Search Results (273)

Background/Objectives: Emotional competence is a crucial skill in nursing education, yet it remains underdeveloped in academic curricula. This study aims to (1) propose and preliminarily apply the TRI-COM model as a conceptual and educational framework to operationalize the definition of emotions within nursing contexts, and (2) explore the multidimensional structure of emotional competence among nursing students. Methods: A cross-sectional study was conducted with 233 nursing students (M_age = 23.79, SD = 5.19) from various Italian universities, with 82.8% identifying as female. The participants completed an online questionnaire including the Toronto Alexithymia Scale (TAS-20) and the Jefferson Scale of Empathy—Health Profession Student (JSE-HPS) version. Descriptive statistics, t-test, ANOVA, and Pearson’s correlation analyses were performed. Results: The overall mean TAS-20 score was 60.36 (SD = 11.22), which is close to the clinical threshold (cut-off = 61). The EOT subscale showed the highest mean (M = 26.48, SD = 3.16), suggesting a tendency toward externally oriented thinking. The mean JSE-HPS total score was 87.05 (SD = 7.88), with higher scores for Perspective Taking (M = 60.95, SD = 7.42) than Compassionate Care (M = 18.92, SD = 6.40). A significant gender difference was found in Perspective Taking (female: M = 61.54, male: M = 58.10; p = 0.007). The ANOVA results showed no significant differences in empathy across academic years, but the DIF subscale of TAS-20 showed a trend near significance (p = 0.053). Significant negative correlations were observed between age and TAS-20 scores (e.g., age–TAS-20 total: r = −0.23, p < 0.001). Conclusions: The findings suggest a general tendency toward rationalization and emotional detachment among students, possibly as a coping strategy in emotionally demanding contexts. The TRI-COM model—an original pedagogical framework inspired by tripartite theories of emotion—was used as a conceptual lens, providing a preliminary framework to interpret emotional competence in nursing education. Further research is needed to validate its educational relevance and explore practical applications within curricula. Full article

High strength and high ductility concrete (HSHDC) exhibit exceptional compressive strength (up to 90 MPa) and remarkable tensile ductility (ultimate tensile strain reaching 6%), making them highly resilient under impact loading. To elucidate the influence of strain rate and wet–dry cycling of salt spray on the dynamic compressive response of HSHDC, a series of tests was conducted using a 75 mm split Hopkinson pressure bar (SHPB) system on specimens exposed to cyclic corrosion for periods ranging from 0 to 180 days. The alternating seasonal corrosion environment was reproduced by using a programmable walk-in environmental chamber. Subsequently, both uniaxial compression and SHPB tests were employed to evaluate the post-corrosion dynamic compressive properties of HSHDC. Experimental findings reveal that corrosive exposure significantly alters both the static and dynamic compressive mechanical behavior and constitutive characteristics of HSHDC, warranting careful consideration in long-term structural integrity assessments. As corrosion duration increases, the quasi-static and dynamic compressive strengths of HSHDC exhibit an initial enhancement followed by a gradual decline, with stress reaching its peak at 120 days of corrosion under all strain rates. All specimens demonstrated pronounced strain-rate sensitivity, with the dynamic increase factor (DIF) being minimally influenced by the extent of corrosion under dynamic strain rates (112.6–272.0 s⁻¹). Furthermore, the peak energy-consumption capacity of HSHDC was modulated by both the duration of corrosion and the applied strain rate. Full article

The aim of the present study was to investigate the expression of related genes during the differentiation process of baNCSCs into adipocytes using transcriptomics technique, thereby clarifying the potential mechanism underlying baNCSCs differentiation into adipocytes and providing insights into lipid metabolism and regulation of lipid deposition in ruminants. Transcriptomic analysis was conducted on the adipocytes of baNCSCs on days 0 (CON0), 3 (DIF3), and 9 (DIF9) of differentiation. The results showed that in the early stage of adipocyte differentiation of baNCSCs, differentially expressed genes (DEGs) are mainly involved in metabolic pathways such as chromosome modification, cell cycle progression, and regulation of stem cell pluripotency. In the middle and late stages of differentiation, DEGs are mainly involved in metabolic pathways such as changes in cell morphology and synthesis of fatty acids and triglycerides. Predicting the top 10 core hub genes (CHGs) in the protein–protein interaction (PPI) network that regulate various differentiation stages of adipocytes reveals that ERBB2, EGFR, and MYC are upregulated during the early differentiation stage. In contrast, ITGB1, KRAS, CCND1, ACTB, VEGFA, MET, and HRAS are downregulated. During the middle and late stages of differentiation, the expressions of TP53, CASP3, STAT3, CTNNB1, JUN, EGFR, and MYC are upregulated, while IGF1R, PTEN, and HRAS are downregulated. In conclusion, the primary enrichment pathways of DEGs vary at distinct stages of adipocyte induction and differentiation in baNCSCs. Full article

