Search Results (43)

The Urban Agglomeration in the Middle Reaches of the Yangtze River (UAMRYR), serving as a pivotal hub for coordinated economic and ecological development in central China, is characterized by marked ecological fragility and climate sensitivity. Investigating the land use dynamics and ecological benefit changes within this region holds critical strategic significance for balancing regional development with the construction of ecological security barriers. This study systematically analyzed the spatiotemporal variations in land use/land cover (LULC) across the UAMRYR, using multi-source remote sensing data, climatic factors, land conditions, and anthropogenic influences. By integrating the four-quadrant model and the coupling degree model, we developed a remote sensing ecological index (RSEI)–ecological service index (ESI) coupling evaluation framework to assess the spatiotemporal evolution patterns of changes in ecological benefits in the region. Furthermore, we employed Geodetector analysis to identify the key influencing factors driving the RSEI–ESI coupling relationship and their interactive mechanisms. The research findings are as follows: (1) The ecological regional pattern has changed. The area of Quadrant I (RSEI > 0.5 and ESI > 0.5) decreased by 13,800 km², whereas Quadrants II (RSEI < 0.5 and ESI > 0.5) and IV (RSEI > 0.5 and ESI < 0.5) increased by 14,900 km² and 3500 km², respectively. Quadrant III (RSEI < 0.5 and ESI < 0.5) remained relatively stable. This indicates that the imbalance in ecological functional spaces has intensified, affecting key ecological processes. (2) The quantitative analysis of the spatiotemporal evolution characteristics of the RSEI and ESI revealed contrasting trends: the RSEI decreased by 0.006, whereas the ESI showed a slight increase of 0.001. (3) The ranking of the driving factors indicated that the Normalized Difference Vegetation Index (NDVI) and the mean annual rainfall (MAP) were the primary factors driving ecological evolution, while the influence of economic driving factors was relatively weak. This study establishes a three-pillar framework (quadrant-based diagnosis, Geodetector-driven analysis, and RSEI–ESI coupled interventions) to guide precision-based ecological restoration and spatial governance. Full article

The increasing frequency and intensity of hydrological events driven by climate change, particularly floods, present significant challenges for the design, construction, and maintenance of bridges and culverts. Additionally, the inadequate capacity of existing structures has resulted in substantial financial burdens on governments due to flood-related damages and the costs of their rehabilitation and replacement. A further concern is the oversight of existing hydraulic design standards, which primarily emphasize structural capacity and flood height, often overlooking broader social and environmental implications as two main pillars of sustainability. This oversight becomes even more critical under changing climatic conditions. This paper proposes a flood risk-based framework for the sustainable design, construction, and modification of bridge and culvert infrastructure in response to climate change. The framework integrates flood risk modeling with environmental and socio-economic considerations to systematically identify and assess vulnerabilities in existing infrastructure. A multi-criteria analysis (MCA) approach is employed to rapidly evaluate and integrate climate change, social, and environmental factors, such as population density, industrial activities, and the ecological impacts of floods following construction, alongside conventional hydrologic and hydraulic design criteria. The study utilizes hydrologic and hydraulic analyses, incorporating transportation networks (including roads, railways, and traffic) with socio-economic data through a GIS-based flood risk classification. Two case studies are presented: the first prioritizes the replacement of existing main bridges and culverts in the Ankara River Basin using the proposed MCA framework, while the second focuses on substructure sizing for a planned high-speed railway section in Mersin–Adana–Osmaniye–Gaziantep, Türkiye, accounting for climate change and upstream reservoirs. The findings highlight the critical importance of adopting a comprehensive and sustainable approach that integrates advanced risk assessment with resilient design strategies to ensure the long-term performance of bridge and culvert infrastructure under climate change. Full article

