Search Results (199)

Background/Objectives: Maternal overweight and obesity are critical factors increasing the risk of various pregnancy complications. Maternal obesity can lead to fetal macrosomia and a heightened risk of intrauterine death, with long-term implications for the child’s health. This study aimed to analyze the incidence of obesity and its impact on pregnancy outcomes in women who delivered by cesarean section at the University Hospital “St. George”, Plovdiv. Methods: A single-center retrospective cohort study was conducted. The documentary method was used for gathering data. Records were randomly selected. The statistical methods used included mean values, confidence intervals (of mean), frequency, and the Kolmogorov–Smirnov test for normality of distribution. Data comparisons were performed using the Mann–Whitney test. Mean values of numerical variables were compared using the independent samples t-test. Results: In total, 46.36% of women in this study were affected by obesity to varying degrees, and the proportion of women who were overweight at the end of their pregnancy was 37.85%. In the studied cohort, 15.99% of women were affected by hypertensive complications. This significant prevalence of obesity highlights concerns regarding body weight among women of reproductive age. This study emphasized a strong correlation between maternal obesity, particularly severe obesity, and the occurrence of preeclampsia. Conclusions: In this study among women who delivered by cesarean section, a significant proportion of them were affected by overweight and obesity. Data for our country are insufficient, and a more in-depth study of this problem is needed. Future research should explore the long-term impacts of maternal obesity on the health of the mother and the newborn. Full article

The corrosion of high-strength steel wires is a key factor impacting the durability and reliability of cable-stayed bridges. In this study, the corrosion pit features on a high-strength steel wire, which had been in service for 27 years, were extracted and modeled using three-dimensional point cloud data obtained through 3D surface scanning. The Otsu method was applied for image binarization, and each corrosion pit was geometrically represented as an ellipse. Key pit parameters—including length, width, depth, aspect ratio, and a defect parameter—were statistically analyzed. Results of the Kolmogorov–Smirnov (K–S) test at a 95% confidence level indicated that the directional angle component (θ) did not conform to any known probability distribution. In contrast, the pit width (b) and defect parameter (Φ) followed a generalized extreme value distribution, the aspect ratio (b/a) matched a Beta distribution, and both the pit length (a) and depth (d) were best described by a Gaussian mixture model. The obtained results provide valuable reference for assessing the stress state, in-service performance, and predicted remaining service life of operational stay cables. Full article

Background/Objectives: War conflicts impact public health and patient hospital presentations. We aimed to assess the incidence and severity of acute appendicitis (AA) in children during the 2023 Israeli–Hamas–Hezbollah war. Methods: This multicenter retrospective cohort study included children (<18 years) admitted with AA in six medical centers in a 2-month period during the war (7 October–30 November 2023) and a comparable period in 2022. Demographic, clinical, laboratory, imaging, treatment, and outcome data were collected at individual medical centers and analyzed, with subgroup analysis based on proximity to conflict zones. Statistical tests used were Kolmogorov–Smirnov test, Student’s t-test, Mann–Whitney U, and Pearson chi square. p < 0.05 was considered significant. Results: Among 209 patients (106 in 2023, 103 in 2022), a higher rate of complicated AA during wartime was observed, although not statistically significant (27% vs. 18%, p = 0.11). The median symptom-to-presentation time remained 24 h (p = 0.64). The overall incidence of AA decreased by 20% in medical centers near conflict zones but increased by 28% in centers distant from conflict zones. The proportion of complicated AA doubled during the war in hospitals close to conflict zones as compared to during pre-war time (16% vs. 9%, respectively, p = 0.016), with a trend toward higher C-reactive protein (CRP) levels [26.5 (5.3–107.0) vs. 13 (3.4–40.9), respectively, p = 0.075], although symptom-to-presentation times remained unchanged (24 h in both groups, p = 0.32). Conclusions: Proximity to war zones was associated with an increase in the rate of complicated appendicitis in children. While the causes remain unclear, this finding highlights the complex impact of war on healthcare in general and on the well-being of children in particular. Full article

