Search Results (18,854)

Congenital cataracts (CCs) are a leading cause of preventable childhood blindness, with genetic factors playing a crucial role in their etiology. Nance–Horan syndrome (NHS) is a rare X-linked dominant disorder associated with CCs but is often underdiagnosed due to variable expressivity, particularly in female carriers. Objective: This study aimed to explore the genetic landscape of CCs in a Swiss cohort, focusing on two novel NHS and one novel GJA8 variants and their phenotypic presentation. Methods: Whole-exome sequencing (WES) was conducted on 20 unrelated Swiss families diagnosed with CCs. Variants were analyzed for pathogenicity using genetic databases, and segregation analysis was performed. Clinical data, including cataract phenotype and associated systemic anomalies, were assessed to establish genotype–phenotype correlations. Results: Potentially pathogenic DNA sequence variants were identified in 10 families, including three novel variants, one in GJA8 (c.584T>C) and two NHS variants (c.250_252insA and c.484del). Additional previously reported variants were detected in CRYBA1, CRYGC, CRYAA, MIP, EPHA2, and MAF, reflecting genetic heterogeneity in the cohort. Notably, NHS variants displayed significant phenotypic variability, suggesting dose-dependent effects and X-chromosome inactivation in female carriers. Conclusions: NHS remains underdiagnosed due to its variable expressivity and the late manifestation of systemic features, often leading to misclassification as isolated CC. This study highlights the importance of genetic testing in unexplained CC cases to improve early detection of syndromic forms. The identification of novel NHS and GJA8 variants provides new insights into the genetic complexity of CCs, emphasizing the need for further research on genotype–phenotype correlations. Full article

Computational Thinking (CT) has been an important concept for the computer science education community in the last 20 years. In this work we performed a systematic review of the literature regarding the computational thinking of children from kindergarten to primary school. We compiled a large dataset of one hundred and twenty (120) studies from the literature. Through analysis of these studies, we tried to reveal important insights and draw interesting and valid conclusions. We analyzed various qualitative and quantitative aspects of the studies, including the sample size, the year of publication, the country of origin, the studies’ design and duration, the computational tools used, and so on. An important aspect of the work is to highlight differences between different study designs. We identified a total of 120 studies, with more than half of them (>50%) originating from Asian countries. Most studies (82.5%) conducted some form of intervention, aiming to improve their computational thinking in students. A smaller proportion (17.5%) were assessment studies in which the authors conducted assessments regarding the children’s computational thinking. On average, intervention studies had a smaller number of participants, but differences in duration could not be identified. There was also a lack of large-scale longitudinal studies. Block-based coding (i.e., Scratch) and Plugged and Unplugged activities were observed in high numbers in both categories of studies. CT assessment tools showed great variability. Efforts for standardization and reaching a consensus are needed in this regard. Finally, robotic systems have been found to play a major role in interventions over the last years. Full article

Background and Objectives: Accurately diagnosing acute appendicitis (AA) in children remains clinically challenging due to overlapping symptoms with other pediatric conditions and limitations in conventional diagnostic tools. The systemic immune-inflammation index (SII) has emerged as a promising biomarker in adult populations; however, its utility in pediatrics is still unclear. This study aimed to evaluate the diagnostic accuracy of SII in distinguishing pediatric acute appendicitis from elective non-inflammatory surgical procedures and to assess its predictive value in identifying complicated cases. Materials and Methods: This retrospective, single-center study included 397 pediatric patients (5–15 years), comprising 297 histopathologically confirmed appendicitis cases and 100 controls. Demographic and laboratory data were recorded at admission. Inflammatory indices including SII, neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) were calculated. ROC curve analysis was performed to evaluate diagnostic performance. Results: SII values were significantly higher in the appendicitis group (median: 2218.4 vs. 356.3; p < 0.001). SII demonstrated excellent diagnostic accuracy for AA (AUROC = 0.95, 95% CI: 0.92–0.97), with 91% sensitivity and 88% specificity at a cut-off > 624. In predicting complicated appendicitis, SII showed moderate discriminative ability (AUROC = 0.66, 95% CI: 0.60–0.73), with 83% sensitivity but limited specificity (43%). Conclusions: SII is a reliable and easily obtainable biomarker for diagnosing pediatric acute appendicitis and may aid in early detection of complicated cases. Its integration into clinical workflows may enhance diagnostic precision, particularly in resource-limited settings. Age-specific validation studies are warranted to confirm its broader applicability. Full article

