Search Results (6,866)

Background/Objectives: Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by progressive impairment of neuronal transmission due to focal demyelination. The most common form is RRMS (relapsing-remitting multiple sclerosis), which, under the influence of certain factors, can progress to SPMS (secondary progressive multiple sclerosis). Our study aimed to validate the criteria proposed by a working group of the Romanian Society of Neurology versus the criteria proposed by a group of experts from Spain, Karolinska, and Croatia concerning the progression from RRMS to SPMS. Methods: This was done by gathering epidemiological data (age, gender) and by applying clinical tests such as the 9HPT (9-hole peg test), 25FWT (25-foot walk test), and EDSS (expanded disability status scale) tests and the SDMT test (symbol digit modalities test). The present research is a cohort study that included a number of 120 patients diagnosed with MS according to the McDonald Diagnostic Criteria 2017. The study was carried out between January 2023 and April 2024, including patients hospitalized in the Neurology Clinic of the Clinical Rehabilitation Hospital from Iasi, Romania. The data were collected at baseline (T0) and at a 12-month interval (T1). Results: The statistical analysis was conducted using Kaiser–Meyer–Olkin analysis, which indicated a value of 0.683, thus validating the clinical tests used. The correlation matrix and the linear regression for all the tests showed highly significant statistical results. Furthermore, the ROC curve analysis of the criteria suggested by the working group of the Romanian Society of Neurology demonstrated that the EDSS, 9HPT, and 25FWT are highly sensitive in diagnosing SPMS, an opinion that is shared with the Spanish experts, but not with the Karolinska expert panel. Using the criteria given by the Croatian expert group in the ROC curve analysis showed that only the EDSS was strongly significant for the progression to the SPMS phase. Conclusions: In conclusion, all clinical methods used demonstrated that they are valid and can contribute to identifying patients with an increased risk of progression. The model proposed by the Romanian Society of Neurology working group is similar to other countries’ expert opinions and can be used to detect the risk of disease progression and establish a more tailored therapeutic management of SPMS. Full article

Background: Low back pain is common. For patients with mechanic or non-specific chronic LBP (cLBP), the current guidelines suggest conservative, nonpharmacologic treatment as a first-line treatment. Among the available strategies, physiotherapy represents a common option offered to patients presenting with cLBP. The present systematic review investigates the prognostic factors of patients with mechanic or non-specific cLBP undergoing physiotherapy. Methods: In September 2024, the following databases were accessed: PubMed, Web of Science, Google Scholar, and Embase. All the randomised controlled trials (RCTs) which evaluated the efficacy of a physiotherapy programme in patients with LBP were accessed. All studies evaluating non-specific or mechanical LBP were included. Data concerning the following PROMs were collected: the pain scale, Roland Morris Disability Questionnaire (RMQ), and Oswestry Disability Index (ODI). A multiple linear model regression analysis was conducted using the Pearson Product–Moment Correlation Coefficient. Results: Data from 2773 patients were retrieved. The mean length of symptoms before the treatment was 61.2 months. Conclusions: Age and BMI might exert a limited influence on the outcomes of the physiotherapeutic management of cLBP. Pain and disability at baseline might represent important predictors of health-related quality of life at the six-month follow-up. Further studies on a larger population with a longer follow-up are required to validate these results. Full article

Agroforestry is promoted as a practice at the crossroads of sustainability and productivity objectives; however, many agroforestry programmes have had mixed effects due to a lack of understanding of the compatibility of the species supplied to farmers with cocoa and a failure to take account of their knowledge in designing the programmes. This paper, therefore, examines the effects of socio-economic and agroforestry factors on cocoa yields in Côte d’Ivoire, West Africa. The data used come from surveys of 150 farmers in three areas of the country: Bonon, Soubré and Biankouma. The choice of these areas was based on an east–west gradient, reflecting the evolution of the cocoa loop. The Bayesian Information Criterion method and multiple linear regression were applied to identify the species and their relationship with yield. The results showed that certain species, such as Citrus sp., Cordia senegalensis, Isoberlinia doka, Morinda lucida, Morus mesozygia and Raphia hookeri increased in yield; on the other hand, Anthonotha manii was found to reduce in yield. Finally, labour and insecticides contributed to yield increases. The statistical analysis can be supplemented with agronomic and ecological analyses to improve species management on cocoa farms. Full article

