Search Results (17,512)

Nuclear Factor Y C (NF-YC) transcription factors (TFs) are central regulators of plant development and stress adaptation. However, there remains a gap in identifying NF-YC gene family members in blueberry (Vaccinium corymbosum), a globally significant fruit crop renowned for its nutritional value and good adaptability. In this study, a total of 31 NF-YC genes (designated VcNF-YC1–31) were identified in the blueberry genome, and their basic physicochemical properties, gene structures, motif patterns, and conserved domains were investigated using bioinformatic methods. The cis-acting elements in the promoters of VcNF-YCs were mainly enriched in phytohormone signaling, metabolism, and stress response. qRT-PCR analysis showed that VcNF-YCs were expressed at higher levels in leaves than in roots and stems. Transcriptional profiling revealed rapid upregulation of 24, 25, and 16 VcNF-YC genes upon ABA, salt, and cold treatments, respectively, indicating stress-specific induction patterns. The results of the yeast transformation assay revealed that VcNF-YC10 and VcNF-YC15 lacked transcription-activating activity. The results of tobacco leaf injection revealed that these two TFs were localized in the nucleus. These findings indicate the potentially important roles in abiotic stress responses of blueberry, offering potential targets for molecular breeding to enhance plant resilience. Full article

The new generation of Eurocode standards has prompted enquiries regarding the major distinctions from the current version, particularly in relation to the application of the N2 method. A substantial change has been made to the definition of elastic spectra. The new spectra are defined through a series of fixed, probabilistically determined points, yet they remain rooted in a probabilistic approach. Three building types—multi-storey reinforced concrete (RC) frames, steel moment frames, and steel braced frames—were analysed in accordance with ground accelerations of 1, 2, and 3 m/s², as well as across five soil types (A–E). Variations in target displacements between soil types, particularly A, B, and D, are notable in the results. For accelerations of 2 and 3 m/s², steel structures demonstrate consistent displacements, whereas RC frames exhibit values that are up to 20% higher, particularly on soils C and E. For soils A and B, the distribution of inter-storey drift remains consistent. Nevertheless, in the case of 1 m/s², the utilisation of next-generation spectra results in an average 46% decrease in inter-storey drifts. The significance of adapting design methods to the updated Eurocode provisions is underscored by these findings, which emphasise the substantial influence of soil type on building response and safety performance, particularly under increased seismic demands. Full article

Alpha-1 antitrypsin deficiency (AATD) represents a paradigmatic genetic disorder with well-characterized hepatic manifestations but relatively underexplored pulmonary implications. While liver involvement has been extensively reviewed, the underlying mechanisms of lung disease progression remain poorly understood, particularly regarding immunological pathways and inflammatory processes. The pathophysiology involves defective alpha-1 antitrypsin (AAT) production, including AAT variants that induce neutrophil elastase activity, causing progressive alveolar destruction and sustained inflammation, leading to emphysema, as one of the main components of chronic obstructive pulmonary disease (COPD). AATD and smoking represent major risk factors for COPD, the third leading cause of death worldwide at present. In AATD patients, neutrophils, which constitute the majority of circulating leukocytes, become dysregulated. Under normal conditions, cells perform essential functions, including phagocytosis and neutrophil extracellular trap formation (NETosis); in AATD, however, they accumulate excessively in alveolar spaces due to impaired elastase control. The accumulation of Z-AAT polymers within epithelial cells creates a pathological cycle, acting as chemoattractants that sustain pro-inflammatory responses and contribute to chronic obstructive pulmonary disease development. In addition, monocytes, representing a smaller fraction of leukocytes, migrate to inflammatory sites and differentiate into macrophages while secreting AAT with anti-inflammatory properties. However, in PiZZ patients, this protective mechanism fails, as polymer accumulation within cells reduces both AAT secretion and the number of protective human leukocyte antigen(HLA)-DR-monocyte subsets. In particular, macrophages demonstrate remarkable plasticity, switching between pro-inflammatory M1 (classically activated macrophages) and tissue-repairing M2 (alternatively activated macrophages) phenotypes based on environmental cues. In AATD, this adaptive capability becomes compromised due to intracellular polymer accumulation, leading to impaired phagocytic function and dysregulated cytokine production and ultimately perpetuating chronic inflammation and progressive tissue damage. Recent advances in induced pluripotent stem cell (iPSC) technology have facilitated alveolar epithelial cell (AEC) generation, in addition to the correction of AATD mutations through gene editing systems. Despite the limitations of AAT correction, iPSC-derived organoid models harboring AATD mutations can deliver important insights into disease pathophysiology, while gene editing approaches help demonstrate causality between specific mutations and observed phenotypes. Therefore, in this review, we investigated recent studies that can serve as tools for gene editing and drug development based on recently developed iPSC-related technologies to understand the pathogenesis of AATD. Full article

