Search Results (3,621)

Vertical land motion in urban areas is a critical manifestation of groundwater, directly affecting infrastructure stability and groundwater sustainability. While land subsidence caused by groundwater extraction has been widely investigated, the opposite process—surface uplift induced by groundwater recovery—remains poorly documented or understood, particularly regarding its hydrological mechanisms and potential hazards. Here, we integrate InSAR time-series analysis of Sentinel-1 imagery (2017–2025) with groundwater well records to quantify the spatial–temporal characteristics of uplift in Xi’an, China, and to evaluate its hydrogeological drivers. Results reveal a persistent surface uplift zone south of the ancient city in Xi’an, with rates up to 20 mm/yr. The uplift correlates closely with rising groundwater levels in the shallow confined aquifer, indicating a strong coupling between aquifer recharge and surface uplift. Calculated storage coefficients and hydraulic diffusivity values highlight marked spatial variations, constrained by some ground fissures that act as both mechanical discontinuities and hydrological barriers controlling pressure diffusion. Time-series analysis further identifies the eastward propagation of subsidence-to-uplift reversal in Yuhuazhai, an urban village with groundwater injection, which is used to quantify the diffusivity coefficients. Field investigations show that rapid groundwater rebound can lead to uplift-related hazards, such as basement seepage, underscoring that surface uplift must be considered alongside subsidence in urban water management. Full article

Anti-corrosive coatings are among the most widely used methods for corrosion protection. Zero-dimensional (0D) carbon nanomaterials have attracted increasing attention due to their advantages, such as small size, high specific surface area, ease of surface functionalization, and strong interfacial regulation capability, which enable enhanced barrier properties, densification, and multifunctional protection of coatings. However, existing reviews have largely focused on the application of 2D carbon nanomaterials in anti-corrosive coatings, with a lack of systematic summaries on 0D carbon nanomaterials, particularly comprehensive reviews that combine quantitative bibliometric analysis with qualitative content analysis. To address this gap, this review employs a combined approach of bibliometric analysis and content analysis to systematically summarize the research progress of three typical types of 0D carbon nanomaterials, including nanodiamonds, fullerenes, and carbon dots, in the field of corrosion protective coatings. The quantitative analysis is conducted using CiteSpace 6.4 R.2 to reveal publication trends, research hotspots, and frontier evolution in this field, while the qualitative analysis selects representative studies to summarize application systems, performance characteristics, and underlying mechanisms. On this basis, the key challenges currently faced are identified, and future research directions are proposed. This review provides a systematic reference for the material design, mechanistic understanding, and engineering application of 0D carbon nanomaterial-based anti-corrosive coatings. Full article

Electric vehicles are an important carrier for achieving energy savings and emission reductions in the transportation sector. As the decision-making core of the powertrain, the energy management strategy is responsible for power allocation and energy scheduling and directly determines vehicle economy, power-source lifetime, and overall performance. Model predictive control can handle multiple constraints and objectives within a prediction horizon and realize online closed-loop decision-making via receding-horizon optimization and has become an important research direction for energy management of electric vehicles. This paper presents the basic principles and typical modeling framework of model predictive control and reviews its research progress in hybrid electric vehicle energy management. The related studies are categorized and comparatively analyzed from three perspectives—prediction methods, solution strategies, and optimization objectives—and the characteristics of different approaches are summarized. The review shows that model predictive control has advantages in multi-objective trade-offs and adaptation to time-varying operating conditions. However, practical implementation still faces significant barriers, including prediction uncertainty and computational complexity. Finally, the challenges and future directions of model-predictive-control-based energy management strategies are discussed. Full article

This paper investigates the stability of perovskite films under bonding conditions, focusing on the impact of bonding temperature on the electrical, morphological, and elemental characteristics of perovskite solar cells (PSCs) incorporating a barium–strontium titanate (BST) barrier layer. This study aimed to elucidate the interdiffusion phenomena at interfaces and their effect on device performance. We found that increasing the bonding temperature significantly degrades PSC performance, with efficiencies dropping from 21% at 100 °C to 65% at 180 °C relative to unbonded devices. A critical bonding temperature of 150 °C was identified, which correlates with a pronounced drop in short-circuit current and a peak in series resistance, phenomena primarily attributed to severe elemental interdiffusion and defect formation at the interfaces. Morphological (SEM) and elemental (EDS) analyses confirmed the temperature-dependent nature of interdiffusion across the Au/BST/perovskite interfaces. These findings underscore the critical role of bonding temperature in triggering interfacial degradation, a factor that mediates the stability of BST-interfaced PSCs during packaging. Full article

