bluuebunny/crossref_metadata_2025 huggingface dataset:
Review of the Chinese Aluminum Industry’s Low-Carbon Development Driven by Carbon Tariffs: Challenges and Strategic Responses
Authors: Hou Tianshu , Zhang Lei , Yuan Yuxing , Yang Yuhang , Na Hongming
Published: December 2024

Carbon tariffs are designed to prevent carbon leakage and encourage global industries to adopt low-carbon practices, which present significant challenges for China’s aluminum industry. A critical issue for China’s aluminum sector is how to effectively reduce carbon emissions while maintaining competitiveness in the face of increasingly strict carbon regulations. This review is based on an extensive examination of high-quality, authoritative research literature, industry data, and policy reports. Accurate data have been systematically summarized, and key findings from reputable studies have been extracted to support the perspectives presented in this review. On this basis, this review systematically analyzes the current status of China’s aluminum industry, emphasizing its reliance on fossil fuels, slow transition to low-carbon technologies, and the inadequate use of recycled aluminum. The potential impacts of carbon tariffs are assessed, highlighting increased carbon costs, reduced production scales, and diminished market competitiveness in foreign markets. To address these challenges, the study proposes several pathways for carbon reduction in China’s aluminum industry, including accelerating the adoption of recycled aluminum, enhancing energy efficiency, advancing low-carbon innovations, and developing supportive policy frameworks. Implementing these measures is vital for decreasing carbon emissions and ensuring the long-term sustainability of the industry amid global climate initiatives.
Segregating Laterals for Efficient Gas Re-Injection in Shale Plays Using Smart Completion
Authors: Aoun Ala Eddine , Ben Ameur Mohamed Cherif , Khetib Youcef , Ruiz Nelson G. , Masadeh Mohammad
Published: December 2024

There is a strong global demand for oil and gas resources, and forecasts indicate robust growth in oil demand in the coming years. Meeting this demand necessitates the exploitation of unconventional resources and enhancing the recovery of existing oil and gas fields. Field trials indicate that traditional gas injection in shale wells has low sweeping efficiency. Emerging technologies play an exceedingly significant role in solving the challenges of gas EOR in shale and tight formations. Among these advancements, smart or intelligent well technology has emerged as a promising solution to enhance field development outcomes. This study focuses on improving gas flooding efficiency in the Bakken formation by utilizing smart completions to reduce the gas–oil ratio (GOR) and increase oil recovery. An economic assessment of gas re-injection is conducted, considering both gas storage and enhanced oil recovery, with analysis incorporating capital expenditures, operating costs, and revenue from increased production. Reservoir simulations were employed to determine the most effective gas injection scenarios for maximizing recovery and storage efficiency. Simulation results demonstrate that 20% of perforated laterals account for 80% of the injected gas. To address this challenge, this work proposes using smart completions to segregate lateral sections, thereby optimizing gas injection efficiency, and unlocking additional oil in tight formations. Segregating horizontal laterals for gas re-injection using smart completion technology can achieve gas injection efficiencies of up to 0.25 barrels per Mcf of gas injected, with lower incremental gas production. The optimal injection rate is between 1 MMcfd and 3 MMcfd, with an injection period ranging from one to three years. It was also found that injecting gas into the toe section results in high bottom hole pressure but lower oil recovery due to reduced gas injection efficiency. From an economic perspective, the project yielded favorable outcomes, with a positive net present value (NPV) at a 7% discount rate. Even at lower oil prices (USD 50 per barrel), the Internal Rate of Return (IRR) was calculated to be 170%, indicating strong potential profitability.
Nutritional Properties of Innovatively Prepared Plant-Based Vegan Snack
Authors: Barakat Hassan , Aljutaily Thamer , Khalifa Ibrahim , Almutairi Abdulkarim S. , Aljumayi Huda
Published: December 2024

