Search Results (295)

It is well known that the operation of a Borehole Heat Exchanger (BHE) can thermally induce groundwater convection in aquifers, enhancing the thermal performance of the BHE. However, the effect on the thermal performance of BHEs installed in low-permeable rock formations remains unclear. In this study, two BHEs were installed in a silty sandstone formation, one backfilled with high-permeable materials and the other grouted with sand–bentonite slurry. A Thermal Response Test (TRT) showed that the fluid outlet temperature of the high-permeable-material backfilled BHE was about 2.5 °C lower than that of the BHE refilled with sand–bentonite slurry, implying a higher thermal efficiency. The interpreted borehole thermal parameters also show a lower borehole thermal resistance in the high-permeable-material backfilled BHE. Physical model tests reveal that groundwater convective flow was induced in the high-permeable-material backfilled BHE. A test of BHEs with different borehole diameters shows that the larger the borehole diameter, the higher the thermal efficiency is. Thus, the thermal performance enhancement was attributed to two factors. First, the induced groundwater flow accelerates heat transfer by convection. Additionally, the increment of the thermal volumetric capacity of the groundwater stored inside a high-permeable-material refilled borehole stabilized the borehole’s temperature, which is key to sustaining high thermal efficiency in a BHE. The thermal performance enhancement demonstrated here shows potential for reducing reliance on fossil-fuel-based energy resources in challenging geological settings, thereby contributing to developing more sustainable geothermal energy solutions. Further validation in diverse field conditions is recommended to generalize these findings. Full article

Under the accelerating urbanization, the evolution of public spaces in traditional villages increasingly diverges from social needs. The top-down governance model fails to adequately address the actual needs of indigenous residents, highlighting the necessity for structural analysis and optimization from an integrated physical–social perspective. This study, focusing on traditional villages in Beijing’s Fangshan District, constructs a three-tier model (village-street-node) by integrating Social Network Analysis (SNA) and space syntax theory. It analyzes the relationship between the accessibility and traffic potentiality of linear and point-based public spaces across the region and the frequency/scope of villagers’ daily activities. The findings reveal that within the linear belt-like spatial layout of traditional villages in western Beijing, historical spaces situated within the core residential areas demonstrate high stability and integrity, serving as primary venues for villagers’ daily activities. In contrast, historical spaces located at the periphery of settlements suffer from low utilization rates and even exhibit social segregation. Additionally, deficiencies in spatial choice, intermediary nodes, and functionality within settlements are identified as key factors contributing to social segregation in public spaces. Finally, the study proposes targeted policy recommendations for the preservation and sustainable development of traditional villages. Full article

Flow dynamics were characterized and stable zones in diversions were quantified using physical modeling, in situ experiments, and 3D numerical simulations. ADV (1 cm spatial resolution) and water-level probes (0.01 cm spatial resolution) were used in the physical experiments in a rectangular channel. ADCP (resolution of 50 cm) was employed for in situ validation at a northern China hub. Numerical simulations using ANSYS 2022R2 Fluent software with RNG k-ε and VOF showed little error (<15%) compared to the experiments. The results quantified the diversion zone into four sub-regions: acceleration (length 0.8–1.2 h); stabilization (1.2–3.5 h); diffusion deceleration (3.5–5.0 h); and stagnation (localized eddies, diameter 0.3–0.8 d). The stable zone length was dominantly controlled by the nonlinear coupling of geometric (B_s/B_m, 42%) and hydraulic (Fr, 28%) parameters. Upstream and downstream stable zone empirical models showed high accuracy (R² = 0.83 and 0.76, p < 0.01), with an average relative error <15%. Based on the proposed zoning principles and flow characteristics, measurement facilities in the irrigation area are presented. These tools enhance irrigation diversion design and management for improved water efficiency. Full article

