Search Results (15,503)

In China’s latest mathematics curriculum, project-based learning (PBL) foregrounds mathematical problem solving (MPS) as student-led inquiry in authentic contexts. This study examines teachers’ beliefs about MPS within PBL, and how such beliefs are enacted in planning and teaching. Using a constant comparative approach, we drew on interviews, lesson plans, and reflective accounts from 14 mathematics teachers. Most teachers emphasised application and creativity, positioning themselves as guides/supporters who facilitate students’ exploration. Consistent with these beliefs, lesson plans commonly drew on personally and socially grounded contexts and featured challenging, open-ended tasks attending to cognitive breadth and depth. While espoused beliefs largely aligned with described implementation, a minority endorsed procedure-focused instruction, revealing tensions between exploration- and content-oriented approaches. Examining teachers’ beliefs can inform understanding of progress in curriculum reform. Sustained, long-term professional learning—supported by institutional resources and professional autonomy—is needed to help teachers navigate these tensions. Full article

The growing reliance on cyber deception as a defensive mechanism has revealed persistent limitations in existing deception infrastructures, particularly in their ability to scale, adapt, and provide continuous observability under realistic adversarial workloads. Conventional honeypot deployments are predominantly monolithic and statically configured, which constrains their responsiveness to dynamic attack conditions and limits their applicability in contemporary distributed environments. This work presents a microservice-oriented cyber deception platform that reconceptualizes deception infrastructure as a composition of loosely coupled, independently deployable services. The platform integrates containerized honeypots, a lightweight API-driven orchestration layer, and a centralized telemetry pipeline to enable rapid instantiation, dynamic reconfiguration, and high-resolution monitoring of attacker interactions. Unlike prior approaches that treat deployment, orchestration, and monitoring as separate concerns, the proposed design explicitly unifies these components within a single, measurable system architecture. To support principled reasoning about system behaviour, the paper introduces first-order analytical models that characterize deployment latency, resource utilisation, telemetry throughput, and operational cost as functions of attacker concurrency. These models are not intended as exact predictors, but as tractable abstractions that enable interpretation of system performance and guide capacity planning. Model parameters are empirically derived and validated through controlled experimentation. Evaluation is conducted within a reproducible cyber-range environment using scripted adversarial workloads that emulate reconnaissance, authentication attempts, and sustained interactive sessions. The results indicate that containerised deployment reduces instantiation latency to approximately 1.2 s under warm-start conditions, compared to tens of seconds for virtual machine-based baselines. Resource utilisation exhibits approximately linear scaling under moderate concurrency, while the telemetry pipeline sustains ingestion rates exceeding 18,000 events per minute without observable loss. Stress testing further reveals that telemetry processing, rather than orchestration, constitutes the primary scalability bottleneck. These findings suggest that microservice-based architectures can provide a viable and extensible infrastructure substrate for cyber deception, supporting both operational deployment and integration with higher-level adaptive and learning-based defence mechanisms. The contribution of this work lies not in introducing new deception strategies, but in enabling their practical realisation through a scalable and observable system design. Full article

Tree Bark-Derived bio-based polymers are promising renewable materials for sustainable coatings, surface protection, adhesives, and functional films. This review aims to clarify how harvesting processes affect raw-material quality and coating performance. The materials discussed include Raw Lacquer, pine resin-derived rosin, turpentine, and tree gums. Key harvesting factors, such as incision depth, tapping frequency, collection method, environmental conditions, and tree physiological status, can influence yield stability, impurity content, enzyme activity, viscosity, chemical composition, and batch consistency. These changes further affect film formation, curing behavior, adhesion, barrier properties, corrosion resistance, water sensitivity, and durability. Traditional manual harvesting is flexible but labor-intensive, skill-dependent, and difficult to standardize. Recent precision and intelligent harvesting technologies, including controlled-depth cutting, low-damage incision, multi-sensor perception, adaptive trajectory planning, and closed collection, provide new approaches for improving harvesting efficiency, reducing contamination, protecting tree health, and supplying coating-grade raw materials. This review establishes a framework linking feedstock characteristics, harvesting parameters, raw-material quality, and coating film performance, and outlines future directions for sustainable, automated, and low-damage harvesting to support high-quality bio-based coatings. Full article

