Search Results (25,204)

Background/Objectives: Low back pain (LBP) is one of the most prevalent musculoskeletal disorders globally, significantly impacting quality of life across diverse populations. Despite its association with middle-aged and older populations, evidence indicates that LBP is increasingly prevalent among younger age groups. Health science students are considered a potential risk factor for LBP; however, longitudinal studies are scarce. This study aims to determine the risk factors for LBP among health science students over a 2-year follow-up. Methods: One hundred ninety-seven of the third-class health science students (Nursing, Physiotherapy, Medical laboratory science, and Emergency Medical services) were contacted in June 2024. A self-administered modified version of the Standardized Nordic Questionnaire, and data about sedentary and physical activity behavior, as well as 1-month LBP (lasting at least 12 h and numeric rating scale > 5) and stress scores, were recorded. Results: A total of 172/197 (87.3%) respondents completed the questionnaire at the end of the 2-year follow-up. The mean age was 25 ± 3.5 (years) and body mass index (BMI) value 23.5 ± 4.3 (kg/m²). About 49% (n = 84) and 20% (n = 34) of the participants had 1-month LBP and functional disability, respectively. No significant association was found between health science programs and the presence of 1-month LBP (χ² = 0.55, p > 0.05). The logistic regression analyses found that males (OR = 0.269, p = 0.005) and a history of pain frequency (OR = 3.377, p = 0.001) had a significant association with LBP over time. Conclusions: This prospective study shows a high prevalence of 1-month LBP (48.8%) among health science students at Zefat Academic College. LBP was significantly related to sex (female) and pain frequency, but not to health science students. We believe that implementing ergonomic and educational strategies is recommended for this population. Full article

To assess the market competitiveness of high-speed rail (HSR) express and forecast its freight volume, this paper develops an integrated framework combining strategic analysis, market forecasting, and competition assessment. A hybrid SWOT-AHP model identifies and quantifies key strategic factors, clarifying HSR express positioning. Considering macroeconomic and consumption factors, a GM(1,N) model forecasts intercity express volume. Based on a generalized cost function covering timeliness, economy, safety, and stability, an improved Logit model calculates HSR’s mode share against road and air express, deriving future HSR freight volume. Using China as a case study, results show: (1) A proactive strategy leveraging intrinsic strengths is recommended, supported by rapid intercity express growth; (2) HSR can capture over 20% mode share initially, showing strong competitiveness in medium-long distance transport; (3) Transport cost is the most sensitive factor, a 20% reduction raises mode share by 10%, while rising timeliness demands enhance long distance advantages. This study offers a quantitative basis for HSR express strategic planning. Full article

Background/Objectives: To promote sustainable and healthy diets, increased consumption of pulses (the edible grains of legumes) is recommended. Adolescence is a period in which perceptions and behaviours develop that can impact lifelong dietary behaviours. Therefore, this study aimed to understand how Australian adolescents perceive healthy, sustainable diets and perceive and consume pulses. Methods: Students (11–17 years old, median = 15 years, n = 33) in Brisbane, Australia, participated in school-based face-to-face focus groups and an online survey. Results: Students’ perceptions of healthy and sustainable dietary behaviours largely focused on the health aspects of food and consideration of food waste. The main factors that adolescents identified as influencing the health and sustainability of their diet were a lack of perceived responsibility for the impact of their meal choices and lack of knowledge of what constitutes a healthy and sustainable diet. Most students were unfamiliar with the term ‘pulses’ and lacked a desire to consume pulses more often. Consumption of pulses was below recommendations in national and international dietary guidelines. The main factors that adolescents identified as influencing pulse consumption related to students’ lack of capability to prepare pulses and the limited opportunities to access pulse-based foods. Conclusions: Perceptions of sustainable diets and pulses were very limited, and a lack of knowledge, skills, and limited availability were identified as barriers to their consumption. Education and cooking classes, in conjunction with increased availability of tasty pulse foods, are recommended to increase students’ pulse consumption as part of a healthy and sustainable diet. Full article

