bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Changes in Comprehensive Land Prices for Expropriation Zones Based on Land Use Changes
Authors: Dong Xu , Dong Xinming , Wang Fang , Fu Meichen , Deng Guanzhi , Li Sijia , Kang Haoyang , Xiong Yuqing
Published: November 2024

Comprehensive land prices for expropriation zones can effectively alleviate many conflicts in China’s land expropriation practices. This contributes to achieving sustainable development goals such as “SDG-10: Reduced Inequalities” and “ SDG-11: Sustainable Cities and Communities”. The reasonable delineation of expropriation zones and scientific calculation of zone prices have become crucial. This study used the Cangzhou urban area in Hebei Province, China, as a case study. By integrating the CA–Markov model, multiple linear regression model, coupling coordination degree model, relative development degree model, and GIS spatial analysis techniques, the study deeply analyzed the spatiotemporal coupling relationship between land use and comprehensive land prices for expropriation zones from 2009 to 2021. Furthermore, it simulated and forecasted the changes in land use, expropriation zones, and zone prices in 2027. The study yielded the following conclusions: (1) The changes in land use reflected land economic value, land resource condition and land location condition shifts, which formed an interactive feedback mechanism with the comprehensive land price for land expropriation zones. (2) Land use impacted zone distribution through the spatial distribution characteristics of construction land, with recent development zones in the central urban area primarily extending east and southeast due to planning and policies related to land use for construction. (3) The coupling coordination and relative developmental degree between land use degree and zone price gradually develop in a good direction. A linear relationship is observed among land economic value, land resource condition, and land location condition concerning the zone price. Based on this, the predicted adjustment ranges for zone prices from high to low in 2027 will be 2.6400 to 2.7210, 2.1900 to 2.2537, and 1.8300 to 1.9306 million CNY/hectare. This study provides a new method for studying comprehensive land prices for expropriation zones, supporting decision making.
Selecting the Appropriate Platform: The Varied Effects of Service Merchant Marketing Strategies on the Performance of Supply Chain Participants
Authors: Liu Wenchao , Han Yuliang
Published: November 2024

Traditionally, catering enterprises were restricted to exclusive agreements with food delivery platforms. However, recent regulatory changes in various countries addressing the “one out of two” practices of these platforms have facilitated the ability of catering businesses to engage with multiple platforms simultaneously. The existing body of literature primarily focuses on the competitive interactions between bilateral platforms or the optimal strategies for exclusive trading platform supply chains, yet it does not adequately investigate the differentiated impacts of merchant marketing strategies within this competitive framework. This study seeks to evaluate the effects of diverse strategies on the performance of supply chain participants, concentrating on four distinct strategies employed by catering businesses in their selection of service platforms and the execution of marketing initiatives. By employing game theory and inverse solving methodologies, the research determines the optimal profits for each member of the supply chain under various strategies, as well as the influence of valuation discount factors on member profits. The results reveal that the marketing efforts of service providers across different platforms significantly affect the performance of supply chain participants. Additionally, the profits of both service providers and platforms are correlated with the cost coefficient related to the marketing efforts of service providers, and these marketing initiatives also impact the perceived value of platform coupons. This research provides evidence for the positive influence of marketing decisions made by service providers.
A Hierarchical Spatiotemporal Data Model Based on Knowledge Graphs for Representation and Modeling of Dynamic Landslide Scenes
Authors: Li Juan , Zhang Jin , Wang Li , Zhao Ao
Published: November 2024

Represention and modeling the dynamic landslide scenes is essential for gaining a comprehensive understanding and managing them effectively. Existing models, which focus on a single scale make it difficult to fully express the complex, multi-scale spatiotemporal process within landslide scenes. To address these issues, we proposed a hierarchical spatiotemporal data model, named as HSDM, to enhance the representation for geographic scenes. Specifically, we introduced a spatiotemporal object model that integrates both their structural and process information of objects. Furthermore, we extended the process definition to capture complex spatiotemporal processes. We sorted out the relationships used in HSDM and defined four types of spatiotemporal correlation relations to represent the connections between spatiotemporal objects. Meanwhile, we constructed a three-level graph model of geographic scenes based on these concepts and relationships. Finally, we achieved representation and modeling of a dynamic landslide scene in Heifangtai using HSDM and implemented complex querying and reasoning with Neo4j’s Cypher language. The experimental results demonstrate our model’s capabilities in modeling and reasoning about complex multi-scale information and spatio-temporal processes with landslide scenes. Our work contributes to landslide knowledge representation, inventory and dynamic simulation.
Growing Kratky Basil in Trombe Wall Cavity: Year-Round Overview of Thermal Effects
Authors: Borys Bohoshevych Iryna , Fukuda Hiroatsu
Published: November 2024

