Search Results (2,513)

This study examines the historical and anticipated effects of climate change on essential hydroclimatic variables (temperature, precipitation, evapotranspiration, and soil moisture) in the Southeastern Anatolia Project (GAP) region of Türkiye, a semi-arid and agriculturally significant basin experiencing heightened water stress. The analysis employs a collection of CMIP6 Global Climate Models (GCM) and integrates three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5), utilizing statistical bias correction methods such as Delta Change, Quantile Mapping (QM), and Empirical Quantile Mapping (EQM) to improve the regional accuracy of the projections. The ACCESS-CM2 model, validated with data from Türkiye’s Meteorological General Directorate (MGM), was chosen for comprehensive spatial mapping, utilizing Inverse Distance Weighting (IDW) interpolation across seven temporal intervals encompassing past, present, and future periods. The findings indicate a steady increase in temperature and evapotranspiration, especially under high-emission scenarios, with temperature rises above +4 °C and considerable water losses anticipated by century’s end. Soil moisture exhibits a declining tendency, particularly in the southern and eastern regions, signifying increasing drought susceptibility. Precipitation patterns demonstrate significant spatial variability and rising uncertainty, with relative error (RE%) values increasing under SSP5-8.5. Historical data from 1963 to 2022 corroborate these conclusions, indicating a progressive shift towards a warmer and drier regional climate. These observations highlight the importance of climate adaptation strategies and water management in the GAP region. The research provides decision-makers a high-resolution, bias-corrected hydroclimatic dataset. Full article

Background/Objectives: Ventilator weaning imposes profound hemodynamic stress, unmasking cardiopulmonary vulnerability. Since conventional predictors of post-tracheostomy weaning failure remain elusive, biomarker-driven risk stratification offers a translational approach. We evaluated the prognostic utility of admission N-terminal pro-B-type natriuretic peptide (NT-proBNP) as an early triaging tool for weaning failure and explored its therapeutic implications alongside optimal tracheostomy timing. Methods: In this large-scale retrospective cohort study, we analyzed 707 critically ill patients who underwent tracheostomy in a medical intensive care unit. We investigated the association between baseline NT-proBNP levels—measured as a molecular surrogate of cardiovascular stress at ICU admission; echocardiographic parameters; and weaning outcomes. Multivariable logistic regression analysis was utilized to identify independent pathophysiological predictors associated with weaning failure. Results: Patients experiencing weaning failure exhibited significantly elevated admission NT-proBNP levels compared to those successfully weaned (3077.0 vs. 1410.0 pg/mL, p < 0.001). High admission NT-proBNP (>3271 pg/mL) was independently associated with an increased risk of weaning failure (adjusted odds ratio [aOR] 2.86, 95% confidence interval [CI] 1.81–4.53, p < 0.001). Conversely, an early clinical intervention—tracheostomy performed within 10 days of mechanical ventilation initiation—was associated with a significantly lower risk of weaning failure (aOR 0.55, 95% CI 0.35–0.87, p = 0.010). Furthermore, elevated biomarker levels strongly correlated with prolonged intensive care unit stays and higher 90-day mortality. Conclusions: Admission NT-proBNP serves as a powerful biomarker associated with cardiopulmonary vulnerability from the earliest stages of critical illness. Integrating this diagnostic biomarker with interventional strategies like optimal tracheostomy timing has significant prognostic implications. This biomarker-guided approach facilitates personalized risk stratification from ICU admission, potentially optimizing weaning pathways for mechanically ventilated patients. Full article

