Search Results (2,603)

Intense physical activity imposes substantial oxidative, metabolic, and immunological stress on the human body. It is often accompanied by reductions in plasma glutamine levels, making this amino acid conditionally essential. Glutamine plays a vital role in energy production, nitrogen transport, acid–base balance, antioxidant defense, and immune function. It is required in the biosynthesis of neurotransmitters, nucleotides, nicotinamide-derived coenzymes, glutathione, and hexosamines, making it a candidate for supporting exercise recovery. In addition, glutamine may support key mechanisms involved in muscle adaptation and recovery during exercise-induced stress by contributing to redox balance, energy sensing, anabolic signaling, intestinal barrier integrity, and immune function. This narrative review aims to synthesize biochemical mechanisms underlying glutamine effects relevant to exercise and evaluate preclinical and clinical findings on supplementation outcomes, with emphasis on timing strategies. Preclinical findings demonstrate that glutamine can modulate protein synthesis, reduce oxidative stress, improve intestinal integrity, and attenuate immune and inflammatory disturbances. Limited preclinical data suggest that post-exercise supplementation may better resolve muscle and organ damage. Clinical trials, however, report heterogeneous outcomes: several studies show improvements in markers of intestinal permeability and intestinal epithelial damage, oxidative stress, muscle damage, and inflammation, whereas others report minimal or no effect, including limited influence on performance outcomes. Variability in timing protocols, participant characteristics, and measured endpoints contributes to inconsistent findings. Overall, glutamine demonstrates several biologically plausible mechanisms that could support recovery and overall health in active individuals, athletes, and specific clinical populations. However, current evidence remains insufficient to determine clear supplementation benefits or define an optimal timing strategy. Future research using standardized protocols and integrated biochemical and functional endpoints is needed to clarify timing effects. Until such evidence emerges, recommendations should remain individualized, considering athlete-specific needs. Full article

Integrating Software-Defined Networking (SDN) to enhance mobility management in Vehicular Ad Hoc Networks (VANETs) comes with an additional critical risk. Because centralized controllers are single points of failure, they create the risk that the network will be subject to denial-of-service (DoS) attacks during handovers. Most Intrusion Detection and Prevention systems (IDPSs) do not adequately address these risks because they are topology-blind and have excessive processing layers. This article presents a novel Location-Aware SDN-IDPS Framework that employs a hierarchical defense approach to protect vehicular networks against volumetric attacks. This two-plane system operates with the first tier, which uses dynamic host-location mappings to drop spoofed traffic at the switch level (data plane). In contrast, the second tier analyzes confirmed traffic through a Suricata-based engine to identify and respond to complex flood attack patterns. The experimental results from the Mininet-WiFi testbed show that the system provides a significant improvement over the unprotected state, with controller CPU utilization reduced by up to 18 times (from 9.0% to below 0.5%). In addition, the system provides a 2.3 s guaranteed recovery time, service continuity, successful microsecond-level mitigation time, and a packet delivery ratio (PDR) of 99.73% for legitimate safety messages. In control-plane stress testing, the proposed location-aware logic improved throughput stability by approximately 76.26% compared to the baseline. These findings confirm that offloading anti-spoofing logic to the network edge significantly enhances resilience without compromising performance in safety-critical vehicular environments. Full article

Simulation-based training systems are increasingly deployed to prepare learners for complex, safety-critical, and dynamic work environments. While advances in computing have enabled immersive and data-rich simulations, many systems remain optimized for procedural accuracy and surface-level task performance rather than the macrocognitive processes that underpin adaptive expertise. Macrocognition encompasses higher-order cognitive processes that are essential for performance transfer beyond controlled training conditions. When these processes are insufficiently supported, training systems risk fostering brittle strategies and negative training effects. This paper introduces a macrocognitive design taxonomy for simulation-based training systems derived from a large-scale meta-analysis examining the transfer of macrocognitive skills from immersive simulations to real-world training environments. Drawing on evidence synthesized from 111 studies spanning healthcare, industrial safety, skilled trades, and defense contexts, the taxonomy links macrocognitive theory to human–computer interaction (HCI) design affordances, computational data traces, and feedback and adaptation mechanisms shown to support transfer. Grounded in joint cognitive systems theory and learning engineering practice, the taxonomy treats macrocognition as a designable and computable system concern informed by empirical transfer effects rather than as an abstract explanatory construct. Full article