The construction industry plays a key role in economic development but continues to face challenges in promoting employee well-being, particularly mental health and social sustainability. While existing decision-making tools emphasize environmental and economic factors, the social dimension remains largely overlooked, creating a significant gap in both research and practice. To address this, the study develops a decision support tool (DST) to help construction organizations prioritize strategic investments that enhance employee social sustainability. The tool is based on a hybrid multi-criteria decision-making framework, combining the Analytical Hierarchy Process (AHP) with Fuzzy MOORA to integrate both quantitative and qualitative assessments. A literature review, along with findings from a previous empirical study, identified 27 validated criteria, grouped into seven core sustainability alternatives. Additionally, five decision criteria (cost, risk, compatibility, return on investment, and difficulty) were refined through expert interviews. The DST was implemented as a modular Excel-based tool allowing users to input data, conduct pairwise comparisons, evaluate alternatives using linguistic scales, and generate a final ranking through defuzzification. A case study in a private construction company showed Training and Development and Work Environment as top priorities. An online expert focus group confirmed the DST’s clarity, usability, and strategic relevance. By addressing the often-neglected social pillar of sustainability, this tool offers a practical and transparent framework to support decision-making, ultimately enhancing employee well-being and organizational performance in the construction sector. Full article

As a pillar industry of China’s economy, the real estate sector has been challenged by the increasing prevalence of housing vacancies, which negatively impacts market stability. Traditional vacancy rate estimation methods, relying on labor-intensive surveys and lacking official statistical support, are limited in accuracy and scalability. To address these challenges, this study proposes a novel framework for assessing residential community-level housing vacancy rates through the integration of multi-source data. Its core is based on night-time lighting data, supplemented by other multi-source big data, for housing vacancy rate (HVR) estimation and practical validation. In the case study of Longquanyi District in Chengdu City, the main conclusions are as follows: (1) with low data resolution, the model estimates a root mean square error (RMSE) of 0.14, which is highly accurate; (2) the average housing vacancy rate (HVR) of houses in Longquanyi District’s residential community is 46%; (3) the HVR rises progressively with the increase in the distance from the city center; (4) the correlation between the HVR of Longquanyi District and the house prices of the area is not obvious; (5) the correlation between the HVR of Longquanyi District and the time of completion of the communities in the region is not obvious, but the newly built communities have extremely high HVR. Compared to the existing literature, this study innovatively leverages multi-source big data to provide a scalable and accurate solution for HVR estimation. The framework enhances understanding of urban real estate dynamics and supports sustainable city development. Full article

Eco-design is an innovative design methodology that focuses on minimizing the environmental footprint of industries, including aviation, right from the conceptual and development stages. However, rising industrial demand calls for a more comprehensive strategy wherein, beyond environmental considerations, competitiveness becomes a critical factor, supported by additional pillars of sustainability such as economic viability, circularity, and social impact. By incorporating sustainability as a primary design driver at the initial design stages, this study suggests a shift from eco-driven to sustainability-driven design approaches for aircraft components. This expanded strategy considers performance and safety goals, environmental impact, costs, social factors, and circular economy considerations. To provide the most sustainable design that balances all objectives, these aspects are rigorously quantified and optimized during the design process. To efficiently prioritize different variables, methods such as multi-criteria decision-making (MCDM) are employed, and a sustainability index is developed in this framework to assess the overall sustainability of each design alternative. The most sustainable design configurations are then identified through an optimization process. A typical aircraft component, namely a hat-stiffened panel, is selected to demonstrate the proposed approach. The study highlights how effectively sustainability considerations can be integrated from the early stages of the design process by exploring diverse material combinations and geometric configurations. The findings indicate that the type of fuel used, and the importance given to the sustainability pillars—which are ultimately determined by the particular requirements and goals of the user—have a significant impact on the sustainability outcome. When equal prioritization is given across the diverse dimensions of sustainability, the most sustainable option appears to be the full thermoplastic component when kerosene is used. Conversely, when hydrogen is considered, the full aluminum component emerges as the most sustainable choice. This trend also holds when environmental impact is prioritized over the other aspects of sustainability. However, when costs are prioritized, the full thermoplastic component is the most sustainable option, whether hydrogen or kerosene is used as the fuel in the use phase. This innovative approach enhances the overall sustainability of aircraft components, emphasizing the importance and benefits of incorporating a broader range of sustainability factors at the conceptual and initial design phases. Full article

