Search Results (35,803)

The computing network is a novel architecture that enables resource matching through the network. In distributed computing networks, computing resource management devices collect resource information and report it to network nodes. These nodes then broadcast the information to guide resource matching. One challenge is efficiently aggregating and disseminating computing resource information, as directly reporting fully multi-dimensional data can cause excessive overhead, while overly simplified aggregation may reduce matching accuracy. Existing aggregation methods typically rely on static resource information, overlooking the heterogeneity and dynamics of computing resources that arise from variations in resource capabilities and fluctuations over time, leading to suboptimal matching decisions. In response, this study proposes a dynamic resource aggregation method based on statistical capacity distribution. By modeling the capacity distribution of computing nodes, this method captures dynamic resource information, enabling more precise resource matching. Additionally, constructing resource groups and calculating representative distributions effectively compress the volume of data announcements. Experiments and data analysis demonstrate that, compared to static resource matching methods, the proposed method improves matching accuracy by $48\%$. Furthermore, it reduces announcement overhead by approximately $77.1\%$ compared to existing dynamic resource allocation methods. These findings provide an efficient solution for resource aggregation in distributed computing networks. Full article

According to statistics from the World Health Organization, traffic accidents are one of the leading causes of death among children and young people, and statistical indicators are even worse for the elderly population. Preventive measures require an approach that includes analyses of traffic infrastructure and regulations, users’ traffic behavior, and their interactions. In this study, a methodology based on traffic microsimulations was developed to select the optimal reconstruction solution for urban traffic infrastructure from the perspective of traffic safety. Comprehensive analyses of local traffic conditions at the selected location, infrastructural properties, and properties related to traffic users were carried out. The developed methodology was applied and tested at a selected unsignalized pedestrian crosswalk located in Osijek, Croatia, where traffic safety issues had been detected. Analyses of the possible solutions for traffic safety improvements were carried out, taking into account the specificities of the chosen location and the traffic participants’ behaviors, which were recorded and measured. The statistical analysis showed that children had shorter reaction times and crossed the street faster than the analyzed group of adult pedestrians, which was dominated by elderly people in this case. Using microsimulation traffic modeling (VISSIM), an analysis was conducted on the incoming vehicle speeds for both the existing and the reconstructed conflict zone solutions under different traffic conditions. The results exhibited a decrease in average speeds for the proposed solution, and traffic volume was detected to have a great impact on incoming speeds. The developed methodology proved to be effective in selecting a traffic solution that respects the needs of both motorized traffic and pedestrians. Full article

Afghanistan, a nation already challenged by geopolitical and environmental pressure, faces severe climate change impacts, evident through rising temperatures, decreasing precipitation, and reduced river discharge. These changes profoundly affect the country’s water resources, agriculture, ecosystems, and well-being. This study analyzes trends in mean annual temperature, precipitation, and river discharge across all five of Afghanistan’s river basins from 1980 to 2022, utilizing an innovative trend analysis (ITA), the Mann–Kendall (MK) test, and Sen’s slope (SS) estimator. Climate data were derived from the CRU TS.v4 and TerraClimate gridded datasets, while river discharge data were obtained from GloFAS-ERA5 datasets. The results reveal significant climate shifts, including a notable 1.5 °C rise in mean annual temperature, significantly higher than the global average of 1.3 °C, a 1.2 mm decrease in mean annual precipitation, and a −128 m³/s reduction in river discharge across all basins since 1980. Climate change impacts were particularly severe in the western part of the country. These findings underscore the strain on Afghanistan’s vulnerable water resources, with critical implications for agriculture and water management, highlighting the urgent need for adaptive strategies to mitigate climate-induced risks. Full article

Background: Dental pain is a significant public health issue globally and in Mexico, with substantial negative impacts on affected individuals. Objective: The objective of this study was to evaluate the prevalence of dental pain and its association with clinical, sociodemographic, and socioeconomic risk indicators in schoolchildren aged 6 to 12 years in four cities in Mexico. Material and Methods: A cross-sectional study was conducted on 500 children attending public schools in the cities of Pachuca, Tepatitlán, Toluca, and San Luis Potosí. A questionnaire was applied, and a clinical examination was performed on the schoolchildren. Self-reported dental pain within the 12 months preceding the study, categorized as 0 (no pain) and 1 (pain), was used as the dependent variable. For the statistical analysis, the Stata program was used, where a multivariate binary logistic regression model was applied. Results: The mean age was 8.92 ± 1.99 years; 50% were girls. The prevalence of dental pain was 34.0%. Independent variables associated (p < 0.05) with the experience of dental pain were as follows: age (OR = 0.81), having a car at home (OR = 0.77), a lower socioeconomic position (OR = 2.03), curative or specialized dental care (OR = 8.40), and self-reported dental and/or gingival disease (OR = 5.39). Conclusions: Dental pain is a significant health problem in schoolchildren aged 6 to 12 years in Mexico, with a prevalence of 34% in this study. Sociodemographic and socioeconomic factors, as well as clinical indicators, play an important role in the experience of dental pain. Inequalities in oral health were observed. There is a need for public health interventions to reduce this problem in vulnerable populations. Full article

This paper presents a new methodology for generating continuous statistical distributions, integrating the exponentiated odds ratio within the framework of survival analysis. This new method enhances the flexibility and adaptability of distribution models to effectively address the complexities inherent in contemporary datasets. The core of this advancement is illustrated by introducing a particular subfamily, the “Type 2 Gumbel Weibull-G family of distributions”. We provide a comprehensive analysis of the mathematical properties of these distributions, including statistical properties such as density functions, moments, hazard rate and quantile functions, Rényi entropy, order statistics, and the concept of stochastic ordering. To test the robustness of our new model, we apply five distinct methods for parameter estimation. The practical applicability of the Type 2 Gumbel Weibull-G distributions is further supported through the analysis of three real-world datasets. These real-life applications illustrate the exceptional statistical precision of our distributions compared to existing models, thereby reinforcing their significant value in both theoretical and practical statistical applications. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 19 (COVID-19), has resulted in dramatic changes in human lifestyles and the geographic distribution of populations. However, despite the unequal impact of COVID-19 across urban spaces, research on the association between socioeconomic disparities in the usage of various types of urban amenities during the pandemic is limited. Thus, this study utilized mobile phone data and land use/land cover (LULC) data to investigate COVID-19-induced changes in the hot spots of the daytime and nighttime populations of two districts in Seoul, South Korea: Gangnam (a high-income community) and Gangbuk (a low-income community). First, the differences between Gangnam and Gangbuk in the LULC and mobile phone data, before and during the pandemic, were statistically analyzed by age. Second, the areas with significantly increased mobile phone-based populations during COVID-19 were identified using a hot spot analysis method and Welch’s t-test. This study identified that there were significant disparities in the use of green spaces during the pandemic, with a higher percentage of the mobile phone-based population in Gangnam than Gangbuk. Youths and adults in Gangnam were more likely to visit schools and enjoy physical activities in forests and open spaces during the pandemic, whereas there was no such increase in Gangbuk. The findings contribute to the understanding of the impact of COVID-19 on human behaviors and socioeconomic disparities in the quality of urban life. Full article

The gut microbiota plays a fundamental role in the host’s energy metabolism and the development of metabolic diseases such as arterial hypertension, insulin resistance, and atherosclerosis. Our study aimed to investigate the potential role of the gut microbiota in arterial hypertension among individuals of the Kazakh population without insulin resistance. 16S rRNA gene sequencing of faecal samples from 197 Kazakh subjects was performed. Preliminary binary comparisons of the faecal microbiota composition depending on the presence of arterial hypertension and insulin resistance revealed statistically significant differences in the abundance of the phylum Firmicutes. Logistic regression analysis showed that only the phylum Firmicutes influenced hypertension risk in individuals without insulin resistance after adjusting for age, sex, BMI, fasting glucose, triglycerides, and triglyceride–glucose index. The higher the abundance of the phylum Firmicutes in faeces, the greater the risk of arterial hypertension (OR = 1.064 [95% CI 1.005–1.125]). Correlation analysis revealed a negative association between the abundance of the phylum Firmicutes and the triglyceride–glucose index, primarily driven by triglyceride levels. These findings suggest the potential role of the gut microbiota, especially the phylum Firmicutes, in the development of hypertension in individuals without insulin resistance. Full article

Background: Lasers from the erbium family have been investigated to activate irrigation with sodium hypochlorite (NaOCl), improving the disinfection depth of the dentinal tubules of the root canal walls during root canal treatment. However, the possibility of laser-activated irrigation (LAI) in retro-cavity preparation has not been investigated to the date. The aim of our experimental study is to evaluate the efficacy of NaOCl gel penetration inside the dentinal tubules when activated during retro-cavity preparation, comparing passive ultrasonic activation (PUI) and Er,Cr:YSGG LAI. Materials and Methods: Fifty extracted mature single-root human teeth were divided into four groups (control, PUI, and two LAI groups with different NaOCl concentrations). After conventional endodontic treatment and root end resection, NaOCl gel (impregnated with rhodamine dye for confocal laser scanning microscopy (CLSM) analysis) was applied and activated according to the study group. The penetration index and mean penetration length were measured using computer software. Results: Both penetration index and mean penetration length were found to have increased in the PUI group compared to the control samples. However, LAI had a better penetration that was statistically significant compared to both the PUI and control groups. The difference in NaOCl concentration in the laser groups did not affect the penetration values. Conclusions: Within the limitations of our in vitro study using NaOCl gel activation in the retro-cavity after apicectomy, Er,Cr:YSGG LAI significantly enhanced NaOCl gel penetration capacity compared to PUI, regardless of its concentration. LAI can enhance its penetration in a safe way, avoiding its extrusion to the surrounding periapical tissues. Full article

In recent years, reservoir flood control and dam safety have faced severe challenges due to changing environmental conditions and intense human activities. There has been a significant increase in the proportion of dam breaks caused by floods exceeding reservoir design levels. Dam breaks have periodically occurred due to flood overtopping, threatening people’s lives and properties. This highlights the importance of describing the challenges encountered in reservoir flood risk prevention and control under extreme climatic conditions and proposing strategies to safeguard reservoirs against floods and to protect downstream communities. This study conducts a statistical analysis of dam breaks resulting from floods exceeding reservoir design levels, revealing new risk indicators in these settings. The study examines recent representative engineering cases involving flood risks and reviews research findings pertaining to reservoir flood risks under extreme climatic conditions. By comparing flood prevention standards at typical reservoirs and investigating the problems and challenges associated with current standards, the study presents the challenges and strategies associated with managing flood risks in reservoirs under extreme climatic conditions. The findings show that the driving forces and their effects shaping flood risk characteristics in specific regions are influenced by atmospheric circulation and vegetative changes in underlying surfaces or land use. There is a clear increasing probability of dam breaks or accidents caused by floods exceeding design levels. Most dam breaks or accidents occur in small and medium-sized reservoirs, due to low flood control standards and poor management. Therefore, this paper recommends measures for improving the flood prevention capacity of these specific types of reservoirs. This paper proposes key measures to cope with floods exceeding reservoir design levels, to supplement the existing standard system. This includes implementing an improved flood standard based on dam risk level and the rapid reduction in the reservoir water level. To prevent breaks associated with overtopping, earth–rock dams should be designed to consider extreme rainfall events. More clarity is needed in the execution principles of flood prevention standards, and the effectiveness of flood calculations should be studied, adjusted, and validated. The research results provide better descriptions of flood risks in reservoirs under extreme climatic conditions, and the proposed strategies have both theoretical and practical implications for building resilience against flood risks and protecting people’s lives and properties. Full article

Background: Diabetic retinopathy (DR) is one of the leading causes of blindness among diabetic patients, particularly in areas with an increase in diabetes epidemics, such as Saudi Arabia. Notwithstanding the significant public health implications, data on the prevalence and risk factors of DR in Saudi Arabia are few and scattered, limited to certain geographic areas. Our study objective is to conduct a systematic review of the literature and a meta-analysis of the prevalence and predictors for DR in Saudi Arabia, within both type 1 and type 2 diabetes. Methods: A systematic review and meta-analysis were constructed according to PRISMA guidelines. We searched PubMed, Embase, Web of Science, and Google Scholar electronic databases for studies published from 2000–2023. Any study related to the prevalence of diabetic retinopathy in T1DM or T2DM among adult patients aged ≥18 years that was conducted in Saudi Arabia was included. Pooling prevalence estimates were calculated using a random-effects model, and heterogeneity across the studies was tested by the I² statistic and Cochran’s Q test. Results: A total of 11 studies published between 2006 and 2019 met the inclusion criteria, with sample sizes ranging from 99 to over 50,000 participants. The overall pooled prevalence of DR was estimated to be 31% (95% CI: 24–39%), with substantial heterogeneity observed across studies (I² = 99%). Prevalence estimates ranged from 16.7% to 69.8% and were influenced by variables such as study design, duration of diabetes, and glycemic control. Among individuals with type 2 diabetes, the pooled prevalence was 24% (95% CI: 20–28%). Poor glycemic control and longer diabetes duration were consistently identified as significant predictors of DR, while other factors, such as obesity and hypertension, were also associated with an increased risk of DR. Conclusions: The high prevalence of DR in Saudi Arabia highlights the critical need for focused public health initiatives, especially among those with type 2 diabetes. To minimize the effects of DR, early intervention, routine DR screening programs, and optimal diabetes control are essential. The increasing prevalence of DR in Saudi Arabia requires careful consideration of healthcare policy and resource allocation, which is made possible by our results. Full article

Objectives: This study investigated the characteristics of adolescent-onset epilepsy (AOE) and conducted genetic tests on a cohort of 76 Korean patients to identify variants and expand the spectrum of mutations associated with AOE. Methods: Clinical exome sequencing after routine karyotyping and chromosomal microarray was performed to identify causative variants and expand the spectrum of mutations associated with AOE. Results: In cases of AOE without neurodevelopmental delay (NDD), this study identified four likely pathogenic variants (LPVs) or variants of uncertain significance (VUS) and two copy number variations (CNVs). To explore the unique features of AOE; clinical manifestations were compared between patients with and without NDD. The analysis revealed statistically significant differences in the prevalence of males and the yield of genetic testing results. AOE without NDD had a lower prevalence in males (49%) compared to AOE with NDD (60%) (p = 0.007). Genetic alterations: AOE with NDD exhibited a higher frequency of genetic alterations (35%) compared to AOE without NDD (12%) (p = 0.011). Thorough evaluation of AOE can be particularly challenging in adolescent patients. Some individuals may display genetic variations due to a phenomenon known as locus heterogeneity, where different genetic causes lead to similar clinical presentations. Conclusions: Implementing a robust genetic workflow is crucial for accurately diagnosing AOE, even in cases with complex genetic underpinnings. This study underscores the importance of genetic testing as an essential diagnostic tool for AOE. Identifying genetic variants and understanding their clinical correlations can aid in improving diagnostic accuracy and optimizing treatment approaches for adolescent patients with epilepsy. Full article

An environmentally compatible and less costly (greener) analytical method for the digestion of bone meal samples using microwave-assisted dilute nitric acid (HNO₃) was developed and optimized. The method, employing a mixture of 1 mL concentrated HNO₃ and 4 mL of deionized water, offered a comparable performance to the conventional method using 5 mL of concentrated HNO₃. The accuracy of the method was validated by using certified reference material NIST 1486 (Bone Meal); percentage recoveries were within ±15% for all eight certified elements. Statistical analysis revealed no significant differences (p > 0.05) in percentage recoveries between the green and conventional methods for all elements except calcium. The greenness of the developed method was evaluated by using the analytical Eco-Scale, achieving a score of 87, categorizing it as an “excellent green analysis” method. This research highlights the potential for adopting greener practices in trace element analysis that reduce the environmental impact and safety risks associated with concentrated acids. Full article

