Search Results (1,662)

To maintain product reliability and stabilize performance, it is essential to prioritize the identification and resolution of latent defects. Advanced products such as high-precision electronic devices and semiconductors are susceptible to performance degradation over time due to environmental factors and electrical stress. However, conventional performance testing methods typically evaluate products based solely on predefined acceptable ranges, making it difficult to predict long-term degradation, even for products that pass initial testing. In particular, products exhibiting borderline values close to the threshold during initial inspections are at a higher risk of exceeding permissible limits as time progresses. Therefore, to ensure long-term product stability and quality, a novel approach is required that enables the early prediction of potential defects based on test data. In this context, the present study proposes a machine learning-based framework for predicting latent defects in products that are initially classified as normal. Specifically, we introduce the Sigma Deviation Count Labeling (SDCL) method, which utilizes a Gaussian distribution-based approach. This method involves preprocessing the dataset consisting of initially passed test samples by removing redundant features and handling missing values, thereby constructing a more robust input for defect prediction models. Subsequently, outlier counting and labeling are performed based on statistical thresholds defined by 2σ and 3σ, which represent potential anomalies outside the critical boundaries. This process enables the identification of statistically significant outliers, which are then used for training machine learning models. The experiments were conducted using two distinct datasets. Although both datasets share fundamental information such as time, user data, and temperature, they differ in the specific characteristics of the test parameters. By utilizing these two distinct test datasets, the proposed method aims to validate its general applicability as a Predictive Anomaly Testing (PAT) approach. Experimental results demonstrate that most models achieved high accuracy and geometric mean (GM) at the 3σ level, with maximum values of 1.0 for both metrics. Among the tested models, the Support Vector Machine (SVM) exhibited the most stable classification performance. Moreover, the consistency of results across different models further supports the robustness of the proposed method. These findings suggest that the SDCL-based PAT approach is not only stable but also highly adaptable across various datasets and testing environments. Ultimately, the proposed framework offers a promising solution for enhancing product quality and reliability by enabling the early detection and prevention of latent defects. Full article

Background/Objectives: Blood vessel tortuosity can complicate endovascular procedures such as endovascular thrombectomy in acute ischemic stroke. This study aimed to assess the morphometric characteristics of carotid arteries and investigate the association between the tortuosity of the carotid arteries and the technical aspects of endovascular thrombectomy, patient demographics and clinical characteristics, and treatment outcome. Methods: This retrospective study included 84 patients with ischemic stroke treated by endovascular thrombectomy at the newly established thrombectomy-capable stroke center. The following data were collected from prethrombectomy computed tomography angiography: aortic arch type, type of carotid artery tortuosity, and tortuosity index (TI). The technical aspects of the procedure, as well as patient demographics, were collected from the radiological information system. Results: Time from arterial puncture to the first pass was significantly shorter in patients with a nontortuous carotid artery compared to a tortuous one (p = 0.006). There were no significant differences in the number of passes, total duration of the procedure, and the difference in National Institutes of Health Stroke Scale (NIHSS) score before and after the procedure regarding the form of tortuosity. Patients with hypertension had significantly higher tortuosity index values compared to those without hypertension (p = 0.008), and patients with a nontortuous carotid tree were significantly younger compared to those with all forms of tortuosity (p = 0.003). Conclusions: The majority of patients had tortuous carotid arteries, which were associated with older age and hypertension. A high index of tortuosity was associated with a longer time from arterial puncture to the first pass, but not to the treatment outcome. Preprocedural recognition of carotid artery tortuosity may aid in endovascular thrombectomy procedural planning. Full article

