bluuebunny/crossref_metadata_2025 huggingface dataset:
Ground Risk Assessment for Unmanned Aircraft Focusing on Multiple Risk Sources in Urban Environments
Authors: Li Qiyang , Wu Qinggang , Tu Haiyan , Zhang Jianping , Zou Xiang , Huang Shan
Published: February 2023

This paper investigates the risk quantification for Unmanned Aircraft (UA) in urban environments, focusing on the safety of ground people. An assessment methodology is proposed to quantify the flying risk, which indicates the ground fatalities resulted from different potential risk sources. With the knowledge of UA’s specifications and ground environments, the flying risk of the target UA flying in the target area could be evaluated from the combination of results from independent assessment procedures focusing on multiple potential risk sources with specific safety metrics. A study case to assess the flying risk of the Talon and the DJI Inspire 2 flying in one piece of the region in Chengdu is presented. From the assessment result, the airspace management strategies for both Talon and DJI Inspires 2 could be easily developed to guarantee the safety of ground people, therefore, this risk quantification method could be a general tool to support decision-making in safety work.
A Systematic Literature Review of the Risk Landscape in Fintech
Authors: Jain Ruchika , Kumar Satinder , Sood Kiran , Grima Simon , Rupeika-Apoga Ramona
Published: February 2023

The current study is primarily concerned with the developments in financial technology, or fintech, that have significantly altered traditional financial systems, focusing on several risk categories that have emerged in the financial technology sector’s digital ecosystem. This paper is a review of existing literature related to the risk landscape in fintech, particularly its publication trend, journal productivity, impact, affiliated organizations, and related themes. A bibliometric and content analysis of 84 articles collected through Scopus’ structured database is performed for a comprehensive review. It is revealed that financial technology development has decreased physical crime while simultaneously increasing cybercrime. Another challenge is the asymmetrical technology between financial markets and the relevant supervisors. These current issues necessitate the creation of an Act on Fintech to create a comprehensive legislative framework. The present study’s findings are helpful for academia and industry to aid their existing knowledge about fintech and associated risks, particularly its timeline, geographical spread, and development of coherent themes.
Dependency Modeling Approach of Cause-Related Mortality and Longevity Risks: HIV/AIDS
Authors: Bett Nicholas , Kasozi Juma , Ruturwa Daniel
Published: February 2023

Disaggregation of mortality by cause has advanced the development of life tables for life insurance and pension purposes. However, the assumption that the causes of death are independent is a challenge in reality. Furthermore, models that determine relationships among causes of death such as HIV/AIDS and their impact on mortality and longevity risks seem trivial or inflexible. To address these problems, we aim to determine and build an appropriate copula dependence model for HIV/AIDS against other causes of death in the presence of age, gender, and time. A bivariate copula model is proposed to capture the dependence structure of HIV/AIDS on life expectancy. This approach allows the fitting of flexible and interpretable bivariate copulas for a two-dimensional case. The dataset was derived from the World Health Organization database that constituted annualized death numbers, causes, age, gender, and years (2000 to 2019). Using Kendall’s tau and Pearson linear coefficient values, the survival Joe copulas proved to be a suitable model. The contribution and implication of this research are the quantification of the impact of HIV/AIDS on a life table, and, thus, the establishment of an alternative to the subjective actuarial judgment approach.
Firm Risk and Tax Avoidance in Vietnam: Do Good Board Characteristics Interfere Effectively?
Authors: Tran Trung Kien , Truong Minh Tuan , Bui Kim Tu , Duong Phung Duc , Huynh Minh Vuong , Nguyen Tran Thai Ha
Published: February 2023

This paper investigates the role of board characteristics in the relationship between tax avoidance behavior and corporate risk tolerance to elucidate the importance of corporate governance mechanisms. The applied methodology is System-GMM for 334 listed corporations in Vietnam from 2008 to 2020 to avoid endogenous problems in our models. The main findings are that higher (lower) corporate risk-taking is related to higher (lower) corporate tax avoidance if the size of the board of directors and the supervisory board are larger (lower) than six and three members, respectively. Furthermore, if the board independence ratio is lower than 48.63%, an increase in corporate risk-taking leads to increased tax avoidance. Our results support the argument that the influence of corporate risk-taking on tax avoidance behavior is governed by governance structure. Therefore, the practical implications will be towards building the optimal governance mechanism for enterprises in Vietnam.
Spectral Clustering of CRISM Datasets in Jezero Crater Using UMAP and k-Means
Authors: Pletl Alexander , Fernandes Michael , Thomas Nicolas , Rossi Angelo Pio , Elser Benedikt
Published: February 2023