This research examines the nutritional characteristics of novel-prepared plant-based vegan snacks (PVSs). The proximate composition, mineral content, amino and fatty acid profiles, volatile compounds, phytochemicals, antioxidant activity, and in vitro protein and carbohydrate digestion in prepared snacks were analyzed. The PVSs were mainly prepared by mixing blanched broccoli, pumpkin, chickpeas, whole oat flour, red sweet pepper, fresh onion and garlic, leafy vegetables, and mixed spices, then homogenated, shaped, and freeze-dried. Consequently, sensory evaluation was used to select the most favored PVS; PVS2 contains 25% broccoli and 25% chickpeas, which was the superior model of this study and was analyzed further. The moisture content, crude protein, crude fat, ash, crude fiber, and available carbohydrates were 74.80, 3.40, 28.18, 4.97, 7.86, 3.69, and 51.89 g 100 g−1 of PVS2 (containing 25% of either broccoli or chickpeas), respectively. The results showed that the highest mineral content in macro-elements was sodium, followed by potassium. The PVS2 formula provides 95.24 Kcal 100 g−1 and 54.28 mg 100 g−1 of vitamin C on fresh weight (fw). Consequently, TPC, TCs, TF, TFL, and AOA exhibited valuable content. The HPLC analysis revealed that fifteen phenolics were quantified, with predomination of chlorogenic acid (1741.60 μg g−1), phenolic acid, and naringenin (302.38 μg g−1) as flavonoids, as well as Daidzein (22.27 μg g−1) as an isoflavone. The GC-MS quantification of volatiles exhibited more components; at least 37 displayed concentrations higher than 0.1%. The predominant volatile was cis-13-octadecenoic acid. The percentage of essential amino acids (EAAs) was 25%, and the percentage of non-essential amino acids (NEAAs) was 75%. Among the EAAs and NEAAs, phenylalanine and glutamic acid were the highest, respectively. The fatty acids (FAs) profile exhibited that saturated fatty acids (SFA) and unsaturated fatty acids (USFA) were 20.2% and 79.2%, respectively. The predominant FA in PVS2 was cis-11,14,17-Eicosatrienoic acid, with a percentage of 37.13%, followed by cis-8,11,14-Eicosatrienoic acid, with a percentage of 36.02%. Omega-3 fatty acids reached 39.04%, followed by omega-6 fatty acids at 38.95%. The degree of protein degradation values for the sample was 292.09 mg NH3 g−1 before digestion and increased to 2106.77 mg NH3 g−1 after enzymatic digestion. The glycemic index (GI) of PVS2 was estimated to be 21.12, slightly higher than individual vegetables’ GI. Finally, a prepared PVS may be advantageous for recommending the enhancement and further development of diverse snacks to satisfy the nutritional needs of healthy persons and patients across various age demographics.
Hierarchical Power System Scheduling and Energy Storage Planning Method Considering Heavy Load Rate
Authors: Lu Qiuyu , Xie Pingping , Lin Yingming , Liu Yang , Yang Yinguo , Lin Xu
Published: December 2024

With the rise in the proportion of renewable energy and energy storage in modern power systems, the volatility of renewable energy and the increasing demand for loads pose a significant risk of congestion in transmission lines. Along with transmission congestion, prolonged heavy loads on transmission lines increase equipment failure rates, leading to a range of issues within the power system. This study proposes a scene clustering method for power system scheduling by leveraging the net load related with the load and renewable energy power outputs. Subsequently, a scheduling model and line load evaluation indexes were developed to analyze the line load rate of power systems with different renewable energy proportions. The simulation results indicate that the utilization rate of lines, the fluctuation rate of line load, the maximum line load, and heavy line load time increase as the installed proportion of renewable energy increases. Finally, a penalty term for heavy loads was incorporated into the objective function and methods of rescheduling and planning energy storage considering the heavy load penalty function are proposed. A case study validated the significant improvements in load management, achieving a reduction in heavy load time by approximately 30% and reducing transmission congestion by 20% under high-renewable-energy-penetration scenarios. These results illustrate the effectiveness of the heavy load cost function in enhancing system resilience and optimizing load distribution.
From Existence to Being: Reflections on the Transformation of Personal Identity Through Confrontation with Cultural, Religious, and Spiritual Diversity
Authors: Dojčár Martin , Nemec Rastislav
Published: December 2024

(1) Background: This study describes an exploration of the potential of cultural, religious, and spiritual diversity to trigger one’s psychological self-image and open the possibility of personal identity transformation as a tool for deep intercultural, interreligious, and interspiritual dialog (2) Results: The study provides a philosophical argument for understanding the existential experience of the “unknown” as a stimulus for critical reflection or even for the transformation of personal identity of the individuals involved in such interactions. (3) Methods: The method of phenomenological analysis was employed in this theoretical research. (4) Conclusions: The circumstances were philosophically considered under which the existential experience of the unknown in intercultural, interreligious, and interspiritual contexts can facilitate processes of critical reflection or the transformation of personal identity based on the philosophical distinction between ontic and ontological identity.
Insights Gained from the Review of Landslide Susceptibility Assessment Studies in Italy
Authors: Segoni Samuele , Ajin Rajendran Shobha , Nocentini Nicola , Fanti Riccardo
Published: December 2024

We conducted a systematic literature review of 105 landslide susceptibility studies in Italy from 1980 to 2023, retrieved from the Scopus database. We discovered that Italian researchers primarily focus on rainfall-induced landslides (86.67% of the articles), especially shallow and fast movements (60%), with 72% of studies conducted at the local scale, while regional and national-level studies are rare. The most common data sources include remote sensing images validated by field surveys and official data portals at the national or regional level. Data splitting usually follows a 70:30 ratio and 24 modelling techniques were identified, with logistic regression being historically prevalent, although machine learning methods have rapidly gained popularity. Italian studies used 97 predisposing factors, with slope angle (98.09%), lithology (89.52%), land use/land cover (78.09%), and aspect (77.14%) being the most employed. This review also identifies and discusses a few less-used factors, like soil sealing, rainfall, NDVI, and proximity to faults, which showed promising results in experimental studies. Predisposing factors are generally selected by expert judgment, but methods for forward factors selection and collinearity tests are becoming more common. This review synthesizes current knowledge, pinpointing gaps, highlighting emerging methodologies, and suggesting future research directions for better integration of susceptibility studies with landslide risk management.
A Multi-Source Data-Driven Analysis of Building Functional Classification and Its Relationship with Population Distribution
Authors: Ren Dongfeng , Qiu Xin , An Zehua
Published: December 2024