Background: Dilated Cardiomyopathy (DCM) is one of the leading causes of non-ischemic cardiomyopathy in the United States (US). The aim of our study is to analyze the general trends in DCM admissions between 2016 and 2021, and analyze social and healthcare disparities in terms of treatments and outcomes. Methods: National Inpatient Sample (NIS) data for the years 2016 to 2021 were used for the analysis. General population trends were analyzed. Normality of data distribution was tested using the Kolmogorov–Smirnov test and homogeneity was assessed using Levine’s test. One-way ANOVA was used after confirmation of normality of distribution to analyze social and healthcare disparities. Subgroup analysis was conducted, with the paired t-test for continuous variables and Fischer’s exact t-test for categorical variables to analyze statistical differences. Multivariate regression analysis was conducted to analyze the association of factors that were significant in the one-way ANOVA and paired t/chi square tests. A two-tailed p-value < 0.05 was used to determine statistical significance. Results: A total of 5262 admissions for DCM were observed between 2016 and 2021. A general declining trend was observed in the total number of DCM admissions, with a 33.51% decrease in total admissions in 2021 compared to 2016. All-cause in-hospital mortality remained stable across the years (between 3.5% and 4.5%). A total of 15.3% of admissions had CRT/ICD devices in place. A total of 425 patients (8.07%) for DCM underwent HT, and 214 admissions for DCM (4.06%) underwent LVAD placements between 2016 and 2021 In terms of interventions for DCM, namely Cardiac Resynchronization Therapy (CRT), Left Ventricular Assist Devices (LVADs) and Heart Transplantations (HTs), significant variance was observed in the mean age of the admissions with admissions over the mean age of 55 had lower number of interventions. Significant variance in terms of sex was observed for DCM admissions receiving HT, with lower rates observed for females. In terms of quarterly income, patients belonging to the lowest fourth quartile had higher rates of LVAD and HT compared to general DCM admissions. In the multivariate regression analysis, age at admission had significant association with lower chances of receiving LVADs and HT among DCM admissions, and significant association with higher chances of all-cause mortality during the hospital stay. Conclusions: A general declining trend in the total number of DCM admissions was observed between 2016 and 2021. Significant gender disparities were seen with lower rates of females with DCM receiving LVADs and HT. DCM admissions with mean age of 55 and above were found to have significantly lower rates of receiving LVADs and HT, and higher chances of all-cause mortality during the admission. Full article

The emergence of 6G wireless networks presents new challenges, for which cell-free massive MIMO combined with machine learning (ML) offers a promising solution. A key requirement for practical deployment is the generalizability of ML models—their ability to maintain robust performance across varying propagation conditions, user distributions, and network topologies. However, achieving generalizability typically demands large, diverse training datasets and high model complexity, which can hinder practical feasibility. This study analyzes the robustness of a low-complexity deep neural network (DNN) trained for power control under a single network configuration. The model’s robustness is assessed by testing it across a wide range of unseen scenarios, including changes in the number of access points, user equipment, and propagation environments. The DNN is trained to emulate three power control schemes: max-min spectral efficiency (SE) fairness, sum SE maximization, and fractional power control. To rigorously evaluate robustness, we compare the cumulative distribution functions of performance metrics quantitatively using the Kolmogorov–Smirnov test. Results show strong robustness, particularly for the sum SE scheme, with D statistics below 0.05 and p-values above 0.001. This work provides a reproducible framework and dataset to support further research into practical ML-based power control in cell-free massive MIMO systems. Full article

Background/Objectives: Temporomandibular joint disorders (TMDs) affect the temporomandibular joint and associated structures of the stomatognathic system. Joint Vibration Analysis (JVA) is a non-invasive method used to assess TMJ dysfunction through vibration frequencies. This study aimed to explore how age and gender influence TMJ vibration characteristics, hypothesizing that these factors may affect diagnostic accuracy in TMJ evaluations. Methods: This cross-sectional study includes 251 participants (143 females and 108 males) aged 10 to 30 years. TMJ evaluation used JVA to assess range of motion, integral values, and frequency distributions over and under 300 Hz. Participants with a history of TMJ disorders or significant maxillofacial trauma were excluded. Statistical analysis was conducted using employing Kolmogorov–Smirnov tests for data distribution, Kruskal–Wallis test for group comparisons, and Pearson correlation test for variable relationships. Results: Significant gender differences in range of motion (ROM) were observed, with males exhibiting higher values (p = 0.005). Age notably influenced vibration frequencies, particularly in total integral values (TIL and TIR) and frequency distributions around 300 Hz, suggesting links to degenerative changes. Females showed more pronounced age-related effects on vibration parameters. However, gender did not greatly affect vibration characteristics across all frequency bands, indicating that other factors also impact TMJ function. Conclusions: Age and gender significantly influence TMJ vibrations and the interpretation of JVA in clinical settings. Personalized approaches considering these demographic factors may enhance the accuracy of TMJ dysfunction diagnoses. Full article