In this paper, we expand upon our previous research on unsupervised learning algorithms to map the spectral parameters of the Martian surface. Previously, we focused on the VIS-NIR range of hyperspectral data from the CRISM imaging spectrometer instrument onboard NASA’s Mars Reconnaissance Orbiter to relate to other correspondent imager data sources. In this study, we generate spectral cluster maps on a selected CRISM datacube in a NIR range of 1050–2550 nm. This range is suitable for identifying most dominate mineralogy formed in ancient wet environment such as phyllosilicates, pyroxene and smectites. In the machine learning community, the UMAP method for dimensionality reduction has recently gained attention because of its computing efficiency and speed. We apply this algorithm in combination with k-Means to data from Jezero Crater. Such studies of Jezero Crater are of priority to support the planning of the current NASA’s Perseversance rover mission. We compare our results with other methodologies based on a suitable metric and can identify an optimal cluster size of six for the selected datacube. Our proposed approach outperforms comparable methods in efficiency and speed. To show the geological relevance of the different clusters, the so-called “summary products” derived from the hyperspectral data are used to correlate each cluster with its mineralogical properties. We show that clustered regions relate to different mineralogical compositions (e.g., carbonates and pyroxene). Finally the generated spectral cluster map shows a qualitatively strong resemblance with a given manually compositional expert map. As a conclusion, the presented method can be implemented for automated region-based analysis to extend our understanding of Martian geological history.
Evaluating Threatened Bird Occurrence in the Tropics by Using L-Band SAR Remote Sensing Data
Authors: Kobayashi Shoko , Fujita Motoko S. , Omura Yoshiharu , Haryadi Dendy S. , Muhammad Ahmad , Irham Mohammad , Shiodera Satomi
Published: February 2023

The biodiversity loss in Southeast Asia indicates an urgent need for long-term monitoring, which is lacking. Much attention is being directed toward bird diversity monitoring using remote sensing, based on relation to forest structure. However, few studies have utilized space-borne active microwave remote sensing, which has considerable advantages in terms of repetitive observations over tropical areas. Here, we evaluate threatened bird occurrence from L-band satellite data explaining forest structure in Sumatra, Indonesia. First, we identified L-band parameters with strong correlations with the forest layer structure, defined as forest floor, understory, and canopy layers. Then, we analyzed the correlation between threatened bird occurrence and L-band parameters identified as explaining forest structure. The results reveal that several parameters can represent the layers of forest floor, understory, and canopy. Subsequent statistical analysis elucidated that forest-dependent and threatened bird species exhibit significant positive correlations with the selected L-band parameters explaining forest floor and understory. Our results highlight the potential of applying microwave satellite remote sensing to evaluate bird diversity through forest structure estimation, although a more comprehensive study is needed to strengthen our findings.
Study on Influencing Factors of the Information Content of Satellite Remote-Sensing Aerosol Vertical Profiles Using Oxygen A-Band
Authors: Wang Yuxuan , Sun Xiaobing , Huang Honglian , Ti Rufang , Liu Xiao , Fan Yizhe
Published: February 2023

Aerosol vertical distribution is decisive and hard to be constrained. It is of great significance for the study of atmospheric climate and environment. Oxygen absorption A-bands (755–775 nm) provide a unique opportunity to acquire vertical aerosol profiles from satellites over a large spatial coverage. To investigate the ability of O2 A-bands in retrieving aerosol vertical distribution, the dependence of retrieval on satellite observation geometry, spectral resolution, signal-to-noise ratio (SNR), size distribution, and a priori knowledge is quantified using information content theory. This work uses the radiative transfer model UNL to simulate four aerosol modes and the instrument noise model. The simulations show that a small scattering angle leads to an increase in the total amount of observed aerosol profile information, with the degrees freedom of signal (DFS) of a single band increasing from 0.4 to 0.85 at high spectral resolution (0.01 nm). The total DFS value of O2 A-bands varies accordingly between 1.2–2.3 to 3.8–5.1 when the spectral resolution increases from 1 nm to 0.01 nm. The spectral resolution has a greater impact on DFS value than the impact from SNR (an improvement of roughly 41–53% resulted from the change in spectral resolution and the SNR led to 13–18%). The retrieval is more sensitive to aerosols with a coarse-dominated mode. The improvement in spectral resolution on information acquisition is demonstrated using the DFS and the posterior error at various previous errors and resolutions.
An Unsupervised Learning Approach for Wayside Train Wheel Flat Detection
Authors: Mohammadi Mohammadreza , Mosleh Araliya , Vale Cecilia , Ribeiro Diogo , Montenegro Pedro , Meixedo Andreia
Published: February 2023

One of the most common types of wheel damage is flats which can cause high maintenance costs and enhance the probability of failure and damage to the track components. This study aims to compare the performance of four feature extraction methods, namely, auto-regressive (AR), auto-regressive exogenous (ARX), principal component analysis (PCA), and continuous wavelet transform (CWT) capable of automatically distinguishing a defective wheel from a healthy one. The rail acceleration for the passage of freight vehicles is used as a reference measurement to perform this study which comprises four steps: (i) feature extraction from acquired responses using the specific feature extraction methods; (ii) feature normalization based on a latent variable method; (iii) data fusion to enhance the sensitivity to recognize defective wheels; and (iv) damage detection by performing an outlier analysis. The results of this research show that AR and ARX extraction methods are more efficient techniques than CWT and PCA for wheel flat damage detection. Furthermore, in almost every feature, a single sensor on the rail is sufficient to identify a defective wheel. Additionally, AR and ARX methods demonstrated the potential to distinguish a defective wheel on the left and right sides. Lastly, the ARX method demonstrated robustness to detect the wheel flat with accelerometers placed only in the sleepers.
Urban Traffic Noise Analysis Using UAV-Based Array of Microphones
Authors: Minea Marius , Dumitrescu Cătălin Marian
Published: February 2023