Background: Child sexual abuse (CSA) is a serious public health concern that violates the rights of children. In Mexico, little is known about the actual figures for this type of violence. Objective: This study aimed to determine trends in the prevalence and case characteristics of CSA in a representative sample of children in Mexico. Materials and Methods: Data from the National Health and Nutrition Survey (ENSANUT) for 2018, 2020, 2021, 2022 and 2023 were used (n = 24,179). Proportions of CSA were estimated using the weighted mean of a binary variable, and the variance of the estimated proportion was calculated using the Taylor linearization method. Logistic regression models were estimated, and Adjusted Odds Ratios (AORs) with 95% Confidence Intervals (95% CIs) were obtained. Results: The prevalence of CSA ranged from 2.22% (2018) to 5.66% (2023). There was an increasing trend in CSA between 2018 and 2021, which was even more pronounced (154.95%) between 2018 and 2023 (p < 0.001). The main perpetrator in CSA cases was a family member (78.51%), and most victims did not report the abuse to the authorities. Girls were more likely to experience CSA (AOR = 2.83, 95% CI: 1.72–4.68), and as years passed (from 2018 to 2023), the likelihood of becoming a victim of CSA increased. Conclusions: CSA is a problem that has increased in recent years in Mexico. It is noteworthy that the main perpetrator is within the family, which may influence the lack of reporting of these cases. In view of this situation, it is necessary to implement strategies to prevent CSA in children, involving mothers, fathers, and caregivers. Full article

As a core component of high-speed trains, the traction drive system is also one of the main sources of both pass-by noise and interior noise. Current research primarily focuses on the modeling and design of its dynamic characteristics, while studies on its sound radiation remain relatively scarce. Existing investigations mainly rely on experimental and finite element methods. This paper proposes a rapid modeling method for the sound radiation of traction drive systems and analyzes the acoustic characteristics under different train speeds and gear helix angles. Taking an electric freight locomotive operating on China’s railways as the subject, the primary noise sources were identified through real-vehicle testing, thereby simplifying the non-dominant noise sources. By integrating a gear system dynamic model with theoretical models of gear meshing noise and motor noise, the proposed approach avoids the complexity and high computational cost associated with traditional finite element methods. The results show that at lower train speeds, the main noise source is the motor, while at higher speeds, it is the gearbox. As the train speed and helix angle increase, the radiated sound pressure of the traction drive system first increases and then decreases, though the sound field distribution and directivity remain largely unchanged. Full article

This article presents an extensive experimental investigation of the dynamic characteristics of three-arch historical masonry bridges, using Operational Modal Analysis (OMA). The research thoroughly characterizes the dynamic behavior of four representative masonry bridges from the Apulia Region in Southern Italy through detailed experimental campaigns. These campaigns employed calibrated and optimally implemented accelerometric monitoring systems to acquire high-quality dynamic data under controlled excitation and environmental conditions. The selected bridges include the Santa Teresa Bridge in Bitonto, the Roman Bridge in Bovino, the Roman Bridge in Ascoli Satriano and a moderner road bridge on the Provincial Road SP123 in Troia; they span almost two millennia of construction history. The experimental framework incorporated several non-invasive excitation methods, including controlled vehicle passes, instrumented hammer impacts and ambient vibration tests, strategically chosen for optimal signal quality and heritage preservation. This investigation demonstrates the feasibility of capturing the dynamic behavior of these complex and specific historic structures through customized sensor configurations and various excitation methods. The resulting natural frequencies and mode shapes are accurate, robust, and reliable considering the extended data set used, and have allowed a rigorous seismic assessment. Eventually, this comprehensive data set establishes a fundamental basis for understanding and predicting the seismic response of several three-span masonry bridges to accurately identify their long-term resilience and effective conservation planning of these valuable and vulnerable heritage structures. In conclusion, the data comparison enabled the formulation of a predictive equation for the identification of the first natural frequency of bridges from geometric characteristics. Full article

