bluuebunny/crossref_metadata_2025 huggingface dataset:
How Does the Digital Economy Affect Green Development?—Evidence from 284 Cities in China
Authors: Zhao Pei , Guo Junhua , Wang Yang
Published: July 2023

The expansion of the digital economy has resulted in extensive changes to production factors, production methods, and lifestyles, making it a key factor in green development. In a unified framework, this paper examines the impact of China’s digital economy on green development and the transmission mechanisms of the digital economy. Based on a theoretical analysis of the green attributes and transmission mechanisms of the digital economy, the relationship is empirically examined using the fixed effects model, the instrumental variables method, the quantile regression model, and the mediating effects model with China-specific data from 2011 to 2019. The results indicate that the digital economy has a significant positive impact on green development, and that this impact grows as GTFP (Green Total Factor Productivity) increases. The digital economy has a lasting impact. According to the analysis of heterogeneity, the impact of the digital economy varies significantly between regions, and this disparity exists in both small and large cities. The “digital gap” between high- and low-level cities exacerbates the disparity in the digital economy’s effects. The mechanism analysis reveals that industrial structure rationalization and environmental improvement are the primary means by which the digital economy’s effects are transmitted. Currently, the “innovation-to-application” conversion efficiency is low, and the “demand expansion effect” is greater than the “efficiency enhancement effect”, which impedes the transmission path of green technology innovation and energy use efficiency. The research findings serve as a guide for promoting the development of Digital China and accelerating the green transformation.
The Role of Eudaimonic Motivation on the Well-Being of College Athletes: The Chain-Mediating Effect of Meaning Searching and Meaning Experience
Authors: Wang Guangjun , Sun Wujun , Liu Lei , Jiang Yuan , Ding Xiaosheng , Liu Yuan
Published: July 2023

Subjective well-being is an essential indicator for evaluating the quality of life of college athletes. According to self-determination theory, eudaimonic motivation is a positive psychological characteristic that is supposed to have a favorable influence on college athletes’ acquisition of subjective well-being. In order to examine the relationship between the two and test the mediating effects of meaning searching and meaning experience, this study investigated the relevant data of 593 college athletes from four different provinces in China. The findings are as follows: (1) the direct effect of eudaimonic motivation on college athletes’ subjective well-being was significant and positive. (2) The mediating effect of meaning searching between eudaimonic motivation and subjective well-being was nonsignificant. (3) However, meaning experience mediated the positive influence of eudaimonic motivation on subjective well-being. (4) Eudaimonic motivation was related indirectly and positively to subjective well-being via the chain-mediating effect of meaning searching and meaning experience. The present study provides empirical evidence for the relationship between positive psychological characteristics and the subjective well-being of college athletes and suggests that educators look for positive qualities to cultivate from the perspective of positive psychology, which can help to prevent psychological disorders and improve the well-being of college athletes.
Evaluation of Antioxidant, Antimicrobial, and Anticancer Properties of Onion Skin Extracts
Authors: Bozinou Eleni , Pappas Ioannis S. , Patergiannakis Iason-Spyridon , Chatzimitakos Theodoros , Palaiogiannis Dimitrios , Athanasiadis Vassilis , Lalas Stavros I. , Chatzilazarou Arhontoula , Makris Dimitris P.
Published: July 2023

Onion skins (OS) are a by-product of onion processing that causes both biological and environmental problems. Thus, OS could be used sustainably and as means of circular economy since they contain valuable bioactive compounds that can be used for the production of high-added-value products. This study aims to evaluate the potential antioxidant, antimicrobial, and anticancer properties of onion OS crude extracts. The extracts were prepared using different solvents (i.e., water, ethanol, and their mixtures) and evaluated for their total phenolic content and phytochemical composition, their antioxidant activity (using the DPPH radical scavenging assay, the ferric reducing antioxidant power (FRAP) assay, and the hydrogen peroxide scavenging assay), anti-inflammatory properties, as well as for their antimicrobial (against Listeria monocytogenes, Escherichia coli O157:H7, Bacillus cereus, Enterococcus faecalis, Pseudomonas aeruginosa, Staphylococcus aureus, Salmonella typhimurium, and Yersinia enterocolitica) and anticancer (against human breast cancer cells (MCF-7) and human glioblastoma cells (U-87 MG)) activity. The results revealed that the extracts contained a significant amount of phenolic compounds, ranging between 348.71 and 795.11 mg gallic acid equivalents per g of dry weight. The extracts showed promising cytotoxic effects (up to ~40%) against cancer cell lines, indicating their potential as a natural source of anticancer agents. Additionally, the extracts exhibited strong antioxidant and antimicrobial activity against the tested microorganisms. The findings of this study suggest that OS crude extracts could be a promising candidate for developing natural functional foods and pharmaceuticals. They could be used as natural alternatives for the prevention and treatment of various diseases caused by oxidative stress, microbial infections, or cancer since they are a valuable source of bioactive compounds that can be used for various applications such as food preservation, nutraceuticals, and pharmaceuticals.
Effects of Basicity Index on Incinerator Fly Ash Melting Process and Stabilization
Authors: Chen Wei-Sheng , Chen Gregory , Lee Cheng-Han
Published: July 2023