The acceleration of industrialization and urbanization have led to the increasingly serious problem of waste gas pollution. Pollutants such as sulfur dioxide (SO₂), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH₃), formaldehyde (HCHO), and hydrogen sulfide (H₂S) emitted from industrial production, transportation, and agricultural activities have posed a major threat to the ecological environment and public health. Although traditional physical and chemical treatment methods can partially reduce the concentration of pollutants, they face three core bottlenecks of high cost, high energy consumption, and secondary pollution, and it is urgent to develop sustainable alternative technologies. In this context, probiotic waste gas treatment technology has become an emerging research hotspot due to its environmental friendliness, low energy consumption characteristics, and resource conversion potential. Based on the databases of PubMed, Web of Science Core Collection, Scopus, Embase, and Cochrane Library, this paper systematically searched the literature published from 2014 to 2024 according to the predetermined inclusion and exclusion criteria (such as research topic relevance, experimental data integrity, language in English, etc.). A total of 71 high-quality studies were selected from more than 600 studies for review. By integrating three perspectives (basic theory perspective, environmental application perspective, and waste gas treatment facility perspective), the metabolic mechanism, functional strain characteristics, engineering application status, and cost-effectiveness of probiotics in waste gas bioconversion were systematically analyzed. The main conclusions include the following: probiotics achieve efficient degradation and recycling of waste gas pollutants through specific enzyme catalysis, and compound flora and intelligent regulation can significantly improve the stability and adaptability of the system. This technology has shown good environmental and economic benefits in multi-industry waste gas treatment, but it still faces challenges such as complex waste gas adaptability and long-term operational stability. This review aims to provide useful theoretical support for the optimization and large-scale application of probiotic waste gas treatment technology, promote the transformation of waste gas treatment from ‘end treatment’ to ‘green transformation’, and ultimately serve the realization of sustainable development goals. Full article

Amorphous solid dispersions (ASDs) represent a promising formulation strategy for improving the solubility and bioavailability of poorly water-soluble drugs, a major challenge in pharmaceutical development. This review provides a comprehensive analysis of the physicochemical principles underlying ASD stability, with a focus on drug–polymer miscibility, molecular mobility, and thermodynamic properties. The main manufacturing techniques including hot-melt extrusion, spray drying, and KinetiSol^® dispersing are discussed for their impact on formulation homogeneity and scalability. Recent advances in excipient selection, molecular modeling, and in silico predictive approaches have transformed ASD design, reducing dependence on traditional trial-and-error methods. Furthermore, machine learning and artificial intelligence (AI)-based computational platforms are reshaping formulation strategies by enabling accurate predictions of drug–polymer interactions and physical stability. Advanced characterization methods such as solid-state NMR, IR, and dielectric spectroscopy provide valuable insights into phase separation and recrystallization. Despite these technological innovations, ensuring long-term stability and maintaining supersaturation remain significant challenges for ASDs. Integrated formulation design frameworks, including PBPK modeling and accelerated stability testing, offer potential solutions to address these issues. Future research should emphasize interdisciplinary collaboration, leveraging computational advancements together with experimental validation to refine formulation strategies and accelerate clinical translation. The scientists can unlock the full therapeutic potential with emerging technologies and a data-driven approach. Full article

This paper focuses on the issues of roof movement and ground pressure behavior in large-height mining extraction of shallow coal seams. By adopting a combined method of theoretical analysis and physical simulation experiments, it establishes a mechanical model for the rotational subsidence of key blocks and a physical simulation test model to conduct stability analysis on the rotational subsidence of key blocks, thereby revealing the characteristics and laws of roof movement. The findings indicate that the horizontal thrust during the rotational subsidence of key blocks increases non-linearly with the rotation angle, exhibiting a higher growth rate when the block size coefficient is less than 0.5. Two modes of instability—sliding and deformation—are observed for key blocks. To prevent sliding instability, the block size coefficient should be maintained below 0.75; however, sliding instability is likely to occur when the rotation angle exceeds 10°. Conversely, smaller rotation angles and larger block size coefficients reduce the likelihood of deformation instability. The reasonable working resistance of the support decreases with the increase in the rotation angle (it decreases sharply when the rotation angle exceeds 10°) and increases with the increase in the block size coefficient. Physical simulation indicates that roof movement is divided into three stages: immediate roof collapse, stratified fracturing and instability of the basic roof, and periodic fracturing of the basic roof. An increase in mining height accelerates the instability of the immediate roof, enlarges the opening of through-layer fissures, shortens the step distance of mining pressure, and heightens the risk of sudden pressure. The research results provide theoretical guidance for the safe and efficient mining with large mining height in shallow coal seams. Full article

