Search Results (570)

Compared to commuting, grocery shopping trips, despite their profound implications for mixed land use and transportation planning, have received limited attention in travel behavior research. Drawing upon a travel diary survey conducted in a fast-growing metropolitan region of the United States, i.e., Salt Lake County, UT, this research investigated a variety of influential factors affecting mode choices associated with grocery shopping. We analyze how built environment (BE) characteristics, measured at seven spatial scales or different ways of aggregating spatial data—including straight-line buffers, network buffers, and census units—affect travel mode decisions. Key predictors of choosing walking, biking, or transit over driving include age, household size, vehicle ownership, income, land use mix, street density, and distance to the central business district (CBD). Notably, the influence of BE factors on mode choice is sensitive to different spatial aggregation methods and locations of origins and destinations. The straight-line buffer was a good indicator for the influence of store sales amount on mode choices; the network buffer was more suitable for the household built environment factors, whereas the measurement at the census block and block group levels was more effective for store-area characteristics. These findings underscore the importance of considering both the spatial analysis method and the location (home vs. store) when modeling non-work travel. A multi-scalar approach can enhance the accuracy of travel demand models and inform more effective land use and transportation planning strategies. Full article

The purpose of this research is to examine employee perceptions regarding the implementation of ESG (environmental, social, and governance) practices in financial institutions, with a comparative focus on urban and rural banks in the Republic of Serbia. The study investigates how employees assess environmental, social, and governance aspects of ESG, as well as their own role in applying these principles in everyday work. The results reveal statistically significant differences between the two groups; employees in urban banks report greater engagement, more access to training, and stronger involvement in ESG decision-making. These findings suggest the existence of more developed institutional support, infrastructure, and organisational culture in urban banks. In contrast, employees in rural banks highlight the need for enhanced training, clearer ESG guidance, and improved oversight mechanisms. The study underlines the importance of investing in employee development and internal communication, particularly in rural contexts, to improve ESG outcomes. By focusing on employee-level perceptions, this research contributes to the understanding of how organisational and geographic factors influence the implementation of ESG-related practices in financial institutions. Full article

Agricultural development is vital for East Africa’s economic growth, yet the region faces significant disparities and systemic barriers. A critical problem exists due to the lack of an integrated quantitative framework to systematically comparing agricultural capacities and facilitate optimal resource allocation, as existing studies often overlook combined internal and external factors. This study proposes a comprehensive multi-criteria decision-making (MCDM) model to assess, categorize, and strategically profile the agricultural development capacity of 18 East African countries. The method employed is an integrated Entropy-MAIRCA model, which objectively weighs six criteria (the food production index, arable land, production fluctuation, food export/import ratios, and the political stability index) and ranks countries by their distance from an ideal development state. The experiment applied this framework to 18 East African nations using official data. The results revealed significant differences, forming four distinct strategic groups: frontier, emerging, trade-dependent, and high risk. The food export index (C4) and production volatility (C3) were identified as the most influential criteria. This model’s contribution is providing a science-based, transparent decision support tool for designing sustainable agricultural policies, aiding investment planning, and promoting regional cooperation, while emphasizing the crucial role of institutional factors. Full article

We investigate how the factors influencing aircraft utilization have changed during and post-Pandemic depending on the business model before. We classify the Pandemic into three periods (pre-, during and post- Pandemic) and the business models into three types (Total, FSC and LCC). For each group, we analyze the importance of factors using the SHAP and Random Forest models. Through group-difference tests on factor importance, we examine whether there are significant differences across the three periods and business models. According to the findings of the ANOVA (Analysis of Variance) and the Kruskal–Wallis assay, the importance of factors influencing aircraft utilization has changed across all business models over the three periods. Pre-Pandemic, a coincident index and a consumer price index were the principal factors. However, the exchange rate (KRW/EUR) gained significant importance during the Pandemic. This suggests that the Pandemic’s impact on the aviation industry was not limited to reduced demand but was also associated with changes in the importance of exchange rates and key business indicators for airline operations. Pre-Pandemic, there were significant differences among the business model groups. However, no meaningful differences were observed during and post-Pandemic. In other words, it seems that the leading indexes were closely interconnected pre-Pandemic, whereas lagging indexes and exchange rate became closely interconnected afterward. A group-difference test confirmed that no differences were observed among the business models, but differences were evident when considering the groups in their entirety. We presented the implications for changes in airline decision-making to understand changes in the aviation industry caused by the Pandemic, by identifying how the factors influencing aircraft utilization were altered. Full article

Although research on religion has gained increasing attention, few studies have examined its connection to consumer identity and how it influences purchasing decisions. This gap is especially noticeable when it comes to decision-making around religious services. Previous studies on what influences consumers’ choice of banks have produced mixed findings on the role of religion. This study explores how multiple identities shape the decision to use non-Islamic banking services in Pakistan, where Muslim consumers can choose between Islamic (religious) and non-Islamic (non-religious) banking options. Using a qualitative approach, the research focuses on Muslims who opt for non-Islamic banking to understand the factors behind their choice. Findings reveal that role identity—especially as a son or daughter—plays a key role in bank selection, even when religion is important to the individual. However, identity conflicts arise as people navigate different aspects of their identity. Surprisingly, group identity had little influence on these banking decisions. Full article

Background/objective: Tailoring involves adapting research findings and evidence to suit specific contexts and audiences. This study examines how international stroke guidelines can be tailored to address gait issues after a stroke. Methods: A three-phase consensus method approach was used. A 10-member health experts panel extracted recommendations from three national clinical guidelines in the first phase. In the second phase, 362 physiotherapists completed an online questionnaire to assess the feasibility of adopting the extracted recommendations. In the third phase, a 15-physical therapist consensus workshop was convened to clarify factors that might affect the tailoring process of the extracted recommendations of gait disorder rehabilitation. Results: In phase one, 21 recommendations reached consensus. In the second phase, 362 stroke physiotherapists rated the applicability of these recommendations: 14 rated high, 7 rated low, and none were rejected. The third phase, a nominal group meeting (NGM), explored four themes related to tailoring. The first theme, “organizational factors”, includes elements such as clinical setting, culture, and regulations. The second theme, “individual clinician factors”, assesses aspects like clinical experience, expertise, abilities, knowledge, and attitudes toward tailoring. The third theme, “patient factors”, addresses issues related to multimorbidity, comorbidities, patient engagement, and shared decision-making. The final theme, “other factors”, examines the impact of research design on tailoring. Conclusions: Tailoring international clinical guidelines involves multiple factors. This situation brings home the importance of a systematic strategy for tailoring that incorporates various assessment criteria to enhance the use of clinical evidence. Future research should investigate additional implementation theories to enhance the translation of evidence into practice. Full article

The Gunung Sewu UNESCO Global Geopark (GSUGGp) is one of Indonesia’s 12 UNESCO-designated geoparks. Its presence is expected to enhance rural development by boosting the local economy through tourism. However, there is a lack of statistical evidence quantifying the economic benefits of geopark development, mainly due to the complex, non-linear nature of these impacts and limited village-level economic data available in Indonesia. To address this gap, this study aims to measure how socio-economic and environmental factors contribute to the Village Development Index (VDI) within the GSUGGp area, which includes the districts of Gunung Kidul, Wonogiri, and Pacitan. A machine learning–deep learning approach was employed, utilizing four algorithms grouped into eight models, with hyperparameter tuning and cross-validation, tested on a sample of 92 villages. The analysis revealed insights into how 17 independent variables influence the VDI. The Artificial Neural Network (ANN) algorithm outperformed others, achieving an R-squared of 0.76 and an RMSE of 0.040, surpassing random forest, CART, SVM, and linear models. Economically related factors—considered the foundation of rural development—had the strongest impact on village progress within GSUGGp. Additionally, features related to tourism, especially beach tourism linked to geological landscapes, contributed significantly. These findings are valuable for guiding geopark management and policy decisions, emphasizing the importance of integrated strategies and strong cooperation among local governments at the regency and provincial levels. Full article

Energy storage technologies are becoming increasingly important when it comes to maintaining the balance between electricity generation and consumption, especially with the increasing share of variable renewable energy sources (VRES). Pumped storage hydropower plants (PSHs) are currently the largest form of energy storage at the grid level. The aim of this study is to investigate the importance and prospects of using PSHs as part of the energy transition to decarbonize energy sources. A comparison was made between PSHs and battery energy storage systems (BESSs) in terms of technical, economic, and ecological aspects. To identify the key factors influencing the wider adoption of PSHs, a combined approach using SWOT analysis (which assesses strengths, weaknesses, opportunities, and threats) and the Analytical Hierarchy Process (AHP) as a decision support tool was applied. Regulatory and market uncertainties (13.54%) and financial inequality (12.77%) rank first and belong to the “Threats” group, with energy storage capacity (10.11%) as the most important factor from the “Strengths” group and increased demand for energy storage (9.01%) as the most important factor from the “Opportunities” group. Forecasts up to 2050 show that the capacity of PSHs must be doubled to enable the integration of 80% of VRES into the grids. The study concludes that PSHs play a key role in the energy transition, especially for long-term energy storage and grid stabilization, while BESSs offer complementary benefits for short-term storage and fast frequency regulation. Recommendations to policymakers include the development of clear, accelerated project approval procedures, financial incentives, and support for hybrid PSH systems to accelerate the energy transition and meet decarbonization targets. Full article

Amid the increasing complexity of urban risks, urban parks not only serve ecological and recreational functions but are increasingly becoming a critical spatial foundation supporting public psychological resilience and social recovery. This study aims to systematically evaluate the daily adaptability of urban parks in the context of micro-risks. The research integrates the theories of “restorative environments,” environmental safety perception, urban resilience, and social ecology to construct a five-dimensional framework for perceived resilience, encompassing resilience, safety, sociability, controllability, and adaptability. Additionally, a dynamic feedback mechanism of perception–behavior–reperception is introduced. Methodologically, the study utilizes the Fuzzy Delphi Method (FDM) to identify 17 core indicators, constructs a causal structure and weighting system using DEMATEL-based ANP (DANP), and further employs the VIKOR model to simulate public preferences in a multi-criteria decision-making process. Taking three representative urban parks in Guangzhou as empirical case studies, the research identifies resilience and adaptability as key driving dimensions of the system. Factors such as environmental psychological resilience, functional diversity, and visual permeability show a significant path influence and priority intervention value. The empirical results further reveal significant spatial heterogeneity and group differences in the perceived resilience across ecological, neighborhood, and central park types, highlighting the importance of context-specific and user-adaptive strategies. The study finally proposes four optimization pathways, emphasizing the role of feedback mechanisms in enhancing urban park resilience and shaping “cognitive-friendly” spaces, providing a systematic modeling foundation and strategic reference for perception-driven urban public space optimization. Full article

Background and Objectives: Early detection of cognitive decline (CD) is crucial for managing dementia risk factors and preventing disease progression. This study pursues two main objectives: (1) to review existing cognitive screening practices implemented in community pharmacy settings and (2) to characterize the cognitive profile of individuals eligible for screening in this context. Materials and Methods: This study was conducted in two phases. First, a scoping review of cognitive screening tools used in community pharmacies was carried out following PRISMA-ScR guidelines. Second, a cross-sectional study was performed to design and implement a CD screening protocol, assessing cognitive function. Data collection included demographic and clinical variables commonly associated with dementia risk. Decision tree analysis was applied to identify key variables contributing to the cognitive profile of patients eligible for screening. Results: The scoping review revealed that screening approaches differed by country and population, with limited pharmacy involvement suggesting implementation barriers. Cognitive screening was conducted in 18 pharmacies in Valencia, Spain (1.45%), involving 286 regular users reporting Subjective Memory Complaints (SMC). The average age of participants was 71 years, and 74.8% were women. According to the unbiased Gini impurity index, the most relevant predictors of CD—based on the corrected mean decrease in corrected impurity (MDcI), a bias-adjusted measure of variable importance—were age (MDcI: 2.60), internet and social media use (MDcI: 2.43), sleep patterns (MDcI: 1.83), and educational attainment (MDcI: 0.96). Simple decision trees can reduce the need for full screening by 53.6% while maintaining an average sensitivity of 0.707. These factors are essential for defining the profile of individuals who would benefit most from CD screening services. Conclusions: Community pharmacy-based detection of CD shows potential, though its implementation remains limited by issues of consistency and feasibility. Enhancing early dementia detection in primary care settings may be achieved by prioritizing individuals with limited internet and social media use, irregular sleep patterns, and lower education levels. Targeting these groups could significantly improve the effectiveness of CD screening programs. Full article

Background: Prevention and clinical management of musculoskeletal injuries have historically focused on the assessment and training of modifiable physical factors, but perceptual decision-making has only recently been recognized as a potentially important capability. Immersive virtual reality (VR) systems can measure the speed, accuracy, and consistency of body movements corresponding to stimulus–response instructions for the completion of a forced-choice task. Methods: A cohort of 26 female college soccer players (age 19.5 ± 1.3 years) included 10 players who participated in a baseline assessment, 10 perceptual-response training (PRT) sessions, a post-training assessment that preceded the first soccer practice, and a post-season assessment. The remaining 16 players completed an assessment prior to the team’s first pre-season practice session, and a post-season assessment. The assessments and training sessions involved left- or right-directed neck rotation, arm reach, and step-lunge reactions to 40 presentations of different types of horizontally moving visual stimuli. The PRT program included 4 levels of difficulty created by changes in initial stimulus location, addition of distractor stimuli, and increased movement speed, with ≥90% response accuracy used as the criterion for training progression. Perceptual latency (PL) was defined as the time elapsed from stimulus appearance to initiation of neck rotation toward a peripheral virtual target. The speed–accuracy tradeoff was represented by Rate Correct per Second (RCS) of PL, and inconsistency across trials derived from their standard deviation for PL was represented by intra-individual variability (IIV). Perceptual Decision Efficiency (PDE) represented the ratio of RCS to IIV, which provided a single value representing speed, accuracy, and consistency. Statistical procedures included the bivariate correlation between RCS and IIV, dependent t-test comparisons of pre- and post-training metrics, repeated measures analysis of variance for group X session pre- to post-season comparisons, receiver operating characteristic analysis, and Kaplan–Meier time to injury event analysis. Results: Statistically significant (p < 0.05) results were found for pre- to post-training change, and pre-season to post-season group differences, for RCS, IIV, and PDE. An inverse logarithmic relationship was found between RCS and IIV (Spearman’s Rho = −0.795). The best discriminator between injured and non-injured statuses was PDE ≤ 21.6 (93% Sensitivity; 42% Specificity; OR = 9.29). Conclusions: The 10-session PRT program produced significant improvement in perceptual decision-making that appears to provide a transfer benefit, as the PDE metric provided good prospective prediction of musculoskeletal injury. Full article

Background: Sarcoidosis is a multisystem inflammatory disease characterized by the immune-mediated formation of non-necrotizing epithelioid granulomas. Several commonly used medications can induce similar granulomatous reactions, known as drug-induced sarcoid-like reactions (DISRs), which closely mimic sarcoidosis. Despite their specificity in targeting molecular pathways, certain therapies—particularly targeted treatments—have increasingly been linked to DISRs. Methods: This narrative review was based on a PubMed search using the terms “SARCOID LIKE REACTION” and “DRUG”. A cross-check was performed with “SARCOID” combined with each identified drug to identify misclassified cases. Drugs with limited evidence or weak pathogenetic plausibility were excluded, leaving only molecularly targeted therapies for consideration. Sources included case reports, case series, and reviews selected based on their clinical and scientific relevance, without any restrictions on time or language. Results: In light of the available data, five main pharmacological groups were found to be associated to DISR: immune checkpoint inhibitors, TNF-α antagonists, BRAF inhibitors, monoclonal antibodies, and miscellaneous agents. Each group has distinct mechanisms of action and clinical indications, which likely affect the frequency, presentation, and timing of DISRs. Conclusions: Diagnosing DISRs is challenging, and a structured approach is crucial for differentiating them from other conditions. To support clinicians, we propose a diagnostic algorithm to guide decision-making in suspected cases. Management should be individualized, as most DISRs either resolve spontaneously or improve after the discontinuation of the causative drug. Important factors influencing therapeutic decisions include the severity of the underlying disease, the availability of alternative treatments, and the extent of DISR manifestations. Full article

