Actions Of Players Research Articles

UV-B responses in the spotlight: Dynamic photoreceptor interplay and cell-type specificity.

Plants are constantly exposed to a multitude of external signals, including light. The information contained within the full spectrum of light is perceived by a battery of photoreceptors, each with specific and shared signalling outputs. Recently, it has become clear that UV-B radiation is a vital component of the electromagnetic spectrum, guiding growth and being crucial for plant fitness. However, given the large overlap between UV-B specific signalling pathways and other photoreceptors, understanding how plants can distinguish UV-B specific signals from other light components deserves more scrutiny. With recent evidence, we propose that UV-B signalling and other light signalling pathways occur within distinct tissues and cell-types and that the contribution of each pathway depends on the type of response and the developmental stage of the plant. Elucidating the precise site(s) of action of each molecular player within these signalling pathways is key to fully understand how plants are able to orchestrate coordinated responses to light within the whole plant body. Focusing our efforts on the molecular study of light signal interactions to understand plant growth in natural environments in a cell-type specific manner will be a next step in the field of photobiology.

Player Modeling and Adaptation Methods Within Adaptive Serious Games

Serious games (SGs) have emerged in recent years as a key method to augment education and training. SGs allow players to experience new concepts while exploring engaging virtual environments. To further extend the educational merit of SGs, adaptive SGs integrate games with adaptive systems to provide a more supportive education. Typically, these adaptive systems either focus on assisting or engaging the player, or on providing a more human-like tutoring experience. For appropriate adaptation, these games make use of player analytics and player modeling to determine what help to provide, predict future player actions, or otherwise model a player’s mental or physical state. To assist researchers in the development of future adaptive SGs, this article reviews and categorizes both player modeling and game adaptation methods from publications over the past ten years. We offer comparisons of various methods to achieve both modeling and adaptation, as well as comprehensive categories for both aspects. Furthermore, we also offer insights for future areas of study in adaptive SGs, as well as possible directions for SG developers.

News Framing on Actors of National Capital City (IKN) Through Cultural Communication of `Tanah' and `Air' Unity in Online Media

Against the backdrop of historical communicative actions, the news is the outcome of knowledge in the reality of everyday life. The homo sociological communication model consists of behaviors that refer to collective norms and values, especially laws that declare a requirement, a social order which is then ensured by normative conventions. Through actors and cultural symbols, social action, transcendence, and objectivity become communication acts in the form of news framing. The State Capital or Ibu Kota Negara (IKN) has been the subject of news in the media. This study then aimed to determine news context on the unity of land and water (Tanah dan Air) as a metaphor for the State Capital’s relocation from Jakarta to East Kalimantan Alfred Schutz’s Communicative Action theory. The research used qualitative methodology, while analysis was done using narrative analysis. The findings of this research are the symbols of land and water in the discourse of framing the news of the transfer of the State Capital (IKN) since the administrations of President Sukarno to President Jokowi became a reality of communicative acts with historical significance and cultural communication through land and water rituals. The discourse frame is a value that contributes to profound political and cultural dialogue and equal growth. Sociologically, communicative behavior in new framing results from integrating players historical, cultural, and political interests. Based on the research findings, the recommendation put forward is policy analysis on the transfer of IKN, which must continue to investigate history via cultural communication and social action of players on homo sociologicus and history who possess strategic collective values and norms for sustainable cultural and economic development.
 Keywords: news framing, communicative action theory, cultural communication

Peculiarities of improving the technical preparedness of «libero» at the stage of preliminary basic training

High sports performance in the preparation of a «libero» is one of the main criteria for the success and correctness of the educational and training process. Implementation of technical actions of young volleyball players during competitive activities requires a high level of technical training of «libero» players. Despite the presence of a significant amount of research aimed at improving the process of technical training at various stages of multi-year training, the main problem remains the search for a modern approach to planning the process of technical training of «libero» players.
 The experimental technique consisted of five blocks aimed at mastering the technique of movements, as well as sets of exercises aimed at mastering the player's actions with and without the ball. In the training session, the necessary combinations and placements were used for receiving passes, exercises in defense, passing the ball from above and below, exercises for developing speed.
 The comparative analysis of young volleyball players makes it possible to state that the best indicators obtained in test tasks that characterize the level of technical preparation fully reflect the orientation of experimental method training. The implementation of the developed experimental blocks of exercises in the educational and training process of the «libero» players confirmed their high efficiency in increasing the level of technical preparation, as evidenced by a significant increase in the results of the athletes of the experimental group.

