bluuebunny/crossref_metadata_2025 huggingface dataset:
Crop Water Requirements with Changing Climate in an Arid Region of Saudi Arabia
Authors: Haq Mohd Anul , Khan Mohd Yawar Ali
Published: October 2022

Agriculture is critical for a country’s population growth and economic expansion. In Saudi Arabia (SA), agriculture relies on groundwater, seasonal water, desalinated water, and recycled water due to a lack of surface water resources, a dry environment, and scanty rainfall. Estimating water consumption to plan crop water requirements (CWR) in changing environments is difficult due to a lack of micro-level data on water consumption, particularly in agricultural systems. High-resolution satellite data combined with environmental data provides a valuable tool for computing the CWR. This study aimed to estimate the CWR with a greater spatial and temporal resolution and localized field data and environmental variables. Obtaining this at the field level is appropriate, but geospatial technology can produce repeatable, time-series phenomena and align with environmental data for wider coverage regions. The CWR in the study area has been investigated through two methods: firstly, based on the high-resolution PlanetScope (PS) data, and secondly, using the FAO CROPWAT model v8.0. The analysis revealed that evapotranspiration (ETo) showed a minimum response of 2.22 mm/day in January to a maximum of 6.13 mm/day in July, with high temperatures (42.8). The humidity reaches a peak of 51%, falling to a minimum in June of 15%. Annual CWR values (in mm) for seven crops studied in the present investigation, including date palm, wheat, citrus, maize, barley, clover, and vegetables, were 1377, 296, 964, 275, 259, 1077, 214, respectively. The monthly averaged CWR derived using PS showed a higher correlation (r = 0.83) with CROPWAT model results. The study was promising and highlighted that such analysis is decisive and can be implemented in any region by using Machine Learning and Deep Learning for in-depth insights.
Patterns of Influence of Parallel Rock Fractures on the Mechanical Properties of the Rock–Coal Combined Body
Authors: Li Yakang , Liu Jiangwei , Yu Qian
Published: October 2022

Hydraulic fracturing of a roof can attenuate the strong mineral pressure and stress transfer by creating a series of parallel artificial fractures in it, and different forms of hydraulic parallel fractures have different effects on the attenuation effect of the coal rock system. In this regard, this study investigated the influence law of different forms of parallel pre-cracks on the mechanical properties of a rock–coal combined body through PFC2D numerical simulation, and the following conclusions were obtained. Parallel pre-cracks significantly affected the mechanical properties of the rock–coal combined body. The stress–strain curve of the coal–rock assemblage containing Parallel pre-cracks changes significantly following reductions in peak strength, peak strain, elastic modulus, and crack initiation stress. The closer the angle θ between the single set of parallel pre-cracks and the horizontal is to 30°, the longer the length, L, and the lower the peak strength of the specimen, the peak strain, the modulus of elasticity, and the crack initiation stress. Macroscopic damage patterns are given for a rock–coal combined body containing single sets of parallel pre-cracks of different parameters, with coal sample damage, coal–rock sample damage and rock sample damage; a rock–coal combined body containing parallel pre-cracks is divided into three modes of fracture initiation when pressurized. These are the cracking of the coal sample, the simultaneous cracking of the parallel pre-crack tips in coal and rock samples, and the cracking of the parallel pre-crack tips in rock samples.
A Hybrid Fuzzy MCDM Methodology for Optimal Structural System Selection Compatible with Sustainable Materials in Mass-Housing Projects
Authors: Aghazadeh Ebrahim , Yildirim Hasan , Kuruoglu Murat
Published: October 2022

The present paper aimed to propose a new support approach to choosing the optimal structural system in accordance with sustainable materials in mass-housing projects. To this end, an integrated fuzzy multi-criteria-decision-making (fuzzy MCDM) method was used to identify the criteria affecting sustainable material selection. The proposed approach consists of a three-phase protocol: In phase I, the literature was used to create a database encompassing 42 factors affecting the selection of materials. These factors were classified as four indicators (economic, environmental, socio-cultural, technical-executive) in accordance with the sustainable development aspects. In phase II, the fuzzy Delphi method (FDM) was used to screen the key factors. In phase III, an integrated fuzzy SWARA–ARAS method was used to prioritize the optimal structural system for a case project: evidence from Iran. The results of selecting the structural systems based on 14 efficient key factors showed that the Light Steel Frame (LSF), Insulation Concrete framework (ICF), and the Prefabricated Reinforced Concrete System (PRC) systems have the highest priority to achieve the goals of sustainable material selection, respectively.
Are We Taking Off? A Critical Review of Urban Aerial Cable Cars as an Integrated Part of Sustainable Transport
Authors: Flesser Morten , Friedrich Bernhard
Published: October 2022

