Search Results (291)

Malicious programs, commonly called malware, have had a pervasive presence in the world for nearly forty years and have continued to evolve and multiply exponentially. On the other hand, there are multiple research works focused on malware detection with different strategies that seem to work only temporarily, as new attack tactics and techniques quickly emerge. There are increasing proposals to analyze the problem from the attacker’s perspective, as suggested by MITRE ATT&CK. This article presents a proposal that utilizes Large Language Models (LLMs) to generate malware and understand its generation from the perspective of a red team. It demonstrates how to create malware using current models that incorporate censorship, and a specialized model is trained (fine-tuned) to generate code, enabling it to learn how to create malware. Both scenarios are evaluated using the $pass@k$ metric and a controlled execution environment (malware lab) to prevent its spread. Full article

Background: Training planning in military environments is complex due to diverse operational demands and constant exposure to stressors. When combined with high training volumes and insufficient recovery, this can result in physical and mental overload. Regular assessments are crucial to monitor the condition of personnel and adjust training accordingly, though more research is needed to effectively track performance in real operational settings. Objectives: This study aims to monitor neuromuscular and psychological performance in relation to training load in a military school, addressing the research gap in tracking performance in operational settings. Methods: Overall, 27 marines (age: 27.9 ± 4.8 years; height: 178.1 ± 6.3 cm; weight: 79.1 ± 7.8 kg) were monitored over a 13-week academic-military training period to assess neuromuscular performance and psychological fatigue. Results: Laboratory tests included the countermovement jump (p = 0.002), isometric mid-thigh pull (p = 0.001), and handgrip strength for both dominant (p = 0.947) and non-dominant hands (p = 0.665). Field tests involved maximum pull-ups (p = 0.015), push-ups (p = 0.001), and the medicine ball throw (p = 0.334). Psychological evaluation via the POMS questionnaire showed the highest negative mood scores in Tension–Anxiety, Depression–Melancholia, and Fatigue–Inertia, while Vigor–Activity was the highest positive state. RESTQ-Sport results indicated total recovery was 68.9% greater than total stress. Conclusions: Despite improvements in some field tests, no significant neuromuscular gains were observed, likely due to excessive training loads, limited recovery, and sustained stress. Full article

The progression of content during the training and development of young athletes is essential, while considering the developmental stages of the students/athletes. Therefore, it is crucial to monitor training sessions to ensure that content progression is followed and to assess how it is implemented. The aim of this study was to analyze the associations between different male categories of sports development in basketball through pedagogical variables and external loads planned by the coaches. The sample consisted of 148 sessions and 896 tasks, and the SIATE tool was used to observe both the pedagogical variables and the primary external load variables. Significant differences were observed primarily in the U16 category compared to the U12 and U14 categories. In examining the pedagogical variables, three key aspects were highlighted: content type, training methods, and level of opposition. The external load variables were aligned with the pedagogical variables, suggesting a progression of content. This indicates that instruction should follow an order, in which tactical load evolves from the simplest to the most complex, in accordance with the development and training stage of the students/athletes. The analyzed male basketball team demonstrated a content progression focused on the comprehensive development of the student/athlete, encouraging decision-making, and creating a complex, unpredictable, and random environment that closely resembles the dynamics of the real game. Full article

As cyber threats such as phishing and ransomware continue to escalate, healthcare systems are facing significant challenges in protecting sensitive data and ensuring operational continuity. This study explores how email communication practices influence cybersecurity in Saudi Arabia’s healthcare sector, particularly within the framework of rapid digitalisation under Vision 2030. The research employs a qualitative approach, with semi-structured interviews conducted with 40 healthcare professionals across various hospitals. A phenomenological analysis of the data revealed several key vulnerabilities, including inconsistent cybersecurity training, a reliance on informal messaging apps, and limited awareness of phishing tactics. The inconsistent cybersecurity training across regions emerged as a major weakness affecting overall resilience. These findings, grounded in rich qualitative data, offer a significant standalone contribution to understanding cybersecurity in healthcare settings. The findings highlight the need for mandatory training and awareness programmes and policy reforms to enhance cyber resilience within healthcare settings. Full article

