Search Results (3,278)

In the era of the ‘Internet of Everything’ and amid growing demands for high-quality economic development, public data has emerged as a new core factor of production, establishing itself as a pivotal force behind regional economic growth. However, existing research rarely clarifies the multi-dimensional impact and influence mechanism of public data openness on regional development, and there are still deficiencies in the research on transforming the advantages of data elements into sustainable economic driving forces. This study, in conjunction with the interpretation of data elements, employed a fixed-effects model to empirically investigate the impact and path of public data opening on the high-quality development of regional economies, using panel data from 31 provincial regions in China from 2017 to 2024. Empirical findings provide clear evidence that public data openness acts as a significant catalyst for high-quality economic development, thereby solidifying its role as an indispensable engine for sustainable growth in the digital era. Analysis of the underlying mechanisms reveals two primary channels: business environment optimization and improved factor allocation efficiency, with the latter proving to be the more significant driver. Furthermore, heterogeneity analysis reveals that the positive effects are most pronounced in fostering economic structural optimization, advancing the low-carbon environment and expanding shared public welfare, while their influence on innovation dynamism remains comparatively modest. The research results support the government in increasing the openness of public data, establishing and improving a data opening mechanism oriented towards the business environment, and deepening the integration and application of data to enhance the efficiency of factor allocation. Full article

β-blockers are among the most highly consumed cardiovascular drugs worldwide, resulting in their classification as persistent and bioactive pharmaceutical pollutants. This review provides a mechanistically oriented synthesis of their environmental release, stereochemical and matrix-dependent transformation, biotic and abiotic degradation, and the ecotoxicological significance of their degradation products. Wastewater treatment plants are identified as the primary, yet variably efficient, emission sources to aquatic systems. Molecular structure, chirality, and interactions with environmental matrices are highlighted as key factors influencing transformation behaviour and residue persistence. Current evidence indicates that β-blockers and several transformation products retain pharmacological activity, driving organism- and community-level effects at environmentally relevant exposures. Major limitations in the field stem from methodological heterogeneity and uneven regional and temporal coverage, which continue to weaken long-term risk evaluation. By unifying analytical chemistry, pharmacological mechanistics, and environmental toxicology evidence, this review advances the narrative from descriptive occurrence reports toward systematic evaluation of transformation product persistence, mechanism-dependent residue stability, and their ecological implications. Full article

This study is an attempt to compile and complete structural features of the Kalba-Narym Zone in East Kazakhstan belonging to the western Central Asian Orogenic Belt, which is known to be well-endowed with the occurrence of pegmatite rare-metal mineralization. Remote sensing and GIS-based 2D are utilized to map the geological structural lineaments of faults and granitic pegmatite and pegmatite dikes. This includes lineament extraction on regional and district scales. Then, the spatial relationship between pegmatite dikes and faults is analyzed, including the lineament trends and proximity patterns. The spatial analyses are performed via the geo-computational method of Distance to Nearest Neighbors (DNN), Ripley’s L′ function, and pegmatite orientation families were employed to study the spatial distribution pattern of the pegmatites. The results of this study demonstrate that the occurrence of pegmatite dikes in various Greenfields and Brownfields of the Kalba-Narym Zone follows clustered distributions, the orientation of pegmatite swarms is dominantly NW-SE, and pegmatite emplacement is proximal to the intersection of multiple faulting systems. Extracted fault strikes, demonstrating a pronounced NW–SE to NNW–SSE structural fabric across the zone, show orientation association with the pegmatite dikes. Extraction and demarcation of pegmatites on a regional scale via remote sensing techniques help efficiently narrow down the target areas before conducting geological campaigns. This investigation proposes several new districts of pegmatite occurrence in the Kalba-Narym Zone as potential targets for exploration of critical metals. Full article