The overall growth of the world’s population and urbanization lead to rethinking transport planning, further developing the conventional transport systems, and complementing new ones usefully, especially in urban environments. One way to cope with this challenge is to leave behind the already severely saturated urban land use model and move to the third dimension. This includes the use of urban aerial cable cars, which can complement conventional public transport in certain transport relations. Accordingly, this paper aims to answer how the recent, past, or planned implementations of urban aerial cable cars are assessed in the scientific literature, what open research questions need to be answered to enhance the success of transport systems, and what the chances are of cable cars becoming a standard part of transport planners’ repertoires. Following systematic literature review methods, 54 studies from different databases were identified and processed in a multi-stage procedure to provide transparent insight into the relevant literature. The results, especially concerning urban and transport integration, are discussed in detail, emphasizing that cable cars have already partially found their niche, but their role in the urban environment has not yet been sufficiently studied. In conclusion, the study’s originality fills the gap in providing a review of urban aerial cable cars from a transport planning perspective by systematically considering today’s globally available literature.
The Integrated Production-Inventory-Routing Problem with Reverse Logistics and Remanufacturing: A Two-Phase Decomposition Heuristic
Authors: Chekoubi Zakaria , Trabelsi Wajdi , Sauer Nathalie , Majdouline Ilias
Published: October 2022

Sustainable supply chains depend on three critical decisions: production, inventory management, and distribution with reverse flows. To achieve an effective level of operational performance, policymakers must consider all these decisions, especially in Closed-Loop Supply Chains (CLSCs) with remanufacturing option. In this research paper, we address the Integrated Production-Inventory-Routing Problem with Remanufacturing (IPIRP-R) of returned End-Of-Life (EOL) products. The aim behind solving this optimization problem is to minimize conjointly the total manufacturing, remanufacturing, setup, inventory, and routing costs over the planning horizon. A two-phase decomposition heuristic is developed to solve the model iteratively. Our study finds its originality in the fact of jointly optimizing the Capacitated Lot-Sizing Problem with Remanufacturing (CLSP-R) option and the Vehicle Routing Problem with Simultaneous Pick-up and Delivery (VRPSPD) in a single framework. Numerical results showed that our solution approach provides good solutions regarding small and medium-scale size instances under acceptable computational time, especially for problems occurring with significant manufacturing and remanufacturing costs under relatively low pickup requests.
Does Innovative Industrial Agglomeration Promote Environmentally-Friendly Development? Evidence from Chinese Prefecture-Level Cities
Authors: Li Chuang , Liu Qingqing , Li Qing , Wang Hailing
Published: October 2022

China has promised to meet the “carbon peaking and carbon neutrality” goals. Exploring the relationship between innovative industrial agglomeration and environmental pollution plays an important role in the realization of these goals and sustainable development. Based on the panel data of 277 prefecture-level cities in China from 2007 to 2019, this paper uses the multi-period difference-in-difference (DID) model to examine the impact and mechanism of the innovative industrial agglomeration pilot (IIAP) policy on the environment. Furthermore, we explore the spatial effect of the IIAP using spatial DID. The findings show that, firstly, the IIAP policy significantly contributes to environmentally-friendly development in terms of enhancing carbon emission efficiency (CEE) and reducing environmental pollution index (EPI). Secondly, the IIAP policy promotes environmentally-friendly development mainly by improving the technological innovation level. Additionally, the heterogeneity analysis shows that the environmentally-friendly effect of the IIAP policy is primarily in the eastern region, large cities, and non-resource-based cities. Finally, there is a significant spatial effect of the IIAP policy on environmentally-friendly development, mainly reflected in the weak siphon effect between treatment group cities and neighboring regions. We suggest that the government should continue to maintain the steady growth of the IIAP cities and improve the energy utilization efficiency through a policy of green technology innovation. The government should also optimize the spatial layout of the pilot cities and make full use of the energy advantages of each region to better promote environmentally-friendly development.
Selective Isolation of Bioactive-Pigmented Bacteria from Saline Agricultural Soil and Assessment of Their Antimicrobial Potential against Plant Pathogens
Authors: Bashir Samina , Numan Muhammad , Shinwari Zabta Khan
Published: October 2022

The high incidence of disease and pests and their resistance to chemical control agents pose serious threats to both the agriculture sector and the environment. The present study assessed the antagonistic potential of bioactive pigment-producing bacteria isolated from the saline agricultural fields of Gujrat, Pakistan, against plant pathogenic fungi and bacteria. The seeded agar overlay method was used to selectively isolate bioactive pigment-producing colonies. Isolates were identified as Nonomurae salmonae, Streptomyces chromofuscus, and Actinocorallia libanotica using 16S rRNA gene sequence analysis. All the isolates and their crude pigment extracts were screened to assess antifungal activity against five fungal phytopathogens, namely Fusarium oxysporum (F. oxysporum), Fusarium solani (F. solani), Aspergillus flavus (A. flavus), Aspergillus niger (A. niger), and Alternaria alternata (A. alternata), as well as two bacterial phytopathogens, namely Psuedomonas syringae (P. syringae) and Xanthomonas axonopodis (X. axonopodis). Of these, Streptomyces chromofuscus was found to be active against most of the fungal and bacterial phytopathogens tested, followed by Nonomurae salmonae. Actinocorallia libanotica showed little to no activity against the tested microbes. Nonomurae salmonae and Actinocorallia libanotica are rare actinomycetes and the current study is the first to assess their antimicrobial activity against plant pathogens, specifically, plant pathogenic bacteria, i.e., P. syringae and X. axonopodis. The isolation of these species suggests that the chances of the isolation of rare species of microbes, which can serve as promising new sources of bioactive compounds, can be increased by using enhanced techniques for isolation. The results of this preliminary study assessing the antagonistic effect of bioactive pigment-producing bacterial isolates against plant pathogens are encouraging, and suggest a detailed research on the modes of action, optimum working conditions, and active components involved in an antagonism of these bioactive pigment-producing bacteria.
Solid Waste Generation and Disposal Using Machine Learning Approaches: A Survey of Solutions and Challenges
Authors: Namoun Abdallah , Tufail Ali , Khan Muhammad Yasar , Alrehaili Ahmed , Syed Toqeer Ali , BenRhouma Oussama
Published: October 2022

