bluuebunny/crossref_metadata_2025 huggingface dataset:
Error Analysis of Heterodyne Interferometry Based on One Single-Mode Polarization-Maintaining Fiber
Authors: Qian Yibin , Li Jiakun , Feng Qibo , He Qixin , Long Fei
Published: April 2023

Using polarization-maintaining fiber (PMF) in dual-frequency heterodyne interferometry has the advantages of reducing the laser’s own drift, obtaining high-quality light spots, and improving thermal stability. Using only one single-mode PMF to achieve the transmission of dual-frequency orthogonal, linearly polarized beam requires angular alignment only once to realize the transmission of dual-frequency orthogonal, linearly polarized light, avoiding coupling inconsistency errors, so that it has the advantages of high efficiency and low cost. However, there are still many nonlinear influencing factors in this method, such as the ellipticity and non-orthogonality of the dual-frequency laser, the angular misalignment error of the PMF, and the influence of temperature on the output beam of the PMF. This paper uses the Jones matrix to innovatively construct an error analysis model for the heterodyne interferometry using one single-mode PMF, to realize the quantitative analysis of various nonlinear error influencing factors, and clarify that the main error source is the angular misalignment error of the PMF. For the first time, the simulation provides a goal for the optimization of the alignment scheme of the PMF and the improvement of the accuracy to the sub-nanometer level. In actual measurement, the angular misalignment error of the PMF needs to be smaller than 2.87° to achieve sub-nanometer interference accuracy, and smaller than 0.25° to make the influence smaller than ten picometers. It provides theoretical guidance and an effective means for improving the design of heterodyne interferometry instruments based on PMF and further reducing measurement errors.
A Shallow Autoencoder Framework for Epileptic Seizure Detection in EEG Signals
Authors: Khan Gul Hameed , Khan Nadeem Ahmad , Altaf Muhammad Awais Bin , Abbasi Qammer
Published: April 2023

This paper presents a trainable hybrid approach involving a shallow autoencoder (AE) and a conventional classifier for epileptic seizure detection. The signal segments of a channel of electroencephalogram (EEG) (EEG epochs) are classified as epileptic and non-epileptic by employing its encoded AE representation as a feature vector. Analysis on a single channel-basis and the low computational complexity of the algorithm allow its use in body sensor networks and wearable devices using one or few EEG channels for wearing comfort. This enables the extended diagnosis and monitoring of epileptic patients at home. The encoded representation of EEG signal segments is obtained based on training the shallow AE to minimize the signal reconstruction error. Extensive experimentation with classifiers has led us to propose two versions of our hybrid method: (a) one yielding the best classification performance compared to the reported methods using the k-nearest neighbor (kNN) classifier and (b) the second with a hardware-friendly architecture and yet with the best classification performance compared to other reported methods in this category using a support-vector machine (SVM) classifier. The algorithm is evaluated on the Children’s Hospital Boston, Massachusetts Institute of Technology (CHB-MIT), and University of Bonn EEG datasets. The proposed method achieves 98.85% accuracy, 99.29% sensitivity, and 98.86% specificity on the CHB-MIT dataset using the kNN classifier. The best figures using the SVM classifier for accuracy, sensitivity, and specificity are 99.19%, 96.10%, and 99.19%, respectively. Our experiments establish the superiority of using an AE approach with a shallow architecture to generate a low-dimensionality yet effective EEG signal representation capable of high-performance abnormal seizure activity detection at a single-channel EEG level and with a fine granularity of 1 s EEG epochs.
Viewpoint-Controllable Telepresence: A Robotic-Arm-Based Mixed-Reality Telecollaboration System
Authors: Luo Le , Weng Dongdong , Hao Jie , Tu Ziqi , Jiang Haiyan
Published: April 2023

In mixed-reality (MR) telecollaboration, the local environment is remotely presented to a remote user wearing a virtual reality (VR) head-mounted display (HMD) via a video capture device. However, remote users frequently face challenges in naturally and actively manipulating their viewpoints. In this paper, we propose a telepresence system with viewpoint control, which involves a robotic arm equipped with a stereo camera in the local environment. This system enables remote users to actively and flexibly observe the local environment by moving their heads to manipulate the robotic arm. Additionally, to solve the problem of the limited field of view of the stereo camera and limited movement range of the robotic arm, we propose a 3D reconstruction method combined with a stereo video field-of-view enhancement technique to guide remote users to move within the movement range of the robotic arm and provide them with a larger range of local environment perception. Finally, a mixed-reality telecollaboration prototype was built, and two user studies were conducted to evaluate the overall system. User study A evaluated the interaction efficiency, system usability, workload, copresence, and user satisfaction of our system from the remote user’s perspective, and the results showed that our system can effectively improve the interaction efficiency while achieving a better user experience than two traditional view-sharing techniques based on 360 video and based on the local user’s first-person view. User study B evaluated our MR telecollaboration system prototype from both the remote-user side and the local-user side as a whole, providing directions and suggestions for the subsequent design and improvement of our mixed-reality telecollaboration system.
Proposal and Implementation of a Procedure for Compliance Recognition of Objects with Smart Tactile Sensors
Authors: Lora-Rivera Raúl , Oballe-Peinado Óscar , Vidal-Verdú Fernando
Published: April 2023

