Search Results (1,115)

Deep tight-reservoir fracability depends on temperature, fluid transport, in situ stress, fracture development, and injection energy, so no single response can provide a defensible ranking of fracturing conditions. This study develops a sparse second-order Choquet–Monte Carlo fracability framework. Additionally, the CRITIC method is used independently to quantify the information contrast of the five evaluation indicators. This was done using true triaxial sequential dual-well experiments conducted at 25–200 °C, horizontal stress differences of 3–9 MPa, and with either supercritical CO₂ (SC-CO₂) or water. CT scanning, U-Net segmentation, and three-dimensional reconstruction supplied fracture volume and fractal dimension; two-stage breakdown pressures and hydraulic injection work described initiation accessibility and energy demand. The CRITIC information weights were 0.261 for stress compatibility, 0.235 for injection-work demand, 0.182 for fluid mobility, 0.172 for specimen temperature, and 0.150 for pressure accessibility. The fitted second-order model identified positive temperature–fluid (0.122) and temperature–stress (0.071) non-additive coefficients, while the pressure–work coefficient was close to zero (−0.008). Sequential injection produced a consistent stage-dependent difference in breakdown pressure, with the second-stage value exceeding the first-stage value in every test. This observation is interpreted descriptively within the fixed sequential injection protocol. Condition No. 5 (SC-CO₂, 200 °C, 3 MPa) ranked first with a fracability index of 0.935 and a 95% Monte Carlo interval of 0.908–0.945. Leave-one-out cross-validation gave a Spearman coefficient of 0.830 and R² = 0.860. Within the tested domain, temperature was associated with improved fracability, particularly under the low stress-difference condition where enhanced SC-CO₂ mobility and thermal effects acted together. The framework therefore distinguishes coupled benefits, redundancies, and uncertainty that an additive score would conceal. Full article

Climate change is intensifying challenges to microbial water quality and household water security across Saharan and Sahelian Africa, where water scarcity, variable infrastructure, and reliance on decentralized and informal water sources can increase vulnerability to contamination. This structured narrative review synthesizes evidence on how climatic stressors, including extreme heat, ultraviolet radiation, drought, flooding, rainfall variability, and dust events, influence microbial contamination, persistence, transport, and exposure across groundwater, surface waters, drinking-water distribution systems, and household storage. Heavy rainfall and flooding can mobilize fecal contamination and microbial hazards into water sources, whereas drought and water scarcity can increase dependence on marginal supplies, prolong household storage, and create conditions favorable to post-collection contamination and microbial regrowth. Climatic effects vary across microbial groups and water matrices: temperature, sunlight, turbidity, sediments, biofilms, and hydrological conditions can differentially influence bacterial, viral, and protozoan persistence and transport. Saharan dust also represents a potential pathway for long-range microbial dispersal and deposition, although direct evidence linking individual dust events to pathogen concentrations in drinking-water sources remains limited. The review further shows that microbial water quality is insufficiently integrated with broader dimensions of household water security, including availability, reliability, accessibility, and perceived safety. Strengthening the evidence base will require greater integration of microbial, climatic, hydrological, infrastructure, and household water-security data to support climate-resilient water management and public-health protection in Saharan and Sahelian communities. Full article

Multilingual students’ repertoires are often framed either as resources for participation or as possible sources of difficulty, yet their situated use in special education remains underexamined. This study investigated how students in German special schools for social, emotional and behavioral development (SEBD) mobilized migration-related multilingual repertoires to address practical interactional problems and how situational conditions shaped the functions and consequences of these practices. A multi-sited ethnography was conducted in six SEBD special schools in the Rhine-Ruhr metropolitan region (North Rhine-Westphalia) between April 2024 and March 2025. Data comprised participant observation, written and talking fieldnotes, and informal ethnographic conversations. They were analyzed through a constant-comparative approach informed by reflexive grounded theory. Six recurring practice types were grouped into four result domains: Participation and Meaning-Making, Relational Positioning and Communicative Accessibility, Affective Mobilization and Counter-Positioning, and Navigation of Institutional Language Orders. Repertoire use had no fixed inclusive, disruptive, or resistant function. Its meaning emerged within interaction and changed with participation structures, public visibility, adult comprehension, and peer responses. In SEBD settings, migration-related linguistic marking and behavioral interpretation could reinforce one another. Multilingual practices should therefore be analyzed sequentially and situationally rather than treated as direct indicators of competence or disturbance. Full article

