Search Results (1,491)

This study presents a comprehensive computational analysis of flow rate efficiency during uranium extraction via the In Situ Recovery method. Using field data from a deposit located in Southern Kazakhstan, a series of mathematical models were developed to evaluate the distribution and balance of leaching solution. A reactive transport model incorporating uranium dissolution kinetics and acid–rock interactions were utilized to assess the accuracy of both traditional and proposed methods. The results reveal a significant spatial imbalance in sulfuric acid distribution, with up to 239.1 tons of acid migrating beyond the block boundaries. To reduce computational demands while maintaining predictive accuracy, two alternative methods, a streamline-based and a trajectory-based approach were proposed and verified. The streamline method showed close agreement with reactive transport modeling and was able to effectively identify the presence of intra-block reagent imbalance. The trajectory-based method provided detailed insight into flow dynamics but tended to overestimate acid overflow outside the block. Both alternative methods outperformed the conventional approach in terms of accuracy by accounting for geological heterogeneity and well spacing. The proposed methods have significantly lower computational costs, as they do not require solving complex systems of partial differential equations involved in reactive transport simulations. The proposed approaches can be used to analyze the efficiency of mineral In Situ Recovery at both the design and operational stages, as well as to determine optimal production regimes for reducing economic expenditures in a timely manner. Full article

This review outlines a comprehensive methodology for the research and development of heterogeneous catalytic technologies (R&D_HeCaTe). Emphasis is placed on the fundamental interactions between reactants, solvents, and heterogeneous catalysts—specifically the roles of catalytic centers and support materials (e.g., functional groups) in modulating activation energies and stabilizing catalytic functionality. Particular attention is given to catalyst deactivation mechanisms and potential regeneration strategies. The application of molecular modeling and chemical engineering analyses, including reaction kinetics, thermal effects, and mass and heat transport phenomena, is identified as essential for R&D_HeCaTe. Reactor configuration is discussed in relation to key physicochemical parameters such as molecular diffusivity, reaction exothermicity, operating temperature and pressure, and the phase and “aggressiveness” of the reaction system. Suitable reactor types—such as suspension reactors, fixed-bed reactors, and flow microreactors—are evaluated accordingly. Economic and environmental considerations are also addressed, with a focus on the complexity of reactions, selectivity versus conversion trade-offs, catalyst disposal, and separation challenges. To illustrate the breadth and applicability of the proposed framework, representative industrial processes are discussed, including ammonia synthesis, fluid catalytic cracking, methanol production, alkyl tert-butyl ethers, and aniline. Full article

This paper focuses on the numerical modeling of drug diffusion in biological tissues using fractional time-dependent parabolic equations with non-local boundary conditions. The model includes a Caputo fractional derivative to capture the non-local effects and memory inherent in biological processes, such as drug absorption and transport. The theoretical framework of the problem is based on the work of Alhazzani, et al.,which demonstrates the solution’s goodness, existence, and uniqueness. Building on this foundation, we present a robust numerical method designed to deal with the complexity of fractional derivatives and non-local interactions at the boundaries of biological tissues. Numerical simulations reveal how fractal order and non-local boundary conditions affect the drug concentration distribution over time, providing valuable insights into drug delivery dynamics in biological systems. The results underscore the potential of fractal models to accurately represent diffusion processes in heterogeneous and complex biological environments. Full article

Container liner shipping companies operate within a complex environment where they must balance profitability and service reliability. Meanwhile, evolving regulatory policies, such as surcharges imposed on ships of a particular origin or type on specific trade lanes, introduce new operational challenges. This study addresses the heterogeneous ship routing and demand acceptance problem, aiming to maximize two conflicting objectives: weekly profit and total transport volume. We formulate the problem as a bi-objective mixed-integer programming model and prove that the ship chartering constraint matrix is totally unimodular, enabling the reformulation of the model into a partially relaxed MIP that preserves optimality while improving computational efficiency. We further analyze key mathematical properties showing that the Pareto frontier consists of a finite union of continuous, piecewise linear segments but is generally non-convex with discontinuities. A case study based on a realistic liner shipping network confirms the model’s effectiveness in capturing the trade-off between profit and transport volume. Sensitivity analyses show that increasing freight rates enables higher profits without large losses in volume. Notably, this paper provides a practical risk management framework for shipping companies to enhance their adaptability under shifting regulatory landscapes. Full article

