bluuebunny/crossref_metadata_2025 huggingface dataset:
Health Impact Attributable to Improvement of PM2.5 Pollution from 2014–2018 and Its Potential Benefits by 2030 in China
Authors: Ma Yu , Li Deping , Zhou Liang
Published: September 2021

With the advancement of urbanization and industrialization, air pollution has become one of the biggest challenges for sustainable development. In recent years, ambient PM2.5 concentrations in China have declined substantially due to the combined effect of PM2.5 control and meteorological conditions. To this end, it is critical to assess the health impact attributable to PM2.5 pollution improvement and to explore the potential benefits which may be obtained through the achievement of future PM2.5 control targets. Based on PM2.5 and population data with a 1 km resolution, premature mortality caused by exposure to PM2.5 in China from 2014 to 2018 was estimated using the Global Exposure Mortality Model (GEMM). Then, the potential benefits of achieving PM2.5 control targets were estimated for 2030. The results show that premature mortality caused by PM2.5 pollution decreased by 22.41%, from 2,361,880 in 2014 to 1,832,470 in 2018. Moreover, the reduction of premature mortality in six major regions of China accounted for 52.82% of the national total reduction. If the PM2.5 control target can be achieved by 2030, PM2.5-related premature deaths will further decrease by 403,050, accounting for 21.99% of those in 2018. Among them, 87.02% of cities exhibited decreases in premature deaths. According to the potential benefits in 2030, all cities were divided into three types, of which type III cities should set stricter PM2.5 control targets and further strengthen the associated monitoring and governance. The results of this study provide a reference for the formulation of air pollution control policies based on regional differences.
Insights of Digital Transformation Processes in Industrial Symbiosis from the Viable Systems Approach (vSa)
Authors: Barile Sergio , Bassano Clara , D’Amore Raffaele , Piciocchi Paolo , Saviano Marialuisa , Vito Pietro
Published: September 2021

The main purpose of this contribution is twofold: from a scientific point of view, to interpret the symbiotic logic through the framework of the Viable Systems approach (vSa), and from a managerial viewpoint, to provide the actors of industrial symbiosis initiatives, at any stage of their life cycle, with a guide to the most promising web-based solutions in terms of defining the best configuration for the symbiotic network. The article, therefore, aims to provide an in-depth study of the existing literature, which is still not exhaustive, and to consider synoptically and comparatively the modern platforms capable of supporting industrial symbiosis initiatives. The objective was pursued by examining 10 existing and functioning Web-based platforms, of which only a few were previously explored in the previous literature, while the recognition of the latter was carried out on a bibliometric basis to articulate in more detail the existing gap based on a panel of contributions as large as possible. The joint consideration of the literature review and the examination of the existing and functioning platforms shows an articulated framework of approaches, proposed models, and classification schemes of their functions, which allows us to conclude that given the sectoral, territorial, and specific characteristics of the materials addressed by each platform and considering the different cycles existing in eco-industrial parks (water, energy, by-products, etc.), the most promising way for their implementation is to consider multiple platforms to fully exploit the contribution of each of them. As for the management implications, the suggestion is to integrate the results obtained from the different platforms and to evaluate the configurational alternatives with multi-criteria procedures.
Development of an Urban Heat Mitigation Plan for the Greater Sacramento Valley, California, a Csa Koppen Climate Type
Authors: Taha Haider
Published: September 2021

An urban atmospheric modeling study was undertaken with the goal of informing the development of a heat-mitigation plan for the greater Sacramento Valley, California. Realistic levels of mitigation measures were characterized and ranked in terms of their effectiveness in producing urban cooling under current conditions and future climate and land use. An urban heat-island index was computed for current and future climates based on each location’s time-varying upwind temperature reference points and its hourly temperatures per coincident wind direction. For instance, the UHII for the period 16–31 July 2015, for all-hours averaged temperature equivalent (i.e., °C · h hr−1), ranged from 1.5 to 4.7 °C across the urban areas in the region. The changes in local microclimates corresponding to future conditions were then quantified by applying a modified high-resolution urban meteorology model in dynamically downscaling a climate model along with future urbanization and land use change projections for each area. It was found that the effects of urbanization were of the same magnitude as that of the local climate change. Considering the urban areas in the region and the selected emissions scenarios, the all-hours temperature equivalent of the UHII (°C · h hr−1) increased by between 0.24 and 0.80 °C, representing an increase of between 17% and 13% of their respective values in the current climate. Locally, instantaneous (e.g., hourly) temperatures could increase by up to ~3 °C because of climate effects and up to ~5 °C because of both climate and urbanization changes. The efficacies of urban heat mitigation measures were ranked both at the county level and at local project scales. It was found that urban cooling measures could help decrease or offset exceedances in the National Weather Service heat index (NWS HI) above several warning thresholds and reduce the number of heatwave or excessive heat event days. For example, measures that combine increased albedo and urban forests can reduce the exceedances above NWS HI Danger level by between 50% and 100% and the exceedances above Extreme Caution level by between 18% and 36%. UHII offsets from each mitigation measure were quantified for two situations: (1) a scenario where a community implements cooling measures and no other nearby communities take any action and (2) a scenario where both the community and its upwind neighbors implement cooling measures. In this second situation, the community benefits from cooler air transported from upwind areas in addition to the local cooling resulting from implementation of its own heat mitigation strategies. The modeling of future climates showed that except for a number of instances, the ranking of measures in each respective urban area remains unchanged into the future.
Machine Learning-Based Classification and Regression Approach for Sustainable Disaster Management: The Case Study of APR1400 in Korea
Authors: El-Hameed Ahmed Abd , Kim Juyoul
Published: September 2021