Against the backdrop of global climate change, the rising frequency and intensity of extreme weather events pose severe challenges to urban transport and commercial systems. As a core capacity for managing uncertainty and risk, urban resilience requires infrastructure to resist shocks, recover rapidly, and adaptively evolve. From a resilience perspective, this study develops a comprehensive evaluation system for spatial accessibility between subway stations and commercial complexes, operationalized by 21 indicators across five dimensions: Connectivity, Redundancy, Robustness, Dynamic adaptability, and Comfort. Spatial accessibility is simulated and measured using sDNA spatial network analysis, while an in-depth questionnaire survey collects, feeds back, and validates users’ subjective perceptions. By constructing a dual evaluation model that integrates spatial configuration and behavioral psychology, we find that the integrated development of subway stations and commercial complexes can maintain stable functional performance and sustained vitality under complex urban conditions by optimizing connectivity, enhancing redundancy, and improving adaptability. This is manifested in the expansion of residents’ pedestrian networks and the spillover of social service functions. In parallel, underground spaces can be transformed into resilient infrastructure to enhance civil air defense performance and provide diversified evacuation routes. The findings offer theoretical support and practical guidance for the construction of resilient cities. Full article

Understanding the chronic thermal acclimation capacity of chum salmon (Oncorhynchus keta) is essential for predicting species resilience and developing mitigation strategies under ocean warming. We investigated the upper limit of chronic thermal acclimation and its underlying molecular mechanisms in chum salmon smolts exposed to four constant temperatures (10, 14, 18, and 22 °C) for 6 weeks. Transcriptional responses of genes related to cellular stress protection, endocrine feedback regulation, antioxidant defense, metabolic regulation (AMPKα and mTOR), and protein degradation were quantified in the liver, skeletal muscle, and brain. Chronic exposure to elevated temperature elicited tissue-specific molecular responses, with the most pronounced effects observed at 22 °C. At this temperature, all tissues showed marked induction of heat shock proteins and ubiquitin, accompanied by suppression of antioxidant defenses, glucocorticoid receptor signaling, and AMPKα–mTOR-mediated metabolic regulation, particularly in the liver and muscle. These responses were consistent with previously reported impairments in growth performance, lipid reserves, and hematological indices from the same growth trial. In contrast, smolts maintained at 18 °C exhibited molecular signatures indicative of effective physiological compensation without severe cellular stress. Collectively, these results indicate that chum salmon smolts can acclimate to chronic warming up to 18 °C, whereas exposure to 22 °C exceeds their acclimation capacity and induces a tertiary stress response. Full article

The rapid adoption of large language models (LLMs) in corporate and governmental systems has raised critical security concerns, particularly prompt injection attacks exploiting LLMs’ inability to differentiate control instructions from untrusted user inputs. This study systematically benchmarks neural network architectures for malicious prompt detection, emphasizing robustness against character-level adversarial perturbations—an aspect that remains comparatively underemphasized in the specific context of prompt-injection detection despite its established significance in general adversarial NLP. Using the Malicious Prompt Detection Dataset (MPDD) containing 39,234 labeled instances, eight architectures—Dense DNN, CNN, BiLSTM, BiGRU, Transformer, ResNet, and character-level variants of CNN and BiLSTM—were evaluated based on standard performance metrics (accuracy, F1-score, and AUC-ROC), adversarial robustness coefficients against spacing and homoglyph perturbations, and inference latency. Results indicate that the word-level 3_Word_BiLSTM achieved the highest performance on clean samples (accuracy = 0.9681, F1 = 0.9681), whereas the Transformer exhibited lower accuracy (0.9190) and significant vulnerability to spacing attacks (adversarial robustness ${\mathsf{\rho }}_{spacing}=0.61$). Conversely, the Character-level BiLSTM demonstrated superior resilience (${\mathsf{\rho }}_{spacing}=1.0$, ${\mathsf{\rho }}_{homoglyph}=0.98$), maintaining high accuracy (0.9599) and generalization on external datasets with only 2–4% performance decay. These findings highlight that character-level representations provide intrinsic robustness against obfuscation attacks, suggesting Char_BiLSTM as a reliable component in defense-in-depth strategies for LLM-integrated systems. Full article