Policy misalignment is a key factor affecting the implementation of solid waste management policies and resolving such a misalignment is critical to advancing the solid waste disposal capacity (SWDC) and supporting the goal of a “zero-waste city”. This policy misalignment indicator provides a measurable tool to track progress toward Sustainable Cities and Communities. This study used panel data from 281 cities at the prefecture level and above from 2018 to 2022. The study involved constructing an original database of central and provincial policy documents on urban waste governance and transforming the policy documents into an indicator to capture the degree of policy misalignment, which serves as the key explanatory variable in a fixed-effects model. The study further examined how fiscal decentralization, the digital economy, and regional and administrative characteristics influence cities’ responses to policy misalignments. These factors serve a vital function in moderating the effects of misalignment and explaining heterogeneity across cities. The empirical results show that a vertical policy misalignment significantly reduced the solid waste disposal capacity, while fiscal decentralization and digital economy development mitigated its negative effects. The adverse impacts were particularly pronounced in non-key cities, eastern regions, and cities with low government attention, highlighting the role of local capacity and administrative focus in mediating cross-level policy impacts. The heterogeneous effects observed across city types further offer targeted insights for designing sustainability-oriented waste management policies, enabling regions to tailor interventions based on their administrative capacity and development context. Full article

Efficient utilization of solar energy in equatorial regions depends on accurately determining the optimal tilt and azimuth angles of fixed photovoltaic (PV) systems. This study presents a three-dimensional vector-based methodology that employs Direct Normal Irradiance (DNI) to estimate the mean direction of incident solar flux. Hourly DNI data from 2020–2024 for the city of Guayaquil, Ecuador, were transformed into spatial vectors and integrated to obtain a resultant vector representing the average orientation and elevation of direct solar radiation. The analysis yielded an optimal tilt angle of 5.73° and an azimuth of 59.15°, values consistent with Guayaquil’s equatorial latitude and previous studies conducted in tropical environments. The low tilt angle reflects the persistently high solar elevation typical of equatorial zones, while the slight northeastward orientation deviation corresponds to the asymmetric diurnal distribution of solar irradiance. The main contribution of this work lies in providing a geometrically rigorous and computationally efficient approach capable of synthesizing the directional behavior of solar flux without relying on complex transposition models. The proposed method enhances the optimization of PV system design, urban energy planning, and renewable microgrid modeling in data-scarce contexts, supporting the sustainable development of solar energy in equatorial regions. Full article

An increasing number of juveniles are accessing adult-oriented venues, such as bars and nightclubs, where supervision is frequently inadequate, thereby elevating their risk of both offline harm and unmonitored exposure to harmful online content. Existing facial age estimation systems, which are primarily designed for adults, have significant limitations when it comes to protecting juveniles, hindering the efficiency of supervising them in key venues. To address these challenges, this study proposes a facial age estimation solution for juvenile protection. First, we have designed a ‘detection–cropping–classification’ framework comprising three stages. This first detects facial regions using a detection algorithm, then crops the image before inputting the results into a classification model for age estimation. Secondly, we constructed the the Juvenile Protection Surveillance and Detection (JPSD) Dataset by integrating five public datasets: UTKface, AgeDB, APPA-REAL, MegaAge and FG-NET. This dataset contains 14,260 images categorised into four age groups: 0–8 years, 8–14 years, 14–18 years and over 18 years. Thirdly, we conducted baseline model comparisons. In the object detection phase, three YOLO algorithms were selected for face recognition. In the age estimation phase, traditional convolutional neural networks (CNNs), such as ResNet50 and VGG16, were contrasted with vision transformer (ViT)-based models, such as ViT and BiFormer. Gradient-weighted Class Activation Mapping (Grad-CAM) was used for visual analysis to highlight differences in the models’ decision-making processes. Experiments revealed that YOLOv11 is the optimal detector for accurate facial localisation, and that ResNet50 is the best base classifier for enhancing age-sensitive feature extraction, outperforming BiFormer. The results show that the framework achieves Recall of 89.17% for the 0–8 age group and 95.17% for the over-18 age group. However, we have found that the current model has low Recall rates for the 8–14 and 14–18 age groups. Therefore, in the near term, we emphasise that this technology should only be used as a decision-support tool under strict human-in-the-loop supervision. This study provides an essential dataset and technical framework for juvenile facial age estimation, offering support for juvenile online protection, smart policing and venue supervision. Full article

