Search Results (323)

This paper presents the design, implementation, and experimental validation of a Condition Monitoring (CM) circuit for SiC-based Power Electronics Converters (PECs). The paper leverages in situ drain–source resistance (R_ds,on) measurements, interfaced with cloud connectivity for data processing and lifetime assessment, addressing key limitations in current state-of-the-art (SOTA) methods. Traditional approaches rely on expensive data acquisition systems under controlled laboratory conditions, making them unsuitable for real-world applications due to component variability, time delay, and noise sensitivity. Furthermore, these methods lack cloud interfacing for real-time data analysis and fail to provide comprehensive reliability metrics such as Remaining Useful Life (RUL). Additionally, the proposed CM method benefits from noise mitigation during switching transitions by utilizing delay circuits to ensure stable and accurate data capture. Moreover, collected data are transmitted to the cloud for long-term health assessment and damage evaluation. In this paper, experimental validation follows a structured design involving signal acquisition, filtering, cloud transmission, and temperature and thermal degradation tracking. Experimental testing has been conducted at different temperatures and operating conditions, considering coolant temperature variations (40 °C to 80 °C), and an output power of 7 kW. Results have demonstrated a clear correlation between temperature rise and R_ds,on variations, validating the ability of the proposed method to predict device degradation. Finally, by leveraging cloud computing, this work provides a practical solution for real-world Wide Band Gap (WBG)-based PEC reliability and lifetime assessment. Full article

Per- and polyfluoroalkyl substances (PFAS) have been found worldwide in water, soil, plants, and animals, including humans. A primary route of exposure for humans and animals to PFAS is through the diet and drinking water. Perfluorooctane sulfonate (PFOS), a long-chain PFAS with a relatively long half-life, has been associated with adverse health effects in humans and laboratory animals. There are few toxicokinetic studies on PFOS in domestic livestock raised for human food consumption, which are critical for assessing human food safety. This work aimed to develop a simple daily accumulation model (DAM) for predicting PFOS residues in edible beef cattle muscle. A one-compartment toxicokinetic model in a spreadsheet format was developed using simple calculations to account for daily PFAS into and out of the animal. The DAM was used to simulate two case studies to predict resultant PFOS residues in edible beef cattle tissues. The results demonstrated that the model can reasonably predict PFOS concentrations in beef cattle muscle in a real-world scenario. The DAM was then used to simulate dietary PFOS exposure in beef cattle throughout a typical lifespan in order to derive a generic bioaccumulation factor. The DAM is expected to work well for other PFAS in beef cattle, PFAS in other livestock species raised for meat, and other chemical contaminants with relatively long half-lives. Full article

Downhole kick is one of the most severe safety hazards in deep and ultra-deep well drilling operations. Traditional monitoring methods, which rely on surface flow rate and fluid level changes, are limited by their delayed response and insufficient sensitivity, making them inadequate for early warning. This study proposes a real-time monitoring technique for gas content in drilling fluid based on the attenuation principle of Ba-133 γ-rays. By integrating laboratory static/dynamic experiments and Geant4-11.2 Monte Carlo simulations, the influence mechanism of gas–liquid two-phase media on γ-ray transmission characteristics is systematically elucidated. Firstly, through a comparative analysis of radioactive source parameters such as Am-241 and Cs-137, Ba-133 (main peak at 356 keV, half-life of 10.6 years) is identified as the optimal downhole nuclear measurement source based on a comparative analysis of penetration capability, detection efficiency, and regulatory compliance. Compared to alternative sources, Ba-133 provides an optimal energy range for detecting drilling fluid density variations, while also meeting exemption activity limits (1 × 10⁶ Bq) for field deployment. Subsequently, an experimental setup with drilling fluids of varying densities (1.2–1.8 g/cm³) is constructed to quantify the inverse square attenuation relationship between source-to-detector distance and counting rate, and to acquire counting data over the full gas content range (0–100%). The Monte Carlo simulation results exhibit a mean relative error of 5.01% compared to the experimental data, validating the physical correctness of the model. On this basis, a nonlinear inversion model coupling a first-order density term with a cubic gas content term is proposed, achieving a mean absolute percentage error of 2.3% across the full range and R² = 0.999. Geant4-based simulation validation demonstrates that this technique can achieve a measurement accuracy of ±2.5% for gas content within the range of 0–100% (at a 95% confidence interval). The anticipated field accuracy of ±5% is estimated by accounting for additional uncertainties due to temperature effects, vibration, and mud composition variations under downhole conditions, significantly outperforming current surface monitoring methods. This enables the high-frequency, high-precision early detection of kick events during the shut-in period. The present study provides both theoretical and technical support for the engineering application of nuclear measurement techniques in well control safety. Full article