This study investigated the microbiological, physicochemical, textural, and sensory characteristics of ayran and kefir samples produced from milk treated with different doses of UV-C radiation. For this purpose, raw milk was passed through a UV-C column at three different flow rates (15, 30, and 45 mL/min), and irradiated with doses of 72, 36, and 24 J/mL, respectively, corresponding to the flow rate. Samples produced from milk pasteurised by thermal treatment were used as the control group. This research indicated that UV-C treatment effectively reduced the microbial load in milk to a level comparable to that achieved through conventional pasteurisation. A reduction of 2.15 log cfu/mL in total aerobic mesophilic bacteria count was achieved, while total coliform group bacteria counts were decreased to an undetectable level. Samples produced from milk treated with UV-C showed lower pH and higher titration acidity (% lactic acid). Furthermore, the organic acid content was higher in these samples. Lactic acid, the main organic acid, levels in the ayran and kefir samples were measured at their highest as 11,951.51 mg/kg and 12,989.34 mg/kg, respectively, in the UV45 sample with a radiation dose of 24 J/mL. The treatment of UV-C resulted in a minor change in the colour and textural properties of the samples. Nonetheless, this change was not significant enough to influence consumer acceptance. The application of UV-C to raw milk, depending on the radiation level used, can enhance the fermentation process in the production of ayran and kefir. This study showed that the application of UV-C has improved the quality of drinkable fermented milk products. This research has shown that, while reducing nutritional losses caused by thermal processing, microbial safety is obtained at an approximate value similar to pasteurisation. As a result, UV-C application decreases the loss of dietary compounds and provides an alternative method for microbial inactivation. Full article

α-Cyperone (C₁₅H₂₂O), a critical bioactive sesquiterpene, serves as a representative chemical compound of Cyperi Rhizoma—a classical functional food. To investigate the pharmacokinetic characteristics of α-cyperone, a quantified method was developed in plasma, bile, urine, and feces by ultra-high-performance liquid chromatography tandem triple quadrupole mass spectrometry (UHPLC-QQQ-MS/MS). After being validated, the developed method was applied in a plasma pharmacokinetic study as well as biliary, urinary, and fecal excretion kinetics studies. It revealed poor absolute bioavailability (F = 1.36%) and rare excretion (total cumulative excretion = 0.022%) of α-cyperone, which suggested extensive first-pass metabolism. This study provided crucial insight into explaining the in vivo process and promoting the further development of α-cyperone. Full article

The numerical method was employed to analyze the transient pressure characteristics of a metro train passing through a tunnel in high-altitude regions. The transient pressure evolution inside and outside the train under varying ambient pressures is analyzed and compared. The findings indicate that while ambient pressure minimally impacts the waveform of the exterior transient pressure, it significantly influences the peak value. Specifically, as ambient pressure rises, the maximum transient pressure (P-max) and the peak-to-peak transient pressure (ΔP) on the train’s exterior surface increase linearly, whereas the minimum transient pressure (P-min) decreases linearly. Moreover, this study analyzed pressure changes within the metro train under varying ambient pressures to assess their impact on passengers’ ear comfort. The trend of pressure peak reduction and delay inside the metro train with a certain degree of airtightness remains well aligned for different ambient pressures. In areas of high altitude with low atmospheric pressure, the requirements for the tightness performance of the train are lower. Full article