Background/Objectives: Osteoporosis is a major global health concern, and early risk assessment plays a crucial role in fracture prevention. Although demographic, clinical, and lifestyle factors are commonly incorporated into screening tools, their relative importance within data-driven prediction frameworks can vary substantially across datasets. Rather than aiming to identify novel predictors, this study evaluates the stability and behavior of established osteoporosis risk factors using statistical inference and machine learning-based feature selection methods across heterogeneous data sources. We further examine whether simplified and near-minimal models can achieve predictive performances comparable to that of full-feature configurations. Methods: An open-access Kaggle dataset (n = 1958) and a retrospective clinical dataset from the University of Phayao Hospital (n = 176) were analyzed. Feature relevance was assessed using logistic regression, likelihood ratio testing, MRMR, ReliefF, and unified importance scoring. Multiple predictor configurations, ranging from full-feature to minimal and near-minimal models, were evaluated using decision tree, support vector machine, k-nearest neighbor, naïve Bayes, and efficient linear classifiers. External validation was performed using hospital-based records. Results: Across all analyses, age consistently emerged as the dominant predictor, followed by corticosteroid use, while other variables showed limited incremental predictive contributions. Simplified models based on age alone or age combined with medication-related variables achieved performances comparable to full-feature models (accuracy ≈91% and AUC ≈ 0.95). In addition, near-minimal models incorporating gender alongside age and medications demonstrated a favorable balance between discrimination and computational efficiency under external validation. Although overall performance declined under distributional shift, naïve Bayes and efficient linear classifiers showed the most stable external behavior (AUC = 0.728–0.787). Conclusions: These findings indicate that stability-driven feature selection primarily reproduces well-established epidemiological risk patterns rather than identifying novel predictors. Minimal and near-minimal models—including those incorporating gender—retain acceptable performances under external validation and are methodologically efficient. Given the limited size and single-center nature of the external cohort, the results should be interpreted as preliminary methodological evidence rather than definitive support for clinical screening deployment. Further multi-center studies are required to assess generalizability and clinical relevance. Full article

Background and Objectives: Whole Blood Viscosity (WBV), estimated using the De Simone formula, is a key hemodynamic parameter linked to endothelial dysfunction and atherosclerosis. Its association with significant coronary calcification, defined as a high Coronary Artery Calcium Score (CACS ≥ 100), remains unclear. This study investigated whether calculated WBV predicts high CACS. Materials and Methods: In this single-center, retrospective, cross-sectional study, 403 patients undergoing coronary computed tomography angiography for suspected stable coronary artery disease were included. Participants were stratified into CACS < 100 (n = 258) and CACS ≥ 100 (n = 145). WBV was calculated at High Shear Rate (HSR) and Low Shear Rate (LSR) using the De Simone formula. Multivariate binomial logistic regression adjusted for conventional cardiovascular risk factors was used to identify independent predictors of high CACS. Results: Patients with CACS ≥ 100 were older, more frequently male, and had a higher prevalence of diabetes and hypertension (all p < 0.01). Mean WBV did not differ significantly between groups: WBV-HSR, 4.3 ± 0.5 cP vs. 4.4 ± 0.5 cP (p = 0.456); WBV-LSR, 29.9 ± 8.0 cP vs. 30.4 ± 8.6 cP (p = 0.505). In multivariate models, neither WBV-HSR (OR: 0.489; p = 0.462) nor WBV-LSR (OR: 0.987; p = 0.520) independently predicted high CACS. Age and sex were the strongest independent predictors (p < 0.001). Conclusions: No independent association was found between calculated WBV and high CACS in this cross-sectional study. Full article