Urbanization poses mental health risks for urban dwellers, whereas natural environments offer mental health benefits by providing restorative experiences through visual stimuli. While urban waterfront spaces are recognized for their mental restorative potential, the specific environmental features and individual visual behaviors that drive these benefits remain inadequately understood. Grounded in restorative environments theory, this study investigates how these factors jointly influence restoration. Employing a controlled laboratory experiment, subjects viewed real-life images of nine representative spatial locations from the waterfront space of Guangzhou Long Bund. Data collected during the multimodal experiments included subjective scales data (SRRS), physiological measurement data (SCR; LF/HF), and eye-tracking data. Key findings revealed the following: (1) The element visibility rate and visual characteristics of plant and building elements significantly influence restorative benefits. (2) Spatial configuration attributes (degree of enclosure, spatial hierarchy, and depth perception) regulate restorative benefits. (3) Visual behavior patterns (attributes of fixation points, fixation duration, and moderate dispersion of fixations) are significantly associated with restoration benefits. These findings advance the understanding of the mechanisms linking environmental stimuli, visual behavior, and psychological restorative benefits. They translate into evidence-based design principles for urban waterfront spaces. This study provides a refined perspective and empirical foundation for enhancing the restorative benefits of urban waterfront spaces through design. Full article

Kawasaki disease (KD) is a rare yet potentially life-threatening pediatric vasculitis that, if left undiagnosed or untreated, can result in serious cardiovascular complications. Its heterogeneous clinical presentation poses diagnostic challenges, often failing to meet classical criteria and increasing the risk of oversight. Leveraging routine laboratory tests with AI offers a promising strategy for enhancing early detection. However, due to the extremely low prevalence of KD, conventional models often struggle with severe class imbalance, limiting their ability to achieve both high sensitivity and specificity in practice. To address this issue, we propose a multi-stage AI-based predictive framework that incorporates clustering-based undersampling, data augmentation, and stacking ensemble learning. The model was trained and internally tested on clinical blood and urine test data from Chang Gung Memorial Hospital (CGMH, n = 74,641; 2010–2019), and externally validated using an independent dataset from Kaohsiung Medical University Hospital (KMUH, n = 1582; 2012–2020), thereby supporting cross-institutional generalizability. At a fixed recall rate of 95%, the model achieved a specificity of 97.5% and an F1-score of 53.6% on the CGMH test set, and a specificity of 74.7% with an F1-score of 23.4% on the KMUH validation set. These results underscore the model’s ability to maintain high specificity even under sensitivity-focused constraints, while still delivering clinically meaningful predictive performance. This balance of sensitivity and specificity highlights the framework’s practical utility for real-world KD screening. Full article

The widespread presence of antibiotics in aquatic environments poses significant ecological and public health risks due to their persistence, antimicrobial activity, and contribution to resistance gene proliferation. This review systematically evaluated the advancements in antibiotic degradation using ionizing radiation (γ-rays and electron beam) from laboratory studies to practical applications. By using keywords such as “antibiotic degradation” and “ionizing irradiation OR gamma radiation OR electron beam,” 328 publications were retrieved from Web of Science, with China contributing 33% of the literature, and a number of global representative studies were selected for in-depth discussion. The analysis encompassed mechanistic insights into oxidative (•OH) and reductive (e_aq⁻) pathways, degradation kinetics influenced by absorbed dose (1–10 kGy), initial antibiotic concentration, pH, and matrix complexity. The results demonstrated ≥90% degradation efficiency for major antibiotic classes (macrolides, β-lactams, quinolones, tetracyclines, and sulfonamides), though mineralization remains suboptimal (<50% TOC removal). Synergistic integration with peroxymonosulfate (PMS), H₂O₂, or O₃ enhances mineralization rates. This review revealed that ionizing radiation is a chemical-free, compatible, and highly efficient technology with effective antibiotic degradation potential. However, it still faces several challenges in practical applications, including incomplete mineralization, matrix complexity in real wastewater, and operating costs. Further improvements and optimization, such as hybrid system development (e.g., coupling electron beam with other conventional technologies, such as flocculation, membrane separation, anaerobic digestion, etc.), catalytic enhancement, and life-cycle assessments of this emerging technology would be helpful for promoting its practical environmental application. Full article