With the development of high-density integrated chips, low-k dielectric materials are used in the back end of line (BEOL) to reduce signal delay. However, due to the application of fine-pitch packages with high-hardness copper pillars, BEOL is susceptible to chip package interaction (CPI), which leads to reliability issues such as the delamination of interlayer dielectric (ILD) layers. In order to improve package reliability, the effect of CPI at multi-scale needs to be explored in terms of package integration. In this paper, the stress of BEOL in the flip-chip chip-scale packaging (FCCSP) model during thermal cycling is investigated by using the finite-element-based sub-model approach. A three-dimensional (3D) multi-level finite element model is established based on the FCCSP. The wiring layers were treated by the equivalent homogenization method to ensure high prediction accuracy. The stress distribution of the BEOL around the critical bump was analyzed. The cracking risk of the interface layer of the BEOL was assessed by pre-cracking at a dangerous location. In addition, the effects of the epoxy molding compound (EMC) thickness, polyimide (PI) opening, and coefficient of thermal expansion (CTE) of the underfill on cracking were investigated. The simulation results show that the first principal stress of BEOL is higher at high-temperature moments than at low-temperature moments, and mainly concentrated near the PI opening. Compared with the oxide layer, the low-k layer has a higher risk of cracking. A smaller EMC thickness, lower CTE of the underfill, and larger PI opening help to reduce the risk of cracking in the BEOL. Full article

The energy sector is crucial for the country’s stable and lasting socioeconomic development and for implementing environmentally friendly technologies. The sustainable development of the energy sector takes place in three pillars: economic, social, and environmental. It means improving economic results while increasing the share of alternative energy sources. The paper aims to assess the impact of socioeconomic cohesion on the sustainable development of the energy sector in France, Germany, and Poland. We created indicators of sustainable development and socioeconomic cohesion. We used correlation analysis to examine the relationships. Additionally, we created a single- and multi-equation model, which we reset using the ordinary least squares method and Seemingly Unrealized Regression. The results of the linear correlation coefficients show a very strong relationship between socio-economic cohesion and the sustainable development of the energy sector in Poland (Pearson’s R 0.94), a weaker correlation in Germany (0.811), and the weakest in France (0.59). The results suggest that the relationship is strongest in the country with the lowest economic development and the smallest share of renewable energy, a significant positive impact on the sustainable development of the energy sector. The strength of this impact is varied in the countries studied, indicating a different level of advancement and development in the countries studied. Full article

The incorporation of automatic segmentation methodologies into dental X-ray images refined the paradigms of clinical diagnostics and therapeutic planning by facilitating meticulous, pixel-level articulation of both dental structures and proximate tissues. This underpins the pillars of early pathological detection and meticulous disease progression monitoring. Nonetheless, conventional segmentation frameworks often encounter significant setbacks attributable to the intrinsic limitations of X-ray imaging, including compromised image fidelity, obscured delineation of structural boundaries, and the intricate anatomical structures of dental constituents such as pulp, enamel, and dentin. To surmount these impediments, we propose the Deformable Convolution and Mamba Integration Network, an innovative 2D dental X-ray image segmentation architecture, which amalgamates a Coalescent Structural Deformable Encoder, a Cognitively-Optimized Semantic Enhance Module, and a Hierarchical Convergence Decoder. Collectively, these components bolster the management of multi-scale global features, fortify the stability of feature representation, and refine the amalgamation of feature vectors. A comparative assessment against 14 baselines underscores its efficacy, registering a 0.95% enhancement in the Dice Coefficient and a diminution of the 95th percentile Hausdorff Distance to 7.494. Full article

Urban parks are central to advancing urban sustainability and improving overall quality of life by providing green spaces that promote physical and mental well-being, mitigate environmental issues, and foster community cohesion. However, there is a lack of methodologies that measure these benefits and provide a sustainability rating. In this study, we propose a valuable tool for measuring the sustainability level of urban parks: low (0–50%), medium (51–79%), and high (80–100%). It employs effective and affordable measures for the daily management of urban parks. It is rooted in the three pillars of sustainability: environmental, social, and economic. We have defined 19 indicators (e.g., renewable energy and energy efficiency, environmental impact on society) and 50 criteria (e.g., clean energy generation, water workshops). A multi-criteria analysis facilitated the selection process for these indicators and criteria. This methodology is developed by characterizing and systematically documenting the park’s day-to-day operations. We present a case study of Cárcamos Park in Guanajuato, Mexico. Through this real-life scenario, we demonstrate our methodology’s high applicability and effectiveness. The sustainability assessment of Cárcamos Park reveals a level of 57%, with the environmental pillar at 47.7%, the economic pillar at 49%, and the social pillar at 75%. The adaptability of our methodology during the design phase of new parks plays a crucial role in shaping sustainable park layouts. Park managers can apply our procedure to any park, evaluate their sustainability status, and detect areas of opportunity. Full article