This experimental study explores the possibility of using an existing Trombe wall as a space for year-round cultivation to increase building resource efficiency. To do so with the least cost to the building, a small 0.75 m2/5.45 m3 Trombe wall cavity space was retrofitted with shelves placed behind the glazing, additional ventilation, and a watering network to be able to grow 400 hydroponic Kratky basil plants in individual glass jars. Historical thermal observations made at the site over a year-long timespan were contrasted with the experimental readings. When fully equipped, the Trombe wall’s thermal mass increased by 51%, which had a balancing effect on the system, lowering the average daily thermal oscillations from 35.41 °C to 17.88 °C. The living plants and water have also had significant cooling (26.99 °C to 22.91 °C) and humidifying (39.88 to 47.74%) effects. The system’s energy efficiency, however, decreased from 26 to 18% (absorption) and from 85 to 46 (dissipation), lowering its energy contribution to the building by about 30%. The average plant’s lifespan within the Trombe wall was 46 days, with 15% of the specimens surpassing the 100-day mark. Over the course of a year, 20.55 kg of edible greens were grown in the Trombe wall. The experiment has shown that it is possible to grow the plants inside the Trombe wall cavity during the warmer half of the year, revealing many possible ways to improve the space’s comfort, yields, and energy efficiency.
Predicting the Global Distribution of Gryllus bimaculatus Under Climate Change: Implications for Biodiversity and Animal Feed Production
Authors: Ragab Sanad H. , Alqurashi Shatha I. , Aljameeli Mohammad M. , Tyshenko Michael G. , Abdelwahab Ahmed H. , Selim Tharwat A.
Published: November 2024

The potential range and distribution of insects are greatly impacted by climate change. This study evaluates the potential global shifts in the range of Gryllus bimaculatus (Orthoptera: Gryllidae) under several climate change scenarios. The Global Biodiversity Information Facility provided the location data for G. bimaculatus, which included nineteen bioclimatic layers (bio01–bio19), elevation data from the WorldClim database, and land cover data. For the near future (2021–2040) and far future (2081–2100) under low (SSP1-2.6) and high (SSP5-8.5) emission scenarios, the Beijing Climate Center Climate System Model (BCC-CSM2-MR) and the Institute Pierre-Simon Laplace Coupled Model Intercomparison Project (IPSL-CM6A-LR) were used. Assessing habitat gain, loss, and stability for G. bimaculatus under potential scenarios was part of the evaluation analysis. The results showed that the main environmental parameters affecting the distribution of G. bimaculatus were mean temperature of the driest quarter, mean diurnal temperature range, isothermality, and seasonal precipitation. Since birds, small mammals, and other insectivorous insects rely on G. bimaculatus and other cricket species as their primary food supply, habitat loss necessitates management attention to the effects on the food web. The spread of G. bimaculatus as a sentinel species in the food chain and its use in animal feeds are both impacted by habitat loss and gain.
Measurement of Free Trade Zones’ Investment Attraction: Sustainable Corporate Development Perspective
Authors: Li Ji , Liang Xv , Du Xiaomeng , Xv Shunzhi
Published: November 2024

This study explores the measurement of FTZs’ investment attraction from a sustainable corporate development perspective. Through a comprehensive evaluation framework, the study assesses FTZs’ investment attraction across five indicators: urban business environment, economic development strength, innovation and openness vitality, urban environmental friendliness, and high-quality enterprise development. The weights of each layer’s indicators are calculated using entropy weight and the PCA method. The evaluation results of the investment attractiveness of China’s FTZs show that the investment attraction of FTZs in different regions exhibits hierarchical characteristics and unbalanced development. East China and South China occupy the forefront. Disparities in provincial FTZs’ developmental balance are conspicuous. Guangdong, Shanghai, and Beijing top the charts in terms of congruence with their overall environment rankings, whereas Jiangsu, Zhejiang, and Fujian exhibit a mismatch between their sub-indices and their relatively strong overall investment attractiveness. Conversely, Henan, Anhui, Hebei, Heilongjiang, Hunan, and Tianjin, though balanced in sub-environmental development, lag in overall investment appeal, necessitating concerted efforts towards balanced development. On the whole, compared with other indicators, innovation and openness vitality and high-quality enterprise development seem relatively weak. Drawing from our insights, foreign investors can choose free trade zones according to their own development needs. Policymakers can devise targeted interventions to bolster FTZs’ investment attractiveness, tailored to scores and rankings.
The Impact of Sustainability on the Labour Market and Employability in the Construction Industry
Authors: Silvestru Catalin Ionut , Lupescu Marian-Ernut , Ifrim Ana-Maria , Silvestru Ramona , Icociu Cristina-Vasilica
Published: November 2024

