Chronic heart failure is a widespread clinical condition associated with reduced exercise tolerance, impaired quality of life, and increased morbidity and mortality. Exercise-based cardiac rehabilitation represents an essential component of non-pharmacological management in patients with chronic heart failure; however, optimal training strategies and delivery models remain under discussion. This narrative review summarizes current evidence regarding the safety, efficacy, and feasibility of exercise-based rehabilitation across different heart failure phenotypes. The analysis includes conventional centre-based programs, home-based rehabilitation, telerehabilitation, and novel exercise modalities. Available evidence indicates that structured exercise training improves functional capacity, exercise tolerance, and health-related quality of life, regardless of rehabilitation setting. Combined aerobic and resistance training, as well as high-intensity interval training, appear to provide greater functional benefits than moderate continuous exercise, particularly under supervised conditions. Functional assessment using cardiopulmonary exercise testing remains the reference standard, while the six-minute walk test offers a practical alternative in routine clinical practice. Individualized, patient-centred rehabilitation strategies are crucial for optimizing outcomes and supporting long-term engagement in physical activity among patients with chronic heart failure.
We present ShuttleEnv, an interactive and data-driven simulation environment for badminton, designed to support reinforcement learning and strategic behavior analysis in fast-paced adversarial sports. The environment is grounded in elite-player match data and employs explicit probabilistic models to simulate rally-level dynamics, enabling realistic and interpretable agent-opponent interactions without relying on physics-based simulation. In this demonstration, we showcase multiple trained agents within ShuttleEnv and provide live, step-by-step visualization of badminton rallies, allowing attendees to explore different play styles, observe emergent strategies, and interactively analyze decision-making behaviors. ShuttleEnv serves as a reusable platform for research, visualization, and demonstration of intelligent agents in sports AI. Our ShuttleEnv demo video URL: https://drive.google.com/file/d/1hTR4P16U27H2O0-w316bR73pxE2ucczX/view
Existing match classification models in the tournament design literature have two major limitations: a contestant is considered indifferent only if uncertain future results do never affect its prize, and competitive matches are not distinguished with respect to the incentives of the contestants. We propose a probabilistic framework to address both issues. For each match, our approach relies on simulating all other matches played simultaneously or later to compute the qualifying probabilities under the three main outcomes (win, draw, loss), which allows the classification of each match into six different categories. The suggested model is applied to the previous group stage and the new incomplete round-robin league, introduced in the 2024/25 season of UEFA club competitions. An incomplete round-robin tournament is found to contain fewer stakeless matches where both contestants are indifferent, and substantially more matches where both contestants should play offensively. However, the robustly higher proportion of potentially collusive matches can threaten with serious scandals.
Nodik Qudwal Husnain, I Dewa Made Aryananda Wijaya Kusuma, Arif Bulqini
et al.
In the sport of futsal, enhancing shooting speed is crucial for performance, yet there is a lack of targeted training methods that effectively improve this skill among student players. This study aimed to analyze the effect of plyometric single-leg hurdle hops combined with backward run training on shooting speed in student futsal players. A quasi-experimental design with a one-group pretest–posttest approach was employed. The population consisted of 25 student futsal players, and the sample included 15 players with a mean age of 14.67 ± 0.49 years, height of 160.73 ± 4.46 cm, weight of 50.20 ± 5.93 kg, and BMI of 19.42 ± 2.02, selected using purposive sampling. Shooting speed was measured using a camera, and the recordings were analyzed with the Kinovea application. The results showed a significant increase (p<0.05) in shooting speed following the training program. The mean shooting speed improved from 28.3±2.02 m/s in the pretest to 30.4±2.20 m/s in the posttest, with a mean difference of 2.04±1.98 m/s and a 2-tailed significance value of 0.001 (< 0.05). In conclusion, plyometric single-leg hurdle hops combined with backward run training significantly improved shooting speed in student futsal players.
Hassan Saad Shallak, Abbas Zaki Abdul Hussein, Ali Sabah Nouri
et al.
The aim of the study is to investigate the impact of surgical and non-surgical rehabilitation programs on anterior and posterior cruciate ligament (ACL) injuries in team sports athletes, such as football, basketball, and handball. The methodology used was the descriptive-analytical approach using objective measures. The study included a sample of 60 players aged between 18 and 30 years who had suffered a cruciate ligament injury. The sample was divided into two groups: one group underwent surgical rehabilitation after ACL reconstruction surgery, and another group underwent non-surgical rehabilitation through specialized therapeutic exercises. The researchers concluded that the study showed that surgical rehabilitation for ACL injuries was more effective in improving range of motion, reducing pain, and increasing muscle strength compared to non-surgical treatment. Additionally, the researchers recommended the necessity of designing specialized rehabilitation programs that consider the nature of the injury and the needs of each player to ensure the restoration of movement and safe return to competition
Wide-angle video is favored for its wide viewing angle and ability to capture a large area of scenery, making it an ideal choice for sports and adventure recording. However, wide-angle video is prone to deformation, exposure and other distortions, resulting in poor video quality and affecting the perception and experience, which may seriously hinder its application in fields such as competitive sports. Up to now, few explorations focus on the quality assessment issue of wide-angle video. This deficiency primarily stems from the absence of a specialized dataset for wide-angle videos. To bridge this gap, we construct the first Multi-annotated and multi-modal Wide-angle Video quality assessment (MWV) dataset. Then, the performances of state-of-the-art video quality methods on the MWV dataset are investigated by inter-dataset testing and intra-dataset testing. Experimental results show that these methods impose significant limitations on their applicability.
The topic of aging decline on performance of NBA players has been discussed in this study. The autoencoder with K-means clustering machine learning method was adopted to career trend classification of NBA players, and the LSTM deep learning method was adopted in performance prediction of each NBA player. The dataset was collected from the basketball game data of veteran NBA players. The contribution of the work performed better than the other methods with generalization ability for evaluating various types of NBA career trend, and can be applied in different types of sports in the field of sport analytics.
O objetivo deste estudo foi analisar a associação entre a motivação e vários aspectos da prática de exercício físico (EF) em indivíduos que mantiveram a perda de massa corporal, e explorar o papel do gênero. A amostra foi constituída por 253 participantes, foram avaliadas as suas características sociodemográficas, a composição corporal, o EF, a motivação geral e específica para o exercício, com instrumentos validados. Utilizou-se o teste t-de student para comparar as diversas variáveis entre os participantes. Para analisar a associação entre as variáveis motivacionais e os diferentes aspectos do EF, utilizou-se o coeficiente de correlação de Pearson. Foram ainda criados tercis para as variáveis motivacionais e posteriormente comparadas as médias dos vários aspectos do EF, através do teste da ANOVA one-way. Observaram-se diferenças entre gêneros no que respeita à intensidade, duração e dispêndio energético e na maioria das variáveis motivacionais, favorecendo o gênero masculino. Identificaram-se associações positivas entre as variáveis motivacionais relacionadas com o EF, nomeadamente a motivação intrínseca e as regulações de ordem mais autônoma, e os diferentes aspectos do EF, na amostra total e no gênero feminino (p < 0,05). Em indivíduos com sucesso na manutenção da perda de massa corporal, particularmente nas mulheres, motivações mais autônomas para o EF associaram-se a maior prática de EF. Essas conclusões são significativas para programas de perda de massa corporal e promoção de saúde, indicando que a motivação autônoma pode ser um fator de sucesso na manutenção da massa corporal.
Damjana V. Cabarkapa, Dimitrije Cabarkapa, Jelena Aleksic
et al.
One of the reoccurring questions that arises during the countermovement vertical jump (CVJ) assessment is whether the learning effect has an impact on the accuracy of the results obtained. Thus, the purpose of the present investigation was to examine the impact of the short-term learning effect on the assessment of lower-body neuromuscular performance characteristics when performed on a portable one-dimensional force plate system. Sixteen recreationally active college-age males volunteered to participate in the present study. Each participant completed four sets of three non-consecutive CVJs with no arm swing throughout a single day. Besides strong verbal encouragement, participants were constantly instructed to focus on pushing the ground as explosively as possible. Fourteen force-time metrics were selected for CVJ performance analysis purposes: eccentric and concentric peak and mean force and power, eccentric and concentric duration, contraction time, jump height, reactive strength index-modified, and countermovement depth. Repeated measures multivariate analysis of variance was used to examine statistically significant differences across four testing time points (p < 0.05). The results indicate an absence of any meaningful differences across four testing time points in force-time metrics of interest during both eccentric and concentric phases of the CVJ. Moreover, no differences were observed in CVJ outcome metrics such as countermovement depth, suggesting that the movement strategy tends to remain consistent. Overall, these findings reveal that CVJ test repeatability is not affected by the short-term learning effect and that data are stable at least within the scope of this study and within this population.
Understanding and predicting athletes' mental states is crucial for optimizing sports performance. This study introduces a hybrid BERT-XGBoost model to analyze psychological factors such as emotions, anxiety, and stress, and predict their impact on performance. By combining BERT's bidirectional contextual learning with XGBoost's classification efficiency, the model achieves high accuracy (94%) in identifying psychological patterns from both structured and unstructured data, including self-reports and observational data tagged with categories like emotional balance and stress. The model also incorporates real-time monitoring and feedback mechanisms to provide personalized interventions based on athletes' psychological states. Designed to engage athletes intuitively, the system adapts its feedback dynamically to promote emotional well-being and performance enhancement. By analyzing emotional trajectories in real-time offers empathetic, proactive interactions. This approach optimizes performance outcomes and ensures continuous monitoring of mental health, improving human-computer interaction and providing an adaptive, user-centered model for psychological support in sports.
Success in sports is a complex phenomenon that has only garnered limited research attention. In particular, we lack a deep scientific understanding of success in sports like tennis and the factors that contribute to it. Here, we study the unfolding of tennis players' careers to understand the role of early career stages and the impact of specific tournaments on players' trajectories. We employ a comprehensive approach combining network science and analysis of ATP tournament data and introduce a novel method to quantify tournament prestige based on the eigenvector centrality of the co-attendance network of tournaments. Focusing on the interplay between participation in central tournaments and players' performance, we find that the level of the tournament where players achieve their first win is associated with becoming a top player. This work sheds light on the critical role of the initial stages in the progression of players' careers, offering valuable insights into the dynamics of success in tennis.
Educational supervision is considered one of the most important elements of the educational process, as it has a major role in improving and developing all elements of the educational process. Indeed, the first and basic task of educational supervision is to develop and develop the teacher's capabilities, improve his level of performance, help him solve problems facing him, and provide him with expertise. Occasion .
Educators also unanimously agree that the educational supervision process is a specialized technical service provided by the competent educational supervisor to the teachers who work with him in order to improve the teaching and learning process and work to develop it in all its fields. males and females), to lead and influence those under their responsibility in order to raise the level of performance in the field of work
That is, the educational supervisor must possess multiple qualifications, including (leadership, administrative, and personal), in order to ensure the achievement of the desired goals of supervision, and this is the responsibility of those in charge of the process of selecting supervisors to find ways to ensure the success of the selection process.
The importance of the current research lies in comparing the personal and administrative characteristics of choosing the supervisor (educational and specialist) for physical education teachers and teachers between male and female supervisors through the level of their performance on these standards.
The researchers used the descriptive approach, where the research community included (514) male and female supervisors, and the researchers put out a questionnaire on a sample of the community amounted to (285) male and female supervisors. The results showed that there are significant differences in personal and administrative characteristics between male and female educational supervisors and specialists, and in favor of males.
Aleksandra Kulbat, Aleksandra Karwańska, Mateusz Kulbat
et al.
Depression is a common mental health disorder that affects the majority of the population. The exact cause of depression is not fully understood, but various factors such as genetics, environmental stressors, and psychological factors are believed to play a role. Due to the complexity of the etiopathogenesis of depression, the selection of appropriate therapeutic management is sometimes complicated. Treatment for depression typically involves a combination of medication and psychotherapy. Antidepressant medication can help alleviate symptoms by regulating neurotransmitters in the brain, while psychotherapy can help individuals understand and change negative thoughts and behaviors.
Physical activity, such as sport, has been shown to have a positive impact on mental health and can help alleviate symptoms of depression. Exercise releases endorphins, reducing stress and improving mood. Health education can also play a role in preventing and managing depression by raising awareness, reducing stigma, and teaching individuals coping skills to maintain good mental health.
With the aging of the population in China in recent years, the number of stroke patients is increasing day by day. The sequelae of stroke-induced foot drop are expected to regain some mobility after timely rehabilitation, but if patients do not receive early intervention, they may miss the best rehabilitation period and lose the ability to walk and stand completely. The traditional means of rehabilitation treatment is manual rehabilitation by rehabilitation physicians, but with the increase in the number of patients with movement disorders, the number of rehabilitation physicians has become significantly insufficient. The use of rehabilitation robots to provide adjunctive therapy to patients has become a common and effective means of rehabilitation worldwide. The early rehabilitation robots could only drive the patient to do passive rehabilitation and could not reflect the patient’s true motor intentions. Since EMG signals on the surface of the human body can advance the onset of human movement, they can be used to identify the intention of human movement. This paper validates and explores the experiment based on the underlying data.
With the recent progress in sports analytics, deep learning approaches have demonstrated the effectiveness of mining insights into players' tactics for improving performance quality and fan engagement. This is attributed to the availability of public ground-truth datasets. While there are a few available datasets for turn-based sports for action detection, these datasets severely lack structured source data and stroke-level records since these require high-cost labeling efforts from domain experts and are hard to detect using automatic techniques. Consequently, the development of artificial intelligence approaches is significantly hindered when existing models are applied to more challenging structured turn-based sequences. In this paper, we present ShuttleSet, the largest publicly-available badminton singles dataset with annotated stroke-level records. It contains 104 sets, 3,685 rallies, and 36,492 strokes in 44 matches between 2018 and 2021 with 27 top-ranking men's singles and women's singles players. ShuttleSet is manually annotated with a computer-aided labeling tool to increase the labeling efficiency and effectiveness of selecting the shot type with a choice of 18 distinct classes, the corresponding hitting locations, and the locations of both players at each stroke. In the experiments, we provide multiple benchmarks (i.e., stroke influence, stroke forecasting, and movement forecasting) with baselines to illustrate the practicability of using ShuttleSet for turn-based analytics, which is expected to stimulate both academic and sports communities. Over the past two years, a visualization platform has been deployed to illustrate the variability of analysis cases from ShuttleSet for coaches to delve into players' tactical preferences with human-interactive interfaces, which was also used by national badminton teams during multiple international high-ranking matches.
