Search Results (19,385)

Background: Langerhans Cell Histiocytosis (LCH) is a rare histiocytic hematological disorder that frequently involves the lungs. Due to a lack of data about sex-related differences in LCH, the aim of this study is to evaluate sex-related differences in pulmonary function in a cohort of patients with LCH. Methods: We retrospectively analyzed data from 79 adult patients diagnosed with LCH. Demographic, clinical, and spirometric data were collected and compared by sex. Continuous variables were analyzed using the Mann–Whitney test and categorical variables were analyzed with the Chi-square test. Results: Out of 79 patients, 47 (59.5%) were females and 32 (40.5%) were males. Women showed significantly lower diffusing capacity of the lungs for carbon monoxide (DLCO%) and lower diffusing capacity of the lungs for carbon monoxide per unit of alveolar volume (DLCO/VA%) compared to men. Females showed a trend toward lower small airway indices, including maximal expiratory flow at 25 (MEF₂₅%) and forced expiratory flow at 25–75% (FEF_25–75%), though this was not statistically significant, while the residual volume-to-total lung capacity (RV/TLC) ratio was significantly higher in women. Among the functional parameters, DLCO% showed the highest accuracy (AUC 0.70) in the identification of lung involvement after multivariate regression analysis. Conclusions: Our findings suggest that the combination of lower gas exchange efficiency and increased peripheral air trapping secondary to small airway involvement in female patients may reflect the presence of a distinct functional LCH phenotype in women characterized by early small airway involvement and altered ventilation–perfusion dynamics, which may influence the clinical management of these patients. Furthermore, the moderate predictive value of DLCO% for lung involvement at baseline in LCH women suggests that DLCO may contribute to the detection of LCH women with lung involvement, although it should not be considered a definitive diagnostic test without a prospective and independent external validation. Full article

To evaluate water pollution status and sustainable development potential in the Huai River Basin, this study focused on the spatiotemporal evolution and influencing factors of the grey water footprint (GWF) across 35 cities in the basin from 2005 to 2020. This study quantifies the GWF from agricultural, industrial, and domestic perspectives and analyzes its spatial disparities by incorporating spatial autocorrelation analysis. The Tapio decoupling model was applied to explore the relationship between pollution and economic growth, and geographic detectors along with the STIRPAT model were utilized to identify driving factors. The results revealed no significant global spatial clustering of GWF in the basin, but a pattern of “high in the east and west, low in the north and south” emerged, with high-value areas concentrated in southern Henan and northern Jiangsu. By 2020, 85.7% of cities achieved strong decoupling, indicating improved coordination between the environment and economy. Key driving factors included primary industry output, crop sown area, and grey water footprint intensity, with a notable interaction between agricultural output and grey water footprint intensity. The quantitative analysis based on the STIRPAT model demonstrated that seven factors, including grey water footprint intensity and total crop sown area, exhibited significant contributions to influencing variations. Ranked by importance, these factors were grey water footprint intensity > total crop sown area > urbanization rate > population size > secondary industry output > primary industry output > industrial wastewater discharge, collectively explaining 90.2% of the variability in GWF. The study provides a robust scientific basis for water pollution control and differentiated management in the river basin and holds significant importance for promoting sustainable development of the basin. Full article

This study presents an approach based on machine learning (ML) techniques to analyze the relationship between emergency room (ER) admissions for cardiorespiratory diseases (CRDs) and environmental factors. The aim of this study is the development and verification of an interpretable machine learning framework applied to environmental and health data to assess the relationship between environmental factors and daily emergency room admissions for cardiorespiratory diseases. The model’s predictive accuracy was evaluated by comparing simulated values with observed historical data, thereby identifying the most influential environmental variables and critical exposure thresholds. This approach supports public health surveillance and healthcare resource management optimization. The health and environmental data, collected through meteorological sensors and air quality monitoring stations, cover eleven years (2013–2023), including meteorological conditions and atmospheric pollutants. Four ML models were compared, with XGBoost showing the best predictive performance (R² = 0.901; MAE = 0.047). A 10-fold cross-validation was applied to improve reliability. Global model interpretability was assessed using SHAP, which highlighted that high levels of carbon monoxide and relative humidity, low atmospheric pressure, and mild temperatures are associated with an increase in CRD cases. The local analysis was further refined using LIME, whose application—followed by experimental verification—allowed for the identification of the critical thresholds beyond which a significant increase in the risk of hospital admission (above the 95th percentile) was observed: CO > 0.84 mg/m³, P_atm ≤ 1006.81 hPa, Tavg ≤ 17.19 °C, and RH > 70.33%. The findings emphasize the potential of interpretable ML models as tools for both epidemiological analysis and prevention support, offering a valuable framework for integrating environmental surveillance with healthcare planning. Full article

