bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance of 3D-Printed Beams and Slabs Using Self-Sensing Cementitious Composites and DIC Method
Authors: Li Zhuming , Aslani Farhad
Published: October 2023

This paper aims to explore the structural performance of 3D-printed and casted cement-based steel-reinforced concrete beams and one-way slabs incorporating short carbon fibre and activated carbon powder, which have been shown to enhance concrete’s flexural strength and reduce its electrical resistivity. The samples are cast and printed in 250 × 325 × 3500 mm beams and 150 × 400 × 3500 mm one-way slabs and mechanical, electrical, and piezoresistivity properties were measured. This length of beams and one-way slabs with rebars have been considered as they can magnify the flexural and cracking behaviour and make them easier to be monitored and analysed. The samples were loaded up to 80% of maximum stress. Crack propagation and strain was assessed using the 2D digital image correlation (DIC) method. The results compared samples under continuously increasing loads between 3D-printed and cast samples. The 3D-printed composites had a better piezoresistive response due to the enhanced anisotropic behaviour. DIC analysis illustrated similar results among different samples, while 3D-printed blocks had lower cracking performance due to the horizontal case fracture in lower stress.
Quantitative Thermal Stimulation Using Therapeutic Ultrasound to Improve Cerebral Blood Flow and Reduce Vascular Stiffness
Authors: Yi Kyung-Kwon , Park Chansol , Yang Jiwon , Lee Yeong-Bae , Kang Chang-Ki
Published: October 2023

It is important to improve cerebrovascular health before the occurrence of cerebrovascular disease, as it has various aftereffects and a high recurrence rate, even with appropriate treatment. Various medical recommendations for preventing cerebrovascular diseases have been introduced, including smoking cessation, exercise, and diet. However, the effectiveness of these methods varies greatly from person to person, and their effects cannot be confirmed unless they are practiced over a long period. Therefore, there is a growing need to develop more quantitative methods that are applicable to the public to promote cerebrovascular health. Thus, in this study, we aimed to develop noninvasive and quantitative thermal stimulation techniques using ultrasound to improve cerebrovascular health and prevent cerebrovascular diseases. This study included 27 healthy adults in their 20s (14 males, 13 females). Thermal stimulation using therapeutic ultrasound at a frequency of 3 MHz was applied to the right sternocleidomastoid muscle in the supine posture for 2 min at four intensities (2.4, 5.1, 7.2, and 10.2 W/cm2). Diagnostic ultrasound was used to measure the peak systolic velocity (PSV), heart rate (HR), and pulse wave velocity (PWV) in the right common carotid artery (CCA), and the physiological changes were compared between intervention intensities. Compared to pre-intervention (preI), the PSV showed a significant increase during intervention (durI) at intensities of 7.2 W/cm2 and 10.2 W/cm2 (p = 0.010 and p = 0.021, respectively). Additionally, PWV showed a significant decrease for post-intervention (postI) at 7.2 W/cm2 and 10.2 W/cm2 (p = 0.036 and p = 0.035, respectively). However, the HR showed no significant differences at any of the intensities. The results demonstrate that an intervention at 3 MHz with an intensity of 7.2 W/cm2 or more can substantially increase cerebral blood flow and reduce arterial stiffness. Therefore, the use of therapeutic ultrasound of appropriate intensity is expected to improve the cerebral blood flow and reduce vascular stiffness to maintain cerebral blood flow at a certain level, which is closely related to the prevention and treatment of cerebrovascular diseases, thereby improving cerebrovascular health.
Organic Electronics—Microfluidics/Lab on a Chip Integration in Analytical Applications
Authors: Shinar Ruth , Shinar Joseph
Published: October 2023

Organic electronics (OE) technology has matured in displays and is advancing in solid-state lighting applications. Other promising and growing uses of this technology are in (bio)chemical sensing, imaging, in vitro cell monitoring, and other biomedical diagnostics that can benefit from low-cost, efficient small devices, including wearable designs that can be fabricated on glass or flexible plastic. OE devices such as organic LEDs, organic and hybrid perovskite-based photodetectors, and organic thin-film transistors, notably organic electrochemical transistors, are utilized in such sensing and (bio)medical applications. The integration of compact and sensitive OE devices with microfluidic channels and lab-on-a-chip (LOC) structures is very promising. This survey focuses on studies that utilize this integration for a variety of OE tools. It is not intended to encompass all studies in the area, but to present examples of the advances and the potential of such OE technology, with a focus on microfluidics/LOC integration for efficient wide-ranging sensing and biomedical applications.
Time-Lapse GPR Measurements to Monitor Resin Injection in Fractures of Marble Blocks
Authors: Zanzi Luigi , Izadi-Yazdanabadi Marjan , Karimi-Nasab Saeed , Arosio Diego , Hojat Azadeh
Published: October 2023

The objective of this study is to test the feasibility of time-lapse GPR measurements for the quality control of repairing operations (i.e., injections) on marble blocks. For the experimental activities, we used one of the preferred repairing fillers (epoxy resin) and some blocks from one of the world’s most famous marble production area (Carrara quarries in Italy). The selected blocks were paired in a laboratory by overlapping one over the other after inserting very thin spacers in order to simulate air-filled fractures. Fractures were investigated with a 3 GHz ground-penetrating radar (GPR) before and after the resin injections to measure the amplitude reduction expected when the resin substitutes the air. The results were compared with theoretical predictions based on the reflection coefficient predicted according to the thin bed theory. A field test was also performed on a naturally fractured marble block selected along the Carrara shore. Both laboratory and field tests validate the GPR as an effective tool for the quality control of resin injections, provided that measurements include proper calibration tests to control the amplitude instabilities and drift effects of the GPR equipment. The method is accurate enough to distinguish the unfilled fractures from the partially filled fractures and from the totally filled fractures. An automatic algorithm was developed and successfully tested for the rapid quantitative analysis of the time-lapse GPR profiles collected before and after the injections. The whole procedure is mature enough to be proposed to the marble industry to improve the effectiveness of repair interventions and to reduce the waste of natural stone reserves.
Experimental Evaluation of a Hybrid Sensory Feedback System for Haptic and Kinaesthetic Perception in Hand Prostheses
Authors: Sariyildiz Emre , Hanss Fergus , Zhou Hao , Sreenivasa Manish , Armitage Lucy , Mutlu Rahim , Alici Gursel
Published: October 2023

This study proposes a new hybrid multi-modal sensory feedback system for prosthetic hands that can provide not only haptic and proprioceptive feedback but also facilitate object recognition without the aid of vision. Modality-matched haptic perception was provided using a mechanotactile feedback system that can proportionally apply the gripping force through the use of a force controller. A vibrotactile feedback system was also employed to distinguish four discrete grip positions of the prosthetic hand. The system performance was evaluated with a total of 32 participants in three different experiments (i) haptic feedback, (ii) proprioceptive feedback and (iii) object recognition with hybrid haptic-proprioceptive feedback. The results from the haptic feedback experiment showed that the participants’ ability to accurately perceive applied force depended on the amount of force applied. As the feedback force was increased, the participants tended to underestimate the force levels, with a decrease in the percentage of force estimation. Of the three arm locations (forearm volar, forearm ventral and bicep), and two muscle states (relaxed and tensed) tested, the highest accuracy was obtained for the bicep location in the relaxed state. The results from the proprioceptive feedback experiment showed that participants could very accurately identify four different grip positions of the hand prosthesis (i.e., open hand, wide grip, narrow grip, and closed hand) without a single case of misidentification. In experiment 3, participants could identify objects with different shapes and stiffness with an overall high success rate of 90.5% across all combinations of location and muscle state. The feedback location and muscle state did not have a significant effect on object recognition accuracy. Overall, our study results indicate that the hybrid feedback system may be a very effective way to enrich a prosthetic hand user’s experience of the stiffness and shape of commonly manipulated objects.
A Feasibility Study on Extension of Measurement Distance in Vision Sensor Using Super-Resolution for Dynamic Response Measurement
Authors: Cho Dooyong , Gong Junho
Published: October 2023

The current civil infrastructure conditions can be assessed through the measurement of displacement using conventional contact-type sensors. To address the disadvantages of traditional sensors, vision-based sensor measurement systems have been derived in numerous studies and proven as an alternative to traditional sensors. Despite the benefits of the vision sensor, it is well known that the accuracy of the vision-based displacement measurement is largely dependent on the camera extrinsic or intrinsic parameters. In this study, the feasibility study of a deep learning-based single image super-resolution (SISR) technique in a vision-based sensor system is conducted to alleviate the low spatial resolution of image frames at long measurement distance ranges. Additionally, its robustness is evaluated using shaking table tests. As a result, it is confirmed that the SISR can reconstruct definite images of natural targets resulting in an extension of the measurement distance range. Additionally, it is determined that the SISR mitigates displacement measurement error in the vision sensor-based measurement system. Based on this fundamental study of SISR in the feature point-based measurement system, further analysis such as modal analysis, damage detection, and so forth should be continued in order to explore the functionality of SR images by applying low-resolution displacement measurement footage.
“You Don’t Want to Be Perceived as Wild and Unruly”: How Ethnic Minority Women Experience and Negotiate Their Autonomy within Honor-Related Contexts
Authors: Ahmad Menal
Published: October 2023

Within honor-related contexts, women’s appearances, actions, and life choices are closely tied to the honor of the entire family. As a result, women who opt to deviate from prevailing feminine honor codes are subject to violence as a means of restoring the family’s good name. Based on the life stories of fourteen Dutch ethnic minority women who deviated from feminine honor codes, this study investigates how women experience their autonomy as a process within their social context. Rather than analyzing this process through a binary conception of autonomy (i.e., agency/coercion), this study highlights women’s experiences through a relational approach to autonomy. In doing so, this study uncovers three overarching themes: (1) honor codes are enforced implicitly through expectations surrounding the role of “the honorable daughter/wife”, and explicitly through a shared religious and/or ethnic identity, (2) women detach themselves from honor codes either by strategically renegotiating honor codes or after experiencing a turning point that triggers an immediate process towards detachment from honor codes, and (3) women’s decision-making processes are accompanied with health concerns caused by lingering guilt, social shame, and isolation.
Isolation and Characterization of Culturable Osmotolerant Microbiota in Hypersaline and Hypergypsic Soils as New Treatment for Osmotic Stress in Plants
Authors: Gil Tatiana , Teixeira Raquel , Sousa André , d’Oliveira Palmeiro Maria Alice , Cruz Coimbra de Matos Alice , Niza Costa Marla , Ferrer María Victoria , Rodrígues dos Santos Ana Sofía , Sequero López Cristina , Rebelo Romão Inês , Vílchez Juan Ignacio
Published: October 2023

Saline and gypsic soils impede or condition the establishment of farms in many regions worldwide. Stress caused by the accumulation of sodium or calcium ions in the soil drastically limits plant growth and is a limiting factor in the production of many crops. For this reason, saline and gypsic soils were preferentially exploited for mineral extraction. However, nowadays, they can be a source of new biotechnological tools to help in the osmotic stress to which some crops are exposed. In these environments, despite being traditionally characterized by their low biodiversity, we can find well-adapted microbiota that may be able to interact with plants to deal with different environmental stresses. These mechanisms may consist of a very important contribution to the development of new osmotic stress-dealing bioinoculants. The present study sought to elucidate the diversity of the cultivable population of such environments and use them as regulators of soil nutrients and stress-relieving symbionts in plants under osmotic stress. Among the candidate strains selected to cover more scenarios, we found that the strains Stutzerimonas stutzeri A38 and Bacillus pumilus A49 were able to increase root size under osmotic stress in Medicago sativa and Medicago polymorpha plants. Moreover, Peribacillus frigoritolerans A70 and Bacillus licheniformis A46 also enhanced the performance in M. polymorpha, showing interesting potential for a future use in wasteland use for production to livestock feeding or other relevant industries.
Sedimentary Microfacies Types and Patterns of Chang 6 Member of Triassic Yanchang Formation in the Dalugou Area of Jing’an Oilfield in Ordos Basin, China
Authors: Zheng Jiayu , Wen Zhigang , Wu Chenjun
Published: October 2023

The sixth member of the Triassic Yanchang Formation (Chang 6 member) in the Dalugou area of the Jing’an Oilfield in the Ordos Basin is a typical ultra-low-permeability lithological reservoir. The Dalugou area has achieved some development progress in the past few years. With the development of the Chang 6 member in the Dalugou area, a better understanding of the sedimentary microfacies and depositional patterns is needed for precise oil development. The purpose of the study of the reservoir description is to understand the reservoir more accurately and provide a solid geological basis for the adjustment of the development strategy of the Chang 6 reservoir. The Chang 6 member of the Triassic Yanchang Formation in the Dalugou area of the Jing’an Oilfield belongs to the subfacies of the delta front, and the reservoir in the study area is mainly the underwater distributary channel deposition. There are two main depositional patterns in the study area: the dendritic sandstone depositional pattern and the lobate sandstone depositional pattern. The study on the sedimentary types and patterns of the Chang 6 member of the Triassic Yanchang Formation in the Dalugou Area of the Jing’an Oilfield can provide significant information for the evaluation of reservoir characterization. Furthermore, the heterogeneity of the Chang 6 reservoir under various depositional patterns has an important influence on oil enrichment.
Multi-Criteria Decision Analysis to Evaluate Sustainability and Circularity in Agricultural Waste Management
Authors: Lombardi Patrizia , Todella Elena
Published: October 2023

Agriculture is a major contributor to global anthropogenic emissions, such as waste production and greenhouse gases. In order to reduce these negative impacts, a circular economy should be applied to agriculture waste management. Processes for evaluating treatment and valorization options are fundamental to the implementation of long-term, economically viable, ecologically sound, and socially acceptable policies and practices. In this field, multi-criteria decision analysis methods (MCDAs) can offer a holistic perspective on the decision-making processes. This study deeply explores this area of research by conducting an extensive and critical review of the studies that have used MCDA approaches to support agricultural waste management. The aim is to better understand how MCDA methods have been applied (in an integrated manner or as complementary approaches) and how stakeholders have been involved. The research conducted underlines how MCDAs are now widely used to support decision-making in this area, as well as being increasingly applied in multi-methodologies. This study is part of an ongoing Next-Generation-EU-integrated, large-scale, multi-disciplinary research program, The National Research Centre for Agricultural Technologies.
Comprehensive Analysis of PM1 Composition in the Eastern Indo-Gangetic Basin: A Three-Year Urban Study
Authors: Das Sujit , Roy Anamika , Masiwal Renu , Mandal Mamun , Popek Robert , Chakraborty Monojit , Prasad Dinesh , Chyliński Filip , Awasthi Amit , Sarkar Abhijit
Published: October 2023