In disaster response and other infrastructure-limited settings, UAV-mounted access points can rapidly restore service availability for mobile ground users as demand and fleet availability evolve. Existing single-slot coverage formulations, however, can mask prolonged individual outages and do not jointly represent heterogeneous service priorities, finite battery capacities, and periodic recharging. We study persistent geometricmulti-UAV service coverage, where a user is available for service when it lies inside a UAV footprint. We propose Priority- and Outage-Guided Safe QMIX (POGS-QMIX), a hybrid hierarchical framework in which a centralized online coordinator forms conflict-reduced UAV–user targets from fleet-wide priority and outage information, while parameter-shared QMIX agents independently choose target-conditioned low-level actions. The framework couples class-balanced outage memory, assignment, dense target-progress feedback, and a return-energy action mask. The evaluation includes learning and non-learning baselines, greedy-versus-Hungarian assignment, multi-seed statistics, sensitivity studies, operating-condition studies, and energy-stress tests. In the default scenario, POGS-QMIX obtains high-priority coverage $0.547\pm 0.009$ and maximum high-priority outage $38.0\pm 4.7$ slots over five independent seeds. Full article

Cross-platform cultural heritage systems must coordinate structured domain data, shared services, real-time 3D representation, and device-specific interaction. This paper presents a metadata-centered architecture for delivering a numismatic collection through responsive web, map, conventional 3D, and immersive WebXR interfaces. It combines a relational metadata and media layer, shared REST-based services, and device-adaptive clients. It was instantiated with 253 historical coins. Instead of storing a coin-specific 3D model for each record, Babylon.js generates lightweight geometry at runtime and maps paired obverse and reverse images onto its surfaces. Record identifiers, metadata, media references, and query logic are reused across desktop, mobile, and head-mounted display access. An implementation-level check confirmed that an updated record was available through the catalog, map-related view, and 3D/WebXR gallery without client-specific duplication. Complementary formative evaluations involved 97 web participants and 19 WebXR participants, with mean System Usability Scale scores of 80.41 and 83.55, respectively. Feedback identified object manipulation, information legibility, visual fidelity, and interaction comfort as refinement priorities. This study contributes a system-level approach that connects shared cultural heritage services with conventional and immersive clients without separate collection databases or content-management workflows. Full article

Molecular dynamics simulations examined the roles of molecular structure, thermodynamic compatibility, intermolecular association, and mixture composition in the supercritical CO₂ extraction of ten crude oil components at 363.15 K and 15 MPa. Single-component extraction ratios ranged from 80.70% for n-hexane to 5.85% for 2-naphthol. Compounds of similar size differed widely, indicating that topology, aromaticity, and polar functional groups were more informative than molecular size alone. CO₂ solubility parameters obtained from MD agreed with estimates derived from NIST data, and δ_CO2 = 7.28ρ_r captured their reduced density dependence over 303.15–363.15 K. Extraction generally decreased with increasing oil–CO₂ solubility parameter difference. In binary systems evaluated using oil boundaries determined by the half density criterion, higher fractions of nonpolar partners were associated with increased total extraction ratios, whereas higher fractions of polar partners were associated with decreases. Multicomponent systems showed redistribution that depended on the overall composition, and relative diffusion coefficients qualitatively reflected mobility differences. The gas–oil interaction competition factor, R_comp, decreased from 1.985 to 0.087 in the same order as the extraction ratios. Both the thermodynamic and energetic correspondences persisted after excluding 2-naphthol. Configurations and radial distribution functions showed that association in nonpolar hydrocarbons was dominated by dispersion interactions, whereas polar and aromatic components exhibited additional hydrogen bonding, aromatic stacking, and dipolar or electrostatic organization. Local CO₂ enrichment near polar sites alone did not explain overall extraction. Overall, the selective transfer of individual components was consistent with a balance between local CO₂–oil association and collective oil–oil cohesion that depended on mixture composition, while molecular organization may regulate the accessibility of favorable CO₂ contact sites. Full article

