bluuebunny/crossref_metadata_2025 huggingface dataset:
Data Acquisition Filtering Focused on Optimizing Transmission in a LoRaWAN Network Applied to the WSN Forest Monitoring System
Authors: Brito Thadeu , Azevedo Beatriz Flamia , Mendes João , Zorawski Matheus , Fernandes Florbela P. , Pereira Ana I. , Rufino José , Lima José , Costa Paulo
Published: January 2023

Developing innovative systems and operations to monitor forests and send alerts in dangerous situations, such as fires, has become, over the years, a necessary task to protect forests. In this work, a Wireless Sensor Network (WSN) is employed for forest data acquisition to identify abrupt anomalies when a fire ignition starts. Even though a low-power LoRaWAN network is used, each module still needs to save power as much as possible to avoid periodic maintenance since a current consumption peak happens while sending messages. Moreover, considering the LoRaWAN characteristics, each module should use the bandwidth only when essential. Therefore, four algorithms were tested and calibrated along real and monitored events of a wildfire. The first algorithm is based on the Exponential Smoothing method, Moving Averages techniques are used to define the other two algorithms, and the fourth uses the Least Mean Square. When properly combined, the algorithms can perform a pre-filtering data acquisition before each module uses the LoRaWAN network and, consequently, save energy if there is no necessity to send data. After the validations, using Wildfire Simulation Events (WSE), the developed filter achieves an accuracy rate of 0.73 with 0.5 possible false alerts. These rates do not represent a final warning to firefighters, and a possible improvement can be achieved through cloud-based server algorithms. By comparing the current consumption before and after the proposed implementation, the modules can save almost 53% of their batteries when is no demand to send data. At the same time, the modules can maintain the server informed with a minimum interval of 15 min and recognize abrupt changes in 60 s when fire ignition appears.
Time-Based and Path-Based Analysis of Upper-Limb Movements during Activities of Daily Living
Authors: Šlajpah Sebastjan , Čebašek Eva , Munih Marko , Mihelj Matjaž
Published: January 2023

Patients after stroke need to re-learn functional movements required for independent living throughout the rehabilitation process. In the study, we used a wearable sensory system for monitoring the movement of the upper limbs while performing activities of daily living. We implemented time-based and path-based segmentation of movement trajectories and muscle activity to quantify the activities of the unaffected and the affected upper limbs. While time-based segmentation splits the trajectory in quants of equal duration, path-based segmentation isolates completed movements. We analyzed the hand movement path and forearm muscle activity and introduced a bimanual movement parameter, which enables differentiation between unimanual and bimanual activities. The approach was validated in a study that included a healthy subject and seven patients after stroke with different levels of disabilities. Path-based segmentation provides a more detailed and comprehensive evaluation of upper limb activities, while time-based segmentation is more suitable for real-time assessment and providing feedback to patients. Bimanual movement parameter effectively differentiates between different levels of upper limb involvement and is a clear indicator of the activity of the affected limb relative to the unaffected limb.
Modular Electromagnetic Transducer for Optimized Energy Transfer via Electric and/or Magnetic Fields
Authors: Zărnescu George-Claudiu , Pîslaru-Dănescu Lucian , Tiliakos Athanasios
Published: January 2023

In this paper, a modular electromagnetic transducer that achieves the optimal transfer of energy from the electric and/or magnetic fields is proposed. Both the magnetic field resonance coupling and the influence of the electric field near the copper transducers of the printed circuit board and inside the FR4-type epoxy material are considered. In our printed arrays of flat transducers, we consider face-to-face capacitances for the study of resonance coupling. Because the space between coil turns is almost double the plate thickness, the coplanar capacitance can be ignored for frequencies under 2 MHz. A radio frequency (RF) transmitter and transducer were built to demonstrate the increased energy transfer efficiency when using both electric and magnetic fields in the near-field region. The transversal leakage flux coupling of a long RF coil was more efficient than a simple axial magnetic field coupling when using pancake transceiver coils. The optimal configuration having one long coil at the base and two or more flat coils as capacitor plates near coil ends generated the highest tandem of magnetic and electrical fields. A power regression tool was used to convert and simplify the transducer current and voltage variation with distance. In this regard, the current change corresponded to magnetic field variation and the voltage change to the electric field variation. New formulas for estimating the near-field region and the self-capacitance of the RF transformer coil are proposed; the optimal function in the frequency domain for a given transducer distance was defined by simulation.
Subjective Assessment of Objective Image Quality Metrics Range Guaranteeing Visually Lossless Compression
Authors: Afnan Afnan , Ullah Faiz , Yaseen Yaseen , Lee Jinhee , Jamil Sonain , Kwon Oh-Jin
Published: January 2023