Buildings, as key factors influencing population distribution, have various functional attributes. Existing research mainly focuses on the relationship between land functions and population distribution at the macro scale, while neglecting the finer-grained, micro-scale impact of building functionality on population distribution. To address this issue, this study integrates multi-source geospatial and spatio-temporal big data and employs the XGBoost algorithm to classify buildings into five functional categories: residential, commercial, industrial, public service, and landscape. The proposed model innovatively incorporates texture, geometric, and temporal features of building images, as well as socio-economic characteristics extracted using the distance decay algorithm. The results yield the following conclusions: (1) The proposed method achieves an overall classification accuracy of 0.77, which is 0.12 higher than that of the random forest-based approach. (2) The introduction of time features and the distance decay method further improved the model performance, increasing the accuracy by 0.04 and 0.03, respectively. (3) The correlation between the building functions and population distribution varies significantly across different scales. At the district and county levels, residential, commercial, and industrial buildings show a strong correlation with population distribution, whereas this correlation is relatively weak at the street scale. This study advances the understanding of building functions and their role in shaping population distribution, providing a robust framework for urban planning and population modeling.
Monitoring Anthropogenically Disturbed Parcels with Soil Erosion Dynamics Change Based on an Improved SegFormer
Authors: Li Zhenqiang , Li Jialin , Li Jie , Li Zhangxuan , Jiang Kuncheng , Ma Yuyang , Hu Chuli
Published: December 2024

Amidst burgeoning socioeconomic development, anthropogenic activities have exacerbated soil erosion. This erosion, characterized by its brief duration, high frequency, and considerable environmental degradation, presents a major challenge to ecological systems. Therefore, it is imperative to regulate and remediate erosion–prone, anthropogenically disturbed parcels, with dynamic change detection (CD) playing a crucial role in enhancing management efficiency. Currently, traditional methods for change detection, such as field surveys and visual interpretation, suffer from time inefficiencies, complexity, and high resource consumption. Meanwhile, despite advancements in remote sensing technology that have improved the temporal and spatial resolution of images, the complexity and heterogeneity of terrestrial cover types continue to limit large–scale dynamic monitoring of anthropogenically disturbed soil erosion parcels (ADPSE) using remote sensing techniques. To address this, we propose a novel ISegFormer model, which integrates the SegFormer network with a pseudo–residual multilayer perceptron (PR–MLP), cross–scale boundary constraint module (CSBC), and multiscale feature fusion module (MSFF). The PR–MLP module improves feature extraction by capturing spatial contextual information, while the CSBC module enhances boundary prediction through high– and low–level semantic guidance. The MSFF module fuses multiscale features with attention mechanisms, boosting segmentation precision for diverse change types. Model performance is evaluated using metrics, such as precision, recall, F1–score, intersection over union (IOU), and mean intersection over union (mIOU). The results demonstrate that our improved model performs exceptionally well in dynamic monitoring tasks for ADPSE. Compared to five other models, our model achieved an mIOU of 72.34% and a Macro–F1 score of 83.55% across twelve types of ADPSE changes, surpassing the other models by 1.52–2.48% in mIOU and 2.25–3.64% in Macro–F1 score. This work provides a theoretical and methodological foundation for policy–making in soil and water conservation departments.
Spatiotemporal Characteristics and Influencing Factors of PM2.5 Levels in Lianyungang: Insights from a Multidimensional Analysis
Authors: Li Xue , He Haihong , Wang Dewei , Qiao Wenli , Liu Chunli , Sun Yiming , Li Lulu , Han Shuting , Zha Guozhen
Published: December 2024

The rapid industrialization and urbanization in China have exacerbated air pollution, particularly PM2.5, posing significant threats to public health. This study focused on Lianyungang, an industrial city, to analyze the spatiotemporal variations in PM2.5 concentrations from 2000 to 2023 and identify the influencing factors. Utilizing high-resolution PM2.5 data from the ChinaHighPM2.5 dataset and ERA5 meteorological data, the study employed Empirical Orthogonal Function (EOF) analysis to capture spatial variability and the Bayesian Estimator of Abrupt Change Seasonal and Trend (BEAST) to assess long-term trends and abrupt changes. The key findings include a marked seasonal pattern, with higher PM2.5 levels during the winter months and lower concentrations in the summer, primarily driven by temperature, humidity, and precipitation. A significant decline in PM2.5 levels was observed after 2014, following the implementation of pollution control measures. The study underscores the importance of continued environmental regulation and green technology adoption in mitigating air pollution in rapidly industrializing cities. This research provides a comprehensive analysis of PM2.5 trends and highlights the critical role of natural and human factors, contributing valuable insights for policymakers and researchers aiming to improve air quality.
Children’s Individual Differences in the Responses to a New Method for Physical Education
Authors: Pereira Sara , Santos Carla , Maia José , Vasconcelos Olga , Guimarães Eduardo , Garganta Rui , Farias Cláudio , Barreira Tiago V. , Tani Go , Katzmarzyk Peter T. , Garbeloto Fernando
Published: December 2024

