bluuebunny/crossref_metadata_2025 huggingface dataset:
3D Numerical Analysis for the Valorization Potential of Spoil Heaps by Shallow Foundations
Authors: Theocharis Alexandros I. , Zevgolis Ioannis E. , Roumpos Christos , Koukouzas Nikolaos C.
Published: June 2022

Coal has been an energy source exploited for several decades, with its extraction being linked to creating wastes. Surface mines’ overburden and interburden materials are typically dumped in spoil heaps, many times without considering their future use. Nowadays, sustainability and circular economy principles demand the efficient valorization of these areas. In that vein, this work investigates alternatives from a geotechnical perspective with shallow foundations for the reclamation of a massive spoil heap. Initially, the installation with a raft foundation of a wind turbine was investigated through a serviceability limit envelope employing 3D finite element analysis. However, the spoil material is too soft to withstand such a massive superstructure, and more advanced foundation techniques are needed. Moreover, the installation of supportive constructions was examined, i.e., buildings with shallow isolated footings using a similar approach and 3D finite element analysis. The soil-footing response is much dependent on the constitutive model, and the potential of small buildings requires further attention. Overall, for the appropriate valorization of the spoil heap, it appears that ground improvement or deep foundations are necessary. This conclusion stands for many similar spoil heaps globally due to the material’s nature.
Relationship beyond the Workplace: Impact of Guanxi GRX Scale on Employee Engagement and Performance
Authors: Ameyaw Moses Agyemang , Sun Binghai , Antwi Samuel , Bentum-Micah Geoffrey , Ameyaw Jonathan Edmund
Published: June 2022

The primary objective of this research was to find out the impact of GRX scale (ganqing, renqing, and xinren) on a non-Chinese working environment. Thus, to apply and ascertain the effect of the three dimensions of guanxi on employees’ engagement and, eventually, their job performance in an African working environment. This research used social exchange theory to explain the relationship between supervisors and their subordinates. The research data comprises 530 respondents who were randomly chosen from seven organizations. Smart-PLS 3.2.8 was the primary instrument used to analyze the data. The finding indicated that renqing, synonymous with mutual sharing or need for reciprocity, was highly significant with employee engagement and job performance. Hence, a win-win outcome is achieved whenever employers exhibit genuine concern and care for their employees. Additionally, there was a negative relationship between ganqing (emotional attachment) and employee engagement. This revealed that making decisions based on personal relationships will negatively affect employees’ engagement and job performance. This research adds to the literature by revealing that guanxi is applicable in non-Chinese workplaces.
Voluntary Sustainability Disclosures in Non-Listed Companies: An Exploratory Study on Motives and Practices
Authors: Carmo Cecília , Miguéis Mercedes
Published: June 2022

The aim of this study is to investigate the reasons for the voluntary preparation of a sustainability report and to identify sustainability disclosure practices in the context of non-listed companies. For this purpose, a multiple case study methodology involving five manufacturing Portuguese companies was employed. Data collection consisted of a mixed approach involving interviews with the sustainability report preparers, and content analysis of sustainability reports and company webpages. The results show two main reasons to initiating voluntary sustainability reporting: requirements from specific customers and the parent company, and the need to communicate with stakeholders, in particular customers, the local community, and suppliers. Companies reveal knowledge of sustainability-related concepts and apply frameworks such as GRI Standards and SDG in preparing their sustainability reports. Several departments are involved in preparing the sustainability report (sustainability, quality, environment, human resources, marketing, and/or communication departments), but no company mentioned the financial department. Moreover, on the webpages, sustainability reports and annual reports tend to be presented in separate sections, suggesting that companies still have a way to go in integrating sustainability information with financial information. Overall, the results show that institutional, stakeholder, legitimacy, and signaling theories can provide explanations for the motives and practices adopted by non-listed companies in voluntarily disclosing sustainability information.
Sustainable Operation of Unmanned Ships under Current International Maritime Law
Authors: Boviatsis Michael , Vlachos George
Published: June 2022

The aim of this paper is to evaluate the current international maritime legislative framework and assess its relevance in sustaining the operations of unmanned ships while addressing the issue of liability from system malfunctions. The paper initially explores the legal definition of a ship and evaluates whether the existence of an on-board crew is an integral part of the definition. Subsequently, the analysis continues with assessing the legal implications and challenges for the sustainable operation of unmanned ships, such as the governing flag state legislation that defines liability parameters, taking into consideration the existing levels of vessel automation. The paper concludes with an evaluation of the contractual issues and potential stakeholder liability related to governing a flag state. In addition, the potential transfer of liability from the ship operators to manufacturers as pertains to unmanned ship operation is also addressed. The concluding remarks suggest that unmanned ship operation is sustainable under the current international maritime legislative framework; however, the current legislation should be considered as a baseline from which specific legislation for the operation of unmanned ships can be drawn. The methodology utilised for this paper is based on the legal doctrine.
Vertisols in the Ethiopian Highlands: Interaction between Land Use Systems, Soil Properties, and Different Types of Fertilizer Applied to Teff and Wheat
Authors: Elias Eyasu , Biratu Gizachew Kebede , Smaling Eric M. A.
Published: June 2022