The usage of media such as images and videos has been extensively increased in recent years. It has become impractical to store images and videos acquired by camera sensors in their raw form due to their huge storage size. Generally, image data is compressed with a compression algorithm and then stored or transmitted to another platform. Thus, image compression helps to reduce the storage size and transmission cost of the images and videos. However, image compression might cause visual artifacts, depending on the compression level. In this regard, performance evaluation of the compression algorithms is an essential task needed to reconstruct images with visually or near-visually lossless quality in case of lossy compression. The performance of the compression algorithms is assessed by both subjective and objective image quality assessment (IQA) methodologies. In this paper, subjective and objective IQA methods are integrated to evaluate the range of the image quality metrics (IQMs) values that guarantee the visually or near-visually lossless compression performed by the JPEG 1 standard (ISO/IEC 10918). A novel “Flicker Test Software” is developed for conducting the proposed subjective and objective evaluation study. In the flicker test, the selected test images are subjectively analyzed by subjects at different compression levels. The IQMs are calculated at the previous compression level, when the images were visually lossless for each subject. The results analysis shows that the objective IQMs with more closely packed values having the least standard deviation that guaranteed the visually lossless compression of the images with JPEG 1 are the feature similarity index measure (FSIM), the multiscale structural similarity index measure (MS-SSIM), and the information content weighted SSIM (IW-SSIM), with average values of 0.9997, 0.9970, and 0.9970 respectively.
Smart Shoe Insole Based on Polydimethylsiloxane Composite Capacitive Sensors
Authors: Luna-Perejón Francisco , Salvador-Domínguez Blas , Perez-Peña Fernando , Corral José María Rodríguez , Escobar-Linero Elena , Morgado-Estévez Arturo
Published: January 2023

Nowadays, the study of the gait by analyzing the distribution of plantar pressure is a well-established technique. The use of intelligent insoles allows real-time monitoring of the user. Thus, collecting and analyzing information is a more accurate process than consultations in so-called gait laboratories. Most of the previous published studies consider the composition and operation of these insoles based on resistive sensors. However, the use of capacitive sensors could provide better results, in terms of linear behavior under the pressure exerted. This behavior depends on the properties of the dielectric used. In this work, the design and implementation of an intelligent plantar insole composed of capacitive sensors is proposed. The dielectric used is a polydimethylsiloxane (PDMS)-based composition. The sensorized plantar insole developed achieves its purpose as a tool for collecting pressure in different areas of the sole of the foot. The fundamentals and details of the composition, manufacture, and implementation of the insole and the system used to collect data, as well as the data samples, are shown. Finally, a comparison of the behavior of both insoles, resistive and capacitive sensor-equipped, is made. The prototype presented lays the foundation for the development of a tool to support the diagnosis of gait abnormalities.
A Model-Driven Approach for Software Process Line Engineering
Authors: Agh Halimeh , Ramsin Raman
Published: January 2023

It has become increasingly preferable to construct bespoke software development processes according to the specifications of the project at hand; however, defining a separate process for each project is time consuming and costly. One solution is to use a Software Process Line (SPrL), a specialized Software Product Line (SPL) in the context of process definition. However, instantiating an SPrL is a slow and error-prone task if performed manually; an adequate degree of automation is therefore essential, which can be achieved by using a Model-Driven Development (MDD) approach. Furthermore, we have identified specific shortcomings in existing approaches for SPrL Engineering (SPrLE). To address the identified shortcomings, we propose a novel MDD approach specifically intended for SPrLE; this approach can be used by method engineers and project managers to first define an SPrL, and then construct custom processes by instantiating it. The proposed approach uses a modeling framework for modeling an SPrL, and applies transformations to provide a high degree of automation when instantiating the SPrL. The proposed approach addresses the shortcomings by providing an adequate coverage of four activities, including Feasibility analysis, Enhancing the core process, Managing configuration complexity, and Post-derivation enhancement. The proposed approach has been validated through an industrial case study and an experiment; the results have shown that the proposed approach can improve the processes being used in organizations, and is rated highly as to usefulness and ease of use.
Impact of the EPBD on Changes in the Energy Performance of Multi-Apartment Buildings in Lithuania
Authors: Monstvilas Edmundas , Borg Simon Paul , Norvaišienė Rosita , Banionis Karolis , Ramanauskas Juozas
Published: January 2023

As per general provisions of European Directive 2010/31/EU on the energy efficiency of buildings (recast), the Lithuanian government transposed the Directive into Lithuanian national law. In the process, the Lithuanian government prepared strategic documents in the field of energy performance and renewable energy that were integrated together through the National Energy and Climate Plan for 2021–2030 (NECP). To better understand the current situation vis-à-vis energy performance, the main characteristics of buildings pertaining to the Lithuanian multi-apartment building stock, classified according to their energy performance class, are analysed and discussed in this paper. Through the exploitation of data from the national Energy Performance Certificate (EPC) register, an overview of the energy performance of the existing Lithuanian residential building stock is presented along with an analysis of the unused potential energy savings pertinent to this building category. The results obtained from the analysed data of energy consumption in buildings shows that the policies adopted over the years were successful in improving the building stock, promoting the move towards the specifications required by a Class A++ (nearly zero energy buildings—NZEB) by 2021. The results show that this was primarily achieved by a significant reduction in the thermal energy used for space heating.
Framing Teaching for Sustainability in the Case of Business Engineering Education: Process-Centric Models and Good Practices
Authors: Fleaca Bogdan , Fleaca Elena , Maiduc Sanda
Published: January 2023

