bluuebunny/crossref_metadata_2025 huggingface dataset:
The Real-Time Prediction of Product Quality Based on the Equipment Parameters in a Smart Factory
Authors: Yan Xin , Duan Guijiang
Published: May 2022

Product quality is an important part of enterprise competitiveness. Product processing is the key process of quality formation. In smart factories, the improvement of data acquisition and processing capability provides a basis for data-based quality control. In order to reduce the occurrence of product quality problems, we abstracted the product processing process as a data processing unit, abstracted the process of changing the product quality state as a process of the processing quality characteristics data, divided the measured value of quality characteristics into three states according to the fluctuation of the measured value of product quality characteristics, and then the classification model of process equipment parameters was established. The experimental results show that the error rate of the real-time dynamic prediction of quality characteristics based on equipment parameters was acceptable, and its prediction could be used as a reference in real production. The research could be applied in product quality prediction, production process simulation, digital twin and other fields.
Predicting Mass Transfer in Liquid–Liquid Extraction Columns
Authors: Fells Alex , De Santis Andrea , Colombo Marco , Theobald Daniel W. , Fairweather Michael , Muller Frans , Hanson Bruce
Published: May 2022

In this work, the GEneralised Multifluid Modelling Approach (GEMMA) is applied to the simulation of liquid–liquid extraction in a Rotating Disc Column (RDC) and a Pulsed Sieve-plate Extraction Column (PSEC). A mass transfer modelling methodology is developed, in which the multiphase flows, droplet size distribution and dispersed phase holdup predicted with computational fluid dynamics are coupled to mass transfer correlations to predict the overall mass transfer. The numerical results for the stage-averaged dispersed phase holdup, Sauter mean droplet diameter and axial solute concentration in the RDC and PSEC agree with experimental observations. The proposed modelling method provides an accurate predictive tool for complex multiphase flows, such as those observed in intensified liquid–liquid extraction, and provides an alternative approach to column design using empirical correlations or pilot plant study.
Psychometric Properties of the Short Form-36 (SF-36) in Parents of Children with Mental Illness
Authors: Reed Madeline , Reaume Shannon V. , Ferro Mark A.
Published: May 2022

Given the stressful experiences of parenting children with mental illness, researchers and health professionals must ensure that the health-related quality of life of these vulnerable parents is measured with sufficient validity and reliability. This study examined the psychometric properties of the SF-36 in parents of children with mental illness. The data come from 99 parents whose children were currently receiving mental health services. The correlated two-factor structure of the SF-36 was replicated. Internal consistencies were robust (α > 0.80) for all but three subscales (General Health, Vitality, Mental Health). Inter-subscale and component correlations were strong. Correlations with parental psychopathology ranged from r = −0.32 to −0.60 for the physical component and r = −0.39 to −0.75 for the mental component. Parents with clinically relevant psychopathology had significantly worse SF-36 scores. SF-36 scores were inversely associated with the number of child diagnoses. The SF-36 showed evidence of validity and reliability as a measure of health-related quality of life in parents of children with mental illness and may be used as a potential outcome in the evaluation of family-centered approaches to care within child psychiatry. Given the relatively small sample size of this study, research should continue to examine its psychometric properties in more diverse samples of caregivers.
Portfolio Optimization for Extreme Risks with Maximum Diversification: An Empirical Analysis
Authors: Mehta Navya Jayesh , Yang Fan
Published: May 2022

Heavy tailedness and interconnectedness widely exist in stock returns and large insurance claims, which contributes to huge losses for financial institutions. Diversification ratio (DR) measures the degree of diversification using the Value-at-Risk, which is known to capture extreme risks better than variance. The portfolio optimization strategy based on DR maximizes the effect of diversification for extreme risks. In this paper, we empirically examine the DR strategy by using more than 350 S&P 500 stocks under the assumption that the stock losses are modeled with a flexible multivariate heavy-tailed model. This assumption is verified empirically. The performance of DR strategy is compared with four benchmark strategies: equally weighted portfolio, minimum-variance portfolio, extreme risk index portfolio, and most diversified portfolio. The performance of comparison includes annualized portfolio return, modified Sharpe ratio, maximum drawdown, portfolio concentration, portfolio turnover, and the degree of diversification. DR outperforms other strategies. In particular, DR shows the highest return and maintains the highest level of diversification during the global financial crisis of 2007–2009.
The Impact of Corporate Social Responsibility and Innovative Strategies on Financial Performance
Authors: Costa Joana , Fonseca José Pedro
Published: May 2022

