bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanical Properties and Durability of Textile Reinforced Concrete (TRC)—A Review
Authors: Wu Chao , Pan Yang , Yan Libo
Published: September 2023

Textile reinforced concrete (TRC) is an innovative structure type of reinforced concrete in which the conventional steel reinforcement is replaced with fibre textile materials. The thin, cost-effective and lightweight nature enable TRC to be used to create different types of structural components for architectural and civil engineering applications. This paper presents a review of recent developments of TRC. In this review, firstly, the concept and the composition of TRC are discussed. Next, interfacial bond behaviour between fibre textile (dry and/saturated with polymer) and concrete was analysed considering the effects of polymer saturation, geometry and additives in polymer of the textile. Then, the mechanical properties (including static and dynamic properties) of TRC were reviewed. For static properties, the mechanical properties including compression, tension, flexural, shear and bond properties are discussed. For dynamic properties, the impact, seismic and cyclic properties were investigated. Furthermore, the durability of TRC under different environmental conditions, i.e., temperature/fire, humidity and wet–dry cycles, freeze–thaw, chemical and fatigue were discussed. Finally, typical engineering applications of TRC were presented. The research gaps which need to be addressed in the future for TRC research were identified as well. This review aims to present the recent advancement of TRC and inspire future research of this advanced material.
Happiness and Transcendence: Heavenly or Earthly—Augustine and Bonhoeffer
Authors: Stoker Wessel
Published: September 2023

This article explores two views of happiness in Christianity. According to one view, happiness is heavenly, something that is attained only in eternal life. In the other view, happiness can be experienced on earth. Augustine (354–430) advocated the first view, in which life on earth is viewed as full of misery. The conception of happiness as earthly is articulated by Dietrich Bonhoeffer (1906–1945) in his Letters and Papers from Prison. This article clarifies both views by pointing to the use of different types of content regarding transcendence. The focus is on the comparison between the two views and their impact on daily life.
A New Exploration of the Dharma Lineage of Fazang (法藏): The Third Patriarch of the Huayan School
Authors: Ping Yanhong
Published: September 2023

According to available biography materials, Fazang had six disciples, namely, Hongguan (宏觀), Wenchao (文超), Zhiguang (智光) of Huayansi in the East Capital (東都華嚴寺), Zongyi (宗一) of He’ensi (荷恩寺), Huiyuan (慧苑) of Jingfasi (靜法寺), and Huiying (慧英) of Jingxingsi (經行寺). Most studies on Fazang’s dharma lineage have only focused on Huiyuan because only Huiyuan’s works on Buddhism are still extant. However, Huiyuan has been criticized because “he rebelled against his master’s doctrines, and then was taken placed by Chengguan (澄觀) who was born a hundred years later 弟子慧苑悉叛其說, 滅后百年而得澄觀”. Therefore, research on Huiyuan is not mainstream either. This has led to a lack of studies on the Huayan School during the time between Fazang and Chengguan. In fact, Wenchao, a disciple of Fazang, authored ten volumes of Zifang Yiwangji (自防遺忘集) and one volume of Huayanjing Guanmai Yiji (華嚴經関脈義記) (hereinafter referred to as Guanmai (関脈)), and Guanjian (関鍵: the number of its volumes is unknown, and its text is most likely to be part of Zifang Yiwangji); Fashen (法詵), a disciple of Huiyuan, wrote Huayanjing Shu(華嚴經疏, thirty-one volumes); Kuaiji Shenxiu (會稽神秀), a disciple of Fashen, wrote the Commentary on the Avataṃsaka Sūtra (Huayanjing Shu (華嚴經疏), thirty volumes) and Miaoli Yuanchengguan (妙理圓成觀, three volumes). However, research on these figures is limited. This paper aims to enrich and supplement the study of the Dharma lineage of Fazang by examining the writings of Wenchao, Fashen, and Kuaiji Shenxiu and the ideas revealed by their manuscripts, which may further contribute to the study of the history of Huayan Buddhism and the history of Buddhist schools.
Assessing ChatGPT’s Proficiency in Quantitative Risk Management
Authors: Hofert Marius
Published: September 2023

The purpose and novelty of this article is to investigate the extent to which artificial intelligence chatbot ChatGPT can grasp concepts from quantitative risk management. To this end, we enter a scholarly discussion with ChatGPT in the form of questions and answers, and analyze the responses. The questions are classics from undergraduate and graduate courses on quantitative risk management, and address risk in general, risk measures, time series, extremes and dependence. As a result, the non-technical aspects of risk (such as explanations of various types of financial risk, the driving factors underlying the financial crisis of 2007 to 2009, or a basic introduction to the Basel Framework) are well understood by ChatGPT. More technical aspects (such as mathematical facts), however, are often inaccurate or wrong, partly in rather subtle ways not obvious without expert knowledge, which we point out. The article concludes by providing guidance on the types of applications for which consulting ChatGPT can be useful in order to enhance one’s own knowledge of quantitative risk management (e.g., using ChatGPT as an educational tool to test one’s own understanding of an already grasped concept, or using ChatGPT as a practical tool for identifying risks just not on one’s own radar), and points out those applications for which the current version of ChatGPT should not be invoked (e.g., for learning mathematical concepts, or for learning entirely new concepts for which one has no basis of comparison to assess ChatGPT’s capabilities).
A Review of Parallel Robots: Rehabilitation, Assistance, and Humanoid Applications for Neck, Shoulder, Wrist, Hip, and Ankle Joints
Authors: Abarca Victoria E. , Elias Dante A.
Published: September 2023