Sustainability is a difficult topic, and education systems are generally complicated, including multiple levels as well as diverse organizations and actors. This dual complexity, which affects both sustainability and higher education systems, poses great challenges for research. Although there has been a growing interest in adopting sustainable practices within HEIs, few studies have focused on the integration of sustainability concerns into curricula through a process-centric lens, and the majority of studies in this area are mainly input-oriented. Therefore, in this study, we seek to address the need for a comprehensive understanding to solve local problems through process-centric views and tested methodologies, offering new possibilities for teaching sustainability. We focus on education as a system (i.e., comprising inputs, outputs, and processes) and develop a conceptual design of the deployed teaching processes for a real-world project scenario aimed at mainstreaming sustainability into the curriculum, in the case of business engineering. The research process consisted of (i) the application of a functional decomposition technique at institutional and project levels for integration of the project into current academic practices; (ii) the application of the SIPOC (Supplier, Inputs, Process, Outputs, Customer) method in conjunction with a flowcharting technique to capture the flow of interactions between project processes and the surrounding structure. The added value derives from a better understanding of the relationships between upstream and downstream processes, enabling sustained improvement and strengthening the teaching practices related to sustainability.
Global Mindset and Adaptive Marketing Capabilities in the Internationalization of Mature Chinese SMEs: International Opportunity Perspective
Authors: Ali Hazem , Li Min , Qiu Xunmin , Farooq Qamar
Published: January 2023

Despite the centrality of international opportunity concept in international entrepreneurship field, SMEs’ internationalization literature has focused mainly on SMEs’ international performance with limited attention paid by researchers to understanding the factors influencing the identification of international opportunities especially among mature internationalized SMEs. To this end, the current study examined the impact of SMEs managers’ global mindset (GM) and adaptive marketing capabilities (AMCs) on international opportunity identification (IOI) among mature Chinese SMEs with emphasis on the moderating impact of export market dynamism (EMD). Initial exploratory study using interviews with five managers of exporting SMEs was conducted to figure the relevance of GM and AMC in explaining IOI; and the presence of EMD. Later, self-administered questionnaires were used to collect data from founders/managers of 217 exporting SMEs. Findings showed that IOI is positively influenced by SME manager’s GM and AMCs. Despite the presence of EMD, it had no significant moderating impact on the relationship between GM and AMCs; and IOI. In the respondents’ characteristics analysis, it was revealed that no significant statistical impact of SME’s size, SME’s age, and SME manager’s international experience on IOI. This paper ends with drawing a set of implications and future research avenues.
How Teacher Social-Emotional Competence Affects Job Burnout: The Chain Mediation Role of Teacher-Student Relationship and Well-Being
Authors: Zhang Wanying , He Erlin , Mao Yaqing , Pang Shilong , Tian Jin
Published: January 2023

Teacher social-emotional competence plays a crucial role in teacher professional development as it is associated with effective stress alleviation at work. However, how and under what conditions teacher social-emotional competence contributes to job burnout is a black box. This study aimed to explored the impact of teacher social-emotional competence on job burnout, focusing on the chain mediation effects of teacher-student relationships and teacher well-being. For this undertaking, stratified random sampling was used and the questionnaire was filled out by 990 teachers in 14 primary schools in Beijing. We analyzed these data using structural equation modeling (SEM). The findings suggested that the teacher social-emotional competence and job burnout were negatively correlated, verifying that teacher social-emotional competence can influence job burnout through the separate and chain mediation effects of teacher-student relationship and teacher well-being. In addition, the separate mediation role of the teacher-student relationship had the most significant effect of all mediation paths. To alleviate teacher job burnout and promote the sustainability of teachers’ professional development, we suggested that emphasizing the development of teacher social-emotional competence and the sustained enhancement of teacher well-being, as well as focusing on improving teacher-student relationship.
An Exploratory Analysis of Sustainability Indicators in Turkish Small- and Medium-Sized Industrial Enterprises
Authors: Saygili Ebru , Uye Akcan Elif , Ozturkoglu Yucel
Published: January 2023