This paper introduces a compact analog configuration that concurrently realizes a mixed-mode biquadratic filter and a dual-mode quadrature oscillator (QO) by employing a single differential differencing gain amplifier (DDGA) and all-grounded passive components. The proposed design supports four fundamental operation modes—voltage-mode (VM), current-mode (CM), trans-impedance-mode (TIM), and trans-admittance-mode (TAM)—utilizing the same circuit topology without structural modifications. In filter operation, it offers low-pass, high-pass, band-pass, band-stop, and all-pass responses with orthogonal and electronic pole frequency and quality factor. In oscillator operation, it delivers simultaneous voltage and current quadrature outputs with independent tuning of oscillator frequency and condition. The grounded-component configuration simplifies layout and enhances its suitability for monolithic integration. Numerical simulations in a 0.18-mm CMOS process with ±0.9 V supply confirm theoretical predictions, demonstrating precise gain-phase characteristics, low total harmonic distortion (<7%), modest sensitivity to 5% component variations, and stable operation from −40 °C to 120 °C. These results, combined with the circuit’s low component count and integration suitability, suggest strong potential for future development in low-power IoT devices, adaptive communication front-ends, and integrated biomedical systems. Full article

Drought stress is a major abiotic constraint that severely restricts the growth of Medicago falcata L. by inducing the accumulation of reactive oxygen species (ROS) in plants. WRKY transcription factors (TFs) play a key role in regulating plant responses to drought stress. In this study, we investigated the role of the MfWRKY40 gene in drought tolerance. Under mannitol and ABA stress treatments, MfWRKY40-overexpressing lines (OEs) showed significantly longer primary roots, increased lateral roots, and higher fresh weight compared to wild-type (Col) lines, indicating significantly enhanced growth and drought tolerance. Similarly, under soil drought conditions, transgenic Arabidopsis thaliana exhibited enhanced drought tolerance. NBT staining demonstrated decreased ROS accumulation in transgenic lines after stress treatment. Correspondingly, the MfWRKY40-overexpressing lines displayed significantly lower levels of hydrogen peroxide (H₂O₂), superoxide anion (O₂⁻), and malondialdehyde (MDA) compared to Col, along with elevated activities of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD), as well as increased proline (Pro) content. Furthermore, MfWRKY40 upregulated the expression of antioxidant enzyme genes (AtPOD3, AtSOD4, and AtCAT1) and modulated the expression of other drought-related genes. In summary, our results demonstrate that MfWRKY40 enhances drought tolerance in A. thaliana by improving ROS scavenging capacity. This study provides a theoretical foundation for further exploration of MfWRKY40’s functional mechanisms in drought stress adaptation. Full article

Understanding neuromuscular adaptations resulting from specific training modalities is crucial for optimizing athletic performance and injury prevention. This in silico proof-of-concept study aimed to computationally model and predict neuromuscular adaptations induced by strength and plyometric training, integrating musculoskeletal simulations and machine learning techniques. A validated musculoskeletal model (OpenSim 4.4; 23 DOF, 92 musculotendon actuators) was scaled to a representative athlete (180 cm, 75 kg). Plyometric (vertical jumps, horizontal broad jumps, drop jumps) and strength exercises (back squat, deadlift, leg press) were simulated to evaluate biomechanical responses, including ground reaction forces, muscle activations, joint kinetics, and rate of force development (RFD). Predictive analyses employed artificial neural networks and random forest regression models trained on extracted biomechanical data. The results show plyometric tasks with GRF 22.1–30.2 N·kg⁻¹ and RFD 3200–3600 N·s⁻¹, 10–12% higher activation synchrony, and 7–12% lower moment variability. Strength tasks produced moments of 3.2–3.8 N·m·kg⁻¹; combined strength + plyometric training reached 3.7–4.2 N·m·kg⁻¹, 10–16% above strength only. Machine learning predictions revealed superior neuromuscular gains through combined training, especially pairing back squats with high-intensity drop jumps (50 cm). This integrated computational approach demonstrates significant practical potential, enabling precise optimization of training interventions and injury risk reduction in athletic populations. Full article