The article aims to appraise the role of Corporate Social Responsibility (CSR) and innovation strategies as leverages of a company’s financial performance. The theoretical and empirical statement of this link aims to reinforce the importance of these strategical options in both the managerial and the public policy domain. Shedding light on the economic return of these practices will help managers make better strategic decisions. Policy makers will also grasp the required evidence to encompass CSR in policy packages. To address the research question, data were collected from the Thomson Reuters Eikon Datastream covering the 1000 largest companies listed on the stock exchange worldwide. Thereafter, hierarchical linear regressions were performed to produce the econometric results. Two time frames (2015–2019) were compared to address time–space trends. Enrolling in CSR activities entails additional costs which can undermine the company’s financial performance if not properly supported by public policies. Combining CSR and innovation appears to be the best strategy for companies seeking improvements in their financial performance while being socially responsible. The contribution of this study is threefold: first, the analysis covers the largest thousand firms in operation worldwide; secondly, the econometric results demonstrate that combining CSR with innovation positively impacts financial performance; and lastly, the time comparison evidences a positive but slow evolution in CSR adoption. The article provides an applied perspective, of use both for managers and policy makers, as to how they should approach and disseminate involvement in these types of activities.
Correction: Lin, Z.; Guo, W. Cotton Stand Counting from Unmanned Aerial System Imagery Using MobileNet and CenterNet Deep Learning Models. Remote Sens. 2021, 13, 2822
Authors: Lin Zhe , Guo Wenxuan
Published: May 2022

In the original publication [...]
A Comprehensive Clear-Sky Database for the Development of Land Surface Temperature Algorithms
Authors: Ermida Sofia L. , Trigo Isabel F.
Published: May 2022

Land surface temperature is linked to a wide range of surface processes. Given the increased development of earth observation systems, a large effort has been put into advancing land surface temperature retrieval algorithms from remote sensors. Due to the very limited number of reliable in situ observations matching the spatial scales of satellite observations, algorithm development relies on synthetic databases, which then constitute a crucial part of algorithm development. Here we provide a database of atmospheric profiles and respective surface conditions that can be used to train and verify algorithms for land surface temperature retrieval, including machine learning techniques. The database was built from ERA5 data resampled through a dissimilarity criterion applied to the temperature and specific humidity profiles. This criterion aims to obtain regular distributions of these variables, ensuring a good representation of all atmospheric conditions. The corresponding vertical profiles of ozone and relevant surface and vertically integrated variables are also included in the dataset. Information on the surface conditions (i.e., temperature and emissivity) was complemented with data from a wide array of satellite products, enabling a more realistic surface representation. The dataset is freely available online at Zenodo.
Monitoring and Predicting the Subsidence of Dalian Jinzhou Bay International Airport, China by Integrating InSAR Observation and Terzaghi Consolidation Theory
Authors: Shi Xianlin , Chen Chen , Dai Keren , Deng Jin , Wen Ningling , Yin Yong , Dong Xiujun
Published: May 2022

Dalian Jinzhou Bay International Airport (DJBIA) is an offshore artificial island airport, where the reclaimed land is prone to uneven land subsidence due to filling consolidation and construction. Monitoring and predicting the subsidence are essential to assist the subsequent subsidence control and ensure the operational safety of DJBIA. However, the accurate monitoring and prediction of reclaimed subsidence for such a wide area under construction are hard and challenging. This paper utilized the Small Baseline Subset Synthetic Aperture Radar (SBAS-InSAR) technology based on Sentinel-1 images from 2017 to 2021 to obtain the subsidence over the land reclamation area of the DJBIA, in which the results from ascending and descending orbit data were compared to verify the reliability of the results. The SBAS-InSAR results reveal that uneven subsidence is continuously occurring, especially on the runway, terminal, and building area of the airport, with the maximum subsidence rate exceeding 100 mm/year. It was found that there is a strong correlation between the subsidence rate and backfilling time. This study provides important information on the reclaimed subsidence for DJBIA and demonstrates a novel method for reclaimed subsidence monitoring and prediction by integrating the advanced InSAR technology and Terzaghi Consolidation Theory modeling. Moreover, based on the Terzaghi consolidation theory and the corresponding geological parameters of the airport, predicted subsidence curves in this area are derived. The comparison between predicted curves and the actual subsidence revealed by InSAR in 2017–2021 is highly consistent, with a similar trend and falling in a range of ±25 mm/year, which verifies that the subsidence in this area conforms to Terzaghi Consolidation Theory. Therefore, it can be predicted that in the future, the subsidence rate of the new reclamation area in this region will reach about 80 mm/year ± 25 mm/year, and the subsidence rate will gradually slow down with the accumulation of reclamation time. The subsidence rate will slow down to about 30 mm/year ± 25 mm/year after 10 years.
The Potential of Optical UAS Data for Predicting Surface Soil Moisture in a Peatland across Time and Sites
Authors: de Lima Raul Sampaio , Li Kai-Yun , Vain Ants , Lang Mait , Bergamo Thaisa Fernandes , Kokamägi Kaupo , Burnside Niall G. , Ward Raymond D. , Sepp Kalev
Published: May 2022