Significant differences exist between the sustainability practices of large businesses and those of small- and medium-sized enterprises in the industrial sector. Small- and medium-sized enterprises have restricted access to capital, resources, and experience. Most sustainable manufacturing strategies are based on indicators and evaluation models developed for large firms. This study aims to identify sustainability indicators for small- and medium-sized industrial firms. The sustainability indicators are generated from the G4-specific standard disclosures of the Global Reporting Initiative, which provide a triple-bottom-line approach. A total of 142 senior and middle sustainability-focused managers and partners participated in the survey. An exploratory factor analysis was performed in the first step, and 12 key factors were found. The Best–Worst Method (BWM) was employed in the second step to rank the criteria in order of priority. As a theoretical contribution, this study introduces human rights and economic impact on society as two additional sustainability indicators for small- and medium-sized enterprises. The two most significant aspects of sustainability for Turkish small- and medium-sized businesses are labor rights and energy saving. This study provides empirical evidence from a broad range of stakeholders for the conceptually addressed challenges of sustainability in prior studies. The results demonstrate empirically that the sustainability-based value creation for stakeholder interests, such as employees at the core of business activities, is greater in small and medium enterprises than for other stakeholders. This study’s findings will give managers a framework for establishing key sustainability indicators for allocating the limited resources of small- and medium-sized enterprises.
Transparent Reporting on Financial Assets as a Determinant of a Company’s Value—A Stakeholder’s Perspective during the SARS-CoV-2 Pandemic and beyond
Authors: Dratwińska-Kania Beata , Ferens Aleksandra , Kania Piotr
Published: January 2023

Background: Socio-economic changes prompt companies to disclose their sustainable development activities in the reporting, showing that they balance three capitals—economic, environmental, and social. On the other hand, while formulating strategies and goals, they consider the company’s widely understood environment, where its stakeholders are essential. As a result, the transparency and usefulness of the reported information are limited. Methods: The study employed financial statements’ content analysis and a statistical method (rank Spearman correlation, Shapiro–Wilk test). The percentage of change in critical areas for reporting transparency on financial assets was analyzed, before and during the SARS-CoV-2 pandemic. Results: The research indicated that the identified critical reporting areas concerning financial assets showed a greater value change during the pandemic. Correlations between the accounting value of the company and the same critical reporting areas were significant. Conclusion: It has been shown that larger companies can use more accounting policy instruments; therefore, the reporting transparency on financial assets is potentially lower for these companies. The transparency of the surveyed corporate reports during the pandemic was lower.
Urban Park Lighting Quality Perception: An Immersive Virtual Reality Experiment
Authors: Masullo Massimiliano , Cioffi Federico , Li Jian , Maffei Luigi , Ciampi Giovanni , Sibilio Sergio , Scorpio Michelangelo
Published: January 2023

Green areas and parks are increasingly important in improving citizens’ physical and mental recovery. Lighting systems play a considerable role in affecting city park life and activities along with people’s moods and behavior in the evening and at night. Immersive virtual reality laboratory experiments may support urban and lighting research by providing information on the combination of lighting setup and visual context of existing or new urban parks. Gaze behaviors obtained from eye-tracking recordings and self-reported measurements using the perceived outdoor lighting quality questionnaire were used to determine the factors affecting human perception, comfort, and cognitive load, as the overall illuminance levels of the scene and correlated color temperature changes. Results pointed out that overall illuminance level and CCT significantly affect the perceived strength and comfort qualities of lighting with a dominance of the first compared with the latter when subjects were free to explore the lit environment. Low CCT and intermediate or high overall illuminance levels can improve the sense of accessibility as well as minimize the cognitive load.
Regional Patterns of Pesticide Consumption Determinants in the European Union
Authors: Robu Raluca Georgiana , Holobiuc Ana-Maria , Alexoaei Alina Petronela , Cojanu Valentin , Miron Dumitru
Published: January 2023

This article contributes to the discussion about the socioeconomic factors that reinforce pesticide dependence in the European Union and hinder the transition to more sustainable agricultural practices in light of the European Union’s Green Deal objective of reducing the use of pesticides by 50% by 2030. The analysis has a two-pronged purpose: (1) to identify the determinants of pesticide consumption in the European Union by conducting a set of four seemingly unrelated regressions and (2) to emphasize the existence of regional patterns across EU countries formed by the factors that significantly impact pesticide consumption based on a cluster analysis. Per capita GDP, selling prices, population, and real income positively influence pesticide use, whereas subsidies and organic agricultural area negatively influence them. Pesticide use is most affected by GDP per capita and least affected by subsidies. Cluster analysis highlights regional differences reflected in three clusters: (1) the most recent EU member states, (2) the European countries with large population levels, and (3) the countries with the highest GDP per capita. Our findings may contribute to the EU’s capacity to generate policy changes at the member state level and can be built into recommendations to address the persistent overuse of pesticides.
Structure of Polycentric Circles Based on the Urban Radiation Pattern: A Case Study in the Yangtze River Delta Region, China
Authors: Liu Yanghui , Yang Shan , Lin Jinping , Cai Anning , Fan Qingyu
Published: January 2023

