bluuebunny/crossref_metadata_2025 huggingface dataset:
Active Fault Trace Identification Using a LiDAR High-Resolution DEM: A Case Study of the Central Yangsan Fault, Korea
Authors: Ha Sangmin , Son Moon , Seong Yeong Bae
Published: September 2022

Korea has been recognized as an earthquake-safe zone, but over recent decades, several earthquakes, at a medium scale or higher, have occurred in succession in and around the major fault zones, hence there is a need for studying active faults to mitigate earthquake risks. In Korea, research on active faults has been challenging owing to urbanization, high precipitation, and erosion rates, and relatively low earthquake activity compared to the countries on plate boundaries. To overcome these difficulties, the use of aerial light detection and ranging (LiDAR) techniques providing high-resolution images and digital elevation models (DEM) that filter vegetation cover has been introduced. Multiple active fault outcrops have been reported along the Yangsan Fault, which is in the southeastern area of the Korean Peninsula. This study aimed to detect active faults by performing a detailed topographic analysis of aerial LiDAR images in the central segment of the Yangsan Fault. The aerial LiDAR image covered an area of 4.5 km by 15 km and had an average ground point density of 3.5 points per m2, which produced high-resolution images and DEMs at greater than 20 cm. Using LiDAR images and DEMs, we identified a 2–4 m high fault scarp and 50–150 m deflected streams with dextral offset. Based on the image analysis, we further conducted a trench field investigation and successfully located the active fault that cut the Quaternary deposits. The N–S to NNE-striking fault surfaces cut unconsolidated deposits comprising nine units, and the observed slickenlines indicated dextral reverse strike-slip. The optically stimulated luminescence (OSL) age dating results of the unconsolidated deposits indicate that the last earthquake occurred 3200 years ago, which is one of the most recent along the Yangsan Fault.
An Overview of Ecosystem Changes in Tibetan and Other Alpine Regions from Earth Observation
Authors: Cao Ruyin , Shen Miaogen , Fu Bin
Published: September 2022

Alpine ecosystems have shown sensitive responses to climate change during the past few decades [...]
Satellite Soil Moisture Data Reconstruction in the Temporal and Spatial Domains: Latent Error Assessments and Performances for Tracing Rainstorms and Droughts
Authors: Liu Yi , Chen Ruiqi , Yuan Shanshui , Ren Liliang , Zhang Xiaoxiang , Liu Changjun , Ma Qiang
Published: September 2022

Intermittent records of satellite soil moisture data are major obstacles that constrain their hydrometeorological applications. Based on the European Space Agency Climate Change Initiative (ESA CCI) soil moisture combined product, two machine learning models were employed to reconstruct soil moisture in China during 1979–2019 in both temporal and spatial domains, and latent errors for reconstructed series, as well as their performances for tracing climate extremes, were analyzed. The results showed that with the homogeneity of available data over space, the spatial approach performed well in reproducing the spatial heterogeneity of soil moisture (with medians of the correlation coefficient (CC) above 0.8 and root mean square errors (RMSEs) ranging from 0.02 to 0.03 m3∙m−3). The temporal approach (CC values of 0.7 and RMSEs ranging between 0.02 and 0.03 m3∙m−3) was superior in capturing the seasonality features and the timely and accurate mapping of short-term soil moisture dynamics impacted by rainstorms. However, both approaches failed to identify the location and severity of droughts accurately. The findings highlight the benefits of combining the strengths of both temporal and spatial gap-filling approaches for improving the estimation of missing values and hydrometeorological applications.
A Hybrid Classification of Imbalanced Hyperspectral Images Using ADASYN and Enhanced Deep Subsampled Multi-Grained Cascaded Forest
Authors: Datta Debaleena , Mallick Pradeep Kumar , Reddy Annapareddy V. N. , Mohammed Mazin Abed , Jaber Mustafa Musa , Alghawli Abed Saif , Al-qaness Mohammed A. A.
Published: September 2022