The accelerating integration of electric vehicles (EVs) into contemporary transportation infrastructure has underscored significant limitations in traditional charging paradigms, particularly in accommodating heterogeneous user requirements within dynamic operational environments. This study presents a differentiated optimization framework for EV charging strategies through the systematic classification of user types. A multidimensional decision-making environment is established for three representative user categories—residential, commercial, and industrial—by synthesizing time-variant electricity pricing models with dynamic carbon emission pricing mechanisms. A bi-level optimization architecture is subsequently formulated, leveraging deep reinforcement learning (DRL) to capture user-specific demand characteristics through customized reward functions and adaptive constraint structures. Validation is conducted within a high-fidelity simulation environment featuring 90 autonomous EV charging agents operating in a metropolitan parking facility. Empirical results indicate that the proposed typology-driven approach yields a 32.6% average cost reduction across user groups relative to baseline charging protocols, with statistically significant improvements in expenditure optimization (p < 0.01). Further interpretability analysis employing gradient-weighted class activation mapping (Grad-CAM) demonstrates that the model’s attention mechanisms are well aligned with theoretically anticipated demand prioritization patterns across the distinct user types, thereby confirming the decision-theoretic soundness of the framework. Full article

Natural carbonate stones such as limestones and marbles are widely used in heritage and contemporary architecture, yet their durability is increasingly threatened by wildfire-related thermal stress. Since water transport plays a key role in stone deterioration, understanding how high temperatures affect hydric behavior is critical for conservation. This study investigates thirteen Portuguese carbonate lithotypes (including marbles, limestones, a travertine, and a breccia) exposed to temperatures of 300 °C and 600 °C. Capillary absorption and open porosity were measured, alongside Leeb hardness (HL) and ultrasonic pulse velocity (UPV), to evaluate their predictive capacity for post-fire moisture behavior. Results show that thermal exposure increases porosity and capillary uptake while reducing mechanical cohesion. Strong correlations between UPV and hydric parameters across temperature ranges highlight its reliability as a non-invasive diagnostic tool. HL performed well in compact stones but was less consistent in porous or heterogeneous lithologies. The findings support the use of NDT tests, like UPV and HL, for rapid post-fire assessments and emphasize the need for lithology-specific conservation strategies. Full article

In this case study, we used the Delta Simulation Model II (DSM2) to study the salt balance at the land–water interface in the river delta of California’s San Francisco Estuary. Drainage, a source of water and salt for adjacent channels in the study area, is affected by channel salinity. The DSM2 approach has been adopted by several hydrodynamic models of the estuary to enforce water volume balance between diversions, evapotranspiration and drainage at the land–water interface, but does not explicitly enforce salt balance. We found deviations from salt balance to be quite large, albeit variable in magnitude due to the heterogeneity of hydrodynamic and salinity conditions across the study area. We implemented a procedure that approximately enforces salt balance through iterative updates of the baseline drain salinity boundary conditions (termed loose coupling). We found a reasonable comparison with field measurements of drainage salinity. In particular, the adjusted boundary conditions appear to capture the range of observed interannual variability better than the baseline periodic estimates. The effect of the iterative adjustment procedure on channel salinity showed substantial spatial variability: locations dominated by large flows were minimally impacted, and in lower flow channels, deviations between baseline and adjusted channel salinity series were notable, particularly during the irrigation season. This approach, which has the potential to enhance the simulation of extreme salinity intrusion events (when high channel salinity significantly impacts drainage salinity), is essential for robustly modeling hydrodynamic conditions that pre-date contemporary water management infrastructure. We discuss limitations associated with this approach and recommend that—for this case study—further improvements could best be accomplished through code modification rather than coupling of transport and island water balance models. Full article