The metropolitan area is the inevitable trend of urbanization towards an advanced form. The pattern of urban radiation is the key to building a metro area and promoting high-quality regional development. In order to effectively promote the rationalization of metropolitan areas and regional integration development, this paper takes the Yangtze River Delta (YRD) region as an example, calculates the intensity of city centrality (ICC) based on the statistical data, and explores the radiation pattern and spatial relationship of cities at different levels by using methods such as the extended breaking point model and the hierarchical Voronoi diagram. The research results show that: (1) The ICC in the YRD shows a spatial pattern of “high in the east and low in the west, high in the middle and low in the north and south”. (2) The ICC value of “strong-strong” adjacent cities shows the tendency of the radiation range to shrink and that the radiation direction is perpendicular to both sides. The “strong-weak” adjacent cities’ radiation range and direction show an expansion–contraction trend. The radiation range and direction of “weak-weak” adjacent cities exhibit disorder. (3) Because the ICC is hierarchical, urban radiation is a polycentric, nested circle structure. Shanghai is the first-level center, and Hangzhou, Nanjing, Ningbo, Hefei, and Xuzhou are the second-level centers. (4) The sequence of the spatial morphological complexity and stability in each circle, from complex to simple, is the Hangzhou circle, the Shanghai circle, the Xuzhou circle, the Hefei circle, and the Nanjing circle. The spatial morphological characteristics of the Ningbo circle do not meet the morphological dimension conditions. The study of the polycentric circle structure is of practical significance for the enhancement of the radiation driving effect of the central city and the expansion and improvement of the metropolitan area.
Connecting Sustainable Human Development and Positive Psychology through the Arts in Education: A Systematic Review
Authors: Vazquez-Marin Pedro , Cuadrado Francisco , Lopez-Cobo Isabel
Published: January 2023

Positive psychology and sustainable human development seek to improve the well-being of the individual. To achieve this well-being at the education level, positive education seeks to develop character strengths, and education for development facilitates the development of competencies. Moreover, the literature has demonstrated that the arts in positive education develop individual character strengths, socioemotional competencies and students’ relationship with their environment. Accordingly, in this systematic review, we aim to connect positive psychology and sustainable human development by evaluating the arts in education, based on the concepts of well-being. The results indicate that there are points of confluence between subjective and sustainable well-being, and illuminate the links and their connections between competencies and character strengths, with critical thinking functioning as an important connector between the two. Since character strengths are measurable and educable, we advocate their use as a tool to measure the human development index (HDI) in the education of a specific community. Thus, we are able to evaluate whether the competencies for development are achieved, as well as their role as determinants of the overall well-being of the individual. On the other hand, our work highlights the need to increase the number of investigations in this field to enable an empirical evaluation of how these connections are established and if they are efficient and durable.
Predicting Cu(II) Adsorption from Aqueous Solutions onto Nano Zero-Valent Aluminum (nZVAl) by Machine Learning and Artificial Intelligence Techniques
Authors: Sadek Ahmed H. , Fahmy Omar M. , Nasr Mahmoud , Mostafa Mohamed K.
Published: January 2023

Predicting the heavy metals adsorption performance from contaminated water is a major environment-associated topic, demanding information on different machine learning and artificial intelligence techniques. In this research, nano zero-valent aluminum (nZVAl) was tested to eliminate Cu(II) ions from aqueous solutions, modeling and predicting the Cu(II) removal efficiency (R%) using the adsorption factors. The prepared nZVAl was characterized for elemental composition and surface morphology and texture. It was depicted that, at an initial Cu(II) level (Co) 50 mg/L, nZVAl dose 1.0 g/L, pH 5, mixing speed 150 rpm, and 30 °C, the R% was 53.2 ± 2.4% within 10 min. The adsorption data were well defined by the Langmuir isotherm model (R2: 0.925) and pseudo-second-order (PSO) kinetic model (R2: 0.9957). The best modeling technique used to predict R% was artificial neural network (ANN), followed by support vector regression (SVR) and linear regression (LR). The high accuracy of ANN, with MSE < 10−5, suggested its applicability to maximize the nZVAl performance for removing Cu(II) from contaminated water at large scale and under different operational conditions.
Rapid Assessment of 2022 Floods around the UNESCO Site of Mohenjo-Daro in Pakistan by Using Sentinel and Planet Labs Missions
Authors: Hegyi Alexandru , Agapiou Athos
Published: January 2023

