Search Results (270)

Background/Objectives: Childhood cancer leads to significant physical, cognitive, and psychosocial consequences that adversely affect the development and quality of life. Occupational Therapy (OT) has the potential to mitigate these effects. However, its integration into pediatric oncology care in Spain remains limited and underexplored. This study aims to examine the availability, characteristics, and perceived impact of OT services within pediatric oncology units across Spain and to identify key barriers to their implementation. Methods: A descriptive, cross-sectional study using a mixed-methods approach was conducted. An online questionnaire was distributed to healthcare professionals working in pediatric oncology units nationwide. Quantitative data were analyzed using descriptive statistics, Fisher’s exact test, and odds ratios with 95% confidence intervals to explore associations. Effect sizes were calculated using Cramér’s V where applicable. Qualitative responses underwent inductive thematic analysis. Results: A total of 42 hospital centers from 12 autonomous communities participated. Only 16 reported having OT services in pediatric oncology, with notable regional disparities. A significant proportion of respondents were unaware of the integration of OT in their institutions. Identified barriers included lack of resources, insufficient specialized training, and limited institutional recognition of OT. Nonetheless, professionals familiar with OT interventions reported positive outcomes, particularly in improving patients’ functional autonomy, emotional well-being, and social participation. Conclusions: OT remains insufficiently integrated into pediatric oncology care in Spain. To optimize the quality of care, it is essential to address educational, structural, and institutional challenges and promote OT as a key component of multidisciplinary teams. Full article

Based on the engineering background of a new type of segmental-assembled steel temporary beam buttress, the fatigue strength evaluation method of the steel box girders with open longitudinal ribs was taken as the research objective. The fatigue stress calculation analysis and the full-scale fatigue loading test for the steel box girder local component were carried out. The accuracy of the finite-element model was verified by comparing it with the test results, and the rationality of the fatigue strength evaluation methods for welded joints was deeply explored. The results indicate that the maximum nominal stress occurs at the weld toe between the transverse diaphragm and the top plate at the edge of the loading area, which is the fatigue-vulnerable location for the steel box girder local components. The initial static-load stresses at each measuring point were in good agreement with the finite-element calculation results. However, the static-load stress at the measuring point in the fatigue-vulnerable position shows a certain decrease with the increase in the number of cyclic loads, while the stress at other measuring points remains basically unchanged. According to the finite-element model, the fatigue strengths obtained by the nominal stress method and the hot-spot stress method are 72.1 MPa and 93.8 MPa, respectively. It is reasonable to use the nominal stress S-N curve with a fatigue life of 2 million cycles at 70 MPa and the hot-spot stress S-N curve with a fatigue life of 2 million cycles at 90 MPa (FAT90) to evaluate the fatigue of the welded joints in steel box girders with open longitudinal ribs. According to the equivalent structural stress method, the fatigue strength corresponding to 2 million cycles is 94.1 MPa, which is slightly lower than the result corresponding to the main S-N curve but within the range of the standard deviation curve. The research results of this article can provide important guidance for the anti-fatigue design of welded joints in steel box girders with open longitudinal ribs. Full article