Background/Objectives: Anti-p200 pemphigoid is a rare and likely underdiagnosed autoimmune blistering disorder. Laminin γ1 and laminin β4 have been implicated as potential target antigens in its pathogenesis. Recently, a novel indirect immunofluorescence assay targeting anti-laminin β4 antibodies has been developed, demonstrating high sensitivity and specificity, and offering a valuable tool for improved diagnosis. Methods: Of the 451 patients, 21 were selected for further laboratory analysis based on medical records. Sera from 10 patients, which showed a positive direct immunofluorescence (DIF) result and negative results in multiplex enzyme-linked immunosorbent assays (ELISAs) and/or mosaic six-parameter indirect immunofluorescence (IIF) for various autoimmune bullous diseases, were tested for the presence of anti-laminin β4 antibodies. Additionally, sera from 11 patients with positive DIF and positive ELISA for antibodies against BP180 and/or BP230 were analyzed. Results: Among the 10 patients with positive DIF and negative ELISA and/or mosaic six-parameter IIF, 6 sera were positive for anti-laminin β4 antibodies. These patients presented with atypical clinical features. In contrast, all 11 sera from patients with both positive DIF and positive ELISA for BP180 and/or BP230 were negative for anti-laminin β4 antibodies. Conclusions: In patients with a positive DIF result but negative ELISA and/or mosaic six-parameter IIF findings, testing for anti-laminin β4 antibodies should be considered. Furthermore, in cases presenting with atypical clinical features—such as acral distribution of lesions, intense pruritus, or erythematous–edematous plaques—the possibility of anti-p200 pemphigoid should be included in the differential diagnosis. Full article

This study investigates the impact and mechanisms of digital inclusive finance (DIF) on high-quality economic development in China. Drawing on panel data from 281 prefecture-level cities between 2011 and 2021, we employ a Spatial Durbin Model (SDM) to analyze both the direct effects and spatial spillovers of DIF. The results indicate that (1) DIF has a significantly positive effect on high-quality development, which remains robust after conducting various stability and endogeneity tests; (2) DIF strongly contributes to economic upgrading in eastern regions, while its impact is weaker or even negative in central and western regions, revealing notable regional disparities exist; (3) a key finding is the identification of a double-threshold effect, suggesting that the positive influence of DIF only emerges when financial and industrial development surpass certain thresholds; (4) results from the two-regime SDM further show that spillover effects are more prominent in non-central cities than in central ones; and (5) mechanism analysis reveals that DIF facilitates high-quality growth primarily by promoting industrial structure upgrading. These findings underscore the importance of region-specific policy strategies to enhance the role of DIF and reduce spatial disparities in development across China. Full article

Brown spot, caused by Alternaria alternata, is the most important leaf fungal disease threatening kiwifruit production in China, and it is typically controlled through the application of fungicides, such as procymidone and difenoconazole. To date, fungicide resistance development has not yet been systematically reported for the pathogen of kiwifruit. A total of 135 single-conidium A. alternata isolates were collected from different cities in Zhejiang Province, China. Alternaria alternata developed prevailing resistance to procymidone and initial resistance to difenoconazole, with resistance frequencies of 60.7 and 13.3%, respectively. Positive cross-resistance was observed between procymidone and iprodione but not between procymidone and difenoconazole, tebuconazole, prochloraz, pydiflumetofen, pyraclostrobin, or thiophanate-methyl. Moreover, no cross-resistance was observed between difenoconazole and all other tested fungicides, including the two other demethylation inhibitors, tebuconazole and prochloraz. A fitness penalty was not detected in procymidone-resistant (Pro^R) or difenoconazole-resistant (Dif^R) isolates. However, double-resistant (Pro^R Dif^R) isolates had a fitness penalty, showing significantly decreased sporulation, germination, and pathogenicity. The P894L single point mutation, caused by the change from CCA to CTA at the 894th codon of Os1, was detected in Pro^R isolates. Molecular dynamic simulation showed that the P894L mutation significantly decreased the inhibitory activity of procymidone against AaOs1 in A. alternata. These results provide insight into the development and characteristics of fungicide resistance, offering guidance for the study and management of kiwifruit diseases. Full article