Vertisols are among the most extensive soil types in the Ethiopian highlands, occurring in a wide range of agro-ecological zones where complex crop–livestock-based farming systems are practiced. Sustainable soil management on vertisols always meets with physical characteristics that are driven by clay mineralogy, swelling, shrinking, and risk of temporary waterlogging. The latter causes substantial spatial variability and turns vertisols into obnoxious study material, when compared to other soil classification orders. In this study, we have explored soil properties across different farming systems using soil profile and analytical data generated by the CASCAPE project; an action research project funded by the Dutch government for capacity building on the scaling up of evidence-based best practices for increased agricultural production in Ethiopia. In addition, the effects of variations in vertisol properties on crop yield and fertilizer response were examined through fertilizer trials in different locations. Teff (Eragrostis teff Zucc.) and wheat (Triticum aestivium), the two cereal crops commonly grown on vertisols, were used as test crops. Five treatments of NPSZnB—nitrogen, phosphorous, sulfur, zinc and boron containing blend (50, 100, 150, 200 and 300 kg/ha)—and two treatments comparing NPS and diammonium phosphate (DAP) with the blend containing Zn and B were included in a randomized complete block design with three replications. Results revealed that soil quality was generally poor under the highland cereal systems, i.e., sorghum–teff–livestock mixed system (FS1) and wheat–maize–teff–barley–livestock system (FS2) compared to the enset–coffee–cereal–livestock complex system (FS3), which cannot only be attributed to geological history, but also to the way the land use systems have shaped the soils. The emerging differences in soil properties significantly (p < 0.01) affected crop yields. The soil properties that had the largest influence on teff and wheat yield were soil pH, organic carbon (OC), available sulfur (S), exchangeable potassium (K) and some micronutrients (B, Fe, Mn and Cu). Teff grain and biomass yield were inversely related, unlike wheat. Regarding the rate of fertilizer application, wheat responded significantly up to the highest level (300 kg/ha), but teff yield leveled off earlier. The blend fertilizers did not perform any better than NPS or DAP alone. Given the extent and the importance of vertisols in Ethiopian agriculture, comprehensive future outlooks are needed, including the options for cluster farming and mechanization to realize economies of scale and more efficient use of capital and labor inputs.
Self-Attention ConvLSTM for Spatiotemporal Forecasting of Short-Term Online Car-Hailing Demand
Authors: Ge Hongxia , Li Siteng , Cheng Rongjun , Chen Zhenlei
Published: June 2022

As a flourishing basic transportation service in recent years, online car-hailing has made great achievements in metropolitan cities. Accurate spatiotemporal forecasting plays a significant role in the deployment of a network for online car-hailing demand services. A self-attention mechanism in convolutional long short-term memory (ConvLSTM) is proposed to accurately predict the online car-hailing demand. It can more effectively address the disadvantage that ConvLSTM is not good at capturing spatial correlation over a large spatial extent. Furthermore, it can generate features by aggregating pair-wise similarity scores of features at all positions of input and memory, and thus obtain the function of long-range spatiotemporal dependencies. First, the online car-hailing trajectories dataset was converted into images after geographic grid matching, and image enhancement was performed by cropping. Then, the effectiveness of the ConvLSTM embedded with a self-attention mechanism (SA-ConvLSTM) was demonstrated by comparing it to existing models. The experimental results showed that the proposed model performed better than the existing models, and including spatiotemporal information in images would perform better predictions than including spatial information in time-series pixels.
Interpretable Machine Learning Models for Malicious Domains Detection Using Explainable Artificial Intelligence (XAI)
Authors: Aslam Nida , Khan Irfan Ullah , Mirza Samiha , AlOwayed Alanoud , Anis Fatima M. , Aljuaid Reef M. , Baageel Reham
Published: June 2022