A comprehensive analysis was conducted to explore whether feeding inclusion procyanidin-rich grape seed powders (GSPs) affected the faba bean-induced muscle crispness in the aquaculture of crisped grass carp. The procyanidin content in the prepared GSP was 10.40 g/100 g. Additionally, one thousand 1-year-old grass carp with an initial weight of 27 g and an initial length of 12 cm were divided into five groups, including the blank control (basal diet); the positive control (faba bean diet); and the low (faba bean diet supplemented 100 mg/kg GSP), middle (faba bean diet supplemented 500 mg/kg GSP), and high (faba bean diet supplemented 1000 mg/kg GSP) GSP-supplemented groups. After feeding for 60 days, the weight gain rate, specific growth rate, and condition factor were elevated in the high-GSP-supplemented group in comparison with the blank control (p < 0.05), accompanied by a significant decrease in the feeding coefficient (p < 0.05). Meanwhile, a significant increase in muscle ROS content, shear force, gumminess, and chewiness was determined in the high-GSP-supplemented group when compared with the positive group, suggesting that a relatively high daily supplement of GSP facilitated muscle crispness. Moreover, the composition of intestine microbiota was significantly varied between groups with the daily addition of GSP (p < 0.05). Among them, Lactococcus chungangensis was identified as the key biomarker of the high-GSP-supplemented group, which was closely related to the increased muscle ROS content, the modifications in muscle nutritional metabolites (Met, C20:2n6, C20:3n6, C20:4n6, and C22:4n6), and the alterations in muscle texture (gumminess, chewiness, shear force, hardness, and adhesiveness). Based on these results, we believe that a relatively high daily supplement of GSP (1000 mg/kg) facilitated muscle crispness in the aquaculture of crisped grass carp. Full article

Background/Objectives: Healthcare-associated infections (HAIs), particularly those caused by multidrug-resistant (MDR) bacteria, remain a major challenge for Romanian hospitals. This study aimed to evaluate the epidemiological burden of MDR-related HAIs and to characterize the distribution of MDR bacterial isolates and their antimicrobial resistance patterns over four consecutive semesters in a Romanian tertiary care hospital. Methods: A retrospective study was conducted using data from the Electronic Registry of HAIs, clinical observation sheets, and microbiology laboratory records. An epidemiological analysis was performed on patients diagnosed with MDR-related HAIs, while a separate microbiological analysis included all MDR bacterial isolates identified during the study period. Descriptive and comparative statistical analyses were applied to assess temporal trends, pathogen distribution, and resistance profiles. Results: Of the 327 HAIs identified, 56 cases (17.13%) were caused by MDR bacteria. Most MDR-HAIs originated from the Intensive Care Unit (≈60%), with Acinetobacter baumannii and Klebsiella spp. as the predominant pathogens. Overall mortality among patients with MDR-HAIs was high (51.79%), particularly in infections caused by A. baumannii and K. pneumoniae. Microbiological analysis of MDR isolates (n = 406) revealed consistently high resistance rates to ciprofloxacin, cefepime, and ceftazidime, exceeding 95% in 2023–2024, while resistance to carbapenems surpassed 90% by the end of the study period. Temporal variability in MDR burden was observed across semesters, suggesting an influence of clinical and institutional factors. Conclusions: MDR-related HAIs represent a significant and persistent problem in Romanian acute-care hospitals, particularly in Intensive Care Units. The dominance of carbapenem-resistant A. baumannii and extended-spectrum beta-lactamase-producing and carbapenem-resistant Klebsiella spp. highlights the urgent need for strengthened antimicrobial stewardship, enhanced microbiological surveillance, and reinforced infection prevention strategies. Full article

Gut microbes play a crucial role in regulating physiological processes such as host energy metabolism, nutrient absorption, and environmental adaptation. The predicted functions of gut microbes can be influenced by many factors, both extrinsic and intrinsic to the hosts. The plateau pika is a key species in the alpine ecosystem of the Qinghai–Tibet Plateau. Previous research on the plateau pika primarily examined how extrinsic factors affected its gut microbiota. However, studies on intrinsic factors are scarce. Here, we used live-trapping to capture plateau pikas and collect cecum contents. Using metagenomic sequencing of cecum content samples, we characterized and compared the gut microbial composition and predicted function of plateau pika in adult (n = 9) and juvenile (n = 9) populations. The results indicated that Bacillota and Bacteroidete were the major bacterial phyla. The core gut microbial genera were the same, but the relative abundance of Oscillospira in juveniles was significantly lower than that in adults. The changes in the proportion of cellulose-degradation-related bacterial communities in juveniles suggest that they tend to choose low-fiber diets. In this study, we found no significant differences in the gut microbial composition and diversity, KEGG level 1 metabolic pathways, or CAZy class level between adult and juvenile plateau pikas. In total, the composition and predicted functions of cecal microorganisms in juvenile and adult male plateau pikas were not different. Regarding KEGG level 2 metabolic pathways, the juvenile group had a higher relative abundance of metabolic pathways for cofactors and vitamins, terpenoids, and polyketides, whereas the adult group had a higher relative abundance of energy metabolism. However, the resulting differences remain unclear. Therefore, future research should validate the above findings on a broader spatio-temporal scale and conduct cross-species comparisons to construct a microbial ecological framework for the health management of plateau wild animals. Full article