We present a survey of machine learning works that attempt to organize the process flow of waste management in smart cities. Unlike past reviews, we focused on the waste generation and disposal phases in which citizens, households, and municipalities try to eliminate their solid waste by applying intelligent computational models. To this end, we synthesized and reviewed 42 articles published between 2010 and 2021. We retrieved the selected studies from six major academic research databases. Next, we deployed a comprehensive data extraction strategy focusing on the objectives of studies, trends of ML adoption, waste datasets, dependent and independent variables, and AI-ML-DL predictive models of waste generation. Our analysis revealed that most studies estimated waste material classification, amount of generated waste per area, and waste filling levels per location. Demographic data and images of waste type and fill levels are used as features to train the predictive models. Although various studies have widely deployed artificial neural networks (ANN) and convolutional neural networks (CNN) to classify waste, other techniques, such as gradient boosting regression tree (GBRT), have also been utilized. Critical challenges hindering the prediction of solid waste generation and disposal include the scarcity of real-time time series waste datasets, the lack of performance benchmarking tests of the proposed models, the reliability of the analytics models, and the long-term forecasting of waste generation. Our survey concludes with the implications and limitations of the selected models to inspire further research efforts.
Predicting Freshwater Microbial Pollution Using a Spatial Model: Transferability between Catchments
Authors: Li Jiawei , Liu Junyou
Published: October 2022

Freshwater microbial contamination has become a worldwide problem, but fecal indicator organism (FIO) data are lacking in many catchments and large-scale management is expensive. Therefore, a model that can assist in spatial localization to simulate microbial risk maps and Critical Source Areas (CSAs) is needed. This study aims to generate a predicted risk of microbial contamination in Kent and Leven, Northumberland, and East Suffolk based on the ArcMap hydrological tool using the land use parameters in the Wyre and Yealm catchments. Then, this study will compare the value obtained with the E. coli concentration data (observational risk) in order to evaluate whether land cover weightings are transferable between different catchments and provide microbial risk guidelines for ungauged catchments. In the research, the East Suffolk catchment showed strong fitting with actual values in the rainy and dry seasons after using the predictive values weighted by Wyre and Yealm, respectively. Specifically, as for the models with Yealm land cover weightings, the results show that the adjusted R2 in the rainy season for East Suffolk is 0.916 (p < 0.01) while the adjusted R2 values in the dry season is 0.969 (p < 0.01). As for models with Wyre land cover weightings, the adjusted R2 values (rainy season) is 0.872 (p < 0.01), while the adjusted R2 values (dry season) is 0.991 (p < 0.01). This indicates that this spatial model can effectively predict the risk of fecal microbial contamination in the East Suffolk catchment. Second, this research believes that the land cover weightings are more transferable in catchments that have close geographical locations or similar land cover compositions. This paper makes recommendations for future catchment management based on the results obtained.
Sustainability Communication in Global Consumer Brands
Authors: Primožič Lea , Kutnar Andreja
Published: October 2022

In light of the alarming climate change situation, the focus of society on sustainability has been enhanced. The recent initiatives at national and international levels to significantly lower greenhouse gas emissions and to transition to carbon-neutrality have highlighted the urgency. For a more sustainably oriented society, an important shift is needed; hence, we need to invest in creating more knowledge about the importance of sustainability with different stakeholders, and appropriate marketing and communication strategies can make a big difference. Changes need to happen in all sectors of society. The wood furniture industry, textiles, and car industry all produce products that consumers need daily, namely, furniture, clothes, and vehicles. These industries also produce similar amounts of harmful emissions in their manufacturing processes, which considerably contribute to pollution. Our objective was to investigate and to understand how the chosen industries communicate about sustainability. The three-pillar paradigm of sustainability—economic, environmental, and social—was studied. We chose to compare these different industries as they are among those that contribute to greenhouse gas emissions, and they produce end-consumer products made from different materials. Furthermore, the representative companies are global brands with a strong brand name and presence. The wood furniture industry uses natural materials, while the textile and car industries are more limited in this regard, even if they use some natural materials, for example cotton. Communication about the sustainability of the selected companies in the mentioned sectors was analyzed by applying qualitative content analyses of existing online communication. The companies were selected based on previously defined criteria—the size of the company, geographical location, and brand value. An analysis of the online communication of these companies has demonstrated that the selected industries communicate mostly about environmental topics on their webpages, and less frequently on social and economic issues. The wood furniture industry, although utilizing renewable natural materials, communicates about sustainability similarly to the other two studied sectors. This gives rise to suggestions for improvements in this sector that could give them a leading role in the narrative on communication about environmental, social, and economic sustainability.
Scaling Up Ecovillagers’ Lifestyles Can Help to Decarbonise Europe
Authors: Wiest Franziska , Gamarra Scavone M. , Newell Maya , Otto Ilona , Ringsmuth Andrew
Published: October 2022

