bluuebunny/crossref_metadata_2025 huggingface dataset:
Industrial Transfer Learning for Multivariate Time Series Segmentation: A Case Study on Hydraulic Pump Testing Cycles
Authors: Gaugel Stefan , Reichert Manfred
Published: March 2023

Industrial data scarcity is one of the largest factors holding back the widespread use of machine learning in manufacturing. To overcome this problem, the concept of transfer learning was developed and has received much attention in recent industrial research. This paper focuses on the problem of time series segmentation and presents the first in-depth research on transfer learning for deep learning-based time series segmentation on the industrial use case of end-of-line pump testing. In particular, we investigate whether the performance of deep learning models can be increased by pretraining the network with data from other domains. Three different scenarios are analyzed: source and target data being closely related, source and target data being distantly related, and source and target data being non-related. The results demonstrate that transfer learning can enhance the performance of time series segmentation models with respect to accuracy and training speed. The benefit can be most clearly seen in scenarios where source and training data are closely related and the number of target training data samples is lowest. However, in the scenario of non-related datasets, cases of negative transfer learning were observed as well. Thus, the research emphasizes the potential, but also the challenges, of industrial transfer learning.
Quaternion Wavelet Transform and a Feedforward Neural Network-Aided Intelligent Distributed Optical Fiber Sensing System
Authors: Fan Lei , Wang Yongjun , Zhang Hongxin , Li Chao , Huang Xingyuan , Zhang Qi , Xin Xiangjun
Published: March 2023

In this paper, aiming at a large infrastructure structural health monitoring network, a quaternion wavelet transform (QWT) image denoising algorithm is proposed to process original data, and a depth feedforward neural network (FNN) is introduced to extract physical information from the denoised data. A Brillouin optical time domain analysis (BOTDA)-distributed sensor system is established, and a QWT denoising algorithm and a temperature extraction scheme using FNN are demonstrated. The results indicate that when the frequency interval is less than 4 MHz, the temperature error is kept within ±0.11 °C, but is ±0.15 °C at 6 MHz. It takes less than 17 s to extract the temperature distribution from the FNN. Moreover, input vectors for the Brillouin gain spectrum with a frequency interval of no more than 6 MHZ are unified into 200 input elements by linear interpolation. We hope that with the progress in technology and algorithm optimization, the FNN information extraction and QWT denoising technology will play an important role in distributed optical fiber sensor networks for real-time monitoring of large-scale infrastructure.
Optically Non-Contact Cross-Country Skiing Action Recognition Based on Key-Point Collaborative Estimation and Motion Feature Extraction
Authors: Qi Jiashuo , Li Dongguang , He Jian , Wang Yu
Published: March 2023

Technical motion recognition in cross-country skiing can effectively help athletes to improve their skiing movements and optimize their skiing strategies. The non-contact acquisition method of the visual sensor has a bright future in ski training. The changing posture of the athletes, the environment of the ski resort, and the limited field of view have posed great challenges for motion recognition. To improve the applicability of monocular optical sensor-based motion recognition in skiing, we propose a monocular posture detection method based on cooperative detection and feature extraction. Our method uses four feature layers of different sizes to simultaneously detect human posture and key points and takes the position deviation loss and rotation compensation loss of key points as the loss function to implement the three-dimensional estimation of key points. Then, according to the typical characteristics of cross-country skiing movement stages and major sub-movements, the key points are divided and the features are extracted to implement the ski movement recognition. The experimental results show that our method is 90% accurate for cross-country skiing movements, which is equivalent to the recognition method based on wearable sensors. Therefore, our algorithm has application value in the scientific training of cross-country skiing.
Parabolic-Index Ring-Core Fiber Supporting High-Purity Orbital Angular Momentum Modes
Authors: Liu Yuanpeng , Wang Yingning , Geng Wenpu , Zhao Wenqian , Zhang Hao , Zhang Weigang , Pan Zhongqi , Yue Yang
Published: March 2023

We design a graded-index ring-core fiber with a GeO2-doped silica ring core and SiO2 cladding. This fiber structure can inhibit the effect of spin-orbit coupling to mitigate the power transfer among different modes and eventually enhance the orbital angular momentum (OAM) mode purity. By changing the high-index ring core from the step-index to parabolic graded-index profile, the purity of the OAM1,1 mode can be improved from 86.48% to 94.43%, up by 7.95%. The proposed fiber features a flexible structure, which can meet different requirements for mode order, effective mode area, etc. Simulation results illustrate that the parabolic-index ring-core fiber is promising in enhancing the OAM mode purity, which could potentially reduce the channel crosstalk in mode-division-multiplexed optical communication systems.
ROS-Based Autonomous Navigation Robot Platform with Stepping Motor
Authors: Zhao Shengmin , Hwang Seung-Hoon
Published: March 2023