Background/Objectives: Sexual attitudes, particularly those on the erotophilia (positive openness) to erotophobia (negative fear) scales, play a critical role in shaping behaviors and health decisions. While associations between sexual behavior and substance use have been documented, limited research has explored how sexual attitudes relate to mental health and substance use among Latin American university populations. This study aimed to examine the associations among erotophilic attitudes, mental health symptoms (anxiety and depression), substance use risk, and sexual behaviors in Mexican university students. Methods: A cross-sectional observational study was conducted between 2019 and 2023 with 1475 undergraduate students aged 17–25 years. Participants completed the Revised Sexual Opinion Survey (R-SOS) to assess sexual attitudes, the Hospital Anxiety and Depression Scale (HADS) for mental health evaluation, and adapted items from the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) to measure substance use risk. Erotophilic attitudes were defined as R-SOS scores ≥ 70. Statistical tests included the Kolmogorov–Smirnov test for normality, t-tests or Mann–Whitney U tests for group comparisons, Fisher’s exact test for categorical variables, and Spearman’s correlations. Multivariate binary logistic regression was used to calculate adjusted odds ratios (AdORs) and 95% confidence intervals (CIs), with a significance level of p < 0.05. Results: Erotophilic students were more likely to be male, older, initiate sexual activity earlier, and report a greater number of sexual partners. Erotophilia was positively associated with anxiety and tobacco, alcohol and marijuana use, and negatively associated with depressive symptoms. Multivariate analysis indicated that erotophilia was independently associated with male sex, age ≥ 20, higher anxiety, lower depression, low socioeconomic status, and increased risk of tobacco and marijuana use. Lower rates of consistent condom use were also reported among erotophilic individuals. Conclusions: Erotophilia may serve as a behavioral risk marker linked to anxiety symptoms and increased substance use, but not to depression. These findings highlight the need for integrated interventions addressing sexual health, substance use, and mental well-being in university populations. Full article

Background and Objectives: This study aimed to evaluate the effects of hard, soft, and semi-soft splints on TMJ vibrations in bruxers with JVA and to compare them with data obtained from asymptomatic individuals. Materials and Methods: A total of 64 individuals were divided into four subgroups: control (n = 15); and hard (n = 17), soft (n = 16), and semi-soft (n = 16) splints. Electrovibratography records from all individuals included in the study before and after the 3-month splint treatment were obtained with the Biopak^® System. Joint vibration analysis was used to evaluate TMJ sounds. Data normality was examined with the Kolmogorov–Smirnov and Levene tests. The significance of the differences was investigated by One-Way ANOVA and by the Kruskal–Wallis test. Conover’s multiple comparison test was used in post hoc tests. (ClinicalTrials.gov identifier: NCT06893744, on 24 March 2025, titled; Effects of Different Occlusal Splints). Results: After 3 months of treatment, for I < 300 Hz right opening, the control group was statistically lower than both semi-soft (p < 0.001) and hard (p < 0.001) splint groups. The difference between semi-soft and hard splints in post-treatment I < 300 Hz right opening is not statistically significant. After 3 months of treatment compared with the beginning, the increases in left-opening Ti (p = 0.004), I < 300 Hz (p = 0.004), and PA (p = 0.007) values in the soft splint group were statistically significant. Conclusions: All three kinds of splints improved clinical symptoms and complaints of bruxers. For joint vibrations in bruxers, hard and semi-soft splints are more beneficial than soft splints. Full article

The Mediterranean region is currently experiencing the effects of a climate crisis, marked by an increase in the frequency and intensity of drought events. Climate variability has led to prolonged periods of drought, even in areas not traditionally classified as arid. These events have significant impacts on water resources, agricultural productivity, and socioeconomic systems. This study investigates the evolution of meteorological, hydrological, and socioeconomic droughts using the Standardized Precipitation Index (SPI) at time scales of 3, 12, and 24 months in a Mediterranean region identified as particularly vulnerable to climate change. Observational data from local meteorological stations were used for the 1991–2020 baseline period. Future climate projections were derived from the MPI-ESM model under the RCP 4.5 and RCP 8.5 scenarios, extending to the year 2080. Data were aggregated on a 0.50° × 0.50° spatial grid and bias-corrected using linear scaling. The Kolmogorov–Smirnov test was applied to assess the statistical compatibility between observed and projected precipitation data. Results indicate a substantial decline in annual precipitation, with reductions of up to 20% under the RCP 8.5 scenario for the period 2051–2080, compared to the reference period. The frequency of severe and extreme drought events is projected to increase by 30–50% in several grid meshes, especially during summer. Conversely, altered weather patterns in other areas may increase the likelihood of flood events. This study identifies the grid meshes most vulnerable to drought, highlighting the urgent need for adaptive water management strategies to ensure agricultural sustainability and reduce the socioeconomic impacts of climate-induced drought. Full article

