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Found 5152 publications
Unveiling the mechanisms and implications: how artificial intelligence drives green growth in China’s Huaihe River Ecological Economic Belt under the carbon neutrality agenda
Publication Name: Carbon Footprints
Publication Date: 2025-09-01
Volume: 4
Issue: 3
Page Range: Unknown
Description:
Amidst the backdrop of global climate warming and China’s proactive chase of its carbon peak and carbon neutrality goals, the Huaihe River Basin (HRB), a region of significant strategic importance in the heartland and eastern expanse of the nation is confronted with formidable challenges, including high energy consumption and severe environmental pollution. Despite its substantial contributions to economic development, the traditional development model of the HRB conflicts with the principles of green development, necessitating the urgent exploration of innovative pathways to sustainable progress. Through a comprehensive review of scholarly literature and rigorous theoretical analysis, this study demonstrates that artificial intelligence (AI) can significantly drive green development by enhancing eco-innovation and optimizing industrial structures. Using a panel dataset from 27 cities in the Huaihe River Ecological Economic Belt (HEB) from 2010 to 2022, this study employs a bidirectional fixed-effects model to analyze the repercussions of AI on green development. The baseline regression results show that for every one-unit increase in AI development level (AIDL), HEB’s urban green development level significantly increases by 0.087. This positive influence is further confirmed through robustness tests. We found that AI can indirectly influence the mechanism and pathway of green development through intermediate variables. AI drives green development indirectly through two pathways: green technology innovation and the rationalization of the industrial structure, with a total explanatory power of 56.7% (R2 = 0.812). Based on these findings, we propose vigorously promoting the green effects of AI, refining industrial structures, and leveraging mediating effects to foster sustainable regional development. These insights offer novel perspectives for the green development of the HRB but also provide valuable references for the green transformation of other areas with similar challenges.
Open Access: Yes
DOI: 10.20517/cf.2025.9
Integrating generative and parametric design with BIM: A literature review of challenges and research gaps in construction design
Publication Name: Applications in Engineering Science
Publication Date: 2025-09-01
Volume: 23
Issue: Unknown
Page Range: Unknown
Description:
Parametric Design (PD), Generative Design (GD), and Building Information Modelling (BIM) have emerged as transformative tools in the construction industry, offering significant potential for design optimisation, interdisciplinary collaboration, and data-driven decision making. This paper presents a comprehensive literature review to evaluate the current state of PD, GD, and BIM integration, highlighting practical applications and identifying research gaps. In addition to mapping the academic discourse, the review also highlights selected practical implementations from existing literature to illustrate how these technologies are being translated into applied workflows. Furthermore, the methodology section critically reflects on the limitations of the keyword-based search strategy and suggests future directions to mitigate potential literature gaps. While many studies demonstrate efficiency gains in early design phases, the integration of these technologies across the full building lifecycle remains limited. Key challenges include insufficient interoperability between platforms, lack of standardisation, and minimal adoption of GD-BIM combinations in construction and logistics. Furthermore, few studies address the regulatory compliance and real-world scalability of AI-assisted generative models. The review concludes that although these digital methods can accelerate innovation and sustainability, their practical implementation requires further research in construction management, code-based automation, and human-in-the-loop design workflows.
Open Access: Yes
The Relationship Between EMF Exposure and MIMO Systems, and the Exposure Advantages of Lowband Massive MIMO System
Publication Name: Telecom
Publication Date: 2025-09-01
Volume: 6
Issue: 3
Page Range: Unknown
Description:
With the advancement of mobile communications, technologies based on high-element-count antenna systems—such as massive Multiple Input Multiple Output (massive MIMO)—are playing an increasingly important role in enhancing network capacity. However, they introduce new challenges in the measurement and evaluation of electromagnetic field (EMF) exposure. This study presents a detailed, laboratory-based methodology for assessing EMF exposure in cellular systems using Single Input Single Output (SISO) and MIMO technologies. To address the limitations of traditional exposure assessment techniques—particularly under the conditions introduced by 5G and active antenna systems—a shielded test environment with directional antennas was developed and applied across lowband and midband frequency ranges (700–2100 MHz). Downlink electromagnetic power density was measured under standardized modulation, coding, and bandwidth settings for both SISO and MIMO configurations. The results show that MIMO technology does not lead to a significant increase in EMF exposure compared to SISO, with average differences remaining below 1 dB. Moreover, in lower-frequency bands, massive MIMO systems can ensure the required user capacity at significantly lower transmission power, resulting in more than 15 dB reductions in EMF exposure. These findings confirm the potential of massive MIMO to enhance network performance while reducing the level of electromagnetic exposure.