This review article presents an in-depth examination of research and development in the fields of rehabilitation, assistive technologies, and humanoid robots. It focuses on parallel robots designed for human body joints with three degrees of freedom, specifically the neck, shoulder, wrist, hip, and ankle. A systematic search was conducted across multiple databases, including Scopus, Web of Science, PubMed, IEEE Xplore, ScienceDirect, the Directory of Open Access Journals, and the ASME Journal. This systematic review offers an updated overview of advancements in the field from 2012 to 2023. After applying exclusion criteria, 93 papers were selected for in-depth review. This cohort included 13 articles focusing on the neck joint, 19 on the shoulder joint, 22 on the wrist joint, 9 on the hip joint, and 30 on the ankle joint. The article discusses the timeline and advancements of parallel robots, covering technology readiness levels (TRLs), design, the number of degrees of freedom, kinematics structure, workspace assessment, functional capabilities, performance evaluation methods, and material selection for the development of parallel robotics. It also examines critical technological challenges and future prospects in rehabilitation, assistance, and humanoid robots.
High-Resolution Wideband Waveform Design for Sonar Based on Multi-Parameter Modulation
Authors: Duan Tong , Liang Hong , Dai Zezhou , Yue Lei
Published: September 2023

The design of transmitting waveforms is an effective way to improve the detection performance of sonar systems. For the problem of high-range sidelobe when designing reverberation-resistant waveforms, this paper proposes a high-resolution wideband composite waveform design with reverberation suppression performance and a waveform parameter improvement method. Firstly, we propose a novel wideband waveform, which utilizes linear frequency modulation (LFM) as the fundamental pulse, referred to as multi-parameter coded modulation LFM pulse (MPCM-LFM). Additionally, we deduce the wideband ambiguity function for waveform design. Then, we deduce the constraint relations of the waveform parameters for different sub-band overlaps, and according to the mathematical expressions of the obtained range ambiguity function, we analyze in detail the effects of the waveform parameters on the range ambiguity function under different constraints. Secondly, on the basis of the analysis, we also propose a hopping carrier frequency constraint rule to optimize the spectral performance, and the range sidelobe is restrained effectively in significant measure by this parameter improvement method. Finally, we analyze the computer simulation results. It is obvious that our proposed waveform parameter improvement method leads to good results. The proposed improved MPCM-LFM signal shows a “near-thumbtack” ambiguity function, whose sidelobe suppression performance is superior to other classical waveforms in the desired region, and it can realize high-precision parameter estimation. In addition, the proposed improved MPCM-LFM signal possesses good performance in detecting stationary and low Doppler targets in the background of reverberation.
Rapid Emergency Response Assessment of Earthquake-Induced Landslides Driven by Fusion of InSAR Deformation Data and Newmark Physical Models
Authors: Zeng Ying , Zhang Yingbin , Liu Jing , Wang Qingdong , Zhu Hui
Published: September 2023

Strong earthquakes induce a large number of secondary disasters, such as landslides, which bring serious challenges to post-disaster emergency rescue, and the rapid and accurate assessment of earthquake-induced landslide disasters is crucial for post-earthquake emergency rescue. This research aims to propose an emergency assessment model that is suitable for post-earthquake landslides, specifically targeting the first 72 h after an earthquake for emergency rescue guidance. The model combines remote sensing technology and the Newmark physical mechanics assessment model to form the InSAR Data–Newmark Physical Fusion Driver Model (IDNPM), which comprehensively considers the dynamic deformation of the ground surface and geological features. To validate the predictive performance of the IDNPM, the model is applied to the 5 September 2022 Luding earthquake event and the 8 August 2017 Jiuzhaigou earthquake event. The landslide qualitative evaluation, confusion matrix and Receiver Operating Characteristic (ROC) curve are utilized for quantitative assessment. The results show that the IDNPM can effectively reduce the false negative and false positive errors in landslide prediction by utilizing the SAR deformation information, and to a certain extent, it accounts for the dependence of the Newmark model on the accuracy of empirical formulas and geotechnical parameters. For the Luding earthquake event, the IDNPM shows an accuracy improvement of 10.296% compared to the traditional Newmark model. For the Jiuzhaigou earthquake event, there is also an improvement of 3.152%, with a promising generalization performance. The simplicity and ease of operation in constructing the model are accompanied by high reliability and accuracy. The research findings provide essential references for the development of post-earthquake landslide emergency prediction models and offer robust data support for emergency rescue and recovery efforts in earthquake-stricken areas in the future.
Ionosphere Total Electron Content Modeling and Multi-Type Differential Code Bias Estimation Using Multi-Mode and Multi-Frequency Global Navigation Satellite System Observations
Authors: Wang Qisheng , Zhu Jiaru , Hu Feng
Published: September 2023

With the rapid development of multi-mode and multi-frequency GNSSs (including GPS, GLONASS, BDS, Galileo, and QZSS), more observations for research on ionosphere can be provided. The Global Ionospheric Map (GIM) products are generated based on the observation of multi-mode and multi-frequency GNSSs, and comparisons with other GIMs provided by the ionosphere analysis centers are provided in this paper. Taking the CODE (Center of Orbit Determination in Europe) GIM as a reference during 30 days in January 2019, for the GIMs from JPL (Jet Puls Laboratory), UPC (Technical University of Catalonia), ESA (European Space Agency), WHU (Wuhan University), CAS (Chinese Academy of Sciences), and MMG (The multi-mode and multi-frequency GNSS observations used in this paper), the mean bias with respect to CODE products is 1.87, 1.30, −0.10, 0.01, −0.02, and −0.71 TECu, and the RMS is 2.12, 2.00, 1.33, 0.88, 0.88, and 1.30 TECu, respectively. The estimated multi-type DCB is also in good agreement with the DCB products provided by the MGEX.
Multispectral and Hyperspectral Image Fusion Based on Joint-Structured Sparse Block-Term Tensor Decomposition
Authors: Guo Hao , Bao Wenxing , Feng Wei , Sun Shasha , Mo Chunhui , Qu Kewen
Published: September 2023

Multispectral and hyperspectral image fusion (MHF) aims to reconstruct high-resolution hyperspectral images by fusing spatial and spectral information. Unlike the traditional canonical polyadic decomposition and Tucker decomposition models, the block-term tensor decomposition model is able to improve the quality of fused images using known endmember and abundance information. This paper presents an improved hyperspectral image fusion algorithm. Firstly, the two abundance matrices are combined into a single bulk matrix to promote structural sparsity by introducing the L2,1-norm to eliminate the scaling effects present in the model. Secondly, the counter-scaling effect is eliminated by adding the L2-norm to the endmember matrix. Finally, the chunk matrix and the endmember matrix are coupled together, and the matrix is reorganized by adding the L2,1-norm to the matrix to facilitate chunk elimination and solved using an extended iterative reweighted least squares (IRLS) method, focusing on the problem of the inability to accurately estimate the tensor rank in the chunk-term tensor decomposition model and the noise/artifact problem arising from overestimation of rank. Experiments are conducted on standard and local datasets, and the fusion results are compared and analyzed in four ways: visual result analysis, metric evaluation, time of the algorithm, and classification results, and the experimental results show that the performance of the proposed method is better than the existing methods. An extensive performance evaluation of the algorithms is performed by conducting experiments on different datasets. The experimental results show that the proposed algorithm achieves significant improvements in terms of reconstruction error, signal-to-noise ratio, and image quality compared with the existing methods. Especially in the case of a low signal-to-noise ratio, the proposed algorithm shows stronger robustness and accuracy. These results show that the proposed algorithm has significant advantages in dealing with multispectral high-resolution hyperspectral data.
Spatiotemporal Variations of Aerosol Optical Depth and the Spatial Heterogeneity Relationship of Potential Factors Based on the Multi-Scale Geographically Weighted Regression Model in Chinese National-Level Urban Agglomerations
Authors: Yuan Jiaxin , Wang Xuhong , Feng Zihao , Zhang Ying , Yu Mengqianxi
Published: September 2023

Investigating the spatiotemporal variation characteristics of aerosol optical depth (AOD) and its driving factors is essential for assessing atmospheric environmental quality and alleviating air pollution. Based on a 22-year high-resolution AOD dataset, the spatiotemporal variations of AOD in mainland China and ten national urban agglomerations were explored based on the Mann–Kendall trend test and Theil–Sen median method. Random forest (RF) and multiscale geographically weighted regression (MGWR) were combined to identify the main driving factors of AOD in urban agglomerations and to reveal the spatial heterogeneity of influencing factors. The results showed that areas with high annual average AOD concentrations were mainly concentrated in the Chengdu–Chongqing, Central Plains, Shandong Peninsula, and Middle Yangtze River urban agglomerations. Southern Beijing–Tianjin–Hebei and its surrounding areas revealed the highest AOD pollution during summer, whereas the worst pollution during the remaining three seasons occurred in the Chengdu–Chongqing urban agglomeration. Temporally, except for the Ha-Chang and Mid-Southern Liaoning urban agglomerations, where the average annual AOD increased, the other urban agglomerations showed a decreasing trend. Among them, the Central Plains, Middle Yangtze River, Guanzhong Plain, and Yangtze River Delta urban agglomerations all exhibited a decline greater than 20%. According to the spatial trends, most urban agglomerations encompassed much larger areas of decreasing AOD values than areas of increasing AOD values, indicating that the air quality in most areas has recently improved. RF analysis revealed that PM2.5 was the dominant factor in most urban clusters, followed by meteorological factors. MGWR results show that the influencing factors have different spatial scale effects on AOD in urban agglomerations. The socioeconomic factors and PM2.5 showed strong spatial non-stationarity with regard to the spatial distribution of AOD. This study can provide a comprehensive understanding of AOD differences among urban agglomerations, and it has important theoretical and practical implications for improving the ecological environment and promoting sustainable development.
A Sensitive Strain Sensor Based on Multi-Walled Carbon Nanotubes/Polyaniline/Silicone Rubber Nanocomposite for Human Motion Detection
Authors: Hosseini Seyedmajid , Norouzi Mohsen , Xu Jian
Published: September 2023