Indoor navigation robots, which have been developed using a robot operating system, typically use a direct current motor as a motion actuator. Their control algorithm is generally complex and requires the cooperation of sensors such as wheel encoders to correct errors. For this study, an autonomous navigation robot platform named Owlbot was designed, which is equipped with a stepping motor as a mobile actuator. In addition, a stepping motor control algorithm was developed using polynomial equations, which can effectively convert speed instructions to generate control signals for accurately operating the motor. Using 2D LiDAR and an inertial measurement unit as the primary sensors, simultaneous localization, mapping, and autonomous navigation are realised based on the particle filtering mapping algorithm. The experimental results show that Owlbot can effectively map the unknown environment and realise autonomous navigation through the proposed control algorithm, with a maximum movement error being smaller than 0.015 m.
SS-CPGAN: Self-Supervised Cut-and-Pasting Generative Adversarial Network for Object Segmentation
Authors: Chaturvedi Kunal , Braytee Ali , Li Jun , Prasad Mukesh
Published: March 2023

This paper proposes a novel self-supervised based Cut-and-Paste GAN to perform foreground object segmentation and generate realistic composite images without manual annotations. We accomplish this goal by a simple yet effective self-supervised approach coupled with the U-Net discriminator. The proposed method extends the ability of the standard discriminators to learn not only the global data representations via classification (real/fake) but also learn semantic and structural information through pseudo labels created using the self-supervised task. The proposed method empowers the generator to create meaningful masks by forcing it to learn informative per-pixel and global image feedback from the discriminator. Our experiments demonstrate that our proposed method significantly outperforms the state-of-the-art methods on the standard benchmark datasets.
Development of a Particle Filter-Based Path Tracking Algorithm of Autonomous Trucks with a Single Steering and Driving Module Using a Monocular Camera
Authors: Kim Sehwan , Jang Munjung , La Hanbyeol , Oh Kwangseok
Published: March 2023

Recently, in various fields, research into the path tracking of autonomous vehicles and automated guided vehicles has been conducted to improve worker safety, convenience, and work efficiency. For path tracking of various systems applied to autonomous driving technology, it is necessary to recognize the surrounding environment, determine technology accordingly, and develop control methods. Various sensors and artificial-intelligence-based perception methods have limitations in that they must learn a large amount of data. Therefore, a particle-filter-based path tracking algorithm using a monocular camera was used for the recognition of target RGB. The path tracking errors were calculated and a linear-quadratic-regulator-based desired steering angle were derived. The autonomous trucks were steered and driven using a pulse-width-modulation-based steering and driving motor. Based on an autonomous truck with a single steering and driving module, it was verified that the path tracking could be used in three evaluation scenarios. To compare the LQR-based path tracking control performance proposed in this paper, an elliptical path tracking scenario using a conventional sliding mode control with robust control performance was performed. The results show that the RMS of the lateral preview error of the SMC was approximately 18% larger than that of the LQR-based method.
Recognition Performance Analysis of a Multimodal Biometric System Based on the Fusion of 3D Ultrasound Hand-Geometry and Palmprint
Authors: Micucci Monica , Iula Antonio
Published: March 2023

Multimodal biometric systems are often used in a wide variety of applications where high security is required. Such systems show several merits in terms of universality and recognition rate compared to unimodal systems. Among several acquisition technologies, ultrasound bears great potential in high secure access applications because it allows the acquisition of 3D information about the human body and is able to verify liveness of the sample. In this work, recognition performances of a multimodal system obtained by fusing palmprint and hand-geometry 3D features, which are extracted from the same collected volumetric image, are extensively evaluated. Several fusion techniques based on the weighted score sum rule and on a wide variety of possible combinations of palmprint and hand geometry scores are experimented with. Recognition performances of the various methods are evaluated and compared through verification and identification experiments carried out on a homemade database employed in previous works. Verification results demonstrated that the fusion, in most cases, produces a noticeable improvement compared to unimodal systems: an EER value of 0.06% is achieved in at least five cases against values of 1.18% and 0.63% obtained in the best case for unimodal palmprint and hand geometry, respectively. The analysis also revealed that the best fusion results do not include any combination between the best scores of unimodal characteristics. Identification experiments, carried out for the methods that provided the best verification results, consistently demonstrated an identification rate of 100%, against 98% and 91% obtained in the best case for unimodal palmprint and hand geometry, respectively.
A Dynamic Emergency Plan Generation Method Considering Different Situations and Limited Resources
Authors: Zhang Zixin , Wang Liang , Lai Jiayan , Wang Yingming
Published: March 2023