This communication study aims to provide evidence on how Sentinel sensors and Copernicus Programme’s contributing missions can support heritage endangered by natural hazards. The recent catastrophic floods of 2022 in Pakistan, mainly in the Indus Valley, threatened one of the most iconic sites within the country; thus, the UNESCO World Heritage Site of Mohenjo-Daro was selected here as a case study. Even if the main area of the site was not directly affected by the floods but rather by the heavy rains, its landscape suffered profound damage. This study aims to report a combined remote-sensing methodology for a rapid assessment of the flooded areas around the site. By using Sentinel-1 radar data in combination with mid-resolution Sentinel-2 data and Planet Lab images, it was possible to accurately map the affected areas near the site. This approach can be used to better understand the extent of the affected areas and build a better recovery strategy. A near-real-time satellite-based investigation and observations combining various sensors and resolutions (Sentinel 1 and 2 images, as well as Planet Lab images) can provide valuable insights for local heritage managers.
Exploring the Determinants of the Urban–Rural Construction Land Transition in the Yellow River Basin of China Based on Machine Learning
Authors: Chen Wenfeng , Liu Dan , Zhang Tianyang , Li Linna
Published: January 2023

Understanding the determinants of urban–rural construction land transition is necessary for improving regional human–land relationships. This study analysed the spatiotemporal pattern of urban–rural construction land transition at the grid scale in the Yellow River Basin (YRB) of China during 2000–2020 by bivariate spatial autocorrelation analysis and further explored its determinants based on a machine learning method, the gradient boosted decision tree (GBDT) model. The results showed that both urban construction land (UCL) and rural residential land (RRL) increased, with an annual growth amount of UCL three times that of RRL, and the proportion of UCL (LUUR) remained stable after 2015. The determinants of UCL, RRL, and LUUR varied. The UCL mainly depended on socioeconomic factors, with their contribution exceeding 50%, while the RRL transition was mainly determined by physical geographic factors, with their contribution decreasing from 67.6% in 2000 to 59.7% in 2020. The LUUR was influenced by both socioeconomic and physical geographic factors, with the relative importance of socioeconomic factors increasing over the years. Meanwhile, the impacts of different determinants were nonlinear with a threshold effect. In the future, optimizing the distribution of urban–rural construction land and rationally adjusting its structure will be necessary for promoting urban–rural sustainability in the YRB.
A Game Strategy Study on Innovation Efficiency of China’s Listed Charging Pile Companies: Based on Generalized Fuzzy DEA Method
Authors: Li Shanwei , Li Jingjie , Ding Junli , Sun Mochen , Cui Chenying
Published: January 2023

As a necessary infrastructure for new energy vehicles (NEV), charging piles have become a hot topic of social concern. Studying the innovation efficiency of charging pile companies can help to solve the development dilemma of the charging pile industry. This paper uses the generalized fuzzy data envelopment analysis (DEA) method based on game theory to study 23 Chinese listed charging pile manufacturing companies’ innovation efficiency from 2019 to 2021. On this basis, 15 charging pile technological interrelatedness companies are joined to establish a new game environment and to discuss the possibility of charging pile product manufacturing companies shifting to a new business model led by value-added service provision. The results show that the innovation efficiency of each company is significantly improved in the cooperative state, while the opposite is true in the competitive state, so cooperation is the company’s priority choice. Charging pile product manufacturing companies are more inclined to cooperate with technologically interrelated companies. The business model dominated by value-added service provision is conducive to improving the level of industrial innovation. The competition will easily lead to the decline of their innovation efficiency. Hence, companies should carefully choose their competition strategy.
Analysis of the Current Situation of the Research on the Influencing Factors of Online Learning Behavior and Suggestions for Teaching Improvement
Authors: Li Zhigang , Liu Yi
Published: January 2023

With the rapid development in online education and the recurrence of COVID-19 around the world, people have temporarily turned to online education. To identify influencing factors of online learning behavior and improve online education, this study used CiteSpace to visually analyze research on influencing factors of online learning behavior on WoS. It discusses the research status, hotspots, and trends. Then, through cluster analysis and literature interpretation, the paper summarizes the types of online learning behavior and the influencing factors of different online learning behaviors from positive and negative dimensions. The findings of this paper are as follows. (1) The number of studies on the influencing factors of online learning behavior has increased in the last decade, especially after the outbreak of COVID-19. The research countries and institutions in this field lack contact and cooperation. (2) Online learning behaviors mainly include online learning engagement behavior, continuous behavior, procrastination behavior, and truancy behavior. (3) Online learning engagement behavior is mainly affected by perceived usefulness, perceived ease of use, individual characteristic differences, and other factors. (4) Online learning continuous behavior is mainly affected by quality, perceived usefulness, learning self-efficacy, and other factors. (5) The influencing factors of online learning procrastination mainly include learning environment, individual characteristics, social support, and pressure. (6) The main influencing factors of online learning truancy behavior are social interaction, participation, and learner control. At the end of this paper, according to the action mode of the influencing factors of online learning behavior, some suggestions for teaching improvement are put forward from the two perspectives of promoting positive online learning behavior and avoiding negative online learning behavior, which can provide a reference for teachers and schools in the future when conducting online education.
Plasma Treatment as a Sustainable Method for Enhancing the Wettability of Jute Fabrics
Authors: Ivanovska Aleksandra , Milošević Marija , Obradović Bratislav , Svirčev Zorica , Kostić Mirjana
Published: January 2023