With the expansion of the internet, a major threat has emerged involving the spread of malicious domains intended by attackers to perform illegal activities aiming to target governments, violating privacy of organizations, and even manipulating everyday users. Therefore, detecting these harmful domains is necessary to combat the growing network attacks. Machine Learning (ML) models have shown significant outcomes towards the detection of malicious domains. However, the “black box” nature of the complex ML models obstructs their wide-ranging acceptance in some of the fields. The emergence of Explainable Artificial Intelligence (XAI) has successfully incorporated the interpretability and explicability in the complex models. Furthermore, the post hoc XAI model has enabled the interpretability without affecting the performance of the models. This study aimed to propose an Explainable Artificial Intelligence (XAI) model to detect malicious domains on a recent dataset containing 45,000 samples of malicious and non-malicious domains. In the current study, initially several interpretable ML models, such as Decision Tree (DT) and Naïve Bayes (NB), and black box ensemble models, such as Random Forest (RF), Extreme Gradient Boosting (XGB), AdaBoost (AB), and Cat Boost (CB) algorithms, were implemented and found that XGB outperformed the other classifiers. Furthermore, the post hoc XAI global surrogate model (Shapley additive explanations) and local surrogate LIME were used to generate the explanation of the XGB prediction. Two sets of experiments were performed; initially the model was executed using a preprocessed dataset and later with selected features using the Sequential Forward Feature selection algorithm. The results demonstrate that ML algorithms were able to distinguish benign and malicious domains with overall accuracy ranging from 0.8479 to 0.9856. The ensemble classifier XGB achieved the highest result, with an AUC and accuracy of 0.9991 and 0.9856, respectively, before the feature selection algorithm, while there was an AUC of 0.999 and accuracy of 0.9818 after the feature selection algorithm. The proposed model outperformed the benchmark study.
The Effect of the COVID-19 Pandemic on the Labor Markets of the Visegrad Countries
Authors: Zieliński Mariusz
Published: June 2022

The COVID-19 pandemic caused a sudden and deep recession contributing, among other things, to a sharp rise in unemployment. The article addresses changes in the labor markets of the Visegrad countries (Czechia, Hungary, Poland, and Slovakia), covering the period 2018–2021. It attempts to answer the questions: how deep a slump was caused by the pandemic in these markets, how flexible forms of employment responded to it, and whether there were discriminatory phenomena (decline in employment and increase in unemployment in the most vulnerable groups in the labor market). The analysis was based on quarterly data published by Eurostat on the size and structure of the employed and unemployed population. The results of the compilations indicate a relatively small deepening of imbalances in the labor markets of the analyzed countries, a differentiated reaction of flexible forms of employment (depending on the form of employment), which was in line with expectations (they were used as a business cycle buffer). In most of the V4 countries, women were relatively less likely to lose their jobs than men during the pandemic. In a few cases, a relatively stronger decline in employment (increase in unemployment) affected young people, people aged 55–64, and people with the lowest education.
An Advanced and Robust Approach to Maximize Solar Photovoltaic Power Production
Authors: Alaraj Muhannad , Kumar Astitva , Alsaidan Ibrahim , Rizwan Mohammad , Jamil Majid
Published: June 2022

The stochastic and erratic behavior of solar photovoltaic (SPV) is a challenge, especially due to changing meteorological conditions. During a partially irradiated SPV system, the performance of traditional maximum power point tracking (MPPT) controllers is unsatisfactory because of multiple peaks in the Power-Voltage curve. This work is an attempt to understand the performance uncertainties of the SPV system under different shading conditions and its mitigation. Here, a novel hybrid metaheuristic algorithm is proposed for the effective and efficient tracking of power. The algorithm is inspired by the movement of grey wolves and the swarming action of birds, and is thus known as the hybrid grey wolf optimizer (HGWO). The study focuses on the transient and steady-state performance of the proposed controller during different conditions. A comparative analysis of the proposed technique with incremental conductance and a particle swarm optimizer for different configurations is presented. Thus, the results are presented based on power extracted, shading loss, convergence factor and efficiency. The proposed HGWO–MPPT is found to be better as it has a maximum efficiency of 94.30% and a minimum convergence factor of 0.20 when compared with other techniques under varying conditions for different topologies. Furthermore, a practical assessment of the proposed controller on a 6.3 kWp rooftop SPV system is also presented in the paper. Energy production is increased by 8.55% using the proposed approach to the practical system.
Improving the Material and Financial Circularity of the Plastic Packaging Value Chain in The Netherlands: Challenges, Opportunities, and Implications
Authors: Çevikarslan Salih , Gelhard Carsten , Henseler Jörg
Published: June 2022

This article outlines a bespoke process for uncovering crucial economic and social considerations in the quest to convert the Dutch plastic packaging system from a linear to a circular economy. Using a serious game tool as part of a qualitative research method, we developed, prioritized, and elaborated on various conceivable and effective policies that would create a circular plastic packaging value chain in The Netherlands. A key aim of this study was to fill a gap in the predominantly technical-focused research in this area by offering a holistic overview of how a circular economy impacts key industry stakeholders and their business models, as well as highlight system-level consequences of these policies, were they to be adopted. We used simulation and statistical analyses to explore the effects of these policies on the material and financial circularity of the Dutch plastic packaging value chain. The results reflect that one of the policies—establishing a center of excellence —would benefit the Dutch plastic packaging system the most.
Planning Sustainable Community-Based Tourism in the Context of Thailand: Community, Development, and the Foresight Tools
Authors: Chatkaewnapanon Yuthasak , Lee Timothy J.
Published: June 2022