Background: Artificial Intelligence (AI) and Machine Learning (ML) are increasingly integrated into sport and exercise through wearable biosensing systems that enable continuous monitoring and data-driven training adaptation. However, their practical value for coaching depends on the validity of biosensor data, the robustness of analytical models, and the conditions under which these systems have been empirically evaluated. Methods: A structured narrative review was conducted using Scopus, PubMed, Web of Science, and Google Scholar (2010–2026), synthesising empirical and applied evidence on wearable biosensing, signal processing, and ML-based adaptive training systems. To enhance transparency, an evidence map of core empirical studies was constructed, summarising sensing modalities, cohort sizes, experimental settings (laboratory vs. field), model types, evaluation protocols, and key outcomes. Results: Evidence from field and laboratory studies indicates that wearable biosensors can reliably capture physiological (e.g., heart rate variability), biomechanical (e.g., inertial and electromyographic signals), and biochemical (e.g., sweat lactate and electrolytes) markers relevant to training load, fatigue, and recovery, provided that signal quality control and calibration procedures are applied. ML models trained on these data can support training adaptation and recovery estimation, with improved performance over traditional workload metrics in endurance, strength, and team-sport contexts when evaluated using athlete-wise or longitudinal validation schemes. Nevertheless, the evidence map also highlights recurring limitations, including sensitivity to motion artefacts, inter-session variability, distribution shift between laboratory and field settings, and overconfident predictions when contextual or psychosocial inputs are absent. Conclusions: Current empirical evidence supports the use of AI-driven biosensor systems as decision-support tools for monitoring and adaptive training, but not as autonomous coaching agents. Their effectiveness is bounded by sensor reliability, appropriate validation protocols, and human oversight. The most defensible model emerging from the evidence is human–AI collaboration, in which ML enhances precision and consistency in data interpretation, while coaches retain responsibility for contextual judgement, ethical decision-making, and athlete-centred care. Full article

There is considerable interest in the connection between alcohol-induced oxidative stress, DNA methylation, antioxidants, and accelerated aging across diverse populations. Nevertheless, self-reported alcohol consumption is prone to bias, and objective biomarkers of alcohol intake are needed. Our aims were to investigate the performance of an epigenomic biomarker of alcohol consumption in a Mediterranean population using self-reported data and the biomarker gamma-glutamyl transferase (GGT); to examine the effects of alcohol (self-reported and biomarker-assessed) on epigenome-wide methylation; to analyze the association between alcohol (self-reported and biomarker-assessed) and telomere length and other aging biomarkers; and to explore the modulating effect of the Mediterranean diet (MedDiet). We performed blood epigenome-wide methylation studies (EWAS) in a Mediterranean cohort (aged 55–75 years). Self-reported alcohol consumption and MedDiet were assessed by questionnaires. A replication cohort (cohort 2) from the same area was also analyzed. For both cohorts, the DNA methylation-based biomarker (450-CpGs) was computed alongside epigenetic clocks for the following biological age acceleration metrics: DNAm telomere length, GrimAgeAcceleration, PhenoAgeAcceleration, and CausalityAgeYing (cohort 1). The association between the epigenomic biomarker and self-reported alcohol consumption was significant (p < 0.001) in both cohorts, but modest. However, the association was stronger when predicting high alcohol intake (AUC: 0.76; 95%CI: 0.65–0.86; p < 0.0001). In the EWAS, the hit (cg06690548-SLC7A11, in a cystine transporter that enhances glutathione production for antioxidant defense) was shared among the self-reported alcohol consumption, GGT, and the epigenomic biomarker, with alcohol linked to hypomethylation. We detected differential methylation in pre-selected oxidative stress-related genes. Enrichment analysis revealed “Rap1 signaling pathway” as the hit (p < 0.00001). High self-reported alcohol consumption and the epigenomic biomarker were associated with shorter telomere length (p < 0.05) in cohort 1. Additionally, a modulation by Mediterranean diet adherence was hypothesized. No significant associations were found between self-reported alcohol intake and the other aging biomarkers; however, the epigenomic score was directly associated with GrimAge, PhenoAge and CausAgeYing biomarkers in cohort 1 (p < 0.001), and two were replicated in cohort 2. In conclusion, alcohol intake has an impact on DNA methylation at the epigenome-wide level in this Mediterranean population, replicating the main hits from other populations and validating the epigenomic biomarker for intake, although improvement is needed. Moreover, several associations with aging biomarkers were observed. Full article