When an emergency event occurs, emergency plans are usually employed to respond the emergency situations in order to prevent or mitigate possible losses of life and property. Therefore, emergency plans play an important and indispensable part in emergency decision-making. With regard to the question of how to generate emergency plans, extant studies have discussed the problem from various perspectives, and fruitful results have been obtained. Dynamic evolution is a typical feature of emergency events, and usually involves the updating of related information regarding an emergency event. Existing studies have considered dynamic evolution during the emergency plan generation process only from a single perspective, neglecting the related need to update information as dynamic evolution occurs. Information related to the emergency event plays a vital role in the emergency plan generation process, and needs to be considered. To overcome these limitations, the present study proposes a novel dynamic emergency plan generation method based on integer linear programming, which considers different emergency situations and limited resources. An illustrative example and descriptive comparisons are provided to demonstrate the novelty, superiority, and validity of the proposed method.
Anaerobic Digestion of Poultry Droppings in Semi-Continuous Mode and Effect of Their Co-Digestion with Physico-Chemical Sludge on Methane Yield
Authors: Mansour Marie-Noël , Lendormi Thomas , Louka Nicolas , Maroun Richard G. , Hobaika Zeina , Lanoisellé Jean-Louis
Published: March 2023

Poultry waste is rich in organic matter, which allows its treatment by the process of anaerobic digestion (AD) to reinforce economic and environmental green strategies. The aim of this study is to assess the technical feasibility of poultry waste AD in semi-continuous mode and to intensify methane production by co-digestion with physico-chemical sludge, i.e., the product of the primary treatment of wastewater after the slaughtering process. First, the AD of poultry droppings is conducted in a continuous stirred anaerobic digester (CSAD) at 37 °C. A volume of 0.791 and 0.623 Nm3·Nm−3 reactor·days−1 of biogas and methane, respectively, were produced during the entire process stabilization period. Biochemical characterization of the substrate and the final digestate show high reduction rates of the biochemical fractions, which corroborates with methane yield. In addition, the co-digestion of poultry droppings with two different ratios of physico-chemical sludge (20% and 40% added sludge considering the amount of volatile solids) shows an increase in methane production versus droppings alone, with a higher increase of 54% with a sludge ratio of 40%. Altogether, these promising results were obtained in stable processes, highlighting the pertinence of our study.
Discussion on the Relationship between Debris Flow Provenance Particle Characteristics, Gully Slope, and Debris Flow Types along the Karakoram Highway
Authors: Yang Zhiquan , Wei Lai , Liu Yuqing , He Na , Zhang Jie , Xu Hanhua
Published: March 2023

Debris flow, the most extensive and most severe geological hazard along the Karakoram Highway, frequently blocks the Karakoram Highway. Based on the methods of field measurement, indoor statistical analysis and theoretical research, this paper discusses the relationship between the four types of debris flow along the Karakoram Highway. The four types are the rain type, the rain glacier type, the glacier ice lake break type and the freeze–thaw type, and their particle characteristics and gully slope are also considered in the discussion. The results are as follows: (1) The provenance particle size of debris flow is controlled by the type of debris flow. Generally, the provenance average particle equivalent diameter of the debris flow induced by the glacier ice lake type is relatively small, followed by the freeze–thaw type and glacier ice lake break type, and the equivalent diameter of the debris flow induced by the rain type is relatively large; (2) The gully slope coefficient of the debris flow C along the Karakoram Highway is greater than 1, and it increases with the increase in gully slope α, that is, the larger C is, the steeper the gully slope will be; (3) The gully slope coefficient C and the average particle equivalent diameter D of the four types of debris flow are distributed in the ellipse with them as the axis. This ellipse quantitatively describes the relationship between the gully slope of the four types of debris flow and the corresponding provenance particle characteristics. This paper analyzes the formation and causes of debris flow along the Karakoram Highway. It accurately understands the scientific connotation of debris flow formation in the surface matrix layer and improves the diversity, stability, and sustainability of the ecosystem. The paper also proposes ideas and suggestions for promoting the ecological protection and restoration of the Karakoram Highway. Therefore, the research has a certain theoretical significance and practical application value for the appropriate selection and rational design of the debris flow prevention projects along the China–Pakistan Highway.
Identifying Key Assessment Factors for a Company’s Innovation Capability Based on Intellectual Capital: An Application of the Fuzzy Delphi Method
Authors: Lianto Benny
Published: March 2023

Innovation has become one of the most important sources of a company’s sustainable competitiveness. Therefore, every company strives continuously to improve its innovation capability. A company’s innovation capability is largely determined by various factors originating from its tangible and intangible resources. A lot of research related to increasing innovation capability with assessment factors originating from tangible resources has been carried out, whereas the use of assessment factors originating from intangible capital, such as intellectual capital, is still relatively limited. This study aims to identify and screen the key assessment factors for innovation capability, based on the intellectual capital of Indonesia’s manufacturing sectors. This study used a systematic literature review and focus group discussions to establish 18 initial assessment factors, after which 14 final factors were screened out by industry practitioners and academic experts using the Fuzzy Delphi Method. Four factors had the highest de-fuzzy value (0.89), namely adaptation, innovation behavior, organization culture, climate, and forward linkages. The results also showed that three factors of the aspects of human capital (adaptation, innovation behavior, and high motivation and commitment) are considered important determinants for the assessment of innovation capabilities, based on intellectual capital.
Testing Food Waste Reduction Targets: Integrating Transition Scenarios with Macro-Valuation in an Urban Living Lab
Authors: Black Daniel , Wei Taoyuan , Eaton Eleanor , Hunt Alistair , Carey Joy , Schmutz Ulrich , He Bingzi , Roderick Ian
Published: March 2023