During nuclear accidents, decision-makers need to handle considerable data to take appropriate protective actions to protect people and the environment from radioactive material release. In such scenarios, machine learning can be an essential tool in facilitating the protection action decisions that will be made by decision-makers. By feeding machines software with big data to analyze and identify nuclear accident behavior, types, and the concentrations of released radioactive materials can be predicted, thus helping in early warning and protecting people and the environment. In this study, based on the ground deposition concentration of radioactive materials at different distances offsite in an emergency planning zone (EPZ), we proposed classification and regression models for three severe accidents. The objective of the classification model is to recognize the transient situation type for taking appropriate actions, while the objective of the regression model is to estimate the concentrations of the released radioactive materials. We used the Personal Computer Transient Analyser (PCTRAN) Advanced Power Reactor (APR) 1400 to simulate three severe accident scenarios and to generate a source term released to the environment. Additionally, the Radiological Consequence Analysis Program (RCAP) was used to assess the off-site consequences of nuclear power plant accidents and to estimate the ground deposition concentrations of radionuclides. Moreover, ground deposition concentrations at different distances were used as input data for the classification and regression tree (CART) models to obtain an accident pattern and to establish a prediction model. Results showed that the ground deposition concentration at a near distance from a nuclear power plant is a more informative parameter in predicting the concentration of radioactive material release, while the ground deposition concentration at a far distance is a very informative parameter in identifying accident types. In the regression model, the R-square of the training and test data was 0.995 and 0.994, respectively, showing a mean strong linear relationship between the predicted and actual concentration of radioactive material release. The mean absolute percentage error was found to be 26.9% and 28.1% for the training and test data, respectively. In the classification model, the model predicted a scenario (1) of 99.8% and 98.9%, scenario (2) of 98.4% and 91.6%, and scenario (3) of 98.6% and 94.7% for the training and test data, respectively.
Lane-Level Map-Aiding Approach Based on Non-Lane-Level Digital Map Data in Road Transport Security
Authors: Luz Philipp , Zhang Li , Wang Jinyue , Schwieger Volker
Published: September 2021

To prevent terror attacks in which trucks are used as weapons as happened in Nice or Berlin in 2016, the European Project Autonomous Emergency Maneuvering and Movement Monitoring for Road Transport Security (TransSec) was launched in 2018. One crucial point of this project is the development of a map-aiding approach for the localization of vehicles on digital maps, so that the information in digital map data can be used to detect prohibited driving maneuvers, such as off-road or wrong-way drivers. For example, a lane-level map-aiding approach is required for wrong-way driver detection. Navigation Data Standard (NDS) is one of the worldwide map standards developed by several automobile manufacturers. So far, there is no lane-level NDS map covers a large area, therefore, it was decided to use the latest available NDS map without lane level accuracy. In this paper, a lane-level map-aiding approach based on a non-lane-level NDS map is presented. Due to the inaccuracy of vehicle position and digital map the map-aiding does not always provide the correct results, so probabilities of off-road and wrong-way diver detection are estimated to support risk estimation. The performance of the developed map-aiding approach is comprehensively evaluated with both real and simulated trajectories.
Transboundary Ecological Conservation, Environmental Value, and Environmental Sustainability: Lessons from the Heart of Borneo
Authors: Keong Choy Yee , Onuma Ayumi
Published: September 2021

Balancing economic growth with international commitments to environmental sustainability is a global challenge. One of the main objectives of this study is to address this challenge by stimulating and sustaining motivation for environmental conservation by means of a comprehensive rethinking of the values inherent in nature and the limitations of monetary approaches to biodiversity valuation. This is achieved based on a case study of a transboundary ecological conservation project, the Heart of Borneo (HoB) in Borneo Island, covering Kalimantan in Indonesia, Borneo Malaysia comprising the states of Sarawak and Sabah, and Brunei Darussalam. This study synthesizes critical insights into the multiple ranges of life-supporting environmental values embedded in the HoB natural capital to enhance stronger motivations for environmental conservation. The study also reports on evidence gathered from extensive field studies conducted in Borneo Malaysia, confirming the correlations between environmental beliefs in value pluralism, ecological action, and environmental sustainability, and its implications for sustainable resource use and management. The synthesis is expected to serve as practical guidance for sustainable resource and environmental management decision-making, which is conceptually and universally applicable.
Essential Oil-Based Nano-Biopesticides: Formulation and Bioactivity against the Confused Flour Beetle Tribolium confusum
Authors: Palermo Davide , Giunti Giulia , Laudani Francesca , Palmeri Vincenzo , Campolo Orlando
Published: September 2021