Unmanned aerial vehicles (UAVs) are widely used in surveillance and combat for their efficiency and autonomy, whilst complex, dynamic environments challenge the modeling of inter-agent relations and information transmission. This research proposes a novel UAV tactical choice-making algorithm utilizing graph neural networks to tackle these challenges. The proposed algorithm employs a graph neural network to process the observed state information, the convolved output of which is then fed into a reconstructed critic network incorporating a Laplacian convolution kernel. This research first enhances the accuracy of obtaining unstable state information in hostile environments. The proposed algorithm uses this information to train a more precise critic network. In turn, this improved critic network guides the actor network to make decisions that better meet the needs of the battlefield. Coupled with a policy transfer mechanism, this architecture significantly enhances the decision-making efficiency and environmental adaptability within the multi-agent system. Results from the experiments show that the average effectiveness of the proposed algorithm across the six planned scenarios is 97.4%, surpassing the baseline by 23.4%. In addition, the integration of transfer learning makes the network convergence speed three times faster than that of the baseline algorithm. This algorithm effectively improves the information transmission efficiency between the environment and the UAV and provides strong support for UAV formation combat. Full article

The development of Global Positioning System (GPS) technology has contributed in various ways to improving the physical condition of modern football players by enabling the quantification of physical load. Previous studies have reported that the running demands of matches vary depending on playing position and formation. Over the past decade, despite the widespread use of GPS technology, studies that have investigated the running performance of young football players within the 1-4-3-3 formation are particularly limited. Therefore, the aim of the present study was to create the match running profile of playing positions in the 1-4-3-3 formation among high-level youth football players. An additional objective of the study was to compare the running performance of players between the two halves of a match. This study involved 25 football players (Under-19, U19) from the academy of a professional football club. Data were collected from 18 league matches in which the team used the 1-4-3-3 formation. Positions were categorized as Central Defenders (CDs), Side Defenders (SDs), Central Midfielders (CMs), Side Midfielders (SMs), and Forwards (Fs). The players’ movement patterns were monitored using GPS devices and categorized into six speed zones: Zone 1 (0.1–6 km/h), Zone 2 (6.1–12 km/h), Zone 3 (12.1–18 km/h), Zone 4 (18.1–21 km/h), Zone 5 (21.1–24 km/h), and Zone 6 (above 24.1 km/h). The results showed that midfielders covered the greatest total distance (p = 0.001), while SDs covered the most meters at high and maximal speeds (Zones 5 and 6) (p = 0.001). In contrast, CDs covered the least distance at high speeds (p = 0.001), which is attributed to the specific tactical role of their position. A comparison of the two halves revealed a progressive decrease in the distance covered by the players at high speed: distance in Zone 3 decreased from 1139 m to 944 m (p = 0.001), Zone 4 from 251 m to 193 m (p = 0.001), Zone 5 from 144 m to 110 m (p = 0.001), and maximal sprinting (Zone 6) dropped from 104 m to 78 m (p = 0.01). Despite this reduction, the total distance remained relatively stable (first half: 5237 m; second half: 5046 m, p = 0.16), indicating a consistent overall workload but a reduced number of high-speed efforts in the latter stages. The results clearly show that the tactical role of each playing position in the 1-4-3-3 formation, as well as the area of the pitch in which each position operates, significantly affects the running performance profile. This information should be utilized by fitness coaches to tailor physical loads based on playing position. More specifically, players who cover greater distances at high speeds during matches should be prepared for this scenario within the microcycle by performing similar distances during training. It can also be used for better preparing younger players (U17) before transitioning to the U19 level. Knowing the running profile of the next age category, the fitness coach can prepare the players so that by the end of the season, they are approaching the running performance levels of the next group, with the goal of ensuring a smoother transition. Finally, regarding the two halves of the game, it is evident that fitness coaches should train players during the microcycle to maintain high movement intensities even under fatigue. Full article