This paper presents a procedure for classifying objects based on their compliance with information gathered using tactile sensors. Specifically, smart tactile sensors provide the raw moments of the tactile image when the object is squeezed and desqueezed. A set of simple parameters from moment-versus-time graphs are proposed as features, to build the input vector of a classifier. The extraction of these features was implemented in the field programmable gate array (FPGA) of a system on chip (SoC), while the classifier was implemented in its ARM core. Many different options were realized and analyzed, depending on their complexity and performance in terms of resource usage and accuracy of classification. A classification accuracy of over 94% was achieved for a set of 42 different classes. The proposed approach is intended for developing architectures with preprocessing on the embedded FPGA of smart tactile sensors, to obtain high performance in real-time complex robotic systems.
Advances in Portable Heavy Metal Ion Sensors
Authors: Hu Tao , Lai Qingteng , Fan Wen , Zhang Yanke , Liu Zhengchun
Published: April 2023

Heavy metal ions, one of the major pollutants in the environment, exhibit non-degradable and bio-chain accumulation characteristics, seriously damage the environment, and threaten human health. Traditional heavy metal ion detection methods often require complex and expensive instruments, professional operation, tedious sample preparation, high requirements for laboratory conditions, and operator professionalism, and they cannot be widely used in the field for real-time and rapid detection. Therefore, developing portable, highly sensitive, selective, and economical sensors is necessary for the detection of toxic metal ions in the field. This paper presents portable sensing based on optical and electrochemical methods for the in situ detection of trace heavy metal ions. Progress in research on portable sensor devices based on fluorescence, colorimetric, portable surface Raman enhancement, plasmon resonance, and various electrical parameter analysis principles is highlighted, and the characteristics of the detection limits, linear detection ranges, and stability of the various sensing methods are analyzed. Accordingly, this review provides a reference for the design of portable heavy metal ion sensing.
A Multimodal Feature Fusion Framework for Sleep-Deprived Fatigue Detection to Prevent Accidents
Authors: Virk Jitender Singh , Singh Mandeep , Singh Mandeep , Panjwani Usha , Ray Koushik
Published: April 2023

Sleep-deprived fatigued person is likely to commit more errors that may even prove to be fatal. Thus, it is necessary to recognize this fatigue. The novelty of the proposed research work for the detection of this fatigue is that it is nonintrusive and based on multimodal feature fusion. In the proposed methodology, fatigue is detected by obtaining features from four domains: visual images, thermal images, keystroke dynamics, and voice features. In the proposed methodology, the samples of a volunteer (subject) are obtained from all four domains for feature extraction, and empirical weights are assigned to the four different domains. Young, healthy volunteers (n = 60) between the age group of 20 to 30 years participated in the experimental study. Further, they abstained from the consumption of alcohol, caffeine, or other drugs impacting their sleep pattern during the study. Through this multimodal technique, appropriate weights are given to the features obtained from the four domains. The results are compared with k-nearest neighbors (kNN), support vector machines (SVM), random tree, random forest, and multilayer perceptron classifiers. The proposed nonintrusive technique has obtained an average detection accuracy of 93.33% in 3-fold cross-validation.
Assessing Virtual Reality Spaces for Elders Using Image-Based Sentiment Analysis and Stress Level Detection
Authors: Kosti Makrina Viola , Georgakopoulou Nefeli , Diplaris Sotiris , Pistola Theodora , Chatzistavros Konstantinos , Xefteris Vasileios-Rafail , Tsanousa Athina , Vrochidis Stefanos , Kompatsiaris Ioannis
Published: April 2023

Seniors, in order to be able to fight loneliness, need to communicate with other people and be engaged in activities to keep their minds active to increase their social capital. There is an intensified interest in the development of social virtual reality environments, either by commerce or by academia, to address the problem of social isolation of older people. Due to the vulnerability of the social group involved in this field of research, the need for the application of evaluation methods regarding the proposed VR environments becomes even more important. The range of techniques that can be exploited in this field is constantly expanding, with visual sentiment analysis being a characteristic example. In this study, we introduce the use of image-based sentiment analysis and behavioural analysis as a technique to assess a social VR space for elders and present some promising preliminary results.
Documentation Status and Youth’s Critical Consciousness across Borders
Authors: Gallo Sarah , Adams Corral Melissa
Published: April 2023