The development of the Great Wall National Cultural Park has unleashed the potential for integrating cultural and tourism development along the Great Wall. However, ICH along the Great Wall, a key part of its cultural identity, suffers from low recognition and a mismatch between protection and development efforts. This study analyzes provincial-level and above ICH along Hebei’s Great Wall using geospatial tools and the Geographical Detector model to explore distribution patterns and influencing factors, while Geographically Weighted Regression is utilized to reveal spatial heterogeneity. It tests two hypotheses: (H1) ICH shows a clustered pattern; (H2) economic factors have a greater impact than cultural and natural factors. Key findings show: (1) ICH distribution is numerically balanced north–south but spatially uneven, with dense clusters in the south and scattered patterns in the north. (2) ICH and crafts cluster significantly, while dramatic balladry spreads evenly, and other categories are random. (3) Average annual temperature and precipitation have the greatest impact on ICH distribution, with the factors ranked as: natural > cultural > economic. Multidimensional interactions show significant enhancement effects. (4) Influencing factors vary spatially. Population density, transport, temperature, and traditional villages are positively related to ICH. Elevation, precipitation, tourism, and cultural institutions show mixed effects across regions. These insights support targeted ICH conservation and sustainable development in the Great Wall cultural corridor. Full article

This study investigates the behavior of phosphate ion transport through two structurally distinct anion-exchange membranes—AMV (homogeneous) and HC-A (heterogeneous)—in an electrodialysis system under both static and stirred conditions at varying pH levels. Chronopotentiometric and current–voltage analyses were used to investigate the influence of pH and hydrodynamics on ion transport. Under underlimiting (ohmic) conditions, the AMV membrane exhibited simultaneous transport of H₂PO₄⁻ and HPO₄²⁻ ions at neutral and mildly alkaline pH, while such behavior was not verified at acidic pH and in all cases for the HC-A membrane. Under overlimiting current conditions, AMV favored electroconvection at low pH and exhibited significant water dissociation at high pH, leading to local pH shifts and chemical equilibrium displacement at the membrane–solution interface. In contrast, the HC-A membrane operated predominantly under strong electroconvective regimes, regardless of the pH value, without evidence of water dissociation or equilibrium change phenomena. Stirring significantly impacted the electrochemical responses: it altered the chronopotentiogram profiles through the emergence of intense oscillations in membrane potential drop at overlimiting currents and modified the current–voltage behavior by increasing the limiting current density, reducing electrical resistance, and compressing the plateau region that separates ohmic and overlimiting regimes. Additionally, both membranes showed signs of NH₃ formation at the anodic-side interface under pH 7–8, associated with increased electrical resistance. These findings reveal distinct ionic transport characteristics and hydrodynamic sensitivities of the membranes, thus providing valuable insights for optimizing phosphate recovery via electrodialysis. Full article

The multiscale interactive system composed of wind, leaves, and droplets serves as a critical dynamic unit in precision orchard spraying. Its coupling mechanisms fundamentally influence pesticide transport pathways, deposition patterns, and drift behavior within crop canopies, forming the foundational basis for achieving intelligent and site-specific spraying operations. This review systematically examines the synergistic dynamics across three hierarchical scales: Droplet–leaf surface wetting and adhesion at the microscale; leaf cluster motion responses at the mesoscale; and the modulation of airflow and spray plume diffusion by canopy architecture at the macroscale. Key variables affecting spray performance—such as wind speed and turbulence structure, leaf biomechanical properties, droplet size and electrostatic characteristics, and spatial canopy heterogeneity—are identified and analyzed. Furthermore, current advances in multiscale modeling approaches and their corresponding experimental validation techniques are critically evaluated, along with their practical boundaries of applicability. Results indicate that while substantial progress has been made at individual scales, significant bottlenecks remain in the integration of cross-scale models, real-time acquisition of critical parameters, and the establishment of high-fidelity experimental platforms. Future research should prioritize the development of unified coupling frameworks, the integration of physics-based and data-driven modeling strategies, and the deployment of multimodal sensing technologies for real-time intelligent spray decision-making. These efforts are expected to provide both theoretical foundations and technological support for advancing precision and intelligent orchard spraying systems. Full article

