Search Results (4,679)

Using Shanghai as a case study, this paper estimates multi-sector urban carbon emissions by integrating multi-source statistical data from 2000 to 2023 with IPCC guidelines. Via rolling-window time-series validation, XGBoost is the most reliable model. To better understand the underlying drivers, explainable machine-learning approaches, including SHAP and the Friedman H-statistic, are applied to examine the nonlinear effects and interactions of population scale, industrial energy efficiency, investment structure, and infrastructure. The results suggest that Shanghai’s emission pattern has gradually shifted from a scale-driven process toward one dominated by structural change and efficiency improvement. Building on an incremental framework, four scenarios, Business-as-Usual, Green Transition, High Investment, and Population Plateau, are designed to simulate emission trajectories from 2024 to 2060. The simulations reveal a two-stage pattern, with a period of rapid growth followed by high-level stabilisation and a weakening path-dependence effect. Population agglomeration, economic growth, and urbanisation remain the main contributors to emission increases, while industrial upgrading and efficiency gains provide sustained mitigation over time. Scenario comparisons further indicate that only the Green Transition pathway supports early peaking, a steady decline, and long-term low-level stabilisation. Overall, this study offers a data-efficient framework for analysing urban carbon-emission dynamics and informing medium- to long-term mitigation strategies in megacities. Full article

The current study explores the social experiences of adolescent and transition-age youths with intellectual disabilities (IDs) and the support mechanisms available to these groups in Saudi Arabia. This study adopts a qualitative methodology with a semi-structured interview constituting the data collection method involving 13 parents with children aged between 11 and 19 years, a critical adolescent period and transition to early adulthood. The results suggest that family, caregivers, community, friendships, and healthcare providers play important roles that impact the quality of life for these groups. The main challenges identified include health-related issues, employment challenges, educational barriers, insufficient services, inadequate community participation, and limited social relationships, with special emphasis on obstacles linked to transition during the 18 to 19-year period when youths must navigate transfers from pediatric to adult services and changes associated with legal rights. This study highlights several reasons it is important to increase awareness and education, while also continuing to improve support systems aimed at dealing with both transition challenges and adolescent needs. The results further illustrate that although support from family provides the foundation for care, systemic changes are needed to promote social inclusion and reduce stigma during critical development periods. The current study contributes to the limited research related to IDs in the context of the Middle East, with special reference to Saudi Arabia. Finally, the discussion highlights several insights that are culturally specific for the development of policy and provision of services associated with the transition from adolescence to early adulthood. Full article

Greenhouse gas emissions from the energy sector are the main driver of global warming, which has led to an increase in the average surface temperature of the Earth by more than 1 °C above pre-industrial levels. Responding to the urgent need for energy transition, the countries of the European Union have set themselves the goal of achieving climate neutrality by 2050. The main objective of this article is to comprehensively assess the progress of decarbonization in the 27 European Union countries between 2004 and 2024, using an advanced multi-criteria model. The study used the quantitative Analytical Hierarchy Process (AHP) method to construct a multidimensional decision-making model. Eight energy technologies were evaluated through the prism of 13 criteria grouped into three pillars of sustainable development: economic (including technical), environmental, and social. Based on the weights of each criterion, estimated by a group of experts, a synthetic decarbonization index (DI) was calculated for each technology. In the next stage, a cumulative decarbonization index (CDI) was formulated for each country, reflecting the structure of its energy mix. The analysis revealed a fundamental divergence between conventional and zero-emission technologies. Renewable sources and nuclear energy have the highest positive impact on decarbonization (highest DI): hydropower (27.5), nuclear (20.7), wind (20.3). The lowest, unfavorable values of the index are characteristic of fossil fuels: oil (3.6), coal (3.9), and gas (4.8). The average cumulative decarbonization index (CDI) for the EU-27 rose from 14.0 in 2004 to 26.4 in 2024, demonstrating the effectiveness of the EU’s common policy. The leaders of the transition are countries with diversified, green mixes, such as Luxembourg (CDI = 40.4), Lithuania (CDI = 39.6), Portugal (38.5), Austria (36.9), and Spain (33.6). Despite starting from the lowest level in 2004 (CDI = 5.2), Poland recorded one of the most dynamic increases in 2024 (CDI = 17.7), mainly due to a reduction in the share of coal from 93% to 53.5%. The analysis confirms the effectiveness of the EU’s common climate and energy policy and demonstrates the usefulness of the methodology presented for a comprehensive assessment of the decarbonization process. The results indicate the need to further increase the share of zero-emission energy sources in the energy mix in order to achieve the objectives of the European Green Deal. The varying pace of transformation among Member States requires an individualized approach and support for countries with a historical dependence on fossil fuels. Full article

