A common practice in the construction of residential and commercial buildings in Saudi Arabia is to insulate the outer walls and windows only. Other building components such as the roof, columns and slabs, and doors are usually neglected. Moreover, vital components such as the roof and windows are especially neglected in commercially built residential and commercial buildings. The aim of this study is to put this common impression and practice to the test by quantifying the contribution of every building component to the overall air-conditioning load of the building. The hypothesis evaluated in this paper is that despite the common practices, there could be an optimum selection of insulators for the building components that yields the lowest energy consumption and maximum savings not only in energy costs but also installation costs. The required air-conditioning load is determined using manual calculations and the HAP software package for 1022 possible configurations. The findings of the analysis point to the importance of the roof, as it is the major contributor to the thermal load, followed closely by columns and slabs, with 44.2% of the overall cooling load. It is found that a single wall consisting of 2 cm of cement plaster, 20 cm of cement–polyurethane brick, and 2 cm of cement plaster is less expensive and has higher thermal resistance than any of the more expensive double walls. The study found one scenario of possible configurations with the optimized selection of building materials and their insulation materials that provides the most effective insulation at the lowest cost. Full article

In the context of urban sustainability, promoting pedestrian travel is fundamental. Residents’ needs are critical to creating truly pedestrian-friendly streets. The objective of this study was to answer the following questions: What aspects most increase the willingness of citizens to walk? Is the extent to which these aspects are prioritized related to the context in which citizens move on a daily basis? Two linked surveys, conducted through the institutional website of the Department of Civil Engineering and Architectural of the University of Catania, allowed the inclusion of more than 1000 respondents residing in the metropolitan areas of eastern Sicily. The large database was first reduced using Principal Component Analysis (PCA) and then statistically processed using Path Analysis. Thus, it was found that in the residential areas of the respondents that were not very “pedestrian friendly”, the macro factors of “safety”, “comfort”, and “quality” of pedestrian infrastructures were equally desirable for citizens to adapt to the existing pedestrian routes and thus promote walking. On the other hand, the “attractiveness” of the urban environment as a whole was a non-statistically significant variable for residents’ decision to walk. These results are not valid for every urban context, but the method used is generalizable and applicable in any urban setting. If the quality, safety, and comfort of pedestrian infrastructure results are important, urban planning should prioritize the provision of safe and accessible sidewalks, crosswalks, and pedestrian streets. Furthermore, if the attractiveness of a neighborhood result is significant, urban design and planning should go beyond functional requirements and also focus on creating a vibrant and livable urban environment. Full article

This paper empirically tests the impact mechanism of digital economy development on manufacturing total factor productivity, using data from Chinese manufacturing enterprises from 2011 to 2020, and based on the theoretical framework of the impact of digital economy development on manufacturing total factor productivity. The development of the digital economy has been found to have a significant positive impact on the total factor productivity of the manufacturing industry. The heterogeneity effect demonstrates that the digital economy in coastal areas has a significant effect on the improvement of manufacturing total factor productivity, with the eastern coastal area having the strongest effect; the digital economy in the Yellow River’s middle reaches, the Yangtze River’s middle reaches, and the southwest also having a significant effect, with the effect in the southwest region being more significant; and the digital economy in the northwest and northeast having no effect. Possible reasons include larger bottlenecks in the western region’s labor force structure, technology level, and management capabilities, which may lead to the inability of enterprises to effectively absorb the dividends of digital change and apply the scenarios, thus affecting the release of their productivity effects. Full article

Realizing green development in agriculture is fundamental to sustained economic development. As a measure to facilitate the transfer of rural population, urbanization is considered to be strategic in promoting agricultural green development. This paper employs a SBM-DDF–Luenberger method to measure agricultural green total factor productivity (AGTFP) and the agricultural labor surplus in China, and empirically tests the heterogeneous effects of household registration urbanization, permanent residence urbanization, and employment urbanization on the efficiency of agricultural green development. The results reveal that: (1) the average annual growth rate of China’s AGFTP is 4.4374%, which is achieved mainly through improvements in green scale efficiency. (2) The agricultural sector in China is suffering a large surplus of labor force, with an estimation of 20.64 million in 2020. (3) Both household registration urbanization and permanent residence urbanization have a significant promoting effect on agricultural green development efficiency, though the former promotes less. (4) Employment urbanization improves agricultural green development efficiency by providing employment guidance for migrant workers, and employment urbanization of the tertiary industry has a more pronounced improvement effect. The findings suggest that governments remove restrictions on the household registration system and actively guide surplus agricultural laborers to engage in urban service industries to provide an impetus for promoting green agricultural development. Full article

The fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), is a polyphagous non-native pest identified as a serious threat to crop production and food security globally, including in India. Its unintentional introduction and quick coverage in large areas is a serious concern to millions of farmers in the eastern Himalayan region. However, detailed understanding of farmers’ perceptions and the biological attributes associated with the meteorological factors for FAW is limited. The present investigation, which aimed to create baseline data on this pest, concurs with the idea that the FAW is widely dispersed throughout the maize ecosystems of Tripura, with an average infestation rate of 21.33 percent. The severity ranged from 0 to 1.40, with an average leaf damage score of 1 on a 0–4 categorical scale. The findings indicate that pheromone trap catch was significantly correlated with the evaporation rate as other meteorological factors influenced variably. The biological attributes imply that the life cycle was completed in 32.82 ± 0.08 days, with a high fecundity potential (1068.57 ± 4.35 numbers) in controlled conditions (25 ± 1 °C, 70 ± 5% RH). Indigenous natural enemies, such as entomopathogens, spiders, and wasps, were found to be the first defence against this invasive pest. A minority of the population (17.51%) was aware of the incidence of FAW. Furthermore, respondents’ socio-demographic variables were associated significantly with FAW status. This is the first scientific report from the eastern Himalayan region about farmers’ knowledge and awareness of the invasiveness of FAW. This finding enumerates a detailed understanding of FAW from diverse perspectives. Further, the concerted data provide an important baseline that could help the development of holistic management strategies for FAW. Full article

The increasing growth trend of the global Muslim population implies an increase in the consumption of halal products. The importance of the halal market attracts much attention from many stakeholders, including academia/researchers. Many scholars have conducted studies on halal topics. However, these studies cover broad topics, such as ICT potential in the halal sector, the halal supply chain, Islamic Law, and other halal studies related to natural sciences. This study aims to study the research gap and future trends of halal food additive and ingredient research in business and economics using bibliometric analysis. The data were obtained from the Scopus database from 1999 to 2022. The authors analyzed the keyword “Halal Consumption and Production” by using the general keyword “Halal or Haram Additive and Ingredient”. The dataset was uploaded on VOSviewer and R language (Bibliometrix) software. This study found a deficit of studies on halal food additives and ingredients in business and economics. The co-occurrence network output demonstrated that future studies on halal food additives and ingredients should consider clusters that have lower density and central positions, such as production–consumption and the supply chain, healthy foods, and the logistics market and health effects. The Bibliometrix strategic diagram of the 2020–2022 thematic evolution demonstrates a research gap in three out of four quadrants (i.e., emerging or declining, basic, and motor themes). This study suggests potential research areas in the field of halal food additives and ingredients, such as ethical and sustainable sourcing, responsible consumption, consumer sovereignty, international trade, economic modeling, food security, green/sustainable supply chain, and halal regulation and product safety. Full article

The Great East Japan Earthquake and Tsunami struck the northeastern coastal area of Japan on 11 March 2011, resulting in the relocation of 329,000 households and the repair of 572,000 houses. Previous studies predominantly addressed the impact of demographic factors on housing recovery. However, the types of housing recoveries and the impact of individual psycho-behavioral factors have been poorly addressed. This study examined the impact of survivors’ demographic and personality-trait factors using a discriminant analysis of five types of housing recovery among 573 survivors in the five years after the disaster. The results revealed two important axes. One axis discriminated self-procured (rebuilt, repaired, and chartered housing) houses from those that were publicly available (emergency temporary and public disaster housing) affected by three personality traits (stubbornness, problem-solving, and active well-being) and survivors’ age. The other axis represented rebuilt houses affected by household size. These results demonstrate that personality traits and not just demographic factors impact three types of self-procured housing recoveries. Further exploration of personality traits that impact housing recovery can improve post-disaster reconstruction and recovery practices. Full article

The current aquaculture environment anomaly monitoring system is limited in function, making it difficult to provide overall technical support for the sustainable development of aquaculture ecosystems. This paper designs a set for an IoT-based aquaculture environment monitoring device. The device is capable of collecting five aquaculture environment factors such as water temperature, pH, salinity, dissolved oxygen and light intensity throughout the day by wireless data transmission via 4G DTU with a communication success rate of 92.08%. A detection method based on time series sliding window density clustering (STW-DBSCAN) is proposed for anomaly detection, using the confidence interval distance radius of slope to extract subsequence timing features and identify the suspected abnormal subsequences and then further determine the anomalous value by the DBSCAN clustering method. The detection results show that the algorithm can accurately identify abnormal subsequences and outliers, and the accuracy, recall and F1-Score are 87.71%, 82.58% and 85.06%, respectively, which verifies the usability of the proposed method. Further, a fuzzy control algorithm is adopted to specify the warning information, and a software platform is developed based on data visualization. The platform uses WebSocket technology to interact with the server, and combined with the surveillance camera, it can monitor the aquaculture environment and perform data monitoring and analysis in a real-time, accurate and comprehensive manner, which can provide theoretical reference and technical support for sustainable development of aquaculture. Full article