Objectives: Post-activation performance enhancement (PAPE) has been explored for its potential to improve performance in combat sports. This part II of the systematic review and meta-analysis investigated the acute effects of PAPE protocols on sport-specific performance outcomes and evaluated the influence of moderating variables, specifically competitive level and training experience. Methods: A PRISMA-guided search (2010–2024) identified 13 studies examining PAPE in combat sports athletes. Inclusion criteria required human trials using defined PAPE protocols and evaluating sport-specific tests, primarily the Frequency Speed of Kick Test (FSKT-10) and the Taekwondo-Specific Agility Test (TSAT). A random-effects meta-analysis (Hedges’ g) was conducted on data from 176 athletes. Results: The meta-analysis revealed a profound moderating effect of training status on PAPE responsiveness. For the FSKT-10, amateur athletes demonstrated large, significant improvements (g = 1.28, p < 0.001), whereas elite athletes showed trivial, non-significant changes (g = 0.11, p = 0.357). Similarly, athletes with <6 years of training experience exhibited substantially larger enhancements in both FSKT-10 (g = 1.60) and TSAT agility (g = −1.64) compared to their more experienced (>6 years) counterparts (g = 0.42 and g = −0.65, respectively). Furthermore, dynamic and biomechanically specific conditioning activities (e.g., repeated high-intensity techniques) were most effective at driving sport-specific potentiation. Conclusions: PAPE protocols may enhance acute sport-specific performance when utilizing dynamic, highly specific conditioning activities. However, a possible “ceiling effect” may blunt this potentiation in elite and highly experienced athletes, suggesting a potential need for highly individualized priming strategies at the top competitive levels, specifically in taekwondo. Full article

The Brazilian craft beer market has experienced continuous growth, increasing operational challenges for small- and medium-sized breweries that frequently rely on empirical and spreadsheet-based production routines. These practices often lead to inefficient resource allocation, production instability, and sustainability concerns. This study proposes an integrated analytical framework combining Machine Learning (ML) and Operations Research (OR) to improve demand forecasting and production planning. The methodology is based on a synthetic dataset calibrated to the operational conditions of a Brasília-based craft brewery, incorporating realistic demand patterns such as seasonality, trend, and intermittency across multiple SKUs over an 18-month horizon. Forecasting models—including Moving Average, Single Exponential Smoothing, and a global ML-based proxy—were evaluated using rolling-origin validation. The resulting probabilistic forecasts were integrated into a capacity-constrained optimization model based on linear programming, extended with risk-aware decision-making using Conditional Value-at-Risk (CVaR). The results indicate that the ML-based approach achieved competitive forecasting performance (sMAPE = 5.83% and MAE = 11.76) while enabling the generation of capacity-feasible and risk-aware production plans aligned with service-level targets. The integration of probabilistic forecasts into the optimization model allowed explicit trade-offs between cost, service level, and resource utilization. The main contribution of this study lies in demonstrating how the integration of predictive and prescriptive analytics can support more sustainable production planning in resource-constrained manufacturing environments. By replacing ad hoc spreadsheet routines with a closed-loop decision-support system, the proposed framework advances the literature on data-driven PPC and provides practical guidance for SMEs operating under uncertainty. Full article

The connection of large-capacity loads at nodes in a radial distribution network can readily lead to severe voltage sag phenomena, thereby significantly deteriorating power supply quality. To ensure the safe operation of both voltage-sensitive equipment and the power grid, the deployment of Dynamic Voltage Restorers (DVR) and Static Var Compensators (SVC) is recognized as one of the most effective countermeasures for addressing voltage sag issues. Considering the inherent topological characteristics of the radial distribution network, a dimensional collaborative governance strategy is proposed, which takes longitudinal dimension collaborative governance as the primary approach and horizontal dimension collaborative governance as a supplementary measure. Based on sensitivity analysis, the concepts of horizontal sensitivity and longitudinal sensitivity are defined. Furthermore, considering the response time of governance equipment, the voltage sag governance process is divided into two distinct stages: in the first stage, governance is primarily reliant on DVR, and a longitudinal dimension collaborative optimization algorithm is proposed to solve the corresponding optimization model; in the second stage, governance mainly utilizes SVC, where a standard particle swarm optimization (PSO) algorithm is employed to solve its optimization model. A case study conducted on a 42-node radial distribution network validates that the proposed approach effectively governances the voltage sag problem in the distribution network. Through analysis, the number of nodes experiencing voltage sag was reduced from 29 to 0 in both the first and second governance stages. In the first stage, the total compensation voltage of the DVR is 0.581 p.u. With the coordinated participation of SVC in the second stage, the total DVR compensation voltage decreases to 0.100 p.u., corresponding to a significant reduction of 82.79%. Given the higher capital cost of DVR relative to SVC, this substantial decrease in required DVR capacity effectively lowers the overall governance cost. Full article

Background/Objective: Periodontitis is a chronic inflammatory disease influenced by clinical, behavioral, and microbial determinants. However, the contribution of these factors to disease remains a topic of debate, particularly in untreated adult populations. This study aims to characterize the clinical, epidemiological, and microbial features associated with periodontitis in an adult cohort and to compare the discriminatory performance of microbiome-based predictive models with conventional clinical–behavioral models. Methods: A cross-sectional study was conducted in 943 adults. Periodontal status was determined by experienced clinicians according to the 2017 World Workshop on the Classification of Periodontal and Peri-implant Diseases and Conditions. Clinical variables, behavioral factors (smoking, bruxism, diet), intraoral conditions (caries and malocclusion), and systemic comorbidities were recorded. The oral microbiome was analyzed using targeted PCR for selected periodontal bacteria. Predictive models were constructed using logistic regression and least absolute shrinkage and selection operator (LASSO) variable selection. Results: Periodontitis was diagnosed in 47.2% of participants. Age, smoking, and bruxism were significantly associated with periodontitis. Malocclusion was the only significant intraoral predictor (OR = 2.00). Individuals with periodontitis exhibited increased levels of periodontopathogens, including P. gingivalis, T. forsythia, and E. corrodens, along with reduced levels of S. mutans. Microbiome-based models demonstrated superior discriminatory performance (AUC = 0.76, LASSO). E. corrodens and C. sputigena were independently associated with greater probing depth (p < 0.001). Conclusions: Microbiome-based predictive models, particularly at the species level, showed better discriminatory performance than conventional clinical–behavioral models. These findings support the potential utility of salivary microbial signatures as adjunctive, non-invasive biomarkers of periodontal inflammatory status. Full article

Precipitation is a fundamental element in terrestrial water circulation and ecosystem hydrological balance. The occurrence of concentrated precipitation is closely linked to vegetation growth and soil fertility rather than accumulated or averaged precipitation. Despite its importance, the characteristics of continuous precipitation and its specific effects on vegetation cover remain uncertain. In this study, we formulated a new continuous precipitation index system, including $C{P}_d$ (continuous precipitation days); $AC{P}_t$ (annual continuous precipitation times); $C{P}_a$ (continuous precipitation amount); and $FCP$ (frequency in different ranges of $AC{P}_a$). We utilized daily precipitation data from 467 meteorological stations across China, which were divided into eight vegetation type regions. We observed that the spatial distribution of continuous precipitation differed to varying degrees from accumulated precipitation. The national average of $MAC{P}_a$ for a single event was 16.7 mm, ranging from 3.8 mm in the temperate desert region to 37.1 mm in the tropical monsoon forest and rainforest region. Similarly, the national average of $MC{P}_d$ ($MMC{P}_d$) for a single event was approximately 2.3 or 9 days. At the regional level, the tropical monsoon forest and rainforest region experienced the longest $MMC{P}_d$. Furthermore, the national average of $MAC{P}_t$ occurrences for 1 year was 57.7 times, varying from 29.8 times in the temperate desert region to 77.9 times in the tropical monsoon forest and rainforest region. Vegetation responses to precipitation regimes exhibit significant regional heterogeneity across China. Our analysis reveals that $MAC{P}_t$ and $M{P}_a$ show markedly positive correlations with vegetation growth. In subtropical monsoon climate zones, particularly the Yunnan–Guizhou Plateau and Qinling Mountains, $MAC{P}_t$ demonstrates strong positive correlations (r = 0.6–1.0) with NDVI, where sustained rainfall provides stable moisture availability for vegetation. While a positive correlation between vegetation (NDVI) and mean annual consecutive precipitation is observed in some arid northern regions, in ecosystems such as the Loess Plateau (TG/TM), vegetation growth shows greater dependence on $M{P}_a$, highlighting the crucial role of total precipitation amount in water-limited ecosystems. Notably, extreme precipitation events display dual effects on vegetation dynamics. Prolonged heavy rainfall ($MMC{P}_d$/$MMC{P}_a$) exhibits significant negative impacts on NDVI (r = −1.0 to −0.6) in topographically complex regions, including the Hengduan Mountains and Yangtze River Basin (SE), likely due to induced soil erosion and waterlogging stress. Our findings underscore the importance of incorporating continuous precipitation indices to evaluate and forecast the influence of precipitation on ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges. Full article

Rakı, a traditional distilled beverage produced from grapes, holds significant economic importance in Türkiye; however, comprehensive consumer-focused sensory research remains limited. This study aims to determine the aroma profile, sensory characteristics, and consumer preferences of commercial rakı to guide producers in aligning product characteristics with consumer expectations. Nine commercial rakı samples were evaluated. The aroma composition was analyzed using SBSE-GC-MS. Sensory attributes were assessed by a trained panel through descriptive analysis (DA) and by 100 consumers utilizing the Check-All-That-Apply (CATA) method alongside a liking test. Eighty-one aroma compounds were identified, predominantly the phenylpropanoids trans-anethole and estragole, with monoterpenes and sesquiterpenes dominating the secondary profile. Integrating instrumental data with DA evaluations suggests that anethole and sesquiterpenes likely contribute to the attributes related to visual coating, body, creamy, mastic, persistency, and complexity. Consumer profiling revealed two distinct preference groups. Older, frequent consumers preferred complex, high-alcohol profiles with trigeminal harshness and visual glass coating, whereas younger, casual consumers preferred smoother rakı with a traditional white appearance, reacting negatively to “boiled aniseed” flavors and the yellowish tint of oak-aged versions. The CATA technique effectively distinguished these profiles. To enhance overall product quality, producers should eliminate “boiled” defects and adjust sensory profiles: complex products for experienced consumers and visually traditional, smooth profiles for younger consumers. According to current knowledge, this is the first study to employ the CATA method alongside consumer profiling and preference mapping in the sensory evaluation of rakı. Full article

Background and Objectives: Engaging in sports activities presents several benefits but also carries a risk of injury. Performing warm-up exercises may serve as a preventive measure against sports injuries. This study explored how participating in warm-up exercises is associated with complications, subsequent injury frequency, and recovery duration among athletes with a history of sports injuries. Materials and Methods: In this study, we performed cross-sectional secondary analysis of data derived from the 2024 Sports Safety Accident Survey conducted by the Korea Sports Safety Foundation, which is a nationally administered survey based on a structured questionnaire. The survey, conducted from November 2024 to December 2024, targeted 10,000 athletes aged ≥12 years registered in 64 sports nationwide. We utilized the data of 6063 athletes who had experienced sports injuries. The collected data were analyzed using frequency analyses, chi-squared tests, and multivariate logistic regression analyses. This study was conducted as a physical activity epidemiology study to examine associations between warm-up exercise participation and injury outcomes. Results: The likelihood of complications was higher among those who responded “not really” or “neutral” regarding participation in warm-up exercises. The likelihood of injuries was higher among those who responded “neutral” or “somewhat”. Furthermore, the likelihood of prolonged recovery was higher among those who responded “not really”, “neutral”, or “somewhat”. Conclusions: Performing warm-up exercises is an essential measure for athletes with a history of injuries to safely engage in sports activities. Therefore, it is necessary to highlight the importance of warm-up exercises among athletes and to implement a safety management system to encourage consistent performance. Full article

Background/Objectives: Anticholinergic burden is an important risk marker in older adults, associated with cognitive decline, falls, and increased mortality. This study aimed to assess anticholinergic burden in institutionalized elderly individuals using two tools (ACB calculator and CALS—CRIDECO Anticholinergic Load Scale), as well as to analyze its relationship with pharmacotherapeutic variables like polypharmacy. Methods: A descriptive cross-sectional study was conducted by analyzing the pharmacotherapeutic profiles of institutionalized elderly individuals (≥65 years) utilizing individualized medication preparation services from a community pharmacy in Alentejo (Portugal). Participants agreed to the study and had complete, up-to-date pharmacotherapeutic profiles. Results: The pharmacotherapeutic profiles of 75 institutionalized elderly people were analyzed; the sample comprised mostly women (72%) who had experienced excessive polypharmacy (≥10 medications) (56%) and had an average age of 85.62 ± 7.62 years. It was found that 90.7% (ACB) and 89.3% (CALS—CRIDECO) of the elderly had anticholinergic burden, with mean values of 3.60 ± 2.84 and 3.33 ± 2.51, respectively. Women exhibited higher anticholinergic burden in unadjusted analyses (p < 0.05). The burden correlated moderately with the total number of medications (p < 0.05). Conclusions: The results show high exposure to anticholinergic medications in the institutionalized elderly population, reinforcing the rationale for systematic therapeutic reviews focused on the pharmacological safety of institutionalized older adults in community pharmacies. Full article