Decarbonisation is an essential response to the threat of climate change. To achieve Europe’s net-zero 2050 climate targets, radical technological and social changes are required. Lifestyle changes for reducing greenhouse gas (GHG) emissions are an important component of complex systemic transformation. The typical behaviour of inhabitants in ecovillages is potentially more conducive to sustainable lifestyles than the current European standard lifestyle. This study explores the potential of ecovillagers' lifestyles to contribute to decarbonisation using the Multilevel Perspective (MLP) theoretical framework. The research data were obtained through the model tool EUCalc and an online survey of 73 ecovillage residents in 24 European countries. The results indicate that current ecovillagers’ lifestyles, regarding home, consumption, diet, and mobility, would continue to produce 40% fewer emissions per capita than the standard European lifestyle by 2050. The study identifies which ecovillage behaviours would produce the largest reductions in per-capita CO2eq emissions if adopted by society more broadly.
Metal Resistant Enterobacter cloacae ZA14 Enhanced Seedling Vigor and Metal Tolerance through Improved Growth, Physiology and Antioxidants in Tomato (Solanum lycopersicum) Irrigated with Textile Effluents
Authors: Naseem Zainab , Naveed Muhammad , Asghar Hafiz Naeem , Hameed Mansoor
Published: October 2022

The presence of toxic heavy metals and dyes in textile wastewater is a serious problem contaminating vegetables by irrigation. This contaminated food upon consumption undermines human health and is lethal for human life. The endophytic bacteria have the ability to degrade textile dyes and remediate heavy metals. The purpose of the present investigation was to evaluate useful concentration levels of textile wastewater (TWW) for irrigation in combination with the endophytic bacterium Enterobacter cloacae ZA14 to remediate heavy metals for improving growth of the tomato (Solanum lycopersicum) plant. The tomato seedlings showed inhibited germination (52%); suppressed root length (55%) and shoot length (53%); declined RWC (47%); lowest CSI (34%); reduced MSI (32%); increased accumulation of heavy metals Cr, Pb, and Cd in roots and shoots; with decreased metal tolerance index; and rise in production of total thiols (57%) at use of 100% TWW without bacterial application. On the contrary, the supplementation of endophytic bacterium ZA14 showed improved germination (100%), a decline of 3 and 5% in root and shoot length respectively, increased CSI (13%), decrease in MSI (6%), reduced bioaccumulation of Cr (root 30 and shoot 56%), Pb (root 58 and shoot 65%), and Cd (root 21 and shoot 58%), total thiols (76%), when irrigated with 25% TWW. Hence, it is concluded that the irrigation with 25% TWW, along with the application of Enterobacter cloacae ZA14, may improve the growth of tomato by mitigating the phytotoxicity of dyes and heavy metals from textile wastewater.
Sawdust Amendment in Agricultural and Pasture Soils Can Reduce Iodine Losses
Authors: Mohiuddin Muhammad , Hussain Zahid , Abbasi Asim , Ali Jawad , Irshad Muhammad , Tariq Muhammad Atiq Ur Rehman , Intisar Anum , Hina Aiman , Zaman Qamar Uz , Ng Anne Wai Man
Published: October 2022

Iodine loss is common in the soil of hilly regions due to higher precipitation rates and steeper slopes. Iodine deficiency in soil reduces iodine’s bioavailability to fruits and vegetables and consequently may contribute to health complications. However, the iodine retention of soils after the addition of selected organic and inorganic amendments has not been studied. Therefore, a study was carried out to investigate iodine loss during surface runoff. For this purpose, a soil amendment (namely, sawdust, charcoal, wood ash, lime or gypsum) was applied separately to pasture and agricultural soils under natural rainfall conditions. The soil was fertigated with iodine in the form of potassium iodide (KI) at the rate of 200 ppm. Surface runoff was related to soil properties. Results showed that iodine content in surface runoff was linearly related with soil pH (R2 = 0.89, p < 0.05) and inversely related with soil organic carbon (R2 = −0.76, p < 0.05). Soils amended with sawdust had significantly reduced iodine content in runoff. A higher amount of iodine was lost via surface runoff from soil after inorganic amendment. Soil amendments were varied for iodine retention in soil in the order of sawdust > charcoal > wood ash > lime > gypsum. The study results indicated that organic amendments, especially sawdust, improved soil properties and increased the iodine retention capacity of soils.
Optimization of Urease Production Capacity of a Novel Salt-Tolerant Staphylococcusxylosus Strain through Response Surface Modeling
Authors: He Yunxiu , Zhao Yuan , Zhang Wen , Zhang Yurong , Zou Yi
Published: October 2022

