Search Results (1,496)

The impact of a quarter-circle corner crack on an adjacent parallel semi-elliptical surface crack (SESC) located in a semi-infinite solid subjected to in-plane bending is studied using a 3-D finite element analysis. The stress intensity factor (SIF) distributions along the front of the SESC are evaluated to determine said impact. The SESC’s semi-major axis ranged from a₁ = 10 mm to 30 mm with ellipticities of b₁/a₁ varying from 0.1 to 1.0 for a constant quarter-circle corner crack length of a₂ = 15 mm. Furthermore, several crack configurations are considered where the normalized vertical and horizontal gaps between the two cracks are taken to be H/a₂ = 0.4 and 1.2 and S/a₂ = −0.5 and 1.0, respectively. The results show that the effect of the quarter-circle corner crack on the SESC can be considerable both in amplifying and in attenuating the SIFs along the semi-elliptical surface crack front. Moreover, these opposite effects can occur simultaneously, but in different sections of the SESC’s crack front. The magnitude and pattern of these effects depend on the length and ellipticity of the SESC. It is further concluded that when considering the fitness-for-service of a critical real mechanical component, a complete 3-D analysis is needed to provide a reliable solution for such crack configurations. Full article

The Philippines experiences intense rainfall but has limited ground-based monitoring infrastructure for flood prediction. Satellite rainfall products provide broad coverage but contain systematic biases that reduce operational usefulness. This study evaluated whether three correction methods—Quantile Mapping (QM), Random Forest (RF), and Hybrid Ensemble—maintain accuracy when applied to future periods with substantially different rainfall characteristics. Using the Cagayan de Oro River Basin in Northern Mindanao as a case study, models were trained on 2019–2020 data and tested on an independent 2021 period exhibiting 120% higher mean rainfall and 33% increased rainy-day frequency. During training, Random Forest and Hybrid Ensemble substantially outperformed Quantile Mapping (R² = 0.71 and 0.76 versus R² = 0.25 for QM). However, when tested under realistic operational constraints using seasonally incomplete calibration data (January–April only), performance rankings reversed completely. Quantile Mapping maintained operational reliability (R² = 0.53, RMSE = 5.23 mm), while Random Forest and Hybrid Ensemble failed dramatically (R² dropping to 0.46 and 0.41, respectively). This demonstrates that training accuracy poorly predicts operational reliability under changing rainfall regimes. Quantile Mapping’s percentile-based correction naturally adapts when rainfall patterns shift without requiring recalibration, while machine learning methods learned magnitude-specific patterns that failed when conditions changed. For flood early warning in data-limited basins with equipment failures and variable rainfall, only Quantile Mapping proved operationally reliable. This has practical implications for disaster risk reduction across the Philippines and similar tropical regions where standard validation approaches may systematically mislead model selection by measuring calibration performance rather than operational transferability. Full article

Conventional sensing expends energy at three stages: powering dedicated sensors, transmitting measurements, and executing computationally intensive inference. Wireless sensing re-purposes WiFi channel state information (CSI) inherent in every packet, eliminating extra sensors and uplink traffic, though reliance on deep neural networks (DNNs) often trained and run on graphics processing units (GPUs) can negate these gains. This review highlights two core energy efficiency levers in CSI-based wireless sensing. First ambient CSI harvesting cuts power use by an order of magnitude compared to radar and active Internet of Things (IoT) sensors. Second, integrated sensing and communication (ISAC) embeds sensing functionality into existing WiFi links, thereby reducing device count, battery waste, and carbon impact. We review conventional handcrafted and accuracy-first methods to set the stage for surveying green learning strategies and lightweight learning techniques, including compact hybrid neural architectures, pruning, knowledge distillation, quantisation, and semi-supervised training that preserve accuracy while reducing model size and memory footprint. We also discuss hardware co-design from low-power microcontrollers to edge application-specific integrated circuits (ASICs) and WiFi firmware extensions that align computation with platform constraints. Finally, we identify open challenges in domain-robust compression, multi-antenna calibration, energy-proportionate model scaling, and standardised joules per inference metrics. Our aim is a practical battery-friendly wireless sensing stack ready for smart home and 6G era deployments. Full article