Pablo Moraes, Hiago Sodre, Monica Rodriguez
et al.
This article describes the design and development of robotic prototypes for robotic soccer competitions using Dynamixel motors. Although the prototypes are not aimed at world-class competitions, they represent a significant step in the development of sports robots. Model XL430-W250 Dynamixel motors were chosen and electronic circuits were implemented using control boards such as OpenCR and Raspberry Pi 3. A crucial component was introduced: a step-up board that charges a capacitor to create a powerful kick to the ball via anelectromagnet controlled by Arduino Nano. The programming and coordination of the prototypes was carried out using the ROS environment (Robot Operating System), which allows effective integration of movements and communication. Although the prototypes were not optimized for global competition, they underwent extensive testing, evaluating their speed and maneuverability, as well as soccer tactics in the GRSim simulator. These prototypes contribute to the further development of sports robotics and illustrate the research potential in this exciting area.
Sayako Ueda, Yoko Iwamoto, Fumikazu Taketani
et al.
Abstract. Atmospheric transport of iron (Fe) in fine anthropogenic aerosol particles is an important route of soluble Fe supply to remote oceans from continental areas. To investigate Fe properties of aerosol particles over remote oceans, we analyzed atmospheric aerosol particles over the Indian Ocean during the research vessel Hakuho Maru KH-18-6 cruise. Aerosol particles collected using a cascade impactor were analyzed using transmission electron microscopy (TEM) with an energy-dispersive X-ray spectrometry analyzer. The particle shape and composition on the sample stage of 0.3–0.8 μm aerodynamic diameter indicated that most particles collected north of the equator were composed mainly of ammonium sulfate. Regarding the particle number fraction, 0.6–3.0 % of particles contained Fe, which mostly co-existed with sulfate. Of those particles, Fe was found 26 % as metal spheres, often co-existing with Al or Si, regarded as fly ash, 14 % as mineral dust, and 7 % as iron oxide aggregations. Water-dialysis analyses of TEM samples indicated that Fe in spherical fly ash was almost entirely insoluble, whereas Fe in the other morphological-typed particles was partly (65 % Fe mass on average) soluble. Global model simulations mostly reproduce observed Fe mass concentrations in PM2.5 collected using a high-volume air sampler, including their north–south contrast during the cruise. In contrast, a marked difference was found between the simulated mass fractions of Fe mineral sources and the observed Fe types. For example, the model underestimated anthropogenic aluminosilicate Fe contained in matter such as fly ash from coal combustion. Our observations suggest that Fe in particles over remote ocean areas has multiple shapes and minerals, and further suggest that its solubility after aging processes differs depending on their morphological and mineral type. Proper consideration of such Fe types at their sources is necessary for accurate estimation of atmospheric Fe effects on marine biological activity.
<h4>Introduction</h4>Low back pain is a major health issue in elite rowers. High training volume, frequent flexion movements of the lower spine and rotational movement in sweep rowing contribute to increased spinal strain and neuropathological patterns. Perturbation-based trunk stabilization training (PTT) may be effective to treat neuromuscular deficits and low back pain.<h4>Methods</h4>All boat classes (8+, 4+/-, 2-) of the male German national sweep rowing team participated in this non-randomized parallel group study. We included 26 athletes (PTT: n = 12, control group: n = 14) in our analysis. Physical and Sports therapists conducted 16 individualized PTT sessions á 30-40 minutes in 10 weeks, while the control group kept the usual routines. We collected data before and after intervention on back pain intensity and disability, maximum isometric trunk extension and flexion, jump height and postural sway of single-leg stance.<h4>Results</h4>We found less disability (5.3 points, 95% CI [0.4, 10.1], g = 0.42) for PTT compared to control. Pain intensity decreased similar in both groups (-14.4 and -15.4 points), yielding an inconclusive between-group effect (95% CI [-16.3, 14.3]). Postural sway, strength and jump height tend to have no between- and within-group effects.<h4>Conclusion</h4>Perturbation-based trunk stabilization training is possibly effective to improve the physical function of the lower back in elite rowers.