Municipal wastewater contains high amounts of nitrogen (N) and phosphorus (P), as well as other compounds that are harmful to the environment; however, it can also be used as an algae growth medium. In this study locally (Lithuania) isolated algae Scenedesmus quadricauda were cultivated in local (Vilnius city) municipal wastewater. Data show that Scenedesmus algae can be grown in municipal wastewater as successfully as in Bold’s basal medium for 14 days. Algae cultivation significantly reduced the concentration of organic nitrogen forms and phosphate levels. The nitrogen concentration in wastewater after cultivation was reduced to 8 mg N L⁻¹ (up to 89% reduction in total nitrogen concentration). Phosphorus concentration was reduced to 5.4 mg P L⁻¹ (up to 86%). The analysis indicates that the optimal temperature for S. quadricauda cultivation is 25 °C; temperatures higher or lower than this result in a reduction in algal biomass. A higher amount of light leads to higher yields. No statistically significant differences were found comparing cultivation in BB medium and wastewater under different conditions. The analysis showed that the main factors influencing algae biochemical composition were final total nitrogen concentration and available total nitrogen amount per unit of algae biomass produced, as well as molar N:P ratios. Algae biomass cultivated in wastewater contained a consistent lipid concentration (on average 14.94 ± 2.38%), a lower final total nitrogen concentration, and overall lower total nitrogen availability, leading to higher carbohydrate concentrations (up to 51.10%) and a lower protein content (down to 15.52%). Algae biomass that was cultivated in the BB medium biochemical composition was not dependent on environmental factors and remained consistent (on average 22.89 ± 3.85% carbohydrate, 39.32 ± 3.89% protein, and 13.99 ± 2.21% lipid). Full article

Background/Objectives: The aim of the present systematic review is to evaluate the performance of AI models for length of stay prediction. Methods: This SR was carried out in accordance with PRISMA 2020 and registered in PROSPERO database (CRD420251039985). Using the PICOS framework, we formulated the following research question: “Can artificial intelligence models accurately predict hospital length of stay (LOS) in patients undergoing head and neck (H&N) cancer surgery?” We searched the Cochrane Library, Embase, PubMed, and Scopus, with additional gray literature identified through Google Scholar and ProQuest. Risk of bias (RoB) was assessed using the Prediction Model Risk of Bias Assessment Tool (PROBAST), and a narrative synthesis was performed to summarize qualitative findings. Results: Of 1304 identified articles, 5 met inclusion criteria, covering 5009 patients. All studies used supervised learning to predict LOS with different variables presenting stronger associations with increased hospital LOS. Age, race, ASA score, BMI, and comorbid factors like smoking and arterial hypertension were comon variables across studies but not always the ones most strongly associated with LOS. One study also predicted discharge to non-home facilities and prolonged LOS; only one applied data balancing. Model accuracies ranged from 0.63 to 0.84, and area under the receiver operator characteristics curve (AUROC) values from 0.66 to 0.80, suggesting moderate discriminative performance. All studies had a high risk of bias, though no applicability concerns were noted. Conclusions: AI models show potential for LOS prediction after H&N cancer surgery; however, an elevated RoB and methodological shortcomings constrain the current evidence. Methodological improvements, external validation, and transparent reporting is essential to enhance reliability and generalizability, enabling integration into clinical decision-making. Full article