This study investigates the influence of Trait Emotional Intelligence (TEI) on affective dimensions of English language learning among 515 Pakistani EFL learners, addressing a key gap in Global South research. Using bootstrapped multiple regression and culturally adapted instruments (Cronbach’s α = 0.724–0.857), findings reveal that in Pakistan’s exam-driven, teacher-centered classrooms, well-being significantly enhances attitudes (β = 0.172, p < 0.001), motivation (β = 0.219, p = 0.002), and engagement (β = 0.179, p < 0.001). Emotionality, however, increases anxiety (β = 0.192, p < 0.001) and lowers engagement (β = −0.092, p = 0.025), contradicting global models due to punitive error correction. Sociability shows no significant effect (attitudes: β = 0.038, p = 0.366; engagement: β = 0.019, p = 0.613), reflecting limited peer interaction in hierarchical classrooms. Notably, an emergent auxiliary facet—contextual adaptability—strongly predicts motivation (β = 0.269, p < 0.001) and anxiety (β = 0.109, p = 0.020), highlighting the role of competencies like Urdu–English code-switching. These results call for a Contextually Stratified TEI Framework, emphasizing that while well-being is universal, other TEI dimensions are context-dependent. Implications urge educators to foster well-being, reframe emotionality as a risk-detection skill, and promote adaptability to local linguistic realities. Full article

The livestock sector, a crucial source of revenue and global food security, is facing serious challenges due to climate change driven by global warming. This leads to serious effects on animal health and productivity, making it difficult for the livestock industry to meet the global demand and sustain the livelihoods of farmers. The main factor affecting livestock’s productivity is heat stress. However, animals develop various adaptive mechanisms to cope with the effects of heat stress. Cellular and molecular responses act as key defense mechanisms, enabling animals adapt to environmental changes. The recent advancements in molecular biology have opened up opportunities for extensive research on epigenetics, which has a key role in regulating gene expression in animals in response to environmental stimuli. Such studies have gained considerable attention regarding heat acclimation in animals due to the fact that epigenetic mechanisms have been recognized as key players in long-term adaptation to high temperatures in farm animals. This review summarizes the different mechanisms and methodologies used to assess heat stress-associated epigenetic changes, including DNA methylation, which is an extensively studied epigenetic regulatory mechanism in relation to gene expression. The review also highlights the mechanisms and regulation of adaptation to heat stress in animals and collates information related to various epigenetic markers to assess the heat stress response, thereby aiding in improving thermal resilience in animals. Full article

This study explores the application of federated learning (FL) in security camera surveillance systems to overcome the structural limitations inherent in traditional centralized artificial intelligence (AI) training approaches, while simultaneously enhancing operational efficiency and data security. Conventional centralized AI models require the transmission of raw surveillance data from individual security camera units to a central server for model training, which poses significant challenges, including network congestion, a heightened risk of personal data leakage, and inadequate adaptation to localized environmental characteristics. These limitations are particularly critical in high-security environments such as military bases and government facilities, where reliability and real-time processing are paramount. In contrast, FL enables decentralized training by retaining data on local devices and sharing only model parameters with a central aggregator, thereby improving privacy preservation, reducing communication overhead, and facilitating adaptive, context-aware learning. This paper does not present a new federated learning algorithm or original experiment. Instead, it synthesizes existing research findings and applies the Analytic Hierarchy Process (AHP) to evaluate and prioritize critical factors for deploying FL in surveillance systems. By combining literature-based evidence with structured expert judgment, this study provides practical guidelines for real-world application. This paper identifies four key performance metrics—detection accuracy, false alarm rate, response time, and network load—and conducts a comparative analysis of FL and centralized AI-based approaches in the recent literature. In addition, the AHP is employed to evaluate expert survey data, quantitatively prioritizing eight critical factors for effective FL implementation. The results highlight detection accuracy and data security as the most significant concerns, indicating that FL presents a promising solution for future smart surveillance infrastructures. This research contributes to the advancement of AI-powered surveillance systems that are both high-performing and resilient under stringent privacy and operational constraints. Full article