Background: Lysosomal storage diseases (LSDs) are a genetically and clinically heterogeneous group of inborn errors of metabolism caused by variants in genes encoding lysosomal hydrolases, membrane proteins, activator proteins, or transporters. These disease-causing variants lead to enzymatic deficiencies and the progressive accumulation of undegraded substrates within lysosomes, disrupting cellular function across multiple organ systems. While classical phenotypes typically manifest in infancy or early childhood with severe multisystem involvement, a combination of advances in molecular diagnostics [particularly next-generation sequencing (NGS)] and improved understanding of disease heterogeneity have enabled the identification of attenuated forms characterised by residual enzyme activity and later-onset presentations. These milder phenotypes often evade early recognition due to nonspecific or isolated symptoms, resulting in significant diagnostic delays and missed therapeutic opportunities. Objectives/Methods: This study characterises the clinical, biochemical, and molecular profiles of 10 adult patients diagnosed with LSDs, all representing attenuated forms, and discusses them alongside a narrative review. Results: Enzyme activity, molecular data, and phenotypic assessments are described to explore genotype–phenotype correlations and identify diagnostic challenges. Conclusions: These findings highlight the variable expressivity and organ involvement of attenuated LSDs and reinforce the importance of maintaining clinical suspicion in adults presenting with unexplained cardiovascular, neurological, ophthalmological, or musculoskeletal findings. Enhanced recognition of atypical presentations is critical to facilitate earlier diagnosis, guide management, and enable cascade testing for at-risk family members. Full article

This research examines the traffic disruptions resulting from the collapse of the Francis Scott Key Bridge in Baltimore, utilizing advanced econometric methods and real-time ClearGuide data. Employing Fixed Effects (FEs), Mixed Effects (MEs), Difference-in-Differences (DiDs), and stratified regression models, the study uniquely examines the impacts of congestion across Immediate, Fall, and Winter periods, distinctly separating AM and PM peak patterns. Significant findings include severe PM peak congestion, up to four times greater than AM peak congestion, particularly on critical corridors such as the Harbor Tunnel Thruway northbound and MD-295 northbound. Initial route-level impacts were heterogeneous, gradually becoming uniform as the network adapted. The causal DiD analysis provides strong evidence that increased congestion is causally linked to proximity to the collapse. It is anticipated that incorporating the suggested framework will yield insightful information for stakeholders and decision-makers, such as targeted freight restriction, peak-hour dynamic pricing, corridor-specific signal adjustments, and investments in real-time traffic monitoring systems to strengthen transportation network resilience. Full article

Dark skies, a vital natural and cultural resource, have been increasingly threatened by light pollution due to rapid urbanization, leading to ecological degradation and biodiversity loss. As a key strategy for sustainable regional development, dark sky parks (DSPs) not only preserve nocturnal environments but also enhance livability by balancing urban expansion and ecological conservation. This study develops a novel framework for evaluating DSP suitability, integrating ecological and socio-economic dimensions, including the resource base (e.g., nighttime light levels, meteorological conditions, and air quality) and development conditions (e.g., population density, transportation accessibility, and tourism infrastructure). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, we employ Delphi expert consultation, GIS spatial analysis, and multi-criteria decision-making to identify optimal DSP locations and prioritize conservation zones. Our key findings reveal the following: (1) spatial heterogeneity in suitability, with high-potential zones being concentrated in the GBA’s northeastern, central–western, and southern regions; (2) ecosystem advantages of forests, wetlands, and high-elevation areas for minimizing light pollution; (3) coastal and island regions as ideal DSP sites due to the low light interference and high ecotourism potential. By bridging environmental assessments and spatial planning, this study provides a replicable model for DSP site selection, offering policymakers actionable insights to integrate dark sky preservation into sustainable urban–regional development strategies. Our results underscore the importance of DSPs in fostering ecological resilience, nighttime tourism, and regional livability, contributing to the broader discourse on sustainable landscape planning in high-urbanization contexts. Full article

Background/Objectives: Frailty is a multifactorial clinical syndrome characterized by diminished physiological reserves and increased vulnerability to stressors. It is increasingly recognized as a predictor of poor outcomes in cardiac rehabilitation (CR). However, how frailty is defined, assessed, and addressed across outpatient CR programmes remains unclear. This scoping review aimed to map the extent, range, and nature of research examining frailty in the context of outpatient CR, including how frailty is measured, its impact on CR participation and outcomes, and whether sex and gender considerations or participation barriers are reported. Methods: Following the PRISMA-ScR guidelines, we conducted a comprehensive search across six electronic databases (from inception to 15 May 2025). Eligible peer-reviewed studies included adult participants assessed for frailty using validated tools and enrolled in outpatient CR programmes. Two reviewers independently screened citations and extracted data. Results were synthesized descriptively and narratively across three domains: frailty assessment, sex and gender considerations, and barriers to CR participation. The protocol was registered with the Open Science Framework. Results: Thirty-nine studies met inclusion criteria, all conducted in the Americas, Western Pacific, or Europe. Frailty was assessed using 26 distinct tools, most commonly the Kihon Checklist, Fried’s Frailty Criteria, and Frailty Index. The median pre-CR frailty prevalence was 33.5%. Few studies (n = 15; 38.5%) re-assessed frailty post-CR. Sixteen studies reported sex or gender data, but none applied sex- or gender-based analysis (SGBA) frameworks. Only eight studies examined barriers to CR participation, identifying physical limitations, emotional distress, cognitive concerns, healthcare system-related factors, personal and social factors, and transportation as key barriers. Conclusions: The literature on frailty in CR remains fragmented, with heterogeneous assessment methods, limited global representation, and inconsistent attention to sex, gender, and participation barriers. Standardized frailty assessments and individualized CR programme adaptations are urgently needed to improve accessibility, adherence, and outcomes for frail individuals. Full article

Spatial association analysis is essential for understanding interdependencies, spatial proximity, and distribution patterns within spatial data. The spatial scale is a key factor that significantly affects the result of spatial association mining. Traditional methods often rely on a fixed distance threshold (bandwidth) to define the scale effect, which can lead to scale sensitivity and discontinuity results. To address these limitations, this study introduces the Fuzzy Geographically Weighted Colocation Quotient (FGWCLQ) method. By integrating fuzzy theory, FGWCLQ replaces binary distance cutoffs with continuous membership functions, providing a more flexible and stable approach to spatial association mining. Using Point of Interest (POI) data from the Beijing urban area, FGWCLQ was applied to explore both intra- and inter-category spatial association patterns among star hotels, transportation facilities, and tourist attractions at different fuzzy neighborhoods. The results indicate that FGWCLQ can reliably discover global prevalent spatial associations among diverse facility types and visualize the spatial heterogeneity at various spatial scales. Compared to the deterministic GWCLQ method, FGWCLQ delivers more stable and robust results across varying spatial scales and generates more continuous association surfaces, which enable clear visualization of hierarchical clustering. Empirical findings provide valuable insights for optimizing the location of star hotels and supporting decision-making in urban planning. The method is available as an open-source Matlab package, providing a practical tool for diverse spatial association investigations. Full article