Indium oxide (In₂O₃) has recently emerged as a promising semiconductor for advanced electronics due to its high electron mobility and wide bandgap. In this article, the lateral scaling characteristics of top-gate In₂O₃ thin-film transistors (TFTs) featuring a 1.5 nm thick channel and a 7 nm thick HfO₂ gate dielectric are investigated by two-dimensional device simulation. The analysis covers short-channel effects, DC characteristics, transconductance behavior, and small-signal radio frequency (RF) metrics across a gate-length (L_G) range of 20 nm to 700 nm. Simulation results identify a critical gate length near 100 nm for the transition from long-channel to short-channel behavior. For L_G ≤ 100 nm, pronounced short-channel effects emerge, featuring a significant negative V_TH shift and a drain-induced barrier lowering (DIBL) coefficient up to ~130 mV/V. A non-classical gm scaling behavior is observed, where g_{m_max} initially increases with L_G, then remains within a narrow range and eventually evolves toward the conventional long-channel trend. Further analysis of the lateral electric field distribution, field-dependent mobility, and transconductance efficiency indicates that this behavior originates from a crossover between short-channel field-assisted transport and gate-controlled channel modulation. The devices show strong RF potential, with f_T and f_max reaching 124.32 GHz and 157.64 GHz, respectively, at L_G = 20 nm. The high-mobility In₂O₃ channel leads to a less distinct f_T scaling transition from the classical 1/L²_G dependence to the short-channel 1/L_G dependence, while f_max scaling evolves through different regimes governed by capacitance-related limitations, intrinsic transport enhancement, and short-channel non-idealities. This work provides physical insight into the lateral scaling behavior of ultrathin top-gate In₂O₃ TFTs and highlights their potential for high-frequency and power-dense applications. Full article

Conductive hydrogels have emerged as promising candidates for flexible strain sensors owing to their high water content, low elastic modulus, and intrinsic ionic conductivity. However, conventional hydrogel networks often suffer from an inherent trade-off among conductivity, mechanical robustness, and long-term stability, which limits their practical deployment in wearable sensing scenarios. The introduction of metal–ligand coordination bonds into hydrogel networks offers a versatile strategy to address these challenges: dynamic coordination cross-links can dissipate energy under deformation and reform upon unloading, thereby enhancing toughness, enabling self-healing, and contributing to ionic transport. This review focuses on metal-ion-coordinated conductive hydrogels designed for strain-sensing applications. Representative coordination systems based on Fe³⁺, Ca²⁺, Zn²⁺, Al³⁺, Cu²⁺, Ti⁴⁺, and Zr⁴⁺ are surveyed, with emphasis on their characteristic polymer matrices, ligand chemistries, and network-construction strategies. Key sensing-relevant properties—including ionic conductivity, mechanical stretchability, self-healing capability, interfacial adhesion, freezing resistance, and resistance to dehydration—are discussed in relation to coordination network design. Typical application demonstrations in large-deformation motion monitoring and subtle physiological signal detection are reviewed. Unlike existing reviews that survey conductive hydrogels broadly by conductive mechanism or sensor type, this review takes metal-ion coordination as the central organizing principle and systematically traces its influence across the full design chain—from ion–ligand coordination chemistry through network architecture to macroscopic sensing output. By comparatively analyzing seven representative metal-ion systems within a unified framework, this work aims to clarify how the choice of metal ion governs the interplay among conductivity, mechanical robustness, self-healing, and strain sensitivity—a perspective that has not yet been systematically addressed in prior reviews. Finally, current challenges—including the conductivity–mechanics coupling bottleneck, insufficient long-term stability, biosafety concerns for skin-contact deployment, the lack of standardized evaluation protocols, and device-integration barriers—are identified, and future directions for this field are outlined. Full article