Background/Objectives: Stemness has been proposed as a unifying driver of invasion, treatment resistance, and relapse in oral squamous cell carcinoma (OSCC). We synthesized two complementary evidence streams to determine whether higher stemness predicts poorer survival in OSCC: (i) computational stemness signatures derived from transcriptomic/epigenetic data and (ii) tissue cancer stem cell (CSC) immunophenotypes by immunohistochemistry (IHC). Methods: Following PRISMA 2020, we searched PubMed/MEDLINE, Embase, Scopus, and SciELO. Adults with histologically confirmed OSCC were eligible. Primary outcome was overall survival (OS); disease-specific survival (DSS) and recurrence-free survival (RFS) were secondary. Two parallel meta-analyses pooled effects within domains; random-effects restricted maximum likelihood (REML) models were applied. Results: Of 785 records, 11 studies met criteria. For computational signatures (k = 6), higher stemness was associated with poorer OS (pooled HR 2.24, 95% CI 1.61–3.12; I² ≈ 49%). Sensitivity excluding the single unadjusted Kaplan–Meier (KM)-derived estimate yielded a similar effect (HR 2.13, 95% CI 1.56–2.89). For CSC-IHC (main analysis, k = 2), CSC-positive profiles predicted worse OS (pooled HR 2.01, 95% CI 1.42–2.84; I² ≈ 0%); results were robust to excluding an internally inconsistent study (single-study HR 2.078). An exploratory sensitivity analysis, including a 1-year HR (different time horizon), increased heterogeneity and was not considered definitive. A functional meta-synthesis converged on epithelial–mesenchymal transition/extracellular matrix remodeling, hypoxia/glycolysis, redox/ferroptosis resistance, and ribosome/rRNA biogenesis, supporting biological plausibility across modalities. Conclusions: Across computational and IHC evidence, stemness consistently portends inferior OS in OSCC, offering a biologically anchored framework for risk stratification and testable therapeutic hypotheses. Full article

As the climate crisis intensifies, the importance of carbon mitigation policies has become increasingly prominent. Rural regions, serving as one of China’s major carbon emission sources, are poised to become key focus regions for emission reduction. However, significant disparities in rural development levels and carbon emissions across China’s regions necessitate tailored energy sustainability and carbon mitigation strategies. Notably, advanced and emerging/developing nations exhibit substantial differences in research priorities and practical pathways, offering multifaceted insights for China’s rural carbon emission research. Adopting a hybrid bibliometric and narrative approach, the study retrieves data from the Web of Science, applies CiteSpace for bibliometric visualization, and synthesizes thematic developments in the international literature through a narrative analysis, with a discussion of the implications for China. The findings reveal distinct trajectories: over the past 25 years, advanced countries have shifted their research focus from air quality improvement to low-carbon mitigation, while emerging and developing countries have transitioned from energy demand toward air quality enhancement, with emerging momentum toward low-carbon strategies. By reviewing 95 relevant articles, this study summarizes the differences between the two in terms of their main lines of research. Building on these differences, this study proposes targeted research priorities for advanced and emerging/developing regions of China. Full article

This paper introduces a novel method for determining the optimal exploitation contour, that is, the point of transition from surface to underground exploitation of dimension stone. Exploitation of dimension stone is primarily carried out using surface mining from the main plateau, but it can also be done by underground or combined methods. The decision regarding the mining method—surface, underground, or combined—is made before mining operations commence. This occurs during preliminary, pre-investment, and investment studies. The choice of mining method primarily depends on natural, technological, environmental, and economic factors, which together form a group referred to as techno-economic factors that influence the decision in varying proportions. Using the novel method for comparing techno-economic factors, the optimal transition point (OTP) from surface to underground exploitation of dimension stone deposits was determined. The position of the OTP from surface to underground mining of dimension stone is not a constant value; it changes over time and space according to techno-economic factors. Full article

The reliability of rubber materials in nuclear sealing applications depends on their resistance to ionizing radiation. To explicitly reveal the differences in radiation damage mechanisms among rubbers with varying molecular structures, this study investigated four typical elastomers—natural rubber (NR), butyl rubber (IIR), chloroprene rubber (CR), and nitrile rubber (NBR)—under ⁶⁰Co γ-irradiation at cumulative doses of 1, 10, and 100 kGy. By coupling macroscopic physical testing (mechanical, permeability) with microstructural characterization (FT-IR, DSC, crosslink density), a correlation between material structure and irradiation behavior was established. The results indicate that main-chain saturation dictates the dominant degradation mechanism: unsaturated rubbers (NR, CR, NBR) are dominated by cross-linking, macroscopically manifested as increased hardness and reduced ductility; conversely, saturated rubber (IIR) is dominated by main-chain scission, leading to a paste-like transition at 100 kGy and a complete loss of mechanical load-bearing and barrier functions. Comparatively, NR exhibited optimal overall stability due to “clean” cross-linking without significant oxidation. The overall radiation resistance ranking within the 0–100 kGy range is NR > CR > NBR > IIR. This study clarifies the “structure-mechanism-property” evolution law, providing a critical theoretical basis for lifetime prediction and rational material selection of rubber components in nuclear environments. Full article