Background/Objectives: Diagnosing interstitial pregnancy (IP) using ultrasonography can be challenging, as it is often mistaken for eccentrically located intrauterine pregnancy (IUP). In this retrospective cohort study, we aimed to develop a predictive scoring model using multiple clinical factors to enhance the diagnosis of IP and facilitate timely interventions in suspected cases. Methods: We enrolled 63 pregnant women with a diagnosis of suspected IP who visited a single tertiary center between January 2006 and December 2023. Data on the clinical risk factors, symptoms, laboratory test results, and ultrasound findings were analyzed. A statistical predictive score was developed using logistic regression analysis with feature selection based on the least absolute shrinkage and selection operator to optimize the predictive accuracy and clinical applicability. Results: From a total of 12 factors, a scoring model was constructed from the three most prominent factors—ultrasound findings showing no surrounding endometrium, myometrial thinning of less than 5 mm, and vaginal bleeding—all of which demonstrated high feature importance. This predictive score identified IP with a negative predictive value of 0.950 in the low-risk group and a positive predictive value of 1.000 in the high-risk group, whereas the overall area under the curve was 0.998 (95% confidence interval, 0.992–1.000). Conclusions: The statistically derived predictive model––ultrasound showing no surrounding endometrium and myometrial thinning < 5 mm combined with vaginal bleeding––demonstrated high accuracy and practical applicability for IP diagnosis, providing a robust tool to enhance clinical decision-making and optimize routine management strategies for IP. Full article

The seasonal and interannual irregularity of temperature and precipitation is a feature of the Mediterranean climate that is intensified by climate change and constitutes a relevant driver of water and soil degradation. This study was developed during three years in a hydro-agricultural area of the Alqueva irrigation system (Portugal) with Mediterranean climate conditions. The sampling campaigns included collecting water samples from eight irrigation hydrants, analyzed four times yearly. The analysis incorporated meteorological data and indices (precipitation, temperature, and drought conditions) alongside chemical parameters, using multivariate statistics (factor analysis and cluster analysis) to identify key water quality drivers. Additionally, machine learning models (Random Forest regression and Gradient Boosting machine) were employed to predict electrical conductivity (ECw), sodium adsorption ratio (SAR), and pH based on chemical and climatic variables. Water quality evaluation showed a prevalence of a slight to moderate soil sodification risk. The factor analysis outcome was a three-factor model related to salinity, sodicity, and climate. The cluster analysis revealed a grouping pattern led by year and followed by stage, pointing to the influence of inter-annual climate irregularity. Variations in water quality from the reservoirs to the distribution network were not substantial. The Random Forest algorithm showed superior predictive accuracy, particularly for ECw and SAR, confirming its potential for the reliable forecasting of irrigation water quality. This research emphasizes the importance of integrating time-sensitive monitoring with data-driven predictions of water quality to support sustainable water resources management in agriculture. This integrated approach offers a promising framework for early warning and informed decision-making in the context of increasing drought vulnerability across Mediterranean agro-environments. Full article

This study aims to assess the spatial distribution and health risk potential of nitrate (NO₃⁻) contamination in groundwater resources of the Harran Plain, a semi-arid agricultural region in Southeastern Türkiye. Groundwater samples were collected from 20 locations during pre- and post-irrigation periods and analyzed for a range of hydrochemical parameters. A probabilistic risk assessment framework, based on the U.S. Environmental Protection Agency (USEPA) guidelines, was employed to evaluate non-carcinogenic health risks across different demographic groups. The integration of Geographic Information Systems (GIS), multivariate statistical analyses, and Monte Carlo simulation enabled a comprehensive evaluation of exposure scenarios and contributing factors. This research contributes to the scientific understanding of groundwater vulnerability in intensively farmed areas, provides a decision-support framework for water quality management, and emphasizes the importance of protecting sensitive populations in nitrate-affected regions. Full article