bluuebunny/crossref_metadata_2025 huggingface dataset:
SPT-UNet: A Superpixel-Level Feature Fusion Network for Water Extraction from SAR Imagery
Authors: Zhao Teng , Du Xiaoping , Xu Chen , Jian Hongdeng , Pei Zhipeng , Zhu Junjie , Yan Zhenzhen , Fan Xiangtao
Published: July 2024

Extracting water bodies from synthetic aperture radar (SAR) images plays a crucial role in the management of water resources, flood monitoring, and other applications. Recently, transformer-based models have been extensively utilized in the remote sensing domain. However, due to regular patch-partition and weak inductive bias, transformer-based models face challenges such as edge serration and high data dependency when used for water body extraction from SAR images. To address these challenges, we introduce a new model, the Superpixel-based Transformer (SPT), based on the adaptive characteristic of superpixels and knowledge constraints of the adjacency matrix. (1) To mitigate edge serration, the SPT replaces regular patch partition with superpixel segmentation to fully utilize the internal homogeneity of superpixels. (2) To reduce data dependency, the SPT incorporates a normalized adjacency matrix between superpixels into the Multi-Layer Perceptron (MLP) to impose knowledge constraints. (3) Additionally, to integrate superpixel-level learning from the SPT with pixel-level learning from the CNN, we combine these two deep networks to form SPT-UNet for water body extraction. The results show that our SPT-UNet is competitive compared with other state-of-the-art extraction models, both in terms of quantitative metrics and visual effects.
Intelligent Inspection Method and System of Plastic Gear Surface Defects Based on Adaptive Sample Weighting Deep Learning Model
Authors: Shi Zhaoyao , Fang Yiming , Song Huixu
Published: July 2024

After injection molding, plastic gears often exhibit surface defects, including those on end faces and tooth surfaces. These defects encompass a wide range of types and possess complex characteristics, which pose challenges for inspection. Current visual inspection systems for plastic gears suffer from limitations such as single-category defect inspection and low accuracy. There is an urgent industry need for a comprehensive and accurate method and system for inspecting defects on plastic gears, with improved inspection capability and higher accuracy. This paper presents an intelligent inspection algorithm network for plastic gear defects (PGD-net), which effectively captures subtle defect features at arbitrary locations on the surface compared to other models. An adaptive sample weighting method is proposed and integrated into an improved Focal-IoU loss function to address the issue of low inspection accuracy caused by imbalanced defect dataset distributions, thus enhancing the regression accuracy for difficult defect categories. CoordConv layers are incorporated into each inspection head to improve the model’s generalization capability. Furthermore, a dataset of plastic gear surface defects comprising 16 types of defects is constructed, and our algorithm is trained and tested on this dataset. The PGD-net achieves a comprehensive mean average precision (mAP) value of 95.6% for the 16 defect types. Additionally, an online inspection system is developed based on the PGD-net algorithm, which can be integrated with plastic gear production lines to achieve online full inspection and automatic sorting of plastic gear defects. The entire system has been successfully applied in plastic gear production lines, conducting daily inspections of over 60,000 gears.
DOT-SLAM: A Stereo Visual Simultaneous Localization and Mapping (SLAM) System with Dynamic Object Tracking Based on Graph Optimization
Authors: Zhu Yuan , An Hao , Wang Huaide , Xu Ruidong , Sun Zhipeng , Lu Ke
Published: July 2024

Most visual simultaneous localization and mapping (SLAM) systems are based on the assumption of a static environment in autonomous vehicles. However, when dynamic objects, particularly vehicles, occupy a large portion of the image, the localization accuracy of the system decreases significantly. To mitigate this challenge, this paper unveils DOT-SLAM, a novel stereo visual SLAM system that integrates dynamic object tracking through graph optimization. By integrating dynamic object pose estimation into the SLAM system, the system can effectively utilize both foreground and background points for ego vehicle localization and obtain a static feature points map. To rectify the inaccuracies in depth estimation from stereo disparity directly on the foreground points of dynamic objects due to their self-similarity characteristics, a coarse-to-fine depth estimation method based on camera–road plane geometry is presented. This method uses rough depth to guide fine stereo matching, thereby obtaining the 3 dimensions (3D)spatial positions of feature points on dynamic objects. Subsequently, by establishing constraints on the dynamic object’s pose using the road plane and non-holonomic constraints (NHCs) of the vehicle, reducing the initial pose uncertainty of dynamic objects leads to more accurate dynamic object initialization. Finally, by considering foreground points, background points, the local road plane, the ego vehicle pose, and dynamic object poses as optimization nodes, through the establishment and joint optimization of a nonlinear model based on graph optimization, accurate six degrees of freedom (DoFs) pose estimations are obtained for both the ego vehicle and dynamic objects. Experimental validation on the KITTI-360 dataset demonstrates that DOT-SLAM effectively utilizes features from the background and dynamic objects in the environment, resulting in more accurate vehicle trajectory estimation and a static environment map. Results obtained from a real-world dataset test reinforce the effectiveness.
Fabrication of Automated Hydrostatic Pressure-Based Densitometer with a Calibrated Pressure Sensor
Authors: Jayakantha D. N. P. Ruwan , Gamage Kelum A. A. , Bandara Navaratne , Karunarathne Migara , Seneviratne Madushani , Comini Elisabetta , Zappa Dario , Gunawardhana Nanda
Published: July 2024