Background: The Hajj pilgrimage, a significant religious event, presents unique health challenges due to the large number of participants and the physical demands of the pilgrimage. Despite efforts by Saudi health authorities to provide comprehensive health services, the effectiveness of these interventions relies heavily on pilgrims’ knowledge of available services and emergency measures. Objectives: The aim of this study is to assess the level of knowledge of health services among Hajj pilgrims in Saudi Arabia during the 1445 H (2024 G) season and its associated demographic and health-related factors. Methods and Materials: This cross-sectional study was conducted during the 1445 H (2024 G) Hajj season with 1215 pilgrims, 51.7% male. Participants were randomly selected from selected pilgrimage accommodations or passing through the airport in Jeddah. Data were collected through face-to-face interviews using a structured questionnaire covering demographics, health characteristics, and knowledge of health services. Results: The study found that 62.1% of participants correctly believed that health services during Hajj were free of charge. Furthermore, 44.4% were aware of the emergency health number, with 31.5% exhibiting good knowledge. Bivariate analysis showed that younger participants had better knowledge (p < 0.001), and males were more likely than females to demonstrate partial or good knowledge (p = 0.011). Participants with university education were significantly more likely to have good knowledge, with 29.6% demonstrating good knowledge compared to 7.4% of illiterate participants (p < 0.001). Geographic region was also a factor, with 48.9% of Middle Eastern participants exhibiting good knowledge, compared to 27.1% of African and 23.6% of Asian participants (p < 0.001). However, multivariable logistic regression, revealed that only younger age (OR = 0.98, p = 0.005), university education (OR = 1.96, p = 0.024), and being from the Middle East (OR = 1.61, p = 0.009) were significant predictors of good knowledge of health services. Conclusions: The study identified significant gaps in pilgrims’ knowledge of health services during Hajj, with younger age, higher education, and Middle Eastern geographic region identified as independent predictors of better knowledge. These findings suggest the need for targeted health education initiatives, particularly for older pilgrims, those with lower educational attainment, and individuals from regions with lower awareness levels, to improve knowledge and potentially enhance health outcomes during Hajj. Full article

Background/Objectives: Despite the recognized importance and distinctive characteristics of the intestinal lymphatic pathway in drug absorption, its pharmacokinetic modeling remains largely unexplored. This study aimed to address this gap by developing a physiologically based pharmacokinetic model (PBPK) to represent the oral lymphatic uptake of halofantrine following a fatty meal. Methods: Using GastroPlus™ 9.8.3 and published literature data, halofantrine absorption, distribution, metabolism, and elimination in both fasting and fed states were modeled. As the used software does not directly simulate intestinal lymphatic transport, lymphatic involvement in the fed state was examined indirectly through parameter adjustments such as first-pass metabolism, pKa-driven solubility changes, and bile-salt-mediated solubilization, with the aid of molecular dynamics simulations under post-prandial pH. Results: The pharmacokinetic models revealed a reduction in the first-pass effect of halofantrine in the fed state compared to that in the fasting state. While adjustments in metabolism kinetics sufficed for constructing a representative PBPK model in the fasting state, capturing the fed-state profile required both modifications to metabolism kinetics and other parameters related to the structural rearrangements of halofantrine driven by the changes in intestinal pH following food intake. These changes were confirmed using molecular dynamics simulations of halofantrine in pHs reflecting the post-prandial conditions. Conclusions: This study underscores the need for further exploration and direct modeling of intestinal lymphatic uptake via PBPK models, highlighting its underexplored status in simulation algorithms. Moreover, the importance of integrating representative physicochemical factors for drugs, particularly in post-prandial conditions or lipid formulations, is evident. Overall, these findings contribute to advancing predictive regulatory and developmental considerations in drug development using post hoc analyses. Full article

Due to the “low damping” characteristics of the DC distribution system, the traditional passive scheme is not suitable for DC fault detection and positioning. Therefore, this paper proposes an active injection fault identification method suitable for DC feeder line under single-pole grounding faults. Based on the high controllability of converters, this method uses the oscillation circuit characteristics of the DC side single-pole grounding fault to superimpose the harmonics of fixed frequency into the converter modulated wave, and derives the selection principles of harmonic amplitude and frequency. After the fault, the positive and negative current signals are extracted from the feeder lines, and the zero-mode current components are extracted by the Karrenbauer transformation and band-pass filter, the current phases are compared to achieve the fault feeder line selection. According to simulation verification, the power quality of the actively injected harmonics is within the standard range under the condition of global injection, and the single-pole grounding faults in each feeder line can be identified. Full article

