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Found 6674 publications
The impact of extreme climate on urban resilience in China and the associated moderating mechanisms
Publication Name: Environmental Science and Policy
Publication Date: 2026-09-01
Volume: 183
Issue: Unknown
Page Range: Unknown
Description:
Global climate change continues to intensify, with frequent extreme climate events and abnormal climate patterns profoundly altering humanity's living environment. As a rapidly urbanising developing nation, China's practices in building resilience against extreme climate hold significant global reference value. This research constructs an Urban Comprehensive Resilience Index and an Extreme Climate Index based on Chinese urban panel data, systematically examining the impact of extreme climate on urban resilience. Findings reveal that both extreme climate and urban resilience exhibit a spatially distinct "eastern high, western low" gradient pattern, with fluctuating temporal trends. Among the four resilience dimensions, social and economic resilience levels have strengthened, while engineering resilience has weakened, and ecological resilience remains largely stable. Extreme climate events exert a significant inhibitory effect on urban resilience, a conclusion upheld after rigorous endogeneity and robustness tests employing instrumental variables, double machine learning, and spatial econometric analysis. Further investigation indicates this suppression primarily manifests as extreme heat and drought weakening urban economic and social resilience. Through an analysis of moderating mechanisms, this paper further reveals that fiscal flexibility, industrial diversity, and technological innovation can effectively mitigate the negative impacts of extreme climate on urban resilience. Furthermore, this inhibitory effect exhibits marked heterogeneity across different levels of urban development, geographical locations and policy interventions; whilst it remained significant throughout the period 2006–2021, the intensity of its effect has generally shown a gradual decline. This research provides empirical evidence on the link between extreme climate and urban resilience, and offers scientific guidance for differentiated enhancement policies.
Open Access: Yes
Sustainable city tourism—A systematic analysis of Budapest and Mumbai
Publication Name: Journal of Infrastructure Policy and Development
Publication Date: 2024-01-01
Volume: 8
Issue: 9
Page Range: Unknown
Description:
International Tourist arrivals, guest nights and their contribution to GDP are key indicators reflecting a country’s actual perception. A growing percentage of tourists prioritize environmental awareness across tourism products and services each year. Dest inations aiming to meet the expectations of eco conscious travellers must center sustainability in their branding strategies. This approach aligns with UNWTO (World Tourism Organization of United Nations) Agenda 2030 of sustainable tourism development. This paper examines various dimensions of sustainability in tourism, focusing on Mumbai and Budapest. Using specific sustainability indicators, it employs sustainability city index to compare international tourism in these cities, which face distinct environmental and infrastructural challenges. By using specific sustainability indicators such as: (1) Carbon Emissions: Measurement of the total greenhouse gases produced by the city. (2) Proportion of Green Public Spaces: Evaluation of the percentage of urban areas dedicated to parks and natural spaces. (3) State of Infrastructure: Assessment of the quality and sustainability of urban infrastructure, including transportation systems. (4) Water Usage: Analysis of the amount of water consumed by the city and its conservation practices. (5) Waste Management: Review of the city’s effectiveness in managing and recycling waste. (6) Air Pollution: Monitoring of the levels of pollutants in the air to assess environmental health. This research provides a comprehensive view of how cities can attract environmentally conscious tourists. The findings offer guidance for policy makers and tourism professionals to align strategies with sustainable development goals. This detailed assessment highlights each city’s commitment to sustainability and delivers actionable insights for improving tourism strategies in accordance with global standards. While valuable for tourism professionals, it is important to note that this research covers only six SCI factors, with incomplete data for studied countries. The practical and social implications indicate areas needing improvement to enhance tourist appeal, beneficial for industry professionals and educational purposes. This comparative analysis aids in promoting sustainable tourism and can guide governments in achieving sustainability goals with raising awareness of environmental quality and conscious living.
