Search Results (19,973)

Background: Lifestyle factors such as diet and physical activity significantly impact on the risk of obesity in individuals with Down syndrome (DS). However, in the absence of national nutritional guidelines in individuals with DS, further work is needed to understand their dietary and physical activity patterns. In this work we retrieved caregivers’ responses on those aspects. Methods: We analyzed data from a cross-sectional online survey of caregivers of individuals with DS conducted as part of the GO-DS21 project and reported in the accompanying paper (nutrients-4216283) (n = 764). We explored physical activity patterns, dietary habits, beliefs around weight-loss interventions and caregiver confidence that family members with DS would engage in a healthier lifestyle. Associations were examined using correlation analysis, and cumulative and binary logistic regression models. Results: Caregivers reported that most individuals with DS exercised 1–3 times per week, with frequency declining with age. Males were more likely to exercise daily than females. Caregiver exercise frequency was positively correlated with that of their DS family member (ρ = 0.521, p < 0.001), suggesting clustering of shared health behaviors within households. In adjusted models, caregivers who exercised regularly had up to thirteen-fold higher odds of having a physically active family member with DS (aOR = 13.02, 95% CI: 7.40–24.06, p < 0.001). Fried food consumption and higher snack frequency were independently associated with perceived obesity status, while sugar-sweetened beverage consumption was not. Caregivers favored exercise as a weight-loss strategy, while anti-obesity drugs were endorsed by only 11% of caregivers primarily and were more likely to be endorsed when obesity was perceived (aOR = 4.21, 95% CI: 2.44–7.39, p < 0.001). Finally, caregiver confidence that their family member with DS would engage in healthier behaviors was associated with perceived obesity status and strongly associated with higher physical activity levels (aOR 14.68, 95% CI: 6.59–33.40, p < 0.001). Conclusions: In this large European caregiver survey, reported consumption of selected energy-dense foods was generally low, although fried food intake and higher snack frequency were associated with perceived obesity. Physical activity patterns were closely aligned between caregivers and individuals with DS, suggesting shared household health behaviors. These findings highlight the importance of involving caregivers and family environments in lifestyle interventions aimed at supporting physical activity and weight management in individuals with DS. Full article

Adult hippocampal neurogenesis persists throughout the human lifespan, yet declines in Alzheimer’s disease and major depression, associated in part with reduced brain-derived neurotrophic factor (BDNF) levels. For rodents, environmental enrichment, dichotomised primarily as physical activity and spatial complexity, robustly promotes adult hippocampal neurogenesis, but no framework has translated these findings to human environments. This review is the first to synthesise evidence across the full translational pathway, arguing that spatial complexity and physically active navigation in neighbourhoods and buildings constitute a humanised form of environmental enrichment. It proposes that standard indoor environments may represent a functionally impoverished condition for the human hippocampus, paralleling standard laboratory caging. An applied model is presented, mapping built environment features onto the neurobiological mechanisms regulating adult hippocampal neurogenesis, with BDNF as the central translatable biomarker linking environmental exposures to neurogenic outcomes. A methodological roadmap for future empirical validation is also outlined. This framework repositions the built environment as a modifiable determinant of adult hippocampal neurogenesis in humans, with implications for mitigating the risk of depression, cognitive impairment, and Alzheimer’s disease. Full article

Soil moisture content plays a crucial role in precision agriculture and geological hazard monitoring, driving the need for stable, reliable, and high-precision sensors. Capacitive soil moisture sensors based on Frequency Domain Reflectometry (FDR) are widely adopted due to their favorable measurement performance, yet their accuracy is highly susceptible to environmental interferences such as temperature, salinity (electrical conductivity), and soil type. This paper systematically reviews current calibration strategies addressing these three factors, classifying them into hardware-based compensation and software-based calibration (including conventional mathematical and machine learning models). Furthermore, it critically analyzes the trade-offs of these approaches in terms of robustness, scalability, and field applicability. To break through current technical limitations, this review argues that future research must prioritize the physical decoupling of multi-parameter interferences under extreme conditions. Additionally, to overcome the generalization crisis of current data-driven models, adaptive strategies utilizing techniques like transfer learning are essential. Finally, implementing Edge-AI on resource-constrained hardware is crucial for achieving calibration-free or real-time online calibration strategies, ensuring long-term measurement accuracy. Full article

Hydroponic (HP) and aquaponic (AQ) systems are widely known in greenhouse production; however, the combined effects of nutrient delivery system and substrate physical structure on crop performance and root-zone microbiomes remain insufficiently understood. Substrate physical properties influence water retention and aeration, which can affect root-associated microorganisms, plant growth, and yield. This study evaluated cucumber (Cucumis sativus L.) growth, yield, nutrient dynamics, physiological stress responses, and bacterial community composition under HP and AQ systems using bamboo-derived biochar substrates and coconut coir as a control. Vegetative growth was enhanced under AQ, with the greatest plant elongation (1102 ± 40.1 cm) and stem diameter (15.1 ± 1.0 mm) observed in biochar-grown plants. Total yield was consistently higher under AQ than HP, with the highest yield recorded in the coarse biochar treatment (28.6 kg m⁻²). Aquaponic systems were associated with greater nutrient availability under the conditions evaluated during mid to late season production, including nitrate concentrations of up to 226 mg L⁻¹. Physiological stress monitoring indicated lower stress exposure under aquaponic conditions in plants grown in medium and coarse biochar substrates across both systems, with 78 to 81% of the growing season classified within low to balanced stress conditions. Bacterial community composition was primarily shaped by cultivation system, which explained 19.3% of the observed variation, whereas substrate treatment did not significantly alter overall bacterial community structure. Overall, cultivation system was the dominant factor associated with variation in cucumber performance and root-zone bacterial communities, while biochar substrates supported improved plant growth, yield, and reduced physiological stress. Full article

This article focuses on the research and development of innovative polymer-concrete composites for the manufacture of precision machine tool frames and critical mechanical engineering components. The relevance of this work stems from the need to replace traditional cast iron and cement concrete with materials with superior damping properties and thermal stability. The polymer matrix used in this study was ED-20 epoxy-diane resin, modified with (FAM) furan resin and cured with polyethylenepolyamine (PEPA), which together ensured minimal linear shrinkage (less than 0.5–1%) during polymerization. The focus was on the effect of multimodal filler distribution, including quartz sand, gabbro, and basalt, as well as reinforcing additives such as silicon carbide and fiberglass, on the final performance characteristics of the material. Experimental studies determined the key physical and mechanical parameters of the obtained samples. The results showed that the optimized composition (Smp_001) exhibited compressive strength up to 92.3 MPa, significantly exceeding that of standard high-strength concrete. It was established that the use of silicon carbide and glass fiber promotes the formation of a dense heterogeneous microstructure characterized by extremely low porosity (1.2–2.5%) and record-low water absorption (less than 0.05%). These characteristics guarantee high dimensional stability of the frames during prolonged contact with process fluids and cutting fluids. The scanning electron microscopy (SEM) and (EDS) energy dispersive X-ray spectroscopy methods confirmed the dense packing and high degree of interaction of the polymer matrix with the crystalline phases of the filler. This condition of the interfacial boundaries guarantees stable stress transfer throughout the entire volume of the material, which minimizes the risk of local damage during operation. The study confirmed that the developed material has vibration damping properties 6–10 times more effective than gray cast iron, a critical factor in improving machining accuracy on modern metal-cutting machines. The scientific novelty of the study lies in its substantiation of the synergistic effect of the combined use of basalt fillers and silicon carbide to achieve the precision properties of a structural material. Its practical significance is confirmed by the possibility of producing large-scale parts by casting without the need for complex finishing, opening up new prospects for modernizing the machine tool industry. Full article

Depleted hydrocarbon reservoirs (DHRs), particularly depleted gas reservoirs (DGRs), are increasingly regarded as promising candidates for geologic carbon storage (GCS). However, their low abandonment pressure poses significant thermo-hydraulic challenges during the injection of cold, high-pressure CO₂. In such non-isothermal conditions, complex processes may occur, including Joule–Thomson (J-T) cooling, hydrate formation, salt precipitation, and thermal fracturing, all of which may affect storage performance. This study presents an integrated assessment of the impact of CO₂ injection into DGRs on the three key pillars of GCS: capacity, injectivity, and containment. The analysis integrates laboratory experiments conducted at our institute, simplified analytics and numerical simulations to assess the governing physical mechanisms. The findings indicate that the cold CO₂ injection can enhance effective storage capacity during the injection phase. This is attributed to the increase in fluid density and the delay in pressure buildup. However, the post-injection thermal equilibrium may result in pressure rebound. The CO₂ injectivity has been demonstrated to be significantly impacted by the near-wellbore thermal effects. While thermo-induced fracturing may enhance injectivity, it poses potential risks to wellbore and caprock integrity. The process of hydrate formation depends on the local temperature and petrophysical conditions, with dynamic factors further reducing the likelihood of pore plugging. Salt precipitation has been found to be less critical under typical DGR conditions with low initial water saturation, although having the potential to become significant in the presence of water influx and/or cyclic injection. The findings provide a technical basis for enhancing the engineering design, accelerating the certification process, and ensuring the safe operation of future GCS projects in DGRs. Full article