Accurate State of Charge (SOC) estimation for retired power batteries remains a critical challenge due to their degraded electrochemical properties and heterogeneous aging mechanisms. Traditional methods relying solely on electrical parameters (e.g., voltage and current) exhibit significant errors, as aged batteries experience altered internal resistance, capacity fade, and uneven heat generation, which distort the relationship between electrical signals and actual SOC. To address these limitations, this study proposes a surface temperature-assisted SOC estimation method, leveraging the distinct thermal characteristics of retired batteries. By employing infrared thermal imaging, key temperature feature regions—the positive/negative tabs and central area—are identified, which exhibit strong correlations with SOC dynamics under varying operational conditions. A Gated Recurrent Unit (GRU) neural network is developed to integrate multi-region temperature data with electrical parameters, capturing spatial–temporal thermal–electrical interactions unique to retired batteries. The model is trained and validated using experimental data collected under constant current discharge conditions, demonstrating superior accuracy compared to conventional methods. Specifically, our method achieves 64.3–68.1% lower RMSE than traditional electrical-parameter-only approaches (V-I inputs) across 0.5 C–2 C discharge rates. Results show that the proposed method reduces SOC estimation errors compared to traditional voltage-based models, achieving RMSE values below 1.04 across all tested rates. This improvement stems from the model’s ability to decode localized heating patterns and their hysteresis effects, which are particularly pronounced in aged batteries. The method’s robustness under high-rate operations highlights its potential for enhancing the reliability of retired battery management systems in secondary applications such as energy storage. Full article

The ship waterjet propulsion system is a crucial power unit for high-performance vessels, and the operational state of its core component, the waterjet pump, is directly related to navigation safety and mission reliability. To enhance the intelligence and accuracy of pump fault diagnosis, this paper proposes a novel diagnostic framework that integrates a supervised autoencoder (SAE) with a large language model (LLM). This framework first employs an SAE to perform task-oriented feature learning on raw vibration signals collected from the pump’s guide vane casing. By jointly optimizing reconstruction and classification losses, the SAE extracts deep features that both represent the original signal information and exhibit high discriminability for different fault classes. Subsequently, the extracted feature vectors are converted into text sequences and fed into an LLM. Leveraging the powerful sequential information processing and generalization capabilities of LLM, end-to-end fault classification is achieved through parameter-efficient fine-tuning. This approach aims to avoid the traditional dependence on manually extracted time-domain and frequency-domain features, instead guiding the feature extraction process via supervised learning to make it more task-specific. To validate the effectiveness of the proposed method, we compare it with a baseline approach that uses manually extracted features. In two experimental scenarios, direct diagnosis with full data and transfer diagnosis under limited-data, cross-condition settings, the proposed method significantly outperforms the baseline in diagnostic accuracy. It demonstrates excellent performance in automated feature extraction, diagnostic precision, and small-sample data adaptability, offering new insights for the application of large-model techniques in critical equipment health management. Full article

A cross-sectional study was conducted in Bangladesh from January 2023 to December 2024 to assess the prevalence of BVDV antibodies and associated risk factors in dairy herds. Initially, 138 bulk milk samples were collected from herds across 14 districts and screened using a commercial ELISA for BVDV antibodies. Subsequently, 767 individual milk samples were tested from cows in herds that screened positive. The overall herd-level seroprevalence was 72.5% (95% CI: 64.1–79.6), while the cow-level seroprevalence was 93.3% (95% CI: 91.3–94.9%). Within-herd seroprevalence varied from 81.8% to 100%. Herds with more than 70 cows had 31.95 times higher odds of BVDV seropositivity than those with 13–23 cows. BVD seroprevalence was significantly higher in the third, fifth, and eighth semen sources compared to the reference source. Cows older than 8 years had 4.53 times higher odds of seropositivity than those aged up to 4 years. Cows in thin physical condition had 13.02 times higher odds of seropositivity than those in normal condition. Conversely, cows producing over 8.8 kg of milk daily had a significantly lower seroprevalence of BVDV compared to those producing less than 8.8 kg, with an odds ratio of 0.41 (95% CI: 0.17–0.98). These findings suggest that BVDV exposure is widespread in dairy herds in Bangladesh. Regular serological screening, the use of semen from BVD-free bulls, and prioritizing surveillance for thin cows and low milk producers are essential. Improving nutrition, herd management, and targeted monitoring may help reduce BVDV transmission and improve herd productivity. Full article

