Search Results (6,582)

6061 aluminum alloy is lightweight and has good thermal conductivity, while 304 stainless steel possesses excellent mechanical properties and corrosion resistance; both have broad application prospects in cooling circuits. Propylene glycol coolant shows great potential in liquid cooling systems due to its low toxicity and good antifreeze properties. However, during operation, galvanic corrosion may occur when the two metals come into direct contact within the coolant, thereby threatening system safety and service life. This study focuses on 6061 aluminum alloy, 304 stainless steel, and their galvanic couples. Electrochemical testing, SEM, 3D confocal microscopy, and XPS were used to systematically investigate their self-corrosion and galvanic corrosion behavior in propylene glycol coolant at pH values of 4.8, 6.8, and 8.8. The results indicate that 6061 aluminum alloy is more sensitive to pH changes; its corrosion resistance first increases and then decreases as pH rises, with the least corrosion occurring at pH = 6.8 and the most severe at pH = 4.8. 304 stainless steel exhibited lower corrosion rates at pH 6.8 and 8.8, but corrosion significantly worsened at pH 4.8. For the 6061 aluminum alloy/304 stainless steel couple, the galvanic current first decreased and then increased with rising pH, while the galvanic potential first increased and then decreased. The 6061 aluminum alloy consistently acted as the anode, and the 304 stainless steel consistently acted as the cathode, with the highest sensitivity to galvanic corrosion observed at pH 4.8. XPS analysis shows that under different pH conditions, the corrosion products of 6061 aluminum alloy are Al(OH)₃ and Al₂O₃, while the main components of the passivation film on 304 stainless steel remain unchanged. Full article

To address the critical challenges of multi-scale temporal dynamics and sensor-intrusiveness in driver fatigue detection, this paper proposes the Multi-Temporal Fusion Attention Network (MTFA-Net). The framework integrates two core innovations: a Multi-scale Temporal Adaptive Fusion (MTAF) module that dynamically weights short-, mid-, and long-term behavioral features via a scene-aware modulator, and a Physiological–Behavioral Cross-modal Adversarial Alignment (PBCAA) network that implicitly infers latent physiological states (e.g., HRV) from facial videos using adversarial learning and mutual information maximization. Experimental results on RLDD and NTHU-DDD datasets demonstrate that MTFA-Net achieves state-of-the-art accuracy (92.8%) while maintaining high interpretability and real-time efficiency, providing a robust, non-intrusive solution for intelligent cockpit safety. Full article

Although non-structural walls do not determine the structural safety of a building, they are responsible for its functionality by serving as acoustic, thermal, and fire-resistant partitions. They may be freely located and relocated and are typically constructed during the finishing stage of building works. Reliable performance of non-structural walls depends on appropriate connections to floors and adjacent walls. Connections to walls are most commonly achieved using traditional masonry bonding or sufficiently durable wall connectors, usually made of steel. An alternative to steel connectors may be connectors made of polymer-based materials or meshes. This paper proposes an innovative method for connecting non-structural masonry walls using a spatially arranged mesh, which serves not only as reinforcement of the wall connection but also as reinforcement of the bed joints. The aim of the study was to evaluate the effectiveness of this method in comparison with other connection techniques, including traditional solutions. Experimental investigations were carried out using an original test setup on 12 specimens made of AAC masonry units, divided into three series: series P—traditional connection (reference series), series H—connection with mesh placed in bed joints, and series SHP—connection with spatially arranged mesh. Silica Glass Mesh (SGM), intended for reinforcement of bed joints in AAC masonry, was used in the study. The experiments focused on the analysis of connection behavior and load-bearing capacity, with particular emphasis on maximum load values and failure mechanisms. Individual stages of the behavior of mesh-reinforced connections were identified, and empirical relationships enabling estimation of maximum loads were developed. The results confirmed that the traditional connection achieved the highest load-bearing capacity. However, as expected, the mesh-reinforced connections—particularly those with the spatial mesh arrangement—exhibited a more stable response and a greater ability for progressive load transfer. The SHP series connections with spatially arranged meshes exhibited significantly lower load-bearing capacity compared to the reference unreinforced connections, while at the same time demonstrating substantially greater deformability. The stiffness degradation in the mesh-reinforced connections did not occur abruptly, as observed in the reference models, which makes them an effective alternative for practical applications. Technical models for predicting forces and displacements of connections reinforced with spatially arranged meshes and meshes placed in bed joints were also developed. Full article