Particulate matter (PM) pollution poses a severe threat to the environment and health worldwide. This study aimed to evaluate the mass concentration, physicochemical characteristics, and emission sources of aerodynamic diameters of ≤1 µm (PM1) within an urban sprawl situated in the eastern Indo-Gangetic basin over three years (2017–2019). The study encompassed the monitoring of PM1 using an ambient PM1 sampler; physicochemical characteristics were determined through scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and inductively coupled plasma-optical emission spectrometry (ICP-OES). Possible emission sources were analysed through principal component analysis (PCA) and enrichment factor (EF) analyses. The results showed that the PM1 concentrations were consistently high throughout the research period, even exceeding the national standards for PM2.5 and PM10, especially during the post-monsoon period. Significant seasonal fluctuations were confirmed by the elemental and inorganic ion analyses, highlighting the dominance of elements like Al, Ca, Fe, K, and Mg and inorganic ions like NH4+, SO42−, and NO3−. Vehicular exhaust and non-exhaust (47%), sea salt and biomass burning (26%), and industrial activities (10.3%) are the dominant sources of PM1. Therefore, the findings are thought-provoking and could inspire policymakers to formulate reduction policies in India.
The Impact of Land Use/Cover Change on Ecological Environment Quality and Its Spatial Spillover Effect under the Coupling Effect of Urban Expansion and Open-Pit Mining Activities
Authors: Liu Haobei , Wang Qi , Liu Na , Zhang Hengrui , Tan Yifei , Zhang Zhe
Published: October 2023

Suburban open-pit mining concentration areas are both the frontline of urban expansion and the main battlefield in mineral resource development. These dual forces have resulted in significant land use/cover changes (LUCC), which play a crucial role in determining the ecological environment quality (EEQ). However, research examining how LUCC affects EEQ under the coupled impact of these two development events is currently lacking. In this study, the response of EEQ to LUCC was evaluated using Landsat images from 2000, 2010, and 2020 for the southern suburban open-pit mining concentration area in Jinan City. A relative contribution index was used to address the ecological and environmental effects of non-dominant land use/cover types, and the impact of LUCC on EEQ and its spatial spillover effects were revealed by also carrying out a buffer zone analysis. The findings of this study indicate that: (1) the dominant land use/cover types that influence the EEQ spatial pattern are farmland, grassland, and construction land. Among them, the area of farmland was the largest, with more than 1800 km2. Changes in non-dominant land use/cover types to mining land and mine rehabilitation made the most significant relative contribution to the changes in EEQ, i.e., 0.0735 and 0.0184, respectively. (2) The transformation of farmland into construction land and mining land and woodland into mining land was shown to exacerbate the deterioration of the EEQ in the study area, with a deterioration area of 1367.54 km2 and spatial spillovers of up to 1000 m. (3) Returning farmland to woodland and grassland, as well as returning mine rehabilitation, were found to be the main factors contributing to the improvement of EEQ in the study area, with an improvement area of 1335.67 km2 and spatial spillover extending from 500 to 800 m. (4) Nevertheless, uneven changes in land use/cover continue to aggravate the agglomerative effect of EEQ deterioration. Further refinement and enhancement of the methods and standards of ecological governance are urgently needed to counterbalance the uneven spatial spillover effects between ecological degradation and improvement. This study provides a scientific reference for the promotion of ecological protection and sustainable development in mining cities.
Spatial Distribution of Pollutants and Risk Assessment of Heavy Metals in Farmland Groundwater around a Traditional Industrial Park—A Case Study of Shifang City, Southwestern China
Authors: Zhang Yibo , Yu Yue , An Guanping , Huang Tao , Huang Junhan
Published: October 2023

In this paper, the groundwater environment in the farmland area around a traditional industrial park in Shifang City, southwest China, was taken as the research object. Geostatistical methods with GIS technology were adopted to analyze the spatial distribution of conventional pollutants and heavy metals in groundwater and to evaluate potential ecological risks. Chemical oxygen demand (CODMn) and ammonia nitrogen (NH3-N) distributions showed poor continuity and apparent spatial differentiation, which were primarily attributed to intensive anthropogenic activities (e.g., industrial discharges). The total relative hardness of (TH), SO42−, and Cl− were uniformly affected by external factors, with little spatial differentiation. Concentrations of total phosphorus (TP), TH, SO42−, and Cl− followed an approximately normal distribution; the peak values of detected concentrations appeared in the frequency distribution range, while CODMn and NH3-N did not. Groundwater showed enrichment for various heavy metals, mainly Zn and Cu, with apparent spatial differentiation in Cr and Cu, consistent with external interference. The correlation coefficients of Cr–Cu and Cu–Pb were 0.693 and 0.629 (p < 0.01), respectively, indicating similar pollution sources. The single-factor pollution index for groundwater was Ni > Pb > Mn > Zn > Cu > Cr. Cu had a moderate potential ecological risk. The six heavy metals’ average integrated potential ecological risk index (RI) revealed that mild pollution accounted for 96.2% of the investigation area. Overall, the traditional industrial park poses a mild ecological risk to the shallow groundwater in the surrounding farmland.
Dynamic Simulation Model of Channel Leakage Based on Multiple Regression
Authors: Ma Jianqin , Yang Jiangshan , Hao Xiuping , Cui Bifeng , Yang Shuoguo
Published: October 2023

Aiming at the problem that the existing channel leakage calculation methods generally ignore the dynamic changes of influencing factors, which leads to a large calculation error, this study attempts to utilize the machine learning method to accurately calculate the channel leakage loss under the dynamic changes in the influencing factors. By using the machine learning method to analyze the impact of dynamic changes in the flow rate and soil moisture content over time on the channel leakage loss in the water transmission process and quantify the impact of the selected factors on the leakage loss, a dynamic simulation model of the multi-parameter channel leakage loss was constructed, and a test was carried out in the irrigation area to verify the accuracy of the model. The test results are as follows: the actual leakage loss of the U1 channel is 1094.03 m3, the simulated value of the model is the 1005.24 m3, and the error between the simulated value and the measured value is 8.12%; the total leakage of the U2 channel is 1111.24 m3, the simulated value of the model is 1021.1 m3, and the error between the simulated value and the measured value is 6.31%. The experimental results show that the use of machine learning to construct a dynamic simulation model of channel leakage loss under the comprehensive consideration of the dynamic change in influencing factors over time has a better effect, and the calculation accuracy is high.
Identification and Reduction of Product Carbon Footprints: Case Studies from the Austrian Automotive Supplier Industry
Authors: Rüdele Kai , Wolf Matthias
Published: October 2023

Greenhouse gas (GHG) emissions from human activities have climbed significantly above pre-pandemic levels and have reached record highs that unequivocally accelerate global warming. Industry has a significant impact on climate change, emitting at least 21% of global GHGs and making little overall progress toward its reduction until now. Reducing industry’s emissions requires coordinated action along the value chains in order to promote mitigation options, such as energy and material efficiency, circular material flows, and transformative changes within production processes. This article is the first evaluation of GHG emissions generated during the manufacturing of vehicle components by Austrian companies. For this, the authors analyzed three different products of automotive suppliers according to the methodology of ISO 14067. Despite previous efforts toward an environmentally compatible fabrication, additional and significant reduction potentials were identified. These measures for product carbon footprint (PCF) reduction included the sourcing of low-carbon materials (which are already available on the market), more extensive use of renewable energy, and changes towards more resource efficient manufacturing processes and machinery. Depending on the materials used, the PCF can be reduced by up to 80%. The findings serve to prepare for future PCF reporting regulations and illustrate reduction potentials to achieve future market advantages, especially when PCFs become an awarding criterion.
The Effects of Local Government Expenditures on Carbon Dioxide Emissions: Evidence from Republic of Korea
Authors: Oh Juhyun
Published: October 2023

This study analyzes the direct and indirect effects of local government expenditure for air quality on CO2 emissions using a two-stage dynamic panel model. The results of the first-stage empirical analysis show that local government expenditure for air quality has a positive effect on per-capita GRDP. In the second-stage empirical analysis, an inverse U-shaped relationship between the per-capita GRDP and CO2 emissions is observed. The average direct and indirect effects of local government expenditure for air quality on CO2 emissions indicate that local government expenditure directly reduces CO2 emissions, while it indirectly increases CO2 emissions through regional economic growth. However, the direct effect is found to be greater than the indirect effect, and the total effect indicates that local government expenditure for air quality reduces CO2 emissions. Furthermore, the results demonstrate significant regional disparities in both the direct and indirect effects, emphasizing the pivotal role of tailored air-related expenditure policies in relation to regional economic growth.
Interpersonal Behavior, Basic Psychological Needs, Motivation, Eating Behavior, and Body Image in Gym/Fitness Exercisers: A Systematic Review
Authors: Salvador Rogério , Monteiro Diogo , Rebelo-Gonçalves Ricardo , Jiménez-Castuera Ruth
Published: October 2023

Background: Body image seems to be a determining factor in the behavior and satisfaction of the basic psychological needs of exercise practitioners in gyms and fitness centers, and may influence motivation, interpersonal behavior, and eating behavior. This review aims to examine possible patterns between the variables under study in a gym/fitness context, specifically considering if body image perception has a determinant factor. Methods: Web of Science, PubMed, SCOPUS, and Psycnet were consulted and only data published between 2007 and 2021 were considered in the present review. After an initial search of 1373 records, a total of 6 were considered eligible for a detailed analysis after checking for the inclusion and exclusion criteria. Results: There is a positive relationship between body image dissatisfaction and less self-determined forms of motivation, as well as the adoption of less healthy eating behaviors. Younger participants have higher levels of body image dissatisfaction and unhealthy eating behaviors. Conclusions: Body image dissatisfaction leads to less self-determined forms of motivation for exercise in the context of gyms and fitness centers. On the other hand, a negative perception of body image can also lead to sustained patterns of less regulated forms of exercise and less healthy eating behaviors.
Unleashing the Potentials of Flexible Education with Pedagogical and Technological Innovations
Authors: Yang Harrison Hao , Li Richard Chen , Cheung Simon K. S. , Kwok Lam For
Published: October 2023

The COVID-19 global pandemic had a profound impact on the education sector, forcing many educational institutions worldwide to adapt to new modes of teaching and learning rapidly [...]
Education for Sustainability—Some Bibliometric Insights
Authors: Gorski Andra-Teodora , Ranf Elena-Diana , Badea Dorel , Halmaghi Elisabeta-Emilia , Gorski Hortensia
Published: October 2023

The opportunities and challenges related to sustainability impose not only a societal transformation but also a personal one. Higher Education Institutions (HEIs) have great potential to promote sustainability and shape future generations’ skills, knowledge, thinking, and actions. Addressing environmental, social, and economic pillars, education for sustainable development (ESD), or education for sustainability (EfS), is a catalyst for quality education towards a sustainable future. This paper aims to analyze the state of the art and prevailing trends in the scientific literature pertaining to ESD/EfS. In this regard, specific objectives were established to identify the following: (1) authors’ productivity over time; (2) countries’ contribution and collaboration; (3) the most relevant keywords; and (4) the most prominent themes—in terms of relevance and degree of development. To fulfill the research objectives, quantitative research employing bibliometric analysis was carried out in April 2023. The research data sample was collected from the Web of Science (WoS) database. By conducting the search using a combined topic (“education for sustainable development” OR “education for sustainability”), a total of 2827 documents in English were identified within a timeframe of 33 years (1989–2023). These documents served as the foundation for subsequent data processing, visualization, and analysis using Biblioshiny/Bibliometrix (version R-4.2.0), as well as Excel (version 2309) software. The visualization and analysis focused on examining the most prolific authors and countries, in addition to generating word clouds based on keywords. Moreover, the thematic map that was delineated into four quadrants—Basic, Motor, Niche, and Emerging or Declining themes—provides an overview of the researched subject. ESD—embracing environmental, social, and economic pillars—implies transformative learning, action-oriented pedagogies, and professional development. As a holistic framework, it requires interdisciplinarity, system thinking, critical and experiential thinking, problem-based learning, and the use of 4IR technologies to enhance the teaching-learning process.
The Interconnected Effects of Financial Constraints, Social Connections, and Health on the Subjective Well-Being of the Unemployed in Abu Dhabi
Authors: Badri Masood , Alkhaili Mugheer , Aldhaheri Hamad , Yang Guang , Yaaqeib Saad , Albahar Muna , Alrashdi Asma
Published: October 2023

Research consistently highlights the substantially negative effect of unemployment on subjective well-being. This study’s objective is to provide deeper understanding of the complex nature of the associations between happiness and unemployment, which could enrich the duties of social policymakers when designing policy frameworks to improve the well-being of the unemployed. The methodology in this paper employs a path analysis using the Abu Dhabi Quality-of-Life survey (third cycle) data with 4815 unemployed respondents. The present study suggests a comprehensive path model to recognize the most significant associates of the happiness of the unemployed. Key findings indicate that income satisfaction and the ability to make ends meet have the highest effect on the happiness of the unemployed. The model also reveals the strength of different mediation roles played by family connection, quality time with family, and the ability to make ends meet, suggesting that financial difficulties resulting from unemployment can impact social relationships. In addition, the significant differences found between demographic groups based on age, marital status, gender, and educational attainment are also investigated. Policy implications are briefly discussed.
Long-Term Solar Power Time-Series Data Generation Method Based on Generative Adversarial Networks and Sunrise–Sunset Time Correction
Authors: Shi Haobo , Xu Yanping , Ding Baodi , Zhou Jinsong , Zhang Pei
Published: October 2023

Constructing long-term solar power time-series data is a challenging task for power system planners. This paper proposes a novel approach to generate long-term solar power time-series data through leveraging Time-series Generative Adversarial Networks (TimeGANs) in conjunction with adjustments based on sunrise–sunset times. A TimeGAN model including three key components, an autoencoder network, an adversarial network, and a supervised network, is proposed for data generation. In order to effectively capture autocorrelation and enhance the fidelity of the generated data, a Recurrent Neural Network (RNN) is proposed to construct each component of TimeGAN. The sunrise and sunset time calculated based on astronomical theory is proposed for adjusting the start and end time of solar power time-series, which are generated by the TimeGAN model. This case study, using real datasets of solar power stations at two different geographic locations, indicates that the proposed method is superior to previous methods in terms of four aspects: annual power generation, probability distribution, fluctuation, and periodicity features. A comparison of production cost simulation results between using the solar power data generated via the proposed method and using the actual data affirms the feasibility of the proposed method.
Determining Factors Influencing Short-Term International Aviation Traffic Demand Using SHAP Analysis: Before COVID-19 and Now
Authors: Song Ki-Han , Choi Solsaem , Elkosantini Sabeur , Suh Wonho
Published: October 2023