Strain sensors play a pivotal role in quantifying stress and strain across diverse domains, encompassing engineering, industry, and medicine. Their applicability has recently extended into the realm of wearable electronics, enabling real-time monitoring of body movements. However, conventional strain sensors, while extensively employed, grapple with limitations such as diminished sensitivity, suboptimal tensile strength, and susceptibility to environmental factors. In contrast, polymer-based composite strain sensors have gained prominence for their capability to surmount these challenges. The integration of carbon nanotubes (CNTs) as reinforcing agents within the polymer matrix ushers in a transformative era, bolstering mechanical strength, electrical conductivity, and thermal stability. This study comprises three primary components: simulation, synthesis of nanocomposites for strain sensor fabrication, and preparation of a comprehensive measurement set for testing purposes. The fabricated strain sensors, incorporating a robust polymer matrix of polyaniline known for its exceptional conductivity and reinforced with carbon nanotubes as strengthening agents, demonstrate good characteristics, including a high gauge factor, stability, and low hysteresis. Moreover, they exhibit high strain sensitivity and show linearity in resistance changes concerning applied strain. Comparative analysis reveals that the resulting gauge factors for composite strain sensors consisting of carbon nanotubes/polyaniline and carbon nanotubes/polyaniline/silicone rubber are 144.5 and 167.94, respectively.
Satisfaction Level of Slum Dwellers with the Assistance of the City Corporation during COVID-19: The Bangladesh Context
Authors: Seddiky Md. Assraf , Madeha Chowdhury Nuzhat , Ara Esmat
Published: September 2023

The COVID-19 pandemic has affected Bangladesh’s economic and social well-being in many ways. Slum dwellers, including day laborers, rickshaw pullers, CNG (Compressed Natural Gas) drivers, housemaids, hawkers, and street vendors, were the worst victims of this pandemic. Besides the voluntary organizations, the City Corporation (urban local government), instructed by the central government, took the initiative to distribute necessary food as well as financial assistance to the city dwellers to survive during the lockdown. The objective of this study is to identify the satisfaction level of slum dwellers with the assistance received from the City Corporation and obtain an idea of whether these supports were enough for them to maintain their livelihood. This is a mixed method research consisting of both qualitative and quantitative approaches. Researchers conducted a field survey in Sylhet City Corporation, in the northeastern part of Bangladesh, and collected primary data from one hundred and fifty-five respondents through a structured questionnaire along with an interview (semi-structured) schedule. Samples were selected by applying a multistage sampling technique. Researchers analyzed quantitative data using SPSS software and qualitative data using the thematic analysis method. Study findings reveal that nepotism, patron–client relation, corruption, unequal treatment, management flaws, low level of community engagement, political consideration, and lack of monitoring were the major issues in providing effective service delivery to slum dwellers during COVID-19. Citizen participation, well coordination, proper monitoring, impersonality, and good governance are indispensable for dealing with any crisis.
Exploring the Settlement Models of the Main Foreign Communities Residing in Italy (2003–2021)
Authors: Conti Cinzia , Mucciardi Massimo , Simone Maura
Published: September 2023

In the last few decades, the foreign resident population in Italy has grown considerably, showing a tendency towards a stable settlement. The spatial distribution of this population is an important key to better understanding the integration process in the host society. This paper aims to explore the diachronic evolution of the settlement models of the foreign population and the main ethnic groups usually classified as residents in Italy in the period 2003–2021. Towards this aim, we computed statistical global indices referring to evenness, concentration, and clustering dimension of residential segregation and ad hoc indices that regard territorial dimensions. One of the major novelties of the contribution lies in the attempt to compute these indices not only in reference to the major population group—i.e., the Italians—but also between foreign communities and considering the gender structure. The indices are then synthesised by a multivariate analysis (principal component analysis and cluster analysis). The results of this study show that (a) higher differences in terms of settlement models are found by comparing different minority groups rather than by comparing minorities to Italians; (b) the settlement models of each foreign citizenship remain almost stable over time despite their growth in both absolute and relative terms.
Coast Change: Understanding Sensitivity to Beach Loss for Coastal Tourism in the Colombian Caribbean
Authors: Portz Luana Carla , Pérez Torres Yacira Sheilla , Manzolli Rogério Portantiolo
Published: September 2023

Beach and sun tourism in the Colombian Caribbean is an extremely important activity that leads to social practices that generate recreational and economic activities directly impacting the environment. The research focuses on assessing the sensitivity to the loss of beaches as tourist resources in four locations within the Colombian Caribbean (Santa Verónica, Salinas del Rey, Bocatocino, and Las Arenas). The sensitivity indicator was developed using GIS to process variables such as the width of the usable beach, the presence of dunes, and rates of coastal erosion spanning from 2003 to 2019. Additionally, anthropic occupation was examined through satellite images. The results allowed for identifying vulnerability indices and recognizing the critical role of dunes in beach preservation. The study revealed that the analyzed beaches exhibited varying degrees of sensitivity. Notably, historical erosion rates and dunes were the most influential variables affecting sensitivity. In conclusion, understanding the sensitivity state concerning the loss of beach areas as tourist resources helps delineate stable sectors and those more susceptible to erosion processes. This knowledge proves invaluable in prioritizing the design and implementation of protective measures in areas requiring urgent attention.
Spatiotemporal Variation of Evapotranspiration and Its Driving Factors in the Urumqi River Basin
Authors: Ablikim Kamila , Yang Han , Mamattursun Azimatjan
Published: September 2023

Evapotranspiration (ET) is a key indicator of arid and semi-arid ecosystem processes and hydrological cycles. The study of basin-scale ET characteristics and drivers can provide a better understanding of regional water balance and energy cycles. This study used the Pixel Information Expert Engine platform based on MODIS (MOD16A2) data to extract the separate spatial and temporal characteristics of interannual and seasonal ET in the Urumqi River Basin in Xinjiang, China, over a 20-year period, from 2000 to 2020, and to analyze the influence of land-use data and altitude on ET in the basin. The average interannual ET in the watershed has had an increasing trend over the past two decades, varying from 126.57 mm to 247.66 mm, with the maximum ET in July and the minimum in December. On the seasonal scale, the ET trend is greatest in summer, followed by spring, and it is the least in winter. Spatially, the surface ET in the Urumqi River Basin is generally high in the upstream area and low in the downstream area, with the average multi-year ET throughout the basin falling within the range of 22.74–479.33 mm. The average ET for each type of land use showed that forest land had the highest ET and unused land the lowest. Analysis found that the effect of altitude on ET was more pronounced, with a significant increase in ET as altitude increases. Analysis of the drivers of ET change from 2000 to 2020 using the Optimal Parameters-based Geographical Detector model (OPGD) showed that the natural factors that had the greatest influence were, in descending order, temperature > vegetation cover > precipitation. Among the interacting factors, vegetation index with temperature, elevation, and precipitation and land use with elevation had a relatively greater influence on ET in the basin, and the effects of interacting factors were all greater than those of single factors.
Research on the Effect of Sand Barriers on Highways in Desert Areas on Sand Control
Authors: Wang Fang , Liu Shixiao , Jiang Yujia , Duan Weijia
Published: September 2023

Sand barriers are one of the essential measures used to prevent wind and sand disasters on expressways in desert areas. The article uses Fluent numerical simulation to consider different heights, as well as different spacing from two perspectives, and determine the ideal vertical height of sand barriers (porosity is fixed at 20%). Adding to existing wind and sand flow field research, our analysis of the wind speed and sand characteristics reveals the changing rules that affect a single group of high vertical sand barriers along the highway when considering different parameters and measuring the wind and sand performance. At the same time, we also use field research to verify the accuracy of numerical simulation. The study shows the following. (1) When the airflow passes through the single group of vertical sand barriers, it will form a deceleration zone, acceleration zone, turbulence zone and stabilization zone in different areas, and the overall distribution of the wind and sand flow field is in the shape of a “W”. (2) When the spacing is 4 H, the maximal wind speed in the transition area of the sand barriers is two to three times bigger than that when the spacing is 2 H, which is not conducive to the accumulation of sand particles. When the spacing is 1 H, the maximum wind speed of the two rows of sand barriers is two to three times bigger than that when the spacing is 2, and the two rows of sand barriers overlap in wind protection performance, reducing the overall protective capacity of the sand barriers. (3) As the height of the sand barriers continues to grow, the protective performance of the sand barriers is also enhanced. In the same position around the sand barriers, the wind speed under the 2.5 m sand barriers is lower than that under the 1.0 m sand barriers by 2–3 m/s. It is suggested that the height of the sand barriers should be controlled at 1.5–2.0 m in the actual deployment, and 2 H spacing should be used.
Participatory Geographic-Information-System-Based Citizen Science: Highland Trails Contamination due to Mountaineering Tourism in the Dolomites
Authors: Özbek Satı Elifcan , Lanzavecchia Alberto , Ferrarese Francesco
Published: September 2023

Environmental pollution is a persistent problem in terrestrial ecosystems, including remote mountain areas. This study investigates the extent and patterns of littering on three popular hiking trails among mountaineers and tourists in the Dolomites range located in northeastern Italy. The data was collected adopting a citizen science approach with the participation of university students surveying the trails and recording the macroscopic waste items through a GPS-based offline platform. The waste items were categorized according to their material type, usage, and geographical location, and the sorted data was applied to Esri GIS ArcMapTM 10.8.1. Even though littering is found to be widespread all along the trails, the outcomes of the study reveal diverse patterns based on density (cigarette butts, napkins and wet wipes, and mountain equipment littering) while highlighting the prevalence of plastic pollution. The other patterns include voluntary and involuntary littering and different hot spots of contamination, with lodge, barn, and cableway effects. The implications of littering patterns for alpine environment sustainability are discussed, and recommendations are drawn indicating the need for increased supervision for waste management and maintenance on-site, GIS tech-based participatory awareness raising, and zippered clothing and equipment design for sustainable practices of mountaineering in the area.
Integrated Anaerobic–Aerobic Moving Bed Biofilm Reactor and Biochar Adsorption for the Efficient Removal of Organic Matter and Nutrients from Brazilian Landfill Leachate
Authors: Faggiano Antonio , Motta Oriana , Ricciardi Maria , Cerrato Francesco , Garcia Junior Carlos Augusto , Fiorentino Antonino , Proto Antonio
Published: September 2023