Firearm homicide is a leading cause of death among children and young men in the U.S. (ages 1–19), with young Black males in urban environments facing rates 18-to-24-fold higher than their non-Hispanic White peers in 2023. A key precursor to firearm violence victimization is weapon-carrying behavior (WCB), defined as carrying, concealing, or displaying firearms or other weapons in community or social contexts that elevate risk for injury, interpersonal threats, or law enforcement contact. Several structural, behavioral, and trauma-based risk factors fuel weapon-carrying. Yet these WCBs are rarely studied in tandem, leaving a critical gap in our understanding of these high-risk behaviors for youth. This cross-sectional study leveraged baseline data from a convenience sample of 226 violence-exposed urban young Black males, ages 15–24 (M_age = 18.3 years; SD = 3.1) enrolled in a trauma-informed digital firearm violence prevention pilot study. Eligibility required prior personal or witnessed experience of youth violence; reported prevalence therefore characterizes a high-risk subgroup rather than urban young Black males as a whole. Past-30-day weapon-carrying frequency was measured across five YRBS-aligned categories (0, 1, 2 to 3, 4 to 5, and 6+ days) and modeled as a categorical index under negative binomial regression. Associations with peer and community violence exposure, substance use, sociodemographic, and socioeconomic factors were estimated as incidence rate ratios (IRRs) with 95% CI. Past-30-day weapon carrying was reported by 42.5% of participants, with carrying frequency ranging from 1 day to 6 or more days. Participants reported high levels of direct victimization (64.8%), witnessing community violence (76.4%), and use of nonprescribed medications, including in instances preceding violence. In the fully adjusted model, indicators of violence exposure were the most consistent correlates of carrying. Direct victimization (IRR = 1.15, p < 0.05), general exposure to violence or aggression (IRR = 7.82, p < 0.01), and physical fighting (IRR = 1.11, p < 0.05) remained independently significant. Conversely, associations with substance use, dating aggression, and employment were attenuated, suggesting shared ecological vulnerability rather than independent causal pathways. Findings underscore the central role of chronic violence exposure and support the need for trauma-informed, multilevel prevention strategies in clinical and community settings. Full article

Background: Hypertension is one of the most common noncommunicable diseases. Objectives: This research assessed the magnitude of hypertension among young adults, identified its key determinants, and explored potential strategies adopted for prevention. Methods: A cross-sectional design was employed, including 1606 participants aged 18 years and older, recruited through convenience sampling from universities and community settings. Data were collected using a content-validated questionnaire covering sociodemographic information, personal and family medical history, and lifestyle habits. Results: Of the participants, 993 (61.8%) reported hypertension, nearly double previous national estimates. Male gender, age ≥ 30 years, and family history were significant risk factors, along with smoking, alcohol use, sedentary lifestyle, and unhealthy diet, while physical activity and dietary modification were protective. Despite high prevalence, only 22.1% had controlled blood pressure and 17.8% adhered to medication, with 51.5% relying on herbal remedies. Conclusions: These findings highlight the urgent need for early screening, youth-focused awareness, and culturally tailored interventions to reduce hypertension and prevent long-term cardiovascular complications. Hypertension among young adults in the UAE is a major public health concern, requiring integrated strategies combining education, lifestyle modification, and medical management to improve outcomes. Full article

Cable-driven minimally invasive surgical robots suffer from significant motion inaccuracies due to nonlinear transmission effects such as friction, elasticity, and hysteresis. These factors lead to strong nonlinear and direction-dependent behaviors, making accurate modeling and compensation challenging. To address this issue, this study investigates the error characteristics of a cable-driven surgical robot prototype based on its structural features. A kinematic model is first established, and geometric errors are corrected through Denavit–Hartenberg (DH) parameter identification using a least-squares method. To further characterize nonlinear effects, the LuGre friction model and equivalent stiffness theory are introduced to analyze friction and cable deformation behaviors. Since physics-based models alone cannot accurately capture the coupled nonlinear errors, a radial basis function (RBF) neural network is employed to approximate the residual errors. To enable real-time implementation, the predicted errors are further simplified using equivalent polynomial functions for efficient compensation. Experimental results demonstrate that the proposed method significantly improves the motion accuracy of the cable-driven system, effectively reducing both tracking error and hysteresis effects. By integrating mechanism-based modeling with data-driven compensation, this approach provides a practical and effective solution for precision enhancement in cable-driven surgical robotic systems. Full article

