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Found 6374 publications
Strategic Business Resilience Affecting Green and Renewable Energy-Related Financial Literacy in Mexico
Publication Name: Data Driven Esg Strategy Implementation Through Business Intelligence
Publication Date: 2025-08-12
Volume: Unknown
Issue: Unknown
Page Range: 87-114
Description:
This research investigates the multifaceted relationship between strategic business resilience and financial literacy in the green and renewable energy industry of Mexico. As Mexico transitions to sustainable energy sources, it is ever more critical to comprehend how companies formulate resilience strategies while maintaining financial literacy for industry growth and economic stability. The key findings indicate that companies with robust resilience mechanisms exhibit enhanced capacity for financial planning, risk assessment, and investment decision- making in renewable energy projects. The study identifies critical factors like adaptive leadership, technology integration, stakeholder engagement, and adherence to regulations as primary drivers of both resilience and financial literacy.
Open Access: Yes
Green and Renewable Energy Financial Literacy Affecting Economy, Society, and Governance (ESG) in Mexico
Publication Name: Data Driven Esg Strategy Implementation Through Business Intelligence
Publication Date: 2025-08-12
Volume: Unknown
Issue: Unknown
Page Range: 115-139
Description:
This research delves into the intricate relationship between green and renewable energy financial literacy and its impact on Environmental, Social, and Governance (ESG) practices in Mexico's changing economic landscape. The study attempts to investigate how financial literacy regarding sustainable energy investments influences the performance of ESG on economic, social, and governance factors in the Mexican context. Through a careful examination of available literature, policy guidelines, and empirical data, this research discovers that greater financial literacy in green and renewable energy sectors has a direct correlation with improved ESG performance, which results in sustainable economic development, social advancement, and governance culture in Mexico. The study concludes that strategic actions to increase financial literacy in renewable energy investments are required for Mexico's sustainable development trajectory and ESG leadership in the Latin American region.
Open Access: Yes
Tourism-Oriented Spatial Analysis of Tangible Cultural Heritage in Bukhara (Uzbekistan)
Publication Name: Forum Geografi
Publication Date: 2025-08-01
Volume: 39
Issue: 2
Page Range: 238-261
Description:
This study examines the spatial distribution and tourism utilization of 829 officially registered architectural heritage sites in the Bukhara, Uzbekistan. Spatial analysis methods including the Gini Index (0.569), Lorenz Curve, Nearest Neighbor Analysis, Kernel Density Estimation, and Bivariate Moran’s I were applied to examine clustering patterns and disparities across districts. The findings reveal unequal heritage distribution: over 50% of the sites are located in two districts, mainly in the eastern region, while others remain underrepresented. The Bukhara city shows strong clustering, whereas several districts exhibit random or dispersed patterns. Despite a sharp rise in tourist arrivals from 13,300 international visitors in 2020 to over 1.7 million in 2024 only 146 sites (17.6%) are actively used for tourism. This increased tourism pressure, with visitors per site growing from 1,798 to 39,351. Typological analysis showed uneven spatial patterns among major religious, administrative, residential, and public groups. Bivariate Moran’s I (I = –0.0621, p = 0.498) indicated no significant spatial correlation between population density and heritage distribution. The study recommends adopting circular tourism strategies to reduce pressure, balance regional disparities, and promote sustainable heritage-based tourism development. Findings offer a basis for balanced heritage management and tourism development in Uzbekistan with comparable regions.
Open Access: Yes
Mechanism of environmental regulation on energy productivity, energy structure, and carbon emissions: The role of directed technological progress
Publication Name: Energy
Publication Date: 2025-08-01
Volume: 328
Issue: Unknown
Page Range: Unknown
Description:
The mechanism of environmental regulation on energy conservation and carbon reduction in the petrochemical industry through directed technological progress remains uncertain due to the directional characteristics of technology. This paper develops a mechanism framework and employs a panel two-way fixed-effects model to clarify the impact of environmental regulation on directed technological progress and energy conservation, while uncovering its underlying mechanisms. Subsequently, a dynamic Kaya model is constructed, using the Monte Carlo method to determine the required intensity of environmental regulation for China's petrochemical industry to actualize the SSP1-CHN, SSP1, and SSP2 scenarios. The model also simulates the future bias of technological progress, energy utilization, and potential carbon emissions under each scenario. The findings indicate that increasing the intensity of environmental regulation drives technological progress toward energy conservation, thereby enhancing energy-saving biased technological progress, improving energy productivity, and optimizing the energy structure. Furthermore, to actualize the carbon peak by 2030 and carbon neutrality by 2060 under the SSP1-CHN scenario, the annual growth rate of environmental regulation intensity in China's petrochemical industry should be no less than 8 % before 2030 and should be strengthened to 20 % after 2030.This study not only extends the application of directed technological progress theory in the energy field but also provides innovative and practical environmental policy recommendations for the low-carbon development of the global petrochemical industry.