(1) Background: Transition to smart cities involves many actions in different fields of activity, such as economy, environment, energy, government, education, living and health, safety and security, and mobility. Environment and mobility are very important in terms of ensuring a good living in urban areas. Considering such arguments, this paper proposes monitoring and mapping of a 3D traffic-generated urban noise emissions using a simple, UAV-based, and low-cost solution. (2) Methods: The collection of relevant sound recordings is performed via a UAV-borne set of microphones, designed in a specific array configuration. Post-measurement data processing is performed to filter unwanted sound and vibrations produced by the UAV rotors. Collected noise information is location- and altitude-labeled to ensure a relevant 3D profile of data. (3) Results: Field measurements of sound levels in different directions and altitudes are presented in the paperwork. (4) Conclusions: The solution of employing UAV for environmental noise mapping results in being minimally invasive, low-cost, and effective in terms of rapidly producing environmental noise pollution maps for reports and future improvements in road infrastructure.
A Novel Type of Boundary Extraction Method and Its Statistical Improvement for Unorganized Point Clouds Based on Concurrent Delaunay Triangular Meshes
Authors: He Xiuzhi , Wang Rongqi , Feng Chao , Zhou Xiaoqin
Published: February 2023

Currently, three-dimensional (3D) laser-scanned point clouds have been broadly applied in many important fields, such as non-contact measurements and reverse engineering. However, it is a huge challenge to efficiently and precisely extract the boundary features of unorganized point cloud data with strong randomness and distinct uncertainty. Therefore, a novel type of boundary extraction method will be developed based on concurrent Delaunay triangular meshes (CDTMs), which adds the vertex-angles of all CDTMs around a common data point together as an evaluation index to judge whether this targeted point will appear at boundary regions. Based on the statistical analyses on the CDTM numbers of every data point, another new type of CDTM-based boundary extraction method will be further improved by filtering out most of potential non-edge points in advance. Then these two CDTM-based methods and popular α-shape method will be employed in conducting boundary extractions on several point cloud datasets for comparatively analyzing and discussing their extraction accuracies and time consumptions in detail. Finally, all obtained results can strongly demonstrate that both these two CDTM-based methods present superior accuracies and strong robustness in extracting the boundary features of various unorganized point clouds, but the statistically improved version can greatly reduce time consumption.
Ultrasonic High-Resolution Imaging and Acoustic Tweezers Using Ultrahigh Frequency Transducer: Integrative Single-Cell Analysis
Authors: Jung Hayong , Shung K. Kirk , Lim Hae Gyun
Published: February 2023

Ultrasound imaging is a highly valuable tool in imaging human tissues due to its non-invasive and easily accessible nature. Despite advances in the field of ultrasound research, conventional transducers with frequencies lower than 20 MHz face limitations in resolution for cellular applications. To address this challenge, we employed ultrahigh frequency (UHF) transducers and demonstrated their potential applications in the field of biomedical engineering, specifically for cell imaging and acoustic tweezers. The lateral resolution achieved with a 110 MHz UHF transducer was 20 μm, and 6.5 μm with a 410 MHz transducer, which is capable of imaging single cells. The results of our experiments demonstrated the successful imaging of a single PC-3 cell and a 15 μm bead using an acoustic scanning microscope equipped with UHF transducers. Additionally, the dual-mode multifunctional UHF transducer was used to trap and manipulate single cells and beads, highlighting its potential for single-cell studies in areas such as cell deformability and mechanotransduction.
A Gated Multiscale Multitask Learning Model Using Time-Frequency Representation for Health Assessment and Remaining Useful Life Prediction
Authors: Wu Tong , Chen Tengpeng
Published: February 2023

Health assessment and remaining useful life prediction are usually seen as separate tasks in industrial systems. Some multitask models use common features to handle these tasks synchronously, but they lack the usage of the representation in different scales and time-frequency domain. A lack of balance also exists among these scales. Therefore, a gated multiscale multitask learning model known as GMM-Net is proposed in this paper. By using the time-frequency representation, GMM-Net can obtain features of different scales via different kernels and compose the features by a gating network. A detailed loss function whose weight can be searched in a smaller scale is designed. The model is tested with different weights in the total loss function, and an optimal weight is found. Using this optimal weight, it is observed that the proposed method converges to a smaller loss and has a smaller model size than long short-term memory (LSTM) and gated recurrent unit (GRU) with less training time. The experiment results demonstrate the effectiveness of the proposed method.
Segmentation of Structural Elements from 3D Point Cloud Using Spatial Dependencies for Sustainability Studies
Authors: Ntiyakunze Joram , Inoue Tomo
Published: February 2023