Essential oils are multicomponent natural products with potential neurobehavioral activity, but integrated comparative studies remain limited. This study compared the essential oils of Satureja brevicalyx, Peperomia dolabriformis, and Rosmarinus officinalis in relation to their chemical profiles, predicted target interactions, preliminary acute oral safety, anxiolytic-like and antidepressant-like effects, antagonist-sensitive behavioral patterns, and exploratory serum biomarkers. Oils were characterized by GC-MS, and their constituents were screened by molecular docking against anxiety-, depression-, sleep-, and stress-related targets. Independent cohorts of male BALB/c mice received oral essential oils (25–100 mg/kg) and were assessed in anxiety-related, depression-related, and locomotor behavioral paradigms, including the elevated plus maze, light–dark box, marble burying, tail suspension, forced swim, and open field tests. Flumazenil and WAY-100635 were used to examine whether the behavioral responses were sensitive to γ-aminobutyric acid type A (GABA-A)/benzodiazepine- and serotonin 1A (5-HT1A)-related pharmacological modulation, respectively. In a preliminary 24-h acute oral toxicity screen, no mortality was observed up to 5000 mg/kg. The three oils produced anxiolytic-like and antidepressant-like effects without reducing spontaneous locomotor activity. Within its experimental block, S. brevicalyx showed the most consistent flumazenil-sensitive anxiolytic-like pattern and FDR-significant reductions in corticosterone and TNF-α, together with increased IL-4. P. dolabriformis showed a broader predicted multitarget docking profile and antagonist-sensitive behavioral attenuation compatible with mixed pathway participation. R. officinalis produced significant but more moderate behavioral effects. WAY-100635 partially attenuated the antidepressant-like effects of all three oils. These findings support differentiated but convergent functional neurobehavioral profiles among the oils. The docking, antagonist, and biomarker results should be interpreted as hypothesis-generating evidence of possible pathway involvement, supporting further validation in chronic stress models, receptor-specific assays, pharmacokinetic studies, and expanded safety evaluations. Full article

Dog parks are widely used recreational spaces for human–dog interaction, yet there is little empirical data about how surface materials influence dogs’ behavior and welfare. This study evaluated dogs’ behavior on three surfaces commonly used in outdoor dog recreation areas. Ten dogs (N = 10) participated in ten structured play sessions in an experimental area with unrestricted access to all surfaces. The testing area consisted of a 12.2 m² playground divided into nine plots of equal size. Each plot was randomly assigned a surface material (i.e., natural grass, stabilized grass, or artificial turf) in a 3 × 3 block design. Environmental and surface temperatures were recorded in each session. Dog behavior was recorded during a pre- and post-play period and measured using a 10 s scan sampling technique. In addition, surface characteristic measures were collected throughout the study to evaluate differences in their tolerance to weather conditions and usage. Artificial turf consistently reached a higher temperature (25.2 °C; 95% CI: 24.5–25.8 °C) than natural (19.4 °C; 95% CI: 18.7–20.1 °C) and stabilized (20.0 °C; 95% CI: 19.3–20.6 °C). In this study, the artificial turf reached temperatures as high as 63.8 °C while, under the same environmental conditions, the surface temperature of both natural turfgrass treatments remained below 40 °C. During the pre-play period, dogs showed more active than passive behaviors on the stabilized surface (35.03%; 95% CI: 30.58–39.80%) compared to the natural (27.86%; 95% CI: 23.94–32.10%) and artificial turf (23.31%; 95% CI: 19.81–27.20%). During the post-play period, activity levels decreased across all surfaces, while the occurrence of passive behaviors increased and was observed more frequently on the natural turfgrass surfaces (27.30% on stabilized and 15.52% on natural) than on artificial turf (2.41%). Artificial turf was less affected by dog traffic and seasonal changes; however, its surface was harder than both natural turfgrass treatments. The addition of the stabilizing grid failed to reduce soil compaction as anticipated. Overall, dogs spent more time on both natural turfgrass surfaces than artificial turf. However, a potential confounding effect of location could have influenced dog behavior. Nonetheless, our findings show that dog owners should be cautious when using artificial turf areas when environmental temperatures are above 25 °C when the turf temperature is above the safety threshold for burn injuries. These findings highlight the importance of carefully selecting surface materials for outdoor dog spaces to ensure dogs’ safety and comfort. Full article

Purpose: The purpose of this paper is to provide an integrative review of Positive Psychology in contemporary organizational contexts, examining how psychological resources such as Psychological Capital, Emotional Intelligence, Mindfulness, Psychological Safety, Self-Determination Theory, and Positive Leadership contribute to employee well-being, flourishing, and organizational effectiveness. Design/Methodology/Approach: This study adopts a narrative integrative literature review approach, synthesizing recent theoretical and empirical research in Positive Organizational Psychology, Organizational Behavior, and Human Resource Management. The review integrates foundational theories with contemporary empirical findings published in high-impact academic journals to develop a comprehensive conceptual framework. Findings: The findings indicate that Positive Psychological constructs are consistently associated with higher levels of employee engagement, job satisfaction, performance, resilience, and flourishing, while reducing burnout, stress, and turnover intentions. Psychological Capital emerges as a key malleable resource, while Mindfulness and Emotional Intelligence enhance self-regulation and interpersonal effectiveness. Originality: The paper integrates multiple streams of Positive Psychology into a unified conceptual model, combining individual-level psychological resources with motivational and organizational-contextual factors. Research limitations/implications: As a narrative review, the study does not include primary empirical data or statistical testing. Future research should empirically validate the proposed integrative framework using longitudinal and cross-cultural designs. Practical implications: Organizations can enhance employee well-being and performance by implementing Psychological Capital Interventions, mindfulness-based programs, strengths-based development, and psychologically safe leadership practices. Social implications: The findings highlight the broader societal value of fostering psychologically healthy workplaces that promote sustainable employment, mental health, and human flourishing. Full article

This study presents a comprehensive analysis of the modeling and optimization of sensor installation nodes for weight measurement in the hoppers of a charging car utilized in coke production. The research highlights the critical role of precise load monitoring in preventing technological disruptions, minimizing equipment degradation, and optimizing energy consumption. Conventional sensor technologies, including capacitive, ultrasonic, and laser-based systems, are evaluated, with weight sensors mounted on hopper supports identified as the most robust solution for real-time mass determination under industrial conditions characterized by high dust levels, temperature fluctuations, and mechanical vibrations. A finite element analysis (FEA) was conducted to assess the structural behavior of sensor installation nodes under three distinct loading scenarios, corresponding to different operational conditions of the charging car. The four-point support structure of the hopper experienced the highest loads and non-uniformities. A stress–strain analysis of the sensor mounting assembly, performed using the Ansys software package, confirmed that both the sensor and its support structure maintain a sufficient safety margin (version 2024 R1, Ansys Inc., Canonsburg, PA, USA, the academic license provided to Wrocław University of Science and Technology). The findings validate the structural integrity and operational reliability of the proposed sensor configuration, contributing to the advancement of automated monitoring and control systems in coke production. Full article

Large language models (LLMs) are increasingly deployed in multilingual settings, yet their safety behavior under Turkish harmful prompts and prompt injection attempts remains insufficiently characterized. This study evaluates the adversarial robustness of 55 open- and closed-source LLMs under paired Turkish and English harmful prompt conditions. We constructed a benchmark of 790 Turkish adversarial prompts, translated the prompts into English for cross-lingual comparison, and applied both prompt sets to the model pool. Model responses were labeled as harmful, harmless, or hallucinatory, and safety was analyzed using safety scores, Turkish–English ranking differences, and inter-rater reliability based on Fleiss’ kappa. The results reveal substantial variation across models. Closed-source systems generally achieved higher safety scores and stronger filtering behavior, whereas open-source and Turkish-oriented models showed a wider performance distribution. GPT-5.4 ranked first in the Turkish tests with a 99.37% safety score but decreased to 96.71% in the English tests, while Qwen3.5:27B ranked first in English with 97.47%. These differences suggest that safety mechanisms are not fully language-invariant. Hallucination also emerged as a distinct safety risk, particularly in Turkish evaluations. The findings indicate that Turkish LLM safety cannot be inferred from general model capability alone and should be assessed through language-specific, culturally aware, and continuously updated adversarial benchmarks. Full article

As a key energy storage component, the rapid detection of battery status and safety and reliability evaluation of the lithium battery have attracted more attention. Among them, the expansion behavior evaluation technology of the lithium battery, as a non-destructive rapid detection method, is an effective means to evaluate the health status of the battery and realize early safety warning. This paper reviews the causes of the current expansion phenomenon of lithium battery, the development status of expansion evaluation technology and the evaluation method of expansion test results. The existing expansion behavior evaluation technology under constant pressure and constant displacement conditions are classified and discussed. By accurately obtaining changes in the internal state of the battery, it can accurately predict and evaluate performance, life and safety. By obtaining the critical conditions of battery expansion, the design and optimization of the module structure are guided. On this basis, the limitations of lithium battery expansion test under different boundary conditions are further discussed. The future development of battery expansion test methods and battery expansion control and solutions are proposed. This paper aims to optimize the evaluation technology of lithium battery expansion behavior and improve the safety and reliability of the battery. Full article

