Search Results (21)

Background/Objectives: Posterior vitreous detachment (PVD) is an age-related physiological process, yet the clinical and biometric factors influencing its progression remain incompletely characterized in adults undergoing routine ophthalmic evaluation at a tertiary center. Characterizing expected vitreous patterns is essential for interpreting vitreoretinal interface changes in disease. This study aimed to identify independent clinical and biometric factors associated with more advanced PVD stages in adults without macular pathology. Methods: In this cross-sectional observational study, 340 eyes from 198 consecutive adults undergoing routine ophthalmological evaluation at a tertiary hospital (March 2022–April 2023) were analyzed. Eyes with current or past macular disease were excluded. Demographic variables, systemic comorbidities and ocular history were recorded. Axial length was measured using optical biometry IOLMaster 700 (Carl Zeiss Meditec, Jena, Germany). Vitreous status was assessed with 10-MHz B-scan ultrasonography and classified as no PVD, partial PVD or complete PVD. Analyses were performed at the eye level. Given its cross-sectional design, this study evaluates associations and cannot establish causal relationships. Bivariate comparisons examined associations between clinical variables and PVD grade. Multivariable modeling was conducted using a clustered generalized estimating equations (GEE) ordinal logit model as the primary analysis, and a secondary independent-eye ordinal logistic regression model was used to evaluate the proportional-odds assumption and model robustness. Results: Mean age was 55.6 ± 18.3 years, and 68.5% of eyes were from female participants. No PVD, partial PVD and complete PVD were present in 30.9%, 43.5% and 25.6% of eyes, respectively. In the primary GEE model, axial length (OR 1.35; p < 0.001), systemic hypertension (OR 7.13; p < 0.001), and prior cataract surgery (OR 2.13; p = 0.020) were independently associated with more advanced PVD stages. Age showed a modest but significant association with increasing PVD severity (OR 1.03; p = 0.012). Sex and diabetes mellitus were not associated with PVD grade. The independent-eye ordinal model yielded consistent effect directions. Conclusions: In adults without macular disease, more advanced PVD stages are independently associated with axial elongation, systemic hypertension, and previous cataract surgery, while age shows a mild but significant association. These findings provide clinically useful contextual reference information for interpreting vitreoretinal interface changes in health and disease. These associations should not be interpreted as causal due to the cross-sectional nature of the study. Full article

Background: Locus of control (LoC) may shape how older adults appraise aging, particularly in acute geriatric rehabilitation. Evidence linking internal/external LoC to domain-specific Views on Aging (VoA, containing Physical Loss, Social Loss, Personal Growth, Self-awareness/Gains) remains limited. Methods: We analyzed a cross-sectional cohort of patients aged 70 and above from an acute geriatric rehabilitation unit (N = 103) and contextualized findings with a 1:1 Mahalanobis-matched subsample from the German Ageing Survey. Internal and external LoC and covariates (age, sex, Barthel, cognitive function, depressive symptoms, health satisfaction) were standardized (z). Associations were estimated using (i) ordinary least squares (OLS) regression across eight LoC effects, as well as (ii) proportional-odds ordinal models (quartiles; logit link), as a complementary, distribution-robust approach. Results: For the Physical VoA domain, higher internal LoC related to more positive appraisals (OLS β = 0.133, 95% CI 0.043–0.223, p = 0.035; OR = 3.52), whereas higher external LoC related to less positive appraisals (β = −0.165, 95% CI −0.285 to −0.045, p = 0.035; OR = 0.274). Internal LoC also increased the odds of more positive Personal Growth (OR = 1.64, 95% CI 1.04–2.72), while effects on Social Loss (external LoC OR = 0.649, 95% CI 0.418–0.991) and Gains were smaller. Univariate Spearman correlations were directionally consistent. In the DEAS comparison, older patients showed greater endorsement of both physical losses and gains. Conclusions: In acute geriatric rehabilitation, internal control beliefs align with more positive views of physical aging and growth, whereas external control aligns with less positive physical (and modestly social) views. The results position LoC as a clinically relevant correlate of aging appraisals. Full article

Ordinal regression combines classification and regression techniques, constrained by the intrinsic order among categories. It has wide-ranging applications in real-world scenarios, such as product quality grading, medical diagnoses, and facial age recognition, where understanding ranked relationships is crucial. Existing models, which often employ a series of binary classifiers with ordinal consistency loss, effectively enforce global order consistency but frequently encounter misclassification errors between adjacent categories. Achieving both global and local (neighbor-level) ordinal consistency, however, remains a significant challenge. In this study, we propose a hybrid ordinal regression model that addresses global ordinal structure while enhancing local consistency between neighboring categories. Our approach leverages ordinal metric learning to generate embeddings that capture global ordinal relationships and extends consistent rank logits with a neighbor order penalty in the loss function to reduce adjacent category misclassifications. Experimental results on multiple benchmark ordinal datasets demonstrate that our model significantly minimizes neighboring misclassification errors and global order inconsistencies, outperforming existing ordinal regression models. Full article

This study investigates the industrial electricity pricing (IEP) profiles of 22 OECD countries to understand the effect of renewable energy and taxes on overall prices. Clustering analysis was performed on pricing data from the year 2000 to 2018 to observe how prices evolved. Ordinal logit regression analysis was performed to determine possible associations between the clustered groups and the percentage share of renewables generated (REG), specifically linked to wind, solar photovoltaics and solar thermal. Other independent variables indicating economic and market structures were also considered. Clustering results for both prices before and after tax indicated three pricing clusters, termed low, median, and high pricing clusters. IEP in Italy and Germany was found to have the highest effect owing to taxes, while IEP in countries such as the US, Norway, Canada, and Denmark was least affected by taxes. Regression results show positive associations between the clustered profiles and REG. The positive association between the non-taxed component of IEP and a unit increase in REG is 1.41 times, whereas the positive association of overall IEP price (including taxes) and a unit increase in REG is 56.26 times, which is 39.9 times higher. Our results show that REG penetration has had a minimal effect on IEP over the time under consideration, but rather that the taxation on IEP coincides with REG penetration, contributing to IEP increases. Full article

According to the Federal Reserve of the United States, in the second quarter of 2024, American credit card debt reached USD 1.14 trillion, the highest balance ever recorded. In an age of high-interest, complex credit cards, how does financial literacy affect credit card debt repayment? Also, how could financial literacy and education stop the rise in credit card debt in America? To answer these questions, we use microdata from the latest wave of the Survey of Consumer Finances for 2022. We aim to capture the likelihood of credit card repayment behaviors related to the monthly balances owed by 3865 credit card holders. We consider three categories of self-reported credit card payoff behavior: hardly ever, sometimes, and always or almost always. Given the ordinal nature of our outcome variable, we perform a series of likelihood-ratio and Brant tests to assess the assumption of the proportionality of odds across response categories. Following the failure of the tests, we conclude with the selection of a generalized ordered logit/partial proportional odds model that allows us to relax the parallel lines constraint for those variables for which it is not justified. In our logistic regressions, we account for a comprehensive set of demographic characteristics, and from our results, we highlight the following: For credit card holders with low financial literacy, we find that the odds of moving to a higher category of payoff behavior are 21% and significantly lower than those of high financial literacy respondents. Further, for college-educated card holders, the odds of paying off always or almost always versus sometimes and hardly ever are 2.49 times and significantly greater than the odds for credit card holders without a college education. Credit card holders who are minority group members, female, under 45, have dependents, or earn less than USD 50,000 demonstrate a tendency for poor credit card payoff behavior. In our conclusion, we discuss how to improve credit card repayments. We stress the importance of monitoring people closely. We also aim to provide better financial advice to certain groups. Lastly, we present a more realistic approach to building and sustaining financial literacy. Full article

Islamic finance (IF) holds significant potential for economic development and the enhancement of financial inclusion in Uzbekistan. Sukuk, as a key Islamic capital market instrument and Shari’ah-compliant investment alternative, plays an important role in this context. However, the demand for sukuk and its determinants are not well understood by policymakers and industry practitioners in Uzbekistan. This study aims to address this research gap by utilizing an ordinal logit model on primary data collected through a survey of 196 individuals from diverse demographic and professional backgrounds, with varying levels of IF and capital market knowledge and experience. The regression results indicate that factors such as prior investment experience, knowledge of sukuk, and a strong inclination toward Shari’ah-compliant investments positively influence an individual’s intent to buy sukuk. Conversely, we found that residents of Tashkent (the capital city) are less likely to invest in sukuk compared to residents of other regions in Uzbekistan or those residing abroad. Based on this study’s findings, several essential policy and practical recommendations are provided to relevant stakeholders. Full article

Along with the rapid development of industries and the acceleration of urbanisation, the problem of air pollution is becoming more serious. Exploring the relevant factors affecting air quality and accurately predicting the air quality index are significant in improving the overall environmental quality and realising green economic development. Machine learning algorithms and statistical models have been widely used in air quality prediction and ranking assessment. In this paper, based on daily air quality data for the city of Xi’an, China, from 1 October 2022 to 30 September 2023, we construct support vector regression (SVR), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), random forests (RF), neural network (NN) and long short-term memory (LSTM) models to analyse the influence of the air quality index for Xi’an and to conduct comparative tests. The predicted values and 95% prediction intervals of the AQI for the next 15 days for Xi’an, China, are given based on the Bootstrap-XGBoost algorithm. Further, the ordinal logit regression and ordinal probit regression models are constructed to evaluate and accurately predict the AQI ranks of the data from 1 October 2023 to 15 October 2023 for Xi’an. Finally, this paper proposes some suggestions and policy measures based on the findings of this paper. Full article

This study evaluates the feasibility of a new food delivery service involving only food products with quality certification. In particular, through an ad hoc survey, it evaluates the influence of consumers’ personal characteristics and choice motives on joining this innovative service and the willingness to pay of the respondents. A survey was completely anonymously and voluntarily administered during the SARS-CoV-2 pandemic. A total of 630 answers were collected. Logit and ordinal logit regression were carried out to analyze data. Women and respondents who have more leisure time are more likely to join the service. The analysis of choice motives suggests that consumers more concerned with food quality, and those devoting a higher weekly budget to buying groceries are more likely to be interested in the proposed service. Individuals willing to buy groceries based on certifications and organoleptic properties and people who habitually consume one to five meals outside were more likely to be willing to increase their weekly budget to join the service. To the best of our knowledge, this is the first study evaluating the influence of personal characteristics and choice motives on an innovative food delivery service involving only certified quality products in Italy. Full article

Using public transport as an alternative to private motorized vehicles (PMVs) is becoming increasingly popular in many cities worldwide. To understand what incentives and enhancements are necessary to attract and retain more passengers, a comprehensive understanding of the quality of public transport services is essential. This study aims to broaden the existing literature on the knowledge of public transport services in a large, heterogeneous metropolitan area. A cross-examination between a binary and an ordinal logit model is proposed, using data from a mobility survey in the Porto Metropolitan Area (PMA) in Portugal. The results show that households use PMVs mainly for speed (58.8%), comfort (49.3%), and lack of public transport to the destination (35.7%). Households using public transport cite not driving/owning a PMV (52.6%), lack of alternative transport modes (49.1%), and service cost (38.2%) as primary reasons. The perceived service quality (PSQ) within the PMA exhibits variance on multiple levels, depending on the characteristics of the household and the municipality’s location. This study provides policymakers of different cities in the PMA with insight into what incentives would most effectively increase the PSQ and, in turn, attract more passengers. This insight would be valuable in developing strategies to improve public transport usage and reduce PMV usage in the PMA. Adopting these strategies will contribute to reducing environmental impact and reducing traffic congestion. Full article

Logistic regression is one of statistical methods that used to analyze the correlation between categorical response variables and predictor variables which are categorical or continuous. Many studies on logistic regression have been carried out by assuming that the predictor variable and its logit link function have a linear relationship. However, in several cases it was found that the relationship was not always linear, but could be quadratic, cubic, or in the form of other curves, so that the assumption of linearity was incorrect. Therefore, this study will develop a bivariate polynomial ordinal logistic regression (BPOLR) model which is an extension of ordinal logistic regression, with two correlated response variables in which the relationship between the continuous predictor variable and its logit is modeled as a polynomial form. There are commonly two correlated response variables in scientific research. In this study, each response variable used consisted of three categories. This study aims to obtain parameter estimators of the BPOLR model using the maximum likelihood estimation (MLE) method, obtain test statistics of parameters using the maximum likelihood ratio test (MLRT) method, and obtain algorithms of estimating and hypothesis testing for parameters of the BPOLR model. The results of the first partial derivatives are not closed-form, thus, a numerical optimization such as the Berndt–Hall–Hall–Hausman (BHHH) method is needed to obtain the maximum likelihood estimator. The distribution statistically test is followed the Chi-square limit distribution, asymptotically. Full article