The present article analyses how the changes in the labour market are impacting employability, within the context of sustainability, with a special focus on the construction industry. This paper explores the relevance of employability in the construction industry, in an economy that is more and more oriented towards sustainable practices. The added value of the present paper resides in the proposed methodology that includes identifying and ranking the sustainability indicators that contribute to a sustainable employability model. The main objective of this research is to highlight the importance of sustainability in terms of training and preserving the specific competencies for the construction industry labour market, which is an essential sector for the transition to a green economy. The methodological innovation of the present study is that it proposes a model for the assessment of the sustainability indicators, thus offering a practical and ready-to-use framework for decision-makers in the industry. These indicators, which influence sustainability in the long term, were analysed from the viewpoint of the construction industry in Romania. This study used secondary statistical data, with a focus on the evolution of employability and of the professional training of graduates in this field of activity. The conclusion of the analysis is that a sustainable employability model should be implemented that meets the needs of the contemporary labour market and ensures an effective transition to a green economy. Implementing sustainable strategies in the construction sector facilitates the transition to responsible practices that are adapted to the current requirements of the green economy.
Birds as Cultural Ambassadors: Bridging Ecosystem Services and Biodiversity Conservation in Wetland Planning
Authors: Ingaramo Michela , Cammerino Anna Rita Bernadette , Rizzi Vincenzo , Gioiosa Maurizio , Monteleone Massimo
Published: November 2024

Coastal wetlands deliver essential ecosystem services, including cultural services, which provide non-material benefits such as recreation, education, and spiritual enrichment that are crucial for human well-being. This study investigates the cultural ecosystem services provided by a 40 ha coastal wetland in the Gulf of Manfredonia, southern Italy, within the Gargano National Park. By integrating an ecological survey of the bird community with a social survey of visitors to the King’s Lagoon Nature Reserve, the content of tailored planning strategies and management tools for the conservation of wetland biodiversity was developed. An ecological analysis of the bird community was carried out on the assumption that it could be representative of the total biodiversity observed in the wetland. On the other hand, a questionnaire was used to collect information from visitors to the reserve, highlighting the aspects of the wetland that they found most interesting and attractive according to their judgement and beliefs, and thus targeting a specific set of cultural ecological services. The two approaches were then combined to develop a comprehensive strategy. The bird community analysis led to the identification of the mixed biotope category (a combination of wetlands, aquatic/riparian ecosystems, semi-natural vegetated areas, and meadows together with agricultural areas) as the reference biotope for prioritizing wetland management. The Ardeidae family was chosen as a bird flagship group because of its high visibility, ease of identification, attractiveness to visitors, wide local distribution, and fairly constant presence in the study area throughout the year. Flagship species have a dual function: to guide conservation measures and actions by wetland managers, and to attract the interest, curiosity and active participation of potential visitors to the wetland. Based on the results, a list of guidelines for improving the birds’ habitats and providing them with resources (feeding, breeding, shelter, roosting, etc.) has been proposed. The aim of these measures is to optimize the presence and abundance of Ardeidae as flagship species, thereby preserving the biodiversity heritage in general and increasing the provision of cultural ecosystem services in the wetland. The resulting dynamic interplay ensures that both natural and cultural resources are fully and appropriately valued, protected, and maintained for the benefit of present and future generations.
International Climate Migrant Policy and Estimates of Climate Migration
Authors: Clements Paul
Published: November 2024

The architecture of international aid and climate finance should be reformed to address the needs of climate migrants. While humanitarian aid agencies that support some climate migrants are increasingly overburdened, climate migration has been underestimated and largely neglected by the United Nations Framework Convention on Climate Change (UNFCCC). The policy community has based a high-end estimate of 216 million potential climate migrants by 2050 on Groundswell (2021), but Groundswell does not address all drivers. It uses statistical methods to estimate internal migration from slow-onset drivers including crop yields, water supplies, and sea level rise, but the state of knowledge only permits rough, “back-of-the-envelope” estimates for other forms and drivers. Working out such estimates for sudden-onset drivers and for the remaining slow-onset drivers, if mitigation and adaptation are weak, I find that there could be about 500 million climate migrants by 2050. While the UNFCCC classifies climate migration under adaptation, few adaptation resources are devoted to migrants’ needs. Based on humanitarian aid expenses for other kinds of migrants, I estimate it could cost around $7000 per person to help climate migrants to rebuild their lives. At this rate, support for climate migrants would be a significant part of the total climate finance, and with organizational needs for supporting climate migrants being quite different from those for adaptation proper, it would make sense for the UNFCCC to address climate migration as a separate category on par with mitigation and adaptation.
Progressive Methods of the Harmfulness Evaluation of Transport in Terms of Emission Production
Authors: Dedík Milan , Kendra Martin , Senci Matúš , Pribula Daniel , Vojtek Martin
Published: November 2024