Recently, the role of businesses in advancing sustainable development has drawn growing attention from governments, investors, and a wide range of stakeholders. This increased focus has led enterprises to incorporate environmental, social, and governance (ESG) considerations into their strategic and operational decisions, driven by evolving regulatory frameworks, increasing investor scrutiny, and rising consumer expectations. Despite this shift toward sustainability-oriented practices, the relationship between ESG performance and financial results remains a subject of considerable debate and empirical uncertainty. The research examines the links between separate ESG pillars and the financial performance of enterprises operating within resource-intensive industries, such as energy, industrials, materials, and utilities across Europe and the USA, based on a sample of 384 companies, using data from 2015 to 2024. The study focuses on differences between regions and further examines whether differences in the influence of individual ESG dimensions on the financial results of enterprises are evident within specific industries. The research findings present identified positive and statistically significant relationships with the environmental pillar of ESG for both Europe and the US regions. There are differences between the social and governance pillars of ESG and the financial performance of the resource-intensive industries of Europe and the USA. In Europe, there is a positive influence of social-related factors on financial performance, while in the USA, there is a negative impact. However, the governance-related factor shows that a statistically significant relationship exists with financial performance in the USA, and a negative one in Europe. These findings show the different focus directions of Europe and the USA regions. Full article

This article presents the results of a comprehensive study aimed at developing automated diagnostic methods for identifying spring wheat phytopathologies using hyperspectral imaging (HSI). The research aimed to create an effective plant disease detection system, including at the early stages, which is critically important for ensuring food security in regions where wheat plays a key role in the agro-industrial sector. The study analyses the spectral characteristics of major wheat diseases, including powdery mildew, fusarium head blight, septoria glume blotch, root rots, various types of leaf spots, brown rust, and loose smut. Healthy plants differ from diseased ones in that they show a mostly uniform tone without distinct spots or patches on hyperspectral images, and their spectra have a consistent shape without sharp fluctuations. In contrast, disease spectra, differ sharply from those of healthy areas and can take diverse forms. Wheat diseases with a light coating (powdery mildew, fusarium head blight) exhibit high reflectance; chlorosis in the early stages of diseases (rust, leaf spot, septoria leaf blotch) exhibits curves with medium reflectance, and diseases with dark colouration (loose smut, root rot) have low reflectance values. These differences in reflectance among fungal diseases are caused by pigments produced by the pathogens, which either strongly absorb light or reflect most of it. The presence or absence of pigment production is determined by adaptive mechanisms. Based on these patterns in the spectral characteristics and optical properties of the diseases, a classification model was developed with 94% overall accuracy. Random Forest proved to be the most effective method for the automated detection of wheat phytopathogens using hyperspectral data. The practical significance of this research lies in the potential integration of the developed phytopathology detection approach into precision agriculture systems and the use of UAV platforms, enabling rapid large-scale crop monitoring for the timely detection. The study’s results confirm the promising potential of combining hyperspectral technologies and machine learning methods for monitoring the phytosanitary condition of crops. Our findings contribute to the advancement of digital agriculture and are particularly valuable for the agro-industrial sector of Central Asia, where adopting precision farming technologies is a strategic priority given the climatic risks and export-oriented nature of grain production. Full article

This study investigates the changes and driving mechanisms of agritourism landscapes in mountainous regions of Southwest China, providing a scientific basis for sustainable landscape management. We analyzed Hanyuan County (2013–2023) using remote images, POI data, terrain niche index, distribution index, landscape transition matrix, and logistic regression model from a landscape function perspective. These analyses reveal that the landscape pattern maintains overall stability with local fluctuations, with ecologically oriented landscapes being consistently dominant (>76% coverage). The primary conversion direction of development-potential landscapes shifted from ecological to agricultural dominance after 2018. All landscape types have shown more distinct distribution advantages in the fifth-level terrain gradient, with intensified fluctuations in low-gradient areas after 2018. Location factors were the most common driving force, but their effects differ: production-oriented landscapes shifted from location–climate correlation to location–socioeconomic–terrain correlation; living-oriented landscapes remain influenced by slope and location accessibility; ecological-oriented landscapes shifted from a location–climate correlation to location–tourism correlation; development-potential landscapes were positively influenced by multiple factors. This study suggests implementing zoned management based on functions and terrain gradients through policy guidance and technological intervention. The findings of this study can provide a reference for the comprehensive revitalization of rural areas and the sustainable development of landscapes in similar areas. Full article