Background: While some evidence supports the benefits of food-related tasks, research examining their association with psychosocial health in adolescents remains scarce. The aim of this study was to examine the association between Spanish adolescents’ involvement in food-related household tasks and their psychosocial health. Methods: This cross-sectional study used secondary data from the original Eating Healthy and Daily Life Activities (EHDLA) study. The final sample comprised 273 boys (43.0%) and 361 girls (57.0%). Adolescents self-reported their weekly frequency of involvement in two food-related tasks: meal preparation and grocery shopping, with responses ranging from ‘never’ to ‘seven times’. Psychosocial health was assessed using the 25-item self-report version of the Strengths and Difficulties Questionnaire (SDQ), comprising five subscales: emotional problems, conduct problems, hyperactivity, peer problems, and prosocial behavior. A total difficulties score was calculated by summing the first four subscales. Generalized linear models were used to evaluate associations between the frequency of food task involvement (categorized into five levels) and SDQ outcomes. All models were adjusted for age, sex, socioeconomic status, body mass index, sleep duration, physical activity, sedentary behavior, and energy intake. Results: Concerning to the frequency of helping to prepare food for dinner, an inverse association was observed between food preparation involvement and several psychosocial problems. Adolescents who helped seven times per week reported significantly lower scores in conduct problems (B = −2.00; 95% CI −3.30 to −0.69; p = 0.003), peer problems (B = −2.83; 95% CI −4.29 to −1.38; p < 0.001), internalizing problems (B = −3.90; 95% CI −7.03 to −0.77; p = 0.015), and total psychosocial difficulties (B = −5.74; 95% CI −10.68 to −0.80; p = 0.023), compared to those who never helped. Conversely, those who helped seven times per week had higher prosocial behavior than their counterparts who never helped (B = 1.69; 95% CI: 0.14 to 3.24; p = 0.033). Regarding the frequency of helping to shop for food, similar patterns were found, with lower conduct problems (B = −2.11; 95% CI −3.42 to −0.81; p = 0.002), peer problems (B = −2.88; 95% CI −4.34 to −1.42; p < 0.001), internalizing problems (B = −4.16; 95% CI −7.28 to −1.04; p = 0.009), and total psychosocial difficulties (B = −6.31; 95% CI −11.24 to −1.39; p = 0.012) associated with more frequent involvement, especially among those who helped five or more times per week. Conversely, adolescents who helped seven times per week had higher prosocial behavior than their peers who never helped (B = 1.56; 95% CI: 0.01 to 3.11; p = 0.049). Conclusions: Although adolescent psychosocial health is influenced by multiple factors, our findings suggest that regular involvement in food-related household tasks may serve as a protective factor against conduct problems, peer problems, internalizing problems, and total difficulties, while also enhancing prosocial behavior. However, given the cross-sectional design, conclusions regarding causality should be made cautiously, and further longitudinal research is needed to confirm these associations and assess their long-term impact. These results highlight the relevance of daily structured routines, such as meal preparation and grocery shopping, as potential support for mental well-being during adolescence. Full article

Background/Objectives: Painful diabetic peripheral neuropathy (pDPN) significantly impacts quality of life, yet its diagnosis remains challenging due to reliance on subjective pain reports and limited objective biomarkers. This meta-analysis evaluated corneal nerve morphology parameters; corneal nerve fibre length (CNFL), corneal nerve fibre density (CNFD), and corneal nerve branch density (CNBD), measured through in vivo confocal microscopy (IVCM), as potential tools for differentiating painful and painless forms of diabetic neuropathy. Methods: A systematic review was performed comparing corneal nerve morphology across four groups: painful diabetic neuropathy (pDPN), non-painful diabetic neuropathy (npDPN), diabetes without neuropathy (DPN-), and healthy controls. Literature search extended over MEDLINE, EMBASE, Web of Science, and Cochrane Library, focusing on studies published since 2000. Study quality was assessed using the Newcastle–Ottawa Scale, while evidence certainly followed GRADE guidelines. Random-effects meta-analyses calculated mean differences (MDs) with 95% confidence intervals (CIs) for CNFL, CNFD, and CNBD. Results: Seven observational studies comprising 803 participants (213 pDPN, 275 npDPN, 99 DPN-, and 216 controls) revealed no significant differences between pDPN and npDPN groups in CNFL (MD = 0.79, 95% CI −0.64 to 2.22), CNFD (MD = 1.67, 95% CI −0.14 to 3.47), or CNBD (MD = 1.84, 95% CI −4.31 to 7.98). However, all metrics were markedly reduced in pDPN compared to DPN- and healthy controls. Conclusions: While effective in identifying diabetic neuropathy, common corneal nerve morphology parameters cannot reliably distinguish pDPN from npDPN. This highlights the need for research into mechanisms like central sensitization, inflammation, and micro-neuromas, which could refine diagnostic and therapeutic approaches for pDPN. Full article