Community-Based Tourism (CBT) has been heavily promoted in Thailand, particularly in rural communities. Tourism transforms the natural and culturally significant attractions of rural communities into consumer products. Tourism development also makes a direct connection between tourism and the community. Therefore, before starting a tourism development project, the interests of local residents need to be investigated and allowances made for their inclusion. This paper introduces foresight tools, community arts, and a community goal-setting technique for putting the authority of future tourism development in the hands of the local community, which is appropriate for tourism development in rural Thailand. This study aims to give the local community useful tools to design their own future development by helping its members develop an understanding of what tourism is and how it impacts their community. A series of inclusive workshops was used to emphasize the need to understand the opportunities and repercussions of tourism as a community, what is at stake, and how important it is to participate in development projects. This methodology was chosen to advance the community members’ ability to generate ideas about what kind of tourism products the community has the potential to develop. Furthermore, it aims to get locals to understand that tourism development is more than just getting that development started. Reaching their future goals requires continuing their tourism activities. Therefore, the two workshops we held advocated community arts and community goal-setting techniques as foresight tools to empower communities to design their future and gave support to those communities to improve the quality of their participation in tourism.
Changes in Temporal Dynamics and Factors Influencing the Environment of the Bacterial Community in Mangrove Rhizosphere Sediments in Hainan
Authors: Lu Kaiqi , Yang Qiu , Jiang Yamin , Liu Wenjie
Published: June 2022

The structural characteristics of the rhizosphere soil’s microbial community is crucial to understanding the ecological function of mangroves. However, the mechanism influencing mangrove plants in soil microbial communities has yet to be determined. Here, the mangrove ecosystem of Xinying Mangrove National Wetland Park in Hainan Province was taken as the research object. The microbial communities, external regulatory factors, and the relationship between communities were analyzed using 16S rRNA high-throughput sequencing in the rhizosphere and non-rhizosphere sediments of mangrove forests under different spatiotemporal conditions. The results showed that there was no significant difference in the α-diversity of the bacterial community between the rhizosphere and non-rhizosphere sediments. However, β-diversity was significantly different. Redundancy analysis (RDA) showed that other environmental factors besides sulfide and Fe2+ affected the bacterial community structure in sediments. The co-occurrence pattern analysis of bacteria in the mangrove ecosystem indicates that the bacteria in rhizosphere sediments were more closely related than those in non-rhizosphere sediments. The results reveal significant differences between the rhizosphere and non-rhizosphere bacterial community diversity, structure, and their interaction in the mangrove ecosystem. Therefore, the ecological system of the mangrove wetland needs to be preserved and rehabilitated, which would have a tremendous impact on the sustainable development.
Enhancing Green Finance for Inclusive Green Growth: A Systematic Approach
Authors: Desalegn Goshu , Tangl Anita
Published: June 2022

Recently, green financing has become a popular technique for dealing with environmental issues. However, whether green financing is effective in addressing current global environmental issues remains to be seen since the green investment gap has been discovered to be rather sizable, with no certainty regarding how to fill it. The purpose of this study was to systematically analyze green finance in all of its forms, instruments, and measurements. Herein, we highlighted overall research trends in an effort to enhance green finance for inclusive green investment, as well as examined the progress needed to fill the green finance gap. This study also provides information on which authors, countries, publishers, and journals are contributing most to green finance. The methodological approach used in many reviewed papers was determined as a benchmark for those authors interested in green finance. Moreover, this study critically analyzes and summarizes 146 relevant studies. The results of our review study imply that the green financing gap is frequently observed because of low finance levels, poor green project selection/management, risk and return trade-off, and a lack of analytical tools and expertise in identifying and assessing green project risks. More specifically, regulatory issues have been observed as the main challenge in enhancing green finance. Therefore, we propose further studies to be conducted on how to enhance green finance for green investment that could deliberately affect green growth. Simultaneously, we noted what incentives could initiate private investors to make green investments, and what additional green financing methods should be introduced to fill the financing gap. Finally, this study seeks to have an impact in assisting future studies to consider the status of each country in terms of green finance mobilization and capital contribution by sharing the specific experience of that country and what lessons could be learned from that country.
Input–Output Efficiency of Chinese Power Generation Enterprises and Its Improvement Direction-Based on Three-Stage DEA Model
Authors: Zhao Wenhui , Qiu Ye , Lu Wei , Yuan Puyu
Published: June 2022

This paper uses the three-stage DEA method to measure the input–output efficiency of China’s 23 listed power generation companies (mainly thermal power generation) in 2019, and uses the SFA regression model to eliminate environmental elements and random disturbances. The results show that in a non-homogeneous environment, the scale efficiencies of most power generation companies are greater than or equal to their pure technical efficiencies. These companies should first improve management and technical levels, and then optimize the scale of investment. Furthermore, after removing environmental variables, half of the companies should turn to increasing economies of scale instead of diminishing economies of scale. It can be seen that environmental factors, such as the degree of regional development and IPO time, have reduced the economies of scale of enterprises, so they should strengthen the communication between different regions, and the government should provide assistance to companies that are listed late.
The Impacts of a COVID-19 Related Lockdown (and Reopening Phases) on Time Use and Mobility for Activities in Austria—Results from a Multi-Wave Combined Survey
Authors: Hartwig Lukas , Hössinger Reinhard , Susilo Yusak Octavius , Gühnemann Astrid
Published: June 2022