Open Access: Yes
Blockchain and Smart Cities: Co-Word Analysis and BERTopic Modeling
Publication Name: Smart Cities
Publication Date: 2025-08-01
Volume: 8
Issue: 4
Page Range: Unknown
Description:
Highlights: What are the main findings? Blockchain plays a foundational role in supporting secure, interoperable infrastructure for key urban services, particularly through integration with IoT, edge computing, and smart contracts. Research has shifted from general blockchain exploration to sector-specific applications, including decentralized healthcare, energy trading, smart mobility, and drone coordination. What is the implication of the main finding? Blockchain enables cross-sectoral innovation in smart cities by enhancing transparency, data integrity, and trust across complex urban systems. As both a technological and ethical infrastructure, blockchain supports the development of secure, resilient, and sustainable smart city ecosystems aligned with Industry 5.0 values. This paper explores the intersection of blockchain technology and smart cities to support the transition toward decentralized, secure, and sustainable urban systems. Drawing on co-word analysis and BERTopic modeling applied to the literature published between 2016 and 2025, this study maps the thematic and technological evolution of blockchain in urban environments. The co-word analysis reveals blockchain’s foundational role in enabling secure and interoperable infrastructures, particularly through its integration with IoT, edge computing, and smart contracts. These systems underpin critical urban services such as transportation, healthcare, energy trading, and waste management by enhancing data privacy, authentication, and system resilience. The application of BERTopic modeling further uncovers a shift from general technological exploration to more specialized and sector-specific applications. These include real-time mobility systems, decentralized healthcare platforms, peer-to-peer energy exchanges, and blockchain-enabled drone coordination. The results demonstrate that blockchain increasingly supports cross-sectoral innovation, enabling transparency, trust, and circular flows in urban systems. Overall, the current study identifies blockchain as both a technological backbone and an ethical infrastructure for smart cities that supports secure, adaptive, and sustainable urban development.
Open Access: Yes
An Assessment of Motor Skills in Infants at Risk of Atypical Psychomotor Development Using the Vojta Method
Publication Name: Children
Publication Date: 2025-08-01
Volume: 12
Issue: 8
Page Range: Unknown
Description:
Background: Some neonates are assessed for the risk of atypical psychomotor development at birth and are referred for reflex locomotion therapy using the Vojta method. Aim: The aim of this study was to analyze the relationships between spontaneous motor activity (SMA), ideal movement patterns (IMPs), central coordination disorders (CCDs), vital signs at birth, involuntary reflexes, and postural asymmetry in infants. Methods: This study involved 90 female and 107 male subjects in the age interval of 1–16 months (4.15 ± 2.18). Their psychomotor development was assessed using the Vojta method. Age-appropriate involuntary reflexes were evaluated, and both parameters were correlated with perinatal risk factors. Results: Males scored significantly higher than females (difference of −0.7, p = 0.022) in the SMA test. In both genders, SMA (p < 0.001 in both genders) and IMP scores improved significantly with age. In male infants, higher CCD scores were associated with significantly lower SMA and IMP scores (p = 0.017 and p < 0.001, respectively). Significantly higher CCD scores were noted in female subjects with the Moro reflex and postural asymmetry (p = 0.003 and p = 0.002, respectively). In males, the Moro reflex was significantly correlated with the Vojta reaction (p = 0.012) and the Collis vertical suspension reflex (p < 0.001). Conclusions: Vital signs at birth, including birth weight, Apgar score, and type of delivery, can predict motor development disorders but do not clearly differentiate infants that require neurodevelopmental therapy.