In carbon sequestration in saline aquifers, many factors affect multiphase fluid migration and reservoir pressure change. This study developed a high-resolution three-dimensional numerical model to investigate large-scale CO₂ geological storage in the Ordovician carbonate aquifer of the Tarim Basin, China. This study focuses on the quantitative prediction of CO₂ plume migration, multiphase flow interactions between supercritical CO₂ and brine, and formation pressure evolution under coupled injection operations. Injection strategies were compared by constant rate (CR) and variable rate (VR) injection, and two caprock morphology-type selection by placing wells into monocline traps (wells 1/3/5) and anticline traps (wells 2/4) with varying limb dip angles and closure depths. The results demonstrate that both injection speed and caprock morphology strongly control CO₂ trapping evolution and storage security. At the end of the 500-year simulation, the dissolved-CO₂ migration distance followed the order CR > VR, indicating that, under the studied conditions, VR injection most effectively limited the lateral spread of dissolved CO₂ and thereby enhanced dissolved-CO₂ immobilization. In addition, CR and VR injection schedules have a subtle impact on long-term pressure change; Across all cases, formation pressure remained below the caprock breakthrough pressure. CR injection promotes the fastest CO₂ dissolution and pressure dissipation but yields the weakest long-term immobilization, whereas VR injection trades early dissolution rate for more effective plume containment. This result indicates that injection-strategy selection should be matched to dominant site controlled near-term pressure management versus long-term containment and to the trapping behavior imposed by caprock morphology. This study provides a mechanistically grounded optimization framework linking injection-speed control and caprock morphology to the coupled evolution of pressure-buildup safety and long-term CO₂ immobilization, supporting CCUS decision-making in the Tarim Basin. Full article

Responding to residents’ differentiated health-promoting needs has become important for improving the adaptability of street renewal in old urban neighborhoods. Based on 1404 valid questionnaires from residents in old urban neighborhoods of Jinan, China, this study develops an analytical framework linking group classification, environmental responses, and renewal strategies from the perspective of health literacy–activity behavior mismatch. Health literacy and activity behavior indices were constructed, and K-means clustering was used to identify mismatch groups. Estimated marginal means, average marginal effects, and multiple-response analysis were then employed to compare group-specific response trajectories and improvement preferences across four street environmental dimensions: slow-mobility space, service function, natural aesthetics, and activity facilities. Further interpretation of the obtained analytical results demonstrates that the investigated resident samples are partitioned into four typical subgroups: behavior-driven, high-literacy/high-behavior, literacy-driven, and low-literacy/low-behavior groups. Slow-mobility space was mainly associated with participation willingness and mismatch adjustment; natural aesthetics was primarily related to environmental cognition and perceived attractiveness; activity facilities were more relevant to mismatch changes among low-literacy/low-behavior residents; and service function mainly provided everyday convenience support. Improvement preferences were generally concentrated on basic environmental conditions, especially traffic safety, natural environment, and public activity spaces. These findings provide empirical evidence for group-based health-promoting street renewal and highlight its relevance to socially inclusive and sustainable urban regeneration. Full article

The 6 February 2023 Kahramanmaraş earthquakes caused widespread structural damage and highlighted the need for rapid building-level decision support in post-earthquake assessment. This study presents an explainable ensemble learning framework for seismic damage prediction using 16,611 building-level field observations from Kırıkhan, Hatay, Türkiye. The original damage records were reorganized into three operational classes: No-Damage, Slight–Moderate, and Heavy–Collapse. Eight tree-based ensemble models, LightGBM, CatBoost, XGBoost, Random Forest, Extra Trees, Gradient Boosting Machine, AdaBoost, and HistGradientBoosting, were evaluated under a consistent protocol using class-weighting strategies where supported, with Balanced Accuracy as the primary metric. LightGBM and Random Forest achieved the joint-highest Balanced Accuracy value (0.650). Random Forest produced the strongest agreement-based metrics, while LightGBM remained closely competitive and was selected as the representative model for explainability because of its balanced class-wise behavior. CatBoost achieved the highest Heavy–Collapse recall (0.729), XGBoost achieved the highest Macro-AUC (0.821), and GBM produced the highest Overall Accuracy (0.658), showing that model ranking varied by evaluation criterion. SHapley Additive exPlanations identified building age, lithology, number of floors, structural system, plinth area, and proximity to faults and surface ruptures as key contributors. The remaining classification uncertainty, particularly among adjacent damage states, indicates that the framework is best interpreted as a complementary decision-support tool for preliminary screening and prioritization before final safety decisions or official damage assessment. Full article