Centering the testimonios of two sets of transborder high school seniors living and learning in Mexico and the U.S., in this article, we draw upon decolonizing approaches to theorize critical consciousness formation for and with students from families with mixed documentation status who cross physical and metaphorical borders. Data come from two larger qualitative studies on immigration and education and demonstrate how young people recognize inequity, critique it, and engage in a range of actions to counteract it. We argue that border-crossing youth draw upon personal experiences to critique and take action to change oppressive realities. We extend critical consciousness scholarship by bringing unique attention to the role of undocumentedness in critical consciousness formation.
Role of Lignin in Wheat Plant for the Enhancement of Resistance against Lodging and Biotic and Abiotic Stresses
Authors: Riaz Muhammad Waheed , Yousaf Muhammad Irfan , Hussain Quaid , Yasir Muhammad , Sajjad Muhammad , Shah Liaqat
Published: April 2023

Lignification is a vital function in plants for improving tolerance against stressors. This article presents studies conducted on the relationship of wheat straw lignin with enhanced plant adaptation against lodging and stressors. Herein, we provide a thorough discussion of the chemical structure and lignin composition of straw and its alteration and uses. Lignin plays a critical role in withstanding harsh environments (biotic and abiotic). Resistance to accommodation in wheat also plays a critical role. Lignin can also produce several products, e.g., costly petroleum-based materials and other vital products, such as resins and composites, and new materials, such as biofuels and chemicals. In this study, wheat straw lignification analysis highlighted that lignin formation regulates cellulose and hemicellulose biosynthesis. In addition, the analysis showed considerable encouragement of lignin growth inside wheat straw and the formation of lignin interfaces, as for cellulose and hemicellulose. Wheat straw lignin is an important source of many essential bioactive moieties, particularly lignocelluloses, straw-based biofuels, and various chemicals. We also explored the molecular tools that influence lignin formation in wheat and the significant strides taken in broadening our understanding of nanotechnology tools. This knowledge could assist in the development of advanced wheat cultivars, increase lignin content, and strengthen feedstock efficiency, reducing the impact of other lignin-associated agronomic gains.
Design Criteria for the Construction of Energy Storage Salt Cavern Considering Economic Benefits and Resource Utilization
Authors: Song Huiyong , Zhu Song , Li Jinlong , Wang Zhuoteng , Li Qingdong , Ning Zexu
Published: April 2023

Underground salt caverns have been widely used for oil and gas storage and have attracted increasing attention. The construction design of salt caverns is directly related to the final storage capacity, economic benefits, and resource utilization. However, due to the numerous combinations of multi-stage process parameters involved in the construction design, it is difficult to optimize them individually through indoor experiments and numerical simulations. In this regard, this paper attempts to put forward the basic principles of cavern construction design criteria with economic benefits and resource utilization as indicators. Firstly, 1258 groups of cavern construction process parameters were randomly generated under certain basic rules, including inner tube depth, outer tube depth, oil pad depth, duration, and water injection flow rate, for five direct leaching stages. Then, the cavern capacity, economic benefit, and rock salt resource utilization corresponding to these process parameters were obtained through batch processing using single-well salt cavern leaching simulation software (SSCLS). Finally, the influence laws of the distance between the inner tube and oil pad and lifting heights, and the rates of the inner tube and oil pad on the expected economic benefits and salt resource utilization, are discussed. In the actual project, it is recommended to increase the distance between the inner tube and the oil pad, increase the ratio of oil pad lifting height to duration, and use the appropriate lifting height to obtain greater expected revenue and resource utilization. This work will improve the efficiency and scientificity of cavern construction design, which is of great significance in guiding the construction and design for energy storage in salt caverns.
Coal Is a Priority for Energy Security, until It Is Not: Coal Phase-Out in the EU and Its Persistence in the Face of the Energy Crisis
Authors: Mišík Matúš , Jursová Prachárová Veronika
Published: April 2023