Heat stress is a critical constraint to poultry production in tropical regions, where the temperature–humidity index (THI) frequently exceeds thermoneutral thresholds. Despite growing interest in climate-resilient livestock, limited research has explored the genetic sensitivity of local chicken breeds to increasing THI levels. This study aimed to evaluate the genetic effects of increasing THI on growth performance traits in two tropical chicken breeds. The data included body weight (BW), average daily gain (ADG), and absolute growth rate (AGR) from 4,745 black-boned and 3,001 Thai native synthetic chickens across five generations. Growth data were collected from hatching to 12 weeks of age, whereas temperature and humidity were continuously recorded to calculate daily THI values. A reaction norm model was used to estimate genetic parameters and rate of decline of BW, ADG, and AGR traits under varying THI thresholds (THI70 to THI80). Results indicated that the onset of heat stress occurred at THI72 for black-boned chickens and at THI76 for Thai native synthetic chickens. Heritability estimates for BW, ADG, and AGR decreased as the THI increased in both chicken breeds. However, the Thai native synthetic chickens consistently exhibited higher genetic potential across all THI levels (average heritability: BW = 0.28, ADG = 0.25, AGR = 0.36) compared to the black-boned chickens (average heritability: BW = 0.21, ADG = 0.15, AGR = 0.23). Under mild heat stress (THI72), black-boned chickens showed sharp declines in all traits (average reduction in BW = −10.9 g, ADG = −0.87 g/day, AGR = −3.20 g/week), whereas Thai native synthetic chickens maintained stable performance. At THI76, both breeds experienced significant reductions, particularly in males. Estimated breeding values (EBVs) for AGR decreased linearly with THI, though Thai native synthetic chickens showed greater individual variability, with some birds maintaining stable or positive EBVs up to THI80—suggesting the presence of heat-resilient genotypes. In conclusion, Thai native synthetic chickens demonstrated superior thermotolerance and genetic robustness under increasing THI conditions. The identification of breed-specific THI thresholds and resilient individuals provides novel insights for climate-smart poultry breeding. These findings offer valuable tools for genetic selection, environmental management, and long-term adaptation strategies in response to global climate change. Full article

Background: Chronic wounds are a growing clinical challenge due to their prolonged healing time and associated healthcare burden. Combined therapeutic approaches, including topical oxygen therapy (TOT) and negative-pressure wound therapy (NPWT), have shown promise in enhancing wound healing. This pilot exploratory study aimed to assess the clinical effectiveness of combined TOT and NPWT in chronic wound treatment and to explore the prognostic value of selected laboratory and thermographic markers. Methods: Eighteen patients with chronic wounds due to type 2 diabetes mellitus or chronic venous insufficiency were treated with either TOT alone (control group) or TOT combined with NPWT (intervention group). Wound characteristics, thermographic data, and laboratory parameters (NLR, MLR, PLR, CRP, and total protein) were collected at baseline and during therapy. The primary endpoints were the total treatment duration and complete wound closure. Statistical analyses were exploratory and used non-parametric tests, correlation analyses, and simple linear regression. Results: Ulcer duration was significantly associated with the wound surface area. Lower serum total protein levels correlated negatively with ulcer duration, wound size, and granulation tissue area. A significant reduction in treatment duration was observed in the intervention group compared to the controls. One strong correlation was found between MLR and peripheral wound temperature on day 7 in the control group. No significant group differences were observed in wound size or thermographic measures after one week of treatment. Conclusions: Combining TOT and NPWT may reduce treatment duration in chronic wound management. Selected laboratory and thermographic markers show promise as prognostic tools. These exploratory findings require confirmation in larger, randomized trials. Full article