This study evaluated the physicochemical properties and sensory acceptance of third-generation, potato-based, extruded snacks enriched with mushroom powder (5% and 10%) across different European regions. The mushroom powder was produced from dried button mushrooms (Agaricus bisporus), ground and incorporated into the snack formulations, while control samples contained no mushroom powder. The investigation was conducted in Denmark, Poland, and Spain, involving 230 young adult consumers identified as the target demographic for this snack format. Incorporation of mushroom powder increased protein, fiber, ash, polyphenols, and antioxidant capacity while producing a darker color and crisper texture. Consumer acceptance varied across countries and was significantly influenced by individual differences in food involvement, neophobia, sustainability orientation, and dietary habits. Participants with greater health consciousness and sustainability engagement expressed a higher preference for snacks with greater levels of mushroom enrichment. Overall, moderate mushroom addition (5–10%) provides an optimal balance between enhanced nutritional quality, favorable sensory attributes, and broad consumer appeal, underscoring the potential of mushrooms as sustainable functional ingredients in snack product development. Full article

Drawing on panel data from 279 prefecture-level cities in China from 2011 to 2022, this study employs the National Pilot Policy of Information Benefiting the People (NPIB) as a quasi-natural experiment to examine how government-led digital governance shapes the digital divide among cities. Using a difference-in-differences (DID) design combined with mediation and spatial analyses, the results demonstrate that the NPIB policy significantly narrowed inter-city digital disparities, with findings robust across alternative model specifications and placebo tests. Mechanism analysis shows that digital governance promotes inclusion primarily through three pathways: strengthening strategic policy orientation, enhancing technological innovation capacity, and stimulating digital market vitality. Heterogeneity analysis indicates that policy effects vary by regional development, urbanization level, and fiscal autonomy, being most pronounced in eastern cities and those with moderate urbanization and fiscal self-sufficiency. Spatial analysis reveals that while digital governance improves local inclusion, it can generate negative spillovers among neighboring cities with similar economic structures, partially offsetting aggregate gains. Overall, the findings highlight the importance of regionally differentiated strategies, cross-regional coordination, and sustained investment in digital infrastructure to promote balanced, inclusive, and sustainable digital transformation—providing practical insights for developing countries aiming to bridge structural divides and advance digital sustainability. Full article

Global restrictions related to climate change and the increasing demand for electricity are accelerating the transition from conventional energy sources, such as oil, gas, and coal, to renewable options like wind, solar, and biomass. Among these, solar photovoltaic (PV) systems are highly promising, offering clean and reliable electricity generation. In support of the Maldives’ target to achieve net-zero emissions by 2030, the deployment of PV systems has significantly increased. However, there is still a lack of detailed operational performance assessment specific to the Maldives. This study aims to address this gap and fulfill three main objectives. Firstly, to evaluate the real performance of six selected rooftop grid-connected PV systems installed in the Greater Malé region, Maldives. Secondly, the ideal performance ignoring shading, soiling, and aging effects of the selected systems on the islands are simulated, and the optimal orientation angles are estimated. Finally, the real and predicted performances are compared, and a module-level analysis is conducted to pinpoint the area for improving the performance of the rooftop PV systems installed on the island. The well-known International Electro-Technical Commission (IEC) standard, IEC 61724, is used for operational performance assessment, in addition, the PVsyst simulation tool and the S-Miles microinverters monitoring system are implemented for simulation and module-level analysis, respectively. In 2023, the six studied sites recorded annual daily averages of 2.52–4.45 kWh/kWp/day for yield factor, 0.98–2.9 h/day for total loss, 45.19–82.13% for performance ratio (PR), 10.51–18.55% for capacity utilization factor (CUF), and 7.69–15.94% for system efficiency. The actual performance was found to be lower than the simulated ideal values. The main reasons for this reduction were near-shading and microinverter connection issues. The orientation study showed that a 5° tilt angle with an azimuth between −25° and 5° gives the best results for fixed PV installations. These findings can guide better PV system design and operation in the Maldives and other similar climates. Full article