When activity locations were shut down in the first lockdown to prevent the spread of COVID-19 in Austria, people reduced their trips accordingly. Based on a dataset obtained through a weeklong mobility and activity survey we analyse mobility and time use changes, as well as changes in activity locations and secondary activities. Regression analysis is used to analyse differences in time use changes between socio-demographic groups. We show that trip rates and distances as well as public transport use dropped significantly during the lockdown and did not recover fully in the subsequent opening phase. Former travel time was used for additional leisure, sleep, domestic tasks, and eating in the lockdown, but only the latter two retained their increases in the opening phase. The lockdown resulted in a convergence of time use of socio-demographic groups with formerly different patterns, but the differences reappeared in the opening phase. Our findings are consistent with results from the literature but offer an integrated perspective on mobility and time use not found in either mobility- or time use-focussed studies. We conclude that there is a potential for trip reduction through a shift to virtual performance of activities, but the extent of this shift in post-pandemic times remains unclear.
Close Interval Approximation of Pentagonal Fuzzy Numbers for Interval Data-Based Transportation Problems
Authors: Juman Z. A. M. S. , Mostafa Salama A. , Batuwita A. P. , AlArjani Ali , Sharif Uddin Md , Jaber Mustafa Musa , Alam Teg , Attia El-Awady
Published: June 2022

Due to globalization in this modern age of technology and other uncontrollable influences, transportation parameters can differ within a certain range of a given period. In this situation, a managerial position’s objective is to make appropriate decisions for the decision-makers. However, in general, the determination of an exact solution to the interval data-based transportation problem (IDTP) becomes an NP-hard problem as the number of choices within their respective ranges increases enormously when the number of suppliers and buyers increases. So, in practice, it is difficult for an exact method to find the exact solution to the IDTP in a reasonable time, specifically the large-sized problems with large interval sizes. This paper introduces solutions to the IDTP where supply, demand, and cost are all in interval numbers. One of the best interval approximations, namely the closed interval approximation of pentagonal fuzzy number, is proposed for solving the IDTP. First, in the proposed closed interval approximation method (Method-1), the pentagonal fuzzification method converts the IDTP to a fuzzy transportation problem (FTP). Subsequently, two new ranking methods based on centroid and in-center triangle concepts are presented to transfer the pentagonal fuzzy number into the corresponding crisp (non-fuzzy) value. Thereafter, the optimal solution was obtained using Vogel’s approximation method coupled with the modified distribution method. The proposed Method-1 is reported against a recent method and shows superior performance over the aforementioned and a proposed Method-2 via benchmark instances and new instances.
Theoretical Study on the Effect of Parallel Air Chambers Embedded in Rockwool Panels on the Energy Consumption of a Low-Energy High School
Authors: Ene Raul C. , Brata Silviana , Boros Iosif , Chendes Remus , Dan Daniel
Published: June 2022

In the construction industry, sustainability is evaluated, not only in terms of harmful emissions generated during the operation phase, but also in terms of the embodied emissions belonging to building materials and technical equipment. As a consequence, the implementation of highly efficient building materials has become crucial. The objective of this study is to investigate an insulation system based on parallel air chambers embodied in rockwool panels, and to correlate the implications of its implementation compared to an existing insulation system. The analysis was conducted on the first administrative/public building completed in Romania, according to passive house standards. The study begins with experimental investigations of insulation systems under laboratory conditions. Thus, the influence of air layers on the thermal properties of existing rockwool panels was assessed. On the basis of the experimental results, the theoretical energy demand of the high school building and life cycle analysis are determined using simulation software for both insulation solutions: existing insulation composed of solid rockwool panels, and rockwool panels with embedded air layers. The thickness of the insulating air layers is optimized, and with the help of Rayleigh–Bénard equations for each of the five climate zones that were further determined. Taken together, it is expected to achieve a better insulation system by maintaining constant embedded emissions. In conclusion, assuming a 50-year life cycle for the high school building, the insulation system composed of rockwool with embedded air layers brings about a reduction in the total energy consumption of approximately 9.82%, compared to the case of a standard insulation system based on solid rockwool panels without additional air layers.
A Novel Sustainable Processing Mode for Burr Classified Prediction of Weak Rigid Drilling Process Using a Fusion Modeling Method
Authors: Ding Siyi , Zheng Xiaohu , Wu Mingyu , Yang Qirui
Published: June 2022