Teachers in lower secondary education often lack content knowledge and self-efficacy to teach molecular biology. The focus of this study was to develop and evaluate an innovative educational approach to prepare pre-service teachers for teaching molecular biology. Therefore, an educational double-decker, with two master courses in a teaching-learning laboratory, has been developed. First, teacher students acquire virtual and authentic lab experiences in a blended-learning course. Later they gain reflective teaching experience by instructing peers or secondary school students. Using a mixed-methods approach in a one-shot-case study design, we examined the effects of the two courses on content knowledge of molecular biology and self-efficacy to teach it, the relationship between knowledge and self-efficacy, and the influence of teaching secondary students compared to peer teaching on self-efficacy. Questionnaires (N = 92 and N = 20) measured knowledge and self-efficacy before and after both courses; differences were analyzed statistically. In addition, guided interviews were conducted with teacher students after the educational double-decker (N = 14) and analyzed qualitatively using content analysis. The results demonstrate that blended-learning formats are efficacious in developing molecular biology knowledge. Content knowledge is positively correlated with teaching self-efficacy, but this effect diminishes after having a reflective teaching experience. These experiences are pivotal factors in self-efficacy development. Teaching real secondary school students is valuable in fostering self-efficacy, as such authentic experiences can be readily applied in everyday school life. Full article

Background: Borderline Personality Disorder (BPD) is a debilitating mental health condition characterized by emotional dysregulation and interpersonal dysfunction, with perceived social rejection exacerbating these issues. Emerging evidence suggests that a single session of transcranial direct current stimulation (tDCS) over the right ventrolateral prefrontal cortex (rVLPFC) may decrease the unique tendency of BPD patients to feel rejected even when socially included during a laboratory task. Objectives: This protocol outlines a double-blind, sham-controlled study evaluating the longitudinal effects of repeated anodal tDCS over the right ventrolateral prefrontal cortex (rVLPFC) on rejection-related emotions (RRE) during real-life social interactions in individuals with BPD. Methods: Sixty BPD patients will be randomized to receive real or sham tDCS across 10 daily sessions, coupled with an ecological momentary assessment (EMA) protocol capturing emotional and behavioral responses to real-life social interactions over four timepoints: baseline, during treatment, ten days post-treatment, and three months post-treatment. Primary outcomes include changes in RRE, with exploratory analyses examining feelings of social connection, aggressive tendencies, trust toward others, and interpersonal and affective dynamics. Multilevel modeling will assess temporal and group-level effects. Expected Results and Impact: This study aims to establish the efficacy of tDCS in reducing BPD patients’ negative emotional response in real-life social situations and to determine whether such effects are maintained in time. The findings could advance the clinical application of tDCS as an adjunctive intervention to alleviate social–emotional impairments in BPD, addressing gaps in current treatment approaches and guiding future research into the neural mechanisms of social emotion regulation. Full article

The production of electric vehicle (EV) batteries is playing an increasingly significant role in the decarbonization of the mobility sector. In order for EV batteries to be competitive against internal combustion engines, it is crucial to maximize the primary and secondary life cycles of batteries. This necessitates a battery management system that can ensure performance, safety, and longevity. State of Charge (SoC) estimation is important for such a system, as it ensures efficiency of the battery’s performance, and it is necessary for the prediction of the battery’s health and lifespan. Existing SoC estimation methods heavily depend on laboratory tests, which are both costly and time consuming. Additionally, the simulated nature of laboratory settings cannot guarantee robustness when the same method is applied to field data collected from real-world scenarios. A suitable alternative to this problem is the use of data-driven approaches. The goal of this work is the estimation of SoC with a real-world dataset using neural networks. Furthermore, we demonstrate how explainable AI (xAI) and importance estimate can be applied to inform what signals and which parts of a signal are important for SoC estimation. This helps to reduce redundancy, and it provides more information regarding the relationships within battery cells that are otherwise obscured by the complexity of the battery. The methods that we used resulted in a mean squared error (MSE) of as low as 3 × ${10}^{-4}$, and the information provided by xAI suggested that it is possible to discard up to 25% of the input profile whilst retaining similar performance. Full article