Ransomware represents a critical and evolving cybersecurity threat that often evades traditional defenses during its early stages. We present a novel intelligent sensing framework (ISF) designed for proactive, early-stage ransomware detection, centered on a Multi-Head Self-Attention Long Short-Term Memory (MHSA-LSTM) sensor model. The core innovation of this sensor is its self-attention mechanism, which is augmented to autonomously prioritize the most discriminative behavioral features by incorporating a relevance coefficient derived from information gain ($\mu$), thereby filtering out noise and overcoming data scarcity inherent in initial attack phases. The framework was validated using a comprehensive dataset derived from the dynamic analysis of 39,378 ransomware samples and 9732 benign applications. The MHSA-LSTM sensor achieved superior performance, recording a peak accuracy of $98.4\%$, a low False Positive Rate (FPR) of $0.089$, and an F1 score of $0.972$ using an optimized 25-feature set. This performance consistently surpassed established sequence models, including CNN-LSTM and Stacked LSTM, confirming the significant potential of the ISF as a robust and scalable solution for enhancing defenses against modern, stealthy threats. Most significantly, integration of $\mu$ as a statistical anchor resulted in a 49% reduction in False Positive Rates (FPRs) compared to standard attention-based models. This addresses the main operational barrier to deploying deep learning sensors in live environments. Full article

Real-time telecom scam detection is difficult without cloud AI, particularly for privacy-sensitive, low-resource environments. We developed a lightweight, offline voice scam detector using on-device audio segmentation, automatic speech recognition (ASR), and semantic similarity. Four detection strategies were implemented. We used Whisper ASR and DeepSeek to process 5 s speech chunks. An analysis of 120 synthetic and paraphrased Mandarin phone call dialogues reveals the A4 voting strategy’s superior performance in optimizing early detection and minimizing false positives, achieving an F1 score of 0.90, a 2.5% false positive rate, and a mean response time of under 4 s. The system is deployable on ESP32 for offline mobile inference. The proposed architecture provides a robust and scalable defense against threats targeting vulnerable user groups, such as older adults. It introduces a new method for real-time voice threat mitigation on devices through interpretable segment-level semantic analysis. Full article

Wireless devices are increasingly used today, and the presence of vulnerabilities represents a significant risk to modern security systems. This study analyzes the different functionalities of the Flipper Zero device and its capability to compromise everyday systems. Through various tests and an exhaustive analysis of its infrared, RFID/NFC, sub-GHz, USB, and Bluetooth functionalities, several critical vulnerabilities were identified, such as access credential emulation and interference with remote control signals. These results demonstrate that the device is a highly versatile and useful tool for performing security audits, not only improving traditional testing methods but also opening new possibilities for developing more resilient defense systems. However, it also poses a potential risk if misused for malicious purposes. Full article