Background: Tuberculosis (TB) remains a major public health challenge globally, particularly in high-burden countries such as South Africa. Treatment interruption is a critical barrier to effective TB control, contributing to poor treatment outcomes, increased risk of multidrug-resistant tuberculosis (MDR-TB), and continued community transmission. Understanding the determinants of treatment interruption in rural healthcare settings is essential for strengthening TB programme implementation. Methods: This qualitative study explored the factors influencing TB treatment interruption from the perspectives of professional nurses working in primary healthcare facilities in the Nyandeni Subdistrict, Eastern Cape, South Africa. Semi-structured interviews were conducted with nurses involved in TB programme implementation. Data were analysed using thematic analysis following the six-phase approach described by Braun and Clarke. Descriptive statistical analyses were also used to summarize participant characteristics, including age and years of nursing experience. Conceptual frameworks were developed to illustrate the multilevel determinants of TB treatment interruption. Results: Participants had a mean age of 40.6 years and an average of 14.2 years of nursing experience, reflecting a workforce with substantial clinical exposure to TB management. Thematic analysis identified multiple interconnected determinants of treatment interruption. Key barriers included poverty, food insecurity, transport costs, long distances to healthcare facilities, limited family support, and challenges related to patient tracing. These factors interact across structural, community, health system, and interpersonal levels to influence patient adherence behaviour. Conceptual models developed from the findings illustrate the complex pathways through which these determinants contribute to treatment interruption and programme-level consequences such as reduced treatment success and increased risk of MDR-TB. Conclusions: TB treatment interruption in rural settings is driven by multilevel socioeconomic and health system determinants rather than individual patient behaviour alone. Strengthening community health worker programmes, improving patient tracing systems, addressing socioeconomic barriers, and enhancing community-based support mechanisms are essential for improving treatment adherence. Integrated, multisectoral interventions are required to strengthen TB programme outcomes in rural high-burden settings. Full article

Against the backdrop of rapid population aging, rural public spaces face growing challenges in meeting the everyday needs of older adults. Drawing on a place-based care perspective, this study develops age-friendly design strategies attuned to the spatial and cultural characteristics of rural environments. Using a mixed-methods approach that includes field observations, structured interviews, and questionnaire surveys, we identify the needs of older adults in rural public spaces. These needs are first clustered using the K-means algorithm and then analyzed using the FKANO model to extract core priorities. Their relative importance is quantified by an integrated procedure that combines ordinal relation diagrams and entropy weighting. Building on these results, we propose an age-friendly design framework and validate it with spatial simulation to assess scale, accessibility, and connectivity. The findings highlight five critical features prioritized by older adults in rural areas: non-slip surfaces, barrier-free access, safety railings, lighting systems, and public restrooms. The study provides a targeted and actionable pathway for the age-adaptive transformation of rural public spaces, offering both a theoretical foundation and a practical design paradigm for aging-friendly rural environments worldwide. Full article

This study investigates methane leakage and diffusion from a buried high-pressure natural gas pipeline (8 MPa, 1000 mm diameter) using CFD simulations with the DES turbulence model. Based on homogeneous and layered soil models, the influences of soil porosity (0.46 to 0.54), particle size (10 μm to 100 μm), and soil stratification on the spatial and temporal characteristics of methane diffusion are systematically explored. The simulation results show that (1) methane diffuses from the leak hole to the surrounding soil in an ellipsoidal pattern, with the fastest diffusion speed along the pipeline’s axial direction. (2) In homogeneous soil, within the range of soil parameter values considered in this study, the absolute changes in risk assessment indices (FDR, GDR) caused by soil particle size were more significant; whereas the relative percentage changes in risk assessment indicators caused by soil porosity were more pronounced. (3) In layered soil, the permeability contrast between adjacent layers creates the permeability discontinuity interface effect. When a fine-grained or low-porosity layer overlies a coarse-grained layer, the upper layer acts as a hydraulic barrier, prolonging FDT from 130 s to 354 s while promoting significant horizontal spread at the interface. Conversely, a coarse-grained or high-porosity upper layer accelerates vertical breakthrough. These findings provide a scientific basis for risk assessment, monitoring site optimization, and emergency response planning, particularly in regions with heterogeneous stratified soils. Full article