Poster 356: Injury patterns of Achilles tendon ruptures: a systematic video analysis of 80 cases in professional male football

Objectives: Achilles tendon ruptures are injuries with a high severity. Analyses of underlying biomechanical and situational patterns may promote a better understanding of Achilles tendon ruptures and aid in their management and prevention. However, a systematic biomechanical and situational video analysis of real-life Achilles tendon ruptures has not been performed to date. Methods: Professional male football players with an acute Achilles tendon rupture were identified by using an online database (Transfermarkt.com, Hamburg, Germany). For every in-competition injury, the coinciding football match leading to injury was detected. Video files of the injuries were accessed using Wyscout.com (Wyscout.com, Genova, Italy). Situational patterns and injury biomechanics of the injury frame were independently analyzed by two reviewers using a standardized checklist and a motion analysis software (Kinovea v.0.8.15, www.kinovea.org). Finally, consensus was reached to describe the main injury patterns of Achilles tendon ruptures in professional male football. Results: Overall, 80 injuries were included for video analysis. Most injuries (94%) were indirect or non- contact injuries. The kinematic analysis revealed a knee extension movement and an ankle dorsiflexion movement in most cases. Typical joint positions at the assumed injury frame were hip extension, knee extension and ankle dorsiflexion. Player actions identified as main injury patterns were stepping back, landing, running/sprinting, starting, and jumping. All main patterns were closed-chain movements (that is, fixation of the affected leg to the ground). Conclusions: Most Achilles tendon ruptures share characteristic injury features, that is, Achilles tendon elongation, closed-chain movements, and sudden loading. The findings of this study allow insight into injury mechanisms of Achilles tendon ruptures in professional male football and may support translation towards future development of prevention programs.

Detection of fixed football matches based on the theory of conformal predictors using the modified Stepanets indicator function

An urgent issue of modern football competitions is the detection of fixed matches. Known methods for predicting the outcome of a match by analyzing bets on a match or analyzing the actions of football players on the field use a large amount of data that is not always available. To overcome this obstacle, there can be applied a method for detecting suspicious fixed match results based on conformal predictors and power martingales, which uses publicly available public data. But in practice, this method does not always detect such matches with high precision. An improved method for determining a suspicious match is proposed, based on the theory of conformal predictors using a modified Stepanets indicator function, which is compared with a threshold. The modified Stepanets indicator function is applied to the power martingale and shows the relative change in the martingale value of the current match compared to the previous match. The threshold value was determined experimentally according to the criterion of the maximum of the F1 metric. Data from the 2013–2014 season of the French II League were used as a training sample, and data from the 2014–2015 season of Serie B in Italy were used as a test sample. Team clustering was performed on all samples. For each of the formed classes of matches on both samples, the measure of non-conformity, the degree of non-conformity, the power martingale, and the modified Stepanets indicator function were calculated. The resulting indicators of precision metrics and F1 are higher (average values of metrics P=0.84, F1=0.87) than the same indicators of martingale and p-value rules (average values of metrics P=0.75, F1=0.78), applied to the same data. The proposed method reveals 4 out of 5 matches of the 2014–2015 Serie B season in Italy, which are considered fixed according to information from official Italian law enforcement sources

Interpersonal coordination of opposing player dyads during attacks performed in official football matches