The segmentation of point clouds obtained from existing buildings provides the ability to perform a detailed structural analysis and overall life-cycle assessment of buildings. The major challenge in dealing with existing buildings is the presence of diverse and large amounts of occluding objects, which limits the segmentation process. In this study, we use unsupervised methods that integrate knowledge about the structural forms of buildings and their spatial dependencies to segment points into common structural classes. We first develop a novelty approach of joining remotely disconnected patches that happened due to missing data from occluding objects using pairs of detected planar patches. Afterward, segmentation approaches are introduced to classify the pairs of refined planes into floor slabs, floor beams, walls, and columns. Finally, we test our approach using a large dataset with high levels of occlusions. We also compare our approach to recent segmentation methods. Compared to many other segmentation methods the study shows good results in segmenting structural elements by their constituent surfaces. Potential areas of improvement, particularly in segmenting walls and beam classes, are highlighted for further studies.
Real-Time Compensation for SLD Light-Power Fluctuation in an Interferometric Fiber-Optic Gyroscope
Authors: Zheng Shijie , Ren Mengyu , Luo Xin , Zhang Hangyu , Feng Guoying
Published: February 2023

An interferometric fiber-optic gyroscope (IFOG) demodulates a rotation signal via interferometric light intensity. However, the working environments of IFOGs typically involve great uncertainty. Fluctuations in temperature, air pressure, electromagnetic field, and the power system all cause the power of the superluminescent diode (SLD) light source to fluctuate as well. In this invited paper, we studied the effects of SLD power fluctuation on the dynamic and static performance characteristics of a gyro system through the use of a light-power feedback loop. Fluctuations of 0.5 mA, 1 mA, and 5 mA in the SLD source entering the IFOG caused zero-bias stability to be 69, 135, and 679 times worse. We established an effective method to monitor power fluctuations of SLD light sources and to compensate for their effects without increasing hardware complexity or system cost. In brief, we established a real-time power-sensing and -compensating system. Experimental results showed that for every 0.1 mA increase in the fluctuation amplitude of the driving current, the zero-bias stability became 4 to 7 times worse, which could be reduced about 95% through the use of SLD power compensation.
Effect of Waveguide Aperture and Distance on Microwave Treatment Performance in Rock Excavation
Authors: Chen Fangfang , Wu Zhanqiang , Zhang Zhiqiang
Published: February 2023

Rock burst is a common hazard during tunnel excavation in high-stress and hard rock strata. Microwave-assisted breaking has a great potential application in hard rock tunnel excavation, reducing the possibility of rock burst, and how to reasonably make the application on the TBM cutterhead is one of the critical issues. The waveguide aperture and distance between the rock face and waveguide have serious effects on its performance. In this paper, based on the arrangement of the microwave waveguide of the TBM cutterhead and the actual excavation situation, considering the reflection of microwave energy by the metal cutterhead and the scattering state of electromagnetic waves at the rock surface irradiation, a 2D model of rock irradiated by microwaves is established. The effects of waveguide aperture and distance on microwave irradiation performance of rock are studied, considering three different waveguide types: convergent waveguide, rectangular waveguide, and horn waveguide. The results show that the maximum temperature is located on the rock irradiation surface, rather than inside the rock. The rock temperature decreases in a cosine pattern with irradiation distance, rather than in linearity, which is consistent with the characteristics of electromagnetic wave propagation. The interval of irradiation distance where the rock temperature local maximum value appears is 1/4 of the electromagnetic wavelength, corresponding to the crest and trough of the electromagnetic wave. The rock temperature at the wave trough distance is lower than that of the wave crest distance, but the high-temperature zone is wider. In the range of 50~200 mm waveguide apertures, the rock temperature and damage decrease with the increase in waveguide aperture when irradiated at the crest distance, while the valley distance is opposite. A convergent waveguide and short irradiation distance enhance the energy focusing performance, so the temperature rise characteristics and rock damage are more concentrated. A large-waveguide-aperture horn waveguide and long irradiation distance form a wide range of high-temperature zones and rock damages.
Impact and Assessment of Suspension Stiffness on Vibration Propagation into Vehicle
Authors: Burdzik Rafał
Published: February 2023