The notion of “AI natives” is increasingly used to describe young learners’ presumed ease with generative artificial intelligence (GenAI), but the label often turns age and exposure into proxies for competence. This study re-examines that assumption through an exploratory secondary analysis of two open student datasets and proposes a practice-based relational framework for AI nativeness. In this framework, AI nativeness is not a generational identity, but a testable configuration of competence foundations, GenAI use practices, access conditions, and institutional mediation. Because the two datasets do not measure all four dimensions within the same learners, the framework is motivated rather than fully tested here. The results show that basic operational skills do not, on their own, explain AI readiness; critical information literacy is the most consistent positive predictor in the regression models. Student GenAI use and access conditions are also heterogeneous, forming four interpretable GenAI use/access profiles: low-adoption learners, high-intensity multi-taskers, mobile-dependent moderate users, and balanced cognitive adopters. These findings do not establish who is or is not an AI native. They show why the age-based label is analytically insufficient and why future research should examine AI nativeness through competence, practice, access, and institutional mediation together. Full article

Public health emergencies often unfold over extended periods and place sustained pressure on community-level governance, particularly when demands for supplies, information, medical access, and daily support exceed routine service capacity. This study examines how community response organizations develop adaptive capacity under such conditions, drawing on a Shanghai community during the 2022 COVID-19 lockdown. Grounded theory was used to analyze semi-structured interviews, field observations, archival documents, and online community records and to identify the process through which fragmented resident mutual aid developed into organized collaboration. The grounded analysis identifies four linked stages of organizational evolution: capacity building, structural emergence, institutional consolidation, and experience accumulation. Building on these findings, a system dynamics model formalizes selected causal relationships and explores the feedback interactions among demand pressure, material reserves, information gaps, panic, volunteer mobilization, organizational division of labor, institutional support, and trust. The analysis illustrates how, within the proposed mechanism, resident participation may be activated through social capital, stabilized through institutional coordination and rule support, and sustained through feedback linking service performance, information reliability, trust, and continued participation. The study provides a feedback-based explanation of how community response capacity develops under prolonged emergency pressure and clarifies how informal resident action and formal governance arrangements can become mutually reinforcing. These findings contribute to research on community emergency adaptation and offer implications for grassroots preparedness, volunteer coordination, and collaborative governance. Full article

Air transport improves accessibility and can make travel more affordable, but it also increases environmental burdens and pressure on tourism destinations, dimensions that are still often examined separately. This study develops the Air Transport Sustainability Tension Score, a framework for individual routes that identifies where mobility benefits and sustainability burdens coexist across European air connections. The analysis covers 11,065 directed routes and integrates accessibility, relative affordability derived from expected fares, environmental burden, and destination tourism pressure. Accessibility and relative affordability form the benefit dimension, while environmental activity and tourism pressure form the burden dimension. Their harmonic aggregation limits compensation and assigns high scores when both dimensions remain elevated. Relative affordability was derived from expected fares generated for each route through five-fold cross-validation with Ridge regression, Random Forest, CatBoost, and XGBoost. Each prediction therefore came from a model that excluded the corresponding observation during training. Among the evaluated fixed model configurations, XGBoost performed best, achieving a mean absolute price error of EUR 28.58 and an $R^2$ of 0.6871 on the logarithmic price scale. TreeSHAP was then used to interpret the model predictions. The environmental activity proxy correlated strongly with the strict CO₂ score derived from fleet information on 3622 routes. Across the sensitivity analyses, the broad route ordering remained comparatively stable, although exact membership in the upper decile was more sensitive to methodological choices. The primary upper decile contained 1107 routes. Monte Carlo weight variation retained 580 routes and the complete specification multiverse retained 506, with 421 supported by both procedures. Two route archetypes revealed distinct empirical profiles involving strong connectivity and environmental activity or greater tourism pressure at destinations. The framework provides an interpretable basis for differentiated air transport and destination management without automatically classifying routes as sustainable or unsustainable. Full article