Background: Hypereosinophilic syndrome (HES) is a heterogeneous group of rare disorders defined by the presence of marked eosinophilia resulting in end organ damage. The diagnostic approach is multidisciplinary and treatment goals include reductions in flares and eosinophils with minimal drug-related side effects. Results: Eleven patients (n = 11) with a diagnosis of idiopathic HES were included in the study [M/F: 6/5, median age: 54 (95% CI: 38.2 to 68.5), smokers/never smokers: 5/6]. Asthma was present in the majority of them (n = 8, 72.7%); four patients (n = 4, 36.4%) presented with eosinophilic pleural effusions, two patients (n = 2, 18.2%) with cardiac arrhythmias, and one with bilateral eyelid angioedema. Eight patients (72.7%) were treated with mepolizumab (300 mg/month) and three (27.3%) with benralizumab (30 mg/4 weeks). The median values of eosinophils at baseline and 12 months after initiation of biologic agent were 3000 (95% CI: 2172 to 11,365) K/μL and 50 (95% CI: 3 to 190) K/μL, respectively, p = 0.0002. All patients with concomitant asthma (n = 8) experienced elimination of asthma flares, asthma control (ACQ < 0.75), functional improvement (mean ΔFEV1: 857 ± 594 mL), and an 82% reduction in oral corticosteroids, p = 0.0001. Materials and Methods: Patients with highly characterized idiopathic HES treated with anti-eosinophilic agents between 1 October 2019 and 1 October 2023 were retrospectively included in the study. The aim of this study was to present clinical, laboratory, and functional features and outcomes in patients with thoroughly investigated idiopathic HES treated with biologic agents targeting eosinophils. Conclusions: Biologic agents in patients with idiopathic HES—following thorough diagnostic investigation—are both safe and effective, sparing the toxicity of immunosuppressive agents. Real-life data from larger registries are greatly anticipated. Full article

In the current scientific and technological scenario, wearable neuroimaging devices represent a revolution in neuroscience and wearable technology. These tools combine the features of neuroimaging technologies with the convenience of wearable devices, enabling real-time exploration of brain activity in real-world contexts. This convergence defines new perspectives in scientific research, medical diagnosis, and human performance analysis. Technologies such as EEG and fNIRS enable the non-invasive monitoring of brain activity without the need for heavy clinical equipment. Indeed, miniaturization, portability, wireless communication, and energy efficiency are key objectives in the design of advanced devices. In such a scenario, comfort is a key requirement to enable widespread use in different contexts, requiring the design of lightweight and minimally invasive wearable devices. The literature review examines the impact of wearable EEG and fNIRS devices on the user in real-life and laboratory environments in terms of usability and acceptability. The study presents evaluation and design factors—applied to laboratory testing—defined to improve the quality and perception of the user experience and to ensure the accuracy of cognitive load detection. These results will be useful in defining wearable devices, new applications, and future challenges for BCI. Full article

Indoor air quality (IAQ) impacts human health, productivity, and well-being. As buildings become more energy-efficient and tightly sealed, the need for effective ventilation systems that maintain adequate IAQ grows. Energy Recovery Ventilators (ERVs) ensure adequate IAQ by bringing fresh outdoor air indoors while minimizing costly energy wastage. ERVs provide major economic, health, and well-being benefits and are a critical technology in the fight against climate change. However, little is known about the impact of ERV operation on the generation and fate of particulate and gaseous indoor air pollutants, including toxic, carcinogenic, allergenic, and infectious air pollutants. Specifically, the air pollutant crossover, aerosol deposition within ERVs, the chemical identity and composition of aerosols and volatile organic compounds emitted by ERVs themselves and by the accumulated pollutants within them, and the effects on bioaerosols must be investigated. To fill these research gaps, both field and laboratory-based experimental research that closely mimics real-life conditions within a controlled environment is needed to explore critical aspects of ERVs’ effects on indoor air pollution. Filling the research gaps identified herein is urgently needed to alert and inform the industry about how to optimize ERVs to help prevent air pollutant generation and recirculation from these systems and enhance their function of pollutant removal from residential and commercial buildings. Addressing these knowledge gaps related to ERV design and operation will enable evidence-based recommendations and generate valuable insights for engineers, policymakers, and heating, ventilation and air conditioning (HVAC) professionals to create healthier indoor environments. Full article