This study presents a comprehensive analysis of the chemical composition of bottom ash samples generated during municipal waste incineration. A total of 52 samples were collected and subjected to statistical analysis for 17 elements and 2 element sums using techniques such as correlation analysis and one-way ANOVA. The results confirm a high degree of heterogeneity in the elemental content, reflecting the variability of waste streams and combustion processes. Strong correlations were identified between certain elements, including Cu-Zn, Co-Ni, and HREE-LREE, indicating common sources and similar geochemical properties. The analysis also revealed significant seasonal variability in the content of Ba and Sr, with lower average values observed during the spring season and greater variability noted during summer and winter. Although Al and HREE did not reach classical significance levels, their distributions suggest possible seasonal differentiation. These findings underscore the need for long-term monitoring and seasonal analysis of incineration bottom ash composition to optimize resource recovery processes and assess environmental risk. The integration of chemical data with operational data on waste composition and combustion parameters may contribute to a better understanding of the variability of individual elements, ultimately supporting the development of effective strategies for ash management and element recovery. Full article

Background: Skin and soft tissue infections (SSTIs) are a major cause of emergency room (ER) visits and hospitalizations. Long-acting lipoglycopeptides (LALs), such as dalbavancin and oritavancin, offer potential for early discharge and outpatient management, especially in patients at risk for methicillin-resistant Staphylococcus aureus (MRSA) or with comorbidities. Methods: We conducted a retrospective observational cohort study from March to December 2024 in an Italian tertiary-care hospital. Adult patients treated in the ER with a single dose of dalbavancin (1500 mg) or oritavancin (1200 mg) for SSTIs were included. Demographic, clinical, and laboratory data were collected. Follow-up evaluations were performed at 14 and 30 days post-treatment to assess outcomes. Results: Nineteen patients were enrolled (median age 59 years; 53% female). Most had lower limb involvement and elevated inflammatory markers. Three patients (16%) were septic. Fourteen patients (74%) were discharged without hospital admission; hospitalization in the remaining cases was due to comorbidities rather than SSTI severity. No adverse drug reactions were observed. At 14 days, 84% of patients had clinical resolution; only 10% had recurrence by day 30, with no mortality nor readmission reported. Conclusions: LALs appear effective and well-tolerated in the ER setting, supporting early discharge and reducing healthcare burden. Broader use may require structured care pathways and multidisciplinary coordination. Full article

Background/Objective: Nursing and non-nursing students experience high stress levels, making them susceptible to mental health issues. This study compared stress, anxiety, and depression between these two groups after 2 years of the COVID-19 pandemic. Additionally, it explored the relationship between perceived helplessness, self-efficacy, and symptoms of mental stress and strain resulting from challenging internship conditions for nursing students. Methods: This cross-sectional study included 154 nursing students (mean age = 22.43 years) and 291 non-nursing students (mean age = 27.7 years). Data were collected using the Depression Anxiety Stress Scales (DASS-21), Perceived Stress Scale-10 (PSS-10), and a questionnaire on mental stress and strain. Results: Nursing students reported significantly higher scores in the DASS-21 subscales depression (ηp² = 0.016) and anxiety (ηp² = 0.037), and global stress (PSS-10; ηp² = 0.029) compared to non-nursing students, but no significant difference on the DASS-21 Stress subscale. The observed group differences in the present study may be partially attributed to group differences in demographic factors. Helplessness correlated strongly with nearly all scales of mental stress and strain during internships (all p’s < 0.001), while self-efficacy showed a strong negative correlation with non-occupational difficulties, health impairment, and emotional problems (all p’s < 0.001). Conclusions: Nursing students experience elevated depression, anxiety, and perceived stress levels compared to non-nursing students. Stronger feelings of helplessness and lower confidence in their ability to overcome challenges were strongly correlated with mental stress and strain during clinical training. Targeted interventions such as cognitive behavioral training and stress management should be integrated into nursing curricula to enhance resilience and coping strategies. Full article

Public transport companies are aware that the success of their operations largely depends on the proper sizing and optimization of their processes. Among the key activities are the maintenance and repair of the vehicle fleet. This paper presents the application of mathematical optimization methods from the field of operations research to improve the efficiency of service workshops for bus maintenance and repair. Based on an analysis of collected data using queueing theory, the authors assessed the current system performance and found that the queueing system still has spare capacity and could be downsized, which aligns with the company’s management goals. Specifically, the company plans to reduce the number of bus repair service stations (servers in a queueing system). The main question is whether the system will continue to function effectively after this reduction. Three specific downsizing solutions were proposed and evaluated using queueing theory methods: extending the daily operating hours of the workshops, reducing the number of arriving buses, and increasing the productivity of a service station (server). The results show that, under high system load, only those solutions that increase the productivity of individual service stations (servers) in the queueing system provide optimal outcomes. Other solutions merely result in longer queues and associated losses due to buses waiting for service, preventing them from performing their intended function and causing financial loss to the company. Full article

