Search Results (1,516)

Distance higher education places increased demands on instructors’ emotional and communicative competencies, as teaching and interaction occur in technologically mediated environments. This study examines the role of teachers’ emotional intelligence, empathy, and communication-related competencies in distance higher education, with particular emphasis on emotional management and instructor well-being. A quantitative research design was employed, using self-report instruments administered to higher education instructors engaged in distance teaching. Non-parametric statistical analyses revealed strong internal coherence among emotional intelligence dimensions and a pattern of functional empathy characterized by high perspective taking and low personal distress. Self-perceived communication was found to be consistent across interactional contexts, indicating a stable communicative disposition. Most notably, emotional management emerged as a key factor associated with positive work-related emotions among instructors. The findings highlight emotional management as a critical mechanism supporting both teaching effectiveness and emotional sustainability in online learning environments. The study contributes to the literature by integrating emotional intelligence, empathy, and self-perceived communication within a unified empirical framework and offers practical implications for professional development and institutional support in distance higher education. Full article

Dissolved oxygen (DO) is a primary environmental regulator of shrimp physiology and behavior in intensive aquaculture systems. Whether shrimp acoustic emissions quantitatively reflect oxygen-driven behavioral modulation under operational pond conditions, however, remains uncertain due to the difficulty of isolating biologically relevant signals from complex soundscapes. In this study, passive acoustic monitoring was conducted in commercial outdoor ponds culturing Litopenaeus vannamei. A periodic-coding non-negative matrix factorization approach was applied to separate putative shrimp-associated acoustic components from broadband background noise and to obtain stable time–frequency representations of acoustic activity. Temporal variations in the extracted acoustic intensity were compared with simultaneously measured DO concentrations. Rather than relying on global correlation, phase-specific analyses revealed that the putative shrimp-associated acoustic component exhibited consistent positive associations with DO dynamics during both rising and declining phases, whereas background noise showed only weak and non-coherent relationships with DO. These results indicate that the observed acoustic–oxygen relationship is non-stationary and context-dependent. Given the observational nature of the study and potential confounding influences (e.g., aeration and other environmental factors), these findings, which are based on observations from a single pond over a limited recording period (62.85 h) under specific operational conditions, should be interpreted with caution and regarded as a proof-of-concept rather than evidence of general applicability. Nevertheless, the results are consistent with the hypothesis that population-level acoustic activity may reflect environmentally modulated behavioral responses. This highlights the potential of soundscape-based approaches as non-invasive tools for supporting aquaculture monitoring, while emphasizing the need for further validation under controlled and multi-site conditions. Full article

Background and Objectives: Chronic kidney disease (CKD) is an increasingly important global health challenge and is frequently accompanied by psychiatric symptoms, including anxiety. A multidimensional assessment of anxiety in hemodialysis (HD) using the Endler Multidimensional Anxiety Scales (EMAS) has not, to our knowledge, been previously reported. We aim to evaluate the reliability, convergent validity, and exploratory domain-level structure of EMAS in HD patients treated at a dialysis center in Craiova, Romania. Materials and Methods: A total of 103 HD patients underwent clinical and sociodemographic/socioeconomic profiling, cognitive screening using the Mini-Mental State Examination (MMSE), and EMAS administration at two time points (4-week interval) for test–retest evaluation. The anxiety subscale of the Depression, Anxiety, and Stress Scale-21R (DASS-21R) was administered to assess convergent validity. Internal consistency (Cronbach’s α), temporal stability (test–retest correlations and intraclass correlation coefficients), and convergent validity (Pearson correlations) were computed. Exploratory factor analyses were conducted on EMAS domain scores (state, trait, and perceived anxiety domains) as an exploratory structural check. Results: EMAS state and trait anxiety scores were higher in women than in men, while perceived anxiety showed a more heterogeneous pattern across dimensions. Total state anxiety increased with age, particularly after 50 years. Domain-level internal consistency was good for state and acceptable for trait components (standardized α ≈ 0.84 and 0.78 across administrations), whereas perceived anxiety domains showed low cross-domain coherence, consistent with context-specific appraisal. The DASS-21R anxiety subscale showed good internal consistency (α = 0.863). Convergent validity analyses indicated small, domain-specific associations between EMAS scores and DASS-21R anxiety. Domain-level EFA supported a theoretically coherent pattern in which state and trait domains clustered distinctly, while perceived anxiety domains formed a partially separable factor; this pattern was broadly consistent across both administrations. Conclusions: In this HD cohort, EMAS demonstrated good reliability and limited but domain-specific evidence of convergent validity, and exploratory domain-level analyses supported its multidimensional organization. Further studies with larger samples are warranted for item-level structural testing and to inform feasibility-oriented shortening for potential clinical use. Full article