Encouraging advances have been made in the application of microbial mineralization towards fixing and improving desertified sandy soils. However, desert soils in arid areas exhibit high salinity that may limit urease activity and production in microbial strains, thereby affecting the solidification effects of microbial calcium binders in saline soils. In this study, a salt-tolerant microbial strain (A80) that produced urease was identified from saline soils of the Qaidam Basin. The culture conditions of the strain were optimized using single-factor tests and response surface methods to optimize urease yields and activity. The optimal composition of the A80 medium included an inoculation amount of 6.32% (V/V), a yeast extract powder concentration of 15.43 g/L, a glucose concentration of 5.20 g/L, a salinity of 3%, and an incubation temperature of 36 °C. Urease activity increased by 64.80% after using optimized medium. The A80 microbial calcium-cementing agent was also used to solidify saline soils, leading to an increased unconfined compressive strength of the solidified saline soil by 25.70%. Thus, the optimization method resulted in improvements in the cultivation of a salt-tolerant strain.
Factorial and Construct Validity of Sit-Up Test of Different Durations to Assess Muscular Endurance of Police Students
Authors: Kukić Filip , Orr Robin , Marković Milan , Dawes J. Jay , Čvorović Aleksandar , Koropanovski Nenad
Published: October 2022

Background: The number of completed sit-ups in a given period of time is a commonly used assessment to measure trunk endurance in tactical populations. This study investigated factorial and construct validity of three different durations of a sit-up test—30 s, 60 s, and 120 s; Methods: Anthropometric characteristics and sit-ups performed for 30, 60, and 120 s by101 (♂: n = 62 and ♀: n = 39) police students were assessed. A factorial analysis was used to determine if three test durations group together in one factor, correlation analysis determined whether the sit-up tests were associated with anthropometric measures and whether the three variations in the test duration correlated between each other, and the Fisher’s transformation determined whether these correlations differed significantly; Results: All three sit-up variations loaded together into one factor in both sexes, providing factorial validity for all three test durations. Anthropometrics were associated with sit-up tests lasting 30 s in males and 120 s in females. A sit-up test lasting 60 s correlated significantly stronger to 120 s than to the 30 s sit-up test; Conclusions: The 60 s sit-up test seems to have the highest construct validity, as it was not affected by anthropometrics, and it may be an optimal choice for its lower risk of lower back injuries. By applying the results of this study, agencies could reduce the bias that may occur during the sit-up test and reduce the risk of injury during physical fitness assessment.
Introducing the Special Issue on Artificial Intelligence Applications for Sustainable Urban Living
Authors: Wei Haoran , Wang Zhendong , Chang Yuchao , Huang Zhenghua
Published: October 2022

All global cities are in the process of transforming from classical cities to sustainable smart cities [...]
Decomposition Analysis of the Aggregate Carbon Intensity (ACI) of the Power Sector in Colombia—A Multi-Temporal Analysis
Authors: Rivera-Niquepa Juan David , Rojas-Lozano Daniela , De Oliveira-De Jesus Paulo M. , Yusta Jose M.
Published: October 2022

This paper presents the application of the Logarithmic Mean Divisia Index Decomposition Analysis (LMDI) to the aggregate carbon intensity (ACI) of the power sector in Colombia in the period 1990–2020, with the aim of identifying the main drivers influencing the ACI change. The analysis performed identifies the main drivers among: carbon intensity, generation efficiency, and contribution of fossil generation at the specific and total level of electricity production. The analysis is performed at the aggregate and disaggregated level of fossil fuels. Due to the highly variable behavior of the ACI, a multi-temporal decomposition is performed in the eight presidential administrations in the period of analysis. For each period, the main drivers are identified and the energy policy implications and their effects on the operation and management of the power sector are analyzed. The results show that the main driver is the fossil share of total energy production. Important effects on thermal generation efficiency and fossil energy mix were also identified in some analysis periods. The need for effective long-term policies and regulation in relation to the factors influencing the ACI was identified. It is recommended to accelerate the diversification of the energy mix of the power sector and the permanent monitoring of the behavior of the drivers.
Decoding Business Potential for Digital Sustainable Entrepreneurship: What Romanian Entrepreneurs Think and Do for the Future
Authors: Nicolau Cristina , Nichifor Eliza , Munteanu Daniel , Bărbulescu Oana
Published: October 2022

The digital environment and the businesses can no longer exist separately; the way in which entrepreneurs adapt to digital environments determines the future of the companies. By aiming to understand Romanian entrepreneurs’ openness and the assets disposed for digitalisation, the authors performed a study which revealed different managerial approaches used in order to achieve digital entrepreneurial sustainability. With exploratory research, they (i) identified the strategic approaches of the businesses within the digital environment, (ii) analysed the importance of strategic objectives and the entrepreneurial vision, (iii) understood the long-term strategies and the costs of digitalisation, and (iv) analysed the future of the business in terms of cyber security. The study highlighted that no Romanian entrepreneur placed digitalisation as an independent objective for its company, showing that companies needed a proper digitalisation strategy correlated to the opportunities and threats of the business environment. Moreover, the Romanian entrepreneurs’ knowledge in cyber security was low even though they were aware that it was imperative to control critical information and develop data security strategy so as to avoid data theft/loss in the company. All the findings favoured conceptualising a new Digital Sustainable Entrepreneurship Model based on owners’ entrepreneurial visions and companies’ strategic objectives alike, a guide-framework to remain competitive in a sustainable, ever-growing market.
How Do Rising Labor Costs Affect Green Total Factor Productivity? Based on the Industrial Intelligence Perspective
Authors: Qian Wei , Wang Yongsheng
Published: October 2022

In the context of the fading demographic dividend, rising labor costs present both opportunities and challenges to China’s green and sustainable development. This paper aims to investigate the impact of rising labor costs on the inter-provincial green total factor productivity (GTFP) of China and to explore the moderating effect of industrial intelligence. Both provincial panel data from 2010 to 2019 and the system GMM model, moderating effect model, and panel threshold model are used to empirically analyze the relationship between the three economic variables. The results show that: Firstly, during the sample period, China’s rising labor costs significant contribute to GTFP, and strengthening green technological progress (GTP) is the main delivery path, though it hinders the improvement of green technological efficiency (GTE). Secondly, industrial intelligence plays an enhanced positive moderating role in the path of labor costs affecting GTFP. Thirdly, grouped regressions show that the role of labor costs only emerges when industrial intelligence reaches a certain high level. Finally, taking industrial intelligence as a threshold dependent variable, labor costs have a non-linear, triple-threshold effect on GTFP. The promotion effect of labor costs increases the most when industrial intelligence exceeds the first threshold. On balance, as the level of industrial intelligence continues to increase, the promotion effect is stronger. The above empirical results are robust under the robustness test of replacement variables and estimation method. The results indicate that the innovation development effect of rising labor costs has to be built on the basis of industrial intelligence development.
Coordination Mechanism of E-Closed-Loop Supply Chain under Social Preference
Authors: Qin Yanhong , Wang Shaojie , Gao Neng
Published: October 2022

This study investigates the effect of social preference on the recycling decision and coordination in an E-closed-loop supply chain (E-CLSC). Firstly, we set the dynamic E-CLSC game model including a manufacturer, an E-commerce platform (E-platform) and a recycler, where the manufacturer dominates the supply chain and both the E-platform and the recycler are followers. Secondly, we propose an E-CLSC information structure to depict four symmetry and asymmetry cases about the E-platform’s fairness concern and the manufacturer’s altruistic reciprocity, and the backward induction method is adopted to solve the equilibrium in each case. By comparative analysis, we propose a revenue-sharing and cost-sharing contract to optimize recycling decisions, coordinate the E-CLSC and Pareto-improve all parties’ profits. We show that whether information is symmetrical or not, only the wholesale price contract cannot coordinate the E-CLSC, whereas the revenue-sharing and cost-sharing contract can always achieve optimal recycling decisions, coordinate the supply chain and Pareto-improve all parties’ profits with a constant cost sharing ratio. In addition, the E-platform’s fairness concern can widen the range of the revenue sharing ratio and make it easier to coordinate the E-CLSC, but the manufacturer’s altruistic reciprocity may narrow the range of the revenue sharing ratio and make it harder to coordinate the E-CLSC.
The Role of False-Claims Ban Regulation in Greenwashing of Firms with Imprecise Greenness Information
Authors: Wang Zhengkai , Ni Debing , Zheng Kaiming
Published: October 2022

The observation that firms are greenwashing in their advertisements to consumers has attracted regulatory false claim concerns; thus, we built a three-stage game theoretical model to explore how a firm’s efficiency in greenness information acquisition and a false claims ban (FCB) regulatory policy induce greenwashing (non-greenwashing) in the green advertising market. We solved the model with the concept of the perfect Bayesian equilibrium. Based on the PBEs, we obtained the following results. (1) A FCB regulatory policy is necessary to rule out any intentional greenwashing PBE. (2) In the presence of a strict FCB regulatory policy (with a large enough FCB penalty), if the precision of the firm’s observed signals is lower (or higher) than a threshold, uninformative non-greenwashing (both unintentional and uninformative non-greenwashing) PBEs arise, and the threshold increases in the FCB penalty. (3) A strict FCB regulatory policy and a high level of efficiency (regarding the firm’s greenness information acquisition) can (together) rule out greenwashing; the threshold of the efficiency of the firm’s greenness information acquisition is independent of the regulatory policy. Managerial implications are also discussed.
Inter-Firm ESG Rivalry: A Competitive Dynamics View
Authors: Guntuka Laharish
Published: October 2022

Sustainability literature has largely focused on business practices that result in environmental benefits that might not always be profitable to the firm, and thus, tend to be less appealing to the corporate board rooms. In this study, I examine if the rival firm’s sustainability behavior is driven by the focal firm’s behavior. Although a growing number of firms globally have voluntarily adopted and carried out a wide range of sustainability practices, there are firms that are driven by the position taken by industry competitors. Here, I examine such phenomena, to determine if a focal firm’s sustainability behavior is influenced by the rival’s sustainability behavior. In addition, I also examine how the competitive landscape of the focal firm, in the form of the focal firm’s size, the rival’s sustainability reputation, and industry concentration moderates the behavioral influence. I find a positive association between the rival firm’s sustainability performance and the focal firm’s sustainability performance. I also find that the focal firm’s size and industry concentration positively moderate the rivalry. Rival firms’ sustainability reputation does not have an impact on the rivalry.
Assessment of a Fast Proxy of Vs30 (Vs30m)
Authors: Saqlain Muhammad , Zada Umar , Muhammad Ghulam , AlQahtani Salman A. , Ali Zulfiqar , Hussain Wakeel
Published: October 2022