Rough-walled fractures in conglomerate reservoirs promote near-wellbore proppant deposition, nonuniform flow, and insufficient distal support, making proppant-schedule screening difficult using small-scale smooth-slot tests alone. This study develops a benchmark-constrained and cost-aware hierarchical screening workflow by integrating a 20 m rough-wall physical experiment, transient Fluent simulations, and archived short-time EDEM sensitivity records. The benchmark experiment used a 20 m × 4.5 m × 10 mm artificial rough-wall fracture and ten operating conditions involving pumping rate, fluid viscosity, proppant size, and sand concentration. In the Fluent model, wall roughness was treated as a regularized roughness representation, and the carrier fluids were modeled using Newtonian constant viscosities measured from laboratory calibration. The experimental effective propped area ranged from 25.5% to 65.1%. Within single-factor comparison subsets, medium viscosity improved support continuity, pumping-rate gains became limited near 0.20 m³/min, particle size affected the balance between distal coverage and bed stability, and 300 kg/m³ sand concentration caused blockage. Image-segmentation-based comparison showed that Fluent captured the main wedge-shaped deposition morphology and screening-level geometric trends. The archived EDEM records indicated that grid-resolution refinement and mixed particle-size representation substantially increased computational cost. A Case 10 mesh-sensitivity check further confirmed that mesh refinement did not alter the first-order deposition morphology. The proposed workflow uses Fluent for whole-domain rapid screening and reserves EDEM/CFD-DEM for targeted short-time sensitivity checks. Full article

CO₂ injection for enhanced oil recovery and carbon sequestration in low-permeability reservoirs has become a major research focus, driven by growing global energy demand and carbon-emission reduction targets. Among available development strategies, synchronous huff-and-puff and asynchronous injection–production show considerable field application potential; however, large-scale physical simulation experiments to validate these approaches remain lacking. In this study, large-scale high-temperature, high-pressure, two-dimensional physical simulation experiments were conducted under CO₂ miscible flooding conditions to compare the displacement mechanisms of these two strategies in a low-permeability reservoir. Numerical simulation was employed to history-match the experimental results, confirming their accuracy and reliability. The results show that CO₂ exhibited strong adaptability under the investigated reservoir conditions. It effectively replenished formation energy and, upon dissolution in crude oil, induced pronounced swelling and viscosity-reduction effects that enhanced oil mobility. Under miscible conditions, interfacial tension was significantly reduced, further improving displacement efficiency. Compared with synchronous huff-and-puff, asynchronous injection–production established a unidirectional pressure gradient by injecting CO₂ into the low-permeability zone while producing from the high-permeability zone, substantially enlarging the swept volume and mobilizing residual oil. The final oil recovery under this mode reached 41.56%, an improvement of 21.78% over synchronous huff-and-puff. Reservoir heterogeneity was identified as the key factor controlling CO₂ flooding effectiveness and residual oil distribution. The high-permeability zone served as the preferential CO₂ migration pathway, while the low-permeability zone retained considerable residual oil. Therefore, rational optimization of the injection–production direction and pressure regime is essential for overcoming heterogeneity constraints and improving overall recovery performance. Full article

Electronic components play a fundamental role in critical missions, performing functions such as data processing, measurement of physical variables, data storage, communication, power generation and storage, and algorithm computation. However, their performance can be compromised in harsh environments like those encountered in aerospace applications, where components are exposed to extreme conditions including radiation, temperature variations, and vibrations. To ensure reliability, electronic components used in aerospace missions must comply with strict specifications, typically requiring space- or military-grade standards. These components are significantly more expensive than commercial alternatives and often involve long development and design times for custom platforms. The use of COTS (Commercial-Off-The-Shelf) components has emerged as a viable solution for aerospace applications where cost and development time are critical factors. This paper presents a state-of-the-art review of COTS components used in aerospace missions. After an extensive literature review and document screening process, the results indicate that COTS components are commonly employed in critical missions, representing 44% of the studies analyzed. Furthermore, approximately 81% of the reviewed projects focused on space applications, with validation performed in space (22%), ground (75%), and air (3%) environments. Among the systems validated for space missions, half used CubeSat-based payload structures, while the rest relied on other platforms. Most launches were conducted using spacecraft (96%), with the remainder using balloons. Full article