Since the 1950s, the screening of the body volatilome has proven to be a powerful tool for preventing diseases from spreading. Following the COVID-19 crisis, several studies began investigating the connection between viruses and the body volatilome, gradually identifying potential biomarkers, which varied depending on the study. To try to elucidate potential sources of inconsistency in biomarker findings, we decided to set up a study taking into consideration the factors often overlooked in previous studies. The VOCs constituting the body volatilomes of 40 COVID-19 patients and 13 healthy subjects were sampled by using PowerSorb^® as the sorbent phase. Thermodesorption, followed by comprehensive two-dimensional gas chromatography combined with time-of-flight mass spectrometry (TD-GC×GC/TOF MS), was utilized for the analysis. A non-targeted biomarker research methodology compared Covid(+) and Covid(−) chromatograms, assessing statistical significance and peak area changes. Out of the 25 compounds highlighted, 13 associated with cosmetic products were excluded, and 8 linked to air pollution in urban settings were also excluded. Finally, after having quantitatively evaluated the potential sources of the compounds (cosmetic or environmental), 4 compounds remained and their relevance was assessed using ROC curves. Among them, hexanoic acid, 2-ethyl- identification was confirmed with standard and led to an area-under-the-curve value of 92%. More in-depth studies are needed to investigate the specificity of the biomarker in relation to COVID-19, but the strategy of this study shows how to avoid obtaining data that are biased by exogenous factors. Full article

In this paper, nonlinear system identification using Bayesian network has been implemented to discover open-loop lateral-directional aerodynamic model parameters of an agile aircraft using a grey box modelling structure. Our novel technique has been demonstrated on simulated flight data from an F-16 nonlinear simulation of its Flight Dynamic Model (FDM). A mathematical model has been obtained using time series analysis of a Box–Jenkins (BJ) model structure, and parameter refinement has been performed using Bayesian mechanics. The aircraft nonlinear Flight Dynamic Model is adequately excited with doublet inputs, as per the dictates of its natural frequency, in accordance with non-parametric modelling (Finite Impulse Response) estimates. Time histories of optimized doublet inputs in the form of aileron and rudder deflections, and outputs in the form of roll and yaw rates are recorded. Dataset is pre-processed by implementing de-trending, smoothing, and filtering techniques. Blend of System Identification time-domain grey box modelling structures to include Output Error (OE) and Box–Jenkins (BJ) Models are stage-wise implemented in multiple flight conditions under varied stochastic models. Furthermore, a reduced order parsimonious model is obtained using Akaike information Criteria (AIC). Parameter error minimization activity is conducted using the Levenberg–Marquardt (L-M) Algorithm, and parameter refinement is performed using the Bayesian Algorithm due to its natural connection with grey box modelling. Comparative analysis of different nonlinear estimators is performed to obtain best estimates for the lateral–directional aerodynamic model of supersonic aircraft. Model Quality Assessment is conducted through statistical techniques namely: Residual Analysis, Best Fit Percentage, Fit Percentage Error, Mean Squared Error, and Model order. Results have shown promising one-step model predictions with an accuracy of 96.25%. Being a sequel to our previous research work for postulating longitudinal aerodynamic model of supersonic aircraft, this work completes the overall aerodynamic model, further leading towards insight to its flight control laws and subsequent simulator design. Full article

Knee arthroplasty, commonly performed to treat osteoarthritis, necessitates precise surgical techniques for optimal outcomes. The introduction of systems such as the Persona Knee System (Zimmer Biomet, Warsaw, IN, USA) has revolutionized knee arthroplasty, promising enhanced precision and better patient outcomes. This study investigates the application of robotic planning specifically in knee prosthetic surgeries, with a focus on Persona Knee System prostheses. We conducted a retrospective analysis of 300 patients who underwent knee arthroplasty using the Persona Knee System between January 2020 and November 2023, including demographic data, surgical parameters, and preoperative imaging. Robotic planning was employed to simulate surgical procedures. The planning process integrated preoperative imaging data from a specific program adopted for conducting digital preoperative planning, and statistical analyses were conducted to assess correlations between patient characteristics and surgical outcomes. Out of 300 patients, 85% presented with minor deformities, validating the feasibility of robotic planning. Robotic planning demonstrated precise prediction of optimal arthroplasty sizes and alignment, closely aligning with preoperative imaging data. This study highlights the potential benefits of robotic planning in knee arthroplasty surgeries, particularly in cases with minor deformities. By leveraging preoperative imaging data and integrating advanced robotic technologies, surgeons can improve precision and efficacy in knee arthroplasty. Moreover, robotic technology allows for a reduced level of constraint in the intraoperative choice between Posterior-Stabilized and Constrained Posterior-Stabilized liners compared with an imageless navigated procedure. Full article