In the wake of the COVID-19 pandemic and the Russian invasion of Ukraine, many countries see coal as the easiest solution to their energy sector challenges, despite the consequences for climate goals. Several countries of the European Union started to re-evaluate their coal policies vis-à-vis the current energy crisis and, although such a change is expected to be short-term in nature, it nevertheless has negative consequences for the Union’s 2050 climate goal. However, most of the EU countries did not revise their phase-out goals. This paper examines Slovakia as a country that embarked on a coal phase-out trajectory only a few years before the pandemic broke out and stayed firmly on this path despite benefits stemming from the continued use of domestic coal. Domestic coal used to be considered a safeguard of energy security in Slovakia, especially after the 2009 gas crisis. However, a decision was made in 2018 to phase out coal by 2023, and this has not changed despite increased focus on domestic energy sources as energy security guarantors during the current energy crisis. This paper explains the decision in favour of a coal phase-out and its support vis-à-vis the energy crisis using the concept of ‘financial Europeanisation’, which stresses the importance of EU funds for the development of the domestic policies of EU member states. While the expected funds serve as a catalyst for the coal phase-out needed to reach climate goals, short-term advantages of revising a coal phase-out were outweighed by long-term benefits provided by EU funds.
Nonlinear Effect of Digital Economy on Urban–Rural Consumption Gap: Evidence from a Dynamic Panel Threshold Analysis
Authors: Zhang Yongqiang , Ma Guifang , Tian Yuan , Dong Quanyao
Published: April 2023

Reducing the disparity in consumption between urban and rural areas, as a critical component in mitigating the economic imbalance between them, holds significant importance in enhancing people’s sense of well-being and achieving collective prosperity. This research investigated the nonlinear impact of the digital economy and its sub-dimensions, including digital industrialization, industrial digitization, and the digital environment, on the urban–rural consumption disparity. We employed a systematic GMM and a dynamic panel threshold regression model and utilized dynamic panel data from 30 provinces in China. Our research reveals that the impact of digital economic development on the urban–rural consumption gap displays an inverted U-shaped nonlinear relationship of widening and then narrowing. This effect is primarily determined by the process of digital industrialization. The digital economy exerts a notable impact on the urban–rural consumption gap, with significant threshold effects identified for the income gap, the education gap, and financial expenditure for livelihoods; these threshold effects exhibit variation across the three sub-dimensions of the digital economy. Further analysis reveals that the digital economy plays a vital role in reducing the disparity between urban and rural hedonic and developmental consumption, while promoting the optimization and upgrading of consumption structure. Upon accounting for regional disparities in urbanization rates, it has been observed that the digital economy’s dampening effect on the urban–rural consumption gap is notably more pronounced in areas with lower rates of urbanization. To more effectively leverage the positive impact of the digital economy on bridging the urban–rural consumption divide, it is recommended that the government accelerate the establishment of a digital environment in rural areas, encourage the integration of digital industries with traditional rural industries, and optimize the investment structure of livelihood-based finance. These measures would help to create a more conducive environment for the digital economy to thrive and could contribute to narrowing the consumption gap between urban and rural areas.
A Highly Condensed Social Fact: Food Citizenship, Individual Responsibility, and Social Commitment
Authors: Bindi Letizia , Belliggiano Angelo
Published: April 2023

The paper is based on the crucial value of food as “a condensed social fact”. The analysis focuses on food narratives, responsible consumption, battles for the food emancipation of subaltern and low-income subjects, and attention to the quality, fairness, and traceability of food products as an expression of individual agency, as well as an expression of public engagement with food democracy/citizenship conflicts and frictions. Preliminarily, the paper moves from a discussion of collective agency on food strategies and representations to a critical approach to food democracy and sustainable society. This public arena for food debates is then confronted with personal behaviors embodying food citizenship in the contemporary scenario of socio-economic and environmental transition. The paper addresses the following sustainable development goals: responsible consumption and production (SDG 12), ending hunger, food security, improved nutrition, sustainable agriculture (SDG 2), and health and well-being (SDG 3). Starting from the democratic/neoliberal dichotomy, the paper will consider food governmentality as a positive alternative to food emancipation and democracy, as well as a personal need and a neo-communitarian political approach opposed to agroindustry and food consumerism and dispossession. Three case studies, all situated in the central–southern Italian region of Molise, will discuss different models of food citizenship and governmentality, as well as the relationship between individual responsibility and desires and collective commitment and perspectives. These issues will be framed within a rural economy paradigm and articulated through an ethnographic methodology: local data collection, emic/ethic representations, participant observation, semi-structured interviews, and focus groups. This long-term observation has been realized in the framework of several projects that were coordinated and developed by the authors, who worked for several years in the regional territory, especially on projects focusing on local/regional/national policies of sustainable rural development and bio-cultural heritage conservation and valorization according to the mission of the research center, which they founded and coordinated over the last seven years. The case studies and discussion allow for some final consideration of the impact of individual and community agencies on the achievement of SDGs, the presence of not exclusively consumeristic and hedonistic behaviors, and the growing attention to ecological concerns being paid food producers and distributors, as well as new forms of rural–urban circularity and entanglements aiming toward greater awareness and democratization of food access, security, and sustainable agriculture.
Spatial Distribution and Controlling Factors of Groundwater Quality Parameters in Yancheng Area on the Lower Reaches of the Huaihe River, Central East China
Authors: Wang Jian , Xu Junli
Published: April 2023