Children’s fundamental movement skills (FMS) require planned and guided interventions to develop appropriately. We investigated the effect of a novel Physical Education (PE) method to develop children’s object control, locomotor skills, and motor competence. Further, we examined children’s trainability, i.e., their differential responses to the new method, and identified low and high responders to the intervention. The study lasted three months and included six to seven-year-old children in two groups: control (the current, official PE program; n = 38) and experimental (the new method; n = 52). Twelve FMS [object control (OC), locomotor (LO)] were reliably assessed using the Meu Educativo® app. Using a mixed-effects model, results showed that the experimental group experienced greater changes (p < 0.05) than the control group in OC and LO. Positive individual changes were more frequent with the new method, but children showed a similar pattern in their interindividual variability in both methods. There was a greater reduction in the number of children with lower proficiency in the experimental group. In sum, the new PE method proved superior to the current, official one. Individual responses to the new method showed considerable variation, highlighting the need for personalization in teaching strategies and necessary support for children with lower proficiency levels, ensuring that no child is left behind in their motor development process.
The Effect of Intraset Rest Periods on External and Internal Load During Small-Sided Games in Soccer
Authors: Ispirlidis Ioannis , Pantazis Dimitrios , Poulios Athanasios , Avloniti Alexandra , Stampoulis Theodoros , Michailidis Yiannis , Troupkos Konstantinos , Evangelou Evangelos , Draganidis Dimitrios , Balampanos Dimitrios , Retzepis Nikolaos-Orestis , Protopapa Maria , Mantzouranis Nikolaos , Zaras Nikolaos , Michalopoulou Maria , Fatouros Ioannis G. , Chatzinikolaou Athanasios
Published: December 2024

The purpose of this study was to compare the internal and external load in continuous and intermittent small-sided games (SSG) formats. Eight semi-professional soccer players participated in the study, and they completed three protocols: (a) I-intermittent SSG protocol (Int-I, 4 sets of 4 min with a 3 min recovery); (b) Continuous SSG protocol (Con, 2 sets of 8 min with a 3 min recovery); (c) II-SSG protocol (Int-II, 4 sets of 4 min, where each set includes 1 min of exercise with varying recovery periods (10, 20, 30 s), with a 3 min recovery period between sets). A one-way analysis of variance (ANOVA) was used to analyze the dependent variables, with significance determined at p < 0.05. The three protocols differed in total distance covered and in distance covered at speeds >19 km/h, with the Int-II protocol resulting in the greatest distance covered (p < 0.05). Additionally, players in the Con protocol exercised at a higher percentage of their maximum heart rate (%HRmax) (p < 0.05), while the highest RPE value was observed in the Int-I interval protocol (p < 0.05). The external load experienced by players in intermittent SSG protocols is higher, while internal load (%HRmax) remains relatively low. This effect is especially notable in the new intermittent exercise model proposed in this study, which incorporates progressively increasing recovery times within each exercise set. Coaches can use this model to increase players’ external load without causing a heightened perception of fatigue.
Traditional Fish Hole Aquaculture System in Benin: Status, Challenges, and Research Prospects for Sustainable Development in Climate Change Mitigation
Authors: Dagoudo Missinhoun , Adjahouinou Dogbè Clément , Tossavi Nounagnon Darius , Amegnaglo Cocou Jaurès , Nzau Matondo Billy , Ovidio Michaël , Montchowui Elie
Published: December 2024

Fish holes called “whédos” are excavations performed near water bodies or in the flood plains of Beninese rivers in Africa for rearing fish. During floods, they are filled and naturally colonized by various fish that remain trapped during recessions. This literature review examines fishing, aquaculture, and fish reared in traditional holes in Benin. It reports on cartography, characterization, socioeconomic aspects, challenges, and status of improvement, and proposes prospects for improving this system. Peer reviews and gray literature were used to conduct the analysis. Our review highlights 19 papers reporting on 17 whédos aquaculture experiences based on the exclusion or inclusion criteria. These results indicate that many genera can be reared in whédos, suggesting that whédos offer the possibility of going beyond the production of Clarias and Tilapia in Africa. Furthermore, the exploitation of the whédos system is fairly profitable for fishermen and their households, at approximately US$ 1713 per household annually, used to finance agricultural activities, children’s education, schooling, mitigating farmers’ vulnerability to climate risks, and health care. However, in the past two decades, there has been a significant decline in the quantity of fish collected owing to the adverse effects of hydroclimatic changes, such as floods and prolonged droughts. Moreover, water eutrophication or pollution, the risk of climate change, and fishing methods have affected crop yield over the years. The implementation of Integrated Multi-Trophic Aquaculture or Integration Agriculture-Aquaculture in whédos systems can be an effective solution for improving profitability and sustainability. The knowledge gained from this review perspective should be helpful in directing future initiatives to grow and sustain this sector of the economy and to optimize its potential to provide food for future generations.
Quantifying the Effects of Wind Turbulence on CO2 Flux Measurement in a Closed Chamber
Authors: Wu Zhiwei , Hu Junguo , Feng Lingxia , Jiang Junjie , Li Guangliang
Published: December 2024