Today, the key challenge is to ensure environmentally acceptable and sustainable transport. This paper analyzes the current state of emissions and greenhouse gases and their impact on the environment. In more detail, it is focused on relevant transport emissions data and their development in the Slovak Republic. It describes and analyzes proposals to improve the current state of rail transport and reduce greenhouse gas (GHG) emissions. Furthermore, it examines current transport trends and their impact on the environment and then analyzes and evaluates these relevant data concerning specific types of emissions. The differences between road, rail, and pipeline transport modes are analyzed and quantified through graphical analysis and analysis of variance (ANOVA) at 5% significance using IBM SPSS statistics software. A subsequent Scheffé post-hoc test is utilized. The usage of ANOVA enables the determination of whether the differences between the transport modes are statistically significant and generalizable or if they arise due to random variation. Based on the knowledge gained, specific measures and strategies are proposed that could contribute to a more efficient use of rail transport to reduce greenhouse gas emissions. The originality and novelty of the contribution lie in the connection between environmental science and applied statistics as well as in finding new progressive synergistic effects between them. The results provide important information for decision-making in the field of investment and planning of rail infrastructure and transport to promote environmental sustainability and reduce the negative environmental impact of rail transport. The research results contribute to the development of a sustainable transport system and will be used in other scientific research activities of the authors in more detailed research on individual proposed measures.
Modest Method for Estimating CO2 Emissions from Container Handling Equipment at Ports
Authors: Budiyanto Muhammad Arif , Ichfari Faril , Shinoda Takeshi
Published: November 2024

The maritime industry is under increasing pressure to reduce CO2 emissions, with the International Maritime Organization (IMO) setting a target to reduce greenhouse gas emissions, including emissions from the port sector, by 40% by 2030. However, accurate and reliable methods for estimating CO2 emissions at container ports, which are significant contributors to maritime emissions, are still lacking. This study aims to address this by evaluating a novel method for estimating CO2 emissions at container ports. The proposed method utilizes the cargo handling equipment movement theory, quantifying both vertical and horizontal movements based on the amount of container handling equipment at the port. The emissions for each piece of equipment are estimated by multiplying the movement quantity by the respective emission factor. To validate the model, a robustness test compares the estimated CO2 emissions with actual energy consumption data from the port. A case study was conducted at a container port with an annual capacity of over 500,000 TEUs and a parallel layout type. The estimated CO2 emissions were approximately 8183 tons per year, with container cranes contributing 56%, rubber-tire gantry cranes contributing 27%, terminal trucks contributing 14%, and reach stackers contributing 3%. The method demonstrated accuracy, with a deviation of less than 1%. This method offers a fast and reliable approach for estimating baseline CO2 emissions at container ports, providing valuable insights for port authorities and policymakers to develop more effective emission-reduction strategies.
Exploring the Impact of Built Environment on Elderly Metro Ridership at Station-to-Station Level
Authors: Duan Chaojie , Ma Shuhong , Li Chenguang
Published: November 2024

Understanding the relationship between the built environment and metro ridership has become essential for advancing sustainable transportation development. Limited research has been given to how built environment factors influence metro ridership at a station-to-station level. Moreover, most studies focus on the general population, overlooking the special groups. This study examines the influence of the built environment on metro origin–destination (OD) ridership for older adults. Specially, we employ the CatBoost model, along with SHAP interpretation, to assess feature importance and capture nonlinear effects. Taking Xi’an as a case study, the results show that: (1) The CatBoost model demonstrates superior fitting and predictive performance, outperforming both the XGBoost and Logistic Regression models. (2) There are distinct variations in the influence of built environment factors at origin and destination stations. Traffic-related variables have a stronger effect at origin stations, while land-use variables exert a more significant influence at destination stations. (3) The built environment’s impact on older adults’ metro ridership exhibits a clear nonlinear relationship. Notably, an optimal land-use mix of 1.8–1.9 and a job density of 5000–7000 significantly enhance ridership. These findings provide valuable insights into how the built environment shapes older adults’ metro travel, contributing to the sustainable urban development.
Thermal Performance of a Straw Bale Building in Relation to Fiber Orientation: A Case Study
Authors: Rota Font Francesc , Ciriano Nogales Yolanda , Temes Mendoza David , Vallbé Mumbrú Marc , Barbeta Solà Gabriel , De Felipe Blanch Jose Juan
Published: November 2024

In the face of escalating global average temperatures, it is urgent to identify mechanisms that can significantly curtail the emission of greenhouse gases. The construction industry plays a pivotal role in shaping these emissions, rendering the selection of environmentally conscious materials indispensable in the imminent future. In this context, attention is drawn to an interesting material from an ecological point of view: straw. Abundant as a natural byproduct exhibiting remarkable thermal properties, straw emerges as a good candidate for sustainable edification. In the present work, an in situ study of its thermal resistance is carried out, and it is found that it allows stable interior temperatures. The apparent thermal conductivity is analyzed in relation to the orientation of its fibers in the same building, and its low conductivity compared with traditional construction materials is confirmed. The relevance of this work lies in the fact that the building studied contains walls with different fiber orientations in the same room, with the same ambiental conditions. This ensures that the different thermal behaviors are exclusively due to the orientation of the fibers. When considering both orientations of the fibers, different values of thermal conductivity are discerned. Conductivity decreases when the direction of the heat flow is perpendicular to the fibers. However, due to the inherent geometry of the bales, their overall thermal behavior ultimately proves comparable.
Sustainable Management of Shrimp Waste to Produce High-Added Value Carbonaceous Adsorbents
Authors: Fotodimas Ioannis , Ioannou Zacharias , Kanlis Grigorios , Sarris Dimitris , Athanasekou Chrysoula
Published: November 2024