Hyperspectral image (HSI) analysis generally suffers from issues such as high dimensionality, imbalanced sample sets for different classes, and the choice of classifiers for artificially balanced datasets. The existing conventional data imbalance removal techniques and forest classifiers lack a more efficient approach to dealing with the aforementioned issues. In this study, we propose a novel hybrid methodology ADASYN-enhanced subsampled multi-grained cascade forest (ADA-Es-gcForest) which comprises four folds: First, we extracted the most discriminative global spectral features by reducing the vast dimensions, i.e., the redundant bands using principal component analysis (PCA). Second, we applied the subsampling-based adaptive synthetic minority oversampling method (ADASYN) to augment and balance the dataset. Third, we used the subsampled multi-grained scanning (Mg-sc) to extract the minute local spatial–spectral features by adaptively creating windows of various sizes. Here, we used two different forests—a random forest (RF) and a complete random forest (CRF)—to generate the input joint-feature vectors of different dimensions. Finally, for classification, we used the enhanced deep cascaded forest (CF) that improvised in the dimension reduction of the feature vectors and increased the connectivity of the information exchange between the forests at the different levels, which elevated the classifier model’s accuracy in predicting the exact class labels. Furthermore, the experiments were accomplished by collecting the three most appropriate, publicly available his landcover datasets—the Indian Pines (IP), Salinas Valley (SV), and Pavia University (PU). The proposed method achieved 91.47%, 98.76%, and 94.19% average accuracy scores for IP, SV, and PU datasets. The validity of the proposed methodology was testified against the contemporary state-of-the-art eminent tree-based ensembled methods, namely, RF, rotation forest (RoF), bagging, AdaBoost, extreme gradient boost, and deep multi-grained cascade forest (DgcForest), by simulating it numerically. Our proposed model achieved correspondingly higher accuracies than those classifiers taken for comparison for all the HS datasets.
Performance Evaluation of Multi-Epoch Double-Differenced Pseudorange Observation Method Using GNSS Ground Stations
Authors: Ebinuma Takuji , Tanaka Toshiki
Published: September 2022

Multi-epoch double-differenced pseudorange observation (MDPO) is a dual-satellite lunar navigation algorithm specially designed for a precursor mission, using a minimum number of lunar orbiting small satellites to realize a GNSS-like radio navigation system for the Moon. In this study, we evaluated the performance of the MDPO algorithm by using real pseudorange measurements obtained from a pair of GNSS ground stations, one of which represented a lander, and the other a rover on the Moon. It was natural that the resulting positioning accuracy varied largely by satellite geometry, but the estimated error distributions of the double-differenced pseudorange observations were consistent and agreed with the predicted value. The results showed that the MDPO algorithm worked properly with the real GNSS observables and was capable of providing the expected navigation performance for future lunar exploration missions.
Cross-World Covert Channel on ARM Trustzone through PMU
Authors: Li Xinyao , Tyagi Akhilesh
Published: September 2022

The TrustZone technology is incorporated in a majority of recent ARM Cortex A and Cortex M processors widely deployed in the IoT world. Security critical code execution inside a so-called secure world is isolated from the rest of the application execution within a normal world. It provides hardware-isolated area called a trusted execution environment (TEE) in the processor for sensitive data and code. This paper demonstrates a vulnerability in the secure world in the form of a cross-world, secure world to normal world, covert channel. Performance counters or Performance Monitoring Unit (PMU) events are used to convey the information from the secure world to the normal world. An encoding program generates appropriate PMU event footprint given a secret S. A corresponding decoding program reads the PMU footprint and infers S using machine learning (ML). The machine learning model can be trained entirely from the data collected from the PMU in user space. Lack of synchronization between PMU start and PMU read adds noise to the encoding/decoding ML models. In order to account for this noise, this study proposes three different synchronization capabilities between the client and trusted applications in the covert channel. These are synchronous, semi-synchronous, and asynchronous. Previously proposed PMU based covert channels deploy L1 and LLC cache PMU events. The latency of these events tends to be 100–1000 cycles limiting the bandwidth of these covert channels. We propose to use microarchitecture level events with latency of 10–100 cycles captured through PMU for covert channel encoding leading to a potential 100× higher bandwidth. This study conducts a series of experiments to evaluate the proposed covert channels under various synchronization models on a TrustZone supported Cortex-A processor using OP-TEE framework. As stated earlier, switch from signaling based on PMU cache events to PMU microarchitectural events leads to approximately 15× higher covert channel bandwidth. This proposed finer-grained microarchitecture event encoding covert channel can achieve throughput of the order of 11 Kbits/s as opposed to previous work’s throughput of the order of 760 bits/s.
Fast Positioning Model and Systematic Error Calibