Search Results (76,314)

Background/Objectives: Developmental Coordination Disorder (DCD) affects approximately 5% of children globally and is characterized by motor difficulties that can negatively impact physical activity levels and increase the risk of obesity. Understanding the behavioral and physiological profiles of children with DCD is essential for early intervention. This cross-sectional study compared physical activity, dietary habits, and obesity indicators between children with DCD and their typically developing (TD) peers. Methods: A total of 243 children (134 boys, 109 girls) aged 6.65 to 11.65 years (M = 9.50, SD = 1.38) from two mainstream schools in the Chartered Community of Navarre, Spain, participated in the study. Children with conditions that could explain poor motor development were excluded based on DSM-5 Criterion D. Motor competence was evaluated using the FUNMOVES (n = 243) and MABC-2 tools (n = 49). Physical activity was assessed using the Physical Activity Questionnaire for Children (PAQ-C), dietary habits with the Krece Plus questionnaire, and obesity indicators through bioimpedance analysis (Body Mass Index and body fat percentage). Regression analyses were adjusted for age and sex. Results: Children classified with probable DCD (pDCD) using FUNMOVES showed significantly higher BMI (95% CI: 0.96 to 4.30 kg/m²) and body fat percentage (95% CI: 3.99 to 10.24%) than TD peers. Differences in physical activity were not statistically significant between DCD and TD (95% CI: −0.68 to 0.01. No significant differences were found in dietary quality. When assessing motor development with MABC-2, the results followed similar trends but lacked statistical significance. Conclusions: Children with DCD are at increased risk of overweight and obesity, primarily due to lower physical activity rather than dietary differences. Early identification and targeted interventions are essential to promote healthier lifestyles in this population. Full article

To facilitate the high-value utilization of reclaimed asphalt pavement (RAP), this study investigated the efficacy of fine separation technology as a pre-treatment method. This technology significantly reduced the variability of RAP, controlling the coefficients of variation for asphalt content and aggregate gradation within 5% and 10%, respectively, and minimized false particle content (agglomerates of fines and aged asphalt). Response Surface Methodology (RSM) was employed to optimize the mix design for ultra-high-RAP- content mixtures (50–70%). A predictive regression model was developed to determine the Optimal Binder Content (OBC) based on RAP and rejuvenator dosage. The road performance of the resulting mixtures was comprehensively evaluated. Results showed that the technology markedly enhanced the overall performance of recycled asphalt mixtures. While high-temperature rutting resistance improved with increasing RAP content, low-temperature performance declined. The mixture with 70% RAP failed to meet low-temperature cracking requirements. Consequently, an optimal RAP content of 60% is recommended. Furthermore, the generalized sigmoidal model effectively constructed dynamic modulus master curves, accurately predicting the viscoelastic behavior of these ultra-high-RAP mixtures. This study demonstrates that fine separation is a critical pre-processing step for reliably producing high-quality, sustainable asphalt mixtures with RAP content far exceeding conventional limits. Full article

In China, most of the ancient wooden structure mortise and tenon buildings, under the long-term upper load, have columns with surface surfaces that have varying degrees of damage, which need to be repaired and strengthened urgently, but the theory related to CFRP, mortise size, and pre-damage simulation still needs to be deeply studied. To investigate the effects of CFRP reinforcement layers, cross-sectional area of concealed tenons as the projected area after installation, and tenon engagement length as the axial length after installation on the axial compressive mechanical properties of pre-damaged quad-segment spliced Pinus sylvestris var. mongolia composited wooden columns, axial compression failure tests were conducted on 10 specimens following pre-damage simulation and CFRP strengthening. The experimental program yielded comprehensive data, including observations, mechanical analyses, load-displacement curves, load-strain curves, ultimate load-bearing capacities, ductility coefficients, and stiffness values. The results demonstrate that with consistent tenon cross-sectional area and engagement length, increasing CFRP layers from 1 to 3 raises the ultimate bearing capacity from 472.3 kN to 620.3 kN and improves the ductility coefficient from 4.67 to 7.95, clearly indicating that CFRP reinforcement significantly enhances axial compressive performance while effectively mitigating brittle failure. When maintaining constant CFRP layers and tenon cross-sectional area, extending the tenon engagement length from 30 mm to 90 mm elevates the bearing capacity from 494.95 kN to 546.3 kN and boosts the ductility coefficient from 5.58 to 7.95. In contrast, with fixed CFRP layers and engagement length, expanding the tenon cross-sectional area from 360 mm² to 810 mm² produces only marginal bearing capacity improvement from 548.2 kN to 556.2 kN with ductility coefficients ranging between 4.67 and 5.56, conclusively revealing that tenon engagement length has substantially greater influence on mechanical properties than cross-sectional area. The optimal axial compressive performance configuration combines 3 CFRP layers, an 810 mm² tenon cross-section, and a 90 mm engagement length.   Full article

Background: The diagnosis and treatment of esophageal cancer often leads to complex and long-lasting psychological distress, such as anxiety and depression, in patients and their partners. This psychological distress can not only potentially worsen the poor prognosis of the disease, but also reduce health-related quality of life by affecting the patient’s ability to function and enjoy life. Objectives: These preliminary data were collected to identify the components required for the development of a health education program pertaining to improving psychological distress. Methods: A narrative review. Results: Two components, diet and physical activity, were identified as important factors for the well-being of esophageal cancer patients and their partners with psychological distress. Moreover, behavioral activation was assumed to be an effective approach for assisting esophageal cancer patients’ behavioral compliance with the given dietary intake and physical activity practices program. Conclusions: A health education program based on the above components (diet and physical activity) with a behavioral activation approach could be developed as a guideline to address the problem of psychological distress among esophageal cancer patients and their partners. However, these conclusions should be treated with caution, given that the findings have not yet been empirically tested. Further rigorous studies are required to confirm their effectiveness and determine which program components may be most effective in improving outcomes. Full article

Rising household carbon emissions (HCEs) substantially increase residential energy consumption. This review evaluates the four principal quantification methods: Emission Coefficient Method (ECM), Input–Output Analysis (IOA), Consumer Lifestyle Approach (CLA), and Life Cycle Assessment (LCA). The methods are compared according to data requirements, uncertainty levels, and scale suitability. The study synthesizes multidimensional determinants—including household income, household size, urbanization, energy intensity and composition, population aging, and household location—and translates these insights into behavior-informed mitigation pathways grounded in behavioral economics principles. Combining compact-city planning, targeted energy-efficiency incentives, and behavior-nudging measures can reduce HCEs without compromising living standards, providing local governments with an actionable roadmap to carbon neutrality. Full article

For aquaculture systems, maximizing feed efficiency is a major challenge since it directly affects growth rates and economic sustainability. Feed is one of the largest costs in aquaculture, and feed waste is a significant environmental issue that requires effective management strategies. This paper suggests a novel approach for optimal fish feeding in pond aquaculture systems that integrates vision language models (VLMs), optical flow, and advanced image processing techniques to enhance feed management strategies. The system allows for the precise assessment of fish needs in connection to their feeding habits by integrating real-time data on biomass estimates and water quality conditions. By combining these data sources, the system makes informed decisions about when to activate automated feeders, optimizing feed distribution and cutting waste. A case study was conducted at a profit-driven tilapia farm where the system had been operational for over half a year. The results indicate significant improvements in feed conversion ratios (FCR) and a 28% reduction in feed waste. Our study found that, under controlled conditions, an average of 135 kg of feed was saved daily, resulting in a cost savings of approximately $1800 over the course of the study. The VLM-based fish feeding behavior recognition system proved effective in recognizing a range of feeding behaviors within a complex dataset in a series of tests conducted in a controlled pond aquaculture setting, with an F1-score of 0.95, accuracy of 92%, precision of 0.90, and recall of 0.85. Because it offers a scalable framework for enhancing aquaculture resource use and promoting sustainable practices, this study has significant implications. Our study demonstrates how combining language models and image processing could transform feeding practices, ultimately improving aquaculture’s environmental stewardship and profitability. Full article