Background/Objectives: The transition from theoretical knowledge to clinical practice poses significant challenges for nursing students globally. This critical period requires comprehensive educational support to build confidence and competence. While short-term preparatory courses have shown promise internationally, their effectiveness within the Saudi Arabian context remains understudied. This study aimed to evaluate nursing students’ satisfaction and self-confidence following participation in short-term preparatory courses conducted before clinical placements at Taibah University, Saudi Arabia. Methods: A descriptive cross-sectional study was conducted from February to April 2025. Data were collected from 117 undergraduate nursing students (response rate: 80.7%) using a validated questionnaire adapted from the National League for Nursing’s Student Satisfaction and Self-Confidence in Learning instrument. The preparatory courses included nursing care plan development, hospital orientation, and infection control procedures delivered over two weeks. Statistical analysis included descriptive statistics and Pearson correlation analysis. Results: Students reported high levels of satisfaction (mean = 4.29 ± 0.92) and self-confidence (mean = 4.31 ± 0.81) scores. The highest satisfaction was with instructor effectiveness (mean = 4.31 ± 1.05) and teaching methods (mean = 4.32 ± 1.01). Students demonstrated strong confidence in personal learning responsibility (mean = 4.44 ± 0.88) and skill development (mean = 4.32 ± 0.95). A strong positive correlation existed between satisfaction and self-confidence (r = 0.79, p < 0.001). Conclusions: Short-term preparatory courses effectively enhanced nursing students’ satisfaction and self-confidence in the Saudi Arabian context. The strong correlation between these constructions suggests that educational interventions improving one dimension is likely to benefit the other. These findings support integrating structured preparatory programs into nursing curricula to facilitate successful clinical transitions. Full article

Virtual reality (VR) has emerged as a transformative tool in the treatment of phobias and the cultivation of emotional resilience. This study aims to explore the potential of VR to create controlled, immersive environments that facilitate exposure therapy, enabling individuals to confront and desensitize themselves to their fears in a safe and personalized manner. The flexibility of VR systems allows therapists to tailor scenarios to the unique needs of patients, addressing specific phobias such as acrophobia, arachnophobia, and social anxiety disorders. Beyond phobia treatment, VR’s capacity to simulate challenging or stress-inducing scenarios presents opportunities for fostering emotional resilience by building adaptive coping mechanisms and reducing stress responses over time. The integration of biofeedback and machine learning further enhances VR applications, enabling real-time adjustments based on physiological and psychological responses. In this article, the current advancements, underlying mechanisms, and challenges in leveraging VR technology for therapeutic purposes are discussed with a focus on its implications for mental health care. By combining immersive technology with evidence-based practices, VR offers a promising pathway for improving mental health outcomes and expanding the accessibility of therapeutic interventions. Full article

The increasing frequency of extreme weather events and rapid urbanization has exacerbated pluvial flood risks, underscoring the urgent need to strengthen the assessment of pluvial flood resilience in China’s southwestern mountainous regions. Kunming—a plateau basin city—was selected as a case study, and an urban pluvial flood resilience assessment system was developed based on the DPSIR model. The analytic hierarchy process (AHP), entropy method, and game theory-informed combination weighting were applied to determine indicator weights, while the extension cloud model was utilized to quantitatively assess resilience evolution from 2013 to 2022. The results reveal that: (1) Kunming’s pluvial flood resilience experienced a clear three-stage evolution—initial construction (Level II), resilience enhancement (Level III), and resilience reinforcement (Level IV)—reflecting a transition from rudimentary resilience to advanced adaptive capacity; (2) the ranking of primary indicator weights is as follows: Driving Forces > Pressure > State > Response > Impact, with Flood Disaster Risk (P6), Flood Disaster Early Warning Capability (R1), and Topographic and Geomorphological Characteristics (P7) identified as key influencing factors; (3) marked disparities exist across the five dimensions: the Driving Forces dimension demonstrates increasing economic support; the Pressure dimension reflects structural vulnerabilities and climate variability; the State and Impact dimensions advance incrementally through policy implementation; and the Response dimension has substantially improved due to smart city technologies, although persistent gaps in inter-agency emergency coordination remain. This research offers a scientific basis for enhancing pluvial flood resilience in southwestern mountainous cities. Full article