Bristol, one of the United Kingdom’s (UK) nine Core Cities, is seeking to achieve Zero Waste City status by 2049. This study combines macro-economic valuation with transition pathway mapping and adapted participatory scenario planning to stress test the city’s ambitious food waste targets. The primary aim is to enable better understanding of who might be affected by achieving these targets, both locally and nationally, the potential scale of impacts, and therefore the potential barriers and policy opportunities. The valuation focuses on household and commercial food waste, combining available site and city data with national level proxies. Impact areas include changes in sectoral income, employee income, capital owner income, tax revenue, and carbon emissions. Four scenarios, based on two extreme cases, are modelled to consider food waste reduction and potential shifts in consumption patterns. Results indicate that current market and governance failures incentivise waste, and suggest potential routes to transition, including trade-offs and resource reallocation, alongside the need to acknowledge and respond to these profound structural barriers. With further development and testing, the approach may contribute to a better understanding of how to achieve city socioenvironmental targets.
Analysis of Territorial Risks and Protection Factors for the Business Continuity of Data Centers
Authors: Gazzola Veronica , Menoni Scira , Ghignatti Paolo , Marini Andrea , Mauri Roberto , Oldani Giovanni
Published: March 2023

The increasing trend towards the global use of Information Technology (IT) is currently determining the need for more and better infrastructures (both physical and digital) for processing, storing and transferring large amounts of data. As Critical Infrastructure (CI) that is potentially exposed and vulnerable to the impact of different types of phenomena (natural, technological, na-tech, etc.), data centers have to guarantee higher levels of security (physical, logical and operational), reliability and efficiency in the provision of services. Starting from a discussion of the main evidence related to this topic, considering both the most recent cases of failure and serious damage to data centers and the evolution of international and European regulation and standards, the authors propose an analytical methodology to assess the territorial risk factors for data centers by a multirisk, multi-dimensional and systemic approach. This proposal leads not only to a more explicit definition of exposure and vulnerable components, but also to the recognition of resources that—in the case of accidental events involving (directly or indirectly) data center infrastructures—may be implemented at different territorial levels as “protection” factors to ensure business continuity by considering the entire resilience cycle, from the prevention phase to the response and recovery phases.
A Community-Based Breeding Program as a Genetic Resource Management Strategy of Indonesian Ongole Cattle
Authors: Darmawan Hariadi , Chang Hsiu-Luan , Wu Hsi-Hsun
Published: March 2023

It is essential to manage genetic resources, especially in local livestock breeds, to establish an equilibrium among livestock, humans, and the environment for sustainable development in conservation. Genetic resource management is necessary to overcome challenges to increasing productivity while ensuring environmental sustainability and climate resilience. Attempts to overcome these challenges have led to the threat of genetic erosion through uncontrolled crossbreeding, particularly threatening the hybrid vigor of indigenous breeds, such as Indonesian Ongole cattle. Considering community-based breeding as a viable management strategy for systematic livestock breeding, this study aimed to design a community-based breeding program for Indonesian Ongole cattle. The profile of socio-ecological community and genetic resources were studied using a purposive random sampling technique within an effective population size as a case study; both the respondents and the objects of the study were investigated. The study revealed that indigenous knowledge and livelihood-supported institutions are crucial to genetic resource management practices in cattle breeding. These factors are shown to be strategic priorities when designing community-based breeding programs. This approach to design empowers local cooperatives to operate a community-based breeding program for Indonesian Ongole cattle by standardizing an integrated system for selecting incentive initiatives using big data.
Vertical Greening Systems: A Perspective on Existing Technologies and New Design Recommendation
Authors: Irga Peter J. , Torpy Fraser R. , Griffin Daniel , Wilkinson Sara J.
Published: March 2023