Background: As life expectancy increases, more elderly patients require a pancreaticoduodenectomy (PD). While minimally invasive approaches are preferred, data indicating the safety of robotic PD in elderly patients remains limited. This study compares operative outcomes of robotic PD in elderly versus younger patients to define its oncological role. Material and Methods: A systematic search of PubMed, Embase, Web of Science, and Scopus identified studies comparing robotic pancreaticoduodenectomy in elderly versus younger patients. Robotic-exclusive cohorts were analyzed for perioperative outcomes, complications, and mortality. A meta-analysis was performed using R to calculate pooled prevalences, Odds Ratios (ORs) and Weighted Mean Differences (WMDs). Results: Elderly patients experienced significantly longer operative times (MD = 11.4 min) and hospital stays (MD = 7.76 days). They demonstrated higher odds of severe complications (Clavien–Dindo ≥ III: OR = 2.20), delayed gastric emptying (DGE) (OR = 2.34), and mortality (OR = 3.42). There were no significant differences in blood loss, transfusions, overall complications, pancreatic fistulae, bile leakage, hemorrhage, infection, readmission, or reoperation. Notably, age-stratified subgroup analyses revealed a distinct risk divergence: studies using an 80-year cutoff reported significantly higher odds of mortality and DGE, whereas 70-year-threshold studies demonstrated more pronounced odds for severe and overall complications. Conclusions: While robotic pancreaticoduodenectomy is feasible in elderly patients with comparable intraoperative blood loss and overall complication rates to younger patients, it does not eliminate all age-related risks. Elderly patients remain at significantly higher risk for severe complications and mortality. Therefore, robotic application in this demographic requires rigorous preoperative assessment, utilizing age as an initial risk-stratifier while allowing physiological reserve to determine final surgical candidacy. Full article

This paper details the development of an autonomous robotic solution for the long-term surveillance of low-level radiation in nuclear facilities. Implementing such a system mitigates personnel health risks by minimizing radiation exposure and automating a mundane, repetitive task. To address the inherent challenges of deploying robots in highly unstructured environments, the core contribution of this work is a novel, error-tolerant behavioral architecture. Specifically, a custom behavior tree is designed to absorb execution imperfections and tolerate environmental uncertainties. This allows the robot to adapt and continue its mission rather than experiencing a hard failure. Bayesian optimization is utilized to perform adaptive mapping via a manipulator-equipped Spot quadruped robot, which features a Kromek Sigma50 gamma spectrometer attached to its end effector. Experiments were conducted in an obstacle-rich testbed using a Cesium-137 source. The results demonstrate the feasibility of the proposed system and its behavioral design approach, as the robot successfully performed adaptive mapping and correctly identified the location and approximate intensity of the radiation source. Full article