Advances in unmanned aerial systems (UASs) have increased the potential of remote sensing to overcome scale issues for soil moisture (SM) quantification. Regardless, optical imagery is acquired using various sensors and platforms, resulting in simpler operations for management purposes. In this respect, we predicted SM at 10 cm depth using partial least squares regression (PLSR) models based on optical UAS data and assessed the potential of this framework to provide accurate predictions across dates and sites. For this, we evaluated models’ performance using several datasets and the contribution of spectral and photogrammetric predictors on the explanation of SM. The results indicated that our models predicted SM at comparable accuracies as other methods relying on more expensive and complex sensors; the best R2 was 0.73, and the root-mean-squared error (RMSE) was 13.1%. Environmental conditions affected the predictive importance of different metrics; photogrammetric-based metrics were relevant over exposed surfaces, while spectral predictors were proxies of water stress status over homogeneous vegetation. However, the models demonstrated limited applicability across times and locations, particularly in highly heterogeneous conditions. Overall, our findings indicated that integrating UAS imagery and PLSR modelling is suitable for retrieving SM measures, offering an improved method for short-term monitoring tasks.
Sparse Adversarial Video Attacks via Superpixel-Based Jacobian Computation
Authors: Du Zhenyu , Liu Fangzheng , Yan Xuehu
Published: May 2022

Adversarial examples have aroused great attention during the past years owing to their threat to the deep neural networks (DNNs). Recently, they have been successfully extended to video models. Compared with image cases, the sparse adversarial perturbations in the videos can not only reduce the computation complexity, but also guarantee the crypticity of adversarial examples. In this paper, we propose an efficient attack to generate adversarial video perturbations with large sparsity in both the temporal (inter-frames) and spatial (intra-frames) domains. Specifically, we select the key frames and key pixels according to the gradient feedback of the target models by computing the forward derivative, and then add the perturbations on them. To overcome the problem of dimensional explosion in the video, we introduce super-pixels to decrease the number of pixels that need to compute gradients. The proposed method is finally verified under both the white-box and black-box settings. We estimate the gradients using natural evolution strategy (NES) in the black-box attacks. The experiments are conducted on two widely used datasets: UCF101 and HMDB51 versus two mainstream models: C3D and LRCN. Results show that compared with the state-of-the-art method, our method can achieve the similar attacking performance, but it pollutes only <1% pixels and costs less time to finish the attacks.
Enhanced Sample Throughput Capillary Zone Electrophoresis with UV Detection in Hydrodynamically Closed System for Determination of Ibuprofen
Authors: Stefanik Ondrej , Horniakova Andrea , Cizmarova Ivana , Matuskova Michaela , Mikusova Veronika , Mikus Peter , Piestansky Juraj
Published: May 2022

A simple analytical approach based on capillary zone electrophoresis with ultraviolet detection and repeated sample injection strategy (applied in a hydrodynamically closed separation system for the first time) was developed for the determination of ibuprofen (IBU) in commercially available pharmaceutical preparations. The proposed method was characterized by significantly increased sample throughput and favorable validation parameters, highly demanded in routine quality control laboratories. The limit of detection was predicted at the concentration level of 0.31 µg/mL. Intra-day precision expressed as the relative standard deviation of IBU concentration ranged from 1.9 to 5.6%, and corresponding intra-day accuracy expressed as the relative error was in the interval of 87.1–106.5%. Inter-day precision was in the range of 2.6–15.0%, and inter-day accuracy was 94.9–102.7%. The developed method was able to quantify IBU in complex pharmaceutical matrices represented by commercially available tablets and oral suspension. The determined contents of IBU in the tested dosage forms were in good agreement with the manufacturer’s declaration. The analytical performance of the developed method was evaluated according to the innovative RGB Additive Color Model strategy. It was demonstrated that the proposed method is characterized by very good analytical performance parameters, safety and eco-friendliness, and practical effectiveness.
Patterning of Sexual Violence against Women across US Cities and Counties
Authors: Pabst Jennifer , Walfield Scott M. , Schacht Ryan
Published: May 2022

Sexual violence against women is a global public health concern; yet, determining its patterning is still largely understudied. An excess of males has emerged as a central concern given that men are the primary perpetrators of violent behavior, particularly against women. However, it is increasingly unclear as to whether an excess or, rather, a shortage of men drives purported negative social outcomes. To address these conflicting expectations, we target data from the U.S. Census and the National Incident-Based Reporting System to explore the patterning of sexual violence against women across cities and counties in the United States. Through the use of generalized linear mixed models, we assess the role of adult sex ratio imbalance, along with measures of gender inequality, on sexual violence. Our results indicate mixed support for competing predictions. Violence does not simply increase by way of male surplus or shortage, but instead with increasing skew in the sex ratio. That is, balanced sex ratios exhibit the lowest rates of violence. However, rates of sexual violence against women increase more quickly with increasing male scarcity and are lowest at low levels of male excess (51%). Thus, our findings are particularly challenging to interpret from a ‘more males = more violence’ framework because violence increases more quickly with female excess and is rarest with a slight male bias in the population. We argue that these results highlight a need to target the specific types of violent behaviors expected to be motivated by partner availability, rather than overly simplistic predictions of male surfeit or deficit leading to an excess of violence.
Revealing Consumer Behavior toward Green Consumption
Authors: Zeynalova Zivar , Namazova Natavan
Published: May 2022