Groundwater samples that were distributed across the Yancheng area in the lower reaches of the Huaihe River were collected from the phreatic aquifer and first confined water layer during the summer of 2016. Using the water quality index, the suitability of the groundwater for drinking and irrigation purposes was systematically evaluated. The controlling factors of solute formation and the causes of water quality deterioration were discussed using the Chadha diagram and the relationship among ions. The results showed that there was a serious lack of excellent- and good-grade groundwater for drinking purposes in the shallow layer. The groundwater was also found to be unsuitable for irrigation, with only approximately 70% being of good quality. The spatial heterogeneity of the water quality was significant, and poor-quality groundwater was found to be distributed discontinuously. The high concentration of alkali metals in the shallow groundwater was found to be due to the weathering of silicate rocks in clay and subclays and the replacement of Ca2+ with Na+ in the surrounding rocks. Additionally, the leaching of residues from the salt industry and marine sediment in historical periods were identified as key factors leading to the scattering of poor-quality groundwater in inland areas. The study found that the shallow groundwater in the study area was not significantly affected by seawater intrusion and human activities. However, signs of human activity, such as agricultural fertilizer and urban sewage, were found to be affecting the “excellent-” and “good-grade” shallow groundwater intended for irrigation purposes.
A Keyword, Taxonomy and Cartographic Research Review of Sustainability Concepts for Production Scheduling in Manufacturing Systems
Authors: Bertolini Massimo , Leali Francesco , Mezzogori Davide , Renzi Cristina
Published: April 2023

The concept of sustainability is defined as composed of three pillars: social, environmental, and economic. Social sustainability implies a commitment to equity in terms of several “interrelated and mutually supportive” principles of a “sustainable society”; this concept includes attitude change, the Earth’s vitality and diversity conservation, and a global alliance to achieve sustainability. The social and environmental aspects of sustainability are related in the way sustainability indicators are related to “quality of life” and “ecological sustainability”. The increasing interest in green and sustainable products and production has influenced research interests regarding sustainable scheduling problems in manufacturing systems. This study is aimed both at reducing pollutant emissions and increasing production efficiency: this topic is known as Green Scheduling. Existing literature research reviews on Green Scheduling Problems have pointed out both theoretical and practical aspects of this topic. The proposed work is a critical review of the scientific literature with a three-pronged approach based on keywords, taxonomy analysis, and research mapping. Specific research questions have been proposed to highlight the benefits and related objectives of this review: to discover the most widely used methodologies for solving SPGs in manufacturing and identify interesting development models, as well as the least studied domains and algorithms. The literature was analysed in order to define a map of the main research fields on SPG, highlight mainstream SPG research, propose an efficient view of emerging research areas, propose a taxonomy of SPG by collecting multiple keywords into semantic clusters, and analyse the literature according to a semantic knowledge approach. At the same time, GSP researchers are provided with an efficient view of emerging research areas, allowing them to avoid missing key research areas and focus on emerging ones.
Effects of ICT Integration in Teaching Using Learning Activities
Authors: Toma Florentina , Ardelean Andreea , Grădinaru Cătălin , Nedelea Alexandru , Diaconu Daniel Constantin
Published: April 2023

Progress in schooling using competence-based teaching for students is a priority in setting up a quality-centered educational process. Thus, using ICT tools as teaching–learning techniques represents an important objective in reaching scholastic performance and the capacity to offer students various experiences in teaching. Starting with an analysis of research on integrating ICT tools in the educational environment, this study is aimed at presenting teaching opportunities for all students, seeing education through the lens of those instruments specific to a secondary school level, referencing the subject of geography. The applied research design includes mixed methods applied to a total of 674 students, based on results received before and after a written evaluation, to determine the level of knowledge of the students. The present study evaluates the learning environment in which a successful and practical integration of ICT tools is anticipated in the teaching and learning process, from the perspective of the comparative measurement of the impact on the tests, resulting from the formative assessment. The conducted experiment and the Google Forms questionnaires suggest, through the degree of involvement of all students, how technology can facilitate the teaching–learning process. The results showed that there are statistically significant differences between the experimental and the control group, and that information and communication technologies (ICT) represent an important tool for improving performance and developing participatory skills, having the ability to provide students with positive results.
Physicochemical Properties and Environmental Effects of Suspended Sediment Particles in the Largest Freshwater Lake, China
Authors: Cui Fang , Wang Hua , Shen Zilin , Li Yuanyuan , Li Siqiong , Tian Xueqi
Published: April 2023