Every year, large amounts of shrimp waste are disposed of in the environment, causing serious environmental problems. The prospect of recycling shrimp waste helps to reduce waste and protect the environment. In this study, three different shrimp species were used, including Pleoticus muellieri, Litopeneus vanamei, and Parapenaeus longirostris, separated into shells (PLMUS, LIVAS, PALOS) and tails (PLMUT, LIVAT, PALOT), and transformed into novel carbonaceous materials. Their adsorption properties were investigated using different chemical compounds (MB, MR, phenol, astaxanthin) in aqueous means. The materials were characterized through FTIR, BET, and SEM–EDS analyses. According to the results, the carbonaceous adsorbents presented high adsorption percentage of MB and astaxanthin (>90%), and low adsorption percentage of phenol and MR, owing to the different bonds that were formed between the functional groups of the organic substances and the corresponding groups on the surface of the materials. The results of the FTIR analysis show the presence of C=C groups from the aromatic rings of the adsorbed MB and MR at 1636 cm−1, the presence of O-H functional groups from the adsorbed phenols at 3330 cm−1, and the presence of C=C or C=O groups at 1730 cm−1 after the adsorption of astaxanthin. According to the BET analysis, the increase in the specific surface area follows the order: LIVAS > PLMUS > PALOT > PALOS > PLMUT > LIVAT. SEM–EDS analysis presented compact structures with the main elements of C (37–56%), O (25–35%), and Ca (12–23%) for all materials. Kinetic analysis showed that the experimental adsorption data of all the organic substances can be best described by the pseudo-second order model, indicating that chemisorption is the prevailing mechanism. Consequently, such methods promote the sustainable management and zero-waste fish farming practices, fostering the production of high-added value materials not only for decontamination purposes but also for the isolation of bioactive substances.
Power Distribution Network Reconfiguration Techniques: A Thorough Review
Authors: Lotfi Hossein , Hajiabadi Mohammad Ebrahim , Parsadust Hossein
Published: November 2024

Distribution network reconfiguration (DNR) plays a vital role in enhancing network sustainability by optimizing its topology. This process achieves key objectives such as reducing power losses, improving voltage profiles, balancing loads, and increasing network reliability, aligning with sustainability metrics. Depending on the goals and equipment available, reconfiguration may be applied for short-term or long-term durations. Long-term or static reconfiguration suits both conventional switches and traditional as well as modern networks. In modern networks equipped with remote-control switches, however, reconfiguration can be implemented rapidly to meet specific operational objectives. This study provides a comprehensive review of recent advancements in network reconfiguration, categorizing methods into four groups: heuristic, metaheuristic, conventional, and modern approaches. Each category is broadly defined and compared, with applications discussed for both static and dynamic reconfiguration. Dynamic reconfiguration is highlighted as a key area for future exploration in smart and modern distribution networks. This article serves as a resource for engineers and researchers, helping them select the most suitable method based on network equipment and performance goals.
Development of Sustainable Industrial Safety and Health Policy for Electronic Industry in Korea: A Study on the Relationship Between Safety Leadership of Managers, Safety Climate, and Safety Behavior
Authors: Won Sula , Choi Jaewook , Kim Kyunghee
Published: November 2024

This study aimed to identify the relationship between the safety leadership of safety and health managers, the safety climate of the organization, and the safety behavior of workers in the electronics industry in order to develop a sustainable industrial safety and health policy. The study included 842 individuals working at electronics industry cooperators. After analyzing the correlation between safety leadership of managers, safety climate, and safety behavior using SPSS 23.0, measurement model analysis and structural equation modeling (SEM) were performed using AMOS 26.0 to evaluate their relationships. We observed that the safety leadership of managers was associated with safety climate and safety behavior. Additionally, among the sub-dimensional variables of safety climate, the management’s commitment to safety and health and the delivery and communication of safety and health information were related to safety behavior. Therefore, enhancing worker participation and behavior requires strengthening the safety leadership of managers, increasing management’s commitment to safety and health, and improving the effectiveness of safety and health information delivery and communication.
Impact of Green Finance on Carbon Emission Efficiency and Spatial Spillover Effects: A Case Study of Guangzhou, China
Authors: Qin Xingcun , Dong Genglin , Xie Pengcheng , Zhang Yulong , Liao Cuiping
Published: November 2024