Background: Food allergy is a leading cause of severe allergic reactions in children and often results in restrictive elimination diets. The oral food challenge (OFC) remains the diagnostic gold standard but is resource-intensive and carries a risk of adverse reactions. This study aimed to identify epidemiological, clinical, and laboratory predictors of OFC outcomes and reaction severity in children with suspected immediate-type food allergies. Methods: We conducted a retrospective review of 148 children who underwent hospital-based, open OFCs due to suspected immediate-type food reactions. Data on demographics, comorbidities, characteristics of the initial reaction, sensitisation profiles (specific IgE [sIgE], skin prick test [SPT]), and OFC outcomes were analysed. Reactions were graded using the Ring and Messmer scale. Results: OFC was positive in 44 of 148 children (29.7%). However, no clinical or laboratory parameters—including prior reaction severity and the magnitude of allergy test results—were associated with the severity of reactions during OFC. Comorbidities—specifically asthma, atopic dermatitis, and allergic rhinitis—were significantly associated with a positive OFC (p < 0.01), as were elevated sIgE levels and larger SPT wheal diameters (p < 0.01 for both). The optimal thresholds for predicting a positive OFC were 0.73 IU/mL for sIgE and 3.5 mm for SPT. Conclusions: Oral food challenge (OFC) remains essential for confirming food allergies in children. Given that the severity of reactions during OFCs cannot be reliably predicted and that low cut-off values of allergy tests were identified for predicting a positive OFC outcome, OFCs should be performed in a controlled and fully equipped medical setting, particularly in children with atopic comorbidities. Full article

This study investigates the magneto-optical imaging (MOI) characteristics of weld defects under alternating magnetic field excitation. A magneto-optical sensor is employed to detect different types of weld defects, and the correlation between MOI features and magnetic field intensity is analyzed based on the Faraday magneto-optical effect. A finite element analysis (FEA) model integrated with a magnetic dipole model is established to explore the relationship between lift-off values and leakage magnetic field intensity, while clarifying the connection between magnetic flux leakage (MFL) signals and defect size as well as type. The results demonstrate that defects of varying sizes and types generate distinct MFL intensities. Meanwhile, in the MOI-based nondestructive testing (NDT) experiments, the gray values of MO images corresponding to defects of different sizes and types exhibit significant differences, indicating that the gray values of MO images can reflect the magnitude of leakage magnetic field defects. This research lays a theoretical foundation for industrial MOI nondestructive testing and provides clear engineering guidance for defect detection. Full article

With the increasing frequency of precipitation events under global warming, understanding rainfall-induced disruptions to urban mobility has become increasingly important. While prior studies primarily focus on road traffic, the lagged and threshold effects of rainfall on urban rail transit (URT) passenger flow remain insufficiently explored. This study analyzes 109 days of automatic fare collection data from Tianhe District, Guangzhou, in combination with hourly meteorological records and station-level built environment attributes. A rainfall threshold-aware gradient boosting framework is proposed to capture nonlinear response regimes, and an explainable learning approach is used to quantify the relative importance of rainfall, temporal factors, and built environment characteristics. The proposed framework outperforms the baseline model, with the root mean squared error (RMSE) and mean absolute error (MAE) reduced by over 5.38% and 5.93%, respectively. Results further indicate that lagged rainfall intensity exerts the strongest influence on passenger flow variation, with impact magnitudes varying systematically across station types. These findings enhance understanding of the nonlinear, time-dependent effects of rainfall on URT demand and provide practical guidance for passenger flow management and operational planning under rainfall conditions. Full article

Background/Objectives: Sepsis is a life-threatening condition associated with high mortality. Optimal dosing strategies for β-lactam antibiotics in sepsis remain controversial, particularly in patients with renal impairment. Cefepime (CFPM) is widely used as empiric therapy; however, its appropriate initial dosing in critically ill patients is unclear. This study aimed to evaluate whether high-dose CFPM administration during the first 48 h improves survival in patients with sepsis, irrespective of renal function. Methods: This single-center, retrospective, observational study included adult intensive care unit (ICU) patients with sepsis who received CFPM as initial therapy between January 2017 and December 2024. Patients were categorized into High-dose (12 g within 48 h; 2 g every 8 h) and Low-dose (<12 g/48 h) groups. The primary outcome was ICU survival. To address confounding, inverse probability of treatment weighting (IPTW) based on serum creatinine was applied, with sensitivity analyses using 1% trimmed and stabilized IPTW. Results: Of 122 eligible patients, 84 were analyzed (High-dose: n = 27; Low-dose: n = 57). After IPTW adjustment, high-dose CFPM was significantly associated with improved ICU survival (odds ratio [OR] 5.43, 95% confidence interval [CI] 1.60–18.39, p = 0.0066). This association remained consistent in the 1% trimmed IPTW analysis (OR 4.07, 95% CI 1.19–13.97, p = 0.0256). Stabilized IPTW yielded a similar effect estimate, though without statistical significance (OR 5.43, 95% CI 0.72–41.16, p = 0.1017). Overall, results were consistent in direction and magnitude across models. Conclusions: High-dose CFPM administration during the initial 48 h was associated with improved ICU survival in patients with sepsis, independent of renal function. Full article

Introduction: Extreme precipitation events in the Ayeyarwady River Basin, Myanmar, exhibit pronounced spatiotemporal heterogeneity and non-stationarity, yet their linkages to large-scale climate oscillations remain poorly understood. Objective: This study aimed to characterize distinct rainfall regimes, quantify non-stationary extreme event dynamics, and identify teleconnections with oceanic-atmospheric variability over 66 years (1958–2023). Materials and Methods: A hybrid analytical framework integrating K-means clustering, non-stationary Generalized Pareto Distribution modeling, and wavelet coherence analysis was applied to gridded monthly precipitation data from TerraClimate. Results: Four spatiotemporal rainfall clusters were delineated, exhibiting fundamentally different monsoonal characteristics with mean seasonal peaks ranging from 188 mm to 686 mm. Extreme precipitation behavior demonstrated substantial heterogeneity, with 100-year return periods varying from 501 mm in subdued northern zones to 983 mm in hyper-intense coastal regions. Wavelet coherence analysis revealed regime-specific teleconnections: Cluster 2 exhibited the strongest ENSO influence (0.536 coherence strength, 64-month median duration, 1960 peak), while Cluster 4 demonstrated unique IOD dominance (0.479 strength, 74-month duration) extending beyond annual timescales. Teleconnection effectiveness varied substantially across regimes (0.428–0.536 strength) with significant decadal non-stationarity. Limitations and Perspectives: Basin-wide precipitation averages obscure critical regional variations in extreme event magnitudes and climate forcing mechanisms, necessitating regime-differentiated approaches for flood risk assessment and climate-informed water resources management in Myanmar’s most vital river basin. Full article

Heat stress represents a pervasive welfare challenge for beef cattle and other species in tropical and subtropical regions. While its physiological and production impacts are well-documented, quantitative measures of the welfare impact of heat stress remain absent. This study provides the first quantification of the welfare impact of heat stress in beef cattle (mostly Nelore), estimated as cumulative time in thermal discomfort of four intensities (Annoying, Hurtful, Disabling, Excruciating) using the Welfare Footprint Framework. We analyzed climate data from 636 locations over five years across major beef production areas in Brazil, Argentina, Colombia, Paraguay, and Uruguay. Daily heat stress episodes and chronic heat stress exposure were assessed, respectively, using Comprehensive Climate Index (CCI) levels and the Annual Thermal Load metric, which sums daily excesses above a threshold of thermal comfort (CCI = 30 °C) throughout the year, classifying locations into five risk categories. Welfare impacts were estimated for thirteen heat stress scenarios modeled by considering each CCI level within each thermal risk category. Beef cattle in moderate-risk regions were estimated to experience primarily mild thermal discomfort for an average of 5 h daily. This duration increased to an average of 7 h daily in high-risk areas, of which 4.5 h in moderate to intense thermal discomfort (Hurtful or higher). Very high-risk regions reached 10 h of daily thermal discomfort, while extreme-risk regions showed beef cattle facing heat stress for over 11 h on 307 days annually, including over 3 h per day under severe thermoregulatory effort. Overall, 65% of animals were in regions of high thermal risk or above, experiencing between 280 and 2800 h annually in moderate to intense thermal discomfort—a magnitude that places heat stress among the most significant welfare challenges in animal production. Shade provision reduced time in severe discomfort of Disabling intensity by 85% (from 578 to 83 h annually), with economic returns of US$12–16 per animal and payback periods of approximately 16 months. By quantifying welfare impacts as cumulative time in thermal discomfort, shade provision emerges as one of the most effective welfare interventions available for beef cattle, and likely other grazing ruminants, in tropical and subtropical regions. Full article