This study aimed to investigate the effects of wind turbulence on CO2 transport within a medium and the extent of measurement errors in a closed chamber. Therefore, in a laboratory with controllable environmental conditions, the measurement performance of the closed chamber at various wind speeds was assessed using a soil respiration calibration apparatus and four types of porous media. The experimental results indicated that the closed chamber under the influence of wind turbulence exhibited varying degrees of underestimation, ranging from −51 to −6%. The effects of wind turbulence were more pronounced in sandy soils. As wind turbulence enhanced gas transport within the medium, the flux measurements of the closed chamber were biased, and this phenomenon was closely related to the medium’s particle size and surface wind speed. To address this issue, it is recommended to conduct long-term monitoring and eliminate errors by averaging repeated measurements, which will improve the accuracy of the ecosystem carbon budget.
Minimal Defect Detection on End Face of Lithium Battery Shells
Authors: Xing Yufeng , Liu Qi , Xing Yuanxiu , Liu Zhuanwei , Wang Wenbo
Published: December 2024

Lithium batteries represent a pivotal technology in the advancement of renewable energy, and their enhanced performance and safety are vital to the attainment of sustainable development goals. To solve the issue of the high missed detection rate of minimal defects on end face of lithium battery shells, a novel YOLO-based Minimal Defect Detection algorithm, named YOLO-MDD, is proposed. Firstly, aimed at the problem of insufficient data, a dataset of defects on the end face of lithium battery shells is constructed and annotated. Secondly, a YOLO-MDD network which includes a feature extraction module and a four-scale detection head for detecting defects of various scales is improved. Here, deformable convolution and an attention module are ingeniously embedded into the backbone of YOLO to capture more detailed and accurate information on object defects, and the four-scale head is used to handle the significant differences in the size and shape of defects on lithium battery shells. Finally, a hybrid loss including localization loss with normalized Wasserstein distance (NWD), classification loss, and confidence loss is designed to optimize our model to further enhance its sensitivity to minimal defects. The experimental results show that the proposed YOLO-MDD has a mean average precision of 80% for the defect detection of the lithium battery shells, especially with a minimal defect rust spots mean average precision of 74.1% and a recall rate of 71.5%, which is superior compared with other mainstream detection algorithms and provides the technical support necessary to achieve the goals of energy and environmental sustainability.
Cooperative Innovation Under the “Belt and Road Initiative” for Reducing Carbon Emissions: An Estimation Based on the Spatial Difference-in-Differences Model
Authors: Zhang Kaicheng , Liu Kai , Huang Caihong
Published: December 2024

The Belt and Road Initiative holds significant importance for achieving the United Nations’ Sustainable Development Goals, particularly Goals 9 and 17. Drawing on data from the Web of Science database, the BRI database, and the World Bank database, this study explores the potential carbon emission reduction effects that cooperative innovations may bring to participating countries under the Belt and Road Initiative. The study constructs variable endogenous spatio-temporal weight matrices based on initial spatial weight matrices and, drawing on trends in co-authored publications, innovatively establishes time dummy variables and event dummy variables in a difference-in-differences (DID) model. This approach fully considers the interconnected, shared model of the Belt and Road Initiative and the spatial effects of policy implementation. A spatial DID model was established for 106 BRI participating countries and regions from 2005 to 2021. The results reveal the following: first, cooperative innovation under the BRI significantly reduces carbon emission intensity in participating countries. Second, the BRI primarily achieves carbon reduction through investment, innovation, and trade mechanisms. Third, the results of the global SDID model indicate that cooperative innovation with China negatively impacts carbon emission intensity. Also, this effect exhibits spatial spillover, suggesting that there is a policy spillover effect. Fourth, the decomposition of local policy shock effects indicates that the influences of cooperative innovation exhibit spatial heterogeneity, with varying degrees of direct and indirect effects on carbon emission intensity across different countries.
Designing Care Spaces in Urban Areas
Authors: Ozga Agnieszka , Frankiewicz Przemysław , Frankowska Natalia , Gibała-Kapecka Beata , Kapecki Tomasz
Published: December 2024

This paper presents a novel approach to sustainable urban revitalization. Care Spaces are defined, and an area selected for revitalization is described. Transformation of city space is of fundamental importance for everyday life, its comfort as regards the functional aspect as well as the psychological and cultural ones. The presented projects are in accord with 2030 Agenda for Sustainable Development and the conception of Baukultur. Both approaches tend to create well designed environment that support health and well-being of people and other living creatures while taking into account cultural aspects in design and construction. Focusing on the combination of soundscape analysis with design elements. To monitor the soundscape, a custom database of urban sound recordings was constructed, and key analytical methods such as Mel-Frequency Cepstral Coefficients (MFCC), feature extraction, Recurrent Neural Networks (RNN), and permutation of feature importance were applied. The effectiveness of these algorithms was confirmed through field investigations.
A Fuzzy Multi-Criteria Decision-Making Approach for Agricultural Land Selection
Authors: Tuncel Gonca , Gunturk Busranur
Published: December 2024