Due to the COVID-19 outbreak, international aviation travel has declined globally to the level it was 30 years ago. Influencing factors are explored to understand the difference in short-term international aviation travel demand before and after the COVID-19 pandemic. SHapley Additive exPlanations (SHAP), an exploratory data analysis methodology, is applied to identify the factors affecting aviation demand. Daily international aviation passenger volume data (1462 in total) between 2018 and 2021 are analyzed with 10 socioeconomic variables and the number of daily confirmed COVID-19 cases in Korea. It was found that the number of confirmed cases did not have the greatest direct influence on the short-term demand for international demand, but it has a strong correlation with socioeconomic factors. This study’s findings on the factors influencing short-term international air passenger demand from a macro perspective will contribute to demand forecasting after COVID-19. It is expected that this research can be applied to other countries or other pandemic data to investigate the post-pandemic demand changes.
Socio-Economic Factors Affecting ESG Reporting Call for Globally Agreed Standards
Authors: Krambia-Kapardis Maria , Savva Christos S. , Stylianou Ioanna
Published: October 2023

The ESG ecosystem has evolved over the years, and macro decisions have had an impact on the implementation and reporting of the ESG Index. This paper aims to first investigate if all the components of the ESG index are equally reported and secondly to identify the impact of socio-economic and political variables on the composite ESG index. To achieve this aim, the authors have utilized macroeconomic variables over the period 1984–2020 for 139 countries from the Refinitiv database and have constructed composite indices based on principal component analysis for the ESG components using a panel fixed effects model with structural breaks. The findings have significant policy implications, emphasizing the importance of globally accepted standards. Finally, by addressing the ESG at a macro level, it provides the context within which to consider the adoption of the ESG ecosystem diachronically, thus providing the backdrop for considering the implementation of the ESG at the micro level.
Enhancing Hydrophobic/Hydrophilic Dual-Layer Membranes for Membrane Distillation: The Influence of Polytetrafluoroethylene (PTFE) Particle Size and Concentration
Authors: Al-Ogaili Mohammed Faleh Abd , Othman Mohd Hafiz Dzarfan , Rava Mohammad , Tai Zhong Sheng , Puteh Mohd Hafiz , Jaafar Juhana , Rahman Mukhlis A. , Kurniawan Tonni Agustiono , Samuel Ojo , Imtiaz Aniqa
Published: October 2023

This study assesses the effects of different polytetrafluoroethylene (PTFE) particle sizes and concentrations on the performance of dual-layer membranes in direct contact membrane distillation (DCMD). Specifically, particle sizes of 0.5 μm, 1 μm, and 6 μm were systematically evaluated at concentrations of 0 wt%, 2 wt%, 4 wt%, and 6 wt%. Comprehensive analyses, including scanning electron microscopy (SEM), liquid entry pressure (LEP), contact angle, thermogravimetric analysis (TGA), mercury intrusion porosimetry (MIP), atomic force microscopy (AFM), permeate flux, nitrogen gas permeation, and salt rejection, were employed to characterize the membranes. Under conditions of a feed temperature of 70 °C and a salt concentration of 8000 ppm for a 24 h duration, the results clearly indicated that a 0.5 μm PTFE particle size combined with a 6 wt% concentration exhibited the highest performance. This configuration achieved a permeate flux of 11 kg·m2/h and a salt rejection rate of 99.8%. The outcomes of this research have significant implications for the optimization of membranes used in DCMD applications, with potential benefits for sustainable water treatment and energy conservation.
Identification Method of Optimal Copula Correlation Characteristic for Geological Parameters of Roof Structure
Authors: Cao Jiazeng , Wang Tao , Zhu Chuanqi , Yu Jianxin , Chen Xu , Zhang Xin
Published: October 2023

Limited by the actual investigation of coal mine engineering, the measured data obtained are often based on small sample characteristics. How to probabilistically de-integrate the prior information to obtain meaningful statistical values has received increasing attention from geotechnical engineers. In this study, an optimal copula function identification method for multidimensional geotechnical structures of coal mine roofs under the Bayesian approach is proposed. Firstly, the characterization method of multidimensional roof parameter correlation structures is proposed based on copula theory, and 167 sets of measured data from 24 coal mines at home and abroad are collected to study the measured identification results using the Bayesian method. Secondly, Monte Carlo simulation is utilized to compare the correct recognition rates of the commonly used AIC criterion and the Bayesian approach under different correlation structures. Finally, the influencing factors affecting the successful recognition rate of the Bayesian approach are analyzed. The results show that compared with the traditional AIC criterion, the Bayesian approach has more marked advantages in correctly recognizing the multidimensional parameter structures of roofs, and the number of measured samples, the strength of correlation coefficients, and the prior information have a major effect on the correct recognition rate of the optimal copula function under different real copula functions. In addition, the commonly used Gaussian copula has a better characterization effect in characterizing the multidimensional parameter correlation structure of the coal mine roofs, which can be prioritized to be used as a larger prior probability function in the evaluation process.
Agricultural Markets, Cropping Patterns, and Consumption Patterns: The Moderating Effect of COVID-19 on Mountainous Communities
Authors: Khayyam Muhammad , Kamal Fatima Daud , Nouman Muhammad , Nizami Arjumand , Ali Jawad , Salim Muhammad Asad
Published: October 2023