Generation Z consumers are reshaping food consumption patterns in urban digital environments, particularly in restaurant contexts characterized by high choice complexity and uncertainty. In Mexico, the evolution of the restaurant industry has intensified the need to understand how digital cues shape consumer food choices. Addressing this gap, this study examines how Social Media Marketing (SMM), Social Media electronic Word of Mouth (Social Media eWOM), and Social Media Influencers (SMIs) shape food consumption intention among Generation Z in Mexico City. Grounded in the Stimulus–Organism–Response (SOR) model and integrating the attitudinal foundations of the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB), this study analyzes how these digital factors impact food consumption intention (operationalized as restaurant purchase intention) through the mediating psychological mechanism of Consumer Brand Engagement (CBE). A quantitative, non-experimental design was employed using a sample of 406 respondents, and data were analyzed through Structural Equation Modeling (SEM). The results indicate that the model explains 73.6% of the variance in food consumption intention. SMM emerged as the strongest direct predictor, followed by Social Media eWOM and SMIs. Crucially, CBE mediates only the relationship between influencers and consumption intention. Conversely, both SMM and Social Media eWOM exert direct effects that bypass affective engagement. These findings highlight the role of digital ecosystems as cognitive proxies in restaurant selection, providing actionable insights for restaurant SMEs to optimize digital strategies and enhance economic resilience. They also suggest potential implications for healthier and more sustainable urban food environments. Full article

As a core component of terrestrial ecosystems, forests play an irreplaceable ecological role in carbon sequestration, biodiversity conservation, and global climate regulation. Home to key global forest belts including the Congo Basin, the African continent’s forest changes directly shape regional ecological balance and sustainable development while profoundly affecting global ecological security and climate dynamics. Based on the Shared Socioeconomic Pathways (SSPs), a unified narrative framework for global socioeconomic and environmental change scenarios, this study couples techniques such as the Future Land Use Simulation (FLUS) model, dynamic degree analysis, transition matrix, K-means clustering analysis, and patch fragmentation analysis. This work aims to answer two key questions: (1) What are the spatiotemporal characteristics and dominant drivers of African woodland changes under different SSPs? (2) How do spatial clustering and fragmentation patterns vary across scenarios? It systematically predicts and analyzes the spatiotemporal characteristics, driving mechanisms, and fragmentation change patterns of African woodlands in 2030, 2050, and 2070 under five scenarios (SSP1-SSP5) with 2020 as the baseline. These five official IPCC SSP frameworks represent five distinctly divergent socioeconomic development trajectories ranging from sustainable to fossil-fuel-driven development, which are the core differentiated scenarios recommended by IPCC; full inclusion facilitates systematic comparison of varied forest feedback features across Africa’s diversified national development backgrounds. The research results show that understory forests in the SSP5 (Fossil Fuel-dominated Development) scenario exhibit a stable growth trend, with the total area transferred in significantly exceeding the area transferred out from 2020 to 2070, resulting in a net increase of 143,513 km². This growth occurs because high-income economies under this scenario invest heavily in ecological restoration and forest protection, offsetting carbon-intensive development impacts. The core forest density continues to increase and is distributed in contiguous areas; the SSP4 (uneven development) scenario regarding forest degradation is the most severe, with the dynamic rate expected to drop to −0.05% between 2050 and 2070, and a net transfer of −265,581 km². Forest fragmentation is highest, and the core density area is gradually shrinking. Cluster analysis shows that forest area remains relatively stable in most African countries, with stable countries accounting for as much as 95.49% under scenario SSP5. Regions with woodland expansion are mainly distributed in North Africa and localized parts of Southern Africa. After refinement using independent tree-density evidence, woodland expansion in South Africa is shown to be more limited and spatially heterogeneous; these newly expanded woodlands are mostly artificial plantations and alien invasive tree stands rather than native natural woodlands, mainly occurring in eastern and southeastern areas rather than in arid western regions. The spatiotemporal transfer process exhibits significant periodic differentiation, with 2030–2050 being a critical transitional period for forest change, and the differentiation effect between scenarios intensifying. Fragmentation analysis indicates that scenario SSP3 (regional rivalry, with moderate population growth and weak policy constraints) has the best forest integration and the lowest degree of fragmentation, while scenario SSP4 is most strongly affected by human activities and has the highest risk of patch fragmentation. These findings can provide a scientific basis for African countries to formulate differentiated forest protection policies and optimize ecological restoration plans, while also offering theoretical insights for continental-scale forest ecological management. Full article