The generation of hazardous industrial waste in Taiwan has rapidly increased, reaching 1.5 million tons produced annually in 2021. Most of this waste was burned in incinerators, with about 15% (225,000 tons) of it converted into fly ash. Incinerator fly ash primarily consists of heavy metals, dioxins, chlorides, and silica. Historically, fly ash disposal has only relied on cement solidification, contributing to insufficient landfill capacity and soil-pollution concerns. To address these issues, the melting process has been a feasible solution, wherein the heavy metals can be encapsulated within a vitrified structure to prevent them from leaching out. However, the melting point of fly ash is too high, so this study aimed to explore the optimal basicity index for fly ash to conduct the melting process. Basicity indices are estimated by the ratio of CaO/SiO2, and the melting point of the fly ash can be decreased during the melting process with the right basicity index. In this study, the characteristics of incinerator fly ashes from industrial waste and laboratory waste were initially investigated. With their basicity indices adjusted with two sources of silica, the fly ashes were tested at 1100~1400 °C to observe whether they melted. The vitrified slags were subsequently subjected to TCLP, XRF, and ICP tests to verify their stability. In summary, we discovered that fly ash could be melted through the melting process with the basicity index adjusted to under 1.28, with the silica source as either glass or silica sand powder. After melting, the heavy metals were confirmed to be stabilized in the vitrified slags. Consequently, the melting process could be an alternative solution for fly ash disposal that is sustainable and eco-friendly.
Intelligent Manufacturing and Value Creation in Enterprises: Lessons from a Quasi-Natural Experiment in a Chinese Demonstration Project
Authors: Zhu Zhao-Zhen , Chen Yue , Zhao Jiang , Yu Zhu-Ying
Published: July 2023

With the rapid advancement of contemporary information technologies, intelligent manufacturing has emerged as a pivotal direction in the global technological transformation. To empirically examine the impact of intelligent manufacturing on enterprise value creation, this article conducts quasi-natural experiments using Chinese intelligent manufacturing demonstration projects as a sample. Specifically, it focuses on Chinese A-share-listed manufacturing enterprises in Shanghai and Shenzhen from 2011 to 2020. According to the report, the implementation of intelligent manufacturing has a positive influence on enterprise value production. This conclusion remains robust even after undergoing a rigorous testing procedure. Mechanism analysis further reveals that alleviating financial constraints and fostering technological innovation are the two primary avenues through which intelligent manufacturing enhances enterprise value creation. Moreover, the study indicates that regions with favorable business environments experience a more conspicuous boost in enterprise value generation due to intelligent manufacturing. Additionally, businesses in the growth stage are more significantly affected by this phenomenon. Overall, this research not only contributes to the existing body of knowledge on this subject but also offers empirical evidence to support businesses in their endeavors to enhance value creation.
Habitat Quality Assessment and Driving Factors Analysis of Guangdong Province, China
Authors: Liu Yongxin , Wang Yiting , Lin Yiwen , Ma Xiaoqing , Guo Shifa , Ouyang Qianru , Sun Caige
Published: July 2023

Habitat quality is a key factor in regional ecological restoration and green development. However, limited information is available to broadly understand the role of natural and human factors in influencing habitat quality and the extent of their impact. Based on remote sensing monitoring data of land use over five time points (2000, 2005, 2010, 2015, and 2020), natural factors, and socioeconomic data, we applied the InVEST model to assess habitat quality in Guangdong Province. Using a multiscale geographically weighted regression (MGWR) model, we explored the spatial scale differences in the role of natural and human factors affecting habitat quality and the degree of their influence. The highlights of the results are as follows: ① From 2000 to 2020, land-use changes in the Pearl River Delta (PRD) region were particularly obvious, with the dynamic degree of construction land being higher than that of other land-use types. Construction land has gradually occupied agricultural and ecological land, causing damage to habitats. ② The overall habitat quality in Guangdong Province is decreasing; the areas with low habitat quality values are concentrated in the PRD region and the coastal areas of Chaoshan, Maoming, and Zhanjiang, while the areas with higher habitat quality values are mainly located in the non-coastal areas in the east and west of Guangdong and the north of Guangdong. ③ The MGWR regression results showed that the normalized vegetation index had the strongest effect on habitat quality, followed by road density, gross domestic product (GDP) per unit area, slope, and average elevation, and the weakest effect on average annual precipitation. ④ The effects of average elevation, GDP per unit area, and normalized vegetation index on habitat quality were significantly positively correlated, while road density was significantly negatively correlated. These results provide a scientific basis for adjusting spatial land-use planning and maintaining regional ecological security.
Travel Characteristics Identification Method for Expressway Passenger Cars Based on Electronic Toll Collection Data
Authors: Cai Xiaoyu , Zhang Yihan , Zhang Xin , Peng Bo
Published: July 2023