Suspended sediment particles (SSPs) act as a potential source of and sink for aquatic pollution. This study sampled six sites in Poyang Lake in August and November 2019. Changes in the physicochemical properties of SSPs were analyzed using scanning electron microscope energy-dispersive spectrometry (SEM-EDS). The results showed that SSPs consisted mainly of clay and chalk, with an average content of 39.71% and 57.52%, respectively. The average particle size distribution of SSPs in the study area ranged from 5.54 to 15.97 μm and the spatial distribution pattern showed the north lake area (I) > west lake area (II) > east lake area (III). The angle (K) of morphological indicators varied widely, with coefficients of variation between 0.25 and 1.23. Water-flow velocity was negatively correlated with SSP size, while suspended-solid concentration was positively correlated with SSP surface roughness. Morphological parameters, chemical composition, and correlation between each SSP form were analyzed to identify morphological distribution characteristics. Linear regression equations estimated endogenous phosphorus load in zones I, II, and III as 1027.202 mg/kg, 1265.343 mg/kg, and 1013.111 mg/kg respectively. Therefore, we conclude that the morphological differences in particulate matter, the interaction between chemical fractions, and the aqueous environment affecting the distribution of phosphorus fugitive forms, may contribute to endogenous lake pollution. These results are essential for revealing the intrinsic relationship between SSP physicochemical properties and lake eutrophication and studying other water–sediment interface processes of lake pollutants.
Participatory Inquiries That Promote Consideration of Socio-Scientific Issues Related to Sustainability within Three Different Contexts: Agriculture, Botany and Palaeontology
Authors: McGregor Debra , Frodsham Sarah , Deller Clarysly
Published: April 2023

The involvement of students in dramatised inquiries, through participatory activity, offers opportunities to act in-role as scientists. The inquiries can ‘set-the-scene’, provide context and challenges for students to consider possibilities within and beyond everyday life. This approach can engage students in thinking about sustainability and developing citizenship competencies, such as thinking scientifically and critiquing ideas, interrogating evidence and assessing the validity of information, as well as decision making and problem solving. In this paper, adopting stories from the history of science is shown to provide rich, authentic contexts that engage students imaginatively and collaboratively in addressing past, present and future socio-scientific issues. To demonstrate how the approach can be adapted we drew on the work of three scientists: an agriculturalist; a botanist and a palaeontologist. Their scientific work informed the learning activities of several primary science lessons (with students aged 9–10). The agricultural activities were informed by the work of George Washington Carver and were related to improving soil quality through crop rotation as well as thinking about the diversity of food and other products that can be produced from plants. The botanically informed activities promoted understanding about processes linked to maintaining species diversity. These drew on the work of Marianne North, a Victorian botanical artist, noted for her detailed plant observations. The final socio-scientific context was related to the work of Mary Anning, a pioneering 19th century palaeontologist, who made significant fossil discoveries that contributed to the understanding of geology and evolution. Interactive and participatory activities, informed by the lives and work of these scientists, were designed to engage students in socio-scientific inquiry-based learning through a drama-based pedagogy. These dramatised inquiries promoted the development of scientific citizenship competencies. Scrutiny of data collected through multiple methods suggested that, by extending opportunities for learners to participate in these dramatised lessons, understanding sustainability became more salient for the students. Outcomes suggest several distinctive affordances offered by dramatisation when supporting understanding about sustainability and the development of scientific citizenship.
Personalized Education for Sustainable Development
Authors: Zdravkova Katerina
Published: April 2023

Progress in eradicating poverty, hunger and pollution by promoting better health, well-being and quality education has begun to weaken due to the pandemic, military conflicts and climate change. There is an urgent need to act decisively and efficiently in order to reduce the frightening dimension of the crisis and return sustainable development indicators to an upward trend. After examining sustainable development goals and indicators and their progress, this paper introduces four focal activity clusters. They can be fulfilled through effective learning, starting with local educational campaigns, well-designed educational initiatives, and even modifying curricula aimed at sustainable development. Several approaches can contribute to achieving the goals, primarily transformative and personalized learning. After comparing them in the light of sustainable development, preference is given to personalized learning. It faces many challenges related to the data collection and processing of, factionalism of, and impossibility of accessing differently abled people. These challenges are further amplified by remote teaching and learning. Recommendations on how to overcome them and how to organize educational interactions on a micro, mezzo and macro level are presented in the conclusion of the paper.
An Analysis of an Ecological–Economic Model of Asian Elephant Population Development under the Influence of Human Disturbance
Authors: Huang Wei , Chen Wenhui
Published: April 2023