Vertical greening systems (VGSs) represent an emerging technology within the field of building-integrated horticulture that have been used to help counteract the global issues of urbanisation and climate change. Research and development within the field of building-integrated horticulture, despite being in the infancy stage, is steadily progressing, highlighting a broad range of achievable social, environmental, and economic benefits this sustainable development technology could provide. However, as VGS technology is relatively new, an array of different designs and technologies have been categorized collectively as VGSs, each having various performances towards the proposed and desired benefits. The purpose of this paper is to review existing VGS technologies and analyse the impact of implementation on sustainable development, and subsequently to propose a new VGS design that theoretically achieves the best possible outcomes when aiming to obtain the maximum benefits of installing a VGS. The resultant design creates new opportunities for VGS environmental amenities and maintenance, increases the scope of applications, and improves the environmental performance of the host building. The proposed design has the potential to transform VGSs beyond conventional functions of aesthetic greening to create novel ecosystems, which enhances the formation of habitats for a more diverse range of flora and fauna.
Understanding Private Preferences in Urban Development—Analysing Spatial Patterns of Food Discount Stores Locations in Switzerland
Authors: Hengstermann Andreas Heinrich , Jehling Mathias
Published: March 2023

This paper examines the spatial pattern of food discount stores in Switzerland, where private actors made location decisions without interference from planning regulations until 2016. Using aerial images and a classification scheme with functional and morphological attributes, the study shows that the majority of discount stores were built in peripheral commercial areas or greenfield sites as solitary buildings, indicating a preference for minimal land acquisition costs and car orientation. Some integrated central locations were also chosen. The average density measured by floor area ratio was low. The results suggest that without planning intervention, private actors’ decisions would lead to sprawled settlement patterns with high ecological and societal costs. Further research is needed to explore the potential role of planning in mitigating this effect.
Effect of Green Human Resource Management on Green Psychological Climate and Environmental Green Behavior of Hotel Employees: The Moderator Roles of Environmental Sensitivity and Altruism
Authors: Uslu Fatih , Keles Ali , Aytekin Arif , Yayla Ozgur , Keles Huseyin , Ergun Gozde Seval , Tarinc Abdullah
Published: March 2023

This article reports the findings of how green human resource management (GHRM) practices can influence the perceptions of hotel employees regarding their organizations’ commitments to green psychological climate (GPC) and their environmentally responsible behavior. GHRM practices refer to the policies and procedures that support environmental sustainability and reduce the negative effects of business activities on the environment. The data used in the research were collected from 425 employees working in 11 5-star hotels in the Antalya/Manavgat districts. For data analysis, data scan analysis was used and the results were then analyzed through the AMOS software to test the structural model. The study has suggested that GHRM practices can positively affect the perceptions of employees concerning their commitment to GPC, which in turn can lead to more environmentally green behaviors. The study also examines the roles of environmental sensitivity and altruism in the relationship between GHRM practices and environmental behavior. The research has shown that individuals with higher levels of environmental sensitivity and altruism are more likely to exhibit environmentally responsible behavior. This means that the employees who are sensitive to environmental issues and have an altruistic personality are more liable to respond positively to GHRM practices of their businesses and are more likely to be environmentally responsible. The research has also emphasized that businesses should consider individual differences in environmental attitudes and behaviors when implementing GHRM practices.
Digital Workplaces and Information Security Behavior of Business Employees: An Empirical Study of Saudi Arabia
Authors: Saeed Saqib
Published: March 2023

In the post pandemic era, the telecommuting of business employees has widely become acceptable in organizations, which demands extensive dependence on digital technologies. In addition, this poses additional security threats for business employees as well as organizations. In order to better respond to security threats, business employees must have a higher level of awareness of the potential threats that are relevant to digital infrastructure used within the workplace. In this paper, we present a quantitative study conducted in line with the theory of planned behavior to gain insight into employee behavior toward information security within different business sectors in Saudi Arabia. The key factors chosen for our model were password management, infrastructure security management, email management, organizational security policy, organizational support and training, and the perception of the level of security. We have applied structured equation modelling to identify most of the relevant factors based on the respondents’ feedback. The results based on the business employee behavior showed that they respondents did not perceive all of the constructs of our model as relevant security factors, which can potentially result in security lapses. This indicates that more security-related measures should be put in place and that business employees should be updated periodically about potential security threats. To this effect, we divided the studied security measures into those which should be implemented at organizational and individual levels. The results will potentially help business managers to design appropriate security trainings, guidelines, and policies for their employees to ensure more information security awareness and protect their technological infrastructure, especially within home office environments.
Analysis of Dynamic Connectedness Relationships among Clean Energy, Carbon Emission Allowance, and BIST Indexes
Authors: Doğan Mesut , Raikhan Sutbayeva , Zhanar Nurbossynova , Gulbagda Bodaukhan
Published: March 2023