Unconventional natural gas development requires a deeper insight into how CH₄ and CO₂ adsorb and diffuse in the pores of coal seams. Graphene (GRA) is frequently employed in microscopic mechanism simulations on coal surfaces because its structure closely resembles that of the coal seam matrix. In this study, molecular dynamics simulations were conducted to systematically investigate the diffusion, adsorption, and desorption behaviors of CH₄ and CO₂ within the pore system of hydrated graphene under three representative temperature and pressure conditions: 190 K-6 MPa, 298 K-0.1 MPa, and 320 K-8 MPa. The results show that heatinfg and depressurization significantly enhance the diffusion ability of gas molecules and promote their desorption from the graphene surface. Low temperature and high pressure are conducive to the formation of a stable adsorption layer, and more hydrogen bond structures are formed between CO₂ and water. However, under high-temperature conditions, this ordered structure is significantly weakened. The density distribution further reveals the spatial distribution characteristics of water molecules and gases and their evolution trends with changes in temperature and pressure. This research is conducive to a deeper understanding of the multiphase behavior of coalbed methane and its regulatory mechanism, providing theoretical support for the gas storage and displacement processes. Full article

This study presents a three-dimensional numerical analysis of natural convection during the postharvest storage of corn and wheat in a galvanized steel silo with a conical roof and floor, measuring 3 m in radius and 18.7 m in height, located in the Bajío region of Mexico. Simulations were carried out specifically for December, a period characterized by cold ambient temperatures (10–20 °C) and comparatively lower solar radiation than in warmer months, yet still sufficient to induce significant heating of the silo’s metallic surfaces. The governing conservation equations of mass, momentum, energy, and species were solved using the finite volume method under the Boussinesq approximation. The model included grain–air sorption equilibrium via sorption isotherms, as well as metabolic heat generation: for wheat, a constant respiration rate was assumed due to limited biochemical data, whereas for corn, respiration heat was modeled as a function of grain temperature and moisture, thereby more realistically representing metabolic activity. The results, obtained for December storage conditions, reveal distinct thermal and hygroscopic responses between the two grains. Corn, with higher thermal diffusivity, developed a central thermal core reaching 32 °C, whereas wheat, with lower diffusivity, retained heat in the upper region, peaking at 29 °C. Radial temperature profiles showed progressive transitions: the silo core exhibited a delayed response relative to ambient temperature fluctuations, reflecting the insulating effect of grain. In contrast, grain at 1 m from the wall displayed intermediate amplitudes. In contrast, zones adjacent to the wall reached 40–41 °C during solar exposure. In comparison, shaded regions exhibited minimum temperatures close to 15 °C, confirming that wall heating is governed primarily by solar radiation and metal conductivity. Axial gradients further emphasized critical zones, as roof-adjacent grain heated rapidly to 38–40 °C during midday before cooling sharply at night. Relative humidity levels exceeded 70% along roof and wall surfaces, leading to condensation risks, while core moisture remained stable (~14.0% for corn and ~13.9% for wheat). Despite the cold ambient temperatures typical of December, neither temperature nor relative humidity remained within recommended safe storage ranges (10–15 °C; 65–75%). These findings demonstrate that external climatic conditions and solar radiation, even at reduced levels in December, dominate the thermal and hygroscopic behavior of the silo, independent of grain type. The identification of unstable zones near the roof and walls underscores the need for passive conservation strategies, such as grain redistribution and selective ventilation, to mitigate fungal proliferation and storage losses under non-aerated conditions. Full article

Mechanical models are capable of simulating the deformation and stress distribution of oocytes under external forces, thereby providing insights into the underlying mechanisms of intracellular mechanical responses. Interactions with micromanipulation tools involve forces like compression and punction, which are effectively analyzed using principles of solid mechanics. Alternatively, fluid–structure interactions, such as shear stress at fluid junctions or pressure gradients within microchannels, are best described by a multiphase flow model. Developing the two models instead of a single comprehensive model is necessary due to the distinct nature of cell–tool interactions and cell–fluid interactions. In this study, we developed a finite element (FE) model of porcine oocytes that accounts for the viscoelastic properties of the zona pellucida (ZP) and cytoplasm for the case when the oocytes interacted with a micromanipulation tool. Atomic force microscopy (AFM) was employed to measure the Young’s modulus and creep behavior of these subcellular components that were incorporated into the FE model. When the oocyte was solely interacting with the fluids, we simulated oocyte deformation in microfluidic channels by modeling the oocyte-culture-medium system as a three-phase flow, considering the non-Newtonian behavior of the oocyte’s components. Our results show that the Young’s modulus of the ZP and cytoplasm were determined to be 7 kPa and 1.55 kPa, respectively, highlighting the differences in the mechanical properties between these subcomponents. Using the developed layered FE model, we accurately simulated oocyte deformation during their passage through a narrow-necked micropipette, with a deformation error of approximately 5.2% compared to experimental results. Using the three-phase flow model, we effectively simulated oocyte deformation in microfluidic channels under various pressures, validating the model’s efficacy through close agreement with experimental observations. This work significantly contributes to assessing oocyte quality and serves as a valuable tool for advancing cell mechanics studies. Full article