Background/Objectives: This scoping review critically evaluated existing literature and summarized the impact of occupational, physiological, and psychological stressors on adrenal and neuroendocrine responses, body composition, and physical performance amongst women in tactical occupations. Methods: Boolean searches identified potentially qualifying reports involving: (1) adult women (≥19 y) currently employed or completing their training for a tactical profession; (2) ≥1 marker of “stress”; and (3) ≥1 adrenal, neuroendocrine, body composition, or fitness/performance outcome. Quantitative data (e.g., sample characteristics, outcomes of interest) were extracted and summarized. The completeness of reporting for each study was documented using existing checklists and quantified as: low (<50%), moderate (50–79%), or high (≥80%). Results: 40 studies (k) of moderate reporting quality (~64%) were included in the final sample (3693 women); 11 studies (28%) focused on women exclusively, and 16 studies identified sex differences in ≥1 outcome. Most studies involved military trainee populations (80%, k = 32). Occupation-related stress tended to negatively impact adrenal, neuroendocrine, body composition, and performance outcomes. Conclusions: This review highlights progress in assessing occupational performance in female tactical personnel exposed to diverse stressors; however, our understanding remains incomplete due to methodological and conceptual limitations in the literature. Holistic research strategies are needed to capture the complexity of performance readiness in women, integrating how stress affects key tactical performance aspects such as muscle physiology, reproductive health, and energy and nutrient balance in realistic operational contexts. Integrating such data is vital for informing policy, improving readiness, and enhancing the health and career longevity of female tactical personnel. Full article

Football performance results from the dynamic interaction between physical, tactical, technical, and psychological dimensions—each of which also influences player well-being, recovery, and readiness. However, integrated monitoring approaches remain scarce, particularly in youth and sub-elite contexts. This systematic review screened 341 records from PubMed, Scopus, and Web of Science, with 46 studies meeting the inclusion criteria (n = 1763 players; age range: 13.2–28.7 years). Physical external load was reported in 44 studies using GPS-derived metrics such as total distance and high-speed running, while internal load was examined in 36 studies through session-RPE (rate of perceived exertion × duration), heart rate zones, training impulse (TRIMP), and Player Load (PL). A total of 22 studies included well-being indicators capturing fatigue, sleep quality, stress levels, and muscle soreness, through tools such as the Hooper Index (HI), the Total Quality Recovery (TQR) scale, and various Likert-type or composite wellness scores. Tactical behaviours (n = 15) were derived from positional tracking systems, while technical performance (n = 7) was assessed using metrics like pass accuracy and expected goals, typically obtained from Wyscout^® or TRACAB^® (a multi-camera optical tracking system). Only five studies employed multivariate models to examine interactions between performance domains or to predict well-being outcomes. Most remained observational, relying on descriptive analyses and examining each domain in isolation. These findings reveal a fragmented approach to player monitoring and a lack of conceptual integration between physical, psychological, tactical, and technical indicators. Future research should prioritise multidimensional, standardised monitoring frameworks that combine contextual, psychophysiological, and performance data to improve applied decision-making and support player health, particularly in sub-elite and youth populations. Full article

Multiple-resolution modeling (MRM) has emerged as a foundational paradigm in modern simulation, enabling the integration of models with varying levels of granularity to address complex and evolving operational demands. By supporting seamless transitions between high-resolution and low-resolution representations, MRM facilitates scalability and interoperability, particularly within distributed simulation environments such as military command and control systems. This paper provides a structured review and comparative analysis of prominent MRM methodologies, including multi-resolution entities (MRE), agent-based modeling (from a federation viewpoint), hybrid frameworks, and the novel MR mode, synchronizing resolution transitions with time advancement and interaction management. Each approach is evaluated across critical dimensions such as consistency, computational efficiency, flexibility, and integration with legacy systems. Emphasis is placed on the applicability of MRM in distributed military simulations, where it enables dynamic interplay between strategic-level planning and tactical-level execution, supporting real-time decision-making, mission rehearsal, and scenario-based training. The paper also explores emerging trends involving artificial intelligence (AI) and large language models (LLMs) as enablers for adaptive resolution management and automated model interoperability. Full article