Cycling is encouraged as a means of sustainable urban transport, yet its uptake rate is uneven between different ethnic groups. The ethnic minority population in England is underrepresented as cyclists, but the reasons for this are unclear. Through linear regression and Geographically Weighted Regression (GWR), this research investigates the spatial distribution of the propensity to cycling among the ethnic minority population and the white population across England with the aim to identify the contributing factors toward the discrepancy of cycling rates between both groups and how these factors vary geographically. Results from OLS regression suggest that cycle rates are generally affected most by hilliness, the presence of school-age children, and income, with the presence of school-age children affecting the ethnic minority group and hilliness affecting the white group the most. The use of GWR revealed that income generally reduces cycle rates but has a positive impact in London for both groups. The length of cycleways and the length of 20 mph speed limit roads per unit area were statistically insignificant, but their local coefficients in GWR showed strong regional variations for both groups. The study also found that, with the exception of the level of income, ethnic minority cyclists are less sensitive to contributing factors than the white cyclists. Full article

Cooking stoves produce significant emissions of PM_2.5 in homes, causing major health impacts in rural communities. The installation of chimneys in cooking stoves has been documented to substantially reduce indoor emissions compared to those of traditional open fires. Majority of the emissions pass through chimneys to the outdoors, while some fraction of the emissions leak directly into the indoor air, which is defined as fugitive emission. Indoor PM_2.5 concentrations are then the result of such fugitive emissions and the infiltration of outdoor neighborhood pollutants. This study uses a combination of the one-contaminant box model and dispersion models to estimate the indoor PM_2.5 household concentration. The results show that the contributions of outdoor infiltration to indoor PM_2.5 concentrations increase with higher packing densities and ventilation rates. For a case study, under WHO recommended ventilation conditions, the 24 h average mass concentration is ~21 μg/m³, with fugitive concentration accounting for ~90% of the total exposure for highly packed communities. These results help to identify the potential benefits of intervention strategies in regions that use chimney stoves. Full article

Extreme climate events are becoming increasingly frequent and intense due to the global climate change. The present investigation aims to ascertain the nature of the climatic variables association with the vegetation variables such as Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI). In this study, the impact of climate change with respect to vegetation dynamics has been investigated over the Indian state of Haryana based on the monthly and yearly time-scale during the time period of 2010 to 2020. A time-series analysis of the climatic variables was carried out using the MODIS-derived NDVI and LAI datasets. The spatial mean for all the climatic variables except rainfall (taken sum for rainfall data to compute the accumulated rainfall) and vegetation parameters has been analyzed over the study area on monthly and yearly basis. The liaison of NDVI and LAI with the climatic variables were assessed at multi-temporal scale on the basis of Pearson correlation coefficients. The results obtained from the present investigation reveals that NDVI and LAI has strong significant relationship with climatic variables during the cropping months over study area. In contrast, during the non-cropping months, the relationship weakens but remains significant at the 0.05 significance level. Furthermore, the rainfall and relative humidity depict strong positive relationship with NDVI and LAI. On the other, negative trends were observed in case of other climatic variables due to the limitations of NDVI viz. saturation of values and lower sensitivity at higher LAI. The influence of aerosol optical depth was observed to be much higher on LAI as compared to NDVI. The present findings confirmed that the satellite-derived vegetation indices are significantly useful towards the advancement of knowledge about the association between climate variables and vegetation dynamics. Full article

Employee performance is the secret to success for every company. Companies want their employees to understand the company’s vision and objectives and meet the individual goals set by the managers. The insurance industry in Bangladesh has stagnant growth compared to other industries. Moreover, insurance companies are lagging in managing human resources, especially permanent employees. Sustainable employee performance will help companies to achieve sustainable growth. This study aimed to identify the influencing factors that impact sustainable employee performance of insurance industry employees in Bangladesh. The study utilized the social exchange theory as the underpinning theory. The study modified the social exchange theory and proposed a research framework with five indicator variables: compensation, job satisfaction, work environment, leadership style, and motivation. The survey included 200 insurance company employees from various departments and companies. The collected data were analyzed using the partial least square–structural equation modeling (PLS–SEM) method using SMART PLS 3.2.7 software. The findings revealed that all the factors significantly positively impacted sustainable employee performance. The results of the study are helpful for academicians and researchers to analyze employee performance further. In addition, the results will help insurance companies and policymakers to make appropriate decisions to ensure sustainable employee performance in the organization. Full article