(1) Background: Worldwide, refugees may have some difficulties in accessing healthcare services. However, little is known about the factors that may predict the level of accessibility to the public healthcare system in the host countries. (2) Aim: To examine the level of accessibility of Syrian refugees to the public healthcare system in Jordan and further to identify the prediction of socioeconomic factors and barriers to healthcare access. (3) Methods: A cross-sectional study was conducted with a convenient sample of 356 Syrian refugees residing outside camps (Irbid, Ajloun, and Jarash). Data were collected using the Access to Healthcare Services Scale instrument (adopted from the Canadian Community Health Survey), which is composed of 2 sections: the general access scale (8 items) and the difficulties scale (20 items). One-way ANOVA test and independent t-test were used to examine epidemiological correlations among variables, whereas a hierarchical linear regression model was used to examine the predictability of socioeconomic factors and barriers to overall access to the public healthcare system by exploring the incremental impact of additional predictors. (4) Results: the mean age of the 356 participants was 35.22 years old, 56.5% were female, 67.4% were married, most of them 46.1% have secondary education, and non-employed 69.9%. Significant associations were observed among participants with different marital status (p < 0.001), educational level (mean 11.85 vs. 19.85, p < 0.001), working status (15.47 vs. 17.93, p < 0.001), family household number (16.42 vs. 17.0, p < 0.001), and health insurance (none: 15.50 vs. governmental 24.50, p < 0.001). Multivariate analysis revealed that the most important factors that may predict the overall access to healthcare services were: family monthly income (beta −0.19, p < 0.001), household family number (beta 0.17, <0.001), health insurance (beta −0.09, p = 0.047), and barriers (beta −0.43, <0.001), even after adjusting for potential confounding effects: sex, age, educational level, and place of residence. (5) Conclusions: Our findings indicate that socioeconomic factors and barriers may considerably predict overall access to public healthcare in Jordan. It is crucially important, therefore, for the Jordanian government and international organizations to create and develop strategic plans and programs that enhance refugees’ access to health services, positively impacting their health and wellness. Full article

Objectives: This study aimed to investigate changes in refraction error in myopic school-age children during the COVID-19 pandemic. Methods: The data of 825 myopic children aged 7–18 years were retrospectively screened from the hospital data access system. The cycloplegic prescriptions of the patients in 2018, 2019, 2020, and 2021 were recorded. The patients were divided into three groups according to their ages: ≤10 years (Group A), 11–14 years (Group B), and ≥15 years (Group C). The mean refraction values and annual progression values were compared between the years and age groups. Results: The mean age of the patients was 13.8 ± 3.17 years. Statistical analysis for the overall sample indicated that the annual myopia progression significantly differed between 2018 and 2021 (−0.42 ± 0.37 and −0.53 ± 0.47, respectively) (p < 0.001), and there was also a significant difference in myopia progression observed in all years in the younger age group (−0.34 ± 0.44 for 2018, −0.50 ± 0.49 for 2019, and −0.76 ± 0.59 for 2020). The highest progression (−0.76 ± 0.59) was determined in the younger age group in 2020. Linear regression analysis showed a negative correlation between myopia progression from 2020 to 2021 and age (B = 0.049 and p < 0.001). Conclusions: Myopia progression has increased in school-age children during COVID-19, with the younger age group being more affected. During the COVID-19 pandemic, myopia progression in younger children has increased statistically significantly. Thus, at times when distance learning is required, it would be appropriate to plan by taking into account the myopia progression of children. Full article

This study examines the predictability of the last 30 min of intraday stock price movements within the US financial market. The analysis encompasses several potential explanatory variables, including returns from each 30 min intraday trading session, overnight returns, the federal reserve fund rate decision days and the subsequent three days, the US dollar index, month effects, weekday effects, and market volatilities. Market-adaptive trading strategies are developed and backtested on the basis of the study’s insights. Unlike the commonly employed multiple linear regression methods with Gaussian errors, this research utilizes a Bayesian linear regression model with Student-t error terms to more accurately capture the heavy tails characteristic of financial returns. A comparative analysis of these two approaches is conducted and the limitations inherent in the traditionally used method are discussed. Our main findings are based on data from 2007 to 2018. We observed that well-studied factors such as overnight effects and intraday momentum have diminished over time. Some other new factors were significant, such as lunchtime returns during boring days and the tug-of-war effect over the days after a federal fund rate change decision. Ultimately, we incorporate findings derived from data spanning 2022 to 2024 to provide a contemporary perspective on the examined components, followed by a discussion of the study’s limitations. Full article

This study investigates the impact of building insulation standards on indoor thermal environments and the risk of heat-related illnesses during heatwaves in South Korea. Indoor temperatures were measured in residential buildings located in Chuncheon and Gwangju during the 2022 heatwave, with outdoor temperature data sourced from the Korea Meteorological Administration. Probability distribution fitting was used to estimate the likelihood of indoor temperatures exceeding the critical threshold of 27 °C. Additionally, a linear regression analysis was conducted to examine the relationship between the probability of exceeding the threshold and heat-related illness data from 2017 to 2023 provided by the Korea Disease Control and Prevention Agency. The findings reveal significant variations in indoor thermal conditions during heatwaves, influenced by factors such as building type, year of construction, and climate region, which affect the thermal insulation performance. Buildings with a lower thermal insulation performance were associated with higher indoor temperatures, increasing the likelihood of exceeding the critical threshold and contributing to a higher incidence of heat-related illnesses, particularly in provincial non-metropolitan areas. These results underscore the need for region-specific building insulation standards that address both winter energy efficiency and summer heatwave resilience. Enhancing thermal insulation in vulnerable regions could significantly reduce the risk of heat-related illnesses and improve public health resilience to extreme heat events. Full article

This study aimed to evaluate the association of TCs (triclosan (TCS) and triclocarban) exposure with T2DM and glucose metabolism-related indicators and the mediating effect of SOCS3 methylation on their associations. A total of 956 participants (330 T2DM and 626 controls) were included in this case-control study. Logistic regression and generalized linear models were used to assess the effect of TCs on T2DM and glucose metabolism-related indicators. The dose–response relationship between TCs and T2DM was analyzed by restricted cubic spline. Finally, after evaluating the association between TCs and SOCS3 methylation levels, the mediating effect of SOCS3 methylation on the TC−associated T2DM was estimated. Each 1-unit increase in TCS levels was associated with a 13.2% increase in the risk of T2DM (OR = 1.132, 95% CI: 1.062, 1.207). A linear dose–response relationship was found between TCS and T2DM. TCS was negatively associated with Chr17:76356190 methylation. Moreover, mediation analysis revealed that Chr17:76356190 methylation mediated 14.54% of the relationship between TCS exposure and T2DM. Exposure to TCS was associated with a higher prevalence of T2DM. SOCS3 methylation partially mediated the association of TCS with T2DM. Our findings may provide new insights into the treatment of T2DM, and the study of the biological mechanisms of T2DM. Full article

In this research, the impact of basalt fiber reinforcement on the unconfined compressive strength of clay soils was experimentally analyzed, and the collected data were utilized in an artificial neural network (ANN) to predict the unconfined compressive strength based on the basalt fiber reinforcement ratio and length. For this purpose, two different lengths of basalt fiber (6 mm and 12 mm) were added to unreinforced bentonite clay at ratios of 0%, 1%, 2%, 3%, 4%, and 5%, and unconfined compressive tests were performed on the prepared reinforced clay samples to determine the unconfined compressive strength (q_u) values. The evaluation of the obtained experimental results was carried out by creating ANN models. To validate the prediction capabilities of the ANN, a comparative analysis was performed using linear regression, support vector machines, and Gaussian process regression models. Ultimately, a five-fold cross-validation technique was employed to objectively evaluate the overall performance of the model. The evaluations revealed that the ANN model predictions using data obtained from experimental studies showed the highest accuracy and were in close agreement with the experimental results. Full article