Spiritual care competence (SCC) is increasingly recognized as relevant in mental health, yet no validated tool exists in Slovenia. This study aimed to translate and validate the Spiritual Care Competence Questionnaire (SCCQ) in a Slovene sample of mental-health professionals. Guided by this aim, our research question was the following: to what extent does the SCCQ demonstrate a replicable seven-factor structure, acceptable reliability, construct validity, and coherent group differences in a Slovene sample of mental-health professionals? In a cross-sectional survey (n = 291) across outpatient, inpatient, private, and other settings, we administered the SCCQ together with measures of spiritual sensitivity (SSS), spiritual transcendence (STS), and the BFI-S. Following forward–backward translation and expert review, we conducted item analysis, exploratory and confirmatory factor analyses, and assessed reliability and construct validity. After removing seven psychometrically weak items, a 35-item, seven-factor structure—perception of spiritual needs, team spirit, documentation/tools, spiritual self-awareness, knowledge of other religions, conversation, and empowerment/proactive opening—showed borderline to acceptable fit (TLI = 0.917, CFI = 0.892, RMSEA = 0.068, SRMR = 0.073) and internal consistency (Cronbach’s alpha = 0.67–0.87). Convergent validity was supported by positive associations with SSS/STS, while expected correlations with Big Five traits were small but significant (negative for Emotional Instability). Older age and psychotherapist profession predicted higher SCC. The Slovene SCCQ is a confession-neutral, psychometrically adequate instrument for assessing SCC in mental-health services. Findings highlight curricular needs—especially documentation/tools and team-based engagement—and enable research, education, and quality improvement aligned with international SCCQ validations. Full article

Ballast compaction is a critical factor influencing ballast bed condition and the operational safety of heavy-haul railways. However, existing quantitative evaluation methods often suffer from overly idealized simulation models and limitations in signal processing and assessment frameworks. To address these issues, this study proposes a quantitative analysis approach for ballast compaction by integrating non-uniform medium simulation modeling, wavelet–Singular Value Decomposition (SVD) joint denoising, frequency–wavenumber (F-K) migration imaging, and wavelet packet decomposition (WPD)-based feature extraction. Forward simulations were conducted based on the constructed model, and the proposed methodology was validated using 1.5 GHz (gigahertz, 1 GHz = ${10}^9$ Hz) ground penetrating radar (GPR) data acquired from compaction experiments. The results demonstrate that wavelet–SVD joint denoising effectively suppresses deep coherent noise caused by strong reflections from sleepers, significantly enhancing the identification of deep effective signals and ensuring accurate localization and feature extraction of compaction zones. The Geometric Mean of WPD High/Low-Frequency Energy Ratio (GMHLFER) exhibits a strong positive correlation with the degree of compaction. In simulations, as the proportion of compacted material increased from $9\%$ to $21\%$, the GMHLFER rose from 21.555 to 26.581. In field tests, the value increased from 22.012 to 26.012 as compaction severity progressed from slight to severe, demonstrating stable responses across full-gradient compaction conditions and indicating high robustness and sensitivity. The proposed method provides an effective approach for quantitative characterization of ballast compaction in heavy-haul railways, and offers a promising technical pathway for intelligent inspection and condition assessment of railway ballast beds. Full article

Optical klystrons have been developed in storage ring free-electron lasers (FELs) as insertion devices to increase the FEL gain in a straight section with limited length. By adjusting the magnetic field in the dispersion section of the optical klystron to shift the relative delay between the electron bunch and FEL pulse from an integer multiple of the FEL wavelength, FELs can oscillate at two wavelengths. The electron density of the electron bunch that interacts with the FEL pulse in a small-signal regime is modulated at the FEL wavelength period. When the FEL oscillates simultaneously at two wavelengths, the electron density of the electron bunch beats through the modulation with two periods. This beat generates long-wavelength coherent edge radiation at a bending magnet located in the straight section containing the optical klystron. Difference-frequency waves induced by dual-wavelength ultraviolet free-electron lasers generate a high-intensity mid-infrared monochromatic beam. Our findings will lay the foundation for the development of the difference-frequency waves of soft X-rays and extreme ultraviolet light using hard X-ray FELs. Full article