The impact of transport-induced vibrations on people is a particularly important problem. Sudden or intensifying vibration phenomena of a local nature may compromise safety, especially in transport. The paper addresses the results of research on the impact of spring stiffness parameters on the propagation of vibrations in the vehicle structure using simple amplitude and frequency measures. The use of the developed method of selective multi-criteria analysis of frequency bands made it possible to compare the vibrations recorded in the vehicle with a new or worn coil spring. The results of the present study allow the development of a large data base in which all signals are classified by the exploitation parameters and location of the propagation of vibration in the vehicle. The most important findings and achievements of the presented study are the testing of actual suspension components with real damage under controlled conditions, the identification of the vibration propagation path from the wheel to the driver and passenger feet, the quantitative comparison of vibrations affecting humans in the vehicle (through the feet), and the frequency decomposition of vibration for selected bands. These findings improve the proper interpretation of the developed measures and, as a result, the difficulties in using this knowledge at the engineering level, for example, in the design and construction improvement stage. Therefore, innovation points and engineering significances are a method of selective multi-criteria analysis of frequency bands and have potential applications in diagnostics and the design of suspension systems and in terms of passengers’ comfort.
How Did the COVID-19 Pandemic and Digital Divide Impact Ciganos/Roma School Pathways?
Authors: Mourão Susana , Pinheiro Sara , Mendes Maria Manuela , Caetano Pedro , Magano Olga
Published: February 2023

The COVID-19 pandemic forced the Portuguese government to declare various lockdowns between 2020 and 2022. The first State of Emergency was enforced in March 2020, in which face-to-face classroom teaching was repeatedly interrupted. At that time, families were expected to provide the necessary supplies for digital learning, with some support from the government, municipalities, civil society, and local institutions. Nevertheless, many families already lived under precarious conditions before the pandemic, and so the lockdown measures increased their vulnerability, with a probable impact on student school attendance and conditions enabling academic success. Since Ciganos/Roma are part of this vulnerable population, we intend to explore how the COVID-19 pandemic impacts the school pathways of these students, namely in secondary education, where they represent a minority group. The data are derived from a variety of qualitative sources collected during research carried out in the two Metropolitan Areas in Portugal. The COVID-19 pandemic affected the youngsters’ access to classes and their motivation to attend school, and opens the discussion about how because of the government’s universal measures, by failing to consider social diversity, in particular Ciganos/Roma Ciganos/Roma families, this pandemic crisis may disproportionally affect the education of their children and youth. The findings highlight, firstly, that these impacts continue to be rendered invisible and naturalized in the public sphere and, secondly, that the measures and legislation underlying the pandemic effects continue not to include Ciganos in policymaking processes.
Violence against Women during the COVID-19 Pandemic: From Children to the Elderly
Authors: Soeiro Cristina , Ribeiro Rita , Almeida Iris , Saavedra Rosa , Caridade Sónia , Oliveira Ana , Santos Manuela
Published: February 2023

Women of all ages can be exposed to violence both within and outside of the home, especially in the context of the COVID-19 pandemic. The purpose of this study is to analyze violence against women (VAW) before and during the first year of the pandemic in Portugal. Crimes perpetrated against female victims from 17 years old and younger to 65 years old and older were analyzed by comparing requests for help in 2019 and 2020. A total of 12,045 requests for help for VAW were received by the Portuguese Association for Victim Support and analyzed in the current study. The findings reveal a 16% increase in requests for help in 2020 and a 95% increase when the lockdown was implemented. That said, the most reported, intimate partner violence (IPV), showed a decrease of 5% in 2020. Furthermore, compared to 2019, requests for help concerning criminal offenses involving psychological violence in non-IPV contexts increased 79% in 2020, especially for victims 17 years old or younger (116%), and attempted femicide/femicide requests for help increased 53%. We are still in the early stages of understanding how the pandemic will affect this situation. Future directions concerning support of female victims during the pandemic are outlined.
Green Synthesis and Characterization of Zinc Oxide Nanoparticles Using Larrea tridentata Extract and Their Impact on the In-Vitro Germination and Seedling Growth of Capsicum annuum
Authors: Sánchez-Pérez Daniela Monserrat , Flores-Loyola Erika , Márquez-Guerrero Selenne Yuridia , Galindo-Guzman Magdalena , Marszalek Jolanta E.
Published: February 2023

The application of green methods in the synthesis of nanoparticles using plants is a cost-effective and eco-friendly approach. Zinc oxide nanoparticles are of great importance due to their versatile properties. The conditions of synthesis strongly influence the characteristics and functionality of the nanoparticles. The present work studied the biological, green synthesis of zinc oxide nanoparticles (ZnONPs) in the presence of different concentrations of ethanolic extract of Larrea tridentata (10, 20, and 30 mg/mL). The time of the formation of nanoparticles was evaluated at different temperatures and pH values of the reaction medium. The formation of ZnONPs was confirmed by ultraviolet-visible (UV-Vis) and Fourier transform infrared spectroscopies (FT-IR), as well as scanning electron microscopy (SEM). X-ray diffraction analysis (XDR) determined the crystallographic structure of the nanoparticles. Obtained ZnONPs had a size range of 18 to 40 nm. The temperature, reaction time, and pH significantly influenced the nanoparticles’ morphology, size, and aggregation. The impact of chosen ZnONPs was tested on the germination of serrano chili seeds (Capsicum annuum). At 100 ppm, the nanoparticles improved germination percentage, vigor, and seedlings’ growth parameters.
A Numerical Approach to Evaluating Groundwater Vulnerability to Seawater Intrusion on Jeju Volcanic Island, South Korea
Authors: Lee Dongyeop , Park Jonghoon , Lee Hyun A. , Woo Nam C.
Published: February 2023

Seawater intrusion (SWI) is a critical issue for coastal aquifers, especially in islands where groundwater is the sole source of water supply. The objective of this study was to develop a straightforward approach to evaluating groundwater vulnerability to SWI, using a statistical method with spatial analyses applied to the four basins of Jeju volcanic island. In this study, five factors were parametrized, including hydraulic conductivity, groundwater level, distance from shoreline to wells, well depth and groundwater use. These parameters were spatially interpolated and correlated with groundwater electrical conductivity as a proxy for groundwater salinization, resulting in three parameters with significant relations: groundwater use, well depth, and groundwater level. Then, a numerical model for the SWI vulnerability assessment was constructed using ratings and weights, and by evaluating the vulnerability as weak, moderate and high with a numerical index. Regional conditions, including major land-use types, industrial activities, population and the degree of urbanisation, could affect parameters differently at each region. Based on the percentage of area with a high vulnerability, regions of Jeju Island followed the order of eastern > northern > western > southern, indicating that preventive measures for SWI and its influencing parameters could be applied more effectively in certain regions.
Investigation of the Physical Mechanical Properties and Durability of Sustainable Ultra-High Performance Concrete with Recycled Waste Glass
Authors: Amin Mohamed , Agwa Ibrahim Saad , Mashaan Nuha , Mahmood Shaker , Abd-Elrahman Mahmoud H.
Published: February 2023

Construction material sustainability and waste reuse have emerged as significant environmental issues. Concrete is widely used in the building and engineering fields. Ultra-high performance concrete (UHPC), which has remarkably high mechanical properties, has become one of the most common concrete varieties in recent years. As a result, substantial amounts of Portland cement (PC) are frequently used, raising the initial cost of UHPC and restricting its broad use in structural applications. A significant amount of CO2 is produced and a large amount of natural resources are consumed in its production. To make UHPC production more eco-friendly and economically viable, it is advised that the PC in concrete preparations be replaced with different additives and that the recycled aggregates from various sources be substituted for natural aggregates. This research aims to develop an environmentally friendly and cost-effective UHPC by using glass waste (GW) of various sizes as an alternative to PC with replacement ratios of 0%, 10%, 20%, 30%, 40%, and 50% utilizing glass powder (GP). Fine aggregate “sand (S)” is also replaced by glass particles (G) with replacement ratios of 0%, 50%, and 100%. To accomplish this, 18 mixes, separated into three groups, are made and examined experimentally. Slump flow, mechanical properties, water permeability, and microstructural characteristics are all studied. According to the results, increasing the S replacement ratio with G improved workability. Furthermore, the ideal replacement ratios for replacing PC with GP and S with G to achieve high mechanical properties were 20% and 0%, respectively. Increasing the replacement rate of GP in place of PC at a fixed ratio of G to S resulted in a significant decrease in water permeability values. Finally, a microstructural analysis confirms the experimental findings. In addition, PC100-S100 was the best mix compared to PC100-S50 G50 and PC100-G100.
How Do House Prices and Financial Expenditure Affect Birth Rate? New Evidence from the Dynamic Threshold Panel Model
Authors: Yan Lifang , Ye Wenzhong
Published: February 2023

Owing to low birth rate, the demographic dividend in China is disappearing. It is thus of great significance to study the regional differences and influencing factors of the birth rate, further proposing political advices on how to raise birth rate. In this study, 31 administrative units in China were chosen as the regional targets, and the nonlinear effects of house prices and financial expenditure on birth rate were extensively investigated by using a dynamic panel threshold model. A dynamic panel threshold model with disposable income as threshold variable, house price as independent variable, financial expenditure that concluding education funds and social security as variables influenced by threshold variable was established, which can effectively handle regional heterogeneity and endogeneity problems. The results show that the effect of financial expenditure on birth rate is complex, exhibiting a “S” shape for education funds and an inverted “U” shape for social security. Previous controversial conclusions on the impact of financial expenditure on birth rate in the literature can thereby be reasonably explained. It shows that birth rate is influenced by the lagged birth rate and house prices have negative effects on birth rate. The rationality of the present results has been verified by using consumption and input-output economic theories. Based on the empirical investigation, specific suggestions have been proposed in order to acquire sustainable development of population.
Experimental and Theoretical Studies of the Corrosion Inhibition Performance of a Quaternary Phosphonium-Based Ionic Liquid for Mild Steel in HCl Medium
Authors: Guo Lei , Huang Yue , Wu Yundong , Shi Wei , Abbas Faheem , Lin Yuanhua , Marzouki Riadh , Zheng Xingwen
Published: February 2023