Objectives: Diabetes Mellitus involves demanding challenges that interfere with family functioning and routines. In turn, family and social context impacts individual glycemic control. This study aims to identify this recursive interplay, the mutual influences of family systems and diabetes management. Design: Data was collected through a cross-sectional design comparing patients, aged 22–55, with and without metabolic control. Methods: Participants filled out a set of self-report measures of sociodemographic, clinical and family systems assessment. Patients (91) were also invited to describe their perception about disease management interference regarding family functioning. We first examined the extent to which family variables grouped dataset to determine if there were similarities and dissimilarities that fit with our initial diabetic groups’ classification. Results: Cluster analysis results identify a two-cluster solution validating initial classification of two groups of patients: 49 with metabolic control (MC) and 42 without metabolic control (NoMC). Independent sample tests suggested statistically significant differences between groups in family subscales- family difficulties and family communication (p < 0.05). Binary logistic regression shed light on predictors of explained variance to no metabolic control, in four models: Sociodemographic, Clinical data, SCORE-15/Congruence Scale and Eating Behavior. Furthermore, groups differ on family support, level and sources of family conflict caused by diabetes management issues. Considering only patients who co-habit with a partner for more than one year (N = 44), NoMC patients score lower on marital functioning in all categories (p < 0.05). Discussion: Family-Chronic illness interaction plays a significant role in a patient’s adherence to treatment. This study highlights the Standards of Medical Care for Diabetes, considering caregivers and family members on diabetes care. Full article

The Lidia cattle breed is featured in several traditional popular bullfighting festivals throughout Spain, including the “Toro de Cuerda” event, in which the animals are subjected to intense physical exercise. However, the physiological impact and welfare implications of these activities remain poorly characterized. This study aimed to evaluate the stress response and muscle damage in Lidia breed bulls during roping bull celebrations through comprehensive blood analysis. Blood samples were collected from 53 adult male Lidia bulls before and after a standardized 45 min continuous running exercise during traditional roping bull events in four Spanish autonomous regions. Hematological parameters, muscle enzymes (creatine kinase, lactate dehydrogenase, lactate), and stress hormones (cortisol and ACTH) were analyzed. Significant increases (p < 0.05) were observed in leukocytes, lymphocytes, monocytes, eosinophils, neutrophils, erythrocytes, hematocrit, hemoglobin, and post-exercise platelets. Muscle enzymes showed marked elevations, with creatine kinase increasing up to 10-fold above baseline values. Stress hormones, cortisol and ACTH, also demonstrated significant increases. Despite the magnitude of these changes, all parameters remained within established reference ranges for the bovine species. This study provides the first physiological assessment of Lidia cattle during popular bullfighting celebrations, establishing baseline data for evidence-based welfare evaluation and management protocols. Full article

Integrating BIM curriculum into traditional construction management (CM) programs is essential to meet the increasing industry demand for BIM-ready graduates. However, academia struggles with BIM curriculum integration due to unfamiliar emerging BIM technologies, and the increased workload associated with curriculum transformation. Disciplines including nursing, health science, and medical overcame the same challenges using the ability-desire-knowledge-ability-reinforcement (ADKAR) change management model, while CM programs have not explored this model for BIM curriculum development. Thus, this research introduces the ADKAR change management lens to BIM curriculum development by proposing a practically modified and replicable ADKAR model for CM programs. Focus group interviews with 14 academics from the UK, USA, Korea, and Australia, revealed establishing a sense of urgency by appointing a BIM champion is the most critical step before the BIM curriculum development. Instant advice demystifying uncertain BIM concepts is recognised the most effective motivation among academia. Well-balanced BIM concept integrations is ‘sine qua non’ since excessively saturating BIM aspects across the program can dilute students’ essential domain knowledge. Students’ evaluation over the BIM curriculum were collected through a six-year longitudinal focus group interviews, revealing that progressive BIM learnings scaffolded from foundational concepts to advanced applications throughout their coursework is the most valuable. Full article