Since COVID-19’s emergence in 2020, all segments of life, including farming communities, have been impacted. The pandemic revealed both vulnerabilities and opportunities for resilience, particularly for those dwelling in the harsh mountainous terrains, which have already strained food ecosystems. Taking influence from an exhaustive literature review, this study proposes and tests a model for the transformations observed in the agriculture markets, particularly input, labor, and product markets, and elucidates the influence of these changes on cropping and consumption patterns. With data from two major mountainous terrains in north Pakistan spanning three years before and during the pandemic, a quantitative inquiry was carried out on the agriculture markets and farming patterns. A total of 5273 members of the farming communities were targeted for data collection. A two-step process was used for data analysis, including an evaluation of the outer or measurement model followed by the inner or structural model through partial least squares structural equation modeling (PLS-SEM). With a hitherto ignored focus on the already vulnerable mountainous communities, the findings confirm the direct influence of agriculture markets on changes in the farmers’ cropping patterns as well as the moderating influence of the pandemic on these relationships. Consistent with previous literature, the results also affirm the influence of changes in cropping patterns and changes in consumption patterns. However, it was found that the agriculture input markets strongly predict the changes in cropping patterns, whereas the labor and product markets have comparatively lower prediction value. By investigating the various facets of food supply chains, this study offers valuable insights on market dynamics in times of a crisis, such as a pandemic.
Differential Evolution Using Enhanced Mutation Strategy Based on Random Neighbor Selection
Authors: Baig Muhammad Hassan , Abbas Qamar , Ahmad Jamil , Mahmood Khalid , Alfarhood Sultan , Safran Mejdl , Ashraf Imran
Published: October 2023

Symmetry in a differential evolution (DE) transforms a solution without impacting the family of solutions. For symmetrical problems in differential equations, DE is a strong evolutionary algorithm that provides a powerful solution to resolve global optimization problems. DE/best/1 and DE/rand/1 are the two most commonly used mutation strategies in DE. The former provides better exploitation while the latter ensures better exploration. DE/Neighbor/1 is an improved form of DE/rand/1 to maintain a balance between exploration and exploitation which was used with a random neighbor-based differential evolution (RNDE) algorithm. However, this mutation strategy slows down convergence. It should achieve a global minimum by using 1000 × D, where D is the dimension, but due to exploration and exploitation balancing trade-offs, it can not achieve a global minimum within the range of 1000 × D in some of the objective functions. To overcome this issue, a new and enhanced mutation strategy and algorithm have been introduced in this paper, called DE/Neighbor/2, as well as an improved random neighbor-based differential evolution algorithm. The new DE/Neighbor/2 mutation strategy also uses neighbor information such as DE/Neighbor/1; however, in addition, we add weighted differences after various tests. The DE/Neighbor/2 and IRNDE algorithm has also been tested on the same 27 commonly used benchmark functions on which the DE/Neighbor/1 mutation strategy and RNDE were tested. Experimental results demonstrate that the DE/Neighbor/2 mutation strategy and IRNDE algorithm show overall better and faster convergence than the DE/Neighbor/1 mutation strategy and RNDE algorithm. The parametric significance test shows that there is a significance difference in the performance of RNDE and IRNDE algorithms at the 0.05 level of significance.
Response of Shock Isolators with Piecewise Linear Asymmetric Damping
Authors: Mitu Ana-Maria , Solomon Ovidiu , Giuclea Marius , Sireteanu Tudor
Published: October 2023

The output of a single-degree-of-freedom (SDOF) piecewise linear system with asymmetric damping and linear stiffness excited by Dirac impulse excitation is studied. Analytical solutions of the response for piecewise linear systems are obtained by replacing the equation of motion with Dirac excitation by a homogeneous differential system with zero initial displacement and a given initial velocity. A significant improvement of the response consisting in a substantial reduction in the after-shock vibrations was obtained. The obtained results are applied to the damping optimization of a shock isolation system for forging hammers.
Exposure Assessment to Deoxynivalenol of Children over 3 Years Deriving from the Consumption of Processed Wheat-Based Products Produced from a Dedicated Flour
Authors: Brera Carlo , De Santis Caterina , Marzona Stefania , Gregori Emanuela , Prisco Sabrina Santa , Monti Maurizio , Chilosi Gabriele , Pantanali Anna
Published: October 2023

Wheat-based products are largely consumed by children worldwide. Deoxynivalenol (DON) is known for its acute and chronic toxicity and is the most common contaminant of cereal grains. Since no legal limits are set for DON in wheat-based products and specific foods intended for children over 3 years on the market, a high risk of overexposure to this contaminant may emerge. The main objective of the study, conducted in 2018–2019, was to produce a wheat flour intended for children over three years, characterized by a high level of safety in terms of DON content, to be used to produce wheat-derived products. The dedicated flour was produced by adopting tailored procedures like the selection of wheat suppliers, the predetermination of the safe contamination of DON in the final products, and the evaluation of the transfer rate from the wheat flour to derived products (bread, breadsticks, biscuits, plumcake, and focaccia). The results showed that the daily exposure of children was considered to be safe, in a range between 7% (biscuits) and 67% (bread) of DON tolerable daily intake (TDI) and that only by producing a flour characterized by DON levels much lower than those in force, can “safe” products be marketed.