Recent advancements in large language models (LLMs) have significantly enhanced the effectiveness of Retrieval-Augmented Generation (RAG) systems. This study focuses on the development and evaluation of a domain-specific AI chatbot designed to support international student admissions by leveraging LLM-based RAG pipelines. We implement and compare multiple pipeline configurations, combining retrieval methods (e.g., Dense, MMR, Hybrid), chunking strategies (e.g., Semantic, Recursive), and both open-source and commercial LLMs. Dual evaluation datasets of LLM-generated and human-tagged QA sets are used to measure answer relevancy, faithfulness, context precision, and recall, alongside heuristic NLP metrics. Furthermore, latency analysis across different RAG stages is conducted to assess deployment feasibility in real-world educational environments. Results show that well-optimized open-source RAG pipelines can offer comparable performance to GPT-4o while maintaining scalability and cost-efficiency. These findings suggest that the proposed chatbot system can provide a practical and technically sound solution for international student services in resource-constrained academic institutions. Full article

Titanium alloys such as Ti-6Al-4V are widely used in biomedical implants due to their excellent mechanical properties and biocompatibility, but their bioinert nature limits osseointegration and antibacterial performance. This study proposes a multifunctional surface coating system integrating a thermally oxidized TiO₂ interlayer with a hydroxyapatite (HAp) top layer synthesized via a green route using Hylocereus undatus extract. The HAp was deposited by electrophoretic deposition (EPD), enabling continuous coverage and strong adhesion to the pre-treated Ti-6Al-4V substrate. Structural, morphological, chemical, and electrical characterizations were performed using XRD, SEM, EDS, Raman spectroscopy, and impedance spectroscopy. Bioactivity was assessed through apatite formation in simulated body fluid (SBF), while antibacterial properties were evaluated against Staphylococcus aureus. The results demonstrated successful formation of crystalline TiO₂ (rutile phase) and calcium-rich HAp with good surface coverage. The HAp-coated surfaces exhibited significantly enhanced bioactivity and strong antibacterial performance, likely due to the combined effects of surface roughness and the bioactive compounds present in the plant extract. This study highlights the potential of eco-friendly, bio-inspired surface engineering to improve the biological performance of titanium-based implants. Full article

This study evaluates the production of base oils for biolubricants using fatty acid methyl esters (FAMEs) derived from sunflower oil as the raw material. The production process involved the synthesis of oleochemical esters through a single-step alkaline transesterification reaction with a high-molecular-weight polyol, such as trimethylolpropane (TMP). To assess the effectiveness of the developed catalytic system in conducting the transesterification reactions and its impact on the properties of the final product, two types of alkaline catalysts were used. Specifically, the reactions were carried out using either Ca/TEA alkoxide or sodium methoxide as catalysts in various configurations and concentrations to determine the optimal catalyst concentration and reaction conditions. Sodium methoxide served as the commercial benchmark catalyst, while the Ca/TEA alkoxide was prepared in the laboratory. The optimal concentration of Ca/TEA was determined to be 3.0% wt. in the presence of iso-octane and 3.5% wt. under vacuum, while the corresponding concentrations of CH₃ONa for both cases were determined to be 2.0% wt. The synthesized biolubricant esters exhibit remarkable performance characteristics, such as high kinematic viscosities and low pour points—ranging from 33–48 cSt at 40 °C, 7.68–10.03 cSt at 100 °C, to −14 to −7 °C, respectively—which are comparable to or improved over those of mineral oils such as SN-150 or SN-500, with the Ca/TEA alkoxide-catalyzed systems showing superior oxidation stability and reduced byproduct formation. Full article

Objective: This study aimed to develop a performance evaluation index system for a district-level public hospital in Chongqing, China, based on Diagnosis-Related Groups (DRGs), to provide a benchmark for performance assessment in similar hospitals. The system was constructed using a literature analysis, the Delphi method, and the Analytic Hierarchy Process (AHP) to identify and weight relevant indicators. Results: The evaluation system consists of three primary indicators and eighteen secondary indicators. Key secondary indicators include the Case Mix Index (CMI), cost consumption index, low-risk group mortality rate, the proportion of patients with three- or four-level surgeries at discharge, and the proportion of medical service revenue to medical income. In 2020, significant improvements were observed in several indicators, such as a decrease in the low-risk group mortality rate to 0% and increases in the proportion of patients with three- or four-level surgeries and CMI by nearly 10% and 13%, respectively. Conclusions: This study successfully developed a comprehensive and scientifically sound performance evaluation index system for a district-level public hospital in Chongqing. The system has proven effective in objectively assessing inpatient medical care performance and providing valuable guidance for improving healthcare services in similar settings. Full article

European pig farmers are challenged by increasingly stringent EU regulations to protect the environment from pollution, to meet animal welfare standards and to make pig farming more sustainable. Economic sustainability is defined as the ability to achieve higher profits by respecting social and natural resources. This study is focused on the analysis of the economic resilience of intensive and extensive farming systems, based on data collected from 56 farms located in Denmark, Poland, Italy and Spain. Productive and economic performances of these farms are analyzed, and economic resilience is assessed through a survey including a selection of indicators, belonging to different themes: [i] resilience of resources, [ii] entrepreneurship, [iii] propensity to extensification. The qualitative data from the questionnaire allow for an exploration of how production systems relate to the three dimensions of resilience. Different levels of resilience were found and discussed for intensive and extensive farms. The findings suggest that intensive farms benefit from high standards and greater bargaining power within the supply chain. Extensive systems can achieve profitability through value-added strategies and generally display good resilience. Policies that support investment and risk reduction are essential for enhancing farm resilience and robustness, while strengthening farmer networks can improve adaptability. Full article

This study evaluates the replacement of petroleum-based naphthenic oil with four types of soybean-derived alternatives—virgin soybean oil (SBO), epoxidized SBO (ESBO), expired SBO, and recycled SBO—in styrene–butadiene rubber (SBR) composites. The materials were tested in both staining rubber (SR) and non-staining rubber (NSR) systems to assess processing characteristics, mechanical performance, and environmental durability. Among the alternatives, SBO demonstrated the best overall performance, improving processability and tensile strength by over 10%, while ESBO enhanced ozone resistance by 35% due to its epoxide functionality. Expired and recycled SBOs maintained essential mechanical properties within 90% of virgin SBO values. The full replacement of CH450 with SBO in tire prototypes resulted in burst strength exceeding 1000 kPa and stable appearance after 5000 km of road testing. To validate industrial relevance, the developed green tire was exhibited at the 2025 Taipei International Cycle Show, attracting interest from international buyers and stakeholders for its eco-friendly composition and carbon footprint reduction potential, thereby demonstrating both technical feasibility and commercial viability. Full article

This paper presents a novel harmonic-selective clocking scheme that facilitates concurrent downconversion of spectrally distant radio frequency (RF) signals using a single low-frequency local oscillator (LO) in an N-path receiver architecture. The proposed scheme selectively generates LO harmonics aligned with multiple RF bands, enabling simultaneous downconversion without modification of the passive mixer topology. The receiver employs a 4-path passive mixer configuration to enhance harmonic selectivity and provide flexible frequency planning.The architecture is implemented on a printed circuit board (PCB) and validated through comprehensive simulation and experimental measurements under continuous wave and modulated signal conditions. Measured results demonstrate a sensitivity of $-55\mathrm{dBm}$ and a conversion gain varying from $-2.5\mathrm{dB}$ to $-9\mathrm{dB}$ depending on the selected harmonic pair. The receiver’s performance is further corroborated by concurrent (dual band) reception of real-world signals, including a GPS signal centered at 1575 MHz and an LTE signal at 1179 MHz, both downconverted using a single 393 MHz LO. Signal fidelity is assessed via Normalized Mean Square Error (NMSE) and Error Vector Magnitude (EVM), confirming the proposed architecture’s effectiveness in maintaining high-quality signal reception under concurrent multiband operation. The results highlight the potential of harmonic-selective clocking to simplify multiband receiver design for wireless communication and global navigation satellite system (GNSS) applications. Full article