Background/Objectives: Mental health service utilization gaps remain a persistent global public health challenge. Among the 61.5 million adults with any mental illness in the United States, nearly half went without treatment in the past year, and dropout rates from outpatient services among those who do enter care range from 19.7% to 30.8%. Only 30 to 60% of individuals with lifetime mental illness are in active recovery at any given time. Existing theoretical frameworks, including Andersen’s Behavioral Model, the Health Belief Model, and the COM-B framework, each address isolated phases of the care continuum but offer no unified structure for understanding the complete, sequential journey from first contact through sustained recovery. This article introduces the Access, Initiation, Engagement, Retention, and Recovery (AIERR) model to address this theoretical gap. Methods: A conceptual review was conducted following Hulland’s framework for theory development through narrative synthesis. Literature was identified through targeted searches in PubMed, PsycINFO, and Google Scholar, prioritizing peer-reviewed empirical studies, systematic reviews, and foundational theoretical frameworks. Sources were assigned to AIERR stages using predefined decision rules corresponding to each phase’s defining characteristics. Results: AIERR maps five sequential, interconnected stages: Access (structural, cultural, and systemic conditions enabling service reach), Initiation (the transition from provider identification to first appointment attendance), Engagement (active and meaningful treatment participation), Retention (sustained continuity of care), and Recovery (long-term reclamation of life quality and community belonging). For each stage, the framework identifies individual-level and structural-level barriers, facilitating conditions, and targeted intervention points. Conclusions: AIERR advances mental health services theory by unifying previously siloed frameworks, establishing stage-specificity as a core theoretical principle, and reorienting research and intervention strategy toward the upstream structural conditions that produce downstream utilization failures. These theoretical contributions require empirical testing to confirm. Implications for health equity research, clinical practice, and health systems design are discussed. Full article

Infrared photodetectors are important for military, medical, and environmental applications. Dual-color quantum well infrared photodetectors (QWIPs) are attractive because they can provide multi-spectral information, but their performance is often limited by high dark current. In this study, we designed and fabricated two dual-color QWIPs. Sample A exhibits rectification-like dark-current behavior, whereas Sample B shows a nearly symmetric current–voltage characteristic together with an approximately two-order-of-magnitude reduction in dark current under the same operating condition. By combining secondary ion mass spectrometry (SIMS), scanning spreading resistance microscopy (SSRM), energy-band simulations, and optoelectronic characterization, we show that Sample B exhibits a larger disparity in effective carrier distribution between the two quantum-well groups than Sample A. The experimental results and simulations consistently indicate that this disparity, together with the higher barrier design, is associated with a redistribution of the internal potential and a stronger voltage drop across the lightly doped region, which is consistent with reduced thermally activated carrier transport. Although the lower carrier concentration in the lightly doped wells is accompanied by reduced blackbody responsivity, the stronger suppression of dark current leads to a higher peak blackbody detectivity under identical blackbody-illumination conditions. At 50 K and −1.5 V, the peak blackbody detectivity of Sample B is approximately four times that of Sample A. These results support the conclusion that combining barrier-height design with controlled inter-group carrier disparity is an effective strategy for tuning carrier transport and improving the peak blackbody detectivity trade-off in dual-color QWIPs within the conditions examined here. Full article

Background: Diarrhea in suckling calves is associated with impaired growth, oxidative stress, immune dysfunction, and intestinal microbial dysbiosis. This study evaluated the effects of compound yeast culture (CYC) supplementation on growth performance, fecal characteristics, antioxidant capacity, immune function, and gut microbiota in diarrheic Holstein calves. Thirty-six approximately 7-day-old calves were enrolled, including 12 healthy calves (CON) and 24 diarrheic calves randomly assigned to a diarrhea group (DIA) or a CYC-supplemented group (DIA-YC; 50 g/d for 30 days). The experimental period lasted 60 days. Results: Compared with the DIA group, calves in the DIA-YC group showed significantly higher average daily feed intake and average daily gain (ADG) during days 31–60 and across the entire period (p < 0.05), with a trend towards increased body weight. Fecal scores were significantly elevated in diarrheic calves during the early and mid-stages but were markedly reduced by CYC supplementation from days 7 to 30; no significant difference was observed between DIA-YC and CON during days 16–30 (p > 0.05). Diarrheic calves exhibited oxidative stress, characterized by decreased total antioxidant capacity (T-AOC) and increased malondialdehyde (MDA). CYC supplementation significantly increased T-AOC, superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) activities, while reducing MDA levels (p < 0.05). Immune analysis showed higher serum IgG and IL-10 levels and lower TNF-α levels in the DIA-YC group, along with improved intestinal barrier indicators, including diamine oxidase (DAO) activity and endotoxin levels. Metagenomic analysis revealed that diarrhea reduced microbial richness and diversity and altered community structure, whereas CYC partially restored microbial diversity and increased beneficial genera such as Prevotella, Coprococcus, Ruminococcus, and Parabacteroides. Functional analysis indicated that CYC enhanced pathways related to immune regulation, energy metabolism, and antioxidant function. Conclusion: CYC supplementation alleviates oxidative stress and immune dysfunction by modulating gut microbiota, thereby improving growth performance and reducing diarrheal severity in calves. Full article