In this paper, raw jute fabric was subjected to atmospheric pressure dielectric barrier discharge (at 150 or 300 Hz) to enhance its wettability, i.e., capillarity and wetting time. Attenuated Total Reflectance-Fourier Transform Infrared (ATR-FTIR) spectroscopy and Field Emission Scanning Electron Microscopy (FE-SEM) were used to assess the changes in the fabrics’ surface chemistry and morphology induced by plasma treatments. The obtained results revealed that both plasma treatments enhanced the wettability of jute fabrics, which could be ascribed to the changes in the fibers’ surface chemistry (the removal of non-cellulosic components, exposure of the cellulose molecules, and oxidation) and morphology (increased roughness due to etching of the surface layers and partial fibrillation). Capillary rise heights increased by approximately 1.8 and 1.9 times, and wetting times were 35 and 34 times shorter 24 h after the plasma treatment at 150 and 300 Hz, respectively. Special attention was given to the aging effect of plasma treatment indicated no significant changes in the fabrics’ capillarity and wetting time after 28 and 7 days, respectively, proving the durability of the effects of plasma treatment. Plasma-treated raw jute fabrics could be used as water-binding geo-prebiotic polysaccharide supports to provide the necessary water for the initial growth of cyanobacterial biocrusts. The lack of moisture is the main constraint in biocrust development after cyanobacterial inoculation. The combination of such water-supportive fabrics and cyanobacterial strains could be used for the rehabilitation of various degraded lands, sediments, and substrates, as well as for air and water pollution control.
Campus Dining Sustainability: A Perspective from College Students
Authors: Yoon Borham , Lee Jinha , Lim Heejin
Published: January 2023

The purpose of the study is to assess campus dining sustainability from the college students’ perspective. A total of 394 responses were analyzed by the importance-performance analysis (IPA) to determine the difference between college students’ importance ratings for and perceived sustainability performance of sustainable practices in campus dining operations. The locus for focus model was applied to demonstrate the priority of the sustainable practices. The results indicate that there is a gap between students’ expectation and university dining services’ performance regarding sustainable practices. The findings suggest that university administrators and operators need to focus on reducing food waste and on food donation so that they can meet the customers’ green values and expectation.
Techno-Economic-Environmental Assessment of an Isolated Rural Micro-Grid from a Mid-Career Repowering Perspective
Authors: Rehmani Abdul Munim , Kazmi Syed Ali Abbas , Altamimi Abdullah , Khan Zafar A. , Awais Muhammad
Published: January 2023

Pakistan is an energy deficient country with depleting energy reserves and increasing energy demand. Due to excessive population growth, the domestic and commercial energy sectors are experiencing rising demand. To meet the requisite demand, renewables are favored rather than conventional counterparts. In this study, we model hybrid power systems using solar, wind and biomass resources for electrifying remote areas. The four locations are chosen for the study around a developing country, Pakistan, where each site is designed according to an isolated microgrid with maximum indigenous resources potential as per the requisite demands. A survey is conducted for the load demand and biomass availability. Optimization is conducted across objectives of minimum levelized cost of the generated energy, least the net present cost and lesser payback period. The optimal results were achieved in-terms of required objectives across southern sites as compared to northern counterparts. The cost of generated energy is comparable to grid electricity and ensures 24 h power supply without cut off and load shedding to the un-electrified rural area. The hybrid power system has a low carbon footprint across emissions due to the use of renewable resources. All the estimated load of rural communities is met with the available resources and mid-career impact has also been conducted across 10 years of the project life to fulfill the increasing load demand of the communities after installation. The results are validated via comparative analysis and show the effectiveness of the proposed study.
On Some Generalizations of Cauchy–Schwarz Inequalities and Their Applications
Authors: Altwaijry Najla , Feki Kais , Minculete Nicuşor
Published: January 2023

The aim of this paper is to provide new upper bounds of ω(T), which denotes the numerical radius of a bounded operator T on a Hilbert space (H,⟨·,·⟩). We show the Aczél inequality in terms of the operator |T|. Next, we give certain inequalities about the A-numerical radius ωA(T) and the A-operator seminorm ∥T∥A of an operator T. We also present several results related to the A-numerical radius of 2×2 block matrices of semi-Hilbert space operators, by using symmetric 2×2 block matrices.
GCAT-GTCU: Graph-Connected Attention Network and Gate Than Change Unit for Aspect-Level Sentiment Analysis
Authors: Ma Chunming , Li Xiuhong , Wang Huiru , Zheng Ying
Published: January 2023