Background/objectives: Polycystic ovary syndrome (PCOS) and metabolic dysfunction-associated steatotic liver disease (MASLD) are common co-morbidities in women of reproductive age. PCOS is highly heterogeneous and is, therefore, divided into four phenotypes. MASLD leads to numerous systemic complications. Studies to date have shown an association between PCOS and MASLD. This study was designed to compare the FIB-4 score (based on age, alanine aminotransferase, aspartate aminotransferase and platelet count) and the results of shear wave elastography in assessing the risk of developing MASLD by patients with PCOS divided by phenotypes. Methods: The study enrolled 242 women age 18–35 years with PCOS diagnosed according to Rotterdam criteria, hospitalized at the Department of Gynaecological Endocrinology of the University Clinical Centre in Katowice. The study subjects were assigned to phenotypes A to D. Clinical and biochemical assessments were performed (including androgens and metabolic parameters), and the FIB-4 index was calculated. Liver fibrosis was evaluated by shear wave elastography. To balance the group sizes of phenotypes, oversampling with replacement was applied (PROC SURVEYSELECT, SAS), increasing the number of observations for phenotypes B, C, and D fivefold. Statistical analyses were performed based on data distribution (Shapiro–Wilk test), using ANOVA or the Kruskal–Wallis test with Dunn’s correction. Statistical significance was set at p < 0.05. Results: The FIB-4 score was the highest in phenotype B patients (0.50 ± 0.15), and the lowest in phenotypes A and C (0.42 ± 0.14). The highest rate of positive elastography findings was recorded in phenotype A patients (34.7%) and the lowest in phenotype C group (13.5%). Significant differences between the phenotypes were also found in terms of androgen levels, insulin, HOMA-IR, and the lipid profile. Among patients with positive elastography, the highest FIB-4 scores were recorded in phenotype C group (0.44 ± 0.06), but the differences between the phenotypes were not statistically significant. Conclusions: The FIB-4 score was the highest in phenotype B patients and differed significantly from phenotypes A, C and D. In the elastography exam, the fibrosis index was statistically significantly higher in phenotype A compared to other phenotypes. No correlation was detected between the FIB-4 index and positive elastography. The findings suggest that the FIB-4 index may be used for MASLD screening, but its usefulness as a predictor of eligibility for elastography requires more research. Full article

Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will collaborate with learning algorithms in the Neural Adaptive Artificial Intelligence Leadership Model, which is informed by the transformational literature on leadership and socio-technical systems, as well as the literature on algorithmic governance. We assessed the model with thirty in-depth interviews, system-level traces of behavior, and a verified survey, and we explored six hypotheses that relate to algorithmic delegation and ethical oversight, as well as human judgment versus machine insight in terms of agility and performance. We discovered that decisions are made quicker, change is more effective, and interaction is more vivid where agile practices and good digital understanding exist, and statistical tests propose that human flexibility and definite governance augment those benefits as well. It is single-industry research that contains self-reported measures, which causes research to be limited to other industries that contain more objective measures. Practitioners are provided with a practical playbook on how to make algorithmic jobs meaningful, introduce moral fail-safes, and build learning feedback to ensure people and machines are kept in line. Socially, the practice is capable of minimizing bias and establishing inclusion by visualizing accountability in the code and practice. Filling the gap between the theory of leadership and the reality of algorithms, the study provides a model of intelligent systems leading in organizations that can be reproduced. Full article