To achieve national and global air quality and climate change objectives, the agricultural sector increasingly requires dependable decision support tools for gaseous emissions at the farm level. We evaluated thirteen greenhouse gas (GHG)-based decision support systems (DSS), considering criteria such as not only the accessibility, user-friendliness, stakeholder involvement, sustainability methodology, and modeling aspects, but also the input parameters and outputs provided, all crucial for decision making. While most DSSs provide information for facilitating their use, only four are suitable for inexperienced users, and stakeholder participation in DSS development is infrequent. The dominant methodology for farm-level GHG estimation is IPCC 2006, with quantitative models primarily used for indicators’ assessment. Scenario and contribution analyses are the prevailing decision support approaches. Soil, crop, and fertilizer types are the most implemented non-livestock-related inputs, while climate- and feed-related costs are the least required. All DSSs assess farm-level mitigation measures, but less than half offer sustainability consultation. These tools promote environmental sustainability by evaluating mitigation strategies, disseminating farm sustainability information, and guiding sustainable farm management. Yet, challenges such as disparate estimation methods, result variations, comparison difficulties, usability concerns, steep learning curves, the lack of automation, the necessity for multiple tools, the limited integration of the results, and changing regulations hinder their wider adoption. Full article

Cities are the engine of human development, and increasing urban sustainability is crucial to ensure human prosperity. The development of smart cities generally increases the sustainability of the cities. However, technical and environmental aspects are generally developed in smart cities neglecting socio-economic dimensions. The urban resilience concept includes the complex interactions of environmental, economic, and societal pillars. In this context, the emerging maker movement proposes an economic paradigm shift, with the interaction of humans and technology at the center of urban evolution. This paper proposes a multi-criteria methodology to define and assess the main characteristics of the resilient approach of the projects involving maker practices applied to urban development. The proposed methodology is based on the application of computer-assisted qualitative text analysis and a subsequent classification according to 12 indicators (community and urban efficiency, co-creation and professional, making sense and problem-solving, network and site-specific, implementation and optimization, sustainability-oriented and market-oriented) that define different dimensions of a bottom-up project’s resilient approach in three main key principles: inclusiveness, complexity, and durability. The method has been tested in 94 EU-funded projects. This analysis reveals the evolution and orientation of EU-funded projects from economic, technical, and social perspectives. Specifically, the patterns of remediation of non-participatory practices, the weak presence of open innovation initiatives, and the development of activities focusing on co-creation as a participatory tool. The applied methodology could be subsequently implemented at different scales and integrated with LCA in order to evaluate the sustainability of bottom-up projects toward urban development. Full article

The subject of this study is Vacuum Insulated Glass (VIG) panels, which consist of two glass panes with an evacuated space and evenly distributed micro-support pillars between them. The deflection of panes towards the centre of the structure caused by atmospheric pressure is a mechanical problem that occurs in this type of structure. The aim of this study was to extend previous research on the optimal arrangement of support pillars in terms of eigenfrequencies and dynamics to include aesthetic aspects. Using Abaqus/CAE v2017 software, a large number of numerical models were created and subjected to a comprehensive multi-criteria analysis. Fractal analysis was employed to automatically assess the aesthetics of the proposed solutions. The study presents theoretical solutions that could be implemented in industrial production. The presented study shows that it is possible to effectively extend the criteria for optimizing the arrangement of pillars with new design criteria. Most studies focus on pillar placement, amount, or shape in terms of panes thermal or mechanical properties. Due to the increasing number of VIG panels applications in places exposed to external vibrations, other design criteria for VIG panels are also required and are provided by the following study. Full article

