump-jet piezoelectric swimmer with acoustic radiation actuation

The acoustofluidic actuation produced by piezoelectric transducer is capable of propelling micro underwater robots forward, yet the motion pattern is relatively simplistic. To solve this problem, a pump-jet swimmer with a combination of the underwater acoustic radiation effect is proposed in this work. The absorption and discharge of internal piezoelectric pump provide the linear forward power, and turning is achieved under the acoustic propulsive force of the external dual piezoelectric actuators. The working mode and optimal driving frequency of the piezoelectric actuators are determined through finite element simulation and mechanical vibration characteristic tests. And the key dimensional parameters of the piezoelectric pump are optimized in the light of the output flow measurements. Finally, a prototype with the size of Ф3.1 cm × 12 cm is fabricated for underwater driving performance experiments, which demonstrated well functions in straight swimming, turning, and loading. The swimmer with 20 g of additional load achieves a maximum speed of 105 mm s−1at the voltage of 180 Vp-p, it also completes the obstacle avoidance in water along a certain path. The rationality of this conceived actuation mechanism is preliminarily verified, which shows a potential for fixed-point transportation in the complex underwater situations.

Differences in spinal axial rotation angles during the lumbar-locked rotation test between hyper and normal thoracic rotation groups: A cross-sectional study.

Trunk rotation is important in many sporting activities The thoracic spine has reciprocal relationships with the lumbar and pelvic spines, such that reduced flexibility in the lumbar or thoracic spine can lead to abnormal patterns of trunk movement and pain. However, few studies have investigated the relative trunk rotation mobilities of the thorax, lumbar, and pelvis. To compare thoracic, lumbar, and pelvic rotation angles during the lumbar-locked rotation test between hyper and normal thoracic rotation groups. Thirty-two young, active participants were enrolled in this study. After the attachment of inertial measurement units at the T1, T7, T12, L3, and S2 levels, the participants were required to stand in a comfortable upright posture for 5s to allow postural measurements before performing the lumbar-locked rotation test. The participants were then divided into hyper thoracic rotation and normal thoracic rotation groups based on T1 angle measurements obtained during the lumbar-locked rotation test. The hyper thoracic rotation group had significantly higher thoracic rotation angles on both the right (p< 0.05) and left (p< 0.05) sides compared with the normal thoracic rotation group. Furthermore, we observed flat lumbar lordosis in the hyper thoracic rotation group compared with the normal thoracic rotation group, particularly in the lower lumbar region in standing posture. Our data suggest that evaluations of thoracic mobility should consider relative thoracic, lumbar, and pelvic motions, rather than the T1 angle alone. This study provides a basis for health professionals to evaluate movement dysfunctions associated with thoracic hypermobility.

Local resource availability drives habitat use by a threatened avian granivore in savanna woodlands.

Conserving threatened species relies on an understanding of their habitat requirements. This is especially relevant for granivorous birds, whose habitat use and movement patterns are intricately linked to the spatial and temporal availability of resources such as food and water. In this study, we investigated the habitat use, home range and daily activity patterns of the Endangered Southern Black-throated Finch (SBTF; Poephila cincta cincta) within a 75,000 ha savanna woodland study area in northeastern Australia. This semi-arid region is one of the key remaining strongholds for the species and is characterised by substantially different habitat and climatic conditions than areas where previous research on this species has been undertaken. We radio tracked 142 SBTF using both manual tracking and an array of 27 automated radio towers, which revealed a strong preference for eucalypt-dominated grassy woodland communities. The preference for these habitats also increased with decreasing distance to permanent water. While SBTF occupied large home ranges, individual SBTF were largely sedentary during the radio tracking period (21.8, range = 0.83-120 days), with few landscape-scale movements of more than 4.5 km. Daily foraging activity of SBTF exhibited bimodal peaks in the early morning and late afternoon, while other activities were greatest from the late morning to the early afternoon. Compared to other estrildid finches, our research suggests that SBTF track resources at a local scale across a large home range. We postulate that in times of resource scarcity SBTF may use dietary diversification, instead of landscape or regional-scale nomadic movements, to meet their resource needs. The species' movement patterns underscore the importance of local scale habitat management to facilitate resource availability throughout the year. Furthermore, our research helps target monitoring designs for granivorous birds that focus on the species' diurnal activity patterns.

Bayesian multistate models for measuring invasive carp movement and evaluating telemetry array performance.

Understanding the movement patterns of an invasive species can be a powerful tool in designing effective management and control strategies. Here, we used a Bayesian multistate model to investigate the movement of two invasive carp species, silver carp (Hypophthalmichthys molitrix) and bighead carp (H. nobilis), using acoustic telemetry. The invaded portions of the Illinois and Des Plaines Rivers, USA, are a high priority management zone in the broader efforts to combat the spread of invasive carps from reaching the Laurentian Great Lakes. Our main objective was to characterize the rates of upstream and downstream movements by carps between river pools that are maintained by navigation lock and dam structures. However, we also aimed to evaluate the efficacy of the available telemetry infrastructure to monitor carp movements through this system. We found that, on a monthly basis, most individuals of both species remained within their current river pools: averaging 76.2% of silver carp and 75.5% of bighead carp. Conversely, a smaller proportion of silver carp, averaging 14.2%, and bighead carp, averaging 13.9%, moved to downstream river pools. Movements towards upstream pools were the least likely for both species, with silver carp at an average of 6.7% and bighead carp at 7.9%. The highest probabilities for upstream movements were for fish originating from the three most downstream river pools, where most of the population recruitment occurs. However, our evaluation of the telemetry array's effectiveness indicated low probability to detect fish in this portion of the river. We provide insights to enhance the placement and use of these monitoring tools, aiming to deepen our comprehension of these species' movement patterns in the system.

The Relationship between Functional Movement Quality and Speed, Agility, and Jump Performance in Elite Female Youth Football Players.

The association between movement screening and physical fitness testing in athletes is conflicting, and therefore, this study aimed to examine the relationship between Functional Movement Screen (FMS) performance and physical performance in elite female youth football players. Twenty-two players from the national U16 team of Bosnia and Herzegovina underwent FMS and physical performance tests, including speed, agility, and jump assessments. Jump and speed performance score correlated well with ASLR, while the overall FMS score was not associated with any of the performance variables. These findings suggest that while certain movement patterns may impact athletic performance, the relationship between movement screening and physical performance is delicate. Coaches and practitioners should consider individual variations and sport-specific demands when interpreting FMS results in order to optimize and maximize athlete performance and reduce injury risks.