A shallow quaternary sedimentary aquifer within the river alluvial deposits of eastern Uzbekistan is increasingly vulnerable to the impacts of climate change and anthropogenic activities. Despite its essential role in supplying water for domestic, agricultural, and industrial purposes, the aquifer system remains poorly understood. This study employed a three-dimensional MODFLOW-based groundwater flow model to assess climate change impacts on water budget components under the SSP5-8.5 scenario for 2020–2099. Model calibration yielded RMSE values between 0.25 and 0.51 m, indicating satisfactory performance. Simulations revealed that lateral inflows from upstream and side-valley alluvial deposits contribute over 84% of total inflow, while direct recharge from precipitation (averaging 120 mm/year, 24.7% of annual rainfall) and riverbed leakage together account for only 11.4%. Recharge occurs predominantly from November to April, with no recharge from June to August. Under future scenarios, winter recharge may increase by up to 22.7%, while summer recharge could decline by up to 100%. Groundwater storage is projected to decrease by 7.3% to 58.3% compared to 2010–2020, indicating the aquifer’s vulnerability to prolonged dry periods. These findings emphasize the urgent need for adaptive water management strategies and long-term monitoring to ensure sustainable groundwater use under changing climate conditions. Full article

The Kuroshio Current’s flow velocity imposes exacting requirements on underwater vehicle propulsive systems. Ecological preservation necessitates low-noise propeller designs to mitigate operational disturbances. As technological evolution advances toward greater intelligence and system integration, intelligent unmanned systems are positioning themselves as a critical frontier in marine innovation. In recent years, the global research community has increased its efforts towards the development of high-maneuverability underwater vehicles. However, propeller design optimization ignores the key balance between acoustic performance and hydrodynamic efficiency, as well as the appropriate speed threshold for blade rotation. In order to solve this problem, the propeller design of the NACA 65A010 airfoil is optimized by using OpenProp v3.3.4 and XFlow 2022 software, aiming at innovating the propulsion system of shallow water agile submersibles. The study presents an integrated design framework combining lattice Boltzmann method (LBM) simulations synergized with fully Lagrangian-LES modeling, implementing rotational speed thresholds to detect cavitation inception, followed by advanced acoustic propagation analysis. Through rigorous comparative assessment of hydrodynamic metrics, we establish an optimization protocol for propeller selection tailored to littoral zone operational demands. Studies have shown that increasing the number of propeller blades can reduce the single-blade load and delay cavitation, but too many blades will aggravate the complexity of the flow field, resulting in reduced efficiency and noise rebound. It is concluded that the propeller with five blades, a diameter of 234 mm, and a speed of 500 RPM exhibits the best performance. Under these conditions, the water efficiency is 69.01%, and the noise is the lowest, which basically realizes the balance between hydrodynamic efficiency and acoustic performance. This paradigm-shifting research carries substantial implications for next-generation marine vehicles, particularly in optimizing operational stealth and energy efficiency through intelligent propulsion architecture. Full article

Occupational heat stress represents an increasing challenge to safety and operational performance in underground mining, where elevated temperatures, humidity, and limited ventilation are common. This study proposes an integrated framework to analyze the systemic impact of heat stress on human reliability in mining operations. We conducted a systematic literature review to identify empirical studies addressing thermal exposure, extracting key operational functions for modeling. These functions were structured using the Functional Resonance Analysis Method (FRAM) to reveal interdependencies and performance variability. Human reliability was evaluated using Fuzzy CREAM, which quantified the degree of contextual control associated with each function. Finally, we applied the Gaussian Analytic Hierarchy Process (AHP) to prioritize functions based on thermal impact, contextual reliability, and systemic connectivity. The results showed that functions involving subjective or complex judgment, such as assessing thermal stress or identifying psychophysiological indicators, exhibited lower reliability and higher vulnerability. In contrast, monitoring and control functions based on standardized procedures were more stable and resilient. This combined approach identified critical points of systemic fragility and offers a robust decision-support tool for prioritizing thermal risk mitigation. The findings contribute to advancing the scientific understanding of heat stress impacts in mining and support the development of targeted interventions to enhance human performance and safety in extreme environments. Full article