Weakly rigid drilling systems, such as the industrial robot, are widely used in aerospace, military, and other fields due to its good flexibility and large scope of operation. However, the weak rigidity can easily cause burrs, seriously affecting the precision of parts and product performance. To reduce the heavy deburring process and to improve continuous production and sustainable processing capacity, accurate prediction of burr quality is a prerequisite. Traditional burr forming theory cannot accurately predict the drilling defects. Data-driven approaches can be independent of prior knowledge and discover relationships between process parameters and machining precision directly from the data structure itself. Therefore, to take advantage of both approaches, a fusion model was established for burr classified prediction. On the one hand, the drilling and burr forming process was firstly modeled, and preliminary classification results for burrs were calculated. On the other hand, according to the measured data, the errors between initial calculation results and actual classification results were obtained and selected as the tag values of dataset, which served as inputs for the error compensation model of burrs. Finally, by training the network of TCN–DNN using the drilling data, the burr classified prediction in a weak rigid hole-making system was realized. Experimental results showed that compared with traditional drilling theory, the prediction accuracy of the proposed model improved by 25%, reaching 91.67%. The results can provide a basis for judging the process of burr post-treatment, which has practical guiding significance. This method is beneficial to reduce the heavy deburring process and to improve sustainable processing capacity.
Protected Cultivation of Horticultural Crops as a Livelihood Opportunity in Western India: An Economic Assessment
Authors: Pachiyappan Prakash , Kumar Pramod , Reddy Krishna Viswanatha , Kumar Kotamraju N. Ravi , Konduru Srinivasa , Paramesh Venkatesh , Rajanna Gandhamanagenahalli A. , Shankarappa Shashidhar K. , Jaganathan Duraisamy , Immanuel Sheela , Kamble Ankush L. , Selvakumar Raman , Immanuelraj Kingsly T. , Manogaran Boopathy Raja , Perumal Anbukani , Maruthanayagam Umamageswari , Niranjan Sivalingam
Published: June 2022

Protected cultivation is an innovative way of raising seasonal and off-seasonal crops under a controlled environment. Vegetables and flower crops have tremendous potential to augment productivity, generate employment, utilize land efficiently and enhance export. This study was undertaken to assess the economic feasibility of protected cultivation in the high export potential zones of the Pune and Nasik districts of Maharashtra, India, by employing project analytical tools and the regression model. The results revealed that the cultivation of flowers and vegetables under protected cultivation was highly lucrative with high investment. The protected cultivation of rose and capsicum had higher cultivation cost (300%), gross return (250%) and net return (190%) as compared to open cultivation. Moreover, most of the crops grown in polyhouses are highly profitable at different discount rates (7%, 10% and 12%), whereas a few crops were rewarding under shade net condition with subsidies. Factors such as literacy (p < 0.05), income (p < 0.05), access to subsidy (p < 0.05) and the risk orientation index (p < 0.01) were found statistically significant in technology adoption. In the context of a changing climate and shrinking land resources, water scarcity, incidence of pests and diseases, an ever-increasing population, low productivity under open conditions and changes in consumer’s preference are the drivers for switching over to protected cultivation. In the recent past, protected cultivation has been gaining importance in different parts of the country, including Maharashtra. The policy implications are creating modern infrastructure, enhanced application of ICTs, maximum crop production with minimum utilization of land and institutional support to promote technology on a commercial scale.
Does the Inclusion of Spatio-Temporal Features Improve Bus Travel Time Predictions? A Deep Learning-Based Modelling Approach
Authors: Lee Gyeongjae , Choo Sangho , Choi Sungtaek , Lee Hyangsook
Published: June 2022

With the abundance of public transportation in highly urbanized areas, it is common for passengers to make inefficient or flawed transport decisions due to a lack of information. The exact arrival time of a bus is an example of such information that can aid passengers in making better decisions. The purpose of this study is to provide a method for predicting path-based bus travel time, thereby assisting accurate bus arrival and departure time predictions at each bus stop. Specifically, we develop a Geo-conv Long Short-term Memory (LSTM) model that (1) extracts subsequent spatial features through a 1D Convolution Neural Network (CNN) for the entire bus travel sequence and (2) captures the temporal dependencies between subsequences through the LSTM network. Additionally, this study utilizes additional variables that affect two components of bus travel time (dwelling time and transit time) to precisely predict travel time. The constructed model is then evaluated by the practical application to two bus lines operating in Seoul, Korea. The results show that our model outperforms three other baseline models. Two bus lines with different types of operation show different model performance patterns that are dependent on travel distance. Interestingly, we find that the variable related to the link of the stop location appears to play an important role in predicting bus travel time. We believe that these novel findings will contribute to the literature on transportation and, in particular, on deep learning-based travel time prediction.
Thermal Properties of Novel Phase-Change Materials Based on Tamanu and Coconut Oil Encapsulated in Electrospun Fiber Matrices
Authors: Paroutoglou Evdoxia , Fojan Peter , Gurevich Leonid , Afshari Alireza
Published: June 2022