Open Access: Yes
Equivalence and difference of the dual device under test setup and the single device under test setup of RFC 8219
Publication Name: International Journal of Communication Systems
Publication Date: 2025-02-01
Volume: 38
Issue: 3
Page Range: Unknown
Description:
RFC 8219 has defined a comprehensive benchmarking methodology for the IPv6 transition technologies. It recommends two kinds of measurement setups: The dual device under test (DUT) setup facilitates the benchmarking of the customer edge (CE) and provider edge (PE) devices together using a legacy RFC 2544 or RFC 5180 Network Performance Tester, whereas the single DUT setup requires a separate technology-specific tester for the benchmarking of each device. As such, special-purpose testers do not exist for the vast majority of the IPv6 transition technologies; the only viable solution can be the usage of the dual DUT setup. In this paper, we investigate if the two kinds of measurement setups provide the same or different results; moreover, we examine how the single DUT measurement results can be estimated from the dual DUT measurement results. To that end, we make theoretical considerations and also perform IPv4 packet forwarding and stateless IP/ICMP translation (SIIT) measurements using both measurement setups and analyze the results of the throughput and latency measurements. It was found that the throughput results of the dual DUT setup could approximate well those of the single DUT setup and their differences followed the predictions of our theoretical considerations. However, the latency results did not always follow the theoretical expectations.
Open Access: Yes
DOI: 10.1002/dac.5982
Structured Representation of Industrial Robot Data for Augmented Reality Applications: A Unified Approach
Publication Name: Isse 2025 11th IEEE International Symposium on Systems Engineering Symposium Proceedings
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Industrial robots generate diverse types of data, such as position, orientation, coordinate system definitions, tooling information, and safety zone configurations. Handling these heterogeneous datasets uniformly is challenging, especially when integrating data from multiple robot manufacturers within augmented reality (AR) environments. This research introduces a unified data structure that encapsulates robot-specific data along with supplementary metadata, including source identifiers, unique data identifiers, data types, original orientation formats, status data, and timestamps. The developed data model, validated by JSON Schema, ensures consistent interpretation and ease of integration into AR visualization environments.
Open Access: Yes
Evaluation of recycled polyethylene terephthalate in asphalt concrete: Laboratory characterization and finite element modelling
Publication Name: Results in Engineering
Publication Date: 2026-09-01
Volume: 31
Issue: Unknown
Page Range: Unknown
Description:
The increasing generation of plastic waste and the growing demand for sustainable pavement materials have encouraged the incorporation of recycled polymers into asphalt mixtures. This study evaluates the engineering performance, microstructural characteristics, numerical response, and preliminary environmental implications of recycled polyethylene terephthalate (RPET)-modified asphalt concrete. RPET obtained from post-consumer plastic bottles was incorporated into asphalt mixtures through the dry process at dosages of 0–9% by weight of binder. Marshall stability, indirect tensile strength (ITS), repeated load dynamic creep (RLDC), scanning electron microscopy (SEM), and finite element modelling (FEM) were employed to assess the influence of RPET content on mixture behavior. Experimental results showed that increasing RPET content improved stiffness-related properties and rutting resistance. Marshall stability increased from 5.5 kN for the control mixture to 14.3 kN at 9% RPET, while ITS increased from 0.72 MPa to 1.02 MPa. RLDC results indicated a reduction in accumulated permanent strain from 3.20% to 1.85%, demonstrating enhanced resistance to deformation under repeated loading. SEM observations revealed comparatively uniform RPET dispersion at moderate dosages (3–5%), whereas higher contents showed localized particle agglomeration. FEM simulations demonstrated reduced surface deflection and improved stress distribution with increasing RPET-related stiffness. Preliminary life cycle assessment indicated modest embodied carbon reduction and potential cost savings. The findings suggest that RPET incorporation can enhance the mechanical and deformation-resistant characteristics of asphalt mixtures while contributing to plastic waste valorization and sustainability objectives. However, the results should be interpreted as comparative laboratory and numerical indicators rather than direct predictors of long-term field performance.
Open Access: Yes
Rethinking sustainable growth: technological and supply chain drivers of the U.S. production-based ecological footprint
Publication Name: Resources Conservation and Recycling Advances
Publication Date: 2026-09-01
Volume: 31
Issue: Unknown
Page Range: Unknown
Description:
The United States (U.S.) has one of the highest production-based ecological footprints (EFP) in the world. Consequently, reducing EFP is essential for ensuring ecological balance, protecting the environment, and reducing ecological degradation. However, the comparative analysis on the long-run associations of AI innovation (AIN), high-tech trade capability (HTTC), supply chain efficiency (SCE), information and communication technology investment growth (ICTIG), and GDP growth (GDPG) with EFP regarding the U.S. remains poorly understood. Using the autoregressive distributed lag (ARDL) method, this study shows a comparative analysis of the EFP’s determinants relying on the U.S. national level data from 1990 to 2023. Based on the ARDL findings, while AIN, SCE, and HTTC show statistically significant association with EFP in the long run, ICTIG and GDPG do not exhibit significant empirical association. Among three significant associations, AIN and SCE are associated with reductions in ecological footprint in the long run, indicating that the country has secured technology-driven ecological benefits and operational efficiency enhancement within the production dynamics by emphasizing AI innovation and efficient inventory management. In contrast, HTTC’s positive association represents significant ecological pressure with the high tech-industries technology advancement, driven by scale and rebound effects. All the results remained stable in FMOLS, DOLS, and CCR robustness tests. Besides, Granger causality indicates mixed predictive patterns of these relationships. The comparative analysis among these determinants' long-run associations with EFP significantly contributes to the single country level production-based ecological footprint literature and depicts several valuable empirical insights for policy actions by the federal government.