An automated device is designed to measure the density of a liquid material using hydrostatic pressure method. A low cost pressure sensor is calibrated and used to get highly accurate readings. The calibration is done by measuring the pressure values vs. the generated voltage signal. The calibration has been challenging due to the low accuracy of the sensor but proved to be highly effective in applications. The interface is developed using a microcontroller, motor drives, analog to digital converters and sensors. The device is designed to get several readings automatically by changing the positions of the device/liquid column heights to increase the accuracy. Also the device can be programmed to measure the real time density of a liquid continuously. The readings were analyzed and averaged by a software developed in python language. The instruments accuracy was tested against 3 liquid types, water, coconut oil, kerosene oil, and showed a low error (0.007%, 0.001%, and 0.002% respectively) compared to the readings of a standard Pycnometer. The low error percentages confirm the accuracy of the device and the effectiveness of the sensor calibrations.
Victorious Voices: Legal and Social Triumphs against Sexual Harassment in Higher Education—A Case Study
Authors: Vidu Ana , Sordé-Martí Teresa , Melgar Patricia , Joanpere Mar
Published: July 2024

Sexual harassment in academia has gained attention due to legislative measures, university mechanisms, and student solidarity networks. This article explores the factors contributing to survivors winning when suing their university. The case described here relates to a North American university in a state with regulations against harassment and an active student movement. It delves into a case at the University of California, Irvine, where four individuals sued for the mishandling of sexual harassment complaints, resulting in the dismissal of a prominent professor. Drawing on data from the EU UniswithHeart research project, the article analyzes the impact of solidarity networks and the trial outcome. Through desk research and qualitative interviews, it identifies key elements leading to legal victories against universities, even in the case of a professor who made a big donation to the university, who was banned from campus, and who had his name removed from buildings. This study shows ten aspects that lead to winning a harassment case within universities, emphasizing the importance of addressing the consequences of harassment. It also illustrates the improvement of the academic environment and science when eliminating the hostile climate and silence. Successful outcomes inspire other survivors and urge universities to uphold policies for a safer academic environment.
Bayesian Model Averaging and Regularized Regression as Methods for Data-Driven Model Exploration, with Practical Considerations
Authors: Han Hyemin
Published: July 2024

Methodological experts suggest that psychological and educational researchers should employ appropriate methods for data-driven model exploration, such as Bayesian Model Averaging and regularized regression, instead of conventional hypothesis-driven testing, if they want to explore the best prediction model. I intend to discuss practical considerations regarding data-driven methods for end-user researchers without sufficient expertise in quantitative methods. I tested three data-driven methods, i.e., Bayesian Model Averaging, LASSO as a form of regularized regression, and stepwise regression, with datasets in psychology and education. I compared their performance in terms of cross-validity indicating robustness against overfitting across different conditions. I employed functionalities widely available via R with default settings to provide information relevant to end users without advanced statistical knowledge. The results demonstrated that LASSO showed the best performance and Bayesian Model Averaging outperformed stepwise regression when there were many candidate predictors to explore. Based on these findings, I discussed appropriately using the data-driven model exploration methods across different situations from laypeople’s perspectives.
Multivariate Statistical Analysis of Cosmetics Due to Potentially Toxic/Heavy Metal(loid) Contamination: Source Identification for Sustainability and Human Health Risk Assessment
Authors: Ahmed Mahmood , Ahmad Muhammad , Sohail Aamir , Sanaullah Mudassar , Saeed Ahmad , Qamar Shaista , Wani Tanveer A. , Zargar Seema , Alkahtani Hamad M. , Khalid Khuram
Published: July 2024

Cosmetics are a staple in daily beauty routines worldwide, embraced for their role in enhancing personal appearance and self-care. However, their direct application exposes the skin to a range of ingredients, including metal(loid)s, and these can have a hazardous impact on human health if they exceed the limits defined by regulatory agencies. As a result, it is important to evaluate metal(loid) levels to ensure the safety of these cosmetic products. This research aimed to analyze several cosmetic products (massage cream, cleaner, mud mask, skin polish, scrub, lipstick, foundation, lotion, face powder, and highlighter) for metalloids (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Sr, As, Sb, Cd, Pb, Bi, and Hg) by using inductively coupled plasma-optical emission spectrometry (ICP-OES). Multivariate and bivariate statistical approaches were used to interpret the sources and association between the metal(loid)s. The concentration ranges of metals were found to be Al (1.18–4.15 mg/kg), Cr (0.13–2.19 mg/kg), Mn (1.89–28.77 mg/kg), Fe (4.09–126.02 mg/kg), Co (0.19–31.62 mg/kg), Ni (0.11–5.39 mg/kg), Cu (0.08–0.19 mg/kg), Zn (1.99–47.81 mg/kg), Sr (0.99–10.34 mg/kg), Cd (0.16–1.50 mg/kg), Pb (0.29–2.44 mg/kg), Bi (0.23–2.18 mg/kg), and Hg (0.012–0.42 mg/kg), whereas the concentration ranges of metalloids were found to be As (0.011–0.051 mg/kg) and Sb (0.042–1.66 mg/kg). Among the tested cosmetic products for the metal(loid) levels, the estimation of the margin of safety (MOS < 100), hazard quotient (HQ > 1), hazard index (HI > 1), and cumulative cancer risk (LCR ≤ 1 × 10−3) indicated non-carcinogenic and carcinogenic health risks associated with the use of few products. Most of the cosmetics products under investigation are safe with respect to non-carcinogenic and carcinogenic health risks. By highlighting the need to limit excessive use and adhering to sustainable safety practices, this study underscores the importance of monitoring and regulating metal(loid) content to ensure consumer safety and mitigate environmental impact.
A Quantitative Index for Evaluating Maize Leaf Wilting and Its Sustainable Application in Drought Resistance Screening
Authors: Zhang Lei , Tang Huaijun , Xie Xiaoqing , Sun Baocheng , Liu Cheng
Published: July 2024

Leaf wilting is one of the most intuitive morphological manifestations of plants under drought stress, and it is useful in drought resistance screening. However, existing quantitative leaf-wilting measurement methods lack simplicity and high-throughput capacity under field conditions, and there is a gap in the systematic drought resistance assessments. The present study was conducted in 2020, 2021, and 2022 using 100 inbred maize lines. The maize lines were subjected to three different water stress treatments: normal irrigation, moderate drought, and severe drought. The findings led to the design of a simplified image acquisition and processing platform for measuring the visible green leaf area. A new measurement index and quantitative formula for wilting have been proposed, which effectively reflect leaf wilting and facilitate a systematic analysis of the relationship between yield and drought resistance. The results showed that the daily variation pattern of the visible green leaf area followed a trend of wilting first and then recovery, with maximum wilting occurring at noon (14:00–16:00 local time). The period of maximum wilting throughout the entire growth stage was the flowering stage. The maize plants with leaf wilt exceeding 1/2 (wilt ratio > 0.5) during the flowering stage were all low-yielding or low-tolerance inbred lines. In conclusion, this study emphasizes that the flowering stage is crucial for monitoring leaf wilting and introduces a quick high-throughput method to quantify leaf wilting. Our findings not only provide details about key indicators for identifying drought and heat resistance but also facilitate research on sustainable screening methods in maize, which will expedite the selection and accelerate the breeding of new varieties.
Spatiotemporal Analysis of Air Quality and Its Driving Factors in Beijing’s Main Urban Area
Authors: Tan Zhixiong , Wu Haili , Chen Qingyang , Huang Jiejun
Published: July 2024

Urban air pollution is a critical global environmental issue, necessitating an analysis of the spatiotemporal characteristics of air quality and its driving factors for sustainable urban development. However, the traditional urban air quality assessment system ignores the impact of internal urban spatial structures. Therefore, this paper proposes an assessment system that integrates natural, socio-economic, and urban layout factors by utilizing the air quality index (AQI) and 14 types of multi-source geographic data in the main urban area of Beijing from 2016 to 2020 and constructs geographically weighted regression (GWR) and multi-scale geographically weighted regression (MGWR) models for spatiotemporal analysis. Our findings revealed an annual improvement in air quality, with a U-shaped seasonal pattern and significant spatial clustering (Global Moran’s I = 0.922). The MGWR model provided a superior fit over the GWR, capturing spatial variability more effectively. Variables such as NDVI, economic output (GDP), and humidity space adjustment capability (HSAC) showed significant positive spatial impacts on air quality, while population density (POP), temperature (TEMP), and road density (RD) exhibited negative effects. These results explain the changes in air quality in the main urban area of Beijing from a spatiotemporal perspective and provide planning input for urban air quality regulations.
Assessment of Utilizing Hard-to-Recycle Plastic Waste from the Packaging Sector in Architectural Design—Case Study for Experimental Building Material
Authors: Cudzik Jan , Kropisz Klaudia
Published: July 2024