Remaining Useful Life (RUL) prediction is a crucial task in predictive maintenance. Currently, gated recurrent networks, hybrid models, and attention-enhanced models used for predictive maintenance face the challenge of balancing prediction accuracy and model lightweighting when extracting complex degradation features. This limitation hinders their deployment on resource-constrained edge devices. To address this issue, we propose TBiGNet, a lightweight Transformer-based classification network model for RUL prediction. TBiGNet features an encoder–decoder architecture that outperforms traditional Transformer models by achieving over 15% higher accuracy while reducing computational load, memory access, and parameter size by more than 98%. In the encoder, we optimize the attention mechanism by integrating the individual linear mappings of queries, keys, and values into an efficient operation, reducing memory access overhead by 60%. Additionally, an adaptive feature pruning module is introduced to dynamically select critical features based on their importance, reducing redundancy and enhancing model accuracy by 6%. The decoder innovatively fuses two different types of features and leverages BiGRU to compensate for the limitations of the attention mechanism in capturing degradation features, resulting in a 7% accuracy improvement. Extensive experiments on the C-MAPSS dataset demonstrate that TBiGNet surpasses existing methods in terms of computational accuracy, model size, and memory access, showcasing significant technical advantages and application potential. Experiments on the C-MPASS dataset show that TBiGNet is superior to the existing methods in terms of calculation accuracy, model size and throughput, showing significant technical advantages and application potential. Full article

Background: Lower respiratory infections (LRIs) are the leading cause of the global disease burden, accounting for millions of deaths each year. Methods: Data on LRIs, including deaths, disability-adjusted life years (DALYs), and incidence, were obtained from the Global Burden of Disease Study 2021. Joinpoint regression was employed to assess temporal trends in the LRIs’ burden, while the age–period–cohort model was used to evaluate age, period, and cohort effects. Pearson’s correlation coefficients were calculated to examine the relationship between DALYs attributable to risk factors and the socio-demographic index (SDI). Results: Over recent decades, the average annual percentage change in age-standardized mortality rate, age-standardized DALYs rate, and age-standardized incidence rate of LRIs globally were −2.4%, −3.5%, and −1.3%, respectively. Notably, the LRIs’ burden dropped considerably from 2019 to 2021. The disease burden was higher among children under five and individuals over 60 compared to other age groups. In terms of gender, males had a higher burden. The age-standardized DALYs rate of LRIs was strongly and negatively correlated with SDI (r = −0.84; p < 0.05). Streptococcus pneumoniae remained the leading pathogen, followed by Staphylococcus aureus, and Klebsiella pneumoniae. Conclusions: In recent years, the global burden of LRIs has declined, but regional, gender, and age disparities persist. Targeted measures are needed to address high-risk populations and major risk factors. Full article

This article reviews methods for estimating the remaining service life of bridges, focusing on the statistical analysis of reliability indices, which aids in identifying risks and predicting structural failures. Among the methodologies examined, the First-Order Reliability Method (FORM) is highlighted for its effectiveness in calculating failure probabilities based on current deterioration and loading conditions. Sensitivity analysis is also discussed, as it pinpoints the variables that most significantly impact structural stability. Enhanced using the Finite Element Method (FEM), this method allows the simulation of structural behavior across different deterioration scenarios, improving the precision of failure predictions and optimizing maintenance planning. This review provides insight into how the integration of probabilistic methods and sensitivity analysis can enhance failure prediction and support more efficient maintenance planning for bridge structures. Full article