Open Access: Yes
Review of multihazards research with the basis of soil erosion
Publication Name: Advanced Tools for Studying Soil Erosion Processes Erosion Modelling Soil Redistribution Rates Advanced Analysis and Artificial Intelligence
Publication Date: 2024-01-01
Volume: Unknown
Issue: Unknown
Page Range: 295-306
Description:
Soil erosion is a primary geomorphic process that may result in hazards and significant socioeconomic losses. These processes occur mainly through the surface and subsurface flows. We conducted a systematic literature review on the quantitative attribution analysis of soil erosion, presenting state-of-the-art erosion processes and demonstrating the relative importance of soil erosion as a natural hazard responsible for land degradation and desertification. This explains why a multidisciplinary approach is needed to understand how erosion occurs and what factors are involved. This justifies the multihazard analysis and the need to model the erosion processes. Knowledge of the quantitative elements of soil erosion measurement combined with the consideration of multiple risk assessments can help develop conceptual models of slope hydrology and soil erosion that can help decision-makers determine an appropriate early warning system design policy. Filling these gaps will guide us to increase our knowledge of surface and subsurface erosion, thereby helping us to better explore the changing landscape for improvement and develop strategies and effective soil erosion control techniques. However, more research is required to better explore the morphology and connectivity of soil erosion, their subsurface watershed, and behavior, as well as several challenges, opportunities, and strategies facing the analysis of soil erosion.
Open Access: Yes
Assessing climate uncertainty in green bonds: Evidence from machine learning and GARCH-MIDAS models
Publication Name: Environmental Impact Assessment Review
Publication Date: 2026-09-01
Volume: 121
Issue: Unknown
Page Range: Unknown
Description:
This paper employs a GARCH-MIDAS framework integrated with machine learning to investigate the impact of climate-related uncertainties on the volatility of the China's green bond market (GBM). By combining high-frequency financial data with multi-source, low-frequency climate uncertainty indicators, we examined how macro-financial conditions and climate risks jointly affect the dynamic changes of the GBM in China. Machine learning methods were used to identify and rank the key drivers of volatility. The research results indicate that traditional macro-financial variables remain the main determinants of the volatility in the green bond market, among which the impact of government bond yields is the most significant. Climate uncertainty information also has a significant impact on the volatility of green bonds. Moreover, incorporating climate uncertainty into the GARCH-MIDAS model significantly enhances its explanatory power, highlighting the importance of considering mixed-frequency risk factors in understanding China's green bond market dynamics. These findings underscore the crucial role of climate uncertainty in green bond pricing and indicate that combining machine learning with mixed-frequency volatility modeling can provide a more comprehensive framework for understanding the dynamics of the green bond market.
Open Access: Yes
A MILP approach combined with clustering to solve a special petrol station replenishment problem
Publication Name: Central European Journal of Operations Research
Publication Date: 2024-03-01
Volume: 32
Issue: 1
Page Range: 95-107
Description:
Vehicle routing problem is a well-known optimization problem in the logistics area. A special case of the vehicle routing problem is the station replenishment problem in which different types of fuel types have to be transported from the depots to the customers. In this paper we study the replenishment problem of a European petrol company. The problem contains several additional constraints such as time windows, different sized compartment vehicles, and restrictions on the vehicles that can serve a customer. We introduce a mixed integer linear programming model of the problem. To reduce the size complexity of the MILP model the customers are clustered and, based on the clusters, additional constraints are added to the MILP model. The resulting MILP model is tested on real problems of the company. The results show that combining the MILP model with clustering improves the effectiveness of the model.
Open Access: Yes