Energy security crises have historically been turning points for energy systems, exposing vulnerabilities, reshaping policy priorities, and boosting technological change. However, whether—and to what extent—such crises accelerate low-carbon transitions remains contested. This paper examines the effects of the 2022 energy crisis on the European Union (EU)’s energy transition, using policy analysis combined with a quantitative assessment of renewable energy trends, forecasts, and targets. We analyse the ambition, implementation, and outcomes of the REPowerEU plan, the main response to the crisis. In an unprecedented move, REPowerEU securitised renewable energy as a means to reduce dependence on Russian energy imports. However, the plan only moderately increased earlier renewable energy targets and did not reverse declining subsidies despite more forceful implementation measures. Its effects have been uneven across technologies. Already accelerating solar may overshoot its targets, onshore wind might only slightly accelerate beyond its current steady growth, and offshore wind remains constrained by economic and institutional uncertainties. Despite increased subsidies for fossil fuels, coal continued declining, oil remained stable, and natural gas dropped. Overall, REPowerEU sustained rather than transformed the EU’s low-carbon transition, illustrating both the potential and limits of accelerating decarbonisation under security crises. Full article

China has abundant deep coalbed methane (CBM) resources; however, high temperature, stress, and reservoir pressure complicate the gas adsorption–desorption–diffusion–seepage processes, severely restricting the development of deep CBM. Through experimental research on adsorption, desorption, diffusion, and seepage behaviors of various coal samples, the control mechanisms of deep coal reservoir properties on CBM production in the Linxing–Shenfu region have been revealed. The results indicate that CBM adsorption and desorption characteristics are jointly controlled by coal rank, ash yield, temperature. and pressure. Among the above conditions, coal rank and pressure exhibit positive effects, while ash yield and temperature show inhibitory effects. Analysis of desorption efficiency based on the Langmuir model further identifies sensitive desorption and rapid desorption stages as key phases for enhancing productivity. Moreover, the gas diffusion mechanism is dynamically evolving, with Knudsen diffusion and Fick diffusion being the main modes during high ground pressure stages, gradually transitioning to the coexistence of Knudsen, transition, and Fick diffusions as pressure decreases. Concurrently, gas–water seepage experiments demonstrate that increasing temperature will reduce the irreducible water saturation and enhance the relative permeability of the gas. Since irreducible water saturation is negatively correlated with relative permeability of gas, the relative permeability of the gas phase, cross-point saturation, and the range of the two-phase co-seepage zone all significantly increases with the increase in temperature. The findings systematically elucidate the regulatory mechanisms of deep coal reservoir properties in the process of “adsorption–desorption–diffusion–seepage,” providing critical theoretical support for optimizing development strategies and enhancing the efficiency of deep CBM development. Full article

Climate change governance has become an essential concern for policymakers, with carbon dioxide (CO₂) emissions representing one of the most pressing challenges to sustainable economic development. In this context, understanding the main drivers of CO₂ emissions is essential for designing effective public policies that support Romania’s transition toward a low-carbon economy. This study investigates the determinants of CO₂ emissions in Romania’s energy sector between 2008 and 2023 using the Logarithmic Mean Divisia Index (LMDI) decomposition method. The analysis considers five key elements: the carbon intensity effect (ΔC), the energy mix effect (ΔM), the energy efficiency effect (ΔL), the economic effect (ΔB), and the population effect (ΔP). The results highlight the need for coherent governance frameworks and targeted policy measures to balance economic expansion with environmental sustainability. The study offers actionable insights for public authorities aiming to strengthen Romania’s climate governance and align national strategies with the objectives of the European Green Deal and climate neutrality by 2050. Full article