Post-harvest pest control can rely on few approved pesticides and tools; hence, there is a rising interest in new sustainable, eco-friendly approaches. In this study, eight commercial essential oils (EOs) (anise Pimpinella anisum, artemisia Artemisia vulgaris, fennel Foenicum vulgare, garlic Allium sativum, lavender Lavandula angustifolia, mint Mentha piperita, rosemary Rosmarinus officinalis, and sage Salvia officinalis) were selected for their bioactivity and commercial availability, and then formulated in nano-emulsions. Repellency and acute toxicity of the developed nano-formulations were tested against a key stored product pest, Tribolium confusum (Coleoptera: Tenebrionidae). All the developed nano-emulsions presented optimal physical characteristics (droplet dimension = 95.01–144.30 nm; PDI = 0.146–0.248). All the formulations were repellent over time tested against adult beetles, in area preference bioassays. The best repellent was the anise EO-based formulation (RC50 = 0.033 mg). Mortality values from cold aerosol trials showed that the majority of tested EOs caused immediate acute toxicity, and garlic EO nano-emulsion caused the highest mortality of T. confusum adults (LC50 = 0.486 mg/L of air). EO-based nano-insecticides, used as cold aerosol and gel, are promising control methods against stored product pests, which can be integrated and combined with other sustainable biorational approaches.
Busting the ‘Princeling’? Demystifying the Effect of Corporate Depoliticization on Green Innovation: The Moderating Effect of Politician Turnover
Authors: Tang Fei
Published: September 2021

China’s anticorruption efforts and depoliticized provisions trigger government officials to resign from firms, terminating corporate political connections established through managers. This paper addresses corporate depoliticization and its effect on firms’ green strategies. We disentangled how and why depoliticized firms actively take on green innovation and the moderating effect of politician turnover on the above relationship. This paper utilized the data related to China’s privately operated firms from 2008 to 2017 to test its hypothesis. Using the methods of propensity score matching (PSM) and difference-in-difference (DID) to mitigate endogeneity issues, the results indicate that (1) corporate depoliticization can foster green innovation; (2) the exploration of the boundary condition of politician turnover shows that the positive relationship between corporate depoliticization and green innovation is enhanced when depoliticized firms have experienced the changes of government officials; (3) anticorruption shocks can significantly and positively affect green innovation when interacted with a firm with depoliticization. These findings enrich corporate depoliticization and green innovation research.
A Systematic Literature Review on Pricing Strategies in the Sharing Economy
Authors: Yang Meijian , Xia Enjun
Published: September 2021

As an emerging business model, the sharing economy has gained a large amount of academic attention; the pricing problem in the sharing economy has also been widely investigated. Aiming to capture the current state-of-the-art research on pricing strategies in the sharing economy and foreseeing directions for future research, this article conducts a systematic literature review and content analysis of 158 articles from the Scopus and Web of Science databases. As a result, first, this review proposes an extended definition covering B2C and C2C models and a model structure covering the entire supply chain, based on which 158 articles are categorized into nine sub-models covering 30 scenarios. Second, the general characteristics (i.e., research fields, time and journal distributions, research themes and scenarios) and technical details (i.e., theories, methodologies, approaches, models, and conclusions) of the 158 articles are reviewed and summarized by the pricing party, business mode, and scenario. Finally, this review proposes some future research directions of existing scenarios from the perspectives of information asymmetry, market competition, and empirical approaches, and discusses some extensions, including uninvestigated scenarios and COVID-19-related topics; correspondingly, this review suggests some analytical models and empirical approaches that can be employed to fill these gaps. The proposed research directions and corresponding approaches can be references for future research.
Analysis of Smallholders’ Livelihood Vulnerability to Drought across Agroecology and Farm Typology in the Upper Awash Sub-Basin, Ethiopia
Authors: Maru Husen , Haileslassie Amare , Zeleke Tesfaye , Esayas Befikadu
Published: September 2021

Assessing the magnitude of smallholder farmers’ livelihood vulnerability to drought is an initial step in identifying the causal factors and proposing interventions that mitigate the impacts of drought. This study aimed to assess smallholders’ livelihood vulnerability to the drought in the upper Awash sub-basin, Ethiopia. Household (HH) and climate data were used for indicators related to sensitivity, exposure, and adaptive capacity that define vulnerability to drought. The vulnerability of farmers’ livelihood to drought was compared among the studies agroecological zone (AEZ) and farm typologies. The result illustrated a diverse magnitude of vulnerability index (VI) ranging from −1.956 to −4.253 for AEZ. The highest magnitude of VI was estimated for livelihood in the lowland AEZ, while the lowest magnitude of VI was estimated in midland AEZ. This could be accounted for by the fact that lowland farmers shown the highest exposure (0.432) and sensitivity (0.420) and the lowest adaptive capacity (0.288). A closer look at farmers’ livelihood typology, in each of the AEZ, showed substantial diversity of farmers’ livelihood vulnerability to drought, implying potential aggregations at AEZ. Accordingly, the vulnerability index for livestock and on-farm-income-based livelihood and marginal and off-farm-income-based livelihood typologies were higher than the intensive-irrigation-farming-based smallholders’ livelihood typology. Based on the result, we concluded that procedures for smallholders’ livelihood resilience-building efforts should better target AEZ to prioritize the focus region and farmers’ livelihood typology to tailor technologies to farms. Although the result emphasizes the importance of irrigation-based livelihood strategy, the overall enhancement of farmers adaptive capacity needs to focus on action areas such as reducing the sensitivity and exposure of the households, improving farmers usage of technologies, diversify farmers’ livelihood options, and, hence, long-term wealth accumulation to strengthen farmers’ adaptive capacity toward drought impacts.
Student-Performulator: Student Academic Performance Using Hybrid Deep Neural Network
Authors: Yousafzai Bashir Khan , Khan Sher Afzal , Rahman Taj , Khan Inayat , Ullah Inam , Ur Rehman Ateeq , Baz Mohammed , Hamam Habib , Cheikhrouhou Omar
Published: September 2021