There is a typical coopetition relationship between the urban rail transit (URT) network scale and the urban development (UD) level. A reasonable URT network scale is essential for promoting sustainable UD. Currently, the determination of the URT network scale for planning primarily relies on qualitative approaches such as static estimation and analogical methods, which fail to dynamically reflect the coopetition relationship between URT and UD. An improved time-varying parameter Lotka–Volterra (LV) model derived from ecological theory is employed to describe the coopetition relationship between the URT network scale and the UD level. The sliding-window least squares method is applied to estimate parameters of the model. Based on the improved LV model, the lower bound of the URT network scale is obtained by solving for the minimum network scale required to promote sustainable UD under a cooperative relationship; the upper bound of the URT network scale is obtained by solving for the maximum network scale that urban resources can support under competitive conditions. The proposed model is validated using eight Chinese cities with different UD levels. The study offers quantitative theoretical insights for determining the reasonable URT network scale for planning. Full article

Flash flood events are among the most critical hydrological hazards in arid and semi-arid regions, posing extreme threats to critical infrastructure, human safety, and sustainable development plans. This paper evaluates the flash flood susceptibility of the Al’Ataya catchment, a key watershed on the southern Red Sea coast, using an integrated geospatial analysis approach. To assess and quantify the flood hazard, we investigated 15 morphometric parameters for 24 particular sub-catchments within a sixth-order drainage system. Two complementary methods, the Morphometric Ranking Method and El-Shamy’s approach, were utilized to classify the catchment into different flood susceptibility levels. Results from the Ranking Method identified seven sub-catchments (SC-2, SC-3, SC-6, SC-7, SC-8, SC-9, and SC-19) as having high flood hazard levels, mainly driven by large watershed areas, steep slopes, and high relief ratios. In contrast, El-Shamy’s approach resulted in a different evaluation, identifying sub-catchments in Zone B (SC-23, SC-16, SC-17, SC-15, SC-6, SC-20) as high hazard sub-catchments due to the particular relationship between the bifurcation ratio parameter and the drainage density and stream frequency parameters. The integration of the two methods suggests that the susceptibility factor is controlled by the combined influence of a low drainage density and steep mountainous terrain draining toward the coastal zone. These results provide a spatial model for flood mitigation and early warning systems, supporting Saudi Vision 2030 through improvement to the development of southern urban centers such as Al’Ataya and Sabya. Full article

Hydropower dams constitute key components of sustainable energy and water resource management, while their long-term operation increasingly depends on social acceptance and local community support. Within this context, the current study investigates residents’ perceptions of the environmental, social, and economic advantages and adverse impacts associated with the operation of the Nestos River dams. It explores the role of the NIMBY (Not In My Back Yard) phenomenon in shaping local attitudes. Data were collected during 2020–2021, and a stratified random sampling design was applied, involving 1101 residents living in mountainous, semi-mountainous, and lowland areas of the Nestos River basin. Reliability analysis and factor analysis were employed to assess the consistency of responses and identify the underlying factors shaping residents’ perceptions. The results indicate that respondents recognize significant benefits associated with the dams, particularly clean energy production and the creation of lacustrine ecosystems, while simultaneously expressing concerns regarding the disruption of the river’s natural flow, biodiversity degradation, and landscape alteration. The findings also reveal complex, spatially differentiated NIMBY dynamics, suggesting that although dams are perceived as socially beneficial infrastructures, their localized impacts influence community acceptance. Overall, the study highlights the importance of incorporating local perceptions into the planning and management of hydraulic infrastructures and provides evidence supporting socially acceptable and sustainable approaches to existing and future dam projects. Full article

Background: Liver cancer is a major public health problem in Thailand due to its high incidence and mortality. Although hepatectomy is a potentially curative treatment, it is a complex procedure with a high risk of postoperative complications, necessitating a structured and systematic approach to care. Objectives: This study aimed to develop a clinical practice guideline (CPG) for patients with liver cancer undergoing hepatectomy and to evaluate the feasibility of its implementation in relation to outcomes for healthcare providers, the organization, and patients. Methods: This implementation research was conducted in three phases: (1) an evidence-triggered phase, (2) an evidence-supported phase, and (3) an evidence-observed phase. The CPG covered five stages of care: preoperative, intraoperative, postoperative, discharge planning, and post-discharge follow-up. It was implemented through a multidisciplinary approach, with an advanced practice nurse (APN) facilitating adherence to Enhanced Recovery After Surgery (ERAS) components. Data were analyzed using descriptive statistics. Results: Healthcare personnel demonstrated high adherence to the CPG and reported high feasibility of implementation. After implementation, favorable trends were observed in postoperative complications, length of hospital stay, hospitalization costs, and patient satisfaction compared with the historical pre-implementation period. The CPG also appeared to support clearer care standards and multidisciplinary coordination. Conclusions: The developed CPG was feasible and contextually appropriate for ERAS-based hepatectomy care in this setting. Preliminary findings suggest favorable trends in care processes and selected outcomes. Larger controlled studies with longer follow-up are needed to determine effectiveness and sustainability. Full article

The Ningxia Yellow River Urban Agglomeration, located in the ecologically fragile arid and semi-arid zone of the upper Yellow River, serves as a critical spatial carrier for maintaining the ecological security of the Yellow River Basin and supporting the regional economy and population agglomeration in Ningxia. Driven by rapid urbanization, intensified human–land conflicts have induced widespread ecological degradation and unbalanced water–soil resource allocation across the region. Based on land use data from 2010, 2015, 2020 and 2023, we applied the land use transition matrix, land use dynamic degree and standard deviational ellipse to characterize the spatiotemporal patterns of spatial expansion of the Ningxia Yellow River Urban Agglomeration over the past decade. The Patch-generating Land Use Simulation (PLUS) model was further employed to predict the land use demand and spatial distribution of the study area under diverse scenarios in 2035. The research results reveal three key findings. First, grassland, cropland and unused land constitute the dominant land use types across the study region, jointly occupying more than 90% of the total territorial area. Over the past decade, regional land use has undergone noticeable changes: grassland area has continuously declined, cropland and built-up land have sustained steady expansion, and water areas have experienced a mild reduction. Land use conversions mainly occur among grassland, cropland and built-up land. Second, driving factors vary substantially in their spatial contributions to the expansion of different land use types. The spatial growth of cropland and built-up land is comprehensively shaped by terrain conditions, economic development and transportation location superiority. In comparison, the distribution and dynamic changes in forestland, grassland and water areas are predominantly restricted by natural elements, including precipitation, temperature and soil characteristics. Third, multi-scenario simulation results verify that differentiated territorial spatial planning and regulatory policies profoundly affect the evolutionary trajectory of regional territorial patterns. The natural development scenario experienced the most intensive expansion of built-up land, with a newly increased area of 181.11 km². The ecological protection scenario can effectively curb the loss of ecological land and minimize the shrinkage of grassland resources. The cropland protection scenario is conducive to stabilizing cropland scale to the greatest extent and restraining the disorderly sprawl of urban land. The sustainable development scenario realizes coordinated and balanced changes in all land use types and delivers mutually beneficial progress between regional ecological conservation and socioeconomic development. Full article

Artificial intelligence (AI) is increasingly used to help consumers detect greenwashing in online food markets, yet how AI-use motivations relate to rational green food consumption intention (RCI) remains unclear. Integrating information processing theory, the consumer decision-making process model, and the theory of planned behavior, this study examines how risk avoidance (RA), performance expectations (PE), and health benefits (HB) are associated with RCI through subjective norm (SN) and perceived behavioral control (PBC). Based on 619 valid responses from a cross-sectional online survey, the data were analyzed using partial least squares structural equation modeling (PLS-SEM) and artificial neural network (ANN). The PLS-SEM results show that PE, RA, SN, and PBC are significantly associated with RCI, whereas HB has no significant direct association. SN is strongly associated with PBC, and the SN–PBC sequential mediation path is supported for RA, PE, and HB. The RA–PBC–RCI path is not supported, indicating that risk awareness does not automatically translate into perceived control. The ANN results identify PE as the strongest nonlinear predictor, followed by RA, while HB shows the weakest predictive importance. The findings advance AI-mediated sustainable consumption research and provide intention-level evidence for responsible online green food purchasing. Full article

Sustainable transport transformation increasingly depends on the configuration and performance of urban infrastructure systems. In coastal and port cities, decarbonizing transport is particularly complex due to spatial constraints, heritage protection requirements, and the coexistence of freight and passenger flows. In such environments, accessibility functions as a key indicator of transport infrastructure performance, reflecting how effectively transport systems enable low-carbon and multimodal mobility choices. Gdynia, a major Baltic port city in Poland, represents a context in which infrastructure limitations intersect with growing mobility demand. The concentration of port-related traffic, compact urban form, and limited opportunities for network expansion create structural conditions that may reinforce car dependency. This study examines infrastructure and accessibility challenges at the micro-scale of the Faculty of Navigation at Gdynia Maritime University, a centrally located campus with limited integration into public and active transport systems. Based on a survey of 342 respondents, including students and employees, the research analyzes modal split, travel time, and perceived barriers to sustainable mobility. The findings reveal infrastructure gaps in public transport connectivity, cycling network integration, and parking policy, collectively influencing transport behavior and constraining the shift toward low-carbon mobility. The study highlights the importance of infrastructure alignment, intermodal integration, and accessibility-based planning as prerequisites for smart and sustainable transport systems in coastal areas. Full article