Decision-making involves selecting the best alternative based on evaluation criteria while considering environmental impacts. The translation of environmental factors into quantifiable mathematical expressions is challenging due to the inherent uncertainties. Decision-makers can address the subjective characteristics of alternatives by incorporating fuzzy set theory into decision-making processes where uncertainty and ambiguity exist. Game theory is introduced as another approach to enhance the robustness of decision-making models, leading to more informed and flexible decision outcomes. This approach promotes strategic thinking and aids decision-making by allowing individuals to visualize the potential consequences of different decisions under various conditions. This study proposes a fuzzy multi-criteria decision support system that provides a structured framework to address the complexities of agricultural land selection. The decision support system employs a two-person zero-sum game to identify the optimal land management option, considering the strategic interactions between players. The results from the payoff matrix reveal the equilibrium point, providing an ideal solution for more effective land use planning decisions.
Comparative Analysis on Policy Frameworks of High-Altitude Mineral Resource Management: Implications for Sustainable Development Goals (SDGs)
Authors: Liu Jing , Liu Chonghao , Zhao Jianan , Jia Xiangying
Published: December 2024

As the global demand for minerals critical to clean energy and technological innovation continues to rise, the sustainable exploitation of mineral resources in high-altitude regions becomes increasingly essential for global sustainable development. Employing SWOT analysis, deep learning, and heatmap techniques, this study delves into the mineral resource policies of China, the United States, Canada, and Chile, assessing their alignment with and impact on Sustainable Development Goals (SDGs). Despite distinct policy frameworks, a shared focus on technological innovation and environmental sustainability is evident. China’s strategic resource allocation and stringent regulations drive a green, low-carbon shift, aligning with SDG 13 (Climate Action). The United States fosters SDG 9 (Industry, Innovation, and Infrastructure) through market-driven technological advancements. Canada’s collaborative approach, emphasizing indigenous rights, underpins SDG 8 (Decent Work and Economic Growth) and SDG 12 (Responsible Consumption and Production). Chile’s national governance and international collaboration mix bolsters the mining industry’s efficiency and sustainability, supporting SDG 7 (Affordable and Clean Energy). The study underscores a trend toward sustainable practices in mineral resource management and stresses the critical need for international cooperation. The study advocates for global collaboration and sharing of green mining technologies to accelerate the industry’s transition to a sustainable and responsible future and boost SDG achievements worldwide.
Sustainable Passenger Services and Child-Friendly Airport Experience: A Case Study of Istanbul Airport
Authors: Yazgan Bahar , Dogan Ozcan , Bakır Mahmut , Gun Devrim
Published: December 2024

This study explores the concept of child-friendly airports, using Istanbul Airport as a case study to understand how such environments can enhance the travel experience for families with children. Through qualitative research methods, including focus group discussion and in-depth interviews with 12 mothers and 12 field specialists, the research identified key attributes that constitute a child-friendly airport. Building upon the Place Diagram model, the results revealed that a child-friendly airport should prioritize sociability, comfort and image, uses and activities, and access and linkages, aligning with the model’s core themes. The results further identified numerous sub-themes linked to these four themes. Accordingly, airports should offer diverse play areas, family-friendly seating, efficient wayfinding, and high-quality, sustainable materials to create a safe, inclusive, and engaging environment for passengers with children. The study emphasizes the importance of designing airports that cater to the needs of children and their families, contributing to social equity and enhancing the overall passenger experience. These insights can serve as a benchmark for other airports aiming to improve their service offerings for families, supporting sustainable development goals related to reducing inequalities and promoting inclusive, safe, resilient, and sustainable environments. This study represents the first academic attempt focusing specifically on comprehensive services for passengers with children and the broader concept of child-friendly airports.
Optimizing Light Intensity and Salinity for Sustainable Kale (Brassica oleracea) Production and Potential Application in Marine Aquaponics
Authors: Pascual Christopher , Xiang Lirong , Hernandez Ricardo , Hall Steven
Published: December 2024

With rising populations and increasing food consumption, the demand for food is placing significant strain on freshwater resources. Exploring crops that can thrive under saline conditions is crucial to ensuring food security. Although brackish and seawater is abundant, it is generally unsuitable for irrigation. However, some plants exhibit tolerance to moderate levels of salinity. This study investigated the effects of varying light intensities (150 and 250 photosynthetic photon flux densities) and salinity levels (<1.5, 5, 10, and 17 parts per thousand, equivalent to <26, 86, 171, and 291 millimolars) on the growth and nutrient composition of Russian kale (Brassica oleracea) grown in indoor hydroponics. The experiment was conducted over five months, from September 2023 to January 2024. The results revealed that a light intensity of 250 PPFD and salinity levels of <1.5–5 ppt (<26–86 mM) were optimal for maximizing the biomass yield of the kale, whereas a significant reduction in the yield was observed at salinity levels exceeding 10 ppt (171 mM). In contrast, the dry matter percentage was significantly higher at 17 ppt (291 mM). The macronutrient contents, particularly the total Kjeldahl nitrogen (TKN), total phosphorus (TP), and magnesium (Mg), were consistent across both light intensities (150–250 PPFDs) and at salinity levels between <1.5 and 10 ppt (<26–171 mM) but were reduced at 17 ppt (291 mM). The micronutrient concentrations, such as those of copper (Cu), iron (Fe), and zinc (Zn), were higher at the lower light intensity (150 PPFD) across the salinity levels. These findings suggest that optimizing the light conditions is essential for enhancing the nutritional value of kale in saline environments. These outcomes are particularly vital for improving agricultural productivity and resilience in salt-affected regions, thereby supporting broader food security and sustainability goals.
Organizational Resilience Opacity in the Prism of Circular Strategy—Metal Industry Manufacturing Practice
Authors: Zapłata Sławomir , Muradin Magdalena , Feliczek Patryk , Banach Joanna Katarzyna , Sieciński Kacper
Published: December 2024