The increasing decentralisation of work has expanded the range of locations in which employees can perform their tasks, making workplace location an increasingly important contextual dimension of work design. This study examines preferences for different workplace arrangements among Generation Z respondents and investigates the organisational, spatial, relational/status, and job-survival characteristics associated with these preferences. Data were collected from 731 respondents in Poland using a researcher-developed questionnaire. Seven workplace arrangements were evaluated, including onsite work at the organisation’s premises and six arrangements involving work outside or across the boundaries of the traditional organisational workplace: working from home, coworking, work at the client’s location, mobile work, platform work, and hybrid work. Descriptive statistics and Pearson correlations were complemented by six multiple linear regression models. Statistical inference was strengthened using HC3 heteroskedasticity-robust standard errors and Benjamini–Hochberg false discovery rate correction. Hybrid work received the highest preference rating, followed by working from home, whereas mobile work and work at the client’s location were evaluated less favourably. The regression models showed that different workplace arrangements were associated with different configurations of workplace characteristics. The strongest explanatory performance was obtained for working from home (R² = 0.353; adjusted R² = 0.318). For hybrid work, employment security emerged as the strongest robust association (β = 0.185) and remained significant after correction for multiple testing. Overall, the findings indicate that preferences for decentralised work cannot be reduced to a general preference for spatial flexibility. Instead, the observed pattern can be interpreted in terms of structured flexibility, combining some discretion over workplace location with organisational stability, autonomy, access to information, coordination, and social connectedness. Workplace location is therefore proposed as a contextual dimension for comparing configurations of established work-design characteristics rather than as a new independent work-design construct. Because the study is cross-sectional and sustainability outcomes were not directly measured, causal and sustainability interpretations should be made cautiously. Full article

Urban fragmentation is often approached through residential patterns, spatial distance and the uneven distribution of urban resources. However, in Southern European medium-sized cities, where socially contrasting neighbourhoods may be located in close physical proximity, fragmentation may operate through less visible everyday mechanisms. This article examines how selective spatial practices reflect and may reproduce unequal access to places, activities and opportunities, and how this perspective may inform debates on spatial governance and urban planning. Drawing on GPS tracking, in-depth interviews and mental maps, it analyses daily mobility, activity spaces and lived spatial boundaries in two socially contrasting neighbourhoods of Lleida, Spain. The article contributes to debates on urban inequality, understood as the structurally conditioned unequal distribution of resources, opportunities, capacities and recognition by conceptualising differentiated everyday geographies as both manifestations of this inequality and mechanisms through which it may be reproduced. The findings show how spatial practices and cognitive representations structure urban experience beyond residential segregation: physical proximity does not necessarily translate into shared urban experience: as some participants develop broader and socially legitimised relations with the city, whereas others display more restricted and symbolically bounded patterns of urban engagement. The article therefore advances practised accessibility as an analytical and planning perspective that incorporates the temporal, modal, cognitive and symbolic conditions that shape everyday access to urban opportunities beyond their informal availability. Full article

QR codes are widely used in digital authentication, mobile payment, access control, and information exchange, making QR code-based covert communication and hidden message delivery relevant to cybersecurity applications. This study proposes a QR code-based information-hiding method via module content modification based on corner-pixel grayscale adjustment. Secret bits are embedded into a QR code image through subtle grayscale adjustments of module corner pixels. To reduce visually noticeable embedding artifacts, embedding in adjacent module corners that share identical original grayscale values is prohibited, thereby preventing noticeable local contrast that could reveal hidden content. Gradient-based smoothing is further applied to suppress contrast artifacts within module interiors after embedding. A theoretical analysis of bilinear interpolation and quarter subregion averages is presented to justify the proposed extraction thresholds. Experiments across multiple QR code versions, error-correction levels, and embedding parameters show that the proposed method achieves an average embedding rate of approximately 1.9 bits per module while generally maintaining QR code readability across the tested commercial scanning devices. Exploratory random-noise experiments further show that hidden-message recovery remains possible up to the observed highest tolerable noise rates in the tested realizations. A comparison with four representative methods indicates that the proposed method achieves substantially higher embedding rates under the adopted comparison framework, demonstrating its potential for high-capacity QR code information-hiding while enabling successful hidden-message recovery under the evaluated conditions. Full article