The Green Finance Pilot Policy (GFPP) is a crucial initiative in China, aiming to provide financial support for achieving carbon neutrality. Objectively evaluating the outcomes of the GFPP is crucial for refining the policy and replicating successful experiences. This paper takes Guangzhou as a case study based on panel data from 25 cities spanning 2005 to 2019 and employs the synthetic control method to evaluate the impact of the GFPP on Guangzhou’s carbon emission efficiency (CEE). Additionally, this paper analyzes its spatial spillover effects and driving mechanisms through the SDID model. The results indicate that the GFPP has effectively enhanced Guangzhou’s CEE by an average of 25.3%. Furthermore, the GFPP has also enhanced the CEE of neighboring cities, with a decaying boundary of 100 km. Promoting green technology innovation and improving energy efficiency are identified as effective mechanisms through which the GFPP enhances the city’s CEE. This paper provides a comprehensive examination of the impact and mechanisms of the GFPP on CEE from a spatial perspective. The findings could offer valuable insights for advancing green finance systems and helping cities leverage financial policies to support low-carbon transition.
Exploration of the Application and Practice of Digital Twin Technology in Teaching Driven by Smart City Construction
Authors: Ning Guangli , Luo Haidan , Yin Wei , Zhang Yin
Published: November 2024

Traditional engineering education cannot effectively respond to the demand for talents in the construction of smart cities. The application of digital twin technology in education is mostly based on case studies and lacks empirical tests. This study takes the practical teaching of a project-based course on smart city parks as an example to explore the action intention of graduate students to use digital twin technology consistently, and to provide a theoretical basis and teaching practice guidance to promote the rational application of digital twin technology in engineering education. This study set up a quasi-experimental design through the digital twin learning system, grouping 24 graduate students with 4 faculty members. The experimental group is digital twin-assisted practical teaching, and the control group is traditional teaching method, the experimental cycle is 12 weeks, and the total lesson time is 24 h. Secondly, combined with UTAUT2 model and TTF theory, the variable factor hypothesis was adopted as the scale design means, and the experimental validity was improved through questionnaire data analysis. Meanwhile, the influencing factors in the use of digital twin platform were recorded in detail through the process of data collection, data processing and modeling, as well as the application practice of digital twin platform. Finally, the results of the comprehensive survey data show that the graduate students in the experimental group are significantly better than the control group in terms of self-confidence, skill enhancement, learning outcomes, and learning experience. All these results provide information for course teaching practice, training professional teaching teams, optimizing innovative teaching paths, and promoting the cultivation and delivery of smart city technology talents.
A Computationally Efficient Rule-Based Scheduling Algorithm for Battery Energy Storage Systems
Authors: Becchi Lorenzo , Belloni Elisa , Bindi Marco , Intravaia Matteo , Grasso Francesco , Lozito Gabriele Maria , Piccirilli Maria Cristina
Published: November 2024

This paper presents a rule-based control strategy for the Battery Management System (BMS) of a prosumer connected to a low-voltage distribution network. The main objective of this work is to propose a computationally efficient algorithm capable of managing energy flows between the distribution network and a prosumer equipped with a photovoltaic (PV) energy production system. The goal of the BMS is to maximize the prosumer’s economic revenue by optimizing the use, storage, sale, and purchase of PV energy based on electricity market information and daily production/consumption curves. To achieve this goal, the method proposed in this paper consists of developing a rule-based algorithm that manages the prosumer’s Battery Energy Storage System (BESS). The rule-based approach in this type of problem allows for the reduction of computational costs, which is of fundamental importance in contexts where many users will be coordinated simultaneously. This means that the BMS presented in this work could play a vital role in emerging Renewable Energy Communities (RECs). From a general point of view, the method requires an algorithm to process the load and generation profiles of the prosumer for the following three days, together with the hourly price curve. The output is a battery scheduling plan for the timeframe, which is updated every hour. In this paper, the algorithm is validated in terms of economic performance achieved and computational times on two experimental datasets with different scenarios characterized by real productions and loads of prosumers for over a year. The annual economic results are presented in this work, and the proposed rule-based approach is compared with a linear programming optimization algorithm. The comparison highlights similar performance in terms of economic revenue, but the rule-based approach guarantees 30 times lower processing time.
The Path to Sustainable Stability: Can ESG Investing Mitigate the Spillover Effects of Risk in China’s Financial Markets?
Authors: Wei Jiangying , Hu Ridong , Chen Feng
Published: November 2024