Statistical hypothesis testing, as formalized by 20th century statisticians and taught in college statistics courses, has been a cornerstone of 100 years of scientific progress. Nevertheless, the methodology is increasingly questioned in many scientific disciplines. We demonstrate in this paper how many of the worrisome aspects of statistical hypothesis testing can be ameliorated with concepts and methods from evidential analysis. The model family we treat is the familiar normal linear model with fixed effects, embracing multiple regression and analysis of variance, a warhorse of everyday science in labs and field stations. Questions about study design, the applicability of the null hypothesis, the effect size, error probabilities, evidence strength, and model misspecification become more naturally housed in an evidential setting. We provide a completely worked example featuring a two-way analysis of variance. Full article

Biogas has improved due to technological advancements, environmental awareness, policy support, and research innovation, making it a more cost-effective and environmentally friendly renewable energy source. The Generalized Linear Model (GLM) was employed to examine the relationship between purchased and generated energy from 2007 to 2023. Metrics such as deviance, log likelihood, and dispersion phi were examined to assess model fit. The Mann–Kendall test was utilized to detect trends in energy datasets. Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) reduction was significant, exceeding 97% from 2014 to 2023. However, treated sewage displayed limited susceptibility to biological degradation, with COD to BOD5 ratios increasing from 2.28 to 6.59 for raw sewage and from 2.33 to 7.05 for treated sewage by 2023. Additionally, the efficiency of sewage purification processes was calculated, and multivariate regression analysis was conducted on gas composition data. Principal Coordinate Ordination (PCO) and k-means clustering were used for dimensionality reduction and biogas component clustering, respectively. This research showed that biogas from the waste water treatment process can be used, particularly in methane production. Technological advancements have made biogas production more efficient, enhancing energy generation within a circular economy framework. Full article

Background: Lactation is known to improve insulin resistance, but this phenomenon remains poorly understood. Our goal was to evaluate whether subclinical inflammation could mediate the association between breastfeeding (BF) and improvement in glucose metabolism and markers of insulin resistance (MIRs) in the postpartum. Methods: A total of 95 adult women (≥18 years) with a BMI ≥ 25 kg/m² from the outpatient clinic of the Federal University of São Paulo were followed from early pregnancy until 60 to 180 days postpartum. The patients were divided based on their BF status: BF and non-BF groups. A latent variable termed SubInf was created incorporating inflammation-related biomarkers: adiponectin, E-selectin, branched-chain amino acids, zonulin, copeptin, and lipopolysaccharides. The association of BR with MIRs in the postpartum was evaluated through linear regression analysis, and mediation analysis was performed to evaluate the role of SubInf in this association. Results: The groups were similar regarding gestational diabetes mellitus (GDM) prevalence, pre-gestational BMI, caloric intake, physical activity, and postpartum weight loss. The BF group presented lower levels of triglycerides (TGs), fasting glucose, fasting insulin, TG/HDLcholesterol ratio (TG/HDL), TyG index, and HOMA-IR compared to the non-BF group. A linear regression analysis adjusted for scholarity, parity, pre-gestational BMI, GDM, weight gain during pregnancy, and mode of delivery revealed an inverse association between BF and fasting glucose [−6.30 (−10.71 to −1.89), p = 0.005), HOMA-IR [−0.28 (−0.50 to −0.05), p = 0.017], TyG index [−0.04 (−0.06 to −0.01), p = 0.002], and TG/HDL ratio [−0.23 (−0.46 to −0.01), p = 0.001]. In the mediation analysis, SubInf did not mediate the indirect effect of BF on MIRs. Conclusions: In overweight and obese women, an association between BF and improvement in MIRs in the postpartum was seen, corroborating that BF should be stimulated, especially in these cardiometabolic high-risk women. Subclinical inflammation did not seem to mediate this association. Full article