Educational data generated through various platforms such as e-learning, e-admission systems, and automated result management systems can be effectively processed through educational data mining techniques in order to gather highly useful insights into students’ performance. The prediction of student performance from historical academic data is a highly desirable application of educational data mining. In this regard, there is an urgent need to develop an automated technique for student performance prediction. Existing studies on student performance prediction primarily focus on utilizing the conventional feature representation schemes, where extracted features are fed to a classifier. In recent years, deep learning has enabled researchers to automatically extract high-level features from raw data. Such advanced feature representation schemes enable superior performance in challenging tasks. In this work, we examine the deep neural network model, namely, the attention-based Bidirectional Long Short-Term Memory (BiLSTM) network to efficiently predict student performance (grades) from historical data. In this article, we have used the most advanced BiLSTM combined with an attention mechanism model by analyzing existing research problems, which are based on advanced feature classification and prediction. This work is really vital for academicians, universities, and government departments to early predict the performance. The superior sequence learning capabilities of BiLSTM combined with attention mechanism yield superior performance compared to the existing state-of-the-art. The proposed method has achieved a prediction accuracy of 90.16%.
Sustainability of the Amazon Nut in Mato Grosso: An Application of the MuSIASEM Method
Authors: Maldonado Thiago Vargas , Allievi Francesca , Panhoca Luiz
Published: September 2021

The Amazon biome occupies 60% of Brazilian territory, configured as a complex metabolism due to its diversity and the history of occupation by humans in the exploitation of its services. The Amazon nut tree (Bertholletia excelsa) occurs in the entire Amazon biome, which is essential for its sustainability. The Amazon nut production chain in the northwest of the State of Mato Grosso presents itself as a relevant case of analysis of the extractive activity of non-timber forest products (NTFP). Based on interpretative assumptions, the multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM) approach is applied to the data collected in a farmers’ cooperative. The objective of this study was to analyze the socio-environmental metabolism of the productive chain of the Amazon nut in the northwest region of the Mato Grosso State (MT) in Brazil. As the MuSIASEM approach can generate an integrated set of indicators measured at different scales and dimensions of analysis, the results show a lack of sustainability in the social dimension, in the environmental dimension, and the presence of intermediaries that serve companies that function as an illegal part of the metabolism. As a next step, the defined method needs testing on different NTFPs and in other micronarratives.
Using Fractionation Profile of Potentially Toxic Elements in Soils to Investigate Their Accumulation in Tilia sp. Leaves in Urban Areas with Different Pollution Levels
Authors: Mitrović Miroslava , Blanusa Tijana , Pavlović Marija , Pavlović Dragana , Kostić Olga , Perović Veljko , Jarić Snežana , Pavlović Pavle
Published: September 2021

Optimal uptake of micronutrients (B, Cu, Fe, Mn, and Zn) and managing the potentially toxic elements (PTEs) (Co, Cr, Ni, Pb, and Sr) in the ranges not detrimental to plant function may be linked to improving plants’ healthy growth and the ability to provide ecosystem services. We investigated concentrations, mobility, and potential availability of potentially toxic elements (PTEs) in soil samples from polluted and non-polluted municipal parks in Reading (UK) and Belgrade (Serbia) and their impact on elemental concentrations in Tilia leaves. We aimed to identify common limiting factors potentially affecting the growth/healthy function of this widely-used tree species. Levels of all elements in soil were below limits established by the directive of European Communities, except for Ni at Belgrade sites. Content of Co, Cr, Cu, Fe, Ni, Pb, and Zn in soluble fraction at all locations was <10%, indicating low mobility; B showed moderate mobility (11.1–20.7%), Mn (6.5–55.6%), and Sr—high (44–76.3%). Principal Component Analysis of Tilia leaf tissues showed a different capacity for uptake/accumulation of PTEs in different locations. Findings indicate the complexity of local edaphic influences on plants’ elemental uptake and the risk of those leading to deficiency of important micronutrients, which may impede trees’ function and thus the ability to optimally provide ecosystem services.
A Novel Concept for Sustainable Food Production Utilizing Low Temperature Industrial Surplus Heat
Authors: Reyes-Lúa Adriana , Straus Julian , Skjervold Vidar T. , Durakovic Goran , Nordtvedt Tom Ståle
Published: September 2021