Open Access: Yes
Optimizing the Artificial Aging Process of Lubricating Oils Contaminated by Alternative Fuel Using Design of Experiments Methodology
Publication Name: Lubricants
Publication Date: 2025-09-01
Volume: 13
Issue: 9
Page Range: Unknown
Description:
This study aimed to develop an experimental method for producing artificially aged oil with properties—such as coefficient of friction, average wear scar diameter, and antiwear additive content—similar to those of used oil contaminated with alternative fuel, sampled after 129 h of engine test bench operation. A design of experiment (DoE) methodology was applied to examine the effects of various parameters and identify optimal settings. Friction and wear tests were conducted using an Optimol SRV5 tribometer in a ball-on-disc configuration, while wear scars were analyzed with a Keyence VHX-1000 digital microscope. Oil analysis was conducted with an Anton Paar 3001 viscometer and a Bruker Invenio-S Fourier-transform infrared spectrometer. The DoE results showed that the heating duration had a negligible effect on oil degradation. Aging time primarily affected changes in the friction coefficient and average wear scar diameter, whereas aging temperature was the primary factor influencing the anti-wear additive content. Gaussian elimination identified the optimal aging parameters as 132.8 °C and 103.1 h. These results were confirmed through surface analysis using a ThermoFisher NexsaG2 X-ray photoelectron spectrometer, which showed that the tribofilm composition of the used oil most closely matched that of artificially aged oils prepared at 120 °C for 96 h and 140 °C for 120 h. The strong correlation between the predicted and experimentally confirmed conditions demonstrates the reliability of the proposed method for replicating realistic aging effects in lubricating oils.
Open Access: Yes
Using Multivariate Statistical Analysis for Examining the Relationship between Food Waste Generation and Socio-economic Factors
Publication Name: Journal of Sustainable Development of Energy Water and Environment Systems
Publication Date: 2025-09-01
Volume: 13
Issue: 3
Page Range: 1-16
Description:
Food waste contributes to social inequalities and sustainability issues by worsening resource overuse and environmental harm. The United Nations Sustainable Development Goal 17 highlights the importance of reducing food waste to address hunger and promote a sustainable, economically viable global food system. This paper examines the geographic differences in food waste levels among European Union member nations and analyses the associations between food waste and diverse environmental, geographic, social and economic indicators, including Sustainable Development Goals and other sustainability metrics. Using dimensionality reduction methods, nontrivial multivariate connections between food waste and these parameters were identified, allowing for the characterisation of countries based on a few significant factors. Principal Component Analysis (PCA), applied to food waste data across European Union countries, uncovered three distinct groups: (1) those with elevated food waste in primary production, manufacturing and distribution stages; (2) those with lower waste in these domains yet elevated waste in restaurants and households; and (3) those with all of their food waste components smaller than or equal to the average. The multivariate linear correlation between the PCA factors and socio-economic parameters is nonsignificant, but a few (nonlinear) regularities could be identified: five of the six countries of the first group above are characterised by the population settled mainly on flatland and an above-average supply of meat or fish. Another pattern observed is that former Eastern Bloc countries belong to the third group. The research findings offer valuable insights that can inform the efforts of environmental experts, professionals and policymakers working in the circular economy and waste management domains. This knowledge can facilitate the development of more effective strategies aimed at mitigating food waste and promoting sustainability.
Open Access: Yes
The ACTN3 R577X Nonsense Allele Is Underrepresented in Professional Volleyball Players and Associated with an Increased Risk of Muscle Injury in Female Players
Publication Name: Genes
Publication Date: 2025-09-01
Volume: 16
Issue: 9
Page Range: Unknown
Description:
Background: Muscle injuries pose a significant challenge in sports, leading to decreased performance and shortened career longevity. Individuals homozygous for the nonsense X allele of the ACTN3 rs1815739 (R577X) polymorphism, characterized by a complete absence of α-actinin-3, have been associated with reduced power performance and may have an increased injury risk. This study aimed to investigate the association between the ACTN3 R577X polymorphism and both volleyball player status and the risk of non-contact musculoskeletal injuries in female volleyball players. Methods: The study included 5382 Turkish and Russian subjects of European descent (187 professional volleyball players and 5195 controls), of whom 50 female players provided injury data. Sport-related injury information was obtained from medical records maintained by team physicians and physiotherapists. Results: A pooled analysis of the two cohorts demonstrated that the frequency of the ACTN3 X allele was significantly lower in volleyball players than in controls, with an odds ratio of 0.763 (95% CI: 0.61–0.95, p = 0.02). In the pre-specified recessive contrast (XX vs. RR + RX) among 50 players, exact methods indicated higher injury odds for the XX genotype (OR = 7.87, 95% CI: 0.94–374.58; p = 0.0366), which was classified as borderline/exploratory. Penalized (Firth) regression produced estimates of a similar magnitude after adjustment for age and playing position (adjusted OR = 5.92, 95% CI: 1.12–60.98), although confidence intervals remained wide. Conclusions: The ACTN3 X allele is underrepresented in professional volleyball players, and it is associated with an increased risk of muscle injury in female players.
Open Access: Yes
A proposed wavelet analysis based fault diagnosis scheme of power transformers using fault signatures and CT saturation
Publication Name: Results in Engineering
Publication Date: 2025-09-01
Volume: 27
Issue: Unknown
Page Range: Unknown
Description:
Diagnosis of concealed internal faults within power transformer is a key for high grid reliability to ensure continuity of power supply to customers. One of the urgent situations of power transformer is the faults under CT saturation and the operation under inrush currents that lead to huge failure of fault identification of the power transformer. In this paper, a fault identification scheme is designed using details and approximate coefficients obtained by discreet wavelet transform applied to a differential current signal under different situations. Also, this paper considers the impact of transformer internal faults such as turn to earth and turn to turn faults, external faults, and inrush currents. The signature of processing differential current is employed for identifying these fault conditions since such fault has a distinct differential current signature. The simulation tests are performed on a 115/22 kV power transformer using ATP-EMTP real-time simulator. Different wavelet families are assessed to show that the optimum mother wavelet, db1, has high fault detection and classification performance. The proposed scheme is verified for transformer energization conditions, and the influence of CT saturation is also considered in this study. Moreover, one of the most important proposed scheme features is simplicity with high lights aspects toward all fault conditions and fault types at different fault location and different fault resistances. Intensive simulation results are obtained to prove the improved selectivity and sensitivity of the proposed scheme for identifying internal transformer faults. Furthermore, sensitivity analysis is not only conducted in terms of transformer loading and fault resistance variation, but transformer scalability study is also verified. Finally, to evaluate the performance of the proposed scheme, an assessment study is adopted to show the accuracy and reliability of differential protection scheme.
Open Access: Yes
From Voice to Action: Upholding Children’s Right to Participation in Shaping Policies and Laws for Digital Safety and Well-Being
Publication Name: Societies
Publication Date: 2025-09-01
Volume: 15
Issue: 9
Page Range: Unknown
Description:
While the digital environment offers new opportunities to realise children’s rights, their right to participation remains insufficiently reflected in digital policy frameworks. This study analyses the right of the child to be heard in the academic literature and in the existing international legal and EU regulatory frameworks. It explores how children’s participation right is incorporated into EU and national digital policies and examines how genuine engagement can strengthen children’s digital resilience and support their well-being. By applying the 7C model of coping skills and analysing its interaction with the right to participation, the study highlights how these elements mutually reinforce the achievement of the Sustainable Development Goals (SDGs). Through a qualitative analysis of key strategic documents and the relevant policy literature, the research identifies the tension between the formal acknowledgment of children’s right to participate and its practical implementation at law- and policy-making levels within the digital context. Although the European Union’s examined strategies emphasise children’s participation, their practical implementation often remains abstract and fragmented at the state level. While the new BIK+ strategy shows a stronger formal emphasis on child participation, this positive development in policy language has not yet translated into a substantive change in children’s influence at the state level. This nuance highlights that despite a positive trend in policy rhetoric, the essential dimension of genuine influence remains underdeveloped.
Open Access: Yes
DOI: 10.3390/soc15090243
A Life Cycle Assessment Framework for Evaluating the Climate Impact of Hydrogen-Based Passenger Vehicle Technologies Toward Sustainable Mobility
Publication Name: Hydrogen Switzerland
Publication Date: 2025-09-01
Volume: 6
Issue: 3
Page Range: Unknown
Description:
Hydrogen-based mobility solutions could offer viable technology for sustainable transportation. Current research often examines single pathways, leaving broader comparisons unexplored. This comparative life cycle assessment (LCA) evaluates which vehicle type achieves the best environmental performance when using hydrogen from grey, blue, and green production pathways, the three dominant carbon-intensity variants currently deployed. This study examines seven distinct vehicle configurations that rely on hydrogen-derived energy sources across various propulsion systems: a hydrogen fuel cell electric vehicle (H2 FCEV), hydrogen internal combustion engine vehicle (H2 ICEV), methanol flexible fuel vehicle (MeOH FFV), ethanol flexible vehicle (EtOH FFV), Fischer-Tropsch (FT) diesel internal combustion vehicle (FTD ICEV) and renewable compressed natural gas vehicle (RNGV). Via both grey and blue hydrogen production, H2 FCEVs are the best options from the viewpoint of GWP, but surprisingly, in the green category, FT-fueled vehicles take over both first and second place, as they produce nearly half the lifetime carbon emissions of purely hydrogen-fueled vehicles. RNGV also emerges as a promising alternative, offering optimal engine properties in a system similar to H2 ICEVs, enabling parallel development and technological upgrades. These findings not only highlight viable low-carbon pathways but also provide clear guidance for future targeted, detailed, applied research.
Open Access: Yes