Landfill leachate is a complex and highly polluted wastewater that poses significant environmental challenges worldwide. This study proposes an innovative approach to addressing this challenge by developing an integrated anaerobic–aerobic moving bed biofilm reactor (MBBR) and biochar adsorption method for the efficient removal of organic matter and nutrients from landfill leachate. The MBBR provides a suitable environment for the growth of microorganisms that can degrade organic matter and nutrients, while biochar adsorption removes any remaining pollutants that are not biodegradable. The performance of this integrated system was evaluated under different operating conditions, such as the hydraulic retention time and the organic loading rate, to optimize its efficiency and sustainability. The results showed that the integrated system achieved high removal efficiencies for chemical oxygen demand (COD), ammonium–nitrogen (NH4-N), and total phosphorus (TP), with maximum removal rates of 98.5% (77% after the anaerobic–aerobic MBBR and 85.4% after biochar adsorption), 91.2% (87% after the anaerobic–aerobic MBBR and 95.9% after biochar adsorption), and 99.9% (92% after the anaerobic–aerobic MBBR and 91.7% after biochar adsorption), respectively. The proposed method offers a promising solution for the treatment of landfill leachate, which is a critical environmental issue worldwide. This study also highlights the importance of developing more effective and sustainable methods for treating landfill leachate, which can have significant impacts on public health and the environment.
Road Performance Evaluation of Unburned Coal Gangue in Cold Regions
Authors: Feng Yan , Shi Liang , Ma Deng , Chai Xiaohe , Lin Chuang , Zhang Feng
Published: September 2023

At present, the cumulative storage of coal gangue in China exceeds 7 billion tons, covering an area of approximately 70 km2. The engineering application of unburned coal gangue is mainly utilized as concrete aggregate or cement production after the overfire process. However, it is prone to environmental pollution and has limited consumption. Using unburned coal gangue as roadbed filling not only alleviates the difficulty of land acquisition and soil collection for road constructions in mining areas, but also consumes a large amount of accumulated unburned coal gangue. This study conducts research on the road performance of unburned coal gangue. A series of laboratory tests have been performed to determine the physical and chemical properties of the unburned coal gangue and its performance as a filling material in cold regions. The influence of compaction effort, clay content, and number of freezing–thawing cycles on the mechanical performance of the unburned coal gangue was investigated. The typical unburned coal gangue in the Heilongjiang region is mainly composed of SiO2, Al2O3, and Fe2O3, which accounts for approximately 91% of the total mass. The unburned coal gangue meets the minimum CBR requirement of 8% after 7 freezing–thawing cycles. This study helps fully and reasonably utilize typical unburned coal gangue in the local area, providing technical support for achieving the overall goal of “green development, conservation and intensification, and low-carbon environmental protection”.
All Shades of Green: The Anatomy of the Fridays for Future Movement in Italy
Authors: Tomnyuk Viktoriia , Varavallo Giuseppe , Parisi Tania , Barbera Filippo
Published: September 2023

The Fridays for Future (FFF) movement has emerged as a critical force in environmental activism in response to pressing climate challenges. Despite its global prominence, few studies have delved deeply into the internal lines of thought within FFF communities. Our research fills this gap by exploring the diverse perspectives within the Italian FFF community and how these viewpoints influence the movement’s civic and political dedication to environmental sustainability. We are specifically interested in the shades of green, namely the internal variations of attitudes and beliefs of the FFF participants. We conducted empirical research with over 300 climate activists from the FFF movement in Italy, collecting data from March to October 2022 using a Web-based respondent-driven sampling technique (webRDS). The questionnaire, comprising 27 questions, covers topics such as political values, institutional trust, technological attitudes, climate knowledge, and personal lifestyles. We chose Multiple Correspondence Analysis (MCA) for our analysis due to its valuable mathematical properties, capability for producing insightful visual representations, and efficient computational features. The analysis reveals four distinct groups within the Italian FFF community based on their attitudes and actions related to environmental sustainability. These groups include Activist Equalizer, Disillusioned Technophobes, Institution Trustee, and Laissez-faire Solitaries, challenging the prevailing notion that FFF activists solely fit the profile of Activist Equalizers often depicted in media and public discourse. Findings offer a novel picture of the FFF movement in Italy and contribute to a better understanding of how the internal diversity of FFF impacts the efficacy and future trajectory of environmental activism. This research offers new insight into the political role of FFF and its potential influence on climate-related political actions.
Awareness and Utilization of Incentive Programs for Household Energy-Saving Renovations: Empirical Findings from Greece
Authors: Karytsas Spyridon , Theodoropoulou Eleni
Published: September 2023