Open Access: Yes
Prediction of possible tornado strike using complex m-polar fuzzy information based on Dombi operators
Publication Name: Ain Shams Engineering Journal
Publication Date: 2025-08-01
Volume: 16
Issue: 8
Page Range: Unknown
Description:
Tornados are extremely catastrophic, and the global effect of natural calamities like tornados is enormous and needs prompt and effective management. We can tackle this problem by using measures like multi-criteria decision-making (MCDM) to identify high-risk areas of a potential tornado strike. We frequently use MCDM techniques to solve the complexities and uncertainties of modern-era problems. We present a study that builds a prediction model by combining the Dombi aggregation operator with a complex m-polar fuzzy set (CmFS) to accurately guess when a tornado will hit. Our proposed model determines an expert panel, criteria, and a set of alternatives after identifying the problem. We create summed-up decision matrices using complex m-polar fuzzy Dombi aggregation operators (CmFDAO) after experts evaluate criteria and options. The algorithm then presents the best option with the help of a final decision score matrix. Our model uses a set of eight meteorological elements and eight experts to assess four possible tornado locations and pinpoint an area with a high risk of tornado strikes. The results generated by our aggregation operator set demonstrate that our proposed method for handling complex and multi-polar data is concise and efficient when compared to other sets. This early prediction highlights the potential of significant risk reduction to the environment and human life due to catastrophic events like tornados by enhancing early warning systems and effective emergency management.
Open Access: Yes
Adaptive Sign Language Recognition for Deaf Users: Integrating Markov Chains with Niching Genetic Algorithm
Publication Name: AI Switzerland
Publication Date: 2025-08-01
Volume: 6
Issue: 8
Page Range: Unknown
Description:
Sign language recognition (SLR) plays a crucial role in bridging the communication gap between deaf individuals and the hearing population. However, achieving subject-independent SLR remains a significant challenge due to variations in signing styles, hand shapes, and movement patterns among users. Traditional Markov Chain-based models struggle with generalizing across different signers, often leading to reduced recognition accuracy and increased uncertainty. These limitations arise from the inability of conventional models to effectively capture diverse gesture dynamics while maintaining robustness to inter-user variability. To address these challenges, this study proposes an adaptive SLR framework that integrates Markov Chains with a Niching Genetic Algorithm (NGA). The NGA optimizes the transition probabilities and structural parameters of the Markov Chain model, enabling it to learn diverse signing patterns while avoiding premature convergence to suboptimal solutions. In the proposed SLR framework, GA is employed to determine the optimal transition probabilities for the Markov Chain components operating across multiple signing contexts. To enhance the diversity of the initial population and improve the model’s adaptability to signer variations, a niche model is integrated using a Context-Based Clearing (CBC) technique. This approach mitigates premature convergence by promoting genetic diversity, ensuring that the population maintains a wide range of potential solutions. By minimizing gene association within chromosomes, the CBC technique enhances the model’s ability to learn diverse gesture transitions and movement dynamics across different users. This optimization process enables the Markov Chain to better generalize subject-independent sign language recognition, leading to improved classification accuracy, robustness against signer variability, and reduced misclassification rates. Experimental evaluations demonstrate a significant improvement in recognition performance, reduced error rates, and enhanced generalization across unseen signers, validating the effectiveness of the proposed approach.
Open Access: Yes
DOI: 10.3390/ai6080189
Investigation of the Load-Bearing Capacity of Resin-Printed Components Under Different Printing Strategies
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-08-01
Volume: 15
Issue: 15
Page Range: Unknown
Description:
This study examines the influence of different printing orientations and infill settings on the strength and flexibility of components produced using resin-based 3D printing, particularly with masked stereolithography (MSLA). Using a common photopolymer resin and a widely available desktop MSLA printer, we produced and tested a series of samples with varying tilt angles and internal structures. To understand their mechanical behavior, we applied a custom bending test combined with high-precision deformation tracking through the GOM ARAMIS digital image correlation system. The results obtained clearly show that both the angle of printing and the density of the internal infill structure play a significant role in how much strain the printed parts can handle before breaking. Notably, a 75° orientation provided the best deformation performance, and infill rates between 60% and 90% offered a good balance between strength and material efficiency. These findings highlight how adjusting print settings can lead to stronger parts while also saving time and resources—an important consideration for practical applications in engineering, design, and manufacturing.
Open Access: Yes
DOI: 10.3390/app15158747