Passenger cars have emerged as a substantial segment of the vehicles traversing expressways, generating extensive traffic data on a daily basis. Accurately identifying individual vehicles and their travel patterns and characteristics is crucial in addressing the issues that impede the sustainable development of expressways, including traffic accidents, congestion, environmental pollution, and losses of both personnel and property. Regrettably, the utilization of electronic toll collection (ETC) data on expressways is currently not adequate, and data analysis and feature mining methods are underdeveloped, leading to the undervaluation of data potential. Focusing on ETC data from expressways, this study deeply analyzes the spatiotemporal characteristics of travel by passenger car users. Here, we propose an advanced user classification model by combining the traditional clustering algorithm with the feature grouping recognition model based on a back propagation neural network (BPNN) algorithm. Real-world data on expressway vehicle travel are used to validate our models. The results show a significant improvement in iteration efficiency of over 26.4% and a 23.17% accuracy improvement compared to traditional algorithms. The travel feature grouping recognition model yielded an accuracy of 95.23%. Furthermore, among the identified groups, such as “Public and commercial affairs” and “Commuting”, there is a notable characteristic of high travel frequency and concentrated travel periods. This indicates that these groups have placed significant pressure on the construction of a safe, efficient, and sustainable urban transportation system.
Use of Waste Tires as Transverse Reinforcement and External Confinement in Concrete Columns Subjected to Axial Loads
Authors: Mahat Mahesh , Acharya Mahesh , Acharya Manish , Mashal Mustafa
Published: July 2023

Approximately 246 million waste tires are generated annually in the United States. That is roughly three tires per four individuals in the country. Most tires end up in landfills, adversely affecting the environment. In the last two decades, researchers have explored using tire chips in concrete to replace a portion of coarse aggregates. Past studies have indicated that up to 50% of coarse aggregates in concrete can be replaced with tire chips. This research proposes using recycled rubber tires and rubber chips in concrete columns. The tires are used as external transverse reinforcement in plain concrete columns. The tires function as formwork during the pour while providing confinement after curing. The concepts in this research can be used for retrofitting structures with inadequate foundations and constructing new structures. After analyzing the data from this research, the axial compressive test of confined columns was 50% greater on average than unconfined columns. The confinement effectiveness ratio for all confined specimens was greater than one.
Work-Life Balance and Employee Satisfaction during COVID-19 Pandemic
Authors: Bocean Claudiu George , Popescu Luminita , Varzaru Anca Antoaneta , Avram Costin Daniel , Iancu Anica
Published: July 2023

The concept of work-life balance derives from the vision that professional life and personal life are two elements that balance each other synergistically in the development of an individual. Work-life balance can positively and negatively influence employees’ performance through employee satisfaction. Using the structural equation modeling (SEM) method (partial least squares), we empirically analyzed the work-life balance of a sample of 452 employees in Romania. The study highlights that work-life equilibrium or disequilibrium significantly affects professional and personal satisfaction, influencing employee motivation and turnover intention. Following the empirical study, we found that a state of balance between professional and personal life generates satisfaction, a higher degree of motivation, increased performance, and reduced employee turnover.
Sustainability Management through Corporate Social Responsibility Activities in the Life Insurance Industry: Lessons from the Success Story of Kyobo Life Insurance in Korea
Authors: Ahn Young Back , Park Hyun Chae
Published: July 2023

The current reality is that Korean insurance companies primarily focus on simplistic social contribution activities, such as making donations, rather than attaining sustainable management practices. So based on the case study methodology, this study examines the CSR activities of Kyobo Life Insurance for sustainable management and investigates how corporate values are aligned with the nature of the industry. The research analyzes Kyobo Life Insurance’s CSR initiatives across three dimensions: environmental, social, and economic, with a focus on sustainable management. The analysis identifies three distinct CSR characteristics of Kyobo Life Insurance. Firstly, the company demonstrates more active engagement in social initiatives compared to the environmental and economic aspects. Secondly, while prioritizing sustainable management through collaborative efforts with major stakeholders, the company exhibits a relatively greater emphasis on CSR activities targeting internal stakeholders. Lastly, since 2011, the company has been an industry leader in annually publishing sustainable management reports, showcasing its commitment to stakeholder communication and co-prosperity. The study suggests that life insurance companies should enhance their CSR activities to ensure greater sustainability and effectiveness while also providing guidance for companies to adapt to evolving industrial landscapes.
A Systematic Review of the Bioactivity of Jatropha curcas L. (Euphorbiaceae) Extracts in the Control of Insect Pests
Authors: Valdez-Ramirez Armando , Flores-Macias Antonio , Figueroa-Brito Rodolfo , Torre-Hernandez Maria E. de la , Ramos-Lopez Miguel A. , Beltran-Ontiveros Saul A. , Becerril-Camacho Delia M. , Diaz Daniel
Published: July 2023

