Search Results (2,474)

Accurate three-dimensional characterization of turbulent flows in natural waterways is essential for the effective design of tidal farms and other critical infrastructure situated along or across rivers. High-fidelity predictions based on the large-eddy simulation (LES) method capture the necessary physics but incur computational costs that hinder rapid scenario testing. Statistically, a relatively long history of instantaneous flow fields is required to generate reliable turbulence statistics, e.g., mean velocity and Reynolds stresses, of river flow. Such a requirement often incurs high simulation runtime and data storage costs. This study seeks to develop a neural network surrogate model that learns from a limited number of instantaneous flow realizations and approximates the outputs of the corresponding time-averaged fields with LES-level accuracy. Such a surrogate would eliminate the need to accumulate extensive ensembles, enabling faster hydrodynamic assessment and making LES-informed analyses more accessible for practical engineering decisions. Full article

Background: Quality of life (QoL) after spinal cord injury (SCI) is influenced by psychosocial factors, yet less is known about how these factors are examined across national contexts. Objective: This scoping review mapped studies examining depression, employment, and social participation in relation to QoL or health-related QoL (HRQoL) among individuals with SCI in the United States and South Korea. Methods: Following PRISMA-ScR guidelines, five databases were searched for peer-reviewed English- and Korean-language studies published between 2007 and 2025. Results: Sixteen studies were included: nine from South Korea and seven from the United States. Depression and psychological distress were associated with lower QoL/HRQoL in both countries, although South Korean studies more often examined depression with stress and functional concerns, whereas U.S. studies situated depression within participation, spirituality, and youth psychosocial functioning. Employment was linked to QoL/HRQoL in both contexts, with South Korean studies emphasizing economic activity, vocational rehabilitation, and financial strain, and U.S. studies emphasizing employment status and vocational outcomes. Social participation was important in both countries, but South Korean studies focused more on community transition, functional independence, and social attitudes, whereas U.S. studies emphasized participation contexts, accessibility, and social relationships. Conclusions: Across the three domains, depression, employment, and social participation emerged as recurring psychosocial domains associated with QoL/HRQoL after SCI in both countries. These differences suggest that psychosocial adaptation after SCI should be understood within cultural and rehabilitation contexts. Full article

Background: Pancreatic ductal adenocarcinoma (PDAC) belongs to the group of killer human cancers. Its ferocity is sustained by an unusual mix of genetic changes—primarily in KRAS and TP53—a hypoxic as well as desmoplastic tumor microenvironment, plus metabolic and redox adaptations that allow tumor life amidst intense stress situations. Content: This paper will discuss the molecular networks of wild-type and mutant p53, wild-type and mutant KRAS, PUMA, TIGAR, PRMT5, NRF2, oxygen tension, reactive oxygen species (ROS), and oxidative stress pathways that contribute to pancreatic cancer. It will describe how these factors help set the tumor’s redox state and control apoptosis and therapeutic resistance. This shall therefore specifically discuss what role oxygen gradients play in pancreatic tissues, as well as retinoic acid, together with redox-targeted therapies that are specific to vulnerabilities within such types of networks. Summary and Outlook: An understanding of the crosstalk of these molecular pathways will be critical in designing rational therapeutic strategies. Genetics, metabolism, and microenvironmental integration may open a path toward combinatorial therapies that would resensitize PDAC to apoptosis and overcome resistance to current treatments. Full article

University professors’ emotional competencies are increasingly discussed as relevant dimensions of teaching professionalism that may shape students’ academic engagement, motivation, and psychological well-being. This qualitative study explores how university students perceive professors’ emotional and relational practices and how students perceived these practices as shaping their academic experience. Twenty-one semi-structured interviews were conducted with undergraduate and master’s students at an Italian university and analyzed through thematic analysis. Five interconnected themes were identified: (1) empathy and the humanization of the professor–student relationship; (2) relational and communicative styles shaping classroom climate and motivation; (3) emotional regulation in high-stress academic situations, particularly examinations; (4) perceived differences across teaching modalities and disciplinary contexts; (5) students’ expectations regarding balanced emotional openness and faculty development. Students described empathetic, approachable, and emotionally regulated professors as helping to reduce stress, strengthen academic confidence, foster engagement, and support a sense of belonging. Conversely, rigid, distant, or humiliating interactions were associated with anxiety, withdrawal, and disengagement. Rather than treating emotional competence as an individual disposition, the study proposes that it should be understood as a professional and institutional dimension of university teaching. It further develops the notion of student-perceived academic psychological safety as a relational mechanism through which professors’ emotional competencies may influence students’ well-being and participation. The findings highlight the need for faculty development initiatives and institutional policies that recognize the emotional and relational dimensions of teaching as integral to higher education quality. Full article