The corrosion inhibition performance of a quaternary phosphonium-based ionic liquid, i.e., hexadecyltriphenylphosphonium bromide (HPP), on mild steel in 1 M HCl solution was investigated by electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization (PDP) methods. The surface characterization of mild steel was examined by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS). The results revealed that the inhibition efficiency increases with its increasing concentration, and it can reach up to 99.1% at the concentration of 0.07 mM HPP. PDP data showed that the absorption of HPP conformed to Langmuir adsorption, which served as a mixed-type inhibitor, involving chemisorption and physisorption. SEM analysis confirmed the formation of barrier film on the metal surface, inhibiting the acid attack. Moreover, density functional theory (DFT) calculations and molecular dynamics (MD) simulations were conducted to elucidate the adsorption mechanism of inhibitor molecules on the mild steel surface. A match between the experimental and theoretical findings was evidenced.
Forecasting Waste Mobile Phone (WMP) Quantity and Evaluating the Potential Contribution to the Circular Economy: A Case Study of Turkey
Authors: Ozsut Bogar Zeynep , Gungor Askiner
Published: February 2023

Information and communication technology (ICT)-based products have a significant effect on increasing levels of waste electrical and electronic equipment (WEEE) or electronic waste (e-waste) due to their shorter lifespan as a result of rapid technological changes. Mobile phones are the most popular ICT products, and their market share is increasing gradually. Therefore, effective management of waste mobile phones (WMP) is sought as their recovery brings enormous economic and regulatory benefits. Forecasting the quantities of WMP and their recoverable material content generates valuable data for the related stakeholders in the circular economy (CE) in the design and management of their supply chain networks. This paper presents an approach to determining the WMP quantity for Turkey considering the system from sales to end-of-life (EOL) stages and the years between 2001 and 2035. The proposed model includes two main parts: estimation and forecasting. Firstly, the generated WMP quantity is estimated based on dynamic lifespan and sales using the Distribution Delay (DD) Method considering the years from 2001 to 2020. To select the most suitable model for future projection, seven different time series methods (e.g., Simple Exponential Smoothing, Holt’s, Logistics, Gompertz, Logarithmic, Bass, and ARIMA models) are considered to estimate the generated WMP. For the given data, the Holt’s Method is determined to be the best method to forecast the WMP quantities for the years from 2021 to 2035. In addition, waste materials amount and revenue potentials are estimated for the years from 2001 to 2035. The WMP for Turkey is expected to be approximately 11.5 million units and has a 52 million US$ revenue potential in 2035. The present study contributes to the literature, as it is the first holistic forecasting study on the quantification of WMPs in Turkey. Moreover, since WMPs include remarkable recovery potential in terms of CE, the data and findings of this study may help policymakers, governments, producers, consumers, and all stakeholders to establish effective e-waste management approaches.
Energy Consumption and Carbon Dioxide Production Optimization in an Educational Building Using the Supported Vector Machine and Ant Colony System
Authors: Anupong Wongchai , Muda Iskandar , AbdulAmeer Sabah Auda , Al-Kharsan Ibrahim H. , Alviz-Meza Aníbal , Cárdenas-Escrocia Yulineth
Published: February 2023

Buildings account for sixty percent of the world’s total annual energy consumption; therefore, it is essential to find ways to reduce the amount of energy used in this sector. The road administration organization in Jakarta, Indonesia, utilized a questionnaire as well as the insights of industry experts to determine the most effective energy optimization parameters. It was decided to select variables such as the wall and ceiling materials, the number and type of windows, and the wall and ceiling insulation thickness. Several different modes were evaluated using the DesignBuilder software. Training the data with a supported vector machine (SVM) revealed the relationship between the inputs and the two critical outputs, namely the amount of energy consumption and CO2 production, and the ant colony algorithm was used for optimization. According to the findings, the ratio of the north and east windows to the wall in one direction is 70 percent, while the ratio of the south window to the wall in the same direction ranges from 35 to 50 percent. When the ratio and percentage of the west window to the west wall is between 60 and 70 percent, the amount of produced energy and CO2 is reduced to negligible levels.
Social Issues and Challenges among Oil Palm Smallholder Farmers in Malaysia: Systematic Literature Review
Authors: Siti-Dina Razman Pahri , Er Ah Choy , Cheah Wai Yan
Published: February 2023

Oil palm smallholder farmers are among the key players and are mostly affected by social challenges to the sustainability of the oil palm sector in Malaysia. Previous literature reviews showed a lack of social studies compared to studies of the economy and environment regarding the sustainability of the oil palm industry. Therefore, a systematic literature review focused on the context of social issues and challenges reported by Malaysian oil palm smallholder farmers is presented. The PRISMA standard is applied as the foundation for the systematic literature review writing procedure. A total of 12 papers were chosen out of 340 from Web of Science, Scopus, and Google Scholar. They covered three themes, including (i) attitudes, (ii) education, and (iii) the welfare of oil palm smallholder farmers. This systematic literature review has revealed that the social issues and challenges are closely related to the respondents’ demographics, such as the study location, the level of education, and the size of the plantations managed by smallholder farmers. This paper provides an up-to-date review of the social issues and challenges that oil palm smallholder farmers in Malaysia have encountered, as well as insights into future research on critical societal issues and challenges that demand attention and efforts towards improvement.
The Impact of Digital Transformation on Manufacturing-Enterprise Innovation: Empirical Evidence from China
Authors: Guo Xingguang , Chen Xi
Published: February 2023