The dynamic shear modulus ratios and dynamic damping ratios of soil are critical parameters for soil seismic response analyses and seismic safety evaluation of engineering sites. This study utilized dynamic triaxial test and resonant column test data of 5208 soil samples collected from more than 2500 boreholes across the Beijing-Tianjin-Hebei (BTH) region. Statistical analyses were conducted for five typical soil types (silty clay, clay, silt, silty sand, and fine sand), focusing on their dynamic shear modulus ratios and dynamic damping ratios. Key parameters representing the characteristics of soil dynamics, including the reference strain, the maximum damping ratio, and the damping ratio nonlinearity coefficient, were statistically evaluated. Median values, as well as the values corresponding to 84% and 16% exceedance probabilities, were provided. The median values of the reference strain, the maximum damping ratio, and the damping ratio nonlinearity coefficient were 13.43 × 10⁻⁴, 0.2155, and 0.7799 for silty clay; 16.47 × 10⁻⁴, 0.2266, and 0.7722 for clay; 10.64 × 10⁻⁴, 0.2012, and 0.7856 for silt; 11.98 × 10⁻⁴, 0.1842, and 0.7911 for silty sand; and 12.73 × 10⁻⁴, 0.1803, and 0.8064 for fine sand. Based on these statistics, the influence of various factors on the reference shear strain, maximum damping ratio, and damping ratio nonlinearity coefficient were investigated. The results showed considerable variability, and weak correlations were observed between these parameters and site-related factors such as sampling depth, shear wave velocity at sampling depth, overburden thickness, 30 m average shear wave velocity (V_S30), and 20 m equivalent shear wave velocity (V_se). The coefficients of determination for the linear regressions considering each factor were between 0.001 and 0.274, which were sufficiently close to 0 and indicated a weak predictive ability of the model considering only one factor. Furthermore, multivariate linear regression models incorporating all five influencing factors also achieved a slight reduction in standard deviation compared with directly adopting the mean values—by <5.5% for the reference shear strain, <3.9% for the maximum damping ratio, and <7.3% for the damping ratio nonlinearity coefficient. A case study was conducted to demonstrate the impact of the variability in soil dynamic parameters on both site seismic response and structural seismic response. For the selected ground motion inputs, site model, and structural model, differences in soil dynamic parameters led to variations in structural seismic response up to 54.5%. Comparative analyses with recommended values from existing studies indicate that the dynamic parameters of the five typical soil types in the BTH region investigated exhibited distinct regional characteristics: the dynamic shear modulus ratios were significantly lower, while the dynamic damping ratios were significantly higher. Comparisons with results from other studies on soil dynamic parameters in China showed that the dynamic shear modulus ratios derived from this study were noticeably smaller, while the dynamic damping ratios were significantly larger. At least one of the three soil dynamic parameters for each soil type failed to pass two-side t-tests, which indicated that the statistical data were from two distributions, that is, soil dynamic properties were intrinsically linked to sedimentary environments, exhibiting distinct regional specificity. Therefore, for boreholes lacking laboratory dynamic test data of soil in the BTH region, it was recommended to use the median values of reference shear strains, maximum damping ratios, and damping ratio nonlinearity coefficients provided in this study for the estimation of dynamic shear modulus ratios and dynamic damping ratios, while their variability must be taken into consideration. Full article