Foodborne pathogens remain a major global concern, demanding rapid, accessible, and determination technologies. Conventional methods, such as culture assays and polymerase chain reaction, offer high accuracy but are time-consuming for on-site testing. This study presents a portable, smartphone-assisted dual-mode biosensor that combines colorimetric and photothermal speckle imaging for improved sensitivity in lateral flow assays (LFAs). The prototype device, built using low-cost components ($500), uses a Raspberry Pi for illumination control, image acquisition, and machine learning-based signal analysis. Colorimetric features were derived from normalized RGB intensities, while photothermal responses were obtained from speckle fluctuation metrics during periodic plasmonic heating. Multivariate linear regression, with and without LASSO regularization, was used to predict Salmonella concentrations. The comparison revealed that regularization did not significantly improve predictive accuracy indicating that the unregularized linear model is sufficient and that the extracted features are robust without complex penalization. The fused model achieved the best performance (R² = 0.91) and consistently predicted concentrations down to a limit of detection (LOD) of 10⁴ CFU/mL, which is one order of magnitude improvement of visual and benchtop measurements from previous work. Blind testing confirmed robustness but also revealed difficulty distinguishing between negative and 10³ CFU/mL samples. This work demonstrates a low-cost, field-deployable biosensing platform capable of quantitative pathogen detection, establishing a foundation for the future deployment of smartphone-assisted, machine learning-enabled diagnostic tools for broader monitoring applications. Full article

This study examines the determinants of goodwill impairment recognition under IFRS 3 in the context of Moroccan listed firms. Using an unbalanced panel covering the period of 2006–2024 and comprising 862 firm-year observations, we employ a three-stage empirical strategy that integrates a Probit model to estimate the likelihood of impairment, a Tobit model to assess the magnitude of the loss, and a Heckman two-step procedure to correct for potential self-selection. The results show that goodwill impairment reflects key economic and financial fundamentals, including revenue growth, book-to-market ratios, and operating performance. However, both real and accrual-based earnings management significantly influence the probability and intensity of impairment, particularly through abnormal cash flows and income-smoothing behavior. Discretionary accruals become significant only after correcting for selection bias, indicating that they do not drive the recognition decision but contribute to determining the size of the impairment once it has been recorded. The findings are robust across multiple specifications and contribute to the broader literature on financial reporting quality under IAS/IFRS, while enriching empirical evidence on managerial discretion and earnings management in emerging-market environments. Full article

Maize is a water-intensive crop widely cultivated in temperate regions, where irrigation practices strongly influence its environmental performance. This study applies Life Cycle Assessment (LCA) to compare the environmental impacts of surface and drip irrigation for maize green silage production in the Po Valley (Italy), following ISO 14040/44 standards and adopting a cradle-to-farm-gate perspective. Results show that, compared to drip irrigation, surface irrigation leads to lower impacts in 14 out of 15 categories, with reductions ranging from −0.2% (marine eutrophication) to −61% (human toxicity, non-cancer), particularly for human toxicity and resource use due to lower diesel and infrastructure requirements. Conversely, drip irrigation achieves a 58% reduction in water use thanks to its higher irrigation efficiency. The single-score assessment highlights water use as the key differentiating factor, positioning drip irrigation as preferable under scenarios of water scarcity. Contribution and sensitivity analyses confirm that nitrogen fertiliser use and mechanisation are major hotspots, while yield variation (±30%) significantly affects the magnitude of results. These findings emphasise a clear trade-off: surface irrigation shows a lower environmental burden across most impact categories, whereas drip irrigation strongly reduces water scarcity impacts and provides robust, site-specific evidence to guide sustainable irrigation strategies in intensive maize systems. Full article

Bovine gammaherpesvirus 4 (BoGHV-4) is an opportunistic uterine pathogen whose reactivation is associated with postpartum inflammation and bacterial lipopolysaccharide (LPS). Platelet-rich plasma (PRP) is a regenerative biotherapeutic capable of modulating inflammatory responses, although its effects may vary depending on BoGHV4 genotype. In this study, primary bovine endometrial cells (BECs) were cultured in medium containing 10% PRP instead of fetal bovine serum, infected with two genetically divergent BoGHV-4 isolates (07-435, genotype 3; 10-154, genotype 2), and subsequently stimulated with bacterial lipopolysaccharide (LPS, 100 ng/mL). Expression of the viral immediate-early gene IE-2 and host immune genes (TLR4, TNF-α, CXCL8, and IFN-γ) were quantified by RT-qPCR from 4 to 48 h after stimulation. Isolate 07-435 induced a sustained activation of IE-2 and gradual cytokine upregulation, while isolate 10-154 elicited an early but transient inflammatory response followed by gene downregulation. PRP did not modify the strain-specific patterns of viral and inflammatory gene expression but established a common inflammatory baseline, whereas the magnitude and temporal profile of the response continued to be dictated by the viral genotype. These findings indicate that BoGHV-4 genotypic diversity remained the main determinant of response intensity and duration, supporting PRP as a context-dependent rather than a universal antiviral modulator. Full article