The accumulation of thermal energy in construction elements during daytime, and its release during a colder night period is an efficient and green way to maintain a comfortable temperature range in buildings and vehicles. One approach to achieving this goal is to store thermal energy as latent heat of the phase transition using the so-called phase-change materials (PCMs). Vegetable oils came recently into focus as cheap, widely available, and environmentally friendly PCMs. In this study, we report the thermal properties of PCMs based on tamanu and coconut oils in three configurations: pure, emulsion, and encapsulated forms. We demonstrate the encapsulation of pure coconut- and tamanu-oil emulsions, and their mixtures and mixtures with commercial PCM paraffins in fiber matrices produced by a coaxial electrospinning technique. Polycaprolactone (PCL) was used as a shell, the PCM emulsion was formed by the studied oils, and sodium dodecyl sulfate (SDS) and polyvinyl alcohol (PVA) were used as emulsifiers. The addition of commercially available paraffin RT18 into a 70/30 mixture of coconut and tamanu oil, successfully encapsulated in the core of a PCL shell, demonstrated latent heats of melting and solidification of 63.8 and 57.6 kJ/kg, respectively.
The Substitution Effect of Chinese Anti-Corruption “Alcohol Ban”
Authors: Ma Yiyuan , Xiao Youzhi
Published: June 2022

Over the past decade, China has intensified its anti-corruption efforts. On 21 December 2012, “Alcohol Consumption Prohibition at Military Functions” was announced, which made the consumption of high-end Chinese Baijiu decline. We apply principal-agent theory to analyze the potential substitution effect, and then, we apply the difference in difference model and event study method to test the substitution effect between Baijiu and foreign alcohol by using macro- and micro-data. The results indicate that, in response to the “Alcohol Ban”, the Chinese consume more imported wine and more expensive foreign spirits. What is more, the CARs of high-end alcohol companies listed on the U.S. stock market significantly increase. We conclude that there exist substitution effects after the “Alcohol Ban”, which is necessary for the government to comprehensively investigate when formulating policies, because it may partially weaken the effectiveness of the policy.
Preference Heterogeneity of Local Participation in Coupling Conservation and Community-Based Entrepreneurship Development
Authors: Saengavut Voravee , Somswasdi Chintana
Published: June 2022

The aims of conservation and economic prosperity for people living near protected areas have rapidly acquired prominence as a viable strategy for global biodiversity protection. To identify potential local enterprise improvement, we examine how rural communities adopt integrated conservation and development programs. Choice experiments are used to establish villagers’ preferences for conservation incentives. The incentive structure as well as attitudes regarding ecosystem services are being investigated. The latent class technique was used to estimate preference parameters, which resulted in two segments that accounted for villager heterogeneity. These segments were discovered through program restrictions, each with different resource usage, time spent, and compensation. Members of the more restrictive program desire a higher reward for participation in one program over another. Attitudes toward provisioning and regulating ecosystem services influence their engagement. The findings show that the younger generation is open to less restrictive programs and sharing resources to boost community enterprises. They are prepared to forego a few hours of farming in exchange for conservation actions. Programs that allow for flexibility in conservation regulations and other program features may be the most effective way to encourage more people to participate in conservation programs while also satisfying community goals.
Innovation and Technological Management Model in the Tequila Sector in Mexico
Authors: Terán-Bustamante Antonia , Martínez-Velasco Antonieta , Castillo-Girón Víctor Manuel , Ayala-Ramírez Suhey
Published: June 2022

Creativity, ideas, and an entrepreneurial attitude are needed to innovate. However, it is also necessary to have practical instruments that allow innovations to be reflected in the company. One of those tools is technology. This research aims to analyze innovation and technology in the tequila industry through Bayesian networks with machine learning techniques. Likewise, an innovation and technology management model will be developed to make better decisions, which will allow the company to innovate to generate competitive advantages in a mature low-tech industry. A model is made in which the critical factors that influence management innovation and technology optimally to generate value translate into competitive advantages. The evidence shows that the optimal or non-optimal management of knowledge management and its various factors, through the causality of the variables, allow the interrelation to be more adequately captured to manage it. The results show that the most relevant factors for adequate management of innovation and technology are knowledge management, sales and marketing, organizational and technological architecture, national and international markets, cultivation of raw materials, agave, and management, use of waste, and not research and development.
Surface Seeding of Wheat: A Sustainable Way towards Climate Resilience Agriculture
Authors: Singh Satish Kumar , Patra Abhik , Chand Ramesh , Jatav Hanuman Singh , Luo Yang , Rajput Vishnu D. , Sehar Shafaque , Attar Sanjay Kumar , Khan Mudasser Ahmed , Jatav Surendra Singh , Minkina Tatiana , Adil Muhammad Faheem
Published: June 2022