Clouds modulate the net radiative flux that interacts with both shortwave (SW) and longwave (LW) radiation, but the uncertainties regarding their effect in polar regions are especially high because ground observations are lacking and evaluation through satellites is made difficult by high surface reflectance. In this work, sky conditions for six different polar stations, two in the Arctic (Ny-Ålesund and Utqiagvik [formerly Barrow]) and four in Antarctica (Neumayer, Syowa, South Pole, and Dome C) will be presented, considering the decade between 2010 and 2020. Measurements of broadband SW and LW radiation components (both downwelling and upwelling) are collected within the frame of the Baseline Surface Radiation Network (BSRN). Sky conditions—categorized as clear sky, cloudy, or overcast—were determined using cloud fraction estimates obtained through the RADFLUX method, which integrates shortwave (SW) and longwave (LW) radiative fluxes. RADFLUX was applied with daily fitting for all BSRN stations, producing two cloud fraction values: one derived from shortwave downward (SWD) measurements and the other from longwave downward (LWD) measurements. The variation in cloud fraction used to classify conditions from clear sky to overcast appeared consistent and reasonable when compared to seasonal changes in shortwave downward (SWD) and diffuse radiation (DIF), as well as longwave downward (LWD) and longwave upward (LWU) fluxes. These classifications served as labels for a machine learning-based classification task. Three algorithms were evaluated: Random Forest, K-Nearest Neighbors (KNN), and XGBoost. Input features include downward LW radiation, solar zenith angle, surface air temperature ($T_a$), relative humidity, and the ratio of water vapor pressure to $T_a$. Among these models, XGBoost achieved the highest balanced accuracy, with the best scores of 0.78 at Ny-Ålesund (Arctic) and 0.78 at Syowa (Antarctica). The evaluation employed a leave-one-year-out approach to ensure robust temporal validation. Finally, the results from cross-station models highlighted the need for deeper investigation, particularly through clustering stations with similar environmental and climatic characteristics to improve generalization and transferability across locations. Additionally, the use of feature normalization strategies proved effective in reducing inter-station variability and promoting more stable model performance across diverse settings. Full article

Metallurgical equipment foundations exposed to prolonged 300–500 °C environments are subject to explosion risks, necessitating materials that are resistant to thermo-shock-coupled loads. This study investigated the real-time dynamic compressive behavior of high-performance concrete (HPC) reinforced with steel fibers (SFs), polypropylene fibers (PPFs), polyvinyl alcohol fibers (PVAFs), and their hybrid systems under thermo-shock coupling using real-time high-temperature (200–500 °C) SHPB tests. The results revealed temperature-dependent dynamic responses: SFs exhibited a V-shaped trend in compressive strength evolution (minimum at 400 °C), while PPFs/PVAFs showed inverted V-shaped trends (peaking at 300 °C). Hybrid systems demonstrated superior performance: SF-PVAF achieved stable dynamic strength at 200–400 °C (dynamic increase factor, DIF ≈ 1.65) due to synergistic toughening via SF bridging and PVAF melt-induced pore energy absorption. Microstructural analysis confirmed that organic fiber pores and SF crack-bridging collaboratively optimized failure modes, reducing brittle fracture. A temperature-adaptive design strategy is proposed: SF-PVAF hybrids are prioritized for temperatures of 200–400 °C, while SF-PPF combinations are recommended for 400–500 °C environments, providing critical guidance for explosion-resistant HPC in extreme thermal–industrial settings. Full article

Brassica napus is one of the most important oil crops. Rapid breeding of excellent genotypes is an important aspect of breeding. As a cutting-edge and reliable technique, genome-wide selection (GS) has been widely used and is influenced by many factors. In this study, ten phenotypic traits of two populations were studied, including oleic acid (C18:1), linoleic acid (C18:2), linolenic acid (C18:3), glucosinolate (GSL), seed oil content (SOC), and seed protein content (SPC), silique length (SL), days to initial flowering (DIF), days to final flowering (DFF), and the flowering period (FP). The effects of different GS models, marker densities, population designs, and the inclusion of nonadditive effects, trait-specific SNPs, and deleterious mutations on GS were evaluated. The results highlight the superior prediction accuracy (PA) under the RF model. Among the ten traits, the PA of glucosinolate was the highest, and that of linolenic acid was the lowest. At the same time, 5000 markers and a population of 400 samples, or a training population three times the size of an applied breeding population, can achieve optimal performance for most traits. The application of nonadditive effects and deleterious mutations had a weak effect on the improvement of traits with high PA but was effective for traits with low PA. The use of trait-specific SNPs can effectively improve the PA, especially when using markers with p-values less than 0.1. In addition, we found that the PA of traits was significantly and positively correlated with the number of markers, according to p-values less than 0.01. In general, based on the associated population, a GS system suitable for B. napus was established in this study, which can provide a reference for the improvement of GS and is conducive to the subsequent application of GS in B. napus, especially in the aspects of model selection of GS, the application of markers, and the setting of population sizes. Full article

Background: Patient-reported outcome measures (PROMs) are essential for capturing the lived experiences of individuals managing chronic diseases. However, few PROMs have been culturally adapted and validated for Arabic-speaking populations. Aim: This study aimed to translate, culturally adapt, and validate the Long-Term Conditions Questionnaire (LTCQ) for use among Arabic-speaking adults living with chronic diseases in Jordan. Methods: Following forward–backward translation and an expert review, a cross-sectional survey of 1057 adults with chronic illnesses was conducted. The psychometric evaluation involved exploratory and confirmatory factor analyses (EFA and CFA) and Rasch modelling. While the original LTCQ assumed a unidimensional structure, EFA and CFA supported a two-factor solution: Empowerment and Functional Wellbeing, and Health-Related Psychosocial Distress. Results: The Rasch analysis confirmed that the item response thresholds were ordered, with good item targeting, and no differential item functioning (DIF) by gender. The removal of one poorly performing item resulted in a refined 19-item scale with strong reliability and validity. Conclusions: The Arabic LTCQ demonstrated robust psychometric properties and cultural relevance, supporting its use in clinical care, research, and policy initiatives. Future work should examine longitudinal responsiveness and further validate the tool across diverse Arabic-speaking populations. Full article

Fly ash and slag powder, as two of the most widely utilized industrial solid waste-based mineral admixtures, have demonstrated through extensive validation that their combined incorporation technology effectively enhances the mechanical properties and microstructural characteristics of concrete. Systematic investigations remain imperative regarding material response mechanisms under dynamic loading conditions. This study conducted microstructural analysis, static compression tests, and dynamic Split Hopkinson Pressure Bar (SHPB) impact compression tests on concrete specimens, complemented by dynamic impact simulations employing an established three-dimensional mesoscale concrete aggregate model. Through integrated analysis of macroscopic mechanical test results, mesoscale numerical simulations, and microstructural characterization data, the research systematically elucidated the influence mechanisms of different mineral admixture combinations on concrete’s dynamic mechanical behavior, energy dissipation characteristics, and fracture mechanisms. The results showed that all specimens exhibited strain rate enhancement characteristics as the strain rate increased. As the admixture approach transitioned from non-admixture to single admixture and subsequently to binary admixture, the dynamic strength, elastic modulus, and DIF of concrete increased progressively. Both the energy dissipation capacity and its proportion relative to total energy absorption showed continuous enhancement. The simulated stress–strain curves, failure modes, and fracture processes show good agreement with experimental results, this effectively verifies both the scientific validity of the mesoscale concrete model’s multiscale modeling approach and the reliability of the numerical simulations. Compared to FHC1, FMHC1’s mesoscale structure can more effectively convert externally applied energy into stored internal energy, thereby achieving superior dynamic compressive energy dissipation capacity. Full article

The rabies virus (genus Lyssavirus), is a deadly zoonotic agent affecting humans and animals. Although Mexico has been declared free of canine rabies (V1), sylvatic rabies persists. This study aimed to determine the prevalence of the virus in Desmodus rotundus and other non-hematophagous bat species in Oaxaca. The methodology comprised four stages: a literature review, data requests to the Servicio Nacional de Sanidad, Inocuidad y Calidad Agroalimentaria (SENASICA), fieldwork using mist nets across 15 municipalities in Oaxaca, and diagnosis via direct immunofluorescence at the Centro Nacional de Servicios de Diagnóstico en Salud Animal (CENASA). SENASICA reported 89 positive rabies cases (2014–2023) across six laboratories, with the majority (67.02%) attributed to the Oaxaca State Public Health Laboratory. Among the 194 bats analyzed (129 D. rotundus), only three tested positive for the virus, yielding a prevalence of 1.54%. Positive cases were exclusively identified in D. rotundus from San Lucas Ojitlán and The Heroic City of Tlaxiaco. This prevalence aligns with that of national studies, which ranges from 0.05% to 3%. These findings underscore the need to maintain epidemiological surveillance in wild and domestic fauna, alongside public awareness campaigns highlighting bats’ ecological importance for ecosystem conservation and the risks associated with their decline. Full article