Cytomegalovirus (CMV) infection of the anterior segment is increasingly recognized as an important cause of corneal endotheliitis and secondary glaucoma, even in immunocompetent individuals. CMV corneal endotheliitis typically presents with coin-shaped or linear keratic precipitates (KPs), corneal edema, mild anterior chamber inflammation, and recurrent intraocular pressure (IOP) elevation; persistent or episodic ocular hypertension may progress to glaucomatous optic neuropathy if inadequately treated. Definitive diagnosis relies on aqueous humor polymerase chain reaction (PCR) testing for CMV DNA, supported by adjunctive imaging including specular microscopy, anterior segment optical coherence tomography (AS-OCT), and in vivo confocal microscopy (IVCM). Management requires a comprehensive strategy integrating antiviral therapy, anti-inflammatory treatment, and appropriate IOP control. Topical or systemic ganciclovir remains the cornerstone, while refractory disease may necessitate surgical intervention. Older age and male sex, host immune status, prolonged or recurrent CMV infection, and pre-existing ocular conditions are major risk factors for progression and poor outcomes. The pathogenesis of secondary glaucoma is thought to involve both direct viral cytopathic effects and inflammation-mediated damage to the trabecular meshwork (TM), resulting in impaired aqueous outflow. Therefore, early recognition, accurate diagnosis, and effective treatment are essential to prevent corneal decompensation and permanent vision loss. Full article

Accurate and spatially resolved yield estimation is a critical requirement for precision agriculture and orchard management. This paper presents a geometrically consistent, orchard-scale apple yield estimation framework that integrates GNSS–visual-inertial odometry (VIO) fusion, deep learning-based object detection, multi-frame tracking, three-dimensional triangulation, and incremental factor-graph optimization. Camera poses are obtained using ZED GNSS–VIO fusion and subsequently refined using an iSAM2-based nonlinear smoothing approach that incorporates strong relative-motion constraints and soft global ENU (East-North-Up) translation priors. Apples are detected using a YOLO-based model and associated across frames via CoTracker3, enabling robust multi-view landmark reconstruction. Reprojection factors and landmark priors are incorporated into a unified nonlinear factor graph to jointly optimize camera trajectories and 3D apple positions. The reconstructed apples are spatially aggregated into a grid-based mass map, where individual fruit volumes are estimated assuming spherical geometry and converted to mass using density models. The resulting ENU-referenced yield plot provides a structured representation of orchard production variability. Experimental results demonstrate significant reductions in reprojection error after optimization and improved global consistency of the trajectory, leading to stable and spatially coherent 3D reconstructions. The proposed pipeline bridges perception, geometry, and optimization, providing a scalable solution for orchard-scale yield mapping and decision support in precision agriculture. Full article

Background: Early childhood caries (ECC) is one of the most common chronic diseases in children and remains unevenly distributed across populations. It is associated with pain, impaired function, and long-term health consequences. Although advances have been made in understanding its aetiology and prevention, important gaps in evidence limit progress in prevention, early detection, and equitable care. Objective: To examine current evidence on ECC and identify key research gaps across biological, behavioral, social, and health system domains. Methods: This narrative review draws on peer-reviewed literature addressing ECC epidemiology, pathogenesis, risk factors, diagnosis, management, and service delivery. The literature was examined to identify areas where evidence is limited, inconsistent, or insufficient to inform clinical practice and public health policy. Results: Research on ECC remains uneven across levels. Longitudinal evidence linking microbiome dynamics, host susceptibility, and lesion progression is limited, restricting causal understanding. Genetic and epigenetic contributions are incompletely defined, particularly in diverse populations. Although socioeconomic gradients are well established, integrative models connecting structural determinants with biological mechanisms are scarce. Emerging diagnostic tools, including biomarkers and artificial intelligence, lack robust evidence demonstrating improved clinical or behavioral outcomes. Implementation research addressing scalability, cost-effectiveness, and equity impact is underdeveloped, especially in low-resource settings. Long-term systemic and developmental consequences of ECC remain insufficiently characterized. Conclusions: Addressing ECC requires integrated and equity-oriented research frameworks that bridge biological, social, diagnostic, and implementation domains. Clarifying these gaps is essential to inform coherent prevention strategies and reduce persistent disparities in child oral health. Full article