This study investigates the impact of circular economy (CE) strategies on organizational resilience (OR) within the metal industry, focusing on a case study of a forging department in a large manufacturing company. The idea of the paper is to link the macroeconomic topic of circular economy (CE) with microeconomic and practical activities in the organization, exploring how CE principles can improve resource efficiency, sustainability, and organizational resilience. A systematic literature review and case study methodology were used to assess the relationship between CE and OR. The findings reveal that companies with higher circularity demonstrate better resilience, both in normal operations and during crises. Specifically, in the case study, the closure of the forging department, following a detailed analysis using the Inputs–Mediators–Outputs (IMO) model, emerged as the most sustainable option, yielding financial, environmental, and operational benefits. This decision aligned with the company’s long-term goals of energy efficiency and carbon neutrality. The research highlights the significance of integrating CE strategies with business processes to not only achieve sustainability but also to build a more adaptable and resilient organization. Future research should explore broader applications of this framework across different industries to strengthen the links between circular economy practices and organizational resilience.
Impact of Green Finance on Regional Green Innovation Performance
Authors: Jin Xin , Chen Chunwu , Li Yuanheng , Yu Yinan
Published: December 2024

Green finance (GF) is a new financial service that supports green and low-carbon (GLC) transformation. Whether green finance (GF) can effectively improve regional green innovation performance (GIP) by optimizing resource allocation and increasing factor input is a key question for achieving sustainable development goals (SDGs): environmental, economic, and society. Based on panel data from 30 provinces in China from 2007 to 2021, this paper explores the impact of GF on GIP and analyzes the mechanisms of the effect. The findings of this paper indicate that GF plays a significantly positive role in promoting regional GIP, increasing both quantity and quality. Heterogeneity analysis reveals that GF has a considerable incentive effect on carbon reduction technology, and the innovation incentive effect of GF is much greater in regions where the attention paid to the environment is high or there is a low natural endowment. Mechanism analysis reveals GF improves GIP by optimizing financial resource allocation and increasing R&D factor input. Therefore, this paper proposes the following suggestions: (1) The central government should improve the top-level design of the GF policy system and provide financial support for GLC transformation and the achievement of SDGs. (2) Local governments should explore diversified development paths for GF according to their own characteristics, stimulate market entities’ enthusiasm for GLC transformation, and improve regional green innovation performance so as to achieve coordinated and sustainable development of the environment, economy, and society.
The Interaction and Sustainable Efficiency Between Tourism Systems and the Energy–Economy–Environment System: A Novel Parallel Network Super-Efficiency Slacks-Based Measure Model
Authors: Chen Zhijian , Zhao Jiqiang , Chen Xinqiang
Published: December 2024

Sustainable tourism entails balancing economic growth, environmental protection, and energy utilisation. However, the current interactive dynamics between urban agglomeration tourism systems and the energy–economy–environment (EEE) system, as well as the sustainable efficiency of the tourism–energy–economy–environment (TEEE) system, remain unclear. For the first time, this study employs a super-efficiency network slacks-based measure (SE-NSBM) model to interact with tourism and EEE systems, proposing a novel network structure that includes feedback variables. To validate the proposed model, this study evaluated the efficiency of the TEEE system and its subsystems in the Yangtze River Delta urban agglomeration (YRDUA) from 2016 to 2020. The study revealed significant variations in the efficiency of the TEEE, tourism, and EEE systems among cities in the YRDUA, with a discernible downward trend. The TEEE and tourism systems exhibit relatively weak coping capabilities when faced with significant unforeseen events, highlighting the urgent need to strengthen system resilience. The results also demonstrate that the new model effectively resolves the issue of efficiency overestimation in the TEEE system observed in traditional models, which tend to overestimate actual efficiency by 3%. The novel model and empirical results offer decision-makers new perspectives and practical insights into formulating sustainable tourism policies.
Fish Kills Related to Harmful Algal Bloom Events in Southeast Asia
Authors: San Diego-McGlone Maria Lourdes , Yñiguez Aletta T. , Benico Garry , Lum Wai Mun , Hii Kieng Soon , Leong Sandric Chee Yew , Leaw Chui Pin , Iwataki Mitsunori , Lim Po Teen
Published: December 2024