The most frequent parameter used to quantify seismic site response in ground motion models is time-averaged shear wave velocity in the top 30 m of a site (Vs30), used by many engineering design codes and most recently by published empirical-scaling equations to estimate the amplitudes of strong ground motion. The current study explores the potential comparison of the results from the predictive equations and formula recommendations by the international building code. A total of 53 synthetic and real data models with distinct types of vs. profile were used to determine the theoretical dispersion curves and avoid forward and inverse modeling. In the prediction equation, VR36 and VR40 were employed to estimate Vs30. Furthermore, using VR40, based on the 53 different models, shows a good agreement with Vs30. The thickness of the first layer substantially affects the correlation. The findings calculated by the correlation are not in the acceptable zone for layer thicknesses of 10 < H < 20 m and thin layers at shallow depths with lower shear wave velocity.
Efficient Degradation of Carbendazim by Ferrate(VI) Oxidation under Near-Neutral Conditions
Authors: Li Yu , Cheng Hefa
Published: October 2022

Carbendazim (CBZ), a widely used fungicide in agriculture, is frequently detected in aquatic environment and causes significant concerns because of its endocrine-disrupting activity. This study investigated the degradation kinetics of CBZ in ferrate (Fe(VI)) oxidation, the influence of water matrices, and the transformation pathways of CBZ. The second-order rate constant for the reaction between CBZ and Fe(VI) decreased from 88.0 M−1·s−1 to 1.6 M−1·s−1 as the solution pH increased from 6.2 to 10.0. The optimum reaction conditions were obtained through response surface methodology, which were pH = 7.8 and [Fe(VI)]/[CBZ] = 14.2 (in molarity), and 96.9% of CBZ could be removed under such conditions. Cu2+ and Fe3+ accelerated the degradation of CBZ by Fe(VI) oxidation; common cations and anions found in natural water had no significant effect, while the presence of humic acid also accelerated the degradation of CBZ. Based on the degradation products identified, degradation of CBZ in Fe(VI) oxidation proceeded via three pathways: namely, hydroxylation, removal of the methoxyl group, and cleavage of the C–N/C=N bond. The initial reaction site of CBZ oxidation by Fe(VI) was also supported by the atomic partial charge distribution on the CBZ molecule obtained from density functional theory (DFT) calculations. CBZ in natural water matrices was efficiently removed by Fe(VI) oxidation under near-neutral conditions, indicating that Fe(VI) oxidation could be a promising treatment option for benzimidazole fungicides.
Study on the Spatio-Temporal Evolution of Land Use in Resource-Based Cities in Three Northeastern Provinces of China—An Analysis Based on Long-Term Series
Authors: Li Qiang , Pu Yuchi , Zhang Yang
Published: October 2022

Land is the basis of development, and the unique patterns of the spatio-temporal evolution of land use in resource-based cities can reflect regional development, help land resources to be used efficiently and rationally, promote scientific regulation, and achieve high-quality development. Based on the land use data of resource-based cities in three northeastern provinces from 1980 to 2020, the spatio-temporal evolution characteristics and driving factors of land use in the sample study area were studied by the Markov transfer matrix and a parametric optimal geographic detector model. The results showed that: (1) From the perspective of time, the land use changes in the sample study area were active, mainly reflected in the continuous conversion of forest land transfer-out (11.66%) and arable land transfer-in (11.28%), and the dynamic attitude of forest land showed a trend of decreasing, then increasing and then decreasing, while the dynamic attitude of arable land showed a trend of increasing, then decreasing and then increasing. (2) Spatially, the areas where land conversion occurred were mainly concentrated in the northern part of the study area and the border area in the east, which is also the area where forest land was converted to arable land and grassland was converted to arable land, and the expansion of construction land was more common; (3) In terms of influencing factors, land conversion before 2000 was mainly influenced by socio-economic factors, and population quantity and urbanization rate had stronger explanatory power. The spatial and temporal evolution of forest land conversion to arable land was realized by the interaction of various factors, and the driver interactions were all non-linearly enhanced and bi-factor enhanced. (4) In terms of influencing factors, land conversion before 2000 was mainly influenced by socio-economics, with population quantity and urbanization rate having a stronger explanatory power; after 2000, land conversion was mainly influenced by physical geography, with precipitation and temperature having a stronger explanatory power. (5) The spatio-temporal evolution of forest land conversion to cropland was realized by the interaction between various factors, and the driving factor interactions all showed non-linear enhancement and bifactor enhancement.
Classification of Cotton Genotypes with Mixed Continuous and Categorical Variables: Application of Machine Learning Models
Authors: Bishnoi Sudha , Al-Ansari Nadhir , Khan Mujahid , Heddam Salim , Malik Anurag
Published: October 2022