This study presents a hybrid intelligent model for predicting Olympic medal distribution at the 2028 Los Angeles Games, based on data-intelligence fusion (DIF). By integrating historical medal records, athlete performance metrics, debut medal-winning countries, and coaching resources, the model aims to provide accurate national medal forecasts. The model introduces a Performance Score (PS) system combining a Traditional Advantage Index (TAI) via K-means clustering, an Athlete Strength Index (ASI) using a backpropagation neural network, and a Host effect factor. Sub-models include an autoregressive integrated moving average model for time-series forecasting, logistic regression for predicting debut medal-winning countries, and random forest regression to quantify the “Great Coach” effect. The results project America winning 44 gold and 124 total medals, and China 44 gold and 94 total medals. The model demonstrates strong accuracy with root mean square errors of 3.21 (gold) and 4.32 (total medals), and mean-relative errors of 17.6% and 8.04%. Compared to the 2024 Paris Olympics, the model projects a notable reshuffling in 2028, with the United States expected to strengthen its overall lead as host while countries like France are predicted to experience significant declines in medal counts. Findings highlight the nonlinear impact of coaching and event expansion’s role in medal growth. This model offers a strategic tool for Olympic planning, advancing medal prediction from simple extrapolation to intelligent decision support. Full article

Mean–geometric mean (MGM) linking compares group differences on a latent variable $\theta$ within the two-parameter logistic (2PL) item response theory model. This article investigates three specifications of MGM linking that differ in the weighting of item difficulty differences: unweighted (UW), discrimination-weighted (DW), and precision-weighted (PW). These methods are evaluated under conditions where random DIF effects are present in either item difficulties or item intercepts. The three estimators are analyzed both analytically and through a simulation study. The PW method outperforms the other two only in the absence of random DIF or in small samples when DIF is present. In larger samples, the UW method performs best when random DIF with homogeneous variances affects item difficulties, while the DW method achieves superior performance when such DIF is present in item intercepts. The analytical results and simulation findings consistently show that the PW method introduces bias in the estimated group mean when random DIF is present. Given that the effectiveness of MGM methods depends on the type of random DIF, the distribution of DIF effects was further examined using PISA 2006 reading data. The model comparisons indicate that random DIF with homogeneous variances in item intercepts provides a better fit than random DIF in item difficulties in the PISA 2006 reading dataset. Full article

Background: The Montreal Cognitive Assessment (MoCA) is widely used to evaluate global cognitive function; however, its precision in measurement in heterogeneous populations—especially among patients with Parkinson’s disease (PD)—remains underexplored. Methods: In this multicenter cross-sectional study, we examined the psychometric properties of the Brazilian Portuguese MoCA in 484 PD patients (age range, 26–90 years; mean ± SD, 59.9 ± 11.1 years; disease duration range, 1–35 years; mean ± SD, 8.7 ± 5.4 years) using Item Response Theory (IRT). The Graded Response Model (GRM) was employed to estimate item difficulty and discrimination parameters, and differential item functioning (DIF) concerning age and education was investigated via a Multiple Indicators Multiple Causes (MIMIC) model. Results: The MoCA demonstrated essential unidimensionality and robust model fit. GRM analyses revealed that items within the Attention and Naming domains had high discrimination, indicating sensitivity to subtle cognitive deficits, while Memory items exhibited lower discrimination. Orientation items showed low difficulty thresholds, suggesting a propensity for ceiling effects. The MIMIC model further indicated that age and education significantly influenced overall scores: increasing age was associated with lower performance, whereas higher educational attainment correlated with better outcomes, particularly in Memory Recall and Executive/Visuospatial domains, even after accounting for their modest inverse relationship. Conclusions: Our findings support the validity of the Brazilian Portuguese MoCA for cognitive screening in PD while highlighting item-level biases linked to age and education. These results advocate for using education-adjusted norms and computerized scoring algorithms that incorporate item parameters, ultimately enhancing the reliability and fairness of cognitive assessments in diverse clinical populations. Full article