Cranioplasty or cranial reconstruction is always a challenging procedure even for experienced surgeons. In this study, two different design techniques for customized cranial prostheses are assessed for cranial reconstruction. Mirror reconstruction is one of the commonly used reconstruction techniques that fails when cranial defects cross the midline of symmetry. Hence, there is a need for a design technique for the reconstruction of cranial defects irrespective of their location on the symmetrical plane. The anatomical reconstruction technique demonstrates its applicability for a wide spectrum of complex skull defects irrespective of the defective position in the anatomical structure. The paper outlines a methodological procedure involving a multi-disciplinary approach involving physicians and engineers in the design and reconstruction of customized cranial implants for asymmetrical skull defects. The proposed methodology is based on five foundation pillars including the multi-disciplinary approach, implant design process, additive-manufactured implant, implant fitting analysis, and cost and time analysis for the customized implant. The patient’s computed tomography scan data are utilized to model a customized cranial implant, which is then fabricated using electron beam melting technology. The dimensional validation of the designed and fabricated titanium implant based on the anatomical approach results in a precision of 0.6345 mm, thus indicating a better fit than the standard mirroring method. The results of fitting accuracy also reveal that the manufactured implant’s average deviation is very close to the planned reconstruction area with an error less than 1 mm, suggesting that the customized titanium implant fits the skull model quite precisely. The cost and time analysis reports that the cost for producing a customized cranial implant using electron beam melting technology is around USD 217.5 and the time taken to build is approximately 14 h and 27 min, which is low when compared to other studies. The cost and time analysis also demonstrates that the proposed design would be less burdensome to patients when compared to standard practice. Therefore, the new anatomical design process can be used effectively and efficiently to treat a number of diverse cranial abnormalities with the enhanced cranial implant design. Full article

Biofuel production from biomass resources can significantly contribute to greenhouse gas mitigation and clean energy generation. This paper aims to develop a new decision analysis approach under an intuitionistic fuzzy set (IFS) setting to rank suitable biomass resources for biofuel production. For this purpose, an intuitionistic fuzzy Symmetry Point of Criterion (IF-SPC) tool was introduced to obtain the objective weight of the indicators and an IF-rank sum (IF-RS) was applied to find the subjective weight of the indicators under an IFS setting. Then, an integrated multi-attributive ideal real comparative assessment (MAIRCA) approach was introduced using aggregation operators and a proposed weight-determining tool to rank suitable biomass resources for biofuel production. Further, the usability of the proposed model was tested with a case study of the selection of biomass resources for biofuel production under the context of IFS. From the obtained outcomes, we found that the most important indicators for selecting suitable biomass resources for biofuel production are cost of biomass supply (EC-3), maturity (T-3), local acceptability (SP-1), cost of the biomass conversion process (EC-2), and reduction of GHG emissions (EN-1), respectively. From this perspective, globally existing sustainable biomass resources for biofuel production were recognized and then ranked over thirteen diverse indicators including environmental, economic, technical, and social-political pillars of sustainability. It was found that municipal solid waste and sewage, forest and wood farming waste, and livestock and poultry waste achieve higher overall utility scores over the other biomass resources for biofuel production in India. Furthermore, comparison with extant models and sensitivity analysis are discussed to present the usefulness and stability of the presented model. Full article

Improvements in and the assessment of land use efficiency are crucial pillars for achieving the Sustainable Development Goals (SDGs). This study reviews 208 representative papers, oral reports, and project reports to provide a systematic and comprehensive understanding of the current status and future trends of research on land use efficiency assessment. The findings reveal that (1) the number of papers on land use efficiency assessment is rapidly increasing, with research primarily focused on environmental science and ecology (n = 157, 75.48%). (2) Quantitative models are gaining popularity for land use efficiency assessment, with more than 46.63% of the studies adopting the data envelopment analysis (DEA) model. (3) The definition and analysis perspectives of land use efficiency are diverse, but research on relative land use efficiency and comprehensive analysis perspectives accounts for a significant proportion. (4) Constructing a large and complex model that incorporates geospatial effects, big data, and computer technology is a hot topic for future research methods. On the other hand, conducting land use efficiency research on a global scale is more conducive to achieving the SDGs. (5) The core to improving land use efficiency lies in the joint implementation of multi-pronged measures. Full article