This article presents a practice-oriented methodological proposal for designing inclusive multimodal learning content with Generative AI (GAI) in migrant adult literacy. It does not report an experimental intervention or a statistical evaluation of learning outcomes. Its contribution lies in formalizing a context-sensitive design pathway for early preA1–A2 literacy and language-learning provision in Italian CPIA settings, where learner profiles are highly heterogeneous, attendance may be discontinuous, and written language is both a learning goal and a barrier to participation. Unlike generic AI-supported instructional design frameworks, the proposed approach starts from recurrent communicative needs in adult migrant education and translates them into short, modular and reusable learning artifacts that coordinate textual, visual, audio-oral and interactive layers. The framework distinguishes multimodal design, understood as the pedagogical coordination of different semiotic modes, from the mere use of multiple media. It also integrates accessibility as a set of concrete design criteria, including linguistic readability, visual clarity, audio quality, layout, font size, contrast, cognitive load and usability in print or mobile formats. The article outlines a sequence of design operations: mapping learner profiles, selecting situated communicative scenarios, generating and revising textual material, developing visual and audio scaffolds, structuring guided interaction, and applying pedagogical, cultural and ethical review. An illustrative micro-unit on asking for information at a municipal office shows how this pathway can support dialog, visual glossary, audio practice, role-play and formative assessment. The proposal is intended for CPIA educators, adult literacy professionals, instructional designers and researchers in multimedia learning and educational technology. Its educational implication is that GAI can support inclusive material design only when its outputs are treated as provisional resources to be selected, adapted and validated through human pedagogical judgment. Full article

Rapid urban expansion in arid intermediate cities often produces fragmented urban structures that exacerbate inequalities in public transport accessibility and hinder sustainable mobility. However, the relationships between urban fragmentation, transport accessibility, and travel behavior remain insufficiently explored in pre-Saharan cities. This study investigates these interactions through the case of El Bayadh, Algeria, using an integrated methodology combining urban morphological analysis, Geographic Information Systems (GIS), a household survey of 577 households, traffic counts, institutional interviews, and spatial equality assessment based on the Gini coefficient. Public transport accessibility was evaluated using a 300 m walking threshold, complemented by sensitivity analyses at 400 m and 500 m. The results indicate that approximately 65% of the population lives within 300 m of a bus stop, although coverage is strongly concentrated in central districts. A Gini coefficient of 0.41, provided by the El Bayadh Directorate of Transport and computed across 20 urban zones, indicates moderate-to-high spatial inequalities in accessibility that persist despite increasing the service threshold, suggesting that these disparities are more closely associated with urban fragmentation than with the specific walking-distance threshold used to define service coverage. The transport network comprises 11 bus routes, approximately 160 bus stops, and 90 km of routes; however, limited service quality and uneven spatial distribution contribute to a high dependence on private transport, with 45% of trips made by private car, 35% by taxi, and only 20% by bus. These findings are consistent with accessibility inequalities arising from the mismatch between fragmented urban morphology, centralized urban functions, and the configuration of the public transport network. The proposed framework provides transferable insights for planning more equitable and sustainable mobility systems in rapidly urbanizing arid intermediate cities. Full article

Falls are a major cause of severe injury and mortality among older adults, requiring rapid state recognition and alerts in healthcare and caregiving environments. However, many existing fall-recognition approaches primarily focus on post-fall detection or assume access to cloud/GPU computing, leaving limited evidence for short-term pre-fall recognition on low-end CPU-based edge devices. This study proposes a lightweight CNN–TCN–Attention framework for recognizing fall and pre-fall states on resource-constrained edge devices. Using MediaPipe, three-dimensional coordinates and visibility scores of 33 human body landmarks are extracted from input videos. Raw RGB frames are not directly used by the classifier, thereby reducing the processing of visually identifiable information. A total of 2300 fall-related videos from the AI-Hub dataset were reorganized into three classes: normal, pre-fall, and fall. The pre-fall onset was defined as the point at which the downward vertical velocity of the nose landmark exceeded a dataset-specific threshold. The model uses a CNN to extract frame-level skeletal patterns, a temporal convolutional network (TCN) to learn temporal changes in posture, and an attention module to aggregate temporal features. It was deployed on a Raspberry Pi Zero 2 W using ONNX Runtime. The proposed model achieved 94.71% accuracy and a macro F1-score of 93.63%, with an average state-decision latency of 325.88 ms/decision. It improved accuracy by 2.83 percentage points over the lightweight CNN–LSTM–Attention baseline while maintaining comparable latency and achieved approximately 1.75× faster processing than the MobileNetV3–TCN–Attention model. Full article