ABSTRACT The purpose of this study was to characterise the interpersonal coordination between opponent players during offensive sequences in official matches and to verify if offensive sequences ended in shots to goal present different coordination patterns when compared than those that ended in defensive tackles. A total of 580 offensive sequences occurred during matches resulting in shots to goal (n = 172) or defensive tackles (n = 408) were analysed. The bidimensional coordinates and technical actions of male professional football players (n = 1160) were obtained using a video-based tracking system. Dyads were defined using a network analysis and composed of the nearest opponent. Interpersonal coordination of the dyads was analysed using the vector coding and the frequency for each coordination pattern was computed. In-phase was predominant for all displacement directions and offensive sequences outcomes, and antiphase was the least frequent. For lateral displacements, offensive sequences ending in shot to goal presented lower frequency for in-phase and higher frequency for offensive player phase than ended in defensive tackle. This information about the relationship of opponent players dyads during decisive moments of the matches provides fundamentals for future research and assists coaches to understand the different behaviours in successful and unsuccessful attacks.

Аpplication of game tactics analysis in sports games on the example of tennis

The article focuses on the current state of various means, methods and systems used in tennis to analyze the tactical activity of players. The purpose of the study is to study modern approaches to the analysis of tactical activity in sports games on the example of tennis. Research methodology: analysis of special, scientific and methodological literature, analysis of computer programs and applications for the use of fixing tactical actions, systematic method, generalization and systematization of data. Results of the study. In the course of studying scientific and methodical literature and modern technologies it has been found that there are several analysis systems for conducting a qualitative and effective analysis of tennis players' tactical actions. One of them is a notational analysis, which can be both manual and computerized. This method can be considered quantitatively consistent and reliable. Areas where it can be applied in tennis: tactical analysis, technical analysis, movement analysis, database and modeling. The article pays special attention to computer programs, which can be divided into two broad categories of tracking and tagging systems. In addition, the article presents the analysis of modern devices and applications that also belong to the category of tracking systems and are particularly popular among coaches and players for training and constant monitoring of the training and competitive processes of athletes. Conclusion. The existing means, methods and computer programs for analyzing the tactical actions of tennis players are diverse, modern, useful and widely used by coaches and players in training and competitive activities.

Distributed Nash Equilibrium Seeking for Aggregative Games With Quantization Constraints

The problem of seeking Nash equilibrium (NE) based on aggregative games under quantization constraints is full of challenges. Although the NE seeking algorithm in continuous-time systems has been studied, this problem in discrete-time systems still needs to be solved urgently. To address this problem, three distributed algorithms are first proposed under three quantization cases, adaptive, random, and time-varying quantizations, based on doubly stochastic communication topology networks. Then, the actions of players would eventually converge to NE under the conditions of vanishing step size and strong monotonicity are proved. Moreover, the convergence rate of the three quantization cases are analyzed, respectively. Finally, numerical experiments are implemented on plug-in hybrid electric vehicles (PHEVs) to validate the effectiveness of the proposed distributed algorithms. Comparing the convergence rates of the three proposed algorithms, the convergence effect of the adaptive quantization is better than that of the other two quantization cases.

Fully Distributed Nash Equilibrium Seeking for High-Order Players With Actuator Limitations

This paper explores the problem of distributed Nash equilibrium seeking in games, where players have limited knowledge on other players' actions. In particular, the involved players are considered to be high-order integrators with their control inputs constrained within a pre-specified region. A linear transformation for players' dynamics is firstly utilized to facilitate the design of bounded control inputs incorporating multiple saturation functions. By introducing consensus protocols with adaptive and time-varying gains, the unknown actions for players are distributively estimated. Then, a fully distributed Nash equilibrium seeking strategy is exploited, showcasing its remarkable properties: 1) ensuring the boundedness of control inputs; 2) avoiding any global information/parameters; and 3) allowing the graph to be directed. Based on Lyapunov stability analysis, it is theoretically proved that the proposed distributed control strategy can lead all the players' actions to the Nash equilibrium. Finally, an illustrative example is given to validate effectiveness of the proposed method.