The remaining lifetime of the cable insulation is an important but hard topic for the industry and research groups as there are more and more cables nearing their designed life in China. However, it is hard to accurately and efficiently obtain the ageing characteristic parameters of cross-linked polyethylene (XLPE) cable insulation. This study systematically analyzes the evolution of the remaining insulation lifetime of XLPE cables under different ageing states using the step-stress method combined with the inverse power model (IPM) and a physical-driven model (Crine model). By comparing un-aged and accelerated-aged specimens, the step-stress breakdown tests were conducted to obtain the Weibull distribution characteristics of breakdown voltage and breakdown time. Experimental results demonstrate that the characteristic breakdown field strength and remaining lifetime of the specimens decrease significantly with prolonged ageing. The ageing parameter of the IPM was calculated. It is found that the ageing parameter of IPM increases with the ageing time. However, it can hardly link to the other properties or physic parameters of the material. The activation energy and electron acceleration distance of the Crine model were also calculated. It is found that ageing activation energy stays almost the same in samples with different ageing time, showing that it is a material intrinsic parameter that will not change with the ageing; the electron acceleration distance increases with the ageing time, it makes sense that the ageing process may break the molecule chain of XLPE and increase the size of the free volume. It shows that the Crine model can better fit the physic process of ageing in theory and mathematic, and the acceleration distance of the Crine model is a physical driven parameter that can greatly reflect the ageing degree of the cable insulation and be used as an indicator of the ageing states. Full article

The capacity estimation of lithium-ion batteries, serving as an auxiliary power source in fuel cell vessels, is crucial for ensuring system stability and enhancing operational efficiency. Accurate capacity estimation technology not only helps extend battery lifespan but also enhances the energy management and scheduling capabilities of the entire vessel. To address the challenge of accurately estimating lithium-ion battery capacity under complex operating conditions, this study extracts universal health factors from battery data under varied charging and discharging scenarios and combines these with a deep learning model to enhance prediction accuracy. First, battery data from three complex conditions are analyzed, extracting partial charge and discharge data. The distance correlation coefficient calculates the correlation between each factor and the capacity sequence, informing the priority of universal health factors. A TCN-BiGRU model is then developed, with hyperparameters determined by the Kepler optimization algorithm (KOA). Cells from a battery pack under consistent conditions are used for training, while other cells in the same pack serve as the test set. Evaluation metrics include mean absolute error (MAE) and root-mean-square error (RMSE). The testing shows that the MAE and RMSE for full-life capacity estimation remain around 1%, with most cells achieving values under 1%. The results indicate that the proposed method effectively aids in accurate capacity estimation for individual cells in complex operating environments. Full article

To investigate the mechanical behavior and damage mechanism of notch–stud connectors in timber–concrete composites under fatigue loading, fifteen push-out specimens in five groups were designed with load cycles as the key variable. Fatigue failure modes and mechanisms were analyzed to examine fatigue life, stiffness degradation, and cumulative damage laws of connectors. Numerical simulations with up to 100 load cycles explored timber/concrete damage effects on stud fatigue performance. Based on the results, an S-N curve was established, a fatigue damage model developed, and a fatigue design method proposed for such connectors. Primary failure modes were stud fracture and local concrete crushing in notches. Stiffness degradation followed an inverted “S”-shaped “fast–slow–fast” pattern. Using residual slip as the damage variable, a two-stage fatigue damage evolution model was constructed from the damage–cycle ratio relationship, offering a new method for shear connector fatigue damage calculation in timber–concrete composites and enabling remaining life prediction for similar composite beam connectors. Finite element simulations of push-out specimens showed high consistency between calculated and experimental fatigue life/damage results, validating the conclusions. Full article