The use of botanical extracts of the plant Jatropha curcas (Euphorbiaceae) represents a valuable alternative to control insect pests and avoid the detrimental effects on the environment and health that arise due to synthetic chemical insecticides. Thus, we conducted a systematic review to summarize the published evidence on the bioactivity of J. curcas against insect pests. Electronic databases were searched to identify studies that assessed J. curcas extracts against insect pests in various types of crops. We included 39 articles that reported the insecticidal and insectistatic activity of several botanical extracts from J. curcas against insects of eight different taxonomic orders. The evidence demonstrates that aqueous and methanolic extracts from seeds and leaves, seed oil, and petroleum ether seed extracts were effective against insect pests of stored grains, aphids of cabbage and sorghum, fruit flies, and desert locusts. The extracts caused high mortality, controlled the populations, reduced oviposition, diminished hatchability, and increased the antifeedant effect. However, the type of solvent used to obtain the botanical extract and the method of application (contact or food) are fundamental to increase its bioactivity. Therefore, botanical extracts from seeds and leaves of J. curcas should be considered as an alternative against insect pests and may be incorporated into integrative and sustainable management for insect control.
Novel TIλDND2N2 Controller Application with Equilibrium Optimizer for Automatic Voltage Regulator
Authors: Tabak Abdulsamed
Published: July 2023

Sustainability is important in voltage regulation control in grids and must be done successfully. In this paper, a novel tilt-fractional order integral-derivative with a second order derivative and low-pass filters controller, referred to as TIλDND2N2 controller, is proposed to enhance the control performance of an automatic voltage regulator (AVR). In this article, the equilibrium optimizer (EO) algorithm is used to optimally determine the eight parameters of the proposed controller. In this study, a function consisting of time domain specifications is used as the objective function. To evaluate the performance of the proposed controller, it is compared with the proportional-integral-derivative (PID), fractional order PID (FOPID), PID accelerator (PIDA), PID plus second order derivative (PIDD2), and hybrid controllers used in previous studies. Then, Bode analysis is performed to determine the achievement of the proposed controller in the frequency domain. Finally, the robustness test is realized to assess the response of the proposed controller against the deterioration of the system parameters. As a result, the proposed controller demonstrates outstanding control performance compared to studies in terms of settling time, rise time and overshoot. The proposed controller shows superior performance not only in frequency domain analysis but also in perturbed system parameters.
A Computational Fluid Dynamics Modelling Approach for the Numerical Verification of the Bioclimatic Design of a Public Urban Area in Greece
Authors: Stavrakakis George M. , Katsaprakakis Dimitris A. , Braimakis Konstantinos
Published: July 2023

Recent recordings of urban overheating reveal a dramatic increase in cities’ population exposure to heatwaves. Heatwaves’ implications are escalated in urban environments due to the intensification of the Urban Heat Island (UHI) effect. To combat the overheating and UHI adverse effects, novel urban rehabilitation actions are needed based on reliable predictions of appropriate Key Performance Indicators (KPIs) (such as pedestrian-level air temperature and thermal comfort) for alternative design scenarios. The objective of the current study is to present the application of a previously developed Computational Fluid Dynamics (CFD) model for the calculation of urban microclimatic conditions for the assessment of the UHI and thermal-comfort conditions in a central urban area in the city of Heraklion in Crete, Greece. Empirical validation of the model is performed through comparisons with monitored microclimate data (i.e., air temperature, relative humidity, wind speed) and actual sensation vote recordings found in another research study. In compliance with the latter, the validation campaign is conducted for a typical hot summer day in July 2009 from 10:00 to 16:00. The model is then used to assess the UHI effects for both the existing urban configuration and a given suggested environmental upgrade of the space. Simulations of the existing situation reveal that the squares located in the studied area already stand for efficient resistances to urban overheating, and heat vulnerabilities are detected mainly in non-shaded traffic and pedestrian roads perimetric to the squares. Based on the CFD simulations, the suggested environmental upgrading plan exhibits a reduction in the peak mean air temperature of 0.46 °C, and thermal comfort is improved by at least 5% (based on SET) throughout the studied area in summer. At the same time, simulations of winter conditions suggest that there are limited potential pedestrian thermal-sensation and building heating penalties under the considered renovation scenario.
Modeling Impacts of Implementation Policies of Tradable Credit Schemes on Traffic Congestion in the Context of Traveler’s Cognitive Illusion
Authors: Han Fei , Wang Jian , Huang Lingli , Li Yan , He Liu
Published: July 2023