Traditional computational methods for pressurized water reactors are unable to handle dispersed fuel particles as the double heterogeneity and the direct volumetric homogenization can result in significant errors. In contrast, reactivity-equivalent physical transformation techniques offer high precision for addressing the double heterogeneity introduced by dispersed fuel particles. This approach converts the double heterogeneity problem into a single heterogeneity problem, which is then subsequently investigated by using the conventional pressurized water reactor computational procedure. However, it is currently empirical and takes a lot of time to obtain the right k_∞. In this paper, we train the RPT model by using the existing dataset of plate-dispersed fuel and rod-dispersed fuel by a machine learning method based on a linear regression model, and we then use the new data to make predictions and derive the corresponding similarity ratios. The burnup verification, density verification, fission rate verification, and neutron energy spectrum analysis are calculated through the OpenMC program. For plate-type fuel elements, the method maintains an accuracy within 200 pcm during depletion, with deviations in the ²³⁵U density and ²³⁵U fission rate within 0.1% and neutron energy spectrum errors within 6%. For rod-type fuel elements, the method maintains an accuracy within 100 pcm during depletion, with deviations in ²³⁵U and ²³⁹Pu density within 1.5% and neutron energy spectrum errors within 1%. The numerical validation indicates that the reactivity-equivalent physical transformation method based on the linear regression model not only greatly improves the computational efficiency, but also ensures a very high accuracy to deal with double heterogeneity in nuclear reactors. Full article

This paper presents a comprehensive fault diagnosis approach for a delta robot utilizing advanced feature extraction and classification techniques. A four-arm delta robot prototype is designed in SolidWorks for realistic fault analysis. Two case studies investigate faults through control effort and vibration signals, with control effort detecting motor and encoder faults, while vibration signals identify bearing faults. This study compares time-domain signal features and wavelet scattering networks, applied by classification algorithms including wide neural networks (WNNs), efficient linear support vector machine (ELSVM), efficient logistic regression (ELR), and kernel naive Bayes (KNB). Results indicate that a WNN, using wavelet scattering features ranked by one-way anova, is optimal due to its consistency and reliability, while these features enhance computational efficiency by reducing classifier size. Sensitivity analysis demonstrates the classifier’s capacity to detect untrained faults, highlighting the importance of effective feature extraction and classification methods for fault diagnosis in complex robotic systems. This research significantly contributes to fault diagnosis in delta robots and lays the groundwork for future studies on fault tolerance control and predictive maintenance planning. Future work will focus on the physical implementation of the delta robot in laboratory settings, aiming to improve operational efficiency and reliability in industrial applications. Full article

Background: Childhood obesity is a major public health challenge in the 21st century, and diet is one of the key modifiable factors in its prevention. This study examined the link between dietary patterns of children and general and central obesity, including the role of C-reactive protein (CRP). Methods: This study enrolled 2413 children aged 9–17. Anthropometric measurements, CRP levels, and dietary data were collected. Factor analysis identified dietary patterns, and logistic regression examined the association between CRP levels and childhood obesity. Multiple linear regression determined the correlation between dietary patterns and CRP. Mediation analysis assessed the role of CRP in the link between dietary patterns and childhood obesity. Results: Three dietary patterns were identified. The rice and meat pattern was significantly correlated to the risk of childhood obesity (OR = 1.166, 95%CI: 1.000, 1.359 for general obesity; OR = 1.215, 95%CI: 1.071, 1.377 for central obesity). CRP was positively correlated with childhood obesity risk (OR = 2.301, 95%CI: 1.776, 2.982 for general obesity; OR = 2.165, 95%CI: 1.738, 2.697 for central obesity). The fruit and vegetable pattern was inversely related to CRP (β= −0.059, 95%CI: −0.081, −0.036), while the snack pattern was positively correlated (β= 0.043, 95%CI: 0.020, 0.065). CRP had a suppressive effect on the association between the fruit and vegetable pattern and snack pattern with childhood obesity. Conclusions: This study revealed the rice and meat pattern as a risk factor for childhood obesity, and cross-sectional evidence linked the fruit and vegetable pattern and snack pattern to childhood obesity risk, mediated by CRP. Full article