Background: This study aimed to examine the difference in blood lactate and oxygen saturation between monofin swimming with respiration and with breath-hold diving. The second aim was to investigate the difference between elite and intermediate breath hold-divers. Methods: This study included 15 freediving athletes (five females). Their chronological age was 25.9 ± 2.9 years, body mass 75.5 ± 11.9 kg, and height 180.2 ± 8.9 cm. The sample of variables included anthropometric indices, blood lactate, and oxygen saturation. The participants were measured during 100 m monofin horizontal swimming with respiration and breath-hold diving. Descriptive and inferential statistics were measured. The Kolmogorov–Smirnov (K-S) test was used to determine the normality of distribution. To determine the differences between the groups of participants, the t-test was used to determine the differences in anthropometric indices. Furthermore, to observe the differences between repeated measures, ANOVA with Fischer LSD test was used. Following that, the two-factor ANOVA analysis group (respiration/apnea) and group (intermediate/elite level)) was performed to determine the possible differences between groups in both conditions. Also, Cohen’s effect size was calculated to quantify the differences among the measurements. Results: The results show that the divers perceive significantly smaller levels of lactates during dives with respiration (intermediate, 2.44 ± 0.64 mmol/L; elite, 2.23 ± 0.34 mmol/L) than during apnea (intermediate, 6.06 ± 2.00 mmol/L; elite, 4.10 ± 0.66 mmol/L). Furthermore, intermediate freedivers tend to perceive significantly higher values. Conclusions: To conclude, it can be noted that apnea monofin diving elicits significantly higher lactate production in comparison with distance-matched swimming. Such findings imply the anaerobic nature of breath-holding diving. Apart from that, elite divers tend to show a lower accumulation of lactate. Such findings imply that elite-level divers can endure prolonged apneas with lower anaerobic metabolism use. Full article

Probability models are instrumental in a wide range of applications by being able to accurately model real-world data. Over time, numerous probability models have been developed and applied in practical scenarios. This study introduces the AAP-X family of distributions—a novel, flexible framework for continuous data analysis named after authors Aadil Ajaz and Parvaiz. The proposed family effectively accommodates both symmetric and asymmetric characteristics through its shape-controlling parameter, an essential feature for capturing diverse data patterns. A specific subclass of this family, termed the “AAP Exponential” (AAPEx) model is designed to address the inflexibility of classical exponential distributions by accommodating versatile hazard rate patterns, including increasing, decreasing and bathtub-shaped patterns. Several fundamental mathematical characteristics of the introduced family are derived. The model parameters are estimated using six frequentist estimation approaches, including maximum likelihood, Cramer–von Mises, maximum product of spacing, ordinary least squares, weighted least squares and Anderson–Darling estimation. Monte Carlo simulations demonstrate the finite-sample performance of these estimators, revealing that maximum likelihood estimation and maximum product of spacing estimation exhibit superior accuracy, with bias and mean squared error decreasing systematically as the sample sizes increases. The practical utility and symmetric–asymmetric adaptability of the AAPEx model are validated through five real-world applications, with special emphasis on cancer survival times, COVID-19 mortality rates and reliability data. The findings indicate that the AAPEx model outperforms established competitors based on goodness-of-fit metrics such as the Akaike Information Criteria (AIC), Schwartz Information Criteria (SIC), Akaike Information Criteria Corrected (AICC), Hannan–Quinn Information Criteria (HQIC), Anderson–Darling (A*) test statistic, Cramer–von Mises (W*) test statistic and the Kolmogorov–Smirnov (KS) test statistic and its associated p-value. These results highlight the relevance of symmetry in real-life data modeling and establish the AAPEx family as a powerful tool for analyzing complex data structures in public health, engineering and epidemiology. Full article