Spring and autumn phenology jointly regulate terrestrial carbon, water, and energy exchanges, yet the mechanisms linking seasonal transitions remain debated under increasing hydroclimatic stress. Here, we integrate satellite-derived phenology with reanalysis-based indicators of land–atmosphere coupling to examine how spring onset interacts with growing season controlling factors and how these interactions shape autumn senescence at the global scale. Globally, start-of-season (SOS) and end-of-season (EOS) timings are positively coupled, with later SOS generally followed by later EOS, and this relationship becomes stronger when only later-SOS years are considered. However, SOS does not induce coherent global shifts in growing season climate limitation. Piecewise structural equation modeling reveals that SOS influences EOS primarily through a direct phenological pathway, with a mean path coefficient of ~0.4 day·day⁻¹ explaining approximately 26% of global EOS variability. In contrast, energy and water-mediated pathways contribute smaller but spatially heterogeneous effects, together accounting for ~5% of explained variance on average. SOS–EOS coupling is strongest in water-limited regimes, particularly in grasslands and shrublands. Managed croplands exhibit distinct and more heterogeneous responses, reflecting partial decoupling of phenology from natural hydroclimatic constraints. Collectively, our results indicate that spring phenology exerts a robust but spatially variable influence on autumn timing, dominated by direct effects rather than indirect mediation through growing season climate limitations, with regional modulation imposed by background hydroclimatic conditions. Full article

Background: Artificial intelligence (AI) is increasingly incorporated into higher education. However, most empirical studies focus on technological adoption or learner satisfaction rather than on how pedagogical design, perceived learning impact, and student experience interact within AI-mediated learning environments. Understanding these relationships is essential to determine whether AI supports higher-order reasoning processes rather than merely increasing technological engagement. Objective: This preliminary study aimed to develop and evaluate a theory-driven AI-mediated pedagogical framework and examine relationships between pedagogical design, perceived learning impact, and student satisfaction in a university learning context. Methods: An observational educational evaluation was conducted during implementation of an AI-mediated instructional framework in an undergraduate physiotherapy course. The full academic cohort (n = 22) completed a 24-item questionnaire assessing seven pedagogical domains on a 5-point Likert scale. Descriptive statistics, Pearson correlations, exploratory regression modeling, and factor analysis were used to examine relationships among domains. Academic performance indicators were summarized descriptively. Results: Students reported high evaluations across all domains (means > 4.5/5). The strongest association with satisfaction was perceived learning impact (r = 0.79, p < 0.001). Moderate correlations were found for usability (r = 0.66), AI content quality (r = 0.61), pedagogical coherence (r = 0.58), critical thinking (r = 0.52), and ethical integration (r = 0.47). Academic pass rates exceeded 90%. Conclusions: Perceived learning impact emerged as the central mechanism linking AI-mediated instructional design to student satisfaction, suggesting that the educational value of AI depends on alignment with cognitively demanding learning processes. Full article

Human transglutaminases (hTGs) are Ca²⁺-dependent enzymes that catalyze protein crosslinking, deamidation and other post-translational modifications, thus acting as key stabilizers of tissue architecture and modulators of protein function across diverse physiological contexts. This family comprises eight catalytically active members, TG1-7, the blood coagulation factor FXIII, and the inactive structural protein Band 4.2 of the erythrocyte membrane. Recent structural and biochemical advances have refined our understanding of the molecular principles governing transglutaminase function. Thus, current evidence reveals how domain organization and catalytic architecture integrate calcium binding, nucleotide-dependent regulation in TG2 and proteolytic activation in selected isoforms to control enzymatic activity. In this review, we provide an updated and comprehensive overview of the active hTGs, combining structural, biochemical and functional data to explain how closely related enzymes achieve isoform-specific regulation and distinct biological roles. We further examine how disruption of these mechanisms contributes to human pathology, highlighting representative examples in autoimmunity, inherited disorders and complex diseases. By integrating recent biochemical and structural findings with disease-associated evidence, we aim to offer a coherent framework for understanding how TG regulation underlies their diverse biological functions and clinical relevance. Full article