Illegitimate tasks are assignments that threaten professional identity by not being related to the intrinsic quality or morality of the main profession. This concept has gained attention within the Stress as Offense to Self (SOS) theory, which emphasizes the impact of self-esteem in stressful situations, particularly in the workplace. The SOS theory suggests that self-esteem plays a critical role in how individuals respond to stress: when self-esteem is threatened, it triggers adverse reactions affecting mental, physical, and behavioral dimensions; conversely, strengthening self-esteem promotes well-being. Illegitimate tasks are perceived as unnecessary or unreasonable, varying by profession and non-voluntary in nature, leading to a lack of purpose and meaning for the employee. The Bern Illegitimate Tasks Scale (BITS) was created to assess and quantify these tasks, demonstrating robust psychometric properties across different languages and cultural contexts, including Spanish, Swedish, and Portuguese adaptations. This study aims to translate and adapt the BITS for a public university context characterized by bureaucratic culture. The sample comprises 601 participants from a Portuguese public higher education institution. The translation process followed rigorous procedures to ensure equivalence between the original and Portuguese versions. Data analysis included descriptive statistics, confirmatory factor analysis (CFA), and internal consistency analysis, revealing satisfactory fit indices and high reliability. Despite contextual limitations, the findings affirm the reliability of the adapted scale for application in similar contexts. Future research should aim for more representative samples to enhance generalizability. Full article

Türkiye has many historically rich cities that host structures of significant cultural value. These structures, especially masonry bridges, reflect the construction techniques and materials of the periods in which they were built. However, studies on the origins of these bridges and the structural deteriorations that develop over time are limited. This situation may lead to damage and even the risk of collapse if necessary precautions are not taken. In this study, stone and mortar samples were first collected from the historic Pamukçular (Şifalısu) Bridge in Bitlis, and the collected materials were analyzed. The structural behavior of the bridge under seismic effects was then investigated using the Finite Element Method (FEM). A three-dimensional geometric model of the bridge was created, and material parameters were defined based on values from the material analyses. Static analysis under self-weight and modal analysis were performed in the ABAQUS software (Version 6.14) to obtain the natural frequencies. Under the bridge’s self-weight, local stress concentrations were concentrated at the arch crown and pier-arch connections, with maximum tensile and compressive stresses reaching approximately 0.15 MPa and 0.27 MPa, respectively. These low stress levels demonstrate that the structure remains fully stable under static loading conditions. Finally, dynamic analyses in the time domain were carried out. In these analyses, records from the 2011 Van Earthquake and the 2023 Kahramanmaraş Earthquake were used to identify the bridge’s critical regions and evaluate its seismic performance. The results indicate that the overall structural stability is adequate; however, local stress concentrations occur in the arch crown and pier connection regions. The study provides engineering-based recommendations for preserving and strengthening historic masonry bridges. Full article

Heart rate variability (HRV) is widely used as a non-invasive marker of autonomic regulation and physiological adaptability, with relevance across cardiovascular, metabolic, neuropsychiatric, and stress-related conditions. HRV biofeedback has emerged as a non-pharmacological intervention intended to influence autonomic function through paced breathing, resonance-frequency training, and real-time physiological feedback. Although this approach has shown promise in improving stress regulation, emotional symptoms, autonomic balance, and selected cardiovascular outcomes, its effects are not consistent across individuals or clinical states. The reasons for this variability remain insufficiently conceptualized. In this narrative conceptual review, we propose the concept of autonomic non-responsiveness during HRV biofeedback as a descriptive framework for situations in which expected autonomic engagement is weakened, absent, or fails to translate into meaningful physiological or clinical benefit. We discuss potential contributors to non-response, including reduced autonomic flexibility, impaired baroreflex function, disease burden, fatigue, stress-related overload, dysfunctional breathing, methodological limitations, and cognitive-behavioral constraints. We then consider the clinical implications of recognizing non-response as a potentially informative state rather than a simple negative outcome. Finally, we outline a future research agenda focused on operational definition, candidate biomarkers, temporal characterization, and minimally adaptive closed-loop systems. Full article

Nursing students in their training process often suffer from anxiety due to stressful situations, and emotional intelligence can help them to manage these situations. The aim of this study is to analyse the associations between the dimensions of perceived emotional intelligence and anxiety in students undergoing their training cycles in different special services in order to check if there are differences between them. It is an observational, cross-sectional and correlational study with a sample of 85 nursing students who had not received training in emotional intelligence. Two measurement instruments were used: the Trait-State Anxiety Inventory (STAI) to assess anxiety and the Trait Meta-Mood Scale (TMMS-24) to measure EI. Data were analysed using Pearson’s coefficient when the distribution was normal, and Spearman’s coefficient in the non-normal distribution. The results showed in the group—ER-Emergency and Oncology—there was a significant negative relationship between state and trait anxiety and emotional understanding and regulation. In contrast, in the Primary Care setting there was also a positive relationship between emotional perception and trait anxiety. The study concludes that nursing students who understand and manage their emotions may have a lower risk of anxiety. Furthermore, if they identify emotions appropriately, the risk of suffering from anxiety in the long term may be lower. This finding was observed when the student did the internship in Primary Care. So there is a difference depending on the clinical context. Full article