It is well known that biodiversity and ecosystem multifunctionality (EMF) guarantee the well-being of human society. Most studies have focused on the relationship between biodiversity and ecosystem function, and less is known about the individual and combined effects of above- and below-ground biodiversity on ecosystem multifunctionality under grazing disturbance. The aim of our study was to investigate the relationship between plant and soil microbial (bacterial and fungal) diversity and ecosystem multifunctionality under grazing disturbance by using multiple methods to assess ecosystem multifunctionality. We conducted experiments in desert grasslands on the northern slopes of the Tian Shan Mountains and compared the relationship between ecosystem multifunctionality and biodiversity assessed by different methods under light grazing and heavy grazing. Our results showed that at the heavy grazing level, ecosystem multifunctionality calculated by the mean method and plant diversity, soil fungal diversity, soil bacterial diversity and soil fertility calculated by the single function method showed a significant decrease (p < 0.05), but grass productivity was significantly increased (p < 0.05). Among them, ecosystem multifunctionality, soil carbon storage function and soil fertility all showed significant positive correlations with plant diversity and soil microbial diversity (p < 0.05). We calculated that ecosystem multifunctionality also essentially showed positive correlation with plant diversity and soil microbial diversity using the multi-threshold method, and the effect curve was approximately a single-peaked curve, first increasing and then decreasing. Finally, we used plant diversity, soil fungal diversity and soil bacterial diversity under grazing disturbance as biotic factors and soil pH as an abiotic factor to construct structural equation models, and we found that grazing can have direct effects on ecosystem multifunctionality and indirect effects on ecosystem multifunctionality through above- and below-ground biodiversity. Our study emphasizes the importance of the combination of above- and below-ground biodiversity in maintaining the multifunctionality of desert grassland ecosystems on the northern slopes of the Tian Shan Mountains. A moderate reduction in grazing intensity can better conserve biodiversity and improve ecosystem multifunctionality, and it is a feasible strategy to maintain sustainable management of desert grasslands. Full article

This study proposes an optimal control method for connected autonomous vehicles (CAVs) through signalized intersections to reduce the energy consumption of mixed human-driven vehicles (HDVs) and CAV traffic. A real-time optimal control model was developed to optimize the trajectory of each CAV by minimizing energy consumption during the control period while ensuring traffic efficiency and safety. The control conditions of the CAVs were analyzed under different driving scenarios considering the impact of signal phase timing and preceding vehicles. Additionally, a method is proposed for CAVs to guide other vehicles directly and reduce the energy consumption of the entire signalized intersection. Simulation experiments using MATLAB and SUMO were conducted to evaluate the performance of the proposed method under various traffic conditions, such as different levels of saturation, market penetration rates (MPRs), and the green ratio. The performance was measured using average energy consumption and an average time delay. The results show that the proposed method can effectively reduce vehicle energy consumption without compromising traffic efficiency under various conditions. Moreover, under traffic saturation, the proposed method performs better at a high MPR and green ratio, especially at 40–60% MPR. Full article

To achieve the announced 2060 carbon neutrality goal, the government of China has recently established its “1 + N” legal and policy framework. However, the emerging autonomous vehicle technology, which is developing rapidly, is not included. Considering the significant potential of autonomous vehicle technology in reducing carbon emissions from the transportation sector, whether and how to integrate it into the current framework can be crucial for China. The existing literature typically does not regard the emission reduction impacts of autonomous vehicles as a major issue, and there are still few studies available aiming to ensure enhancement of emission reduction induced by autonomous vehicle technology from a legal and policy perspective. This article attempts to fill the above research gaps with a three-step research scheme. Specifically, this work begins with a comprehensive and detailed analysis of the possible wide range of factors affecting energy consumption and emissions of autonomous vehicles. Next, an in-depth discussion of the feasibility of incorporating autonomous vehicle technology into the current “1 + N” legal and policy framework is provided. Finally, several recommendations corresponding to these factors are proposed from legal and policy perspectives: (i) adoption of industrial incentives to mitigate research and development costs and risks at the production level and to expand market demand at the consumption level; (ii) priority promotion of the commercialization of autonomous vehicles in the taxi market by filling legal gaps and applying regulatory measures; (iii) development of efficient transportation policies and land use policies. This article provides a systematic and practical scheme for inclusion of autonomous vehicles in China’s legal and policy framework to realize the carbon neutrality goal. The proposed recommendations can be referenced for other governments that may face similar challenges and future development of possible uniform rules at the global level. Full article