The industrial sector is now undergoing digital revolution and upgrade, and it is of strategic significance to study how enterprise digitalization affects enterprise innovation. This paper develops a theoretical model of how digital transformation affects innovation in manufacturing enterprises, based on the resource-based view, network-embeddedness theory, and resource-complementarity theory. It then tests the mechanism and boundary conditions of the model, using data from a World Bank survey of Chinese enterprises. The study reveals how the degree of e-commerce embeddedness might partially mediate the effect of digital transformation on the innovation of manufacturing companies. Managerial human capital positively moderates the effect of digital transformation on manufacturing enterprises’ independent-R&D investment and product-innovation output. Employee human capital significantly and positively moderates the effect of digital transformation on manufacturing enterprises’ product-innovation output, while negatively moderating the effect of digital transformation on manufacturing enterprises’ cooperative-R&D investment. The conclusions can expand the relevant theoretical research on digital transformation and enterprise innovation, and also provide practical enlightenment for the digital transformation and upgrading of manufacturing enterprises.
Enhanced Photoelectrochemical Water Oxidation on BiVO4 Photoanodes Functionalized by Bimetallic Dicyanamide Molecular Catalysts
Authors: Wan Xiaokang , Lu Dashun , Wang Xianyun , Liu Gezhong , Fu Yanming , Hu Chao , Rong Nai , Wang Haitao , Cheng Zude
Published: February 2023

A novel hybrid structure of bimetallic dicyanamide decorated BiVO4 is developed via a simple method to accelerate interfacial water oxidation kinetics. Two types of bimetallic dicyanamides, CoNi(dca)2 and CoFe(dca)2, are coated on BiVO4 photoanodes and are found to exhibit far more enhanced PEC performance than Co(dca)2 or Ni(dca)2 as cocatalysts. The successful deposition of metal dicyanamides on BiVO4 photoanodes is confirmed by physical characterizations including X-ray photoelectron spectroscopy (XPS). The optimized Co0.9Ni0.1(dca)2/BiVO4 photoanode exhibits the highest photocurrent density of 2.58 mA/cm2 at 1.23 V vs. RHE under 100 mW/cm2 AM 1.5 G irradiation, which is 2.5 times that of bare BiVO4. The substantial enhancement of PEC performance can be ascribed to the advantageous interfacial charge transfer and improved charge injection efficiencies. This work presents a feasible strategy using different types of bimetallic dicyanamides to design a modified BiVO4-based photoanode system for enhanced water oxidation efficiency.
Economic Feasibility of a Hybrid Microgrid System for a Distributed Substation
Authors: Arunachalam Ramesh Kumar , Chandrasekaran Kumar , Rusu Eugen , Ravichandran Nagananthini , Fayek Hady H.
Published: February 2023

A hybrid microgrid system is modelled using HOMER-Pro software for real-time load data and available energy sources at Elapakkam village under Ramapuram substation, Kanchipuram, Tamil Nadu, India. Optimization approaches are applied for the selection of rating of the physical components, including solar PV systems, diesel generators, storage batteries, converters, inverters, and economic parameters such as system cost, fuel cost, and cash flow. The daily community load profile for the year 2018 was estimated based on data from TANGEDCO. Accordingly, the total load demand for the village represented 8760 lines of hourly load. The aim of this paper is to select an optimal-sized and reliable hybrid microgrid system to meet the load demands with available energy inputs. However, a comparison based on the cost of energy (COE) and the penetration of renewable energy is carried out for different case studies in the village with the economic-feasibility analysis of various countries. From this analysis, emissions cannot be completely avoided, they could be minimized by combining existing systems with renewable energy systems.
A Virtual Experience System of Bamboo Weaving for Sustainable Research on Intangible Cultural Heritage Based on VR Technology
Authors: Zhang Lufang , Wang Yue , Tang Zhichuan , Liu Xia , Zhang Moran
Published: February 2023

As an important national cultural treasure, intangible cultural heritage (ICH) faces certain problems in inheritance and sustainability. With the development of digital technology, the increasing research and application of virtual reality technology in ICH have been presented. This paper proposes a virtual experience system for Dongyang bamboo weaving, a traditional form of ICH craftsmanship, to display its historical background, cultural connotation, and technical craftsmanship. The learning module of the system is evaluated through the comparative experiments by 8 subjects. From the experimental data, compared with the computer, the average time for subjects to learn bamboo weaving in the system is shorter. The results of the questionnaire indicate that the learning module arouse their interest in bamboo weaving. The result shows the system is able to create an immersive and interactive scene for the users to understand bamboo weaving culture and learn the skills, which may encourage the sustainable development of bamboo weaving culture from the perspective of diffusion and provide research methods for other studies on traditional craftsmanship of ICH.