Background: Water scarcity is a pressing global challenge increasingly addressed by advanced desalination that converts seawater into potable water. Reverse osmosis and ultrafiltration dominate because they deliver permeate with very low impurities. Their principal limitation is membrane biofouling, which causes clogging, raises energy, operation, and maintenance costs, and shortens membrane life. Multiple approaches mitigate biofouling—most notably pretreatment trains and engineered surface coatings—but cleaning remains the most decisive remediation pathway. Current practice distinguishes physical, chemical, and biological cleaning. Biological cleaning has gained momentum by exploiting microorganisms that inherently counter biofilms. These strategies include targeted secretion of enzymes and antifouling metabolites, and the application of whole-cell culture supernatants containing the full suite of secreted components. In addition, predatory bacteria can infiltrate established biofilms and eradicate them by lysing prey, thereby accelerating the removal of adherent biomass. Progress across these bio-based approaches signals meaningful advances in fouling control and could substantially improve the efficiency, reliability, and sustainability of desalination facilities. Collectively, they underscore the transformative potential of biological antifouling agents in operational systems. Realizing that potential will require rigorous evaluation of technical performance, long-term stability, compatibility with polyamide membranes, regulatory acceptance, and environmental safety, ultimately alongside scalable production and cost-effective deployment in full-scale plants. Full article

Under the typical scenario of high-speed mobility, channel disturbances at the physical layer may disturb the transmission of video base layers. Due to the close dependency of Scalable Video Coding (SVC) on base layers, such disturbances will result in retransmissions and handover delays. Meanwhile, ineffective enhancement layers continue to occupy resources, ultimately causing system performance collapse and further exacerbating physical-layer disturbances. To address this challenge, we propose an edge computing resource coordination optimization scheme for highly dynamic mobile terminals. The scheme first empowers the SVC layered transmission with the local caching capabilities, enabling rapid retransmission of base layer data by employing a Lyapunov optimization framework for transmission queue scheduling. Secondly, we design a strategy for dynamically releasing the enhancement layer (EL) cache. This can mitigate resource waste caused by invalid enhancement layers. Finally, Lyapunov drift optimization is implemented to ensure base layer transmission stability and accelerate system state convergence. Simulation and experimental results demonstrate that the proposed scheme significantly improves video transmission reliability and user experience in highly dynamic network environments. Full article

Digital twins represent a transformative innovation for battery energy storage systems (BESS), offering real-time virtual replicas of physical batteries that enable accurate monitoring, predictive analytics, and advanced control strategies. These capabilities promise to significantly enhance system efficiency, reliability, and lifespan. Yet, despite the clear technical potential, large-scale deployment of digital twin-enabled battery systems faces critical governance barriers. This study identifies three major challenges: fragmented standards and lack of interoperability, weak or misaligned market incentives, and insufficient cybersecurity safeguards for interconnected systems. The central contribution of this research is the development of a comprehensive governance framework that aligns these three pillars—standards, market and regulatory incentives, and cybersecurity—into an integrated model. Findings indicate that harmonized standards reduce integration costs and build trust across vendors and operators, while supportive regulatory and market mechanisms can explicitly reward the benefits of digital twins, including improved reliability, extended battery life, and enhanced participation in energy markets. For example, simulation-based evidence suggests that digital twin-guided thermal and operational strategies can extend usable battery capacity by up to five percent, providing both technical and economic benefits. At the same time, embedding robust cybersecurity practices ensures that the adoption of digital twins does not introduce vulnerabilities that could threaten grid stability. Beyond identifying governance gaps, this study proposes an actionable implementation roadmap categorized into short-, medium-, and long-term strategies rather than fixed calendar dates, ensuring adaptability across different jurisdictions. Short-term actions include establishing terminology standards and piloting incentive programs. Medium-term measures involve mandating interoperability protocols and embedding digital twin requirements in market rules, and long-term strategies focus on achieving global harmonization and universal plug-and-play interoperability. International examples from Europe, North America, and Asia–Pacific illustrate how coordinated governance can accelerate adoption while safeguarding energy infrastructure. By combining technical analysis with policy and governance insights, this study advances both the scholarly and practical understanding of digital twin deployment in BESSs. The findings provide policymakers, regulators, industry leaders, and system operators with a clear framework to close governance gaps, maximize the value of digital twins, and enable more secure, reliable, and sustainable integration of energy storage into future power systems. Full article