The aim of this study was to determine the relationship between the attitudes and behaviors of the administrative staff of four Baku universities toward the consumption of environmentally friendly products. The study used 536 consumer questionnaires belonging to different socio-economic and demographic consumer groups. The survey evaluated the factors that affected purchasing decisions, purchase intentions, awareness, attitudes and behaviors toward green products of respondents living in an urban area. The results from the survey were analyzed using one-way MANOVA analysis. According to the results of the study, the green consumer behaviors of the survey participants differed according to age, the number of household members, marital status, education level and income. At the same time, the main indicators that consumers paid attention to were price, brand, appearance, advertising, expert opinion and label information. The level of importance of these indicators varied according to the education, income and number of household members of the participants. The results showed that the participants of the survey were partially sensitive to the environment.
The Collaboration Mechanism of Agricultural Product Supply Chain Dominated by Farmer Cooperatives
Authors: Huo Yujia , Wang Jiali , Guo Xiangyu , Xu Yang
Published: May 2022

Problems such as the reduction of the added value of agricultural products and the interruption of the supply of agricultural products caused by the unstable collaborative relationship have seriously hindered the high-quality development of the agricultural product supply chain. Promoting the stable collaboration in the agricultural product supply chain is an urgent problem. Considering the characteristic demand of consumers for agricultural products, this paper takes the supply chain mainly operating characteristic agricultural products and dominated by farmer cooperatives as the research object and constructs a tripartite evolutionary game model of farmer cooperatives, manufacturers, and retailers. We study the supply chain collaboration mechanism from the main strategy choice and the specific factors affecting its strategy choice. The results show that farmer cooperatives implement a strict supervision strategy and increase the reward and punishment to promote the collaboration in the supply chain, but the increase in supervision cost is not conducive to the income of farmer cooperatives. In the case of loose supervision, the difference between the additional income and the collaboration input is higher than the “free-rider” income obtained when adopting a non-collaboration strategy, which is conducive to its evolution towards collaboration. In addition, increasing additional income, improving synergy coefficient, and reducing collaboration input and “free-rider” income will increase the probability of the system evolving to Pareto optimal, and accelerate the realization of comprehensive collaboration in the agricultural product supply chain dominated by farmer cooperatives. The research results provide a certain supplement to the related research on agricultural product supply chains in theory, and provide a reference for the comprehensive collaboration of the agricultural product supply chain dominated by farmer cooperatives in practice.
Evaluation of Decarbonization Technologies for ASEAN Countries via an Integrated Assessment Tool
Authors: Lau Hon Chung
Published: May 2022

A new assessment tool for evaluating decarbonization technologies that considers each technology’s sustainability, security, affordability, readiness, and impact for a specific country is proposed. This tool is applied to a set of decarbonization technologies for the power, transport, and industry sectors for the ten Southeast Asian countries that constitute ASEAN. This results in a list of the most promising decarbonization technologies, as well as the remaining issues that need more research and development. This study reveals several common themes for ASEAN’s decarbonization. First, carbon capture and storage (CCS) is a key technology for large-scale CO2 emission. Second, for countries that rely heavily on coal for power generation, switching to gas can halve their CO2 emission in the power sector and should be given high priority. Third, hydropower and bioenergy both have high potential for the majority of ASEAN countries if their sustainability issues can be resolved satisfactorily. Fourth, replacing conventional vehicles by electric vehicles is the overarching theme in the road transport sector, but will result in increased demand for electricity. In the medium to long term, the use of hydrogen for marine fuel and biofuels for aviation fuel are preferred solutions for the marine and aviation transport sectors. Fifth, for the industry sector, installing CCS in industrial plants should be given priority, but replacing fossil fuels by blue hydrogen for high-temperature heating is the preferred long-term solution.
Oil Spill Environmental Risk Assessment and Mapping in Coastal China Using Automatic Identification System (AIS) Data
Authors: Zhu Gaoru , Xie Zhenglei , Xu Honglei , Wang Nan , Zhang Liguo , Mao Ning , Cheng Jinxiang
Published: May 2022