Background/Objectives: Robot-assisted surgery (RAS) has grown rapidly over the past few decades. To determine the effect of high stress levels on the performance of RAS, monitoring some parameters of surgeons is critical. This can be aided by the development of Artificial Intelligence (AI), which has exponentially grown in recent years. This study aims to predict the surgeon’s stress level based on ergonomic, kinematic and physiological parameters of the surgeon obtained in the immediately previous situation during RAS activities. Methods: Physiological data were recorded from surgeons during twenty-six surgical sessions involving twelve participants with different levels of experience and surgical specialties. After dataset generation, two preprocessing procedures (scaling and normalization) were applied to the recorded signals. The processed data were then partitioned into two subsets: 80% of the samples were used for model training and cross-validation, while the remaining 20% were reserved for testing. Six AI approaches were evaluated to build predictive models: multiple linear regression (MLR), a support vector machine (SVM), a multilayer perceptron (MLP), a convolutional neural network (CNN), random forest (RF), and a U-Net algorithm (UNET). These algorithms were trained using the training dataset and subsequently assessed on the independent test set. In addition, after each surgical session, surgeons completed a questionnaire reporting their perceived stress level, which was later compared with the stress estimates generated by the predictive models. Results: The results obtained showed that MLR and scaling pre-processing reached the highest R² coefficients and the lowest error for each studied parameter. The results of the surgeons’ surveys were highly correlated for microsurgery activities (R² = 0.7989) and for laparoscopy RAS (R² = 0.8381). Conclusions: The linear models proposed were correctly validated on cross-validation and the test dataset. This fact demonstrates the possibility of predicting factors that help us to improve the surgeon’s health during RAS. Full article

Disaster-related social media posts often report casualties, rescue needs, infrastructure damage, shelter demand, and local situation changes earlier than formal channels, yet their brevity and noise make operational classification difficult. This study examines whether a practical and reproducible classification pipeline can support fine-grained, emergency-oriented semantic recognition under a deliberately conservative evaluation setting. We convert 14,392 English tweets from CrisisSense-LLM into six actionable semantic categories, partition the data by proxy event groups, and compare a TF-IDF logistic-regression baseline, supervised BERT-base fine-tuning, and zero-shot natural language inference. The evaluation is further extended to mapped HumAID data, a manually reviewed 177-post Chinese boundary-test set, a Chinese-to-English translation bridge, and a fixed-budget selective adjudication simulation. BERT-base achieves the best held-out main-test performance (Macro-F1 = 0.8824), outperforming TF-IDF (0.6133) and zero-shot inference (0.3581), and reaches 0.8132 Macro-F1 on HumAID without retraining. Direct English-to-Chinese transfer is ineffective, whereas multilingual BERT and translation bridging improve Chinese Macro-F1 to 0.2684 and 0.3603, respectively. With 600 reviewed posts, selective adjudication reaches 0.7792 Macro-F1 on the main test set and 0.7153 on HumAID. These findings indicate that the central contribution is not a new model architecture, but an empirically validated workflow that combines supervised fine-tuning, leakage-aware evaluation, external validation, cross-lingual stress testing, and information-driven human review. The novelty therefore lies in the reproducible integration of data mapping, group-aware evaluation, external and cross-lingual stress testing, and selective human review into a single emergency-oriented assessment workflow. Full article

In complex environments, Operators need to manage continuous, real-time information flows while handling unexpected situations within a limited timeframe. This can lead to high cognitive load, stress, fatigue, etc. To prevent such situations, Artificial Intelligence (AI) systems are increasingly being considered. Their role is no limited to assistance, but extends to performing some or all of the tasks initially carried out by the operator. However, inappropriate allocation of tasks between humans and machines can exclude the operator from the loop or reduce their vigilance. This paper proposes the design and implementation of three strategies for the dynamic reallocation of tasks between a human and an AI, considering factors related to the operator (cognitive load, stress) and their activity (activity modeling). An evaluation is conducted to compare three strategies. The first two are hybrid strategies, in which both the operator and the AI can modify task allocation. The first hybrid strategy is based on self-assessment, while the second is based on activity modeling. The third strategy is an adaptable strategy, in which only the operator can change task allocation. The use case is an emergency call center simulation implemented on InteractiveAI Preliminary findings from our user exploratory study suggest that participants tended to better accept adaptable automation, while also exhibiting a higher error distribution compared to hybrid automation strategies. No significant differences were observed in cognitive load or situational awareness in this limited sample. However, recurring instances of mode confusion were observed with hybrid strategies. Full article