Currently, attention mechanisms are widely used in aspect-level sentiment analysis tasks. Previous studies have only used attention mechanisms combined with neural networks for aspect-level sentiment classification, and the feature extraction of the model is insufficient. When the same aspect and sentiment polarity appear in multiple sentences, the semantic information sharing of the same domain is also ignored, resulting in low model performance. To address these problems, the paper proposes an aspect-level sentiment analysis model, GCAT-GTCU, which combines a Graph-connected Attention Network containing symmetry with Gate Than Change Unit. Three nodes of words, sentences, and aspects are constructed, and local and deep-level features of sentences are extracted using CNN splicing BiGRU; node connection information is added to GAT to form a GCAT containing symmetry to realize the information interaction of three nodes, pay attention to the contextual information, and update the shared information of three nodes at any time; a new gating mechanism GTCU is constructed to filter noisy information and control the flow of sentiment information; finally, the three nodes are extracted information to predict the final sentiment polarity. The experimental results on four publicly available datasets show that the model outperforms the baseline model against which it is compared in some very controlled situations.
A Tent Lévy Flying Sparrow Search Algorithm for Wrapper-Based Feature Selection: A COVID-19 Case Study
Authors: Yang Qinwen , Gao Yuelin , Song Yanjie
Published: January 2023

The “Curse of Dimensionality” induced by the rapid development of information science might have a negative impact when dealing with big datasets, and it also makes the problems of symmetry and asymmetry increasingly prominent. Feature selection (FS) can eliminate irrelevant information in big data and improve accuracy. As a recently proposed algorithm, the Sparrow Search Algorithm (SSA) shows its advantages in the FS tasks because of its superior performance. However, SSA is more subject to the population’s poor diversity and falls into a local optimum. Regarding this issue, we propose a variant of the SSA called the Tent Lévy Flying Sparrow Search Algorithm (TFSSA) to select the best subset of features in the wrapper-based method for classification purposes. After the performance results are evaluated on the CEC2020 test suite, TFSSA is used to select the best feature combination to maximize classification accuracy and simultaneously minimize the number of selected features. To evaluate the proposed TFSSA, we have conducted experiments on twenty-one datasets from the UCI repository to compare with nine algorithms in the literature. Nine metrics are used to evaluate and compare these algorithms’ performance properly. Furthermore, the method is also used on the coronavirus disease (COVID-19) dataset, and its classification accuracy and the average number of feature selections are 93.47% and 2.1, respectively, reaching the best. The experimental results and comparison in all datasets demonstrate the effectiveness of our new algorithm, TFSSA, compared with other wrapper-based algorithms.
Real-Time Scheduling of Pumps in Water Distribution Systems Based on Exploration-Enhanced Deep Reinforcement Learning
Authors: Hu Shiyuan , Gao Jinliang , Zhong Dan , Wu Rui , Liu Luming
Published: January 2023

Effective ways to optimise real-time pump scheduling to maximise energy efficiency are being sought to meet the challenges in the energy market. However, the considerable number of evaluations of popular optimisation methods based on metaheuristics cause significant delays for real-time pump scheduling, and the simplification of traditional deterministic methods may introduce bias towards the optimal solutions. To address these limitations, an exploration-enhanced deep reinforcement learning (DRL) framework is proposed to address real-time pump scheduling problems in water distribution systems. The experimental results indicate that E-PPO can learn suboptimal scheduling policies for various demand distributions and can control the application time to 0.42 s by transferring the online computation-intensive optimisation task offline. Furthermore, a form of penalty of the tank level was found that can reduce energy costs by up to 11.14% without sacrificing the water level in the long term. Following the DRL framework, the proposed method makes it possible to schedule pumps in a more agile way as a timely response to changing water demand while still controlling the energy cost and level of tanks.
Chronic Exposure to Polystyrene Microplastic Fragments Has No Effect on Honey Bee Survival, but Reduces Feeding Rate and Body Weight
Authors: Al Naggar Yahya , Sayes Christie M. , Collom Clancy , Ayorinde Taiwo , Qi Suzhen , El-Seedi Hesham R. , Paxton Robert J. , Wang Kai
Published: January 2023

Microplastics (MPs), in the form of fragments and fibers, were recently found in honey samples collected in Ecuador as well as in honey bees collected from Denmark and China. However, little is known about how MPs impact bee health. To fill this knowledge gap, we investigated the potential toxicity of irregularly shaped polystyrene (PS)-MP fragments on honey bee health. In the first experiment of its kind with honey bees, we chronically exposed bees with a well-established gut microbiome to small (27 ± 17 µm) or large (93 ± 25 µm) PS-MP fragments at varying concentrations (1, 10, 100 µg mL−1) for 14 days. Bee mortality, food consumption, and body weight were all studied. We found that chronic exposure to PS-MP fragments has no effect on honey bee survival, but reduced the feeding rate and body weight, particularly at 10 µg PS-MP fragments per mL, which may have long-term consequences for honey bee health. The findings of this study could assist in the risk assessment of MPs on pollinator health.