Mammography is the main method for early detection of breast cancer, which is still a major global health concern. However, inter-reader variability and the inherent difficulty of interpreting subtle radiographic features frequently limit the accuracy of diagnosis. A thorough assessment of deep convolutional neural networks (CNNs) for automated mammogram classification is presented in this work, along with the introduction of two innovative multi-view integration techniques: Dual-Branch Ensemble (DBE) and Merged Dual-View (MDV). By setting aside two datasets for out-of-sample testing, we evaluate the generalizability of the model using six different mammography datasets that represent various populations and imaging systems. We compare a number of cutting-edge architectures on both individual and combined datasets, including ResNet, DenseNet, EfficientNet, MobileNet, Vision Transformers, and VGG19. Both MDV and DBE strategies improve classification performance, according to experimental results. VGG19 and DenseNet both obtained high ROC AUC scores of 0.9051 and 0.7960 under the MDV approach. DenseNet demonstrated strong performance in the DBE setting, achieving a ROC AUC of 0.8033, while ResNet50 recorded a ROC AUC of 0.8042. These enhancements demonstrate how beneficial multi-view fusion is for boosting model robustness. The impact of domain shift is further highlighted by generalization tests, which emphasize the need for diverse datasets in training. These results offer practical advice for improving CNN architectures and integration tactics, which will aid in the creation of trustworthy, broadly applicable AI-assisted breast cancer screening tools. Full article

This study examined the effects of a short-term ballistic training program on neuromuscular performance and strength-deficit (SDef) in elite youth female soccer players. Twenty-two under-20 athletes completed a 4-week intervention during the pre-season phase, comprising 12 loaded and 8 unloaded ballistic training sessions performed at maximal intended velocity. Pre- and post-intervention assessments included vertical jumps (squat jump [SJ], countermovement jump [CMJ]), sprinting speed (5, 10, and 20 m), one-repetition maximum (1RM) and peak force (PF) in the half-squat (HS), and peak power and velocity during jump squats (JS) at 30% of 1RM. SDef was calculated as the percentage difference in PF between 1RM in the HS and 30% 1RM. Significant improvements were observed in SJ, CMJ, sprint speed, 1RM-strength, and bar-derived mechanical outputs (ES = 1.18–1.66; p < 0.05), with no significant changes in SDef. These results indicate that elite youth female soccer players can improve strength-, power-, and speed-related capacities without compromising force production at higher movement velocities (thus maintaining their SDef). The improvements observed likely reflect the combined effect of a high-frequency, velocity-oriented training approach and a concurrent reduction in traditional technical–tactical (i.e., soccer-specific) training volume. This is the first study to demonstrate that ballistic exercises alone—when properly structured—can enhance neuromuscular performance in female soccer players without increasing SDef. These findings provide practical guidance for practitioners aiming to optimize physical development in team-sport athletes without relying on heavier training loads or extended resistance training sessions—and, especially, without compromising their ability to apply force at higher velocities. Full article

The rapid proliferation of wearable sensors and advanced tracking technologies has revolutionized data collection in elite sports, enabling continuous monitoring of athletes’ physiological and biomechanical states. This study proposes a comprehensive big data analytics framework that integrates data acquisition, processing, analytics, and decision support, demonstrated through synthetic datasets in football, basketball, and athletics case scenarios, modeled to represent typical data patterns and decision-making workflows observed in elite sport environments. Analytical methods, including gradient boosting classifiers, logistic regression, and multilayer perceptron models, were employed to predict injury risk, optimize in-game tactical decisions, and personalize sprint mechanics training. Key results include a 12% reduction in hamstring injury rates in football, a 16% improvement in clutch decision-making accuracy in basketball, and an 8% decrease in 100 m sprint times among athletes. The framework’s visualization tools and alert systems supported actionable insights for coaches and medical staff. Challenges such as data quality, privacy compliance, and model interpretability are addressed, with future research focusing on edge computing, federated learning, and augmented reality integration for enhanced real-time feedback. This study demonstrates the potential of integrated big data analytics to transform sports performance optimization, offering a reproducible and ethically sound platform for advancing personalized, data-driven athlete management. Full article