Lower bounds for the query complexity of equilibria in Lipschitz games

Nearly a decade ago, Azrieli and Shmaya introduced the class of λ-Lipschitz games in which every player's payoff function is λ-Lipschitz with respect to the actions of the other players. They showed that such games admit ϵ-approximate pure Nash equilibria for certain settings of ϵ and λ. They left open, however, the question of how hard it is to find such an equilibrium. In this work, we develop a query-efficient reduction from more general games to Lipschitz games. We use this reduction to show a query lower bound for any randomized algorithm finding ϵ-approximate pure Nash equilibria of n-player, binary-action, λ-Lipschitz games that is exponential in nλ/ϵ. In addition, we introduce “Multi-Lipschitz games,” a generalization involving player-specific Lipschitz values, and provide a reduction from finding equilibria of these games to finding equilibria of Lipschitz games, showing that the value of interest is the average of the individual Lipschitz parameters. Finally, we provide an exponential lower bound on the deterministic query complexity of finding ϵ-approximate Nash equilibria of n-player, m-action, λ-Lipschitz games for strong values of ϵ, motivating the consideration of explicitly randomized algorithms in the above results.

Application of athletics equipment in sprinting training of rugby players

Aim – to justify the use of athletics exercises in the sprint training of rugby players. Methods: theoretical methods of pedagogical research. Results and discussion. The modern game of rugby requires a player, regardless of his role and position on the field in the game, to be prepared to execute short, repetitive bursts of running at high intensity. It has been established that the structure of the sprint of rugby players is similar to the actions of a sprinter who has to perform a run from the start or an instant powerful acceleration in motion. The results of the analysis of the scientific and methodological literature and pedagogical modeling showed that in order to improve the rugby player's sprinting performance, the physical training coach should include in the training program plyometric exercises, fast squats with a barbell, towing a sled and exercises aimed at improving the technique of sprinting. It is these practical and scientifically proven means in the field of athletics that determine the impact on the structure of sprinting abilities of rugby players, identical to the sprinting characteristics of a player on the field. Conclusions. It has been established that rugby players need the ability to perform powerful quick movements in accordance with the structure inherent in short-distance runners. Therefore, there is an opportunity to build a sprint training program using exercises and training methodology for short-distance runners. Sprinting exercises should be selected taking into account the powerful short sprints that are inherent in the actions of a rugby player during the game. At the same time, the need for readiness for their serial implementation should be taken into account. Therefore, it is promising to develop a methodology for applying elements of sprinter training in the construction of sprint training for rugby players.

Polychaetoid/ZO-1 strengthens cell junctions under tension while localizing differently than core adherens junction proteins.

During embryonic development, dramatic cell shape changes and movements reshape the embryonic body plan. These require robust but dynamic linkage between the cell-cell adherens junctions and the force-generating actomyosin cytoskeleton. Our view of this linkage has evolved, and we now realize linkage is mediated by mechanosensitive multiprotein complexes assembled via multivalent connections. Here we combine genetic, cell biological, and modeling approaches to define the mechanism of action and functions of an important player, Drosophila polychaetoid, homologue of mammalian ZO-1. Our data reveal that Pyd reinforces cell junctions under elevated tension, and facilitates cell rearrangements. Pyd is important to maintain junctional contractility and in its absence cell rearrangements stall. We next use structured illumination microscopy to define the molecular architecture of cell-cell junctions during these events. The cadherin-catenin complex and Cno both localize to puncta along the junctional membrane, but are differentially enriched in different puncta. Pyd, in contrast, exhibits a distinct localization to strands that extend out from the region occupied by core junction proteins. We then discuss the implications for the protein network at the junction-cytoskeletal interface, suggesting different proteins localize and function in distinct ways, perhaps in distinct subcomplexes, but combine to produce robust connections.