In this study different strategies have been adopted to promote the shelf-life prolongation of fresh chicken nuggets. Two different by-products, grape pomace powder (GPP) and pomegranate peel extract (PE), alone and in combination with lactic acid, were suggested as meat preservatives. The antioxidant properties measured by different assays confirmed the presence of bioactive compounds in both by-products. To test their effects on meat samples, a control nugget without any compounds and a nugget with sole lactic acid were also used for comparison. During a refrigerated storage of about 2 weeks, microbiological stability and changes in sensory properties were monitored to assess the product shelf life. Results demonstrated that GPP promoted a good preservation of meat, and its combination with other compounds further increased the effectiveness. The control without any active agent remained acceptable for less than 1 day, the control with lactic acid for less than 2 days (p > 0.05). The other active samples lasted longer depending on the combinations of active compounds. When the sole GPP was used, about 3 days of shelf life were recorded (p < 0.05). While the combination of GPP with PE promoted only a slight increase of shelf life by 1 day (2.9 vs. 3.9 days), the combination of GPP with LA prolonged the shelf life to more than 6 days (2.9 vs. 6.58 days) (p < 0.05). The best results were found when both LA and PE were combined with GPP because the nuggets lasted about 10 days (p < 0.05). To better highlight the single and combined effects of the tested active agents, a proper index $\left(∆\%\right),$ comprising the normalized percent difference between the shelf life of the sample with the most antimicrobials and that of the sample with the least antimicrobials, was calculated, thus comparing the various samples and demonstrating the potential synergic effects among them. Full article

Remaining useful life (RUL) prediction of rolling bearings is of significance for improving the reliability and durability of rotating machinery. Aiming at the problem of suboptimal RUL prediction precision under cross-working conditions due to distribution discrepancies between training and testing data, enhanced cross-working condition RUL prediction for rolling bearings via an initial degradation detection-enabled joint transfer metric network is proposed. Specifically, the health indicator, called reconstruction along projection pathway (RAPP), is calculated for initial degradation detection (IDD), in which RAPP is obtained from a novel deep adversarial convolution autoencoder network (DACAEN) and compares discrepancies between the input and the reconstruction by DACAEN, not only in the input space, but also in the hidden spaces, and then RUL prediction is triggered after IDD via RAPP. After that, a joint transfer metric network is proposed for cross-working condition RUL prediction. Joint domain adaptation loss, which combines representation subspace distance and variance discrepancy representation, is designed to act on the final layer of the mapping regression network to decrease data distribution discrepancies and ultimately obtain cross-domain invariant features. The experimental results from the PHM2012 dataset show that the proposed method has higher prediction accuracy and better generalization ability than typical and advanced transfer RUL prediction methods under cross-working conditions, with improvements of 0.047, 0.053, and 0.058 in the MSE, RMSE, and Score. Full article

The spread of per- and polyfluoroalkyl substances (PFAS) in the environment poses a severe threat to soil organisms, aquatic life, and human health. Many PFAS compounds are mobile and easily transported from soils to groundwater and further to surface waters. Leaching tests are valuable tools for assessing the site-specific leaching behaviour of contaminants. Here, we report the results of an evaluation of two standardized leaching tests for PFAS-contaminated soil materials: the batch test (ISO 21268-2:2019) using either demineralized water or 1 mM CaCl₂ as leachants (liquid-to-solid (L/S) ratio of 10) and the up-flow percolation test (ISO 21268-3:2019) using 1 mM CaCl₂ as leachant. One field-contaminated soil and three spiked (12 PFAS compounds) soils (aged 5 months) were included in the study. Desorption kinetics in the batch test were fast and equilibrium was obtained for all PFAS compounds within 24 h, the prescribed equilibration time. The same solubility was obtained for short-chain PFAS (PFBA, PFHxA, PFHpA, PFBS) in demineralized water and 1 mM CaCl₂, whereas significantly lower solubility was often observed for long-chain PFAS in CaCl₂ than in water, probably due to decreased charge repulsion between soil surfaces and PFAS compounds. In the up-flow percolation test, concentrations of short-chain PFAS in leachates decreased rapidly with increasing L/S, in contrast to long-chain PFAS, where concentrations decreased gradually or remained constant. Solid–solution partitioning coefficients (K_d), calculated from the data of the batch and percolation tests (1 mM CaCl₂), were generally in agreement, although differing by more than three orders of magnitude between different PFAS compounds. Uncertainties and pitfalls when calculating K_d values from leaching test data are also explored. Full article