Conservation easements (CEs) represent a complex policy instrument designed to mediate the feedback loops within coupled human and natural systems in protected areas. However, their efficacy is often constrained by a lack of systemic understanding of the localized drivers of community support. Building upon the successful implementation of Forest Land Easements (FLEs) within China’s Qianjiangyuan National Park Pilot, this study investigates the potential to expand this policy model to other land types. This study investigates the multilevel factors influencing residents’ willingness to adopt three types of CEs, including forest land (FLE), agricultural land (ALE) and homestead land (HLE) easements in China’s Qianjiangyuan National Park Pilot, the country’s primary CE reform site. We conceptualize a hierarchical support model wherein community participation (CP) and human well-being (HW) interact with support for park management (SM), forming a subsystem that drives decisions within the broader land-use. Utilizing structural equation modelling (SEM) and stepwise regression analysis on survey data from 336 households, we tested this model. The results reveal that SM acts as a critical direct mediator and positive driver of CE acceptance, while CP and HW exert significant indirect effects through SM, demonstrating a key feedback pathway. Regression analyses further elucidate that support for different CE types is driven by distinct configurations of factors, highlighting the heterogeneous nature of subsystems. Notably, livelihood benefits and prior participation experiences emerged as consistent, cross-cutting systemic leverages. It demonstrates that leveraging the implementation experience and community support gained from existing forest land easements is crucial. This study concludes that effective CE design must move beyond one-size-fits-all approaches. It necessitates differentiated, adaptive policies that are coherently aligned with local livelihood subsystems and strategically strengthen participatory feedback mechanisms initiated by successful FLEs. Our findings provide an evidence-based framework for designing resilient, socially sustainable conservation policies in complex protected area systems, grounded in proven practice. Full article

Aims: To conduct an exploratory analysis the psychometric properties of the Spanish version of the Soft Skills Questionnaire for Nurses (SSQN) and examine its conceptual coherence and its preliminary empirical behavior among nursing professionals and students. The aim is to critically assess the instrument’s suitability as a tool for exploring perceptions and self-reported soft skills rather than to establish its psychometric validity. Design: Exploratory methodological study focused on analyzing the empirical performance and conceptual adequacy of the SSQN within a Spanish sample, with particular attention to the internal patterns of responses and the coherence between the instrument’s items and its proposed dimensions. Methods: The process included the translation of the questionnaire and an empirical application in a sample of nursing professionals and students. Exploratory analyses were performed, including exploratory factor analysis and reliability assessment (Cronbach’s alpha and McDonald’s omega), using Jeffreys’s Amazing Statistics Program (JASP) (version 1.18.3), in order to examine the structural performance of the instrument and detect possible conceptual and methodological limitations. Results: The SSQN showed notable inconsistencies in its empirical structure, with dimensions that did not display clear or theoretically coherent patterns. Factor inconsistencies and low internal consistency suggest that the instrument does not adequately capture the multidimensionality of interpersonal skills, reflecting weaknesses inherent in its original formulation rather than in the adaptation process. Conclusions: The Spanish version of the SSQN cannot be considered valid or reliable in its current form. The results underscore the need for a thorough revision of the questionnaire and a conceptual rethinking to develop more robust tools for assessing soft skills. Impact: This study highlights the need for a solid methodological evaluation before introducing instruments designed to measure complex and subjective competencies in the healthcare field. Full article

Waveguide-like propagation in elongated underground environments—utility corridors, logistics tunnels—generates dense multipath that can cause the earliest or strongest resolvable channel impulse response (CIR) component to originate from a specular reflection rather than the direct line-of-sight (LOS) path. In the single-anchor CIR-tap-based implementations common to practical ultra-wideband (UWB) systems, baseline estimators such as phase-difference-of-arrival (PDOA) and MUSIC rely on selecting a single dominant CIR component, producing large angle-of-arrival (AoA) errors whenever the selected path is a reflection. We propose a multipath credibility selection (MCS) AoA estimator, MCS-AoA, that does not require explicit LOS/NLOS classification. The algorithm scores each resolvable CIR component with four credibility factors—amplitude significance, time-of-flight (TOF) consistency, inter-baseline phase–geometry agreement, and cross-baseline coherence—and fuses retained candidates into a credibility-weighted spatial covariance matrix for 2D MUSIC search. Field experiments on a custom five-channel coherent UWB platform compare MCS-AoA against six baselines—PDOA, MUSIC, MVDR/Capon, TLS-ESPRIT, PwMUSIC, and DNN-AoA. In an underground corridor (5–40 m), MCS-AoA achieves an azimuth/elevation MAE of 1.00°/1.46°, outperforming all baselines (PDOA: 2.26°/2.49°; MUSIC: 1.76°/2.40°; next-best PwMUSIC: 1.44°/2.17°); in a logistics tunnel (5–80 m), it achieves a 1.19° overall azimuth MAE. Simulations corroborate these gains, with a 0.71° azimuth RMSE at 80 m (69.3% reduction over PDOA) and 86.6% of estimates falling within 1°. Full article