A tradable credit scheme (TCS) is a novel traffic demand management (TDM) measure that can effectively mitigate traffic congestion in a revenue-neutral way. Under a given TCS, the cognitive illusion (CI) would occur when travelers instinctively use a specious thinking logic to estimate travel cost. The traveler’s CI would significantly influence his/her route choice behaviors, and thus the regulation effect of TCS on mitigating traffic congestion. To reveal the impacts of implementation policies of TCS on managing network mobility in the context of the traveler’s CI, this study investigated the traffic equilibrium assignment model with consideration of the traveler’s CI and the specific implementation policies of TCS. By incorporating the two types of factors into the generalized path travel cost (GPTC), the coupled user equilibrium (UE) and market equilibrium (ME) conditions are established to describe the equilibrium state of the traffic network under a given TCS. As the implementation policies of TCS are factored in the GPTC, different types of initial credit distribution scheme (ICDS) and the transaction costs (TC) of trading credits can be analyzed within the unified model framework. The coupled UE and ME conditions are then reformulated as an equivalent variational inequality (VI) model, and the sufficient conditions for the uniqueness of UE link flows and ME credit price are also provided. The system optimal (SO) TCS design problem is further investigated to achieve the minimum total travel time (TTT) of the transportation network, and two analytical methods are proposed to obtain the SO TCS in the context of the traveler’s CI. Numerical experiments are presented to verify the proposed model and methods. The results show that the presence of the traveler’s CI has an effect of lowering the ME credit price, and ICDS and TC have a complex network-wide influence on the ME credit price and UE link flows, which depends on the specific values of the relevant parameters.
Comparative Phycoremediation Performance of Three Microalgae Species in Two Different Magnitude of Pollutants in Wastewater from Farmhouse
Authors: La Bella Emanuele La , Occhipinti Paride Salvatore , Puglisi Ivana , Fragalà Ferdinando , Saccone Rossella , Russo Nunziatina , Randazzo Cinzia Lucia , Caggia Cinzia , Baglieri Andrea
Published: July 2023

The cultivation of microalgae using urban wastewater as a nutrient substrate represents a promising bio-refinery concept that can serve multiple purposes; indeed, it allows for the generation of biomass, which can be used for various applications while meanwhile removing nutrients from wastewater. In this study, the potential of urban wastewater collected at two different time periods in a farmhouse as a nutrient substrate for microalgal growth was assessed. Wastewater samples were treated on a laboratory scale, inoculating reactors with two common species, Chlorella vulgaris (CV) and Scenedesmus quadricauda (SQ), and with an autochthonous strain of Klebsormidium sp. K39 (Kleb), directly isolated from effluents of the same system. The main aim of the study was to compare the microalgae’s performances in terms of wastewater re-mediation and biomass productivity. In the first case study, which involved an effluent with a lower pollutant level, microalgal cultivation showed removal efficiencies in the range of 57–63% for total nitrogen, 65–92% for total phosphorous, 94–95% for COD, and 100% for E. coli. In the second case study, involving an effluent with a higher pollutant level, the remediation performances of the three microalgae strains ranged from 93 to 96% for total nitrogen, from 62 to 74% for total phosphorous, from 96 to 97% for COD, and 100% for E. coli. At the end of the experimental trials, treated waters showed values of pollutants suitable for irrigation use, in accordance with environmental and national legislation, which established specific thresholds for irrigation purposes.
Identification of Limestone Aquifer Inrush Water Sources in Different Geological Ages Based on Trace Components
Authors: Shi Longqing , Ma Xiaoxuan , Han Jin , Su Baocheng
Published: July 2023

In the process of mining Carboniferous coal resources in China’s coal mines, catastrophic water inrush from the floor often occurs. The water inrush source is mainly the fifth limestone aquifer of Carboniferous or Ordovician limestone aquifers. Conventional elements cannot effectively identify the source of water inrush as limestone aquifers of different geological ages. Against the background of floor water inrush in Baizhuang Coal Mine in Feicheng Coalfield, water samples of the fifth-layer limestone aquifer, Ordovician limestone aquifer and water inrush point water samples of Feicheng Coalfield were collected. Trace components F−, Br−, I−, H3BO3 and Rn were selected for compositional analysis. The minimum deviation method was used to combine and weight the weights obtained by the entropy weight method, principal component analysis method and analytic hierarchy method. An improved grey correlation model was established for water inrush source identification. The model discrimination result shows that the water inrush source comes from the Ordovician limestone aquifer, and the discrimination accuracy is high.
Unveiling the Presence of Social Prescribing in Romania in the Context of Sustainable Healthcare—A Scoping Review
Authors: Surugiu Roxana , Iancu Mihaela Adela , Lăcătus Anca Maria , Dogaru Carmen Adriana , Stepan Mioara Desdemona , Eremia Irina Anca , Neculau Andrea Elena , Dumitra Gheorghe Gindrovel
Published: July 2023

Background: Social prescribing initiatives are tailored coaching programs created to assist participants in improving their personal circumstances and might constitute a creative way to enhance public and preventive health as we work toward providing universal financially sustainable healthcare. Methods: We conducted a scoping review with the aim of summarizing the main global trends on social prescribing and to identify the existing resources and potential targets of social prescribing in Romania. Results: One of the main concerns that arose from this review is the lack of defined pathways to access social programs and the lack of link workers, recognized as a valuable form of support in directing people toward the most appropriate intervention, necessary to increase long-term sustainability. We also acknowledge the importance of primary care in social prescribing, especially in prevention. The level of awareness and the capacity of primary care providers to identify the need for social prescription to increase the awareness of resources and encourage teamwork should be increased. Conclusions: By focusing on these areas, we can enhance the health and well-being of the population and fully realize the benefits of social prescribing in Romania. Further research and collaboration on social prescribing are crucial for optimizing its impact in Romania.
GEV Analysis of Extreme Rainfall: Comparing Different Time Intervals to Analyse Model Response in Terms of Return Levels in the Study Area of Central Italy
Authors: Gentilucci Matteo , Rossi Alessandro , Pelagagge Niccolò , Aringoli Domenico , Barbieri Maurizio , Pambianchi Gilberto
Published: July 2023