Understanding how primary structural features and secondary material properties adapt to functional loads is essential to determining their effect on changes in joint biomechanics over time. The objective of this study was to map and correlate spatiotemporal changes in primary structural features, secondary material properties, and dentoalveolar joint (DAJ) stiffness with age in rats subjected to prolonged chewing of soft foods versus hard foods. To probe how loading history shapes the balance between the primary and secondary features, four-week-old rats were fed either a hard-food (HF, N = 25) or soft-food (SF, N = 25) diet for 4, 12, 16, and 20 weeks, and functional imaging of intact mandibular DAJs was performed at 8, 12, 16, 20, and 24 weeks. Across this time course, the primary structural determinants of joint function (periodontal ligament (PDL) space, contact area, and alveolar bone socket morphology) and secondary material and microstructural determinants (tissue-level stiffness encoded by bone and cementum volume fractions, pore architecture, and bone microarchitecture) were quantified. As the joints matured, bone and cementum volume fractions increased in both the HF and SF groups but along significantly different trajectories, and these changes correlated with a pronounced decrease in PDL-space from 12 to 16 weeks in both diets. With further aging, older HF rats maintained significantly wider PDL-spaces than SF rats. These evolving physical features were accompanied by an age-dependent significant increase in the contact ratio in the SF group. The DAJ stiffness was significantly greater in SF than HF animals at younger ages, indicating that food hardness-dependent remodeling alters the relative contribution of structural versus material factors to joint function across the life course. At the tissue level, volumetric strains, representing overall volume changes, and von Mises bone strains, representing shape changes, increased with age in HF and SF joints, with volumetric strain rising rapidly from 16 to 20 weeks and von Mises strain increasing sharply from 12 to 16 weeks. Bone in SF animals exhibited higher and more variable strain values than age-matched HF bone, and changes in joint space, degrees of freedom, contact area, and bone strain correlated with joint biomechanics, demonstrating that multiscale functional biomechanics, including bone strain in intact DAJs, are colocalized with anatomy-specific physical effectors. Together, these spatiotemporal shifts in primary (structure/form), and secondary features (material properties and microarchitecture) define divergent mechanobiological pathways for the DAJ and suggest that altered loading histories can bias joints toward early maladaptation and potential degeneration. Full article

Seismic action significantly affects the mechanical properties and failure characteristics of bridge pile foundations, soft rocks, and sediments. This study, by integrating shaking table tests, numerical simulations, and on-site monitoring, systematically analyzed the influence mechanisms of seismic intensity, sediment characteristics, and pile foundation layout on structural responses. Tests show that the 2.5-layer rock–sand pile exhibits nonlinear bearing degradation under seismic force: when the seismic acceleration increases from 0 to 100 m/s², the bearing capacity of the pile foundation decreases by 55.3%, and the settlement increases from 3.2 mm to 18.5 mm. When the acceleration is ≥2 m/s², the cohesion of the sand layer is destroyed, causing a semi-liquefied state. When it is ≥10 m/s², the resistance loss reaches 80%. The increase in pore water pressure leads to dynamic settlement. When the seismic acceleration is greater than 50 m/s², the shear modulus of the sand layer drops below 15% of its original value. The thickness of the sediment has a nearly linear relationship with the reduction rate of the bearing capacity. When the thickness increases from 0 to 1.4 cm, the reduction rate rises from 0% to 55.3%. When the thickness exceeds 0.8 cm, it enters the “danger zone”, and the bearing capacity decreases nonlinearly with the increase in thickness. The particle size is positively correlated with the reduction rate. The liquefaction risk of fine particles (<0.1 mm) is significantly higher than that of coarse particles (>0.2 mm). The load analysis of the pile cap shows that when the sediment depth is 140 cm, the final bearing capacity is 156,187.2 kN (reduction coefficient 0.898), and the maximum settlement is concentrated at the top point of the pile cap. Under the longitudinal seismic load of the pile group, the settlement growth rate of the piles containing sediment reached 67.16%, triggering the dual effect of “sediment–earthquake”. The lateral load leads to a combined effect of “torsional inclination”, and the stress at the top of the non-sediment pile reaches 6.41MPa. The seismic intensity (PGA) is positively correlated with the safety factor (FS) (FS increases from 1.209 to 37.654 when 10 m/s²→100 m/s²), while sediment thickness (h) is negatively correlated with FS (FS decreases from 2.510 to 1.209 when 0.05 m→0.20 m). The research results reveal the coupled control mechanism of sediment characteristics, seismic parameters, and pile foundation layout on seismic performance, providing key parameters and an optimization basis for bridge design in high-intensity areas. Full article