Fish kills in Southeast Asia are frequently associated with harmful algal blooms (HABs) and cause significant ecological and economic impacts and can have negative effects on the sustainability of aquatic ecosystems and the fisheries they support. This paper serves as a review of fish-kill events with focus on those related to HABs within the region. It examines the causative algal species, known mechanisms of fish mortality, and socio-economic consequences in order to better understand and manage this threat to sustainable fisheries. Fish kills have been reported across multiple countries within Southeast Asia, with notable hotspots in the Philippines, Malaysia, Singapore, Indonesia, and Thailand. The common harmful microalgal species span a diverse group including dinoflagellates (Karenia spp., Karlodinium spp., Margalefidinium polykrikoides, Noctiluca scintillans), raphidophytes (Chattonella spp.), diatoms (Skeletonema spp. and Chaetoceros spp.), and cyanobacteria (Trichodesmium spp.). These microalgae lead to fish kills through mechanisms such as hypoxia, physical gill damage, and ichthyotoxin production. Freshwater fish kills linked to HABs have also been documented for the Philippines, but there is no or limited information for the region. Our review highlights the widespread and recurring nature of fish kills, their impact on fisheries and aquaculture, and challenges in managing and mitigating their effects. There are efforts at enhancing management and mitigation using clay and early warning systems. However, it is essential to further improve monitoring efforts, the development and deployment of early warning systems, and viable and holistic mitigation strategies to protect the region’s aquatic resources and dependent communities, especially as aquaculture and coastal development are increasing concurrent with a changing climate that can exacerbate the risks of fish kills and HABs in Southeast Asia.
Towards Carbon Neutrality: Machine Learning Analysis of Vehicle Emissions in Canada
Authors: Guo Xiaoxu , Kou Ruibing , He Xiang
Published: December 2024

The transportation sector is a major contributor to carbon dioxide (CO2) emissions in Canada, making the accurate forecasting of CO2 emissions critical as part of the global push toward carbon neutrality. This study employs interpretable machine learning techniques to predict vehicle CO2 emissions in Canada from 1995 to 2022. Algorithms including K-Nearest Neighbors, Support Vector Regression, Gradient Boosting Machine, Decision Tree, Random Forest, and Lasso Regression were utilized. The Gradient Boosting Machine delivered the best performance, achieving the highest R-squared value (0.9973) and the lowest Root Mean Squared Error (3.3633). To enhance the model interpretability, the SHapley Additive exPlanations (SHAP) and Accumulated Local Effects methods were used to identify key contributing factors, including fuel consumption (city/highway), ethanol (E85), and diesel. These findings provide critical insights for policymakers, underscoring the need for promoting renewable energy, tightening fuel emission standards, and decoupling carbon emissions from economic growth to foster sustainable development. This study contributes to broader discussions on achieving carbon neutrality and the necessary transformations within the transportation sector.
Evaluation of the Performance and Sustainability of Historical Cultural Symbols in Xuzhou’s City Brand Based on Grey System Theory and Fuzzy Evaluation Method
Authors: Zhao Jiajia , Bao Qian , Wei Kaiqi , Jung Euitay
Published: December 2024

This study systematically evaluates ten historical cultural symbols in the brand image design of Xuzhou City based on Grey System Theory and Fuzzy Evaluation Method, revealing their significance and distinctions within city branding. First, Grey System Theory is applied to rank these symbols, establishing their prioritization in the brand design process. Subsequently, Fuzzy Evaluation Method is employed to perform a comprehensive analysis of each symbol across five dimensions: visual appeal, cultural heritage, brand recognizability, public acceptance, and sustainability. The Analytical Hierarchy Process (AHP) is used to set weights for each dimension, ensuring a scientific and reasonable evaluation. Results indicate that Xuzhou’s ancient city wall and the culture of Xiang Yu excel in visual appeal and sustainability, while symbols like Pengzu culture show relatively lower public acceptance. Targeted recommendations are proposed based on these findings. This study provides a quantitative basis for Xuzhou’s city brand design and suggests a greater emphasis on the sustainability and adaptability of cultural symbols in future city branding efforts.
Nexus Between Intellectual Capital and Sustainable Growth: Moderating Roles of Military-Experienced CEOs and Sustainable Corporate Governance
Authors: Arshad Muhammad Usman , Memon Rafique Ur Rehman , Anwar Waleed , Tunio Fayaz Hussain , Silveira Ferreira Paulo Jorge
Published: December 2024

This study explores the nexus between intellectual capital (IC) and the sustainable growth rate (SGR), with a unique emphasis on the moderating roles of military-experienced CEOs (MCEOs) and sustainable corporate governance (SCG). We utilize the Method of Movement Quantile Regression Analysis (MMQR) with data gathered from 750 Chinese non-financial firms listed on the Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE) from 2010 to 2022. The findings indicate that IC exerts a favorable and significant influence on the SGR across various quantiles. Furthermore, across multiple quantiles, the SGR exhibits a positive and strong correlation with capital employed efficiency (CEE), human capital efficiency (HCE), and structural capital efficiency (SCE). Moderation analysis reveals that MCEOs and SCG demonstrate a positive correlation between IC and the SGR. The results extend our understanding of how MCEOs and SCG can enhance the SGR through effective IC utilization.