The extreme rainfall events of recent years in central Italy are producing an increase in hydrogeological risk, with disastrous flooding in terms of human lives and economic losses, as well as triggering landslide phenomena in correspondence with these events. A correct prediction of 100-year return levels could encourage better land planning, sizing works correctly according to the expected extreme events and managing emergencies more consciously through real-time alerts. In the recent period, it has been observed that the return levels predicted by the main forecasting methods for extreme rainfall events have turned out to be lower than observed within a few years. In this context, a model widely used in the literature, the generalised extreme value (GEV) with the “block maxima” approach, was used to assess the dependence of this model on the length of the collected precipitation time series and the possible addition of years with extreme events of great intensity. A total of 131 rainfall time series were collected from the Adriatic slope in central Italy comparing two periods: one characterised by 70 years of observations (1951–2020), the other by only 30 years (1991–2020). At the same time, a decision was made to analyse what the effect might be—in terms of the 100-year return level—of introducing an additional extreme event to the 1991–2020 historical series, in this case an event that actually occurred in the area on 15 September 2022. The results obtained were rather surprising, with a clear indication that the values of the 100-year return level calculated by GEV vary according to the length of the historical series examined. In particular, the shorter time series 1991–2020 provided higher return level values than those obtained from the 1951–2020 period; furthermore, the addition of the extreme event of 2022 generated even higher return level values. It follows that, as shown by the extreme precipitation events that have occurred in recent years, it is more appropriate to consider a rather short period because the ongoing climate change does not allow true estimates to be obtained using longer time series, which are preferred in the scientific literature, or possibly questioning the real reliability of the GEV model.
International Trade and Carbon Emissions: Evaluating the Role of Trade Rule Uncertainty
Authors: Zhao Xinwei , Yang Xinsong , Peng Geng , Yue Shengjie
Published: July 2023

Based on textual data mining methods and global English articles, we develop an index for measuring the uncertainty of international trade rules and evaluating the role of trade rule uncertainty in the relationship between international trade and carbon emissions, via a mediating effect model. The empirical results show that: (1) Increasing trade volume in developing countries contributes to a rise in trade rule uncertainty, which in turn triggers trade conflicts and even trade wars between countries. (2) There are significant correlations between international trade and carbon emissions, and international trade impacts carbon emissions in both direct and indirect ways. (3) Trade rule uncertainty plays a mediating role in the relationship between international trade and carbon emissions. (4) Trade rule uncertainty significantly impacts carbon emissions in most developed and developing countries, but the impact is not significant in the USA. Our work not only contributes to extending measurements of uncertainty but also helps to quantify the impacts of trade rule uncertainty on carbon emissions.
On Carbon Tax Effectiveness in Inducing a Clean Technology Transition: An Evaluation Based on Optimal Strategic Capacity Planning
Authors: Wolf Nathalia , Escalona Pablo , López-Campos Mónica , Angulo Alejandro , Weston Jorge
Published: July 2023

This paper studies carbon tax effectiveness in inducing a transition to cleaner production when a firm faces different technologies and demands over a planning horizon. To determine carbon tax effectiveness, we propose a model based on strategic capacity production planning under carbon taxes that considers proper performance measures. The model, which is formulated as a mixed integer linear problem (MILP), considers issues that previous works have not studied jointly, and that are relevant in a technological transition, such as machine replacement, workforce planning, and maintenance. The effectiveness measures consider levels of clean production and periods to reach a technological transition. Our computational experiments, based on a real case, have shown that in the absence of carbon taxes, a firm has no incentive to transition to clean technology. Still, the effectiveness of carbon taxes depends on the characteristics of the technology available for the production process and the magnitude of the demand. We include managerial insights aimed at both companies and the environmental authority.
Research on Peak Load Prediction of Distribution Network Lines Based on Prophet-LSTM Model
Authors: Chen Zhoufan , Wang Congmin , Lv Longjin , Fan Liangzhong , Wen Shiting , Xiang Zhengtao
Published: July 2023