In the context of a low-carbon economic transition and escalating uncertainties in financial markets, understanding the relationship between the long-term benefits of ESG (Environmental, Social, and Governance) investments and the stability of China’s financial markets emerges as a critical issue. This paper analyzes the risk contagion mechanisms within China’s financial system from the perspective of volatility spillovers associated with ESG investments. Initially, the study employs the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to calculate the variance decomposition spillover index, contrasting the dynamics and risk transmission mechanisms of market volatility between portfolios composed of ESG and conventional stocks. Building upon the analysis of risk spillover relations among financial sub-markets, the study utilizes the generalized forecast error variance decomposition method to construct a complex network of financial system risk spillovers, investigating the risk contagion characteristics within both financial systems through network topology. Empirical findings indicate a significant reduction in the risk and net spillover effects of China’s financial system when ESG stock indices replace conventional stock indices, with a notable mutation in the volatility spillover network structure during extreme risk events and even more substantial changes during the COVID-19 pandemic. Furthermore, based on volatility spillover analysis, the study computes optimal weights and hedging strategies for portfolios incorporating the ESG volatility index and other market volatility indices. The conclusions of this research are instrumental for regulatory authorities in establishing early warning mechanisms and for investors in avoiding financial investment risks.
Maximum Power Point Tracking Based on Finite Voltage-Set MPC for Grid-Connected Photovoltaic Systems Under Environmental Variations
Authors: Hassan Mohammed A. , Adel Mahmoud M. , Saleh Amr A. , Eteiba Magdy B. , Farhan Ahmed
Published: November 2024

This paper proposes a model predictive control (MPC)-based approach for optimizing the performance of a photovoltaic (PV) system. The proposed method employs finite voltage-set maximum power point tracking (FVS-MPPT), ensuring precise duty cycle adjustment for a boost converter in the PV system considering the environmental changes in irradiation and temperature. Additionally, MPC is implemented for the grid-side converter to determine the optimal switching vector, ensuring precise control of active power via reference d-axis current and the elimination of reactive power by setting the reference q-axis current to zero. This approach optimizes the converter’s performance, maintaining a stable DC-link voltage while ensuring efficient grid integration. To ensure proper synchronization with the grid, a phase-locked loop (PLL) is utilized to provide the necessary grid voltage angle for dq frame transformation. Simulation results highlight the efficiency of the proposed MPC strategy, with the PV-side converter showing a robust response by dynamically adjusting the duty cycle to maintain optimal performance under varying irradiation and temperature conditions. Furthermore, the grid-side converter ensures precise control of active power and eliminates reactive power, enhancing the overall system’s stability and efficiency during grid interactions. A functional comparison of simulation results between the conventional P&O algorithm and the FVS-MPPT approach is presented, demonstrating the enhanced performance of the proposed technique over the conventional method including the total harmonic distortion for both techniques.
Toward a Comprehensive Economic Comparison Framework for Solar Projects: A Case Study of Utility and Residential Scales
Authors: He Bowen , Zheng Han , Zhang Qixiao , Zhao Ava , Tang Huaizhi , Xi Ping , Wei Laiwei , Li Muqing , Guan Qun
Published: November 2024

The growing demand for clean energy transitions has become increasingly significant, with solar energy emerging as one of the most prominent clean energy resources contributing to this effort. However, there remains limited knowledge regarding the economic feasibility of solar project development across different geographic locations and scales. This study introduces a comprehensive economic analysis framework to assess the economic viability of residential- and utility-scale solar projects, using California, Tennessee, and Texas as case studies. The economic assessment is conducted through a cost–benefit analysis that adopts a full life-cycle approach, encompassing phases from permitting to demolition for both scales of solar projects. We found that utility-scale solar projects generally offer more favorable investment return ratios (IRRs) compared to residential projects, with IRRs of 0.57 to 0.61 for California, 0.63 to 0.80 for Texas, and 0.11 to 0.52 for Tennessee. Moreover, utility-scale solar projects in Texas were found to exhibit the earliest breakeven point, reaching financial viability by the seventh year. Furthermore, the incorporation of energy storage solutions, such as battery energy storage systems (BESSs), is shown to be essential for improving the efficiency of residential solar energy usage, with efficiency gains of up to 50%. Finally, region-specific strategies, including net-metering policies, electricity retail market structures, and the promotion of solar adoption, play a crucial role in enhancing the financial viability of solar projects for both residential and utility scales.
Offloading Strategy for Forest Monitoring Network Based on Improved Beetle Optimization Algorithm
Authors: Cheng Xiaohui , Lu Xiangang , Deng Yun , Lu Qiu , Kang Yanping , Tang Jian , Shi Yuanyuan , Zhao Junyu
Published: November 2024

In forest monitoring networks, the computational capabilities of sensors cannot meet the latency requirements for complex tasks, and the limited battery capacity of these sensors hinders the long-term execution of monitoring tasks. Mobile edge computing (MEC) acts as an effective solution for this issue by offloading tasks to edge servers, significantly reducing both task latency and energy consumption. However, the computational capacity of MEC servers and the bandwidth in the system are limited, and the communication environment in forested areas is complex. To simulate the complexity of the forest communication environment, we incorporate empirical path loss and multipath fading into the calculation of signal transmission rates. The computational offloading problem is then converted into a minimum-cost optimization problem with multiple constraints related to energy consumption and latency, which we formulate as an NP-hard problem. We propose a dung beetle optimization (DBO) strategy for computational offloading, enhancing it with an improved circle chaotic mapping, a dimension decomposition strategy, and Cauchy disturbance. This algorithm has the beauty of symmetry in the search range, and the symmetrical features can comprehensively search for existing solutions. Experimental results demonstrate that the improved dung beetle optimization algorithm (IDBO) achieves better convergence, lower complexity, and superior optimization outcomes compared to local offloading strategies and other metaheuristic algorithms, confirming the effectiveness of the proposed algorithm and ensuring the service quality of the forest monitoring network.
GRouteNet: A GNN-Based Model to Optimize Pathfinding and Smart Charging Management for Autonomous Guided Vehicles
Authors: Kazmi Sadia Nishat , Akber Syed Muhammad Abrar
Published: November 2024