Background: Gastroesophageal reflux disease (GERD) is a chronic condition that causes an abrupt decrease in salivary pH in the oral cavity, which can lead to demineralization, erosion, hypersensitivity, functional impairment, and possibly fracture of dental elements. The aim of this clinical study is to compare two types of treatment in patients with dental erosion diagnosed with gastroesophageal reflux. Methods: Thirty patients were enrolled in this randomized clinical trial. Each patient underwent clinical evaluation and esophageal pH measurement, in order to diagnose GERD. After an initial examination and assessment by an experienced dentist, the Trial group (15 patients) was assigned to home treatment with a zinc hydroxyapatite-based toothpaste and a hydroxyapatite-based paste, while the Control group (15 patients) was assigned to home treatment with zinc hydroxyapatite-based toothpaste only. The following indices were measured: Basic Erosive Wear Examination Index (BEWE); Schiff Air Index (SAI); Plaque Index (PI); and Bleeding Score (BS). Each index was assessed at T0 during the first visit, one month (T1), three months (T2), six months (T3), nine months (T4), and 12 months (T5). The Kolmogorov–Smirnov test was used to analyze the normality of the data, while Friedman’s test followed by Dunn’s post hoc test were used to compare the two groups (significance threshold: p < 0.05). Results: The results showed no statistically significant change in the BEWE and SAI indexes (p > 0.05). However, an improvement in dentin sensitivity and BS was observed. Plaque control also improved. Conclusions: The results of this study indicate that the additional hydroxyapatite paste did not significantly improve the outcomes of the study in respect to hydroxyapatite toothpaste alone. However, there was an improvement in the oral health of GERD patients using hydroxyapatite-based remineralizing treatment in terms of oral and periodontal indices calculated. Full article

In this work, we introduce an edge centrality measure for the Helmholtz equation on metric graphs, a particular flow network, based on spectral edge energy density. This measure identifies influential edges whose removal significantly changes the energy flow on the network, as indicated by statistically significant p-values from the two-sample Kolmogorov–Smirnov test comparing edge energy densities in the original network to those with a single edge removed. We compare the proposed measure with eight vertex centrality measures applied to a line graph representation of each metric graph, as well as with two edge centrality measures applied directly to each metric graph. Both methods are evaluated on two undirected and weighted metric graphs—a power grid network adapted from the IEEE 14-bus system and an approximation of Poland’s road network—both of which are multigraphs. Two experiments evaluate how each measure’s edge ranking impacts the energy flow on the network. The results demonstrate that the proposed measure effectively identifies influential edges in metric graphs that significantly change the energy distribution. Full article

Under the rapid evolution of financial technology, traditional credit risk management paradigms relying on expert experience and singular algorithmic architectures have proven inadequate in addressing complex decision-making demands arising from dynamically correlated multidimensional risk factors and heterogeneous data fusion. This manuscript proposes an enhanced credit rating model based on an improved TabNet framework. First, the Kaggle “Give Me Some Credit” dataset undergoes preprocessing, including data balancing and partitioning into training, testing, and validation sets. Subsequently, the model architecture is refined through the integration of a multi-head attention mechanism to extract both global and local feature representations. Bayesian optimization is then employed to accelerate hyperparameter selection and automate a parameter search for TabNet. To further enhance classification and predictive performance, a stacked ensemble learning approach is implemented: the improved TabNet serves as the feature extractor, while XGBoost (Extreme Gradient Boosting), LightGBM (Light Gradient Boosting Machine), CatBoost (Categorical Boosting), KNN (K-Nearest Neighbors), and SVM (Support Vector Machine) are selected as base learners in the first layer, with XGBoost acting as the meta-learner in the second layer. The experimental results demonstrate that the proposed TabNet-based credit rating model outperforms benchmark models across multiple metrics, including accuracy, precision, recall, F1-score, AUC (Area Under the Curve), and KS (Kolmogorov–Smirnov statistic). Full article

The growing volume and complexity of gene expression data necessitate biologically meaningful and statistically robust methods for feature selection to enhance the effectiveness of disease diagnosis systems. The present study addresses this challenge by proposing a pipeline that integrates RNA-seq data preprocessing, differential gene expression analysis, Gene Ontology (GO) enrichment, and ensemble-based machine learning. The pipeline employs the non-parametric Kruskal–Wallis test to identify differentially expressed genes, followed by dual enrichment analysis using both Fisher’s exact test and the Kolmogorov–Smirnov test across three GO categories: Biological Process (BP), Molecular Function (MF), and Cellular Component (CC). Genes associated with GO terms found significant by both tests were used to construct multiple gene subsets, including subsets based on individual categories, their union, and their intersection. Classification experiments using a random forest model, validated via 5-fold cross-validation, demonstrated that gene subsets derived from the CC category and the union of all categories achieved the highest accuracy and weighted F1-scores, exceeding 0.97 across 14 cancer types. In contrast, subsets derived from BP, MF, and especially their intersection exhibited lower performance. These results confirm the discriminative power of spatially localized gene annotations and underscore the value of integrating statistical and functional information into gene selection. The proposed approach improves the reliability of biomarker discovery and supports downstream analyses such as clustering and biclustering, providing a strong foundation for developing precise diagnostic tools in personalized medicine. Full article