The rapid expansion in shipping traffic, oil tankers, and oil field exploration in coastal and marine areas has, inevitably, resulted in the occurrence of many oil spill accidents. Oil spill accidents, which cause serious socio-economic, health, and environmental risks in coastal and marine areas, are a global concern. An oil spill pollution risk distribution map, combining multiple spill sources, is an effective tool by which to identify high-risk areas, which may help decision-makers in adopting contingency response and integrated coastal management. However, the assessment of oil spill distribution and risk assessment has been restricted, due to their heavy dependence on laboratory experiments and model simulations lacking reliable shipping data, which often derive inaccurate mapping results. This study combines the automatic identification system (AIS) and other data to precisely quantify the spatial extent of accident risk in coastal China. Based on oil quantity, oil spill rate, and accident probability, the ship, oil storage tank, submarine pipeline, and oil platform accidents spill risk index is analyzed. Next, combined with the sensitive degree of a coastal area, considering environmental and social issues, the oil spill environmental risk index is calculated. The oil spill pollution risk level is classified into five categories based on the oil spill pollution risk index, namely the low-risk zone, relatively low-risk zone, moderate-risk zone, relatively high-risk zone, and high-risk zone. The relatively high oil spill environmental risk concentration zone is located in the Bohai Sea, inter-border area between the Yellow Sea and Bohai Sea, the Yangtze River estuary, south of the Taiwan Strait, and the Pearl River estuary. The high-risk zone in the Bohai Sea is 36,018 km2 in area, with an average risk value of 32.23, whereas the high-risk area in the Pearl River estuary is only 14,007 km2. The high-risk area proportions in Tianjin are 23.5%, while those in Fujian, Hainan, Jiangsu, and Guangxi are very low. The low-risk area proportion in Hainan Province is 62%, while the value in Tianjin is only 2.9%. This study will be helpful in assisting decision-makers in mapping the influence area of oil spills and adopting the important strategies and effective management and conservation countermeasures for ship accidents in the coastal areas of China.
Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia
Authors: Bucea-Manea-Țoniş Rocsana , Kuleto Valentin , Gudei Simona Corina Dobre , Lianu Costin , Lianu Cosmin , Ilić Milena P. , Păun Dan
Published: May 2022

In their struggle to offer a sustainable educational system and transversal competencies for market requests, significant transformations characterise the higher education system in Serbia and Romania. According to EU policy, these transformations are related to educational reforms and the introduction of new technology and methodologies in teaching and learning. They are expected to answer to the PISA requirements and to increase the DESI (Digital Economy and Society Index). They are also likely to mitigate the inequity of HEIs (higher education institutions), empowered by a structured, goal-oriented strategy towards agile management in HEIs that is also appropriate for new market demands. Our study is based on an exploratory survey applied to 139 Romanian and Serbian teachers from the Information Technology School—ITS, Belgrade, and Spiru Haret University, Romania. The survey let them provide their knowledge of AI or their perceptions of the difficulties and opportunities of these technologies in HEIs. Our study discovered how difficulties and opportunities associated with AI impact HEIs. This study aims to see how AI might assist higher education in Romania and Serbia. We also considered how they might be integrated with the educational system, and if instructors would utilise them. Developing creative and transversal skills is required to anticipate future breakthroughs and technological possibilitiesThe new methods of education focuses on ethics, values, problem-solving, and daily activities. Students’ learning material, how they might achieve critical abilities, and their educational changes must be addressed in the future. In this environment, colleges must create new digital skills in IA, machine learning, IoT, 5G, the cloud, big data, blockchain, data analysis, using MS Office and other applications, MOOCs, simulation applications, VR/AR, and gamification. They must also develop cross-disciplinary skills and a long-term mindset.
Influence of Clay Mineral Amendments Characteristics on Heavy Metals Uptake in Vetiver Grass (Chrysopogon zizanioides L. Roberty) and Indian Mustard (Brassica juncea L. Czern)
Authors: Otunola Beatrice Omonike , Aghoghovwia Makhosazana P. , Thwala Melusi , Gómez-Arias Alba , Jordaan Rian , Hernandez Julio Castillo , Ololade Olusola Oluwayemisi
Published: May 2022