Real-time binaural beat synthesis in dynamic acoustic environments is challenged by carrier non-stationarity, interaural phase discontinuities, and processing delay in conventional digital signal processing pipelines. This study proposes a predictive dual-stage neural framework for phase-coherent auditory synthesis under non-stationary acoustic conditions. The framework decouples real-time carrier estimation from phase-coherent signal generation through two specialized modules. An intelligent acoustic sensing module (AI-1) estimates time-varying carrier information across harmonic, fluctuating, and broadband acoustic profiles using a causal neural front-end with an adaptive confidence-driven strategy. A predictive phase-coherent generator (AI-2) then forecasts short-horizon carrier trajectories and drives a discrete-time phase accumulator to maintain continuous phase evolution during binaural beat embedding. Objective evaluation under multiple acoustic profiles and noise conditions shows that the proposed framework maintains strong phase continuity, with a Phase Coherence Factor greater than 0.91, and low artifact levels, with a Signal-to-Artifact Ratio greater than 39.8 dB, under the evaluated conditions. Additional comparisons with conventional DSP baselines, stronger classical F0 estimators, a lightweight neural F0 tracker, and component-wise ablation variants further demonstrate that the performance improvement arises from the combination of adaptive carrier estimation and predictive phase-coherent actuation, rather than from carrier estimation alone. Hardware profiling shows a combined INT8 inference time of 2.4 ms per frame on a resource-constrained Raspberry Pi Zero 2W-class edge device. Importantly, this inference time and the sub-millisecond phase-accumulator resolution should not be interpreted as sub-millisecond end-to-end physical audio latency. The complete system still includes buffering, framing, neural inference, and output processing delay; the proposed method instead reduces effective phase-boundary misalignment through short-horizon predictive compensation. These results support the proposed framework as a lightweight engineering solution for real-time phase-continuous auditory synthesis in dynamic listening environments. The reported PCF and SAR values should be interpreted as signal-level indicators of phase continuity and artifact suppression, rather than as evidence of listener comfort, perceptual preference, or neurophysiological efficacy. Full article

Heap bioleaching is widely used to extract copper from low-grade sulfide ores thanks to its operational simplicity, low cost, and environmental sustainability. However, current control strategies rely primarily on single-factor optimization and often overlook the synergistic interactions of multiple key parameters, such as ore particle size, pore structure, pH, temperature, microbial activity, and oxygen transfer efficiency. As a result, issues such as low recovery rates, extended leaching periods, and high operational costs persist. Moreover, the “gray-box” nature of heap systems impedes real-time monitoring of internal physical, chemical, and biological processes. In addition, empirical multi-parameter optimization is time-consuming and inadequate for capturing complex interdependencies. This review was conducted to systematically examine the key factors influencing heap bioleaching efficiency and critically evaluate recent advances in numerical simulation and intelligent control strategies. As a result, we identified a major research gap: the existing models—including microscale shrinking core models (SCMs), mesoscale pore-network models based on CT reconstruction, and macroscale continuum models—have inherent limitations. SCMs assume idealized spherical particles with uniform mineral distribution while neglecting pore structure evolution and biofilm dynamics. Mesoscale models offer detailed pore characterization but lack robust multi-physics coupling (thermal–hydro–mechanical–chemical–biological, or THMCB). Macroscale models rely on homogenization assumptions that oversimplify spatial heterogeneity and temporal variations in permeability. This analysis covers the relevant literature from 1985 to 2025, with a focus on three methodological scales (micro, meso, and macro) and their integration with machine learning approaches. A notable finding is that hybrid neural network models (e.g., BP and RBF architectures) outperform purely physics-based models in predicting leaching kinetics under varying operational conditions. However, their accuracy depends heavily on high-quality field data—a limitation rarely addressed in prior reviews. By clearly delineating these model-specific limitations and scale-dependent trade-offs, this review makes two unique contributions: a structured framework for selecting and coupling numerical methods according to process requirements and a roadmap for integrating artificial neural networks with multi-physics simulations to achieve real-time intelligent control of heap bioleaching. The findings offer both theoretical guidance and practical references for optimizing the processing of low-grade copper sulfide ores. Full article

Background/Objectives: Light training tasks are widely used in athletic training, yet the cognitive processes that underlie performance on these tasks remain poorly understood. Method: In this study, we investigated whether exogenous attentional orienting and visual search abilities could explain individual differences in performance on SpeedPad, a Virtual Reality light training task, in participants who engage in physical exercise and in controls. Results: Our results showed that participants engaging in physical exercise outperformed those who did not in SpeedPad sessions that required fast reactions to targets with or without distractors. Furthermore, hierarchical regression analyses revealed that engagement in physical exercise accounted for a significant amount of variance in SpeedPad performance. In addition, both the cueing benefit from an exogenous orienting task and the intercept of a visual search task with feature search trials accounted for unique variance in SpeedPad performance. Conclusions: Overall, the current findings suggest that performance in light training tasks such as SpeedPad depends on both physical/physiological and cognitive factors, especially those related to different types of attention. Full article