College student military training is an organized, high-intensity, short-term militarized activity in China; this study aims to explore the differences in thermal perception between different intensities of military training. Questionnaires and microclimate measurements were conducted during summer military training in cold regions, including the Protective and Rescue Training and Assessment (PRTA), Formation Training (FT), the Shooting and Tactical Training and Assessment (STTA), the Route March (RM), and Dagger Practice (DP). The results indicated that (1) there was no significant correlation between the intensity of the activity and votes on thermal perception. The strongest thermal sensations, the lowest comfort, and the lowest thermal acceptability were experienced during FT, with a lower activity intensity. (2) Air temperature (T_a), globe temperature (T_g), relative humidity (RH), mean radiant temperature (T_mrt), and solar radiation (G) had significant effects on the TSV. (3) FT involved the lowest neutral temperatures (NUTCI/NPET), while DP and RM training had the highest NUTCI and NPET values, respectively. The neutral temperature range during military training was narrower compared to that in other aerobic activities. This study reveals, for the first time, the non-traditional correlation between military training intensity and thermal perception, confirming the specificity of thermal sensations in mandatory training and providing a theoretical basis for optimizing military training arrangements and developing thermal protection strategies. Full article

Background and Objective: Match analysis plays a vital role in forming the scientific foundation of training and guiding strategic decision-making in wrestling. By objectively evaluating athletes’ technical and tactical performances, coaches and athletes can optimize preparation and in-match strategies. This study aimed to analyze the technical and tactical characteristics of medal matches in Greco-Roman (GR), Freestyle (FS), and Women’s Wrestling (WW) at the 2024 European Wrestling Championships. Methods: A total of 54 elite-level matches (18 from each style), held in Bucharest between 12 and 18 February, 2024, were retrospectively analyzed. Three expert observers evaluated the matches using video footage from the United World Wrestling (UWW) archive. Descriptive statistics were performed using SPSS 25.0. Results: Across 301 recorded actions, 2-point techniques (52.16%) and 1-point techniques (43.85%) were dominant; only 3.99% were 4-point actions. GR primarily utilized body lock and gut wrench; FS favored single-leg attacks and leg lace. In WW, the scores were obtained from techniques applied in the par terre position with a high frequency (60.8%). Most victories in all styles occurred by points rather than technical superiority or falls. Conclusion: The findings reveal a strategic preference for low-risk, controlled techniques in high-level matches. These insights can inform evidence-based training and match preparation for future championships. Full article

Olympic women’s judo has increased in complexity and competitiveness, demanding detailed tactical analysis. This observational study aimed to examine the relationship between the results of combats (Wazari [half point] vs. Ippon [full point]) and the techniques used in women’s judo combats in the Rio 2016 and Tokyo 2020 Olympic Games. A significant association was found between technique type and contest outcome (χ² = 40.004, df = 6, p < 0.001): Nage Waza (throwing techniques) produced 92.3% of Wazari, whereas Katame Waza (groundwork techniques) accounted for 61.1% of Ippon. Subgroup analysis confirmed these relationships (χ² = 17.217, df = 6, p = 0.009; Cramer’s V = 0.745), with Ashiwaza (foot/leg techniques) dominating Wazari. Uchimata was the most frequently used technique in the repechage (20%), bronze medal (22.6%), and final (23.1%) matches. In lightweights, Katame Waza dominated Ippon in finals (53.8%, χ² = 4.000, p = 0.046), while Nage Waza secured all Wazari. Middleweights also showed strong associations (χ² = 14.745, df = 1, p < 0.001; 93.9% of Wazari by Nage Waza). Although no significant association was found for heavyweights (χ² = 7.535, df = 1, p = 0.095), Katame Waza prevailed in Ippon (69.2%). These findings provide a tactical framework for tailoring technique-specific training by weight category and tournament phase to optimize outcomes in elite female judo. Full article