The influence of competitive standards on physical performance in professional football remains controversial, particularly when teams from different divisions compete against each other. This study aimed to analyze position-specific differences in physical performance, both in possession and out of possession, between Spanish First and Second Division teams during direct competition. Match data from 25 Copa del Rey fixtures across three seasons were analyzed using a validated multi-camera tracking system. Physical performance variables were examined according to playing position. First Division players accumulated greater total distance during in-possession phases, particularly central defenders (CDs), wide defenders (WDs), central midfielders (CMs), and wide midfielders (WMs), whereas Second Division players covered greater distances during out-of-possession phases, mainly CDs, WDs, and CMs. In addition, First Division CMs exhibited higher high-speed running in possession, while Second Division forwards (FWs) demonstrated greater high-speed running and defensive high-speed running. Differences in maximum velocity were also observed in CDs, with higher values recorded in the First Division. Overall, these findings indicate that physical performance is modulated by the competitive standard and playing position. However, the interpretation of these differences should not be dissociated from the tactical nature of football, as players’ specific positions and the tactical roles derived from them may condition the physical demands imposed during different phases of play, rather than reflecting isolated physical capacity. Full article

At present, active defense strategies based on digital watermarking mainly rely on post-event watermark extraction, which verifies the occurrence of deepfake events by measuring the degree of watermark degradation, or on adversarial watermarks to interfere with image generation. To overcome these limitations, we propose a unified watermarking framework that can restore the original content of images tampered with by deepfakes. This scheme integrates three core components: an encoder for watermark pre-embedding, a decoder for robust watermark extraction, and a face restorer for watermark-guided image restoration. Numerous experiments have shown that this method has achieved good results in terms of extraction accuracy and recovery performance, thereby verifying the effectiveness of this approach. Full article

The physiological mechanism of melatonin in alleviating combined saline-alkali stress in Fraxinus mandshurica remains unclear. This study aimed to determine the efficacy of exogenous melatonin in enhancing salt tolerance and elucidate the underlying mechanisms through integrated physiological and multi-omics analyses. Seedlings were subjected to 400 mmol L⁻¹ saline-alkali stress and treated with foliar melatonin. We quantified key growth indicators (height, diameter, dry biomass) and measured the activities of antioxidant enzymes (SOD, POD). Melatonin significantly alleviated growth inhibition, increasing biomass and height by 29% and 13%, respectively, while enhancing net photosynthetic rate and antioxidant capacity. To uncover the systemic regulation, conjoint analysis of transcriptome (RNA-seq) and metabolome data was performed. This integrated approach revealed that melatonin specifically activated common KEGG pathways pivotal for stress adaptation, including plant hormone signal transduction, phenylpropanoid biosynthesis, and starch and sucrose metabolism, with coordinated upregulation of associated genes and metabolites. Collectively, our integrated data demonstrate that melatonin enhances Fraxinus tolerance by synergistically improving photosynthesis and antioxidant defense, underpinned by a reconfigured molecular network. This study provides a theoretical basis for using melatonin as an eco-friendly biostimulant to improve woody plant resilience in saline-alkali soils. Full article

Soil salinity is a major constraint to strawberry cultivation, adversely affecting plant growth, yield, and fruit quality. Salinity stress triggers complex physiological and biochemical responses, including osmotic adjustment, antioxidant defense, ion homeostasis, and shifts in metabolite accumulation, ultimately reducing crop productivity and fruit quality. This review synthesizes current knowledge on strawberry responses to salinity, with emphasis on physiological mechanisms, genotypic variation in tolerance, and emerging biologically based approaches, such as biostimulants, small signaling molecules, and beneficial microorganisms, that alleviate salinity stress and enhance plant resilience. In parallel, recent advances in the identification of stress-responsive genes and regulatory pathways are discussed in the context of their relevance for breeding salt-resilient cultivars. This review also identifies critical gaps in current knowledge that, despite significant progress, hinder the translation of mechanistic insights into stable yield and fruit quality under field conditions. By integrating physiological knowledge with advances in biological and breeding-based approaches, together with long-term field validation, this review provides a comprehensive framework for improving strawberry performance under saline conditions and guiding future cultivation and genetic improvement strategies. Full article