Background: Community-based mental health promotion has gained increasing relevance as a strategy to strengthen population well-being and complement formal healthcare services. However, existing initiatives remain fragmented, and their integration into health systems and public policy frameworks has not been systematically examined. This scoping review aimed to map community-based mental health promotion strategies and analyze their alignment with public health systems and policy frameworks. Methods: A scoping review was conducted following the Joanna Briggs Institute methodology and reported according to the PRISMA-ScR guidelines. Searches were conducted in April 2025 across major databases, including Scopus and PubMed, covering studies published between 1990 and 2024. The retrieved records were subsequently reviewed and analyzed by the researchers between 1 May 2025 and September 2025 Documents published after 2024 were used only as contextual or policy references and were not included in the review corpus. Eligibility criteria were defined using the Population–Concept–Context framework. Two reviewers independently screened records and extracted data. Results: A total of 3799 records were identified, of which 76 studies met the inclusion criteria. Most interventions were implemented in school (18.4%) and community (21.1%) settings and focused on strengthening psychosocial skills, social support, and resilience. Common intervention components included community participation, cultural adaptation, and facilitator training. Several strategies were linked to broader public health frameworks, such as primary health care, intersectoral action, and social determinants of health. Reported outcomes were generally positive, although evaluation methods and indicators varied widely. Conclusions: Community-based mental health promotion interventions represent a valuable complement to healthcare systems, particularly in resource-constrained settings. Strengthening their integration into public policies and health system planning may improve sustainability, equity, and population impact. This review highlights key gaps in implementation and evaluation and provides evidence to inform decision-making in community health, prevention, and mental health policy development. Full article

What does it mean to bring climate adaptation and sustainability “on the ground” into a Thuringian small town that is both urban and rural? From 2021 to 2024, we conducted a cooperative research project with the municipality to investigate this. For three years, the research partners explored ways to integrate the “big” topics of climate adaptation, sustainability, public services, and demographic change into the everyday urban development processes of a small town in rural Thuringia, an area experiencing long-term population decline. The result of the project is three volumes in the ISDN series that provide initial answers, which are often derived from the combination of research and teaching. One volume focuses on energy, housing, and mobility, presenting stakeholders, projects, and research results that can be used to address these issues locally in rural-urban municipalities more broadly. Another collects findings on socio-infrastructural planning, offering a dedicated perspective on gender and youth “in the countryside”. Ultimately, all socio-infrastructural planning activities aim to support an “Urban Social Cultural Care”. This article aims to contextualize transfer-oriented research within theoretical debates on sustainability transitions, paying special attention to the opportunities available to municipalities with limited administrative resources to enhance their own scope of action. Full article

The transition to electric vehicles (EVs) in urban logistics presents complex operational challenges, driven primarily by limited battery capacities, charging station scheduling, and dynamic traffic congestion. This paper introduces a framework to solve the Capacitated Multi-Depot Electric Vehicle Routing Problem (MD-EVRP). We propose a novel Multi-Depot Rotational Sweep Cluster K-means (MD-RSCK) algorithm to partition large-scale spatial data while strictly adhering to vehicle capacity constraints. To optimize intra-cluster routing, we develop an Ant Colony Optimization (ACO) engine augmented with a Time-Dependent Congestion Model. Furthermore, the framework integrates an Energy-Aware Route Refiner (EARR). This architecture utilizes recursive backtracking to ensure battery-feasible routes, adapting to both symmetric Euclidean approximations and real-world asymmetric traffic networks. The framework is evaluated against standard IEEE EVRP benchmarks and a multi-depot urban case study based on the road network of Shanghai, China. Experimental results demonstrate that this integrated architecture achieves competitive distance and cost metrics within a 2.44% optimality gap of state-of-the-art algorithms while ensuring strictly feasible battery states and preventing cyclic entrapment, providing a scalable operational tool for modern sustainable logistics. Full article