The environmental impact of plastic waste has become a significant concern worldwide, prompting innovative approaches to address sustainability challenges, particularly within architectural design. This research paper delves into assessing the environmental impact and sustainability implications of using hard-to-recycle plastic packaging waste in architectural design practices. This study aims to evaluate the feasibility, challenges, and potential benefits of repurposing hard-to-recycle plastic packaging waste as building materials in an architectural context. The paper presents a compelling case study showcasing innovative architectural projects that have successfully integrated hard-to-recycle plastic waste. It offers recommendations for future research directions and policy interventions to promote the adoption of hard-to-recycle plastics in environmentally conscious architecture, thereby advancing sustainability goals and fostering a circular economy paradigm within the construction industry. The research paper also highlights a specific experiment conducted using hard-to-recycle plastic waste, illustrating the potential for creative solutions in sustainable architectural design. This study provides valuable insights into the environmental impact and feasibility of repurposing hard-to-recycle plastics as building materials, contributing to ongoing efforts to address sustainability challenges.
Real-Time Elemental Analysis Using a Handheld XRF Spectrometer in Scanning Mode in the Field of Cultural Heritage
Authors: Asvestas Anastasios , Chatzipanteliadis Demosthenis , Gerodimos Theofanis , Mastrotheodoros Georgios P. , Tzima Anastasia , Anagnostopoulos Dimitrios F.
Published: July 2024

An X-ray fluorescence handheld spectrometer (hh-XRF) is adapted for real-time qualitative and quantitative elemental analysis in scanning mode for applications in cultural heritage. Specifically, the Tracer-5i (Bruker) is coupled with a low-cost constructed computer-controlled x–y target stage that enables the remote control of the target’s movement under the ionizing X-ray beam. Open-source software synchronizes the spectrometer’s measuring functions and handles data acquisition and data analysis. The spectrometer’s analytical capabilities, such as sensitivity, energy resolution, beam spot size, and characteristic transition intensity as a function of the distance between the spectrometer and the target, are evaluated. The XRF scanner’s potential in real-time imaging, object classification, and quantitative analysis in cultural heritage-related applications is explored and the imaging capabilities are tested by scanning a 19th-century religious icon. The elemental maps provide information on used pigments and reveal an underlying icon. The scanner’s capability to classify metallic objects was verified by analyzing the measured raw spectra of a coin collection using Principal Components Analysis. Finally, the handheld’s capability to perform quantitative analysis in scanning mode is demonstrated in the case of precious metals, applying a pre-installed quantification routine.
The Importance of Studying Abroad for a Sustainable Education: Research on Mongolian Student Opinions
Authors: Nyamsuren Khosbayar , Gankhuyag Zolzaya , Ganbaatar Jargalmaa , Marinescu Nicolae
Published: July 2024

Student mobility and internationalization of universities have become an important issue for empowering young people and cultural exchange, in line with the quest for implementing a sustainable education. The young generation of Mongolia has a strong desire to study in foreign universities. The aim of this paper is to analyze the opinions of Mongolian learners on studying abroad as displaying the characteristics of sustainable education. According to our quantitative research, a large percentage of university students are very interested in participating in the ERASMUS mobility program of the European Union. However, there are certain challenges to getting into the program, especially for scholars studying in isolated areas who have limited opportunities to obtain scholarship information. As for the graduates from Mongolia who have already participated in the program, their satisfaction with the program is high. The research found that quality education was the most appraised benefit, while the language barrier posed the main challenge during studying abroad, followed by adaptation to the teaching methods of the host university. Findings show that mobile students developed their academic knowledge and enjoyed experiencing new places and cultures. They also acknowledged improving their professional skills for their future careers and adopting a more sustainable lifestyle.
How Do Environmental Regulation and Decentralization Interactively Affect the Green Productivity of the Construction Industry? Evidence from China
Authors: Yang Zhao , Fang Hong
Published: July 2024

In this paper, based on the spatial panel data of 30 provinces in China from 2008 to 2019, the relationship between environmental regulation (ER), environmental decentralization (ED) and the green total factor productivity of the construction industry (hereafter GTFPCI) was investigated through the spatial Dobbin model, and the heterogeneity of the relationship between three environmental regulations and the GTFPCI under different environmental decentralization intensities was studied through a threshold panel model. The results showed that the three environmental regulations had different degrees of impact on the GTFPCI, among which market-based environmental regulations (MERs) played the most obvious role. Environmental regulation and environmental decentralization have spillover effects on the GTFPCI in surrounding provinces. On the whole, with the increasing intensity of environmental decentralization, environmental regulation plays a stronger positive role in promoting the GTFPCI. However, through a threshold analysis, it was seen that the regulatory impact of different environmental regulations on the GTFPCI are heterogeneous in different ranges of environmental decentralization intensity.
Heterogeneity in the Effects of Atmospheric Moisture Changes on Vegetation in Different Climatic Zones
Authors: Jin Xiaohui , Fan Yumiao , Hu Yawei , Wang Huihui , Jia Qian , Yang Lei , Zhang Mingqi
Published: July 2024

Due to the effects of global warming, the vapor pressure deficit (VPD) will inevitably and continuously rise in future, which is a fact that must be faced when discussing the sustainable development of vegetation ecosystems. Understanding the response of vegetation to changes in the atmospheric moisture state is necessary for minimizing the adverse effects of climate change. Using the leaf area index (LAI) and meteorological data in the Yellow River Basin collected over nearly 40 years, we explore the spatiotemporal variations in VPD and vegetation within the growing season and the differences in the effects of VPD on vegetation in different climatic zones. The results show the following: (1) both VPD and LAI in the Yellow River Basin show an increasing trend, in which VPD increases radially outward centered on the arid regions, while the vegetation develops favorably over almost the whole basin; (2) at the whole-basin scale, the area of VPD positively correlated with vegetation growth is greater than the area of negative correlation, and this overall trend is increasing significantly; (3) the VPD exerts heterogeneous effects on different vegetation in different climatic zones, and these heterogeneity findings suggest that the effects of VPD on vegetation are more influenced by differences among the climatic zones of the vegetation than by differences in the vegetation types themselves. Our results provide insights into the effects of atmospheric moisture on vegetation growth and provide references for the sustainable development of vegetation ecosystems and future safeguarding strategies of vegetation over large spatial scales.
Variation of the Groundwater Table within Indian Railway Embankments in Consideration of Climate Change
Authors: Kumar Manish , Hayano Kimitoshi
Published: July 2024

Climatic changes have intensified heavy rainfall events in India, causing daily downpours from 156 to 594 mm, and these are expected to worsen in the future. This study analyses a double-line railway embankment using transient unsaturated–saturated seepage analysis through numerical modeling to examine the impact of rainfall scenarios, embankment height, initial groundwater table position, and soil water characteristics curves (SWCCs) of subgrade and subsoil. Our findings indicate an increased vulnerability of embankments to future rainfall due to rapid increases in the groundwater level, necessitating the requirement to make railway embankments resilient to climate change and thereby offering a sustainable mode of transportation. The groundwater onset mechanism across different heights remained consistent; rainwater infiltrated through side slopes first, rose near the toe, and then flowed horizontally, leading to convergence. The convergence level is affected by the SWCCs; however, a single normalized convergence plot can be created by presuming the horizontal flow of the infiltrated water through embankment and subsoil, irrespective of the material type, establishing horizontal flow as the principal convergence mechanism. In embankments over low-permeability subsoil, extremely heavy rainfall creates a unique pattern: side slopes and the top saturate early, while the saturation of the bottom central part is delayed. In such cases, deriving a groundwater variation curve might be challenging.
The European Union and Material Deprivation: Measuring the Evolution of Inequalities over the 2000s
Authors: Traversa Susanna , Ivaldi Enrico , Forciniti Alessia
Published: July 2024

Since the early 2000s, the European Union has increasingly prioritized policies aimed at combating social exclusion, with a focus on efficient fund allocation for social and sustainable cohesion objectives. Given the multidimensional nature of material deprivation, synthetic indicators are frequently employed in the literature to measure this phenomenon. However, these indicators often lack suitability for temporal analysis, which is crucial for understanding the persistence of disadvantaged statuses over time and the effectiveness of national and international policies. This article offers an innovative examination of the trends in material deprivation among European Union Member States during the period of 2005–2022. It provides a structured reconstruction of the phenomenon at the NUTS-1 level, within the context of the major economic and health crises that have characterized the 21st century. This study’s key innovation lies in the creation of a temporal index of material deprivation, employing the AMPI method, which incorporates a partially compensatory aggregative synthesis and allows for the monitoring of the phenomenon over time against a baseline year. This novel approach ensures the capability to analyze the evolution of material deprivation over time and across regions, with 2005 as the reference year. The findings reveal a general improvement in material deprivation levels compared to 2005, despite deteriorating conditions in the Mediterranean and Baltic regions. By maintaining 2005 as the reference year, this index facilitates the ongoing monitoring of the impacts of COVID-19 and the effects of national recovery policies, as well as the resilient and sustainable social policies promoted by the RecoverEU fund.
Assessing Students’ Utilization of University Footbridges in Amman City: Motivating Factors and Obstacles in an Urban Setting
Authors: Muhsen Rabab , Al-Majali Rama , Tomah (Maayah) Ayman
Published: July 2024

The use of pedestrian footbridges plays a critical role in urban mobility, particularly in university areas with high pedestrian traffic. Despite its importance, footbridge utilization often remains suboptimal due to various influencing factors that are not well understood. This study aims to identify and analyze the factors affecting footbridge utilization among university students in Amman City. By surveying students from four universities—Islamic Sciences University (ISUF), Balqa Applied University (BAUF), and two branches of Jordan University (JUF1 and JUF2)—we explore how accessibility, design aesthetics, safety, emotional and psychological factors, and environmental considerations influence their decision to use footbridges. The findings reveal significant differences in the impact of these factors across universities. Notably, environmental considerations and design aesthetics are pivotal for ISUF students, while JUF1 and BAUF students prioritize convenience and time-saving. Furthermore, our research identifies a crucial difference in safety concerns, with female students exhibiting a higher focus on safety compared to their male counterparts. This highlights the need for gender-sensitive safety interventions in footbridge design. Environmental considerations consistently emerge as a priority for all, reflecting a collective concern for the eco-friendly features of bridge design. This study is considered the first of its kind in Amman City and the region. The results align with global findings, establishing a basis for wider implications concerning the development of theoretical knowledge of urban mobility. This research fills a crucial gap by providing empirical evidence of the diverse factors impacting footbridge usage. It offers valuable insights for urban planners seeking to design and maintain user-friendly and gender-sensitive footbridges, ultimately promoting sustainable urban mobility.
Modeling and Sustainability Implications of Harsh Driving Events: A Predictive Machine Learning Approach
Authors: Kostopoulos Antonis , Garefalakis Thodoris , Michelaraki Eva , Katrakazas Christos , Yannis George
Published: July 2024