Electric vehicle (EV) adoption remains critically low in Thailand despite government initiatives, with limited understanding of how adoption factors vary across different user segments. This study investigates the determinants of EV adoption intentions across three distinct groups—internal combustion engine (ICE) users, hybrid electric vehicle (HEV/PHEV) users, and current EV users—to develop targeted adoption strategies. Data were collected from 3794 Thai vehicle users through on-site administered questionnaires and analyzed using multi-group structural equation modeling, integrating the Technology Acceptance Model, Theory of Planned Behavior, and environmental psychology constructs. Results reveal significant differences in adoption pathways across groups: ICE users show the strongest sensitivity to perceived ease of use, indicating technology apprehension as the primary barrier; HEV/PHEV users demonstrate transitional characteristics with the highest experience-usefulness relationship, while current EV users exhibit stronger influence from environmental identity and social norms. All 14 hypotheses were supported, though with varying effect magnitudes across groups. Surprisingly, the attitude-intention relationship was consistently weak across all segments, suggesting unmeasured cultural or contextual factors. This study contributes the first empirical evidence of segmented adoption patterns in an emerging market, revealing a progression pathway from technology-focused concerns (ICE) through balanced considerations (HEV/PHEV) to identity-driven adoption (EV). Findings provide actionable insights for policymakers to design segment-specific interventions: technology familiarization for ICE users, transition facilitation for hybrid users, and community-building for EV users. Full article

Background: Managing complex infrastructure increasingly requires predictive, adaptive, and human-centered systems. Traditional approaches often struggle with operational complexity, fragmented data, and high technical barriers. Methods: This study presents a TRL4 proof of concept integrating a conversational AI agent with a user-adaptive digital twin for occupancy forecasting. Users can upload their own datasets, and dynamically configure prediction models (ARIMA, SARIMA, Random Forest, XGBoost) based on input variables such as occupancy or demand drivers. The AI agent, powered by Gemini 2.5 Flash Lite, functions as an orchestration layer, translating natural language instructions into data ingestion, model execution, and query actions. While the digital twin supports additional variables (energy, water, waste), these are envisioned for future work and were not part of the current validation. Results: Functional validation confirmed the system’s capability to interpret user intentions accurately, adapt model training to the characteristics of user-provided data, and present results through convenient and comprehensible visualization methods. The integrated architecture demonstrated stable performance across multiple validation scenarios, achieving satisfactory prediction accuracy (within expected ranges for TRL 4). Conclusions: This work validates the technical and functional viability of integrating conversational AI agents with digital twins as an emergent system of systems, extending beyond conventional predictive pipelines by enabling context-specific modeling. The systems engineering approach reveals how such integration transforms reactive infrastructure management into proactive, data-driven, and human-centered decision-making processes, establishing a foundation for future developments toward higher technology readiness levels. Full article

The United States faces a maternal health crisis marked by stark racial disparities. Although doula support has emerged as an evidence-based intervention to improve perinatal outcomes by addressing social determinants of health, its integration into healthcare systems remains limited. This qualitative study, informed by phenomenological principles, examined multi-level experiences, perceived barriers, and perceived facilitators of integrating doula services into perinatal care systems and their intersection with health equity goals. We conducted 17 semi-structured interviews with 20 participants across Nebraska and Tennessee, including doulas, midwives, physicians, Medicaid administrators, and public health professionals, and analyzed data using reflexive thematic analysis guided by the Socio-Ecological Model. Three themes emerged: the integration paradox, an overarching theme capturing tensions between doula independence and healthcare system demands for standardization, including divergent views on practice models, provider dynamics, and certification; sustainable financing as the prevailing barrier, encompassing grant limitations, private pay inequities, absent Medicaid reimbursement, and the need for cost-effectiveness evidence; and cultural concordance as the prevailing facilitator, including cultural matching, addressing social determinants, and lived experience as motivation. Sustainable doula integration requires reconciling system demands for standardization with the relational, culturally responsive characteristics that define effective care, through Medicaid reimbursement pathways and policy reforms developed in partnership with doula communities. Full article