Old airplanes produced in the 1970s are still flying, while being exposed to various new types of detriments, leading to a need to repair them to enable the safe use of the airborne body. The present state of the art advocates the use of laminated composite to repair aluminum parts due to their effective durability. The studies presented in the literature mainly focused on bodies under tensile loads. It seems that shear-type loading appearing in the fuselage of airplanes when being under torsion has been ignored in literature. Therefore, to fill this gap, the present study investigates the behavior of defective aluminum panels under pure shear. The present investigation uses a novel finite element (FE) method of modelling the loaded body by 2D and 3D elements. Then, the model is used to calculate the influence of various parameters, like the size of the repair patch, overlaps, sequences of the laminated composite plate, and other structural properties on the stability and strength of the examined part. To validate the numerical predictions, tests were performed on typical elements. Based on the experimental results, the fidelity of the FE model was assessed and the method approach of repairing using composite patches was validated. The main conclusion from the present study is the use of solid (3D) elements, over shell (2D) elements, due to their high-fidelity results. Full article

Lithium plating (LP), as a specific degradation mechanism in lithium-ion batteries (LIBs), has been thoroughly investigated regarding formation conditions and potential safety hazards, but it is yet unknown how this effect influences the mechanical properties of batteries in the case of mechanical deformation. To address this issue, pouch cells used in EVs were artificially aged (AA) to a state of health of 80–82% in conditions that predominantly cause the formation of LP. These cells were subjected to a mechanical abuse load, and safety-relevant parameters, such as tolerated deformation level, failure force, and the process of thermal runaway (TR), were analyzed and compared with respective fresh (F) and aged cells of the same type. Complementary microscopy analyses were carried out to compare the found changed mechanical response with the different layer morphology caused by LP. The tests did exhibit a significantly different mechanical response of cells in the three states but also clearly altered short-circuiting behavior. The tolerated peak force at discharge state dropped by −28% and at charge state by −37% compared to fresh cells, while the deformation at failure slightly increased by +6% for the AA cells. A clear reduction in stiffness (−16%) of the LP cells was attributed to the formed layer, identified as mossy LP. The significantly stronger voltage drop at failure, seen for the LP cells, was associated with severe exothermal reactions of LP in contact with air and moisture during TR. This study revealed the strong influence of LP on the mechanical properties of LIBs. However, the transferability of the findings to other cell chemistries or formats is unclear, emphasizing the need for further investigations in this research field. Full article

The rise of financial technology (FinTech) has generated substantial research on its adoption by customers and the associated implications for traditional banks. This systematic review addresses two questions: (1) What factors enable or hinder consumer adoption of FinTech? (2) How does consumer adoption of FinTech affect the performance of traditional banks? Following the PRISMA guidelines, we screened and analyzed 109 peer-reviewed articles published between 2016 and 2024 in Scopus and Web of Science. The findings show that adoption is driven by economic incentives, digital infrastructure, personalized services, and institutional support, while barriers include limited literacy, perceived risk, and regulatory uncertainty. At the bank level, adoption enhances operational efficiency, customer loyalty, and revenue growth but also generates compliance costs, cybersecurity risks, and competition. Consumer adoption studies primarily employ the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), often extended with trust and privacy constructs. In contrast, bank performance research relies on empirical analyses with limited theoretical grounding. This review bridges behavioral and institutional perspectives by linking consumer-level drivers of adoption with organizational outcomes, offering an integrated conceptual framework. The limitations include a restriction of the retrieved literature to English publications in two databases. Future work should apply longitudinal, multi-theory models to deepen the understanding of how consumer behavior shapes bank performance. Full article