Batteries are ubiquitous, with their presence ranging from electric vehicles to portable electronics. Research focused on increasing average voltage, improving stability, and extending cycle longevity of batteries is pivotal for the advancement of battery technology. These advancements can be accelerated through research into battery chemistries. The traditional approach, which examines each material combination individually, poses significant challenges in terms of resources and financial investment. Physics-based simulations, while detailed, are both time-consuming and resource-intensive. Researchers aim to mitigate these concerns by employing Machine Learning (ML) techniques. In this study, we propose a Transformer-based deep learning model for predicting the average voltage of battery electrodes. Transformers, known for their ability to capture complex dependencies and relationships, are adapted here for tabular data and regression tasks. The model was trained on data from the Materials Project database. The results demonstrated strong predictive performance, with lower mean absolute error (MAE) and mean squared error (MSE), and higher R² values, indicating high accuracy in voltage prediction. Additionally, we conducted detailed per-ion performance analysis across ten working ions and apply sample-wise loss weighting to address data imbalance, significantly improving accuracy on rare-ion systems (e.g., Rb and Y) while preserving overall performance. Furthermore, we performed SHAP-based feature attribution to interpret model predictions, revealing that gravimetric energy and capacity dominate prediction influence, with architecture-specific differences in learned feature importance. This work highlights the potential of Transformer architectures in accelerating the discovery of advanced materials for sustainable energy storage. Full article

Although numerous observational and theoretical studies have examined the mean and turbulent structure of the tropical cyclone boundary layer (TCBL) over the open ocean, there have been comparatively fewer studies that have examined the kinematic and thermal structure of the TCBL across the land–ocean interface. This study examines the impact of different continental environments on the thermodynamic evolution of the TCBL during the landfall transition using high-resolution, full-physics numerical simulations. During landfall, the changes in the wind field within the TCBL due to the development of the internal boundary layer (IBL), combined with the formation of a surface cold pool, generates a pronounced thermal asymmetry in the boundary layer. As a result, the maximum thermodynamic boundary layer height occurs in the rear-right quadrant of the storm relative to its motion. In addition, azimuthal and vertical advection by the mean flow lead to enhanced turbulent kinetic energy (TKE) in front of the vortex (enhancing dissipative heating immediately onshore) and onshore precipitation to the left of the storm track (stabilizing the environment). The strength and depth of thermal asymmetry in the boundary layer depend on the contrast in temperature and moisture between the continental and storm environments. Dry air intrusion enhances cold pool formation and stabilizes the onshore boundary layer, reducing mechanical mixing and accelerating the decay of the vortex. The temperature contrast between the continental and storm environments establishes a coastal baroclinic zone, producing stronger baroclinicity and inflow on the left of the track and weaker baroclinicity on the right. The resulting gradient imbalance in the front-right quadrant triggers radial outflow through a gradient adjustment process that redistributes momentum and mass to restore dynamical balance. Therefore, the surface thermodynamic conditions over land play a critical role in shaping the evolution of the TCBL during landfall, with the strongest asymmetries in thermodynamic boundary layer height emerging when there are large thermal contrasts between the hurricane and the continental environment. Full article

The convergence of flexible electronics and miniaturized ultrasound transducers has accelerated the development of wearable ultrasound devices, offering innovative solutions for continuous, non-invasive physiological monitoring and disease diagnosis. This review systematically examines the recent progress in the field, focusing on three key aspects: physical principles, device design, and clinical applications. From the perspective of physical principles, we provide an in-depth analysis of the fundamental theories underlying ultrasound imaging, including acoustic wave propagation in biological tissues, interface reflection mechanisms, and Doppler effects. In terms of device design, we compare technical approaches for rigid and flexible ultrasound transducers, with particular emphasis on innovative designs for flexible transducers. The key developments discussed include optimization of piezoelectric materials, the fabrication of stretchable electrodes, and advances in flexible encapsulation materials. Regarding clinical applications, we categorize the use cases by anatomical region and illustrate their diagnostic value through representative examples, demonstrating their utility in disease detection, health monitoring, and sports medicine. Finally, we identify critical challenges such as signal stability, coupling material compatibility, and long-term wearability, while outlining future directions including AI-assisted diagnosis and multifunctional integration. This review aims to provide a comprehensive reference for both fundamental research and clinical translation of wearable ultrasound technologies. Full article