Model Representation Considerations for Artificial Intelligence Opponent Development in Combat Games

The performance and behavior of an Artificial Intelligence (AI) opponent in games requires coordination of multiple agents and complex tasks depends on many design choices made during implementation. Currently, gaming agents developed with Reinforcement Learning (RL) methods are constructed to play the game, leading to natural design choices for observations, actions, and rewards that are congruent with a human player's actions and objectives. However, in simulation and serious games, the objective of the implemented opponent should be developed in a way that supports the learning objectives for the user, such as by including additional ground truth environment data in the observation space or action structure. Therefore, the reward structure for the AI needs to incorporate more sophisticated considerations than just whether the game was won or lost by the AI. In this way the design space for opponent AI in these settings is considerably broader than what is traditionally used for RL gaming AI. This paper considers the implications of observation representation and reward design for the AI agent and associated actions in the context of 2-player battlefield-type games that are not strictly zero-sum. Semi-cooperative and fully competitive models are considered. The environment in these games is a spatially extended battlefield in which agents must maneuver their forces to bring them into combat range of each other. The objective of the game is control over a pre-specified location in the game, and combat is executed via Lanchester attrition. We demonstrate the impact of aggregation on stochasticity of the model, where aggregation of the state model is controlled by various entropy-based metrics, as well as on the policy learned by an RL agent. Generalizations to alternative scenarios and objectives are discussed, as well as applications to the development of an AI combat opponent that can cohesively manage its forces over multiple scales.

Collaborative museum heist with reinforcement learning

AbstractNon‐playable characters (NPCs) play a crucial role in enhancing immersion in video games. However, traditional NPC behaviors are often hard‐coded using methods such as Finite State Machines, Decision and Behavior trees. This has a few limitations; namely, it is quite difficult to implement complex cooperative behaviors and secondly this makes it easy for human players to identify and exploit patterns in behavior. To overcome these challenges, Reinforcement learning (RL) can be used to generate dynamic and real‐time NPC responses to human player actions. In this paper, we report on first results of applying RL techniques to a Non‐Zero Sum, adversarial asymmetric game, using a multi‐agent team. The game environment simulates a museum heist, where the objective of the successfully trained team of robbers with different skills (Locksmith, Technician) is to steal valuable items from the museum without being detected by the scripted security guards and cameras. Both agents were trained concurrently with separate policies and received both individual and group reward signals. Through this training process, the agents learned to cooperate effectively and use their skills to maximize both individual and team benefits. These results demonstrate the feasibility of realizing the full game where both robbers and security guards are trained at the same time to achieve their adversarial goals.

Curriculum based Reinforcement Learning for traffic simulations

Non-Playable Characters (NPCs) are essential for creating a fully immersive video game experience. However, their behaviours are typically programmed using rigid methods such as Finite State Machines and Behaviour Trees. These methods are hard to maintain, struggle with implementing intricate cooperative behaviours, and patterns in NPC behaviour can easily be exploited by human players. Machine Learning and Reinforcement Learning (RL) methods in particular, offer a solution to these challenges by allowing dynamic and real-time NPC responses to human player actions and other characters in the game. This work describes and extends upon a Curriculum-based RL approach to train a single model for multiple agents representing vehicles to respect traffic regulations. These vehicles learn to navigate a road network which includes a traffic lights crossroad intersection and a roundabout junction. A comparison of our simulated data against datasets obtained from real world data is conducted; results demonstrate that the learned models have similar trends to the real-world data.

Performance indicators to be explored in order to win Premier League matches

Football is a dynamic collective sport that involves the actions of players on the field, in addition to the availability and application of player data. Being a sport extensively investigated in terms of performance analysis, there is still a need for more predictive analyzes to better understand the indicators of success. Due to these aspects, this research aimed to verify the influence of the market value of football clubs, as well as the influence of the venue and the tactical/technical aspects - shots on target, corners, crosses, ball possession and passes -, to win Premier League matches. To carry out this research, data from all 380 matches of the PL 2015/2016 season were used. The Transfermarkt website was used to collect the market value of the teams and the Daily Mail website to collect the matches data. Data analysis was performed using the Weka software. The results showed that the market value and the venue, separately, were not relevant to the victories, but when associated to tactical/technical indicators, both contributed with the victories of the teams. Concept A teams, with higher market values, achieved more victories than the concept C teams, with lower market values, in the home games when the aforementioned associations were analyzed. The results of the performed analyzes show that direct and indirect game actions are relevant for teams to win matches played at home, especially for the ones with higher market value.