The Shatt al-Basrah Canal, a brackish artificial waterway in southern Iraq, experienced a fish mortality event in August 2021, raising serious environmental and socioeconomic concerns. This study documents field observations, photographic evidence, and in situ water-quality measurements collected during the event to characterize environmental conditions associated with the mortality and situate them within the context of long-term ecosystem degradation in the region. The event coincided with critically low dissolved oxygen concentrations (1–2.5 mg L⁻¹), elevated summer water temperatures (31.2–31.6 °C), high total ammonia nitrogen levels (1.88–2.2 mg L⁻¹), and brackish salinity (17.4–23 ppt), reflecting strong anthropogenic influence and limited hydrological flushing. These stressors occurred in areas receiving untreated wastewater inputs and affected both native and non-native fish species tolerant of estuarine conditions. Comparison with documented fish-kill events from Kuwait Bay and other parts of the northern Arabian Gulf indicates similar environmental settings characterized by hypoxia, organic enrichment, and summer thermal stress. The 2021 mortality event suggests how acute ecological deterioration may arise in chronically degraded brackish systems and underscores the need for continuous water-quality monitoring, improved wastewater treatment, and proactive management to reduce the risk of recurrent fish kills in Iraq’s vulnerable aquatic ecosystems. Full article

Satellite-derived vegetation indices and climate data from 2018 to 2024 were analysed to quantify smallholder agricultural responses to climate variability in two rural villages in the Eastern Cape, South Africa. Using Google Earth Engine, R programming 4.4.0, and ArcGIS Pro 3.6, the study assessed spatiotemporal trends in vegetation condition in relation to bioclimatic variables and plot-scale land ownership. The results showed an overall accuracy of 96%, with producer and user accuracies at 79% and 85%, respectively, and a kappa coefficient of 0.95. Time-series analysis revealed a trend of decreasing rainfall and increasing temperatures across the study area, accompanied by elevated Plant Senescence Reflectance Index (PSRI > 0.294) values indicative of advanced vegetation stress. Spatial analysis showed that valley areas exhibited higher moisture accumulation potential and aligned with drainage networks, reflecting enhanced soil moisture retention relative to surrounding terrain. These findings demonstrate the strong influence of topography-mediated water availability on vegetation health in rain-fed smallholder systems. In accordance with the Sustainable Development Goals, the study stresses the importance of gender equity in combating climate change and achieving food security, highlighting the value of integrating multi-scale remote sensing and climate data to identify localised agricultural vulnerability, and underscores the importance of gender-responsive, climate-aware land management strategies to support food security under changing environmental conditions. By situating smallholder agriculture within a land system science framework, the study advances understanding of how topography-mediated soil moisture retention, climate variability, and gendered land governance jointly shape land system trajectories in communal tenure settings. Full article

Previous research demonstrates that housing security and quality influence physical and mental health. Despite a rich literature on housing and health, less is known about the processes through which housing mobility programs directly affect family health. We use a single-case design to examine how the health of families with children is impacted by Families Flourish, a mobility program that combines three years of rental assistance with life coaching and placement in safe, well-resourced neighborhoods. Drawing on developmental and formative evaluation data, including longitudinally collected surveys, interviews, and administrative records, we trace families’ experiences over time. Our analysis identifies distinct pathways through which mobility improves mental and physical health—via improved indoor air quality, reduced environmental and parental stress, and enhanced access to resources. Initial health gains are subsequently leveraged to improve educational and economic outcomes. We observe a temporal sequence in outcomes, with early physical health gains and later mental health improvements as stability and safety increase. We conclude by situating these identified pathways within existing scholarship and discussing implications for planning and fair housing practice. Full article

This article describes a portable Arduino-based prototype for the recording and analysis of electroencephalogram (EEG) signals associated with anxiety situations. The system’s main aim is to enable the user to self-detect stress and take self-regulating/relaxing actions in real time before stress escalates. The recorded EEG signals are first processed in the analog domain (including amplification and noise reduction) and then, by using an Arduino Uno board, they are converted into digital format and transmitted through either a wired or wireless connection to a computer to be depicted in both the time and the frequency domains by means of an open-source software. During the performed tests, the system successfully showed visible changes in the alpha and beta brain signals corresponding to the states of resting, induced stress, and the subsequent self-regulation/relaxation process. The proposed prototype (though non-clinical in its present form) has the merits of relatively low cost, easy self-use (outside clinical environments), and real-time EEG signal depiction, and, apart from enabling the user to self-detect and self-monitor stress, it can also be used for educational and/or research purposes. Full article