From the perspective of environmental history, which examines the interplay between socio-economic development and the natural environment, this paper discusses the evolution of Japanese landscapes. These landscapes evolved in somewhat different ways, absorbing influences from China and the West. Following the country’s opening up in the late 19th century, various forest management techniques were introduced from Europe and America. This paper examines the environmental history of the changes to the landscape that accompanied rapid Westernisation and the guidance provided by “Forest aesthetics” in forest operations—a crucial element of the landscape. Proposed by H. von Salisch, forest aesthetics is a forest management philosophy that provided guidelines for sustainability before the concept of ecosystems emerged. Although Japan is a small nation comprising elongated islands, mountains cover 67% of its land area. Its north-south orientation means that each region has unique forests and ways of life. This overview examines historical information concerning the formation of gardens and artificial forests, landscape transformations, and perceptions of forests across different eras. Using primarily secondary sources dating from around the 11th century, it demonstrates that, even in Japan, which is subject to natural disturbances under a monsoon climate, the sustainability of gardens and forests could be achieved by emulating the nature advocated for by forest aesthetics as closely as possible. This approach also considered hunting. Full article

The seismic design of aluminum alloy structures requires specific attention due to the material’s distinct mechanical properties compared to steel, which renders direct application of steel joint design methods inappropriate. This study investigates the seismic behavior of T-shaped aluminum alloy beam–column bolted connections, which consist of 6061-T6 aluminum alloy beams and columns connected by S304 stainless steel connectors via high-strength bolts. A finite element model, incorporating a mixed hardening constitutive model for accurate cyclic response, is established and validated against low-cycle cyclic loading tests. Parametric analyses evaluated the influence of L-shaped connector dimensions on hysteresis response, skeleton curves, stiffness degradation, energy dissipation, and ductility. Results demonstrate that increasing the thickness of the short leg of the L-shaped connector between the beam flange and column flange significantly enhances the ultimate bending moment, with an increase of up to 36.7% per 2 mm increment, alongside improved energy dissipation and ductility. Stiffness degradation follows a natural exponential decay, with residual stiffness between 23.85% and 32.57% at ultimate deformation. An efficiency analysis identifies the most cost-effective measures for seismic design. The primary novelty of this work lies in the successful application and validation of a mixed hardening model for simulating the complex cyclic behavior of T-shaped aluminum alloy connections, coupled with a systematic efficiency-oriented parametric study. The findings offer practical, quantitative guidelines for designing aluminum alloy bolted connections in seismic-prone regions. Full article

Optimizing irrigation strategies to simultaneously enhance crop yield and fruit quality under water scarcity is a critical challenge for sustainable agriculture. This study addresses this challenge by developing a novel fuzzy credibility-constrained fuzzy multi-objective programming (FCC-FMOP) model for irrigation planning under uncertainty. The model incorporates stochastic hydrologic factors, decision-maker preferences, and complex interrelationships among fruit quality attributes and market dynamics. Applied to a citrus-producing region in Southwest China prone to seasonal drought, the approach demonstrates its capability to reconcile multiple objectives under fuzzy constraints. The key findings include the following: (1) The IVIF-TOPSIS analysis quantitatively revealed that yield was the paramount objective for decision-makers in the study region, followed by single fruit weight, highlighting the economic drivers that must be balanced with qualitative metrics. (2) The FCC-FMOP model effectively balances yield and quality objectives while adapting to real-world fuzzy constraints, proving to be both robust and practical. (3) Compared with conventional practices, the proposed irrigation strategy—calibrated under varying credibility levels (β = 0.55, 0.75, and 0.95)—significantly improves yield, fruit weight, hue angle, water content, and soluble sugar content. Performance evaluation using synthetic degree (SD), the sustainability index (SI), and approximation degree (AD) confirmed the model’s superiority over single-objective models and conventional practices. The FCC-FMOP model provides a scalable and decision-maker-oriented tool for sustainable irrigation management in water-limited environments. Full article