The Greek policy targeting residential energy efficiency has launched the “Residential Energy Saving” financial incentives program to assist in achieving the goals related to reducing energy use and GHG emissions. Considering the research gaps of previous work, the present study examines the sociodemographic, dwelling, and geographical characteristics, and the environmental awareness and behavior that affect individuals’ (a) actual decision to perform an energy-saving renovation of their dwelling; this has been previously examined, but not in the Greek context, (b) awareness of the incentives program; this has not been addressed in previous research, and (c) utilization of the program; this has not been addressed in previous research. Accordingly, we performed a questionnaire-based survey in Greece in 2019 (n = 451). Based on the development of three binary logistic regression models, it is indicated that the decision to perform an energy-saving renovation is affected by ownership status, year of construction, income, and environmental behavior; awareness is affected by education level, environmental awareness, and residence location; use of the incentives program is affected by residence ownership and year of construction, presence of senior citizens and education level. The study’s results, indicating the determinants of energy-saving renovation decisions and awareness and utilization of financial incentives programs, can assist policymakers in planning financial incentives adapted to different characteristics, thus achieving improved awareness and utilization of such tools.
Can Unveiling the Relationship between Nutritional Literacy and Sustainable Eating Behaviors Survive Our Future?
Authors: Mortaş Hande , Navruz-Varlı Semra , Çıtar-Dazıroğlu Merve Esra , Bilici Saniye
Published: September 2023

The primary objective of this study was to explore the relationship between food and nutrition literacy and sustainable, healthy eating behaviors among young adults. This cross-sectional study took place in Ankara, the capital city of Turkey, involving 500 participants (265 females, 235 males) whose average age was 22.6 ± 3.97 years. A questionnaire was administered through face-to-face interviews, covering three sections: (1) general information, (2) the food and nutrition literacy instrument (FNLI), and (3) the sustainable and healthy eating behaviors scale (SHEBS). The females exhibited a higher FNLI score (94.8 ± 10.9) compared with the males (89.9 ± 13.1), with a statistically significant difference (p < 0.001). Statistically significant differences were observed in the mean SHEBS scores for the FNLI behavior sub-dimension among all three categories: inadequate (106.6 ± 32.7), limited (125.5 ± 23.6), and excellent (147.5 ± 28.8) (p < 0.05). The significant correlations of the FNLI score with various factors, including seasonal foods (0.163-unit increase per unit), avoidance of food waste (0.312-unit increase per unit), reduction in meat consumption (0.750-unit increase per unit), and education status (1.399-unit increase per unit) (p < 0.001) was revealed in the study. Based on the findings from this study, we can plan to promote sustainable resource utilization by developing educational materials in the field of nutrition.
The Integration of HBIM-SIG in the Development of a Virtual Itinerary in a Historical Centre
Authors: López-González Concepción , García-Valldecabres Jorge
Published: September 2023

The continuous increase in cultural tourism, together with the deficient planning of public use, increases the risk of heritage resource degradation. Currently, there are collaborative methodologies enabling all the agents involved in the conservation of a heritage site to work in a coordinated way (HBIM), such as in the management of public use. However, in this study, through a review of the scientific literature, the lack of a method and tool that allows sustainable conservation management and the planning of cultural tourism of heritage assets in a specific geographical environment is demonstrated. The objective of this research is thus to explore and identify the possibilities of interoperability between HBIM and GIS for the development of a protocol aimed at synchronizing the information concerning heritage architecture across the management and cultural tourism planning and preventive conservation. This protocol was implemented for three monumental buildings in the historic centre of the city of Valencia (Spain). This novel protocol provides a new technological system that fosters the cultural development and preservation and conservation of heritage assets through a single tool integrating HBIM and GIS.
Optimal Allocation of Photovoltaic Distributed Generations in Radial Distribution Networks
Authors: Ayanlade Samson Oladayo , Ariyo Funso Kehinde , Jimoh Abdulrasaq , Akindeji Kayode Timothy , Adetunji Adeleye Oluwaseye , Ogunwole Emmanuel Idowu , Owolabi Dolapo Eniola
Published: September 2023

Photovoltaic distributed generation (PVDG) is a noteworthy form of distributed energy generation that boasts a multitude of advantages. It not only produces absolutely no greenhouse gas emissions but also demands minimal maintenance. Consequently, PVDG has found widespread applications within distribution networks (DNs), particularly in the realm of improving network efficiency. In this research study, the dingo optimization algorithm (DOA) played a pivotal role in optimizing PVDGs with the primary aim of enhancing the performance of DNs. The crux of this optimization effort revolved around formulating an objective function that represented the cumulative active power losses that occurred across all branches of the network. The DOA was then effectively used to evaluate the most suitable capacities and positions for the PVDG units. To address the power flow challenges inherent to DNs, this study used the Newton–Raphson power flow method. To gauge the effectiveness of DOA in allocating PVDG units, it was rigorously compared to other metaheuristic optimization algorithms previously documented in the literature. The entire methodology was implemented using MATLAB and validated using the IEEE 33-bus DN. The performance of the network was scrutinized under normal, light, and heavy loading conditions. Subsequently, the approach was also applied to a practical Ajinde 62-bus DN. The research findings yielded crucial insights. For the IEEE 33-bus DN, it was determined that the optimal locations for PVDG units were buses 13, 25, and 33, with recommended capacities of 833, 532, and 866 kW, respectively. Similarly, in the context of the Ajinde 62-bus network, buses 17, 27, and 33 were identified as the prime locations for PVDGs, each with optimal sizes of 757, 150, and 1097 kW, respectively. Remarkably, the introduction of PVDGs led to substantial enhancements in network performance. For instance, in the IEEE 33-bus DN, the smallest voltage magnitude increased to 0.966 p.u. under normal loads, 0.9971 p.u. under light loads, and 0.96004 p.u. under heavy loads. These improvements translated into a significant reduction in active power losses—61.21% under normal conditions, 17.84% under light loads, and 33.31% under heavy loads. Similarly, in the case of the Ajinde 62-bus DN, the smallest voltage magnitude reached 0.9787 p.u., accompanied by an impressive 71.05% reduction in active power losses. In conclusion, the DOA exhibited remarkable efficacy in the strategic allocation of PVDGs, leading to substantial enhancements in DN performance across diverse loading conditions.
Coupling LSTM and CNN Neural Networks for Accurate Carbon Emission Prediction in 30 Chinese Provinces
Authors: Han Zhonghua , Cui Bingwei , Xu Liwen , Wang Jianwen , Guo Zhengquan
Published: September 2023

Global warming is a major environmental issue facing humanity, and the resulting climate change has severely affected the environment and daily lives of people. China attaches great importance to and actively responds to climate change issues. In order to achieve the “dual carbon” goal, it is necessary to clearly define the emission reduction path and scientifically predict future carbon emissions, which is the basis for setting emission reduction targets. To ensure the accuracy of data, this study applies the emission coefficient method to calculate the carbon emissions from the energy consumption in 30 provinces, regions, and cities in China from 1997 to 2021. Considering the spatial correlation between different regions in China, we propose a new machine learning prediction model that incorporates spatial weighting, namely, an LSTM-CNN combination model with spatial weighting. The spatial weighting explains the spatial correlation and the combined model is used to analyze the carbon emissions in the 30 provinces, regions, and cities of China from 2022 to 2035 under different scenarios. The results show that the LSTM-CNN combination model with four convolutional layers performs the best. Compared with other models, this model has the best predictive performance, with an MAE of 8.0169, an RMSE of 11.1505, and an R2 of 0.9661 on the test set. Based on different scenario predictions, it is found that most cities can achieve carbon peaking before 2030. Some cities need to adjust their development rates based on their specific circumstances in order to achieve carbon peaking as early as possible. This study provides a research direction for deep learning time series forecasting and proposes a new predictive method for carbon emission forecasting.
Systematic Study of Vibrational Spectra of Octahedral Rhenium Clusters {Re6S8-xBrx}Bry (x = 0, 1, 2, 3, 4) with Mixed Sulfur/Bromine Inner Ligands
Authors: Ledneva Alexandra Yu. , Ivanova Mariia N. , Poltarak Pavel A. , Yarovoy Spartak S. , Kolesov Boris A. , Fedorov Vladimir E. , Naumov Nikolay G.
Published: September 2023

A series of rhenium compounds with the octahedral cluster core {Re6S8-xBrx} (x = 0–4): with molecular and polymeric structure were obtained. In these compounds the cluster core composition varies monotonically, the geometry of the cluster and the rhenium coordination polyhedron are retained unchanged, while the symmetry of the cluster changes. The vibrational spectra (Raman and IR) were recorded and analyzed for compounds with all possible S/Br ratios in the cluster core. The group vibrations of clusters were attributed with the use of DFT calculations of vibrational spectra. It is shown that the set of main characteristic bands is retained in both ionic and polymeric compounds regardless of the composition and the symmetry of the cluster core while the observed vibration frequencies of these bands depend on the S/Br ratio in the cluster core. In particular, the group Re–S stretching vibrations (A1g(S8) and T2g(S8) modes) shifted to higher frequencies with the increase in the number of Br atoms in the cluster. The difference in the connectivity in polymeric compounds leads to an increase in the number of bands in the spectra and to the disappearance of the A1g(Br) modes.
Symmetry of Structures under Two-Dimensional Instability in a Finite-Height Horizontal Layer of Boiling Liquid
Authors: Zhukov Vladimir I. , Pavlenko Aleksandr N.
Published: September 2023

The two-dimensional instability of a horizontal layer of boiling liquid with a finite height was experimentally studied. In this layer, “vapor columns” rose at the corners of a square rectangular grid, and the symmetry of “vapor column” location on the heating surface was considered. The model adopts an approach to the boiling crisis from the side of both developed nucleate boiling and transitional boiling (the Zuber problem). When dealing with developed nucleate boiling, the layer of boiling liquid is considered in calculations as an isotropic homogeneous system (foam). It is shown how the conditions on the heating surface (capillary-porous coating) affect the external hydrodynamics of the liquid layer and, ultimately, the value of the critical heat flux. The calculation ratio obtained by approaching the boiling crisis from the side of developed nucleate boiling takes into account the dependence of the critical heat flux on the void fraction of the boiling liquid layer. A new solution to the boiling crisis problem is proposed when approaching the crisis from the side of transitional boiling (the Zuber problem). This new solution eliminates some shortcomings of the classical problem (in particular, the void fraction of the layer corresponds to the experiments).