Background: Sarcina ventriculi is a bacterium predominantly reported in the stomach and associated with emphysematous gastritis, delayed gastric emptying, gastroparesis, or gastric outlet obstruction. Its prevalence is increasing among patients with a history of organ transplants, immunosuppression, and graft-versus-host disease (GVHD). This bacterium can be detected on histology with characteristic tetrad packet morphology; however, confirmation requires PCR and molecular studies. The role of Sarcina ventriculi in human diseases is not fully understood and has unclear clinical significance. While certain studies point to a possible pathogenic role, others regard its detection as incidental with no clear clinical consequence. Case presentation: Herein, we report a case of a 39-year-old male patient with primary refractory cHL, stage IVb, who underwent an autologous bone marrow transplant (BMT) and an allogeneic stem cell infusion. His post-transplant course was complicated by chronic kidney disease (CKD), malnutrition, depression, myopathy, skin, and colon GVHD. He eventually developed sepsis, was admitted to the ICU and developed multiorgan failure and passed away. The patient developed diarrhea, and the gastrointestinal specialist was consulted and revealed ulcerated ileitis and colitis. Biopsies were taken to evaluate for CMV infection and GVHD. The terminal ileum biopsy mainly revealed ulceration with granulation tissue formation and abundant microorganisms arranged in distinctive tetrads, characteristic of Sarcina ventriculi. The colonic biopsies were consistent with GVHD grade II. Conclusions: The significance of Sarcina microorganisms and their mechanisms of injury remain poorly understood. The identification of Sarcina ventriculi in the terminal ileum, which is an unusual and previously unreported finding, adds a new perspective to our understanding of its pathogenic potential and anatomical distribution. While the patient’s clinical decline was influenced by multiple factors, including GVHD, recurrent sepsis, and multiorgan failure, the role of Sarcina ventriculi as a potential exacerbating factor remains unclear. Full article

Total Mixed Ration (TMR) particle size significantly impacts dairy cow health and productivity. This study investigated the effects of TMR particle size tertiles on rumen pH, dry matter intake (DMI), and milk characteristics in Simmental cows by continuous pH monitoring (Moonsyst Ltd., Kilkenny, Republic of Ireland) and particle separation by 19, 8, 4 mm sieves and pad using the Wasserbauer particle separator, along with regular milk and DMI measurements. Data were analyzed by IBM SPSS 26.0 with ANOVA, Pearson correlations and statistically significant differences between tertiles by post hoc Tukey HSD test were performed (p < 0.05). Tertiles by frequency analysis were used to categorize particle size proportions into three groups, each containing an equal number of observations. Principal component analysis (PCA) and heatmaps by SRplot were generated. Moderate particle size distributions (second tertiles of 19 mm, 8 mm, 4 mm sieves, and pad as the fraction of TMR particles that pass through the all sieves and are collected in the bottom pan) optimized rumen pH stability, reducing time below 6.2 (SARA risk) or above 6.8, and correlated with milk β-hydroxybutyrate (BHB), oleic acid, and acetone levels. Moreover, milk production was maximized with a combination of coarser (19 mm and 8 mm, third tertiles) and finer (4 mm, first tertile) particles, milk fat peaked in both the finest pad fraction (third tertile) and coarsest larger sieves (first tertiles), and milk protein in the first tertiles of 19 mm and 8 mm sieves. Similarly, DMI positively correlated with coarser particles, but sometimes negatively with milk quality. In addition, PCA showed fine particle groups clustering with higher milk fat-to-protein ratios, somatic cell counts, and urea. In conclusion, mid-range TMR particle sizes (second tertiles) consistently provided the most benefits across ruminal, metabolic, and production parameters, underscoring TMR structure as a crucial precision feeding tool. Full article

Prototype-Based Networks (PBNs) are inherently interpretable architectures that facilitate understanding of model outputs by analyzing the activation of specific neurons—referred to as prototypes—during the forward pass. The learned prototypes serve as transformations of the input space into a latent representation that more effectively encapsulates the main characteristics shared across data samples, thereby enhancing classification performance. Crucially, these prototypes can be decoded and projected back into the original input space, providing direct interpretability of the features learned by the network. While this characteristic marks a meaningful advancement toward the realization of fully interpretable artificial intelligence systems, our findings reveal that prototype representations can be deliberately or inadvertently manipulated without compromising the superficial appearance of explainability. In this study, we conduct a series of empirical investigations that demonstrate this phenomenon, framing it as a structural paradox potentially intrinsic to the architecture or its design, which may represent a significant robustness challenge for explainable AI methodologies. Full article