The population development of Asian elephants (Elephas maximus) has been greatly affected by the intensification of human activities. In this study, development of the Asian elephant population under the influence of human disturbance was analyzed logically, with expansion of the rubber forest area as the main influencing factor. The ecological–economic model of Asian elephant population development was constructed using the logical analysis method, the population growth model and the integrated environmental–economic control model. The results are as follows: (1) Theoretically, the ecological–economic model could be applied to the analysis of wildlife conservation and regulation and management policies; (2) The data show that in 2016, the intrinsic growth rate of Asian elephants in Xishuangbanna was 0.0216 head/day, which has a strong proliferation capacity, meaning the population will continue to grow under natural conditions. However, at present, the population development of Asian elephants has been negatively affected by human interference, which has reduced the population growth rate of Asian elephants to 0.0193 head/day, and this impact has a tendency to intensify; (3) From 2004 to 2016, the investment rate of Asian elephants increased by 0.182, while the anti-interference protection rate of Asian elephants decreased by 0.227. The overall development trend of Asian elephants was from equilibrium point one (golden age) to equilibrium point two (dark age).
How Does Perceived Value Affect Cooperative Initiatives in Agricultural Organizations: Evidence from 247 Agri-Industrialized Unions
Authors: Li Hanyue , Zhang Runqing
Published: April 2023

In China, an effective form of agricultural organization called an agri-industrialized union (AIU) has been on the rise and is recognized as making a great contribution to rural revitalization. However, individual AIUs appear to be conducted in different ways during their development. Some are successfully operated by active members in cohesive combinations, while some fail because of disconnection and instability. The purpose of this study is to encourage all members to take initiative and to act cooperatively to ensure high-quality resource usage in AIUs. Based on the theory of planned behavior (TPB) and the theory of perceived value, a structural equation model was used to examine the main factors affecting members’ willingness to cooperate in AIUs in Hebei Province. The data collected from a survey of 247 AIUs indicated that behavioral attitudes and subjective norms have a direct impact on cooperative initiatives. Perceived behavioral control indirectly affects cooperative initiatives. Perceived management ability influences subjective norms, while perceived interest–risk influences behavioral attitudes and perceived behavioral control, especially in hierarchical governance groups. The influences of behavioral attitudes, perceived behavioral control, and subjective norms are stronger in mixed-governance groups. The results of this research can provide recommendations for policymaking that may help to ensure the stable development of AIUs and rural development.
Promising Emerging Technologies for Teaching and Learning: Recent Developments and Future Challenges
Authors: Almufarreh Ahmad , Arshad Muhammad
Published: April 2023

As time goes on and the number of people who use information and communication technology (ICT) grows, emerging technologies are receiving a lot of attention from academics, researchers, and users. Emerging technologies are changing more quickly than ever, and it is important to start building skills early in education by using the right examples to teach and learn about digital citizenship. New pedagogies support individual teaching and learning methodologies for knowledge acquisition and self-directed learning. Hundreds of digital education tools have been developed to increase student autonomy, enhance academic process management, promote collaboration, and improve communication between teachers and students. This article examines the current state of emerging technologies from a variety of educational viewpoints, highlights a few of them, and discusses both their established and potential educational benefits. Additionally, it offers in-depth debates on recent developments and future challenges from a wide range of perspectives. The analysis focuses on peer-reviewed research articles published in well-renowned publications databases over the last 8 years, drawing upon a bibliometric analysis using VOSviewer. The results of this study are also anticipated to serve as a substantial impetus for other universities and colleges worldwide to utilize innovatively and revolutionized technology for better academic performance.
A Study of GNSS-IR Soil Moisture Inversion Algorithms Integrating Robust Estimation with Machine Learning
Authors: Ding Rui , Zheng Nanshan , Zhang Hao , Zhang Hua , Lang Fengkai , Ban Wei
Published: April 2023

Soil moisture monitoring is widely used in agriculture, water resource management, and disaster prevention, which is of great significance for sustainability. The global navigation satellite system interferometric reflectometry (GNSS-IR) technology provides a supplementary method for soil moisture monitoring. However, due to the quality of the signal-to-noise ratio (SNR) measurements and the complex surface environment, inevitable outliers in multipath interference signal metrics (amplitude, frequency, and phase) were used as modeling variables to inverse GNSS-IR soil moisture. Besides, it is hard to use the univariate model to comprehensively analyze the relationship between the various factors, due to the poor fitting effect and weak generalization ability of the model. In this paper, the minimum covariance determinant (MCD) robust estimation and machine learning algorithms are adopted. The MCD robust estimation can eliminate outliers of the multipath signal metrics and machine learning algorithms, including the back propagation neural network (BPNN), Gaussian process regression (GPR), and random forest (RF), and can comprehensively establish nonlinear GNSS-IR soil moisture inversion models using multipath interference signal metrics. Moreover, the study of the modeling parameter selection for the three machine learning algorithms and the inversion results for single satellite and all satellites are also carried out to make the algorithms more generalizable. The results show that the correlation coefficients (R) and the root mean square error (RMSE) of the machine learning models for all satellite tracks are increased by 4.3~86.6% and reduced by 2.8~30%, respectively, compared with the MCD multiple regression model. The RF model with 80 decision trees and 1 node shows the clearest improvement. The total model using all satellite data has more generalization ability than the single satellite model but causes some loss of accuracy.
Peaking Dynamics of the Production Cycle of a Nonrenewable Resource
Authors: Perissi Ilaria , Lavacchi Alessandro , Bardi Ugo
Published: April 2023