Low temperature industrial surplus heat represents a major energy source that is currently only rarely utilized due to its low quality. An agricluster allows for the leveraging of this low-quality heat and, hence, may improve the overall energy efficiency. This paper presents the novel concept of an agricluster driven by available surplus heat from industrial processes. We propose the integration of greenhouse production, insect rearing, fish rearing, and drying of seaweed using low temperature surplus heat from the aluminum industry. Each of these processes is already used in or investigated for utilization of surplus heat and partly coupled with other processes, such as in aquaponics. However, the integration of all processes in an agricluster—as proposed in this paper—may result in improved utilization of the surplus heat due to the different seasonality of the heat demand. The potential synergies of this integration approach are discussed in this paper. Furthermore, waste from one process can be utilized as an input stream to other processes, reducing the demand for external material input to the system. The proposed concept of an agricluster is especially interesting for the Nordic countries, as they are dependant on fresh food imports due to the low outside temperatures.
Conceptualizing Smart Manufacturing Readiness-Maturity Model for Small and Medium Enterprise (SME) in Malaysia
Authors: Rahamaddulla Syed Radzi Bin , Leman Zulkiflle , Baharudin B. T. Hang Tuah Bin , Ahmad Siti Azfanizam
Published: September 2021

Manufacturing enterprises today are forced to face radical challenges in the disruptive concepts of Smart Manufacturing (SM) and Industry 4.0 to stay competitive. Most Multinational Enterprise (MNEs) have initiated their journey towards adopting SM. As a mainspring of many manufacturing economies, Small and Medium-Enterprise (SMEs) are still struggling to understand the complexity offered in SM, and many of them are not ready to embrace the concept of SM. To overcome this, SMEs first need to assess their readiness and maturity before embarking on an SM journey. The existing available readiness assessment model seems to be suitable for MNEs, and there is still a lack of tailored models that suit SMEs. This paper sought to pinpoint the conceptual framework from the review of the existing readiness-maturity assessment and identify the gap of existing model as well as proposed a tailored model framework that are suitable for SMEs. Ultimately, this model will be used to pursue a comprehensive scholarly study across Malaysia. The proposed model is enhanced with 4M attributes as the dimension and embedded with the characteristic of Industry 4.0 build component to help the SME’s overcome the possible uncertainties in adopting SM concept.
Effect of New Pre-Emergence Herbicides on Quality and Yield of Potato and Its Associated Weeds
Authors: Abdallah Ibrahim S. , Atia Mohamed A. M. , Nasrallah Amira K. , El-Beltagi Hossam S. , Kabil Farida F. , El-Mogy Mohamed M. , Abdeldaym Emad A.
Published: September 2021

Potato is an economically important vegetable crop in Egypt. Weed infestation, especially broad-leafed, during the vegetative growth stage substantially affects both crop yield and tuber quality. In the current study, the impact of new ready-mix pre-emergent herbicides on broadleaf weeds, tuber yield, and quality was evaluated. The two-year field experiment comprised the following treatments: (1) Un-weeded control, (2) Hand hoeing, (3) Sencor, (4) Ecopart, (5) Zeus, (6) Kroki, and (7) Flomex. The results showed that weed control treatments significantly reduced the weed density compared to un-weeded control and the herbicides efficacy reached over 90%. The herbicidal treatments also significantly increased the activity of antioxidant enzymes peroxidases (POX) and catalase (CAT) and improved the non-enzymatic antioxidant (carotenoids) compared to un-weeded control. Conversely, the higher content of malondialdehyde (MDA) in potato leaves was obtained for un-weeded control. Moreover, weed control treatments caused significant enhancement in plant growth parameters, yield, and its components in addition to tuber quality of potato. Compared to the un-weeded control, maximum tuber yield was observed in Flomex followed by Ecopart, Kroki, Zeus, and Sencor, respectively. The higher number of tubers and total yield were recorded in plants treated with Flomex plus compared to all the other treatments. Higher content of total soluble sugar, total soluble protein, and total starch content was observed in weed control treatments compared with un-weeded control. Based on Pearson’s correlation and heatmap analysis, the changes in agro-physiological parameters data are linked to the herbicidal treatments. The results indicate that the applied herbicides could be alternative products for Sencor and an option for controlling broadleaved weeds. However, further studies are needed to ensure their efficacy and safety under other conditions.
Time-Series Remote Sensing Study to Detect Surface Water Seasonality and Local Water Management at Upper Reaches of Southwestern Bengal Delta from 1972 to 2020
Authors: Huda Nazmul , Terao Toru , Nonomura Atsuko , Suenaga Yoshihiro
Published: September 2021