Background/Objectives: Autism spectrum disorder (ASD) has a wide-ranging impact on individuals’ quality of life and development, and there is a critical need for greater awareness, early intervention, and comprehensive support strategies to effectively address the unique needs of those affected by ASD. Recent studies highlight the gut microbiome’s potential role in modulating ASD symptoms via the gut–brain axis, but specific microbial biomarkers remain unclear. This study aims to investigate differences in gut microbiota composition between ASD patients and neurotypical controls in a novel approach, specifically assessing ratios of Firmicutes/Bacteroidetes (F/B), Actinobacteria/Proteobacteria (A/P), and Prevotella/Bacteroides (P/B) as potential biomarkers. Methods: We analyzed gut microbiome samples from 302 Bulgarian children and adolescents diagnosed with ASD (aged 2–19 years). Microbial ratios (F/B, A/P, and P/B) were calculated and compared against previously reported reference meta-analytic means from European neurotypical populations. The statistical significance of deviations was assessed using parametric (t-tests), non-parametric (Wilcoxon signed-rank tests), and proportion-based (binomial tests) methods. Effect sizes were quantified using Cohen’s d. Significant differences between ASD cases and neurotypical reference values were observed across several age groups. Results: Notably, children with ASD demonstrated significantly lower F/B and A/P ratios, with the youngest cohort (0–4 years) exhibiting the greatest differences. Deviations in the P/B ratio varied across age groups, with a significant elevation in the oldest group (≥10 years). Collectively, ASD cases consistently exhibited microbiota profiles indicative of dysbiosis. Conclusions: Our findings support gut microbiome dysbiosis as a potential biomarker for ASD, highlighting significantly altered bacterial ratios compared to neurotypical controls. These microbiome shifts could reflect early-life disruptions influencing neurodevelopment. Future studies should adopt longitudinal and mechanistic approaches to elucidate causal relationships and evaluate therapeutic microbiome modulation strategies. Full article

Background: Pancreatic cancer (PC), the third leading cause of cancer-related mortality globally, exhibits a persistently low five-year survival rate (13%). While the global burden of PC among individuals aged 15–59 years has declined, trends in China remain understudied. This study evaluates global and national trends in PC incidence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2021 and projects trajectories to 2045. Methods: Using data from the Global Burden of Disease (GBD) 2021 study, we calculated age-standardized rates (ASRs) for 204 countries/territories. Joinpoint (version: 5.3.0.0) regression identified temporal trends via average annual percentage changes (AAPCs), and Bayesian age-period-cohort (BAPC) modeling forecasted future burdens. Results: Globally, PC burden declined among 15–59-year-olds (AAPC for incidence: −0.8%, 95% UI: −1.2 to −0.4). However, China experienced a significant reversal after 2009, with incidence rising by 1.5% annually (95% UI: 0.9–2.1), disproportionately affecting males. Smoking (contributing to 22.2% of DALYs in China) and high fasting plasma glucose (15%) emerged as key modifiable risk factors, while elevated BMI exacerbated burdens in high SDI regions (3.1% of DALYs). Projections indicate a continued surge in China’s PC burden by 2045, particularly among males (incidence projected to increase by 50% from 2010 to 2045). Conclusions: High SDI regions exhibit concentrated PC burdens linked to lifestyle factors, whereas China’s rising trends align with healthcare expansion and metabolic disease proliferation. Targeted interventions—smoking cessation, glycemic control, and weight management—are imperative to mitigate growing burdens in younger populations. This study highlights the urgent need for region-specific strategies to address evolving epidemiological challenges in PC prevention and control. Full article