The increasing demand for precise load forecasting for distribution networks has become a crucial requirement due to the continual surge in power consumption. Accurate forecasting of peak loads for distribution networks is paramount to ensure that power grids operate smoothly and to optimize their configuration. Many load forecasting methods do not meet the requirements for accurate data and trend fitting. To address these issues, this paper presents a novel forecasting model called Prophet-LSTM, which combines the strengths of the Prophet model’s high trend fitting and LSTM model’s high prediction accuracy, resulting in improved accuracy and effectiveness of peak load forecasting. The proposed algorithm models the distribution network peak load using the Prophet-LSTM algorithm. The researchers then analyzed the experimental data and model of the algorithm to evaluate its effectiveness. We found that the Prophet-LSTM algorithm outperformed the Prophet and LSTM models individually in peak load prediction. We evaluate the proposed model against commonly used forecasting models using MAE (mean absolute error) and RMSE (root mean square error) as evaluation metrics. The results indicate that the proposed model has better forecasting accuracy and stability. As a result, it can predict the peak load of distribution networks more accurately. In conclusion, this study offers a valuable contribution to load forecasting for distribution networks. The proposed Prophet-LSTM algorithm provides a more precise and stable prediction, making it a promising approach for future applications in distribution network load forecasting.
Living Wall Plants Are Affected by and Affect Temperature: How to (not) Measure Plants’ Temperature in a Living Wall Experiment
Authors: Stollberg Maren , von Birgelen Alexander
Published: July 2023

Living walls (LWs) are a climate change adaptation strategy for cities, as they have a cooling effect. Previous studies of the cooling effect of LWs were carried out in different climatic zones. These studies differed in their experimental design, or simulated data via models. Plants’ cooling capacity is explained by shading and transpiration, and depends on physical plant parameters, environmental factors, and system-related influences. A three-year-long trial was carried out between 2017 and 2019 at an experimental garden in Geisenheim, Germany. We chose a textile-based LW system with high water demand and plants from a wet/fresh habitat. We assumed that this would achieve high evaporative cooling. The experimental setup included four experimental walls, which were exposed to the north, south, east, and west, respectively. The plant choice was divided into three plant mix variants (Cascade, Ground cover, and Meadow) and a Control with no vegetation. We measured the temperature with sensors and a thermal imaging (IR) camera in different setups. The main results were that the measured vegetation temperature (TV) depends on air temperature (TA), measurement position, plant mix variant, and plant species. We could detect the cooling effect only at a small distance from the LW (microclimatic). Our methodological approaches should be continued in further studies.
Does Direct Monetary Policy Affect the Supply of Bank Credit to Small and Medium-Sized Enterprises? An Analysis Based on Chinese Data
Authors: Jiang Ruishi , Ruan Jia
Published: July 2023

In order to develop the real economy and solve the problems of enterprise financing and lending, banks should increase their support for SMEs (small and medium-sized enterprises). The People’s Bank of China introduced two direct monetary policy tools in June 2020, which are important for alleviating the financing problems of SMEs, improving the construction of financial support for the real economy and promoting the recovery of economic development. This paper manually collects annual data on the loan balances of SMEs from listed commercial banks in China from 2011 to 2021, and it empirically tests the implementation effects of the direct monetary policy tools using the double-difference model and the moderating effect model. The results of the study indicate that the implementation of the direct monetary policy tools can increase the credit supply of commercial banks to SMEs. The moderating effect of digital inclusive finance on the impact of direct monetary policy on the credit supply of SMEs is not statistically significant for the time being. Therefore, it is necessary to improve the transmission mechanism of structural monetary policy, establish a sustainable development mechanism for digital inclusive finance, and guide commercial banks to improve their capital strength and profitability so that structural monetary policy tools can be most effective.
The Restorative and Contingent Value of Biophilic Indoor Environments in Healthcare Settings
Authors: Lan Yuxiang , Liu Qunyue
Published: July 2023

During the COVID-19 pandemic, individuals undergoing healthcare-related quarantine often experience heightened anxiety and stress. While biophilic indoor environments have shown potential in reducing stress, their effectiveness within healthcare quarantine settings remains uncertain. Additionally, the economic value associated with implementing biophilic interventions in healthcare environments remains largely unknown. This study aimed to explore the effects of biophilic interventions in indoor quarantine environments on the perceived outcomes of individuals (such as preference, perceived restorativeness, and satisfaction) and their willingness-to-pay (WTP). Participants were asked to imagine themselves in quarantine and were subsequently assigned to one of four indoor rooms, each featuring a different level of biophilic intervention (non-biophilic, low, medium, and high indoor green). Their perceived outcomes and WTP were then evaluated. The findings consistently demonstrated that incorporating biophilic interventions had a significantly positive impact on perceived outcomes and WTP compared with non-biophilic interventions within healthcare quarantine settings. Among the three levels of biophilic intervention, high indoor green spaces had the highest influence, while low indoor green spaces had the lowest. Moreover, perceived restorativeness consistently played a role in influencing WTP across all three biophilic indoor rooms. Further analysis indicated that a medium level of biophilic intervention would be more advantageous and practical in the design of healthcare indoor environments. This study offers valuable insights into both the monetary and nonmonetary values of biophilic interventions in healthcare settings, aiding designers in selecting appropriate biophilic designs to create enhanced restorative indoor environments.
The Impact of Green Institutional Pressure from Local Governments on Corporate Innovation: An Empirical Evidence from Foreign-Invested Enterprises in China
Authors: Xue Dingqi , Ding Yili , Yu Lu , Deng Xinghua
Published: July 2023