Objectives: The reduction in intrinsic capacity significantly impacts the functional abilities of older individuals, and is strongly linked to adverse health consequences. Safeguarding and enhancing an elderly person’s intrinsic capacity can lead to better life quality and improved social well-being. This research seeks to explore the relationships between social engagement, physical activity, and the likelihood of decline in intrinsic capacity among the elderly in China. Methods: Utilizing the CHARLS data from 2015, individuals with incomplete information were removed from our study. Our analysis included a total of 3502 samples. Social participation and physical activity were assessed through self-reported surveys. The evaluation of intrinsic capacity, based on WHO criteria, thoroughly examined participants in five areas: mobility, sensory functions, vitality, mental health and cognitive abilities. The links between social participation, physical activity and intrinsic capacity decline were revealed through logistic regression. Restricted cubic splines (RCS) were employed as a statistical model, exploring the relationships between dose and response. Interaction analysis was used to examine the interaction between social participation and physical activity. Analyses of subgroups facilitated the evaluation of variations based on factors including age, gender, duration of sleep, and chronic disease numbers. Results: In contrast to the low-level group, individuals with moderate to high degrees of social participation (OR = 0.80, p = 0.012; OR = 0.56, p < 0.001) and those with moderate to high levels physical activity (OR = 0.72, p = 0.019; OR = 0.74, p = 0.016) demonstrated a notably lower risk of decline in intrinsic capacities. A negative correlation was identified in a dose-response manner between social participation and the risk of IC decline. A U-shaped relationship was established between physical activity levels and the risk of intrinsic capacity decline. The fully adjusted interaction model showed that no significant interaction was observed between social participation and physical activity (p = 0.778). Furthermore, subgroup analyses showed that these associations remained generally consistent across older adults of different age groups, genders, sleep duration, and numbers of chronic diseases. Conclusions: In order to slow down the deterioration of intrinsic capacity in older adults in China, it may be beneficial to focus on sustaining elevated levels of social participation and engaging in moderate physical activity. Higher levels of social participation are associated with a lower risk of experiencing a decline in intrinsic capacity, whereas both insufficient and excessive physical activity are associated with an increased risk of intrinsic capacity decline. Full article

This study evaluates how life stress acts as a catalyst for network anomie (online deviance) among college students, specifically examining the mediating influence of anxiety sensitivity. Through a quantitative framework, data were gathered from 612 undergraduates utilizing the Life Stress Scale, the Anxiety Sensitivity Inventory, and the Network Anomie Behaviour Scale. Initial findings confirmed that digital deviance is relatively prevalent across the cohort. Demographic analyses revealed distinct patterns: male respondents and single-child participants experienced elevated punishment-related stress and engaged more frequently in online infringement. Furthermore, academic performance demonstrated a clear polarization effect; students at both extremes of the academic spectrum—particularly those in the lowest 5%—exhibited the most pronounced anomic behaviors. Regression models identified life stress, notably the punishment dimension, as a strong positive predictor of online norm violations. Additionally, anxiety sensitivity serves as a partial mediator in this dynamic, accounting for 7.78% of the overall effect. Ultimately, these results characterize life stress as a critical environmental vulnerability that directly fosters network anomie while indirectly aggravating these behaviors by elevating student anxiety. Full article

The research creates classification maps of wind turbine operational speeds based on the wind regimes of four governorates in central and southern Iraq: Wasit, Diwaniyah, Maysan, and Dhiqar. High-resolution wind data from GEOSUN resource maps, together with statistical analysis of the Weibull distribution, are used to derive site-specific shape and scale parameters, which are then utilized to calculate the ideal cut-in, rated, and cut-out wind speeds for each location. A turbine performance index integrates capacity factor and normalized power output to determine the turbine speed combination that optimizes energy production for the local wind distribution. The resultant maps exhibit distinct geographical gradients: in all four governorates, cut-in, rated, and cut-out speeds consistently escalate towards the eastern regions of the research area, therefore broadening the range of technologically suitable turbines. Quantitatively, Wasit demonstrates the highest rated wind speeds, ranging from approximately 11.1 to 14.9 m per second, and cut-out speeds from about 20.5 to 27.6 m per second, indicating superior wind resource quality relative to other governorates. In contrast, Diwaniyah is suitable for lower-speed turbines, with minimum rated speeds between 8.9 and 9.5 m per second and minimum cut-out speeds around 16.6 to 17.6 m per second. Analysis of wind direction indicates that around fifty percent of the wind power potential originates from the northwest sector, suggesting that turbines should be aligned toward the northwest to optimize yearly energy acquisition. The maps serve as an effective decision support instrument that connects quantitative wind resource assessment to turbine operational specifications, facilitating expedited preliminary turbine selection, enhanced energy efficiency, and diminished dependence on traditional fossil fuel power plants in areas experiencing persistent electricity deficits. Full article