A Game Representation for a Finite Horizon State Constrained Continuous Time Linear Regulator Problem

A supremum-of-quadratics representation for a class of extended real valued barrier functions is developed and applied in the context of solving a continuous time linear regulator problem subject to a single state constraint of bounded norm. It is shown that this very simple state constrained regulator problem can be equivalently formulated as an unconstrained two-player game. By demonstrating equivalence of the upper and lower values, and exploiting existence and uniqueness of the optimal actions for both players, state feedback characterizations for the corresponding optimal policies for both players are developed. These characterizations are illustrated by a simple example.

Protocol for the Assessment of Individual Tactical Behavior (PADTI) – validation and reproducibility: preliminary evidence

In order to carry out the process of validation and reproducibility of the Protocol for the Assessment of Individual Tactical Behavior of Soccer athletes (PADTI), a study was carried out divided into three stages: I) preparation of the PADTI; II) logical, content and construct validation and; III) reproducibility. The PADTI was developed based on the 8 fundamental tactical principles of soccer, which were inserted in a Microsoft Excel® spreadsheet, used to collect, store and process the tactical actions of soccer players during the game. The PADTI validity process was performed by 8 professionals, using a spreadsheet to account for items using a Likert scale (5 points). Reproducibility was carried out in two moments with an interval of 15 days, using as a sample the tactical behaviors of the athletes of the Brazilian team, during a soccer match of the 2018 world cup. validity (IV) of 90%. There were no significant differences between the responses of the evaluators (χ² = 12.199; p = 0.094). The intraclass correlation (ICC) values were greater than 0.814 (CI: 95%: 0.251 - 0.954; p <0.001) and Cronbach's Alpha values were greater than α = 0.814. The results indicated that the PADTI is a valid and useful methodology for assessing the tactical performance of soccer players in a game situation.

Analysis of Movement and Activities of Handball Players Using Deep Neural Networks

This paper focuses on image and video content analysis of handball scenes and applying deep learning methods for detecting and tracking the players and recognizing their activities. Handball is a team sport of two teams played indoors with the ball with well-defined goals and rules. The game is dynamic, with fourteen players moving quickly throughout the field in different directions, changing positions and roles from defensive to offensive, and performing different techniques and actions. Such dynamic team sports present challenging and demanding scenarios for both the object detector and the tracking algorithms and other computer vision tasks, such as action recognition and localization, with much room for improvement of existing algorithms. The aim of the paper is to explore the computer vision-based solutions for recognizing player actions that can be applied in unconstrained handball scenes with no additional sensors and with modest requirements, allowing a broader adoption of computer vision applications in both professional and amateur settings. This paper presents semi-manual creation of custom handball action dataset based on automatic player detection and tracking, and models for handball action recognition and localization using Inflated 3D Networks (I3D). For the task of player and ball detection, different configurations of You Only Look Once (YOLO) and Mask Region-Based Convolutional Neural Network (Mask R-CNN) models fine-tuned on custom handball datasets are compared to original YOLOv7 model to select the best detector that will be used for tracking-by-detection algorithms. For the player tracking, DeepSORT and Bag of tricks for SORT (BoT SORT) algorithms with Mask R-CNN and YOLO detectors were tested and compared. For the task of action recognition, I3D multi-class model and ensemble of binary I3D models are trained with different input frame lengths and frame selection strategies, and the best solution is proposed for handball action recognition. The obtained action recognition models perform well on the test set with nine handball action classes, with average F1 measures of 0.69 and 0.75 for ensemble and multi-class classifiers, respectively. They can be used to index handball videos to facilitate retrieval automatically. Finally, some open issues, challenges in applying deep learning methods in such a dynamic sports environment, and direction for future development will be discussed.