The natural environment of the human world has been deteriorating over the past few decades, and policies to protect the environment are receiving increasing attention from governments worldwide. The question of how green institutional pressures from local governments impact corporate behaviors, especially innovation behaviors, is a critical issue. However, the link between local governments’ institutional pressures and corporate innovative behaviors remains a matter of some dispute. This paper compiles data from foreign-invested enterprises in China, using the frequency of green development terms in the Chinese local governments’ annual reports as a key variable, and discusses the influence of local governments’ green institutional pressure on corporate innovation. The conclusions of this paper demonstrate that local governments’ institutional pressure has a promoting effect on corporate innovation, while the home country’s level of green knowledge reservoir has a negative moderating effect on this influence. Moreover, this conclusion exhibits heterogeneity across corporate nature, industry attributes, location characteristics, export experience and home country type.
Transformative Role of Artificial Intelligence in Advancing Sustainable Tomato (Solanum lycopersicum) Disease Management for Global Food Security: A Comprehensive Review
Authors: Sundararaman Bharathwaaj , Jagdev Siddhant , Khatri Narendra
Published: July 2023

The growing global population and accompanying increase in food demand has put pressure on agriculture to produce higher yields in the face of numerous challenges, including plant diseases. Tomato is a widely cultivated and essential food crop that is particularly susceptible to disease, resulting in significant economic losses and hindrances to food security. Recently, Artificial Intelligence (AI) has emerged as a promising tool for detecting and classifying tomato leaf diseases with exceptional accuracy and efficiency, empowering farmers to take proactive measures to prevent crop damage and production loss. AI algorithms are capable of processing vast amounts of data objectively and without human bias, making them a potent tool for detecting even subtle variations in plant diseases that traditional techniques might miss. This paper provides a comprehensive overview of the most recent advancements in tomato leaf disease classification using Machine Learning (ML) and Deep Learning (DL) techniques, with an emphasis on how these approaches can enhance the accuracy and effectiveness of disease classification. Several ML and DL models, including convolutional neural networks (CNN), are evaluated for tomato leaf disease classification. This review paper highlights the various features and techniques used in data acquisition as well as evaluation metrics employed to assess the performance of these models. Moreover, this paper emphasizes how AI techniques can address the limitations of traditional techniques in tomato leaf disease classification, leading to improved crop yields and more efficient management techniques, ultimately contributing to global food security. This review paper concludes by outlining the limitations of recent research and proposing new research directions in the field of AI-assisted tomato leaf disease classification. These insights will be of significant value to researchers and professionals interested in utilizing ML and DL techniques for tomato leaf disease classification and ultimately contribute to sustainable food production (SDG-3).
The Hyperbolic Ptolemy’s Theorem in the Poincaré Ball Model of Analytic Hyperbolic Geometry
Authors: Ungar Abraham A.
Published: July 2023

Ptolemy’s theorem in Euclidean geometry, named after the Greek astronomer and mathematician Claudius Ptolemy, is well known. We translate Ptolemy’s theorem from analytic Euclidean geometry into the Poincaré ball model of analytic hyperbolic geometry, which is based on the Möbius addition and its associated symmetry gyrogroup. The translation of Ptolemy’s theorem from Euclidean geometry into hyperbolic geometry is achieved by means of hyperbolic trigonometry, called gyrotrigonometry, to which the Poincaré ball model gives rise, and by means of the duality of trigonometry and gyrotrigonometry.
Prevention of Wave Propagation via Circular Arrangement of Seismic Metamaterials Formed with Concrete Piles
Authors: Kaçın Selcuk , Özturk Murat , Sevim Umur Korkut , Karaaslan Muharrem , Akgöl Oğuzhan , Özer Zafer , Demirci Mustafa , Ünal Emin , Mert Bayram Ali , Alkurt Maide Erdoğan , Alkurt Fatih Özkan , Başar Mustafa Tunahan , Kaya Şeyda Gülsüm
Published: July 2023

It is known that the low frequencies of seismic surface waves have a destructive effect. The main purpose of seismic metamaterials is to protect structures from seismic waves at low frequencies, especially in a wide band. In this study, the effects of seismic metamaterials formed using circular array concrete piles on surface waves were investigated. Each concrete pile has been selected due to symmetric properties to investigate the band diagram. Therefore, the direction independence can also be determined with respect to frequency. This study was conducted both numerically and experimentally in the low-frequency range of 5–15 Hz. Two fields, with and without metamaterials, have been designed and compared. In numerical analysis, transmission loss graphs were drawn using the finite element method (FEM), and wave propagation at frequencies where the loss happened was simulated. In numerical analysis, optimum dimensions such as radius and depth were determined, and these dimensions were applied exactly in the experimental field. The results obtained from the experiment using a harmonic vibration device are mapped. In this numerical and experimental study, it has been revealed that the proposed structure prevents the propagation of seismic surface waves.