Background: Several studies have investigated the importance of physical exercise (PE) in overweight and obese populations; however, to date, no bibliometric study has analyzed research trends in high-intensity interval training (HIIT) in overweight and obese populations across the entire life course. Objective: To analyze the scientific output of HIIT trends in overweight and obese populations. Method: Theoretical study using bibliometrics as a research technique. A total of 282 studies were identified in the Web of Science and PubMed databases for analysis with VOSViewer software 1.6.20. The equation used was (“High-intensity interval training” OR HIIT) AND (overweight OR obesity OR “risk factors” OR “obesity risk”). Results: The year 2022 was the most productive year (n = 46). Most of the documents are research articles (81%), followed by review articles (15%). Most studies do not specify the characteristics of the sample, only mentioning the application of a HIIT program in overweight or obese individuals in (65.6%) of the total articles found. There is low scientific output in research focused on women (23.4%). The most frequently occurring words were “exercise” (n = 145), “obesity” (n = 131), “high-intensity interval training” (n = 81), “overweight” (n = 78), “physical activity” (n = 73), “body composition” (n = 46), “weight loss” (n = 45), “health” (n = 42), and “cardiorespiratory fitness” (n = 40). Conclusions: Scientific research has advanced the understanding of the impact of HIIT in relation to excess weight, with total fat reduction being one of the most frequently reported variables and no differences observed between sexes. HIIT has shown benefits in populations with overweight and obesity when compared with low-intensity training programs. Full article

Cabbage stubble left in fields after harvest forms a mechanically complex stubble–soil composite that hinders subsequent tillage and crop establishment. Although the Discrete Element Method (DEM) is widely used to model soil-root systems, calibrated contact parameters for taproot-dominated vegetables like cabbage remain unreported. This study addresses this gap by calibrating a novel DEM framework that couples the JKR model and the Bonding V2 model to represent adhesion and mechanical interlocking at the stubble–soil interface. Soil intrinsic properties and contact parameters were determined through triaxial tests and angle-of-repose experiments. Physical pullout tests on ‘Zhonggan 21’ cabbage stubble yielded a mean peak force of 165.5 N, used as the calibration target. A three-stage strategy—factor screening, steepest ascent, and Box–Behnken design (BBD)—identified optimal interfacial parameters: shear stiffness per unit area = 4.40 × 10⁸ N·m⁻³, normal strength = 6.26 × 10⁴ Pa, and shear strength = 6.38 × 10⁴ Pa. Simulation predicted a peak pullout force of 162.0 N, showing only a 2.1% deviation from experiments and accurately replicating the force-time trend. This work establishes the first validated DEM framework for cabbage stubble–soil interaction, enabling reliable virtual prototyping of residue management implements and supporting low-resistance, energy-efficient tillage tool development for vegetable production. Full article

Traditional automated monitoring systems adopted for Intersection Traffic Control still face challenges, including high costs, maintenance difficulties, insufficient coverage, poor multimodal data integration, and limited traffic information analysis. To address these issues, the study proposes a sovereign AI-driven Smart Transportation governance approach, developing a mobile AI solution equipped with multimodal perception, task decomposition, memory, reasoning, and multi-agent collaboration capabilities. The proposed system integrates computer vision, multi-object tracking, natural language processing, Retrieval-Augmented Generation (RAG), and Large Language Models (LLMs) to construct a Pipeline-based Traffic Analysis System (PTAS). The PTAS can produce real-time statistics on pedestrian and vehicle flows at intersections, incorporating potential risk factors such as traffic accidents, construction activities, and weather conditions for multimodal data fusion analysis, thereby providing forward-looking traffic insights. Experimental results demonstrate that the enhanced DuCRG-YOLOv11n pre-trained model, equipped with our proposed new activation function $\beta silu$, can accurately identify various vehicle types in object detection, achieving a frame rate of 68.25 FPS and a precision of 91.4%. Combined with ByteTrack, it can track over 90% of vehicles in medium- to low-density traffic scenarios, obtaining a 0.719 in MOTA and a 0.08735 in MOTP. In traffic flow analysis, the RAG of Vertex AI, combined with Claude Sonnet 4 LLMs, provides a more comprehensive view, precisely interpreting the causes of peak-hour congestion and effectively compensating for missing data through contextual explanations. The proposed method can enhance the efficiency of urban traffic regulation and optimizes decision support in intelligent transportation systems. Full article