The long-term stable and efficient operation of dams is crucial. How to accurately assess overall dam safety behavior from discrete monitoring data is the key to realizing real-time monitoring and diagnosis of dam safety. Existing real-time dam safety evaluation methods do not fully consider the temporal similarity and spatial aggregation among anomalies of multiple types of monitoring points, resulting in an insufficiently comprehensive judgment of the overall safety state. This study integrates spatial clustering, temporal similarity analysis, and a spatial influence degree algorithm based on topological correlations among multiple abnormal groups. It converts discrete abnormal points into continuous influence zones and quantifies their spatiotemporal correlations. A comprehensive evaluation method is then proposed for dam operation safety behavior, with spatiotemporal coupling of multiple monitoring points. This method extends dam safety evaluation from single-point judgment to multi-point spatiotemporal collaborative judgment. A case study on a typical engineering case shows that the method achieves a comprehensive score of 96.43, reasonably constructs continuous influence zones of multi-point anomalies, and yields evaluation conclusions consistent with engineering practice. It also exhibits robustness and moderate sensitivity to structural anomaly evolution, providing a feasible way to extend dam safety evaluation from a single point to the entire space. Full article

The entry of JD.com into the food delivery sector and the ensuing subsidy competition have resulted in irrational competition, merchant profit squeezes, and food safety risks in China. This study therefore investigates the collaborative governance mechanisms for food delivery platforms under involutionary competition driven by traffic contestation. A two-agent evolutionary game model between platforms and merchants is developed, and Q-learning simulations are conducted to capture dynamic learning behaviors. The analysis examines the effects of coupon face value, cost-sharing mechanisms, traffic incentives, and government incentive-penalty policies on the strategic choices of both agents. Key findings reveal that merchants are more sensitive than platforms to traffic incentives and government penalties. Traffic-dependent merchants and traffic-independent merchants exhibit significantly different responses to government interventions. The coupon face value demonstrates a threshold effect, where only a reasonable range encourages compliant behavior among both parties. Based on these results, a collaborative governance framework is proposed. For traffic-dependent merchants, the government should focus on regulating platform behaviors and supervising coupon value controls, while platforms should establish a reward-oriented, penalty-supported incentive mechanism. For traffic-independent merchants, the government should strengthen consumer-reporting penalty mechanisms and strictly control collusion risks between platforms and merchants. Platforms should increase inspection frequency and reinforce penalties to prevent, at the source, the decline in product quality and market disorder induced by involutionary competition. This study provides strategic insights for achieving collaborative governance of involutionary competition in platform economies under intense traffic contestation. Full article

Speed management remains a central challenge in road safety, particularly in road segments where geometric design, crash concentration, or downstream stopping conditions require drivers to reduce speed. Although conventional traffic signs provide regulatory guidance, recent behavioral approaches suggest that message framing may influence driver compliance by activating different cognitive and social associated psychological constructs. However, limited evidence exists on how traditional speed-reduction signs compare with urgency-based, risk-based, and social-norm messages in shaping drivers’ behavioral intention. This study examined the perceived effectiveness of five speed-reduction messages: a standard regulatory sign, an urgency-based version, a crash-risk warning, and two social-norm variants. A within-subject survey design was applied to 326 active drivers, using seven-point Likert scales to measure behavioral intention, perceived risk, social influence, credibility, and clarity. Descriptive comparisons showed that the urgency message obtained the highest behavioral intention score, followed by the standard regulatory and risk-warning messages, whereas both social-norm messages showed lower means and greater dispersion. A latent structural equation model showed good fit and indicated that stated behavioral intention was primarily associated with perceived risk and message credibility, whereas social influence and clarity did not add significant explanatory value once these appraisal constructs were considered. This pattern suggests that drivers’ stated intention to reduce speed is shaped less by social conformity or basic message comprehension and more by whether the sign is perceived as risk-relevant and credible. Field and simulator studies are still needed to determine whether these stated-intention patterns translate into observable speed reduction. Full article