Bengal delta experiences immense seasonality of surface water due to its geographical position. This study aims to explore the extent and seasonality of surface water in the southwestern part of Bangladesh (SWB) where human intervention has been rapidly changing the land use for several decades. This explorative study relied on a total of 312 high-resolution Landsat images from 1972 to 2020 and interviews to present crucial months, seasons, and periods for surface water in SWB. The study uses a valid threshold point ‘0′ for Normalized Difference Water Index (NDWI) to extract water pixels and confirms that the NIR band has better efficacy to separate water pixels. On average, the SWB has faced around 5.5% of surface water between 1972–2001, which increased to 12.8% between 2002 and 2020. Based on the median value, around 6% of surface water was observed in the 1990s, which increased to 16% in the 2010s. The average surface water was detected around 6% and 7% in December and January between 1972 and 2001, which expanded to 18% and 19% between 2002 and 2020, mainly because of human interventions such as mix-cropping. The study strongly suggests considering December and January months for further land use and land class studies which focus on the southwestern part of Bangladesh.
A Sustainable Approach for the Refurbishment Process of Vernacular Heritage: The Sesga House Case Study (Valencia, Spain)
Authors: Mileto Camilla , Vegas Fernando , Llatas Carmen , Soust-Verdaguer Bernardette
Published: September 2021

The refurbishment of traditional vernacular architecture is currently of interest for the conservation of heritage, historic landscape and cultural landscape, as well as for its potential benefits in the field of environmental sustainability. The carefully selected materials and techniques used in the refurbishment of a traditional dwelling in Sesga (Valencia, Spain) maintain the local construction techniques while causing the least possible environmental impact, saving on transport and transformation and construction energy. This article uses LCA to showcase this contribution, examining three scenarios: the first option is the refurbishment of the case study using natural traditional materials and techniques; the second presents a hypothetical refurbishment using widely used industrial materials; and a third option looks at the demolition of the existing building and the addition of a new construction with widely used industrial materials. This comparison has shown where and why the first option is, broadly speaking, the most sustainable option in environmental, sociocultural and socioeconomic terms.
The Role of Value Appropriation Capability of Chinese Multinationals in Operating Cross-Border Business Models
Authors: Quan Hanxu , Agbanyo George Kwame , Caputo Francesco , Chin Tachia
Published: September 2021

In an ever increasingly competitive and unstable global market, multinational corporations (MNCs) are greatly pressurised to use inherent capacities and develop effective cross-border business models (CBMs) that can transform value into the desired outcome. Amid high uncertainties, MNCs are required to develop some critical capabilities to operate CBMs to the best of their ability. More specifically, it is vital for MNCs to have a unique capability that enables them to more effectively synergise with these commonly recognised capabilities (e.g., technological innovation capabilities (TIC) and marketing capability (MC) alongside the global value chain (GVC)) to sustain balance among and gain profits with stakeholders. From the literature review, we first identified value appropriation capability (VAC) as one of the most important capabilities and thereby developed three hypotheses. Based on the hypotheses, we investigated how VAC efficiently moderates MNCs’ capabilities to appositely operate CBMs. Then, empirical panel data between 2011 and 2019 in the Chinese manufacturing industry were used to examine the hypotheses. The results reveal that VAC, TIC and MC positively impact MNC performance. Moreover, VAC–TIC interaction significantly improves MNC performance, and VAC–MC interaction positively improves MNC performance. Our findings provide novel insights into the CBM literature by examining the importance of VAC for operating CBMs alongside its multifaceted effects on MNC performance, especially in times of uncertainty.
Food Sovereignty and Food Security: Livelihood Strategies Pursued by Farmers during the Maize Monoculture Boom in Northern Thailand
Authors: Charoenratana Sayamol , Anukul Cholnapa , Rosset Peter M.
Published: September 2021

Northern Thailand is the center of a number of controversies surrounding changing cropping patterns, in particular related to deforestation driven by the expansion of maize monocropping by peasant farmers. Growing demand for maize by the global livestock industry has driven the conversion of land from forest and/or shifting cultivation to chemical-intensive maize, with associated environmental (i.e., forest encroachment and annual burning of fields) and social (i.e., farmer indebtedness) problems. Over the years, some of the same farmers have been exposed to ‘alternative development’ programs and projects, initially motivated by pressure to substitute for illegal crops and more recently by concerns over deforestation and particulate matter air pollution from the burning of crop residues. This scenario is made more heterogeneous by a variety of land tenure situations and greater or lesser degrees of community control over land and forest. Faced with varied situations, peasant families can pursue different livelihood strategies, particularly in reference to the degree to which their production is market oriented. Based on surveys and interviews with farmers in Nan and Chiang Mai provinces, over a range of the aforementioned circumstances, we contrast families who pursue what we define as food security (cash cropping to earn money to buy food), food sovereignty (primarily production for self-provisioning) or mixed (a combination of both) strategies. In terms of indicators such as indebtedness, we find greater benefits from the food sovereignty and mixed strategies, though we also find that these are limited by security of land tenure issues, as well as by the degree to which community management of resources is or is not present.
Development and Utilization of Renewable Energy Based on Carbon Emission Reduction—Evaluation of Multiple MCDM Methods
Authors: Li Tao , Li Ang , Song Yimiao
Published: September 2021