Understanding and examining energy markets correctly is crucial for stakeholders to attain maximum benefit and avoid risks. As a matter of fact, the volatility that occurred in energy markets and recent crises had major impacts on national economies. Dynamic connectedness relationships (DCRs) can make quite powerful predictions for both low-frequency data and limited time-series data. The objective of this study is to explicate the dynamic connectedness relationships among the BIST sustainability index, BIST 100 index, S&P Global Clean Energy index (S&P GCEI), and S&P GSCI carbon emission allowances (EUA). The daily data obtained over the period 11 April 2014–11 November 2022 were used for the research study. The DCRs among the variables used in the study were investigated by employing the time-varying parameter vector autoregressive (TVP-VAR) model. As a result of the study, the volatility from carbon emission allowances was determined to spill over to S&P GCEI, BIST 100, and BIST sustainability indexes. During the COVID-19 pandemic, significant reductions were detected in the volatility spillover (VS) from carbon emission allowances to S&P GCEI, BIST 100, and BIST sustainability indexes. Moreover, it was revealed that a weak VS existed from S&P GCEI to BIST sustainability and BIST 100 indexes. The findings reveal the importance of policymakers taking some incentive measures in EUA prices and also its role in portfolio diversification.
Entrepreneurship Research in Times of COVID-19: Experiences from South America
Authors: Fernández-Bedoya Víctor Hugo , Meneses-La-Riva Monica Elisa , Suyo-Vega Josefina Amanda , Gago-Chávez Johanna de Jesús Stephanie
Published: March 2023

The pandemic caused by COVID-19 has had diverse effects on the population and businesses. Due to their low visibility, there is a significant knowledge gap for the scientific community regarding the situation of South American entrepreneurship during the COVID-19 pandemic. Therefore, this systematic review aims to answer the following research questions: What scientific evidence is available on entrepreneurship in South America during the COVID-19 pandemic? From which countries do the studies originate? What conclusions do they present, and what lessons can be learned from them? The Scopus and Scielo databases were explored in this systematic review. Due to the diversity of languages in which articles from this region are published, searches were conducted in English, Spanish, and Portuguese. In each case, we searched for results containing the words COVID-19 and entrepreneurship (emprendimiento in Spanish, empreendedorismo in Portuguese) in the title, abstract, or keywords. The initial search produced 783 records, which were filtered based on seven criteria, resulting in 15 articles. The final articles identified had corresponding authors affiliated with South American institutions. We conclude that, in South America, some entrepreneurs recognize the importance of maintaining the economic stability of their employees and communities in addition to sustaining their businesses. Their actions serve as case studies of resilience and perseverance in adverse circumstances.
Edge Computing Data Optimization for Smart Quality Management: Industry 5.0 Perspective
Authors: Bajic Bojana , Suzic Nikola , Moraca Slobodan , Stefanović Miladin , Jovicic Milos , Rikalovic Aleksandar
Published: March 2023

In the last decade, researchers have focused on digital technologies within Industry 4.0. However, it seems the Industry 4.0 hype did not fulfil industry expectations due to many implementation challenges. Today, Industry 5.0 proposes a human-centric approach to implement digital sustainable technologies for smart quality improvement. One important aspect of digital sustainability is reducing the energy consumption of digital technologies. This can be achieved through a variety of means, such as optimizing energy efficiency, and data centres power consumption. Complementing and extending features of Industry 4.0, this research develops a conceptual model to promote Industry 5.0. The aim of the model is to optimize data without losing significant information contained in big data. The model is empowered by edge computing, as the Industry 5.0 enabler, which provides timely, meaningful insights into the system, and the achievement of real-time decision-making. In this way, we aim to optimize data storage and create conditions for further power and processing resource rationalization. Additionally, the proposed model contributes to Industry 5.0 from a social aspect by considering the knowledge, not only of experienced engineers, but also of workers who work on machines. Finally, the industrial application was done through a proof-of-concept using manufacturing data from the process industry, where the amount of data was reduced by 99.73% without losing significant information contained in big data.
A Comparative Analysis of Separate and Joint Environmental Rights Trading Markets in China
Authors: Luo Tianyu , Chen Hongmin
Published: March 2023

The structuring of effective market-based environmental rights instruments can help to achieve energy efficiency and emission reduction goals while minimizing economic costs. As part of the global drive for sustainable development, pollution rights, carbon emission permits, and white certificates have become widely used as environmental rights trading schemes in many countries. However, interactions between environmental rights can create challenges. For instance, China has established a national carbon market, which it aims to connect with the energy consumption permit trading market. The effectiveness of separate and joint markets in achieving win-win outcomes is an area that requires further research. To address this question, we employed a mixed-integer linear programming model to simulate the potential incremental outputs and energy savings of 16 high-energy-consuming and high-emission industries in China from 2010 to 2019. Our findings indicate that the joint energy consumption permits and the carbon emission permits market yield the greatest economic benefits, but they lack a distinct advantage compared to the separate carbon market. Additionally, industries face less pressure to ensure energy savings in the joint market. The energy saving ratio of the joint market is 0.1% lower than that of the separate carbon market. We also found that the construction of a joint market will incur additional costs for firms and governments. Based on our benefit and cost analysis, we propose that governance subjects of pilot cities prioritize the establishment of the carbon market and not the rapid expansion of the pilot-level scope of energy consumption permits.
Confinement of Concrete Using Banana Geotextile-Reinforced Geopolymer Mortar
Authors: Pilien Vincent P. , Promentilla Michael Angelo B. , Leaño Julius L. , Oreta Andres Winston C. , Ongpeng Jason Maximino C.
Published: March 2023