We use a system dynamics model to analyse the cycle of production of a nonrenewable natural resource, with a specific interest in crude oil. This subject has been empirically studied for a long time. However, modelling studies able to correlate the peaking with the parameters of the system have been very rare, and only recently proposed. In the present paper, we examine the timing of the peaking mainly as a function of the energy return for energy invested (EROI). The model provides approximate formulas for evaluating the peak time and “rules of thumb” that are useful for understanding the peaking phenomenon in the exploitation of natural resources. It shows that the peaking of the production curve occurs at a time that is inversely proportional to the EROI of the process at the start of the cycle.
Reinventing a Rural Area: A Case Study into Cultural Festivals in Oldambt, The Netherlands
Authors: Koreman Maarten C. J.
Published: April 2023

The Oldambt area, in the northeast of the Netherlands, has recently suffered from depopulation and a negative image. However, four high-quality cultural festivals have been developed in or moved towards the area during the last decade. The festivals have different organisational models. This paper assesses how they contribute to rural regeneration through semi-structured interviews with stakeholders around the festivals and local youth. It adds to the existing literature by introducing the concept of rural regeneration, stemming from neo-endogenous rural development, into festival research and by conducting multiple case studies in one area. The paper investigates the festivals’ local legitimacy, rootedness, and ability to create interconnectedness. The findings suggest that the festivals are locally supported, use local resources, and benefit the area, notwithstanding their organisational model. The festivals also help to establish networks within and outside of Oldambt, and there is thus a positive effect on regeneration. The recent more positive developments in Oldambt may be related to the organisation of the festivals.
Research on Envelope Thermal Performance of Ultra-Low Energy Rural Residential Buildings in China
Authors: Deng Qinqin , Zhang Shengnan , Shan Ming , Li Ji
Published: April 2023

Rural energy consumption plays an important role in energy consumption due to the improvement of rural residents’ living quality requirements in China. Ultra-low energy rural residential buildings are proposed to decrease rural energy consumption. First of all, this paper aims to provide the definition of ultra-low energy rural residential buildings, which is to reduce 50% of the building energy consumption of the rural residential benchmark building according to the Chinese standard for energy efficiency of rural residential buildings. Secondly, this paper presents the heat transfer coefficients of building envelopes of ultra-low energy rural residential buildings in the severe cold zone, cold zone and hot summer and cold winter zone in China. Based on optimized design and simulation analysis, the heat transfer coefficients of building envelopes are determined by the construction cost, energy efficiency and retrofit feasibility. Thirdly, the suitable combination of a high-performance external wall and internal wall is recommended based on carbon emission and cost efficiency. As an achievement, a technical specification for ultra-low energy rural buildings has been proposed by the China Academy of Building Research. It is beneficial to design ultra-low energy rural residential buildings in China and other countries.
Industrial Machinery Components Classification: A Case of D-S Pooling
Authors: Batool Amina , Dai Yaping , Ma Hongbin , Yin Sijie
Published: April 2023

Industries are increasingly shifting towards unmanned and intelligent systems that require efficient processing and monitoring of structures across various applications, ranging from machine manufacturing to waste disposal. In order to achieve the goal of intelligent processing, it is crucial to accurately classify and differentiate various components and parts. However, existing studies have not focused on simultaneously classifying electro-mechanical machinery components. This poses a challenge as these components, including capacitors, transistors, ICs, inductors, springs, locating pins, washers, nuts, and bolts, exhibit high intra- and inter-class similarity, making their accurate classification a tedious task. Furthermore, many of these components have symmetrical shapes but are asymmetrical among different classes. To address these challenges, this article introduces a new double-single (D-S) pooling method that focuses on the higher resemblance of seventeen electro-mechanical component classifications with minimum trainable parameters and achieves maximum accuracy. The industrial machine component classification model (IMCCM) consists of two convolutional neural network (CNN) blocks designed with a D-S pooling method that facilitates the model to effectively highlight the differences for the higher similar classes, and one block of grey-level co-occurrence matrix (GLCM) to strengthen the classification outcome. The extracted fused features from these three blocks are then forwarded to the random forest classifier to distinguish components. The accuracy achieved by this proposed model is 98.15%—outperforming the existing state of the arts (SOTAs) models, and has 141,346 trainable parameters– hence, highly effective for industrial implementation.