With the proposed target of carbon peak and carbon neutralization, the development and utilization of renewable energy with the goal of carbon emission reduction is becoming increasingly important in China. We used the analytic hierarchy process (ANP) and a variety of MCDM methods to quantitatively evaluate renewable energy indicators. This study measured the sequence and differences of the development and utilization of renewable energy in different regions from the point of view of carbon emission reduction, which provides a new analytical perspective for the utilization and distribution of renewable energy in China and a solution based on renewable energy for achieving the goal of carbon emission reduction as soon as possible. The reliability of the evaluation system was further enhanced by confirmation through a variety of methods. The results show that the environment and carbon dimensions are the primary criteria to evaluate the priority of renewable energy under carbon emission reduction. In the overall choice of renewable energy, photovoltaic energy is the best solution. After dividing regions according to carbon emission intensity and resource endowment, areas with serious carbon emissions are suitable for the development of hydropower; areas with sub-serious carbon emissions should give priority to the development of photovoltaic or wind power; high-carbon intensity area I should vigorously develop wind power; high-carbon intensity area II should focus on developing photovoltaic power; second high-carbon intensity areas I and II are suitable for the development of wind power and photovoltaic power; and second high-carbon intensity areas III and IV are the most suitable for hydropower.
Implementing ESD in Schools: Perspectives of Principals in Germany, Macau, and the USA
Authors: Müller Ulrich , Hancock Dawson R. , Stricker Tobias , Wang Chuang
Published: September 2021

To successfully cope with global challenges such as climate change or loss of biodiversity, it will require a substantial change in the ways societies make use of the natural resources of our planet. Education for Sustainable Development (ESD) is expected to support the transformation of societies towards more sustainable ways of thinking, working, and living. Although there is a broad range of literature on ESD, little is known about the role of school leadership in ESD. However, leadership is crucial for the implementation of ESD in schools. This article gives a short overview of the status of ESD within Germany, Macau, and the United States and a literature review on leadership for ESD in schools. It reports on a study that seeks to investigate what principals do in Germany, Macau, and the United States; specifically, what management strategies they use and which competences they need to successfully establish ESD in their schools.
Bifuzzy-Bilevel Programming Model: Solution and Application
Authors: Chen Jiahao , Jiang Yujiao , Wang Guang
Published: September 2021

Bi-level programming is widely used in processing various questions, but it cannot deal with the complex and fuzzy information contained in problems. In order to solve such problems better with intricate and vague information that can be efficiently handled by bifuzzy theory, a bifuzzy–bilevel programming model that sets the parameters to bifuzzy variables is proposed in this paper, which can process complex realistic data more accurately and improve the feasibility and validity of bi-level programming models. To ensure the solvability of the model, the equivalent form of the bifuzzy–bilevel programming model is obtained by utilizing the expected value operator. According to the linear and nonlinear characteristics of the model, the Karush–Kuhn–Tucker condition and particle swarm optimization algorithm are employed to handle the problem, respectively. Finally, by taking the distribution center location problem of the supplier as an example, the bifuzzy–bilevel programming model is applied in practice to balance highly intricate customer demands and corporate cost minimization, obtaining the feasible solution of functions at the upper and lower levels, and the bifuzzy information in the problem can also be processed well, which proves the effectiveness of the proposed methodology.
A Combined Model Based on EOBL-CSSA-LSSVM for Power Load Forecasting
Authors: Wang Xinheng , Gao Xiaojin , Wang Zuoxun , Ma Chunrui , Song Zengxu
Published: September 2021

Inaccurate electricity load forecasting can lead to the power sector gaining asymmetric information in the supply and demand relationship. This asymmetric information can lead to incorrect production or generation plans for the power sector. In order to improve the accuracy of load forecasting, a combined power load forecasting model based on machine learning algorithms, swarm intelligence optimization algorithms, and data pre-processing is proposed. Firstly, the original signal is pre-processed by the VMD–singular spectrum analysis data pre-processing method. Secondly, the noise-reduced signals are predicted using the Elman prediction model optimized by the sparrow search algorithm, the ELM prediction model optimized by the chaotic adaptive whale algorithm (CAWOA-ELM), and the LSSVM prediction model optimized by the chaotic sparrow search algorithm based on elite opposition-based learning (EOBL-CSSA-LSSVM) for electricity load data, respectively. Finally, the weighting coefficients of the three prediction models are calculated using the simulated annealing algorithm and weighted to obtain the prediction results. Comparative simulation experiments show that the VMD–singular spectrum analysis method and two improved intelligent optimization algorithms proposed in this paper can effectively improve the prediction accuracy. Additionally, the combined forecasting model proposed in this paper has extremely high forecasting accuracy, which can help the power sector to develop a reasonable production plan and power generation plans.
Gauging the Higher-Spin-Like Symmetries by the Moyal Product. II
Authors: Cvitan Maro , Prester Predrag Dominis , Giaccari Stefano Gregorio , Paulišić Mateo , Vuković Ivan
Published: September 2021