Background. This study aimed to quantify differences in the internal training load (ITL) of an elite rink hockey (RH) team across days within and between three types of microcycles: pre-season, in-season regular, and in-season congested, to provide insights to optimise microcycle scheduling. Methods. One international-level male RH team comprising seven outfielders (29.6 ± 4.7 years; height, 178.9 ± 2.3 cm; body mass, 77.8 ± 5.7 kg) and one goalkeeper (32 years; height, 180.4 cm; body mass, 83.6 kg) was monitored for 21 microcycles. The ITL was assessed using the session rate of perceived exertion (sRPE) and quantified as time based on a triphasic classification commonly utilised in team sports: low-intensity training (LIT, <80% heart rate maximum (HRmax)), medium-intensity training (MIT, 80–90% HRmax), and high-intensity training (HIT, >90% HRmax). Generalized estimating equations were used to examine differences across within-microcycle training days and between seasonal phases, with linear mixed models applied as sensitivity analyses. Results. Across all phases, significant day-to-day variations in ITL were observed within microcycles (all p < 0.001), with both subjective (sRPE) and objective (LIT–HIT) ITLs progressively decreasing as match days (MDs) approached, showing moderate-to-large population-averaged effects with 95% confidence intervals consistently not crossing zero. The pre-season exhibited the highest overall ITL (p < 0.001), characterised by a substantially greater sRPE and increased time spent across all intensity zones, with the largest magnitudes observed for LIT and MIT compared with the in-season phases. Conclusions. Findings suggest that an international-level RH team progressively reduced the ITL as MDs approached with the highest loads scheduled earlier within microcycles. Moreover, the pre-season had the highest ITLs. This ITL distribution may provide useful guidance for RH coaches and support staff in optimising microcycle planning. Full article

Background: Transcranial direct current stimulation (tDCS) involves the application of weak electric currents (typically 0.5–2 mA) via scalp electrodes to promote neuroplastic changes that modulate behaviour or cortical activity. Although there have been promising results in eliminating tinnitus or reducing its loudness or severity, there is also a high degree of inter-individual variability. This may be due to anatomical differences and their influence on the resulting electric field. To optimise and personalise tDCS protocols, computational electric field models based on individual clinical imaging may be utilised to give insight into the induced electric field during tDCS and inform more effective protocols for targeted stimulation. To our knowledge, there are currently no standards for current modelling or reviews which detail the optimal parameters for conducting current modelling studies for tDCS. Objectives: The aim of this review is to investigate the methodology of current modelling studies for tDCS so that informed, personalised protocols can be designed by modelling the electric field of the brain during tDCS for tinnitus. By considering the impact of individual anatomical differences on the electric field induced by tDCS, targeted protocols could be developed to reduce tinnitus loudness and severity in a systematic and predictable way. Design: The protocol for this review is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Checklist. Using online databases, records were identified based on a keyword search for records relevant to current modelling for tDCS, including peer-reviewed papers, clinical trials, the grey literature, theses, dissertations, and conference abstracts. Four thousand two hundred and fifty-three records were retrieved from thirteen online databases and include 4186 records from the initial search completed between May and July 2024, and 67 records from an updated search completed in August 2025. A further 596 records were retrieved from Google Scholar (501 from the initial search and 95 from the updated search). One hundred and fourteen records met our criteria for inclusion. Each record was charted by two separate reviewers, with attention to the modelling pipeline and predicted values in peak and range of electric field magnitude. Results: There was a consensus that, despite model parameters and pipelines, there was inter-individual variability in the predicted electric fields. The reviewed records highlighted the impact of individual differences, including age, sex, and anatomical variation, on the predicted electric field during tDCS. Increased age was often associated with age-related brain atrophy and high relative cerebrospinal fluid volume, which was a significant influence on the resulting E-field intensity and distribution. Conclusions: When creating personalised tDCS protocols for tinnitus, the model parameters and sources of variability (i.e., morphology, age, and sex) should be carefully considered to achieve the desired stimulation outcomes, particularly in regard to applied current intensity. Full article