This article discusses the use of drones in Hungary and considers their future penetration, based on the responses to a nationally representative 2021 questionnaire among 200 large-scale farmers engaged in precision farming and in crop production. Both the applied trans-theoretical model (with ordinal logit regression model) and the questionnaire design are suitable for comparison with the results of a similar survey in Germany. In this study, similar results were found for farm size, age, main job and education, but the evidence that higher education in agriculture has the largest positive effect on the use of drones is a novelty. The frequency values obtained for adopting precision technology elements are not fully suitable for classification due to interpretational shortcomings. The use of drones within precision technologies is no longer negligible (17%), but is nevertheless expected to grow significantly due to continuous innovation and the selective application of inputs. The state could play a major role in future uptake, particularly in the areas of training and harmonisation of legislation. Full article

Traffic accidents are inevitable events that occur unexpectedly and unintentionally. Therefore, analyzing traffic data is essential to prevent fatal accidents. Traffic data analysis provided insights into significant factors and driver behavioral patterns causing accidents. Combining these patterns and the prediction model into an accident prevention system can assist in reducing and preventing traffic accidents. This study applied various machine learning models, including neural network, ordinal regression, decision tree, support vector machines, and logistic regression to have a robust prediction model in injury severity. The trained model provides timely and accurate predictions on accident occurrence and injury severity using real-world traffic accident datasets. We proposed an informative negative data generator using feature weights derived from multinomial logit regression to balance the non-fatal accident data. Our aim is to resolve the bias that happens in the favor of the majority class as well as performance improvement. We evaluated the overall and class-level performance of the machine learning models based on accuracy and mean squared error scores. Three hidden layered neural networks outperformed the other models with 0.254 ± 0.038 and 0.173 ± 0.016 MSE scores for two different datasets. A neural network, which provides more accurate and reliable results, should be integrated into the accident prevention system. Full article

This research aims to determine the belief-based drought perceptions and attitudes of farmers in Şanlıurfa, which is in a semi-arid climate regime, and the factors affecting them. The surveys were conducted through face-to-face interviews with farmers selected by a simple random sampling method in 2020. Analyses were performed with ordinal logit regression in STATA. According to the results, while the effects of settlement location, land size, age, and the size of the household were statistically significant to farmers seeing drought, which is the dependent variable, as caused by fate, the effects of income, experience, and education level were insignificant. For the probability of predicting drought for each independent variable in the sequence analysis, the highest probabilities were found among farmers in the Harran Plain, with 21–30 years of experience, from a household of one to four people, with the land area between 5.1 and 10.0 hectares, aged 61 and above, who were primary school graduates, and who had an annual income of less than 25,000 TL ($3561). The subject of drought should be given more place in religious education in the entire research area by prioritizing these groups. It would also be beneficial to organize workshops for the farmers by agricultural consultants, where Islamic scholars would be present to support science and knowledge in terms of faith. This study is the first in this context in Turkey and provides useful data to policymakers for drought-mitigation policies. Full article

Climate change and disruption in the water cycle patterns are leading to water scarcity. This unsustained water provision is drastically affecting the areas of limited water resources. This research has studied the impacts of climate change on water availability and the localized indigenous technique of glacier grafting for sustained water provision. This adaptation strategy helps the water-stressed locality to conserve water for food security. For this reason, 160 self-administered questionnaires were deployed at the household level, and the primary data were analyzed through STATA Software for ordinal logit regression to estimate the results for both restricted and unrestricted models, against the three dependent variables of glacier grafting, glacier melt water and food security. It is found that glacier grafting ensures sustained water provision for irrigation. It increases fertile land and agricultural production to achieve food security. The income of the households from non-/agricultural products leads to afford a better standard of living. The extension of the glacier grafting strategy to curb climatic effects can help global societies to address the food insecurity issue for sustained living. Full article

Despite the impact of flow cessation on aquatic ecology, the hydrology of intermittent rivers has been largely overlooked. This has resulted in a lack of monitoring projects, and consequently, datasets spanning a period of sufficient duration to characterise both hydrological extremes. This report documents an investigation into the potential for statistical modelling to simulate the spatiotemporal dynamics of flowing, ponded and dry hydrological states in an internationally rare hydrological state dataset. The models presented predict unrecorded hydrological state data with performance metrics exceeding 95%, providing insights into the relationship between ponding prevalence and the performance of statistical simulation of this ecologically important intermediate state between drying and flowing conditions. This work demonstrates the potential for hydrological intermittence to be simulated in areas where hydrological state data are often sparse, providing opportunities for quality control and data infilling. This further understanding of the processes driving intermittence will inform future water resource assessments and the influence of climate change on hydrological intermittence. Full article