Human behavior significantly contributes to severe road injuries, underscoring a critical road safety challenge. This study addresses the complex task of predicting dangerous driving behaviors through a comprehensive analysis of over 356,000 trips, enhancing existing knowledge in the field and promoting sustainability and road safety. The research uses advanced machine learning algorithms (e.g., Random Forest, Gradient Boosting, Extreme Gradient Boosting, Multilayer Perceptron, and K-Nearest Neighbors) to categorize driving behaviors into ‘Dangerous’ and ‘Non-Dangerous’. Feature selection techniques are applied to enhance the understanding of influential driving behaviors, while k-means clustering establishes reliable safety thresholds. Findings indicate that Gradient Boosting and Multilayer Perceptron excel, achieving recall rates of approximately 67% to 68% for both harsh acceleration and braking events. This study identifies critical thresholds for harsh events: (a) 48.82 harsh accelerations and (b) 45.40 harsh brakings per 100 km, providing new benchmarks for assessing driving risks. The application of machine learning algorithms, feature selection, and k-means clustering offers a promising approach for improving road safety and reducing socio-economic costs through sustainable practices. By adopting these techniques and the identified thresholds for harsh events, authorities and organizations can develop effective strategies to detect and mitigate dangerous driving behaviors.
Research on Multi-Objective Optimization of Shield Tunneling Parameters Based on Power Consumption and Efficiency
Authors: Wang Wei , Feng Huanhuan , Li Yanzong , Zheng Xudong , Qi Jinhui , Sun Huaize
Published: July 2024

The shield tunneling method is commonly used in the development and construction of underground spaces, and the adjustment of its parameters is a crucial part of shield construction. However, there are relatively few studies on optimizing tunneling parameters from a sustainable perspective, with a focus on energy saving and emission reduction. This study addresses this gap by combining engineering geological conditions with shield machine propulsion parameters in a specific section of metro construction in China. By aiming to reduce power consumption and improve efficiency, an improved particle swarm optimization algorithm based on the concept of Pareto optimal solutions was employed to optimize the tunneling parameters. The results demonstrated that the optimized parameters reduced power consumption and improved efficiency. This validates the feasibility of the optimization scheme and its potential for broader applications in sustainable underground construction.
Regional and Local Development in Energy Transition Areas: The Case of Lignite Phase-Out in the Peloponnese
Authors: Kourkouridis Dimitris , Salepaki Asimenia , Kasselouris George , Baltas Emmanouil
Published: July 2024

The establishment of sustainable energy frameworks amidst global climate change and dwindling petroleum reserves has prompted a focus on energy transition, marking a shift in how energy is utilized within systems. Greece, historically reliant on lignite for electricity generation, faces the challenge of transitioning towards a low-carbon economy. This study explores the potential of creating a multipurpose entrepreneurship and culture center, the Mediterranean Center for Entrepreneurship and Culture (MCEC), in Megalopolis, Arcadia, Greece, as a strategic intervention for economic, social, and environmental restructuring. Drawing on best practices and comprehensive analyses of external factors, the study outlines the conceptualization and evaluation of the MCEC, considering economic feasibility, development scenarios, financial sustainability, and stakeholder engagement. The discussion highlights the anticipated benefits of the MCEC, including job creation, entrepreneurship promotion, and socio-cultural advancement, underscoring its potential to mitigate the impacts of lignite phase-out and foster sustainable regional development. Overall, the establishment of the MCEC is poised to yield positive socio-economic impacts, including employment growth, entrepreneurship promotion, infrastructure development, and cultural enrichment, contributing to the resilience and prosperity of the Megalopolis region and beyond.
Determinants of Intention to Adopt Recycled Water: Evidence from Four High-Water-Stress Provinces in China
Authors: Liu Lin , Wang Weidong , Njie Yahya
Published: July 2024

Promoting the use of recycled water is essential for environmental sustainability. A key part of promoting the use of recycled water is effectively increasing the public’s intention to adopt it. This research attempts to explore the factors that influence the public’s intention to adopt recycled water. It therefore introduces the baseline water stress indicator and extends the survey area to areas of high water stress. Based on the Diffusion of Innovation Theory (DOI), a new research model is developed from the perspective of “information disclosure (knowledge)–psychological factors (persuasion)–adoption intention (decision)”, and the moderating role of policy instruments is considered. Structural equation modeling and hierarchical regression analysis are used to empirically analyze 724 valid questionnaires. The results indicate that psychological factors (trust, awareness of water environment protection, herd mentality) have multiple parallel mediating effects between recycled water information disclosure and adoption intention, and herd mentality is the key factor influencing the public’s intention to adopt recycled water. Command-and-control policy instruments inhibit adoption intention, while economic incentives and publicity-and-guidance policy instruments promote adoption intention. These findings can help policymakers seek and adopt effective policy measures and provide a reference for popularizing and promoting recycled water in areas with high water stress.
Taoist-Inspired Principles for Sustainability Transitions: Beyond Anthropocentric Fixes and Rethinking Our Relationship with Nature
Authors: Liang Na , Segalas Jordi
Published: July 2024