This paper presents the reconstruction of signal paths acquired from a power electronics system for energy conversion and management. This reconstruction is performed using the Kalman filter (KF) for monitoring photovoltaic (PV) systems enabled for Internet of Things (IoT) systems. This proposal is motivated by the fact that the global energy transition towards renewable sources makes PV systems a crucial alternative. To guarantee the efficiency and stability of these systems, monitoring critical electrical parameters using IoT technology is essential. However, the measurements acquired are frequently corrupted by stochastic noise, which obscures the true behavior of the system and limits its accurate characterization. Based on this problem, the main objective of this work is explicitly defined as evaluating the effectiveness of the KF as a power-path reconstruction method capable of recovering accurate electrical trajectories from noisy measurements in IoT-monitored photovoltaic networks. To achieve this goal, the system is modeled as a discrete-time stochastic process and the KF is implemented as a real-time estimator of power flow behavior. The experiment was conducted using real-world generation and consumption data from a proprietary two-layer IoT platform: an Edge Layer (acquisition with ESP8266 and PZEM-004T-100A sensors) and a Cloud Layer (visualization on Things-Board). To validate the results, quantitative metrics including the mean squared error (MSE), statistical moments, and probability distributions were computed. The MSE values were found to be nearly zero across all reconstructed power-paths. The statistical moments exhibited near-perfect agreement with those of the actual power signals, approaching 100% correspondence. Additionally, the probability distributions were compared visually and assessed statistically using the Kolmogorov–Smirnov (KS) test. The resulting KS values were very low, confirming the high accuracy of the reconstruction for all power-paths. The proposed research concluded that the KF successfully reconstructed the power trajectories, demonstrating high agreement with the measured steady-state behavior. This study thus confirms that integrating Kalman filtering with IoT monitoring delivers a practically viable and statistically accurate method for power trajectory reconstruction, which is fundamental for enhancing the observability and reliability of photovoltaic energy systems. Full article

Alumina (Al₂O₃) reinforced copper matrix composites are widely used in the electronic industry, rail transit, and other fields due to their excellent electrical conductivity, ductility, and wear resistance. However, due to problems such as non-wetting and thermal expansion differences between alumina and Cu, weak interfacial bonding can easily reduce physical and thermal properties. A uniform silver layer was deposited on Al₂O₃ via chemical plating to enhance interface bonding with copper. Al₂O₃@Ag/Cu composites with 1–3 wt.% Al₂O₃ were prepared by rapid hot-press sintering. The effects of plating temperature and Al₂O₃ content on microstructure and properties were investigated. The results show that the optimum coating temperature is 25 °C, and a thin and uniform silver coating can be formed. This effectively improved Al₂O₃–Cu interface bonding while maintaining 77.8% of copper’s thermal conductivity (320.7 W/(m·K)). The composites showed improved wear resistance with increasing Al₂O₃ content. At 3 wt.% Al₂O₃@Ag, the wear rate was 3.36 × 10⁻⁵ mm³/(N·m), 84.4% lower than pure copper, with plow groove wear as the main mechanism. Full article

Lakes play a crucial role in maintaining agricultural irrigation water sources, regulating climate, and supporting the long-term resilience of regional ecosystems. However, accurately delineating the boundaries between lakes and land remains challenging due to seasonal hydrological fluctuations, spectral obfuscation with farmland, and the limitations of single-sensor methods. This study constructs a multi-source remote sensing framework integrating Sentinel-1 SAR, Sentinel-2 optical data, DEM, and key environmental variables to identify the water body, near-water body, and non-water surface of Weishan Lake, a major irrigation source in northern China. The study systematically compares various methods, including the optical index method, SAR-based threshold segmentation, and machine learning classifiers. The results show that the random forest model has higher accuracy and temporal robustness. Introducing the “near-water body” category allows for more accurate characterization of transitional areas sensitive to seasonal hydrological and agricultural processes. Migration tests of the model in three external lake systems demonstrate its strong generalization ability, while correlation analysis and SHAP-based analysis indicate that NDVI and elevation are the main factors influencing the spatial pattern of water and land. The proposed framework supports sustainable irrigation management by enabling accurate water boundary monitoring and enhancing the understanding of agricultural hydrological interactions. Full article

This paper presents accurate TD-DFT calculations for several mixed-ligand gold(III) complexes with ligands including Cl⁻, Br⁻, I⁻, OH⁻, and NH₃. The calculated results show excellent agreement with available experimental data. The spectral shapes are determined by charge transfer transitions, which are systematically influenced by the ligand’s position in the spectrochemical series. The main vertical electron transitions and the molecular orbitals involved are identified and discussed. Furthermore, the results indicate that the iodide-containing gold(III) complexes, [AuCl₂I₂]⁻ and [AuI(OH)₃]⁻, are viable candidates for practical synthesis. Full article

The objective of this paper is to describe the process of transition from the Farm Accountancy Data Network (FADN) to the Farm Sustainability Data Network (FSDN), a European survey that gathers yearly data about agricultural holdings at microeconomic level. Established initially to monitor economic aspects of farm income and support Common Agricultural Policy (CAP) evaluations, the network has now broadened its scope to integrate environmental and social aspects of farm management, in line with the EU Green Deal and the Farm to Fork strategy. The Implementing Regulation (EU) 2023/2674 formalizes this integration, adding new variables, encouraging the participation of the farms (voluntary), and supporting the improvement in interoperability to reduce the statistical burden on farmers and data collectors. The paper discusses the main challenges and opportunities of this transition, emphasizing how FSDN will deliver a more comprehensive and reliable dataset for policy evaluation and for advancing the understanding of farm-level sustainability. Full article