It has been shown previously that repeated positive fighting experience in daily agonistic interactions is accompanied by the development of psychosis-like behavior, with signs of an addiction-like state associated with changes in the expression of genes encoding the proteins involved in the main neurotransmitter events in some brain regions of aggressive male mice. Fighting deprivation (a no-fight period of 2 weeks) causes a significant increase in their aggressiveness. This paper is aimed at studying—after a period of fighting deprivation—the involvement of genes (associated with neurotransmitter systems within the nucleus accumbens) in the above phenomena. The nucleus accumbens is known to participate in reward-related mechanisms of aggression. We found the following differentially expressed genes (DEGs), whose expression significantly differed from that in controls and/or mice with positive fighting experience in daily agonistic interactions followed by fighting deprivation: catecholaminergic genes Th, Drd1, Drd2, Adra2c, Ppp1r1b, and Maoa; serotonergic genes Maoa, Htr1a, Htr1f, and Htr3a; opioidergic genes Oprk1, Pdyn, and Penk; and glutamatergic genes Grid1, Grik4, Grik5, Grin3a, Grm2, Grm5, Grm7, and Gad1. The expression of DEGs encoding proteins of the GABAergic system in experienced aggressive male mice mostly returned to control levels after fighting deprivation, except for Gabra5. In light of the conceptual paradigm for analyzing data that was chosen in our study, the aforementioned DEGs associated with the behavioral pathology can be considered responsible for consequences of aggression followed by fighting deprivation, including mechanisms of an aggression relapse. Full article

Gallstone disease affects approximately 10–20% of the global adult population, with early diagnosis being essential for effective treatment and management. While image-based machine learning (ML) models have shown high accuracy in gallstone detection, tabular data approaches remain less explored. In this study, we have proposed a Random Forest (RF) classifier optimized using the Sand Cat Swarm Optimization (SCSO) algorithm for gallstone prediction based on a tabular dataset. Our experiments have been conducted across four frameworks: only RF without cross-validation (CV), RF with CV, RF-SCSO without CV, and RF-SCSO with CV. Only RF without CV model has achieved 81.25%, 79.07%, 85%, and 73.91% accuracy, F-score, precision, and recall, respectively, using all 38 features, while the RF with CV has obtained a 10-fold cross-validation accuracy of 78.42% using the same feature set. With SCSO-based feature reduction, the RF-SCSO without and with CV models have delivered a comparable accuracy of 79.17% and 78.32%, respectively, using only 13 features, indicating effective dimensionality reduction. SHAP analysis has identified CRP, Vitamin D, and AAST as the most influential features, and DiCE has further illustrated the model’s behavior by highlighting corrective counterfactuals for misclassified instances. These findings demonstrate the potential of interpretable, feature-optimized ML models for gallstone diagnosis using structured clinical data. Full article

Light pollution is becoming more widespread every year, accompanied by the active use of LED lighting. Currently, the ability of organisms to adapt to this pollution and the potential impact of LED lighting of different color temperatures and intensities on organisms remains poorly understood. In this study, we aimed to find out how long-term light pollution affects the behavior of amphipods Gammarus lacustris, and to compare their locomotor activity under different lighting conditions, taking into account the factor of shelter from light. The response of individuals was compared in group and individual experiments under daylight, without light, warm and cold LED light up to 30 lx. The individuals were from two populations: the first is not exposed to light pollution (lake No. 14), while the second is affected (the Angara River within the city of Irkutsk). The locomotor activity of amphipods was assessed in daylight, without light, warm and cold light of 2–2.5 lx and 10–11 lx in the presence and absence of shelters from light. As a result of the experiments, adaptive changes in the reaction of G. lacustris to warm light were identified in individuals from the Angara River. The importance of LED light color temperature and warm light intensity in determining amphipod response to light was also confirmed. It was found that warm and cold light have different effects on the behavior of G. lacustris, and the presence of shelters from light can reduce the negative impact of light pollution in natural conditions. Full article