Mixed data is a combination of continuous and categorical variables and occurs frequently in fields such as agriculture, remote sensing, biology, medical science, marketing, etc., but only limited work has been done with this type of data. In this study, data on continuous and categorical characters of 452 genotypes of cotton (Gossypium hirsutum) were obtained from an experiment conducted by the Central Institute of Cotton Research (CICR), Sirsa, Haryana (India) during the Kharif season of the year 2018–2019. The machine learning (ML) classifiers/models, namely k-nearest neighbor (KNN), Classification and Regression Tree (CART), C4.5, Naïve Bayes, random forest (RF), bagging, and boosting were considered for cotton genotypes classification. The performance of these ML classifiers was compared to each other along with the linear discriminant analysis (LDA) and logistic regression. The holdout method was used for cross-validation with an 80:20 ratio of training and testing data. The results of the appraisal based on hold-out cross-validation showed that the RF and AdaBoost performed very well, having only two misclassifications with the same accuracy of 97.26% and the error rate of 2.74%. The LDA classifier performed the worst in terms of accuracy, with nine misclassifications. The other performance measures, namely sensitivity, specificity, precision, F1 score, and G-mean, were all together used to find out the best ML classifier among all those considered. Moreover, the RF and AdaBoost algorithms had the highest value of all the performance measures, with 96.97% sensitivity and 97.50% specificity. Thus, these models were found to be the best in classifying the low- and high-yielding cotton genotypes.
How Can Sewage Sludge Use in Sustainable Tunisian Agriculture Be Increased?
Authors: Marzougui Nidhal , Ounalli Nadia , Sabbahi Sonia , Fezzani Tarek , Abidi Farah , Jebari Sihem , Melki Sourour , Berndtsson Ronny , Oueslati Walid
Published: October 2022

In recent years, farmers in Beja, an agricultural governorate in northwestern Tunisia, have expressed their willingness to use urban sewage sludge as agricultural fertilizer, especially with the unavailability of chemical fertilizers and the soil type of the region that is poor in organic matter. However, there is an imbalance between the important farmers’ demand versus the limited quantity of sludge produced by the Beja wastewater treatment plants (WWTPs). In the face of this, this study aims to identify the problems related to the agricultural reuse of sludge in Beja and propose solutions to solve them. The quality of the sludge produced by the five Beja WWTPs was assessed based on physicochemical and microbiological parameters. The data were collected using the Delphi method, with 15 experts representing different positions on the issue treated. The SWOT-AHP methodology was used to define the strategies promoting the sustainable use and management of urban sewage sludge for sustainable agricultural development in Beja. Results showed that there were no problems with compliance with the Tunisian standards NT 106.20 for the sludge produced. A set of twelve practical conclusions was identified, constituting the strategies of Strengths–Opportunities, Strengths–Threats, Weaknesses–Opportunities, and Weaknesses–Threats deduced from the SWOT-AHP.
Study on the Spatial Distribution Characteristics and Influencing Factors of Famous Historical and Cultural Towns or Villages in Hubei Province, China
Authors: Wang Qi , Bing He , Wang Siqi , Xu Qing
Published: October 2022

Famous Historical and Cultural Towns or Villages are among the important components of China’s cultural heritage. Their spatial distribution patterns are directly related to regional geographical patterns, historical transportation geography and traditional communities. Meanwhile, their conservation is challenged by the change in regional population density, the level of urbanization, modern transportation and ecological environment conditions. Therefore, studying the provincial distribution patterns is of great practical significance to the conservation and sustainable development of Famous Historical and Cultural Towns or Villages in China. This study takes 44 of China’s national and provincial Famous Historical and Cultural Towns or Villages in Hubei Province that were announced from 2003 to 2022 as the research subjects and uses the Geographic Information Technology (GIS) tools to determine their clusters and linear distribution zones, including nearest distance analysis, nuclear density analysis, buffer zone analysis and imbalance index analysis. We further analyze the causes of their spatial distribution in conjugation with historical geography and factors related to the preservation of the current situation of them via correlation analysis. Finally, we make suggestions for the conservation and development of Famous Historical and Cultural Towns or Villages in Hubei Province.
Japan’s Culture of Prevention: How Bosai Culture Combines Cultural Heritage with State-of-the-Art Disaster Risk Management Systems
Authors: Pastrana-Huguet Josep , Casado-Claro Maria-Francisca , Gavari-Starkie Elisa
Published: October 2022

Due to its geographical location, Japan is exposed to typhoons, floods, earthquakes, tsunamis, and volcanoes. Since time immemorial, the survival of the Japanese people has depended on their ability to prepare for disasters, learn from those painful experiences, and transmit that knowledge from generation to generation as part of their cultural heritage. These elements combined have resulted in a unique Culture of Prevention, known in Japanese as “bosai culture”, encompassing technical measures and requirements, laws, and a strong civic culture that enables the country to face and learn from disasters. Exploring the roots of the Japanese Culture of Prevention by conducting a critical literature review, this article aims to improve our understanding of the Japanese perspective on Disaster Risk Reduction strategies and actions, by focusing on the cultural and religious influences, as well as on the solid national sense of belonging, embedded in the Japanese Disaster Risk Management system.