Conventional tillage (CT)-based agriculture is known to be ecologically indiscreet, economically and environmentally unsustainable, and leads to the degradation of soil and the environment in the Indo-Gangetic Plain (IGP). The surface seeding (SS) method was introduced to manage agro-ecosystems for sustaining productivity and increasing farmers’ profits, while sustaining the natural resources. Here, we conducted a systematic literature review on SS of wheat reported in the IGP, with the aim to cover the concept of SS, its impact on wheat yield, soil properties, and the environment, with the potential benefits and constraints. The major findings are: (i) an SS-based rice–wheat system improves productivity (∼10%) and profitability (20–30%),while employing a lesser amount of irrigation water (15–30%) and energy input (20–25%) compared to a conventional system; (ii) an SS-based system is more adaptive to extreme climatic conditions, reduces the carbon footprint, and increases crop production; (iii) an SS approach enhances soil health by virtue of increased soil organic carbon and improved soil aggregation, as well as soil, water, and energy conservation; (iv) SS consisting of no-tillage with substantial crop residue retention offers an alternative to crop residue burning. Strong policies/legislation are required to encourage SS of wheat, in order to limit residue burning, and provide farmers with carbon credits in exchange for carbon sequestration and reduced greenhouse gas emissions.
Assessment of the Relations for Determining the Profitability of Dairy Farms, A Premise of Their Economic Sustainability
Authors: Chetroiu Rodica , Cișmileanu Ana Elena , Cofas Elena , Petre Ionut Laurentiu , Rodino Steliana , Dragomir Vili , Marin Ancuța , Turek-Rahoveanu Petruța Antoneta
Published: June 2022

The profitability of dairy farms is a broadly addressed issue in research, for different farming systems and even more so now, when it comes to the issue of sustainability in different agricultural fields. The present study presents an evaluation of the relations used for the determination of profitability of various categories of dairy farms, in terms of size, geographical area, and total milk production. In order to analyze the associated influence exerted on the level of profitability by the selected technical and economic indicators, regression functions were applied. The TableCurve program was used to determine the ideal equation that describes the data entered in a two- or three-dimensional representation. The research results showed that the size of farms and the level and value of milk production are directly correlated with profitability, and the unit cost is inversely correlated with it.
Sustainable Development Goals and 2030 Agenda—Survey on Awareness, Knowledge and Attitudes of Italian Teachers of Public Mandatory Schools, 2021
Authors: Smaniotto Cecilia , Brunelli Laura , Miotto Edoardo , Del Pin Massimo , Ruscio Edoardo , Parpinel Maria
Published: June 2022

Achieving the Sustainable Development Goals (SDGs) goes hand in hand with realising a more sustainable future, taking into account environmental, economic and social dimensions. Education can accelerate these goals, with teachers playing a central role. In 2021, a study was conducted among teachers in Italian mandatory schools to investigate knowledge, sources of information and attitudes towards the SDGs. An online survey was conducted, based on a Likert-scale with 62 items. The questionnaire was completed by 417 teachers. The overall knowledge score shows a median of 42.9%, an interquartile range of 25% and a range of 1.8–91.1%. A very good level of knowledge among teachers is limited to some topics, such as the Greenhouse effect (19.6%) and Resilience (13%), which may be better known due to wider media coverage. Sustainability issues are not yet considered as a shared responsibility, as teaching in designated hours was often suggested. The commitment of Italian teachers and schools to a stronger integration of sustainability issues into didactic programmes still needs to be improved. A change of perspective is urgently needed, whereby sustainability education should be seen as a collective responsibility.
Coupling Coordination and Spatiotemporal Evolution between Carbon Emissions, Industrial Structure, and Regional Innovation of Counties in Shandong Province
Authors: Wang Jianshi , Wang Chengxin , Yu Shangkun , Li Mengcheng , Cheng Yu
Published: June 2022

Industrial structure and regional innovation have a significant impact on emissions. This study explores, from the multivariate coupling and spatial perspectives, the degree of coupling coordination between three factors: industrial structure, carbon emissions, and regional innovation of 97 counties in Shandong Province, China from 2000 to 2017. On the basis of global spatial autocorrelation and cold and hot spots, this article analyzes the spatial characteristics and aggregation effects of coupled and coordinated development within each region. The results are as follows. (1) The coupling degree between carbon emissions, industrial structure, and regional innovation in these counties fluctuated upward from 2000 to 2017. Coupling coordination progressed from low coordination to basic coordination. Regional differences in coupling coordination degree are evident, showing a stepped spatial distribution pattern with high levels in the east and low levels in the west. (2) During the study period, the coupling coordination showed a positive correlation in spatial distribution. Moran’s I varies from 0.057 to 0.305 on a global basis. Spatial clustering is characterized by agglomeration of cold spots and hot spots. (3) The coupling coordination exhibited significant spatial differentiation. The hot spots were distributed in the eastern part, while the cold spots were located in the western part. The results of this study suggest that the counties in Shandong Province should promote industrial structure upgrades and enhance regional innovation to reduce carbon emissions.