Vitamin C, an antioxidant in most fruits and vegetables, is highly sensitive to heat, pH, metals, light, and oxidation, making it a key marker for nutrient degradation in thermal processing. Research aimed at improving processing methods to maximize vitamin C retention is usually limited to expensive laboratory equipment, which does not reflect real-world conditions in the food industry. On the other hand, traditional methods are not suitable for on-line monitoring. This paper proposes bridging the gap in liquid food processing with a voltammetric sensor based on poly(3,4-ethylenedioxythiophene)-modified screen-printed carbon electrodes. The sensor showed excellent repeatability, with intra-sensor RSD below 5% and inter-sensor RSD below 10% at 250 mg/L of ascorbic acid. Detection and quantification limits were 0.7 and 2.1 mg/L, respectively. Trueness assessment in commercial orange juice with a declared vitamin C content yielded a recovery rate of 94 ± 1%. Selectivity tests with citric acid at concentrations equal to and 20 times higher than that of ascorbic acid showed no significant interference. Shelf-life studies confirmed the stability of the sensor for at least two months. This nanocomposite-based approach balances performance and cost with simple preparation, affordable materials, and a stable coating that allows long-term storage in uncontrolled environments. Full article

Background: Laboratory monitoring of the effect of low-molecular-weight heparins (LMWHs) is generally not necessary. However, prompt evaluation of heparin inhibitory effects (i.e., anti-Xa activity) is important in cases of life-threatening bleeding, need for urgent surgery or acute thromboembolism under LMWH treatment. We aimed to establish a simple and reliable point-of-care method for the detection of enoxaparin. Methods: Eighty patients under enoxaparin therapy and ten healthy volunteers without any anticoagulant treatment were enrolled. Simultaneous measurements of anti-Xa activity using the chromogenic method and clotting times in the absence and presence of polybrene using viscoelastometric assays containing Russell’s viper venom (RVV-test) were performed on the ClotPro device. Results: Among the measured and derived RVV-test parameters, the ratio of the RVV clotting times (RVV CT) detected in the absence and presence of polybrene showed the best statistically significant correlation with anti-Xa activity (r = 0.774, p < 0.001). Based on ROC analysis, we designated RVV CT ratios of 1.02, 1.23 and 1.6 as the best cut-off values for separating anti-Xa ranges below and above 0.3 and 0.6 IU/mL, respectively. If the RVV CT ratio is below or above 1.23, the anti-Xa activity is suggested to be below 0.6 IU/mL or above 0.3 IU/mL with high certainty, respectively. Further differentiation is possible if the RVV CT ratio is measured below 1.02 or above 1.6. In these cases, the measured anti-Xa values are below 0.3 IU/mL or above 0.6 IU/mL, respectively, with high probability and good predictive values. Conclusions: Our method can provide semiquantitative information on the effect of enoxaparin and the expected anti-Xa activity within 10 min in real clinical situations. Full article

Driven by technological advancements and accelerated infrastructure development, an increase in the need to monitor the performance of prominent structures such as bridges, metro-corridors, and sea-link bridges is being advocated by experts to predict and minimize any hazards resulting from the degradation of the structures over time. However, accessing and replacing the batteries becomes problematic and expensive when the sensors are instrumented in remote areas of the bridge structures, especially when the sensors are embedded. For these reasons, a strong case can be made for harvesting and storing ambient energy from the surroundings to drive the sensors for structural health monitoring (SHM). This study aims to introduce a new trapezoidal strain-amplifying sensor/energy harvester (TSAH) for civil engineering structures that uses flexural strain amplification to enhance energy harvesting from structural vibrations. TSAH also serves as a sensor for integrated energy harvesting and SHM. This article examines the influence of the geometric properties of TSAH on strain amplification via numerical investigations under a specific set of external loads. Based on numerical studies, the sensors are bonded to the trapezoidal strain-amplifying plate to develop and assess the TSAH. Experimental investigations were carried out first in the laboratory to evaluate the effectiveness of the TSAH over the directly bonded (DB) sensors with two different types of piezo-transducers for energy harvesting. The host structure was exposed to impact and shaker vibrations for the laboratory research. For the various scenarios taken into consideration in the study, the typical amplification factor for peak voltage is determined to be between 1.45 and 3.75, while for the power, it is between 1.09 and 6.08. Further, for field verification, the TSAH configuration was evaluated on a real-life bridge structure, viz the Chipiyana rail over-bridge (ROB), Asia’s heaviest steel ROB located on the Delhi–Meerut expressway. The field experiments also establish the superior performance of TSAH, with an amplification factor ranging from 1.75 to 3.75 for peak voltage and 3.75 to 5.53 for peak power. As compared to the previously proposed curved configuration in the literature, the TSAH configuration is suitable for brittle sensors as well. Its ability to be permanently bonded by epoxy/welding, or temporarily using magnets, bolts, or clamps, offers it versatility over other surface bonded/embedded configurations. As a result of this, it imparts reusability in case of any damage, which promotes the goal of sustainability. Full article