The glaciers of the Nyainqêntanglha Mountains serve not only as sensitive indicators of climate change, but also as important water sources for downstream rivers. In this study, we quantitatively analyzed the glacier mass balance of the entirety of the Nyainqêntanglha Mountains using TerraSAR-X/TanDEM-X and SRTM DEM data and compared the mass balance between glaciers in the western and eastern parts of the range, revealing the spatial heterogeneity in glacier mass loss. Finally, data from nine meteorological stations in the region were used to investigate regional climate changes and their impacts on glacier variation. The results show that from 2000 to 2013, the average annual glacier surface elevation in the Nyainqêntanglha Mountains decreased by 0.48 ± 0.02 m, with a mass balance of −0.55 ± 0.04 m water equivalent per year. The majority of glacier mass loss occurred in areas with slopes between 40° and 70°. The mass loss of clean glaciers in the eastern region was higher than that in the western region, whereas at high elevations, the mass loss of debris-covered glaciers was more severe in the western region than in the east. Overall, the debris cover on the glaciers has not yet reached the critical thickness required to effectively mitigate melting, and mass input in the accumulation zones is uneven, scattered, and limited, resulting in weak replenishment capacity. Against the backdrop of continued warming, regional precipitation is insufficient to provide the necessary accumulation, making glaciers more sensitive to rising temperatures. This study not only reveals pronounced spatial differences in glacier mass loss and their climatic drivers but also provides new scientific evidence for understanding water resource security, hydrological responses and potential snow avalanche hazards on the Tibetan Plateau, offering important implications for regional water management and future climate adaptation. Full article

As an essential medium for the cultural narrative of architectural space, studying the cognitive transformation mechanisms of traditional ethnic decorative patterns is critical for their effective preservation and innovative application. This research focuses on typical decorative motifs found in She ethnic architectural heritage, systematically classifying them into five categories—animal, plant, human figure, totem, and geometric—based on symbolic themes, formal structure, and cultural function. Correspondingly, 20 sets of standardized black-and-white line drawing stimuli were developed for experimental use. Methodologically, this study utilized the EyeLink 1000 eye-tracking system to acquire real-time gaze metrics, including fixation duration and saccadic amplitude, as well as pupil dilation responses from participants engaged in a controlled pattern observation task. Immediately after observation, participants completed a semantic differential assessment using a five-point Likert scale. Data analysis employed descriptive statistics, analysis of variance (ANOVA), Kruskal–Wallis tests, and Bonferroni-adjusted post hoc comparisons (α = 0.05). Attention allocation was further examined through heatmaps and gaze trajectory visualizations to provide comprehensive insight into visual engagement. Two principal findings were identified: first, male participants showed a predominant focus on holistic structural composition and cultural symbol representation, whereas female participants exhibited a processing bias towards fine details; second, concrete symbols imbued with historical significance elicited more pronounced emotional responses, while abstract geometric patterns necessitated formal reconstruction to enhance cognitive accessibility. These findings offer empirical support for gender-inclusive architectural design strategies and inform practical approaches for safeguarding cultural heritage within contemporary architectural environments. Consequently, modern reinterpretation of traditional decorative patterns should balance cultural narrative fidelity with functional adaptation, achieving inclusive expression through contextual reconstruction and interactive design strategies. Future research directions include expanding participant demographics to encompass cross-cultural cohorts and incorporating multimodal neuroimaging techniques to elucidate the underlying cognitive and affective mechanisms, thereby advancing the sustainable transmission and innovation of ethnic cultural heritage. Full article

This study investigates the influence of electrical actuation parameters on the performance of a morphing composite aerodynamic profile actuated by Shape Memory Alloy (SMA) wires. A fully coupled electro-thermo-mechanical finite element model has been developed to simulate the transient response of NiTi SMA, capturing the nonlinear interplay between temperature evolution, phase transformation, and mechanical deformation under Joule heating. The model incorporates phase-dependent material properties, heat effects, and geometric constraints, enabling accurate prediction of actuation dynamics. To validate the model, a morphing spoiler prototype has been fabricated using high-performance additive manufacturing with a carbon fibre-reinforced polymer. The SMA wires have been pretensioned and electrically actuated at different current levels (3 A and 6 A), and the resulting deformation has been recorded through video analysis with embedded timers. Experimental measurements confirmed the model’s ability to predict both actuation time and displacement, with maximum deflections of 33 mm and 40 mm corresponding to different current inputs. This integrated approach demonstrates an efficient and compact solution for active aerodynamic surfaces without the need for mechanical linkages, enabling future developments in adaptive structures for automotive and aerospace applications. Full article