The magnitude and scale of the challenges ahead require fundamental sustainability transitions towards sustainable societies on an unprecedented level in human history. This paper argues that reflecting on the philosophical underpinnings of sustainability transitions and complementing the human–nature relationship with a more holistic and ecological perspective is necessary for the transition to a sustainable “humble world”. Using Taoist philosophy as an enabler, this paper explores the three principles of “interconnectedness and symbiosis”, “equality, balance and justice of all things” and “follow the Tzu-Jan and WuWei” to enrich sustainability transition studies and guide the construction for transition trajectories. By exploring the instrumental potential of Taoist-inspired principles in sustainability transitions, this paper provides a pre-paradigm complementary rationale for the “why” behind the “how” of achieving a sustainable future. The paper’s conclusions establish common ground for a transdisciplinary dialogue between Taoist philosophy and sustainability science (especially on sustainability transitions), strengthen the rationale for sustainability transitions, reveal transition commonalities compatible with Taoist philosophy, and add depth, richness, and inclusiveness to the cross-cultural knowledge base of sustainability transitions.
Assessing Agri-Food Waste Valorization Challenges and Solutions Considering Smart Technologies: An Integrated Fermatean Fuzzy Multi-Criteria Decision-Making Approach
Authors: Zhang Qing , Zhang Hongjuan
Published: July 2024

With the growth of the worldwide population and depletion of natural resources, the sustainable development of food systems cannot be ignored. The demand for agri-food waste valorization practices like high-value compounds production has received widespread attention; however, numerous challenges still exist. The present study aims to identify those challenges of agri-food waste valorization and propose effective solutions based on smart technologies. Based on a systematic review of the literature, the study combs existing challenges of agri-food waste valorization and constructs a six-dimension conceptual model of agri-food waste valorization challenges. Moreover, the study integrates a Fermatean fuzzy set (FFS) with multi-criteria decision-making (MCDM) methods including stepwise weight assessment ratio analysis (SWARA), decision-making trial and evaluation laboratory-interpretative structural modeling method (DEMATEL-ISM), and quality function deployment (QFD) to evaluate the weights of each dimension, find causal interrelationships among the challenges and fundamental ones, and rank the potential smart solutions. Finally, the results indicate that the “Government” dimension is the severest challenge and point out five primary challenges in agri-food waste valorization. The most potential smart solution is the “Facilitating connectivity and information sharing between supply chain members (S8)”, which may help government and related practitioners manage agri-food waste efficiently and also facilitate circular economy.
Enhance Stability of Successive Over-Relaxation Method and Orthogonalized Symmetry Successive Over-Relaxation in a Larger Range of Relaxation Parameter
Authors: Liu Chein-Shan , Chang Chih-Wen
Published: July 2024

The successive over-relaxation method and its symmetric extension to the symmetric successive over-relaxation method inherit the advantages of direct method and iterative method; they are simple iterative algorithms to solve the linear systems. We derive the equivalent forms of successive over-relaxation method and symmetric successive over-relaxation method in terms of residual vector and descent vector. Then a new orthogonalized technique is developed to stabilize the successive over-relaxation and symmetric successive over-relaxation methods. For the orthogonalized successive over-relaxation method, the range of relaxation parameter can be extended, even with a negative value. Based on the maximal projection technique, the sub-optimal value of the relaxation parameter for the orthogonalized successive over-relaxation method is derived to enhance its accuracy; the golden section search algorithm is used to find the minimal point of a derived merit function. The orthogonalized successive over-relaxation and orthogonalized symmetric successive over-relaxation methods show absolute convergence. According to the new form of successive over-relaxation method, a new approach of the accelerated over-relaxation method can be achieved by multiplying the descent vector of the successive over-relaxation method by a stabilization factor. Numerical examples confirm that the orthogonalized successive over-relaxation and orthogonalized symmetric successive over-relaxation methods outperform the successive over-relaxation and symmetric successive over-relaxation methods.
Symmetry and Analysis of Fluid Queueing Systems Driven by Non-Truncated Erlangian Service Queues
Authors: El-Paoumy Mahdy Shebl , Radwan Taha
Published: July 2024