Background/Objectives: Recent advancements in innovative drug delivery nanosystems have significantly impacted wound healing, particularly through the incorporation of natural products. This study aimed to develop and characterize a Phlomis crinita extract-loaded nanostructured formulation (PCE-NF) as a topical therapy for skin wounds. Methods: This study involved the incorporation of P. crinita extract in a nanoemulsion by the high-energy emulsification method. This formulation was subjected to physicochemical and biopharmaceutical characterization, and a physical stability study over 30 days. Biocompatibility, tolerability, and irritant effects were assessed, while the wound healing potential was evaluated using in vitro skin models of fibroblasts and keratinocytes. Results: PCE-NF showed a homogeneous appearance with nanometric-sized spherical droplets of 212.27 nm and Newtonian behavior. This formulation showed a sustained release of its majority component (luteonin 7-(6″-acetylglucoside)), which followed a hyperbolic kinetic while showing high permeation, through healthy human skin, with 22.01 µg after 27 h. There were no cytotoxic effects of PCE-NF with improvements in skin barrier function and hydration levels. The wound healing potential of PCE-NF at 3.125 µg/mL was evidenced by enhanced cell migration and accelerated wound closure in 3T3-L1 and HaCaT cells, with values of 94.24 and 92.41%, respectively. Conclusions: These results suggest that this formulation could be used as an effective wound healing treatment. Full article

This study aims to develop environmentally friendly soil-stabilization materials by investigating the synergistic enhancement mechanism of industrial by-product lignin fibers (LFs) and sodium sulfate (Na₂SO₄) on the mechanical and micro-structural properties of cement-stabilized soil. A systematic evaluation was conducted through unconfined compressive strength (UCS), splitting tensile strength, and capillary water absorption tests, supplemented by microscopic analyses including XRD and SEM. The results indicate that the optimal synergistic effect occurs at 1.0% LF and 0.10% Na₂SO₄, which increases UCS and splitting tensile strength by 9.23% and 18.37%, respectively, compared to cement-stabilized soil. Meanwhile, early strength development is accelerated. Microscopically, LF physically bridges soil particles, forming aggregates, reducing porosity, and enhancing cohesion. Chemically, Na₂SO₄ acts as an activator, accelerating cement hydration and stimulating pozzolanic reactions to form calcium aluminosilicate hydrate and gypsum, which fill pores and densify the matrix. The synergistic mechanism lies in Na₂SO₄ enhancing the interaction between the LFs and clay minerals through ion exchange, facilitating the formation of a stable spatial network structure that inhibits particle sliding and crack propagation. This technology offers substantial sustainability benefits by utilizing paper-making waste LF and low-cost Na₂SO₄ to improve soil strength, toughness, and impermeability. Full article

Amid accelerating climate change, climate-related hazards—such as floods, wildfires, hurricanes, and sea-level rise—increasingly drive land transformations and pose growing risks to housing markets by affecting property valuations, insurance availability, mortgage performance, and broader financial stability. This review synthesizes recent progress in two distinct domains and their linkage: (1) assessing climate-related financial risks in housing markets, and (2) applying AI-driven remote sensing for hazard detection and land transformation monitoring. While both areas have advanced significantly, important limitations remain. Existing housing finance studies often rely on static models and coarse spatial data, lacking integration with real-time environmental information, thereby reducing their predictive power and policy relevance. In parallel, remote sensing studies using AI primarily focus on detecting physical hazards and land surface changes, yet rarely connect these spatial transformations to financial outcomes. To address these gaps, this review proposes an integrative framework that combines AI-enhanced remote sensing technologies with financial econometric modeling to improve the accuracy, timeliness, and policy relevance of climate-related risk assessment in housing markets. By bridging environmental hazard data—including land-based indicators of exposure and damage—with financial indicators, the framework enables more granular, dynamic, and equitable assessments than conventional approaches. Nonetheless, its implementation faces technical and institutional barriers, including spatial and temporal mismatches between datasets, fragmented regulatory and behavioral inputs, and the limitations of current single-task AI models, which often lack transparency. Overcoming these challenges will require innovation in AI modeling, improved data-sharing infrastructures, and stronger cross-disciplinary collaboration. Full article