Geopolymer, a sustainable alternative to ordinary Portland cement (OPC), offers reduced embodied energy, lower carbon emissions, enhanced durability, eco-compatibility, and waste valorization potential. In confining structural members, geopolymer still has limitations with respect to its brittleness and other properties. Enhancing the properties of geopolymer by adding banana fibers (BF) and fly ash (FA) to form banana geotextile-reinforced geopolymer mortar (BGT-RGM) as confining material, is investigated in this experimental study. BGT-RGM is a textile-reinforced mortar with varying thickness of BF-reinforced geopolymer mortar (BFRGM) through NaOH-treated 10 mm BFs and 2 mm banana geotextile (BGT) having varied grid spacings. To develop BGT-RGM, the physical, mechanical, and chemical properties of the BFs were determined, while BFRGMs were evaluated for compressive and dog-bone tensile strengths, workability, scanning electron microscopy (SEM) imaging, and thermogravimetric analysis (TGA). The BGT-RGM-confined and unconfined concrete were evaluated, and the strength variations were imparted by the confinement as reflected on the stress-strain curves. The local crack formation mode of failure was also determined through crack patterns during an axial load test. The BGT-RGM with 20 mm thickness of BFRGM with 15 mm and 20 mm geotextile grid spacings, exhibited 33.3% and 33.1% increases in strength, respectively. Future investigations towards the development and application of BGT-RGM are also discussed.
Relationship between Perceived Teacher Support and Student Engagement in Physical Education: A Systematic Review
Authors: Guo Qi , Samsudin Shamsulariffin , Yang Xiaoming , Gao Jianxin , Ramlan Mohd Aswad , Abdullah Borhannudin , Farizan Noor Hamzani
Published: March 2023

Student engagement is an essential indicator of educational quality and an instability behavior influenced by teachers. However, research on how teacher support influences this behavioral outcome in physical education has started late compared to academic settings. Hence, this systematic review aims to examine the empirical literature regarding the relationship between perceived teacher support and student engagement in physical education. This review complied with the PRISMA statement and ultimately found 11 eligible studies through the literature utilizing several databases, namely, Web of Science, SCOPUS, PsycINFO, ERIC, and SPORTDiscus. The results revealed a significant positive relationship between perceived teacher support and multiple dimensions of student engagement in physical education, especially in behavioral and emotional engagement. Mediating effects were found in five studies, and autonomous motivation and psychological need satisfaction were the crucial mediators. Teacher support plays a vital role in positive student–teacher interactions and students demonstrate enhanced engagement in physical education learning when teachers provide autonomy, competence, and emotional support. This study has great significance for developing instructional strategies to improve the sustainability of student engagement in physical education and also provides insight for researchers exploring options for optimizing motivational teaching styles to promote the development of sustainable teaching practices.
Modeling the Impact and Risk Assessment of Urbanization on Urban Heat Island and Thermal Comfort Level of Beijing City, China (2005–2020)
Authors: Amir Siddique Muhammad , Boqing Fan , Dongyun Liu
Published: March 2023

Rapid urbanization poses a threat to various ecosystem services. Beijing has undergone extensive infrastructure development in recent years. The study aims to extract land surface temperature (LST) and land use cover (LUC) data from satellite imagery, identify urban heat island (UHI) areas in Beijing, and determine the correlation between LST, LUC, NDVI, and BUI. It will also investigate the relationship between UHI and built/unbuilt areas, evaluate thermal comfort in Beijing using UTFVI, and assess the ecological quality of different land use types using the Ecological Evaluation Index (EEI). The results can inform urban planning and management in rapidly urbanizing and climate-changing regions. Changes in LUC and other activities affect the distribution of LST. For the study years (2005–2020), the estimated mean LST in Beijing was 24.72 °C, 27.07 °C, 26.22 °C, and 27.03 °C, respectively. A significant positive correlation (r = 0.96 p > 0.005) was found between LST and urban areas with other infrastructures. Geographically weighted regression (GWR) outperformed with Adj R2 > 0.74, suggesting that the extent of an urban heat island (UHI) is strongly dependent on the settlements, LUC composition, size, and terrain of surrounding communities. Urban hotspots in the city were identified and validated using Google Earth imagery. The Ecological Evaluation Index (EEI) value was relatively low compared to other ecosystem-related units. EEI showed a continuous increase of six percent in the most negative categories, indicating an unstable environment. This study concludes that urbanization affects the city’s environment, and study findings would help to regulate the urban ecosystem in Beijing.
Azolla Biofertilizer Is an Effective Replacement for Urea Fertilizer in Vegetable Crops
Authors: Jama Aisha , Widiastuti Dwi P. , Gafur Sutarman , Davis Jessica G.
Published: March 2023

Azolla spp. is a water fern that hosts Anabaena azolla, an N-fixing cyanobacterium, in its dorsal leaf cavities. Azolla occurs naturally in freshwater bodies in warm-temperate and tropical regions, and they have commonly been grown in rice paddies as a living fertilizer, providing N to the rice crop. We evaluated the potential use of Azolla harvested from freshwater bodies and applied as a biofertilizer to dryland vegetable crops. Two-thirds of the greenhouse gas emissions from crop production is attributed to N fertilizer, including fossil fuels used in fertilizer production and transportation. Azolla grown in on-farm ponds could remove CO2 from the atmosphere and minimize the use of fossil fuels in fertilizer production and transport. A 140-d laboratory incubation was used to compare the N mineralization of Azolla biofertilizer with compost and cyanobacterial biofertilizer treatments. Azolla treatments had the greatest N availability at the end of the incubation (73.0%), with compost demonstrating the least N availability (15.5%), and the cyanobacterial biofertilizers moderate in N release (31.6%). A greenhouse study evaluated the N uptake and yield of kale (Brassica oleracea) receiving Azolla biofertilizer compared to urea and organic fertilizers. The nitrogen uptake by kale followed the same pattern as in the incubation study, with the Azolla treatments highest among the organic fertilizers, and urea the greatest overall. Compost yielded better than the control but was the lowest yielding among the fertilizer treatments. Finally, we compared the agronomic effect of Azolla biofertilizer with urea and manure applied at the same N rates to spinach (Amaranthus cruentus) and radish (Raphanus sativus) crops grown in the field on alluvial and peat soils. Fertilizer treatments affected the spinach yield at both locations but did not affect the radish yield. The manure treatment resulted in the highest spinach yields (18–27 t ha−1), and the Azolla treatment applied at the same N rate as the manure yielded the same as the manure treatment on the peat soil and had the highest leaf and branch numbers. Azolla shows promise as a biofertilizer for dryland vegetable crops; however, an economic feasibility analysis is needed prior to encouraging the widespread adoption of on-farm Azolla production and use.
Spatial and Temporal Evolution of Multi-Scale Regional Quality Development and the Influencing Factors
Authors: Du Liping , Zhou Xianghong , Yang Ruting , Cheng Pengfei , Cheng Sijie
Published: March 2023

In recent years, environmental pollution and massive consumption of resources in the traditional development model have posed significant challenges to the environment and society. In this study, we discuss the influencing factors of high-quality development. High-quality development is increasingly important to exploring the current state of quality development in China. Using the evaluation data of the major nodes of China’s provincial administrative regions from 2007 to 2019, the entropy value method was applied to calculate the comprehensive index of high-quality regional development, explain the spatial and temporal evolution pattern of China’s high-quality regional development, and reveal the internal driving factors of spatial and temporal evolution. The study concludes that the level of high-quality regional development in the east is higher than that in the western region, and the level of high-quality regional development in the southern region is higher than that in the north. Investment influence, industrial development, and urban–rural development have positive effects on high-quality regional development. However, location and transportation negatively affect high-quality regional development.
Establishment of Monterrey Pine (Pinus radiata) Plantations and Their Effects on Seasonal Sediment Yield in Central Chile
Authors: Pizarro Roberto , García-Chevesich Pablo , Ingram Ben , Sangüesa Claudia , Pino Juan , Ibáñez Alfredo , Mendoza Romina , Vallejos Carlos , Pérez Felipe , Flores Juan Pablo , Vera Mauricio , Balocchi Francisco , Bustamante-Ortega Ramón , Martínez Gisella
Published: March 2023

Sediment production and transport in a basin are generally a function of the degree of soil protection, normally represented by plant cover. In this study, two basins located at similar latitudes but with different hydrological regimens and plant covers were studied, one with a pluvial regimen and forest plantations (Purapel) and another one with the pluvio-nival regimen and native forest (Ñuble). For this purpose, sediment yield was analyzed in both drainage areas using the Mann-Kendall statistical test. Both basins showed larger amounts of sediment production during winter months. In addition, sediment yield trends did not show significant variation in the case of the Ñuble, most likely due to non-relevant changes in plant cover over time. However, there is a sustained decrease in annual sediment release at Purapel, coinciding with the afforestation in the basin, so it is logical to attribute the referred reduction to this process. For the first time, the behavior of two watersheds is contrasted, one covered with native forest and the other one with forest plantations, appreciating that the basin covered with plantations presents a reduction in sediment production over time, which means that forest plantations are efficient in sediment retention, even in contrast to native forest. However, both basins have different types of soil, topography, etc., meaning that more studies are needed to support this theory.