This paper investigates the behavior of a fluid queue driven by a non-truncated Erlangian service queue, focusing on the symmetrical properties within the system. This study determines the formulations of the steady-state distribution of both the buffer content and stationary state probabilities of a background queueing system. The efficient generating function technique is employed, utilizing a new generalization of the modified Bessel function of the second kind. Performance metrics such as mean buffer content and throughput are calculated, and server utilization is examined. The results contribute to the understanding of fluid queueing systems and offer insights into their performance in various applications, including telecommunications, manufacturing systems, healthcare operations, and ecological models, where symmetry plays a critical role in optimizing performance.
Manifestation of Superfluidity in Atom-Number-Imbalanced Two-Component Bose–Einstein Condensates
Authors: Al-Marzoug Saeed Majed , Baizakov Bakhtiyor , Al Khawaja Usama , Bahlouli Hocine
Published: July 2024

Superfluid and dissipative regimes in the dynamics of a two-component quasi-one-dimensional Bose–Einstein condensate (BEC) with unequal atom numbers in the two components have been explored. The system supports localized waves of the symbiotic type owing to the same-species repulsion and cross-species attraction. The minority BEC component moves through the majority component and creates excitations. To quantify the emerging excitations, we introduce a time-dependent function called disturbance. Through numerical simulations of the coupled Gross–Pitaevskii equations with periodic boundary conditions, we have identified a critical velocity of the localized wave, above which a transition from the superfluid to dissipative regime occurs, as evidenced by a sharp increase in the disturbance function. The factors responsible for the discrepancy between the actual critical velocity and the speed of sound, expected from theoretical arguments, have been discussed.
Synthesis, X-ray Diffraction and Computational Druglikeness Evaluation of New Pyrrolo[1,2-a][1,10]Phenanthrolines Bearing a 9-Cyano Group
Authors: Cristea Mihaela , Popa Marcel Mirel , Shova Sergiu , Gdaniec Maria , Stefaniu Amalia , Draghici Constantin , Raduca Mihai , Banu Nicoleta Doriana , Dumitrascu Florea
Published: July 2024

New 9-cyano-pyrrolo[1,2-a][1,10]phenanthrolines 5a–d, obtained by a 1,3-dipolar cycloaddition reaction between the corresponding N-ylides of 1,10-phenanthrolinium bromides 2a–d, generated in situ and acrylonitrile as a dipolarophile, were investigated by single-crystal X-ray diffraction and computational studies to assess their druglikeness and evaluate their structure-activity properties. The non-covalent interactions present within the supramolecular landscape of the new 9-cyano-pyrrolo[1,2-a][1,10]phenanthrolines were correlated with the SAR investigations with the aim of estimating the propensity for bioactivity in these compounds.
Dynamic Analysis and Optimization of the Coupling System of Vibrating Flip-Flow Screen and Material Group
Authors: Gong Sanpeng , Wang Chenhao , Guo Jialiang , Qiao Ziqi , Zhao Guofeng , Fan Junkai , Xu Ningning , Wang Xinwen
Published: July 2024

Vibrating flip-flow screens (VFFSs) provide an effective solution for deeply screening moist and fine-grained minerals, and an accurate dynamic model of VFFSs is critical for its dynamic analysis and optimization, thereby improving the vibration stability and symmetry of VFFSs. In this paper, uniaxial tension, uniaxial compression, plane tension, and shear stress relaxation experiments were conducted on screen panel samples to illustrate that the third-order Ogden model and the generalized Maxwell model can accurately describe the hyperelasticity and viscoelasticity of screen panels. Then, the coupling method of finite element and discrete element was adopted to establish the simulation model of the screen panel and material group coupling system, and the dynamics of the coupling system under different loading conditions were explored. Finally, the dynamic model of the coupling system of VFFSs mass, screen panel, and material group was proposed, and the non-dominated sorting genetic algorithm II was applied to optimize the system’s dynamic response. The results reveal that the use of optimized shear springs can reduce the relative amplitude change rate of the main and floating screen frame by 44.30% while maintaining the periodic motion of the VFFSs under operation conditions, greatly enhancing the stability of the VFFSs system.
Transforming Controlled Duffing Oscillator to Optimization Schemes Using New Symmetry-Shifted G(t)-Polynomials
Authors: Hussain Fatima , Shihab Suha
Published: July 2024

This work introduces and studies the important properties of a special class of new symmetry-shifted Gt-olynomials (NSSG). Such polynomials have a symmetry property over the interval [−2, 0], with Gn−2,00=−1nGn−2,0(−2). An explicit formulation of an NSSG operational matrixwas constructed, which served as a powerful tool for obtaining the desired numerical solutions. Then, a modified direct computational algorithm was suggested for solving the controlled Duffing oscillator problem. The idea behind the proposed algorithm is based on using symmetry basis functions, which are important and have real-world applications in physics and engineering. The original controlled Duffing oscillator problem was transformed into a nonlinear quadratic programming problem. Finally, numerical experiments are presented to validate our theoretical results. The numerical results emphasize that the modified proposed approach reaches the desired value of the performance index, with a few computations and with the minimum order of the NSSG basis function when compared with the other existing method, which is an important factor to consider when choosing the appropriate method in other mathematical and engineering applications.