Autonomous Guided Vehicles (AGVs) play an important role in the automation of material handling and transportation tasks in modern industrial and logistics systems. However, suboptimal path planning and longer waiting times at charging stations significantly affect the operational efficiency of these vehicles. To address these challenges, we leverage the capabilities of Graph Neural Networks (GNN) to find the optimal paths for AGVs. In this paper, we propose GRouteNet, a GNN-based model that effectively finds the shortest path for AGVs. The proposed model utilizes the message-passing mechanism of GNN to determine the neighbor nodes and then aggregates this information to find the shortest path. We compare the results of GRouteNet with a couple of existing state-of-the-art pathfinding models and show that the path length computed by GRouteNet is up to 45% shorter compared to the existing models. Furthermore, we propose a Shortest Charging Time First (SCTF) scheduling algorithm to reduce the long waiting times in the queues at the charging stations. The proposed SCTF algorithm prioritizes the charging of AGVs based on their charging time and charges the AGVs with the shortest charging time first. We compare the results of SCTF with the first-come-first-serve scheduling algorithm and show that SCTF reduces the waiting times at the charging stations by up to 42%.
Uniform in Number of Neighbor Consistency and Weak Convergence of k-Nearest Neighbor Single Index Conditional Processes and k-Nearest Neighbor Single Index Conditional U-Processes Involving Functional Mixing Data
Authors: Bouzebda Salim
Published: November 2024

U-statistics are fundamental in modeling statistical measures that involve responses from multiple subjects. They generalize the concept of the empirical mean of a random variable X to include summations over each m-tuple of distinct observations of X. W. Stute introduced conditional U-statistics, extending the Nadaraya–Watson estimates for regression functions. Stute demonstrated their strong pointwise consistency with the conditional expectation r(m)(φ,t), defined as E[φ(Y1,…,Ym)|(X1,…,Xm)=t] for t∈Xm. This paper focuses on estimating functional single index (FSI) conditional U-processes for regular time series data. We propose a novel, automatic, and location-adaptive procedure for estimating these processes based on k-Nearest Neighbor (kNN) principles. Our asymptotic analysis includes data-driven neighbor selection, making the method highly practical. The local nature of the kNN approach improves predictive power compared to traditional kernel estimates. Additionally, we establish new uniform results in bandwidth selection for kernel estimates in FSI conditional U-processes, including almost complete convergence rates and weak convergence under general conditions. These results apply to both bounded and unbounded function classes, satisfying certain moment conditions, and are proven under standard Vapnik–Chervonenkis structural conditions and mild model assumptions. Furthermore, we demonstrate uniform consistency for the nonparametric inverse probability of censoring weighted (I.P.C.W.) estimators of the regression function under random censorship. This result is independently valuable and has potential applications in areas such as set-indexed conditional U-statistics, the Kendall rank correlation coefficient, and discrimination problems.
The Strength Within: CSR Governance as an Environmental Performance Driver in Weak Institutional Contexts
Authors: Hyun Eun-jung , Yu Si
Published: November 2024

This study investigates how the relationship between firm-level corporate social responsibility (CSR) governance and corporate environmental performance (CEP) varies across diverse national contexts. Drawing on institutional theory, organizational adaptation theory, and the concept of institutional voids, we analyze an extensive dataset of 5326 firms from 26 OECD countries over a seven-year period (2013–2019). Employing panel data analysis, we examine the moderating effects of country-level factors on the CSR governance–CEP relationship. Our findings reveal a significant positive association between a firm’s CSR governance quality and environmental performance, which is notably stronger in countries characterized by weaker environmental governance, less prominent societal environmental values, and fewer climate mitigation laws and policies. These results suggest that firms with strong CSR governance effectively fill institutional voids in environmental governance, going beyond mere compliance to drive environmental performance improvements where external pressures are weak. Our study contributes to the literature by advancing the current understanding of the contextual nature of CSR, extending the application of institutional void theory to environmental governance landscapes in developed economies, and providing a more nuanced perspective on when and where CSR governance matters most for environmental outcomes. These insights offer valuable implications for managers in diverse institutional contexts and for policymakers seeking to enhance corporate environmental performance through complementary governance mechanisms.