Phytoremediation is limited when heavy metals reduce soil quality and, subsequently, inhibit plant growth. In this study, we evaluated the use of attapulgite and bentonite as amendments in soil contaminated with multiple metals, to improve the phytoremediation capacity of Vetiver grass and Indian mustard. A 21-day greenhouse study was undertaken, to investigate plant tolerance in heavy-metal-contaminated soil, as well as heavy-metal absorption in plant roots and shoots. The results showed a generally higher root-uptake rate for Cr, Cu, Co, Ni, and Zn in Vetiver grass. Overall, the highest absorption for Ni, Cr, Co, Cu, and Zn was 1.37, 2.79, 1.39, 2.48 and 3.51 mg/kg, respectively, in the roots of Vetiver grass. Clay minerals inhibited the translocation of some heavy metals. The addition of attapulgite improved the phytoremediation capacity of Vetiver for Ni, Cr, and Co, while bentonite improved Vetiver’s absorption of Cu and Zn. The translocation factor for Ni in one of the attapulgite treatments was 2, indicating that attapulgite improved the phytoextraction of Ni by Vetiver grass. Our results confirm that attapulgite at 2.5% (w/w) can successfully improve the phytostabilization of heavy metals by Vetiver grass. Indian mustard showed no significant metal uptake that could be detected by inductively coupled plasma optical emission spectrometry (ICP-OES), despite the addition of attapulgite and bentonite. This research contributes to the knowledge repository of suitable amendments that improve the phytoremediation properties of Vetiver grass.
A Location Inventory Routing Optimisation Model and Algorithm for a Remote Island Shipping Network considering Emergency Inventory
Authors: Wu Di , Ji Xuejun , Xiao Fang , Sheng Shijie
Published: May 2022

This paper studies a hub-and-spoke shipping network of remote islands and integrates a maritime location inventory routing problem for a remote island shipping network considering emergency inventory. By determining a series of decisions, including the location of the hub islands, number of shipping routes, schedule of every route, travelling mode of every route, ship size, wharf scale, and inventory capacity, the objective of this study is to minimise the total cost of the remote island shipping network over the operating period. Subsequently, a mixed-integer programming model to minimise the total cost of the system is developed. To solve the model, we present a genetic algorithm based on a stepwise configuration module (SC-GA). Finally, instances are proposed to evaluate the performance of the algorithm. The results of the instance calculation show that the algorithm has good applicability and effectiveness in solving the problem in this paper. Through algorithm comparison, it is found that the performance of SC-GA is better than the algorithms in the relevant literature. This paper provides practical information for the design, optimisation and sustainability of remote island shipping networks considering emergency inventory.
Research on Real-Time Detection of Safety Harness Wearing of Workshop Personnel Based on YOLOv5 and OpenPose
Authors: Fang Chengle , Xiang Huiyu , Leng Chongjie , Chen Jiayue , Yu Qian
Published: May 2022

Wearing safety harness is essential for workers when carrying out work. When posture of the workers in the workshop is complex, using real-time detection program to detect workers wearing safety harness is challenging, with a high false alarm rate. In order to solve this problem, we use object detection network YOLOv5 and human body posture estimation network OpenPose for the detection of safety harnesses. We collected video streams of workers wearing safety harnesses to create a dataset, and trained the YOLOv5 model for safety harness detection. The OpenPose algorithm was used to estimate human body posture. Firstly, the images containing different postures of workers were processed to obtain 18 skeletal key points of the human torso. Then, we analyzed the key point information and designed the judgment criterion for different postures. Finally, the real-time detection program combined the results of object detection and human body posture estimation to judge the safety harness wearing situation within the current screen and output the final detection results. The experimental results prove that the accuracy rate of the YOLOv5 model in recognizing the safety harness reaches 89%, and the detection method of this study can ensure that the detection program accurately recognizes safety harnesses, and at the same time reduces the false alarm rate of the output results, which has high application value.
Innovation Capability and Open Innovation for Small and Medium Enterprises (SMEs) Performance: Response in Dealing with the COVID-19 Pandemic
Authors: Rumanti Augustina Asih , Rizana Afrin Fauzya , Septiningrum Lutfia , Reynaldo Rocky , Isnaini Mohammad Mi’radj
Published: May 2022

The current business environment requires every organization or company to achieve optimal performance and maintain it. Innovation capability and open innovation practices play a critical role in improving organizational performance. However, their role in improving Small and Medium Enterprises (SMEs)’s performance, especially during the COVID-19 pandemic, still needs to be identified further. Thus, this study conducts empirical research elaborating intrinsic factors of innovation capability, as well as the influence of open innovation on organizational efforts, i.e., how SMEs achieve optimal performance during the COVID-19 pandemic. In this research model, 206 respondents were gathered and given a reearch questionnaire. The respondents are the owner of batik SMEs located in several regions in Indonesia. PLS-SEM is used to test the data, and the result of this study shows that all hypotheses developed in this study are accepted, i.e., SMEs’ innovation capability and open innovation practices significantly influence financial and operational performance. The results show that in batik SMEs, the ability to innovate and open innovation, especially open entry innovation, can facilitate greater organizational performance. Therefore, batik SMEs woud benefit from initiatives and opportunities that improve their abilities in open innovation.
Sustainable Aviation Electrification: A Comprehensive Review of Electric Propulsion System Architectures, Energy Management, and Control
Authors: Zhang Jinning , Roumeliotis Ioannis , Zolotas Argyrios
Published: May 2022

The civil aviation sector plays an increasingly significant role in transportation sustainability in the environmental, economic, and social dimensions. Driven by the concerns of sustainability in the aviation sector, more electrified aircraft propulsion technologies have emerged and form a very promising approach to future sustainable and decarbonized aviation. This review paper aims to provide a comprehensive and broad-scope survey of the recent progress and development trends in sustainable aviation electrification. Firstly, the architectures of electrified aircraft propulsion are presented with a detailed analysis of the benefits, challenges, and studies/applications to date. Then, the challenges and technical barriers of electrified aircraft propulsion control system design are discussed, followed by a summary of the control methods frequently used in aircraft propulsion systems. Next, the mainstream energy management strategies are investigated and further utilized to minimize the block fuel burn, emissions, and economic cost. Finally, an overview of the development trends of aviation electrification is provided.
Novel Recommendation-Based Approach for Multidisciplinary Development of Future Universities
Authors: Bi Siguo , Ni Wei , Jiang Yi , Wang Xin
Published: May 2022

Multidisciplinary sustainable development is an important and complex system for comprehensive universities. Typically, a comprehensive university’s objective is to create a free, open, and diversified ecosystem of disciplines. Given finite available resources, e.g., funding or investment, configuring the formation of disciplines is critical. Understanding the interrelationships among different disciplines is challenging. Rather than directly wading through massive high-dimensional interrelated data, we judiciously formulate the cumbersome configurations of disciplines as a discipline recommendation problem. In this paper, we propose a novel data-driven approach to the configuration of disciplines based on a recommendation to predict and recommend an appropriate configuration of disciplines. The proposed approach exhibits good performance against standard metrics on real-world public data sets. It can be implemented as an attractive engine for constructing disciplines for universities.
Authentic Leadership, Trust, and Social Exchange Relationships under the Influence of Leader Behavior
Authors: Chen James K. C. , Sriphon Thitima
Published: May 2022

During the pandemic, government policies such as social distancing and telework have impacted trust and working or social exchange relationships in the workplace. The behavior of leaders is critical for good leadership, employees’ trust, and social exchange relationships. Therefore, the main objective of this study was to assess the associations among authentic leadership, trust, and social exchange relationships under the influence of leader behavior. A regression-based approach was used to test the moderating and mediating effects. The results show that authentic leadership positively impacts trust and social exchange relationships, whereas trust directly affects social exchange relationships. During COVID-19, leader behaviors with ability, ethics, and positive relationships have had a positive impact on the association between authentic leadership, trust, and social exchange relationships. Additionally, trust positively mediates authentic leadership and social exchange relationships. The findings of this paper suggest that authentic leadership promotes trust and high-quality social exchange relationships. Moreover, based on leader behaviors during COVID-19, the ability to manage change effectively, boost employees’ work motivation, provide support, and take appropriate action is essential for authentic leadership to increase trust and foster a positive working relationship based on social exchange. Finally, regarding social exchange theory, high-quality leader behaviors and the leader–follower relationships drive positive associations among variables. These results will help organizational management teams to find methods to improve their organizational working relationships. The implication is that the abilities, ethics, and supportive and positive relationship behaviors of leaders are essential for effective management to improve leadership, trust, and social exchange relationships. Leaders should have the ability to manage work and people, even with teleworkers. Therefore, leader behaviors are important to maintain organizational sustainability. Further discussion on theoretical and practical implications is provided in the section.
Thermal Performance of Concrete with Reactive Magnesium Oxide as an Alternative Binder
Authors: Forero Javier A. , Bravo Miguel , Pacheco João , de Brito Jorge , Evangelista Luís
Published: May 2022

This study evaluates the thermal conductivity of concrete produced with reactive magnesium oxide (MgO) as a partial replacement for cement. MgO is a viable option for the concrete industry, mainly due to its benefits in sustainability and reducing CO2 emissions compared to cement emissions. Four different MgO’s produced in Australia, Canada, and Spain were used in concrete mixes as a partial replacement of cement at 5%, 10%, and 20% by mass. The experimental results showed that the thermal conductivity is higher when MgO increases in mixes after 28 days of curing. With the incorporation of MgO, the thermal conductivity increased between 3.2% and 10.2%, and the mechanical properties declined: compressive strength between 12.7% to 26.2%, splitting tensile strength between 9.7% to 34.0%, and modulus of elasticity between −4.1% to 7.8%. Finally, it is important to highlight that the addition of different contents of MgO in the concrete mixes modified the microstructure of the cement matrix. As a result, there was an increase in porosity, which negatively influenced the mechanical properties and thermal conductivity. Therefore, the relationships between these properties were also analyzed.
The Impact of Government Interventions and Consumer Green Preferences on the Competition between Green and Nongreen Supply Chains
Authors: Cheng Wen , Wu Qunqi , Ye Fei , Li Qian
Published: May 2022

The green supply chain (GSC) has become a major trend that advocates for the sustainability of supply chains. To seek optimal strategies for the GSC, the competition between green and nongreen supply chains (NGSCs), along with the impacts of government subsidies and tax policies and the green preferences of consumers, are discussed in this study. A pricing-strategy model of an NGSC and a GSC was conducted by considering the cross-price effects. The equilibrium strategies (the optimal green-technology level, the pricing, and the profits) were achieved and were comparatively analyzed with backward induction. For more in-depth research, a robust sensitivity analysis was conducted, and the Taguchi method was used to identify the main factors that affect the revenues of NGSCs and GSCs. The results show that the vertical collaboration between manufacturers and retailers can help to improve the greenness of products and bring more benefits to consumers. The government interventions have an effect, and when the government sets a premeditated threshold for subsidies and taxation, GSC members can earn more, and the green products obtain more competitiveness. The green preferences of consumers are the primarily conducive factor to the sustainability and profit increases of GSCs. However, the green-technology-investment cost will not have a significant influence on the equilibrium strategies.
Study of the Enhancements of Porous Structures of Activated Carbons Produced from Durian Husk Wastes
Authors: Jamnongkan Tongsai , Intaramongkol Nitchanan , Kanjanaphong Nattharika , Ponjaroen Kemmika , Sriwiset Wasana , Mongkholrattanasit Rattanaphol , Wongwachirakorn Piyada , Lin Kun-Yi Andrew , Huang Chih-Feng
Published: May 2022

The idea of generating high-value practical materials, such as activated carbons, from agricultural wastes as a raw material has been a quite important trend recently due to its positive contributions to the environment and resource savings from biomass. In this paper, activated carbons prepared from durian husk waste by the KOH chemical activation method are studied. We focus on the effects of stages of the activating temperature on their properties. The optimum conditions for activation were a KOH/char ratio of 1:2 at the first and second activation process at the temperatures of 400 and 800 °C, respectively. The characterization results of Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) surface area showed that the obtained activated carbons have a high surface area and small pore size. The adsorption/desorption isotherms of the obtained activated carbons showed type I and type II isotherms. The chemical structure of obtained activated carbons did not show any variation in the surface functional groups. A feasible method to produce the activated carbons with a high surface area and high adsorption capability from durian husk waste was eventually demonstrated.
Using Bayesian Networks to Provide Educational Implications: Mobile Learning and Ethnomathematics to Improve Sustainability in Mathematics Education
Authors: Johnson Jason D. , Smail Linda , Corey Darryl , Jarrah Adeeb M.
Published: May 2022

There are many Western apps that help students strengthen their mathematics skills through learning and game apps. A research project was designed to create an IOS Math App to provide Grade 6 Emirati students with the opportunity to explore mathematics, then, using Bayesian Networks, to examine the educational implications. The learning app was developed using ethnomathematics modules based on the Emirati culture. Students were required to navigate through several modules to examine various mathematical concepts in algebra and geometry. The survey was written for Grade 6 English language learners. Based on the Bayesian Networks, the findings suggested that if students are allowed to explore mathematics based on familiar cultural norms and practices, students with grades A and C would get higher grades. However, if students are not allowed to explore mathematics in line with their local culture, more students would receive an F grade, while some students with an A grade would get lower grades. Additionally, the findings showed that incorporating cultural elements had a positive change in students’ liking and learning mathematics, even without a mobile device. However, not allowing a mobile device and not allowing culture had an increased negative impact on students’ liking and learning mathematics. The last finding suggested that students valued ethnomathematics examples over a mobile device to learn mathematics. The research findings could help to improve sustainability in mathematics education by promoting ethnomathematics and mobile learning.
Green Deal, Green Growth and Green Economy as a Means of Support for Attaining the Sustainable Development Goals
Authors: Adamowicz Mieczysław
Published: May 2022

The aim of the study is to present the concept of green economy and other notions and concepts related to it and to assess their significance for the formation of development policy and practical solution of problems of socio-economic development. In the part focusing on information and definitions, the premises for the emergence of the issue of the greening of economic processes as a new phenomenon of contemporary development have been presented, as well as various definitions of green economy, green growth, the principles of implementing green economy, and the implementation of green transformation processes. In the further part of the study, measures and indicators of green economy and green growth are presented, as well as the connection of these concepts with the idea and objectives of sustainable development. The review of green economy and green growth indicators includes indicators prepared by specialised agencies of the United Nations, UNEP, UNCTAD, UN ESCAP, UN FGG, OECD, the European Union, and the World Bank. Selected indicators of individual authors and countries have also been presented. The last part of the study presents the concept of the New European Green Deal and its link to the implementation of the Sustainable Development Goals adopted for the current decade. In conclusion, an attempt has been made to present both the expectations and opportunities of emphasising the issue of the greening of the economy, as well as the weaknesses and threats resulting from the excessive confidence in this concept.