Continuing the study of the Moyal Higher Spin Yang–Mills theory started in our previous paper we provide a detailed discussion of matter coupling and the corresponding tree-level amplitudes. We also start the investigation of the spectrum by expanding the master fields in terms of ordinary spacetime fields. We note that the spectrum can be consistent with unitarity while still preserving Lorentz covariance, albeit not in the usual way, but by employing an infinite-dimensional unitary representation of the Lorentz group.
Identification of Magnetorheological Layer Properties by Using Refined Plate Theory
Authors: Kernytskyy Ivan , Koda Eugeniusz , Diveyev Bohdan , Horbay Orest , Sopilnyk Lyubomyr , Humenuyk Ruslan , Sholudko Yaroslav , Osinski Piotr
Published: September 2021

In this paper, the dynamic characteristics of sandwich plates with external rigid layers and an upper layer with magnetorheological properties (MR) are investigated. An analysis of the effect of the magnetic field on frequency and loss factor is presented. Vibration can be controlled by a magnetic-rheological viscoelastomer (MRVE), when used in sandwich plates. During vibration, MRVE exhibits an inhomogeneous complex module, which is controlled by an applied magnetic field and depends on the oscillation frequency. Using the dynamic equilibrium conditions, physical and kinematic relationships, and the partial differential equations for the conjugate transverse and longitudinal oscillations of a sandwich plate, are derived. This paper presents a new method for stress analysis that provides accurate stress distributions for multilayer plates subject to cylindrical bending. It uses an adaptive method that does not make strict assumptions about the plate model. Based on the depicted theoretical model, the deformations of each layer of the plate are accounted for, including both transverse shear deformations and transverse normal deformations where the thickness is concerned, and nonlinear displacement changes. The magnetorheological (MR) identification of an inner layer is carried out using refined plate theory and sandwich bending tests. Using combined methods, the possibility of determining the MRVE parameters robustly, is examined.
Simulated Wildfire Smoke Significantly Alters Sperm DNA Methylation Patterns in a Murine Model
Authors: Schuller Adam , Bellini Chiara , Jenkins Timothy , Eden Matthew , Matz Jacqueline , Oakes Jessica , Montrose Luke
Published: September 2021

Wildfires are now a common feature of the western US, increasing in both intensity and number of acres burned over the last three decades. The effects of this changing wildfire and smoke landscape are a critical public and occupational health issue. While respiratory morbidity due to smoke exposure is a priority, evaluating the molecular underpinnings that explain recent extrapulmonary observations is necessary. Here, we use an Apoe−/− mouse model to investigate the epigenetic impact of paternal exposure to simulated wildfire smoke. We demonstrate that 40 days of exposure to smoke from Douglas fir needles induces sperm DNA methylation changes in adult mice. DNA methylation was measured by reduced representation bisulfite sequencing and varied significantly in 3353 differentially methylated regions, which were subsequently annotated to 2117 genes. The differentially methylated regions were broadly distributed across the mouse genome, but the vast majority (nearly 80%) were hypermethylated. Pathway analyses, using gene-derived and differentially methylated region-derived gene ontology terms, point to a number of developmental processes that may warrant future investigation. Overall, this study of simulated wildfire smoke exposure suggests paternal reproductive risks are possible with prolonged exposure.
MTF1 Is Essential for the Expression of MT1B, MT1F, MT1G, and MT1H Induced by PHMG, but Not CMIT, in the Human Pulmonary Alveolar Epithelial Cells
Authors: Jeong Sang-Hoon , Kim Cherry , Kim Jaeyoung , Nam Yoon-Jeong , Lee Hong , Togloom Ariunaa , Kang Ja-Young , Choi Jin-Young , Lee Hyejin , Song Myeong-Ok , Park Eun-Kee , Baek Yong-Wook , Lee Ju-Han , Lee Ki-Yeol
Published: September 2021

The inhalation of humidifier disinfectants (HDs) is linked to HD-associated lung injury (HDLI). Polyhexamethylene guanidine (PHMG) is significantly involved in HDLI, but the correlation between chloromethylisothiazolinone (CMIT) and HDLI remains ambiguous. Additionally, the differences in the molecular responses to PHMG and CMIT are poorly understood. In this study, RNA sequencing (RNA-seq) data showed that the expression levels of metallothionein-1 (MT1) isoforms, including MT1B, MT1E, MT1F, MT1G, MT1H, MT1M, and MT1X, were increased in human pulmonary alveolar epithelial cells (HPAEpiCs) that were treated with PHMG but not in those treated with CMIT. Moreover, upregulation of MT1B, MT1F, MT1G, and MT1H was observed only in PHMG-treated HPAEpiCs. The protein expression level of metal regulatory transcription factor 1 (MTF1), which binds to the promoters of MT1 isoforms, was increased in PHMG-treated HPAEpiCs but not in CMIT-treated HPAEpiCs. However, the expression of early growth response 1 (EGR1) and nuclear receptor superfamily 3, group C, member 1 (NR3C1), other transcriptional regulators involved in MT1 isomers, were increased regardless of treatment with PHMG or CMIT. These results suggest that MTF1 is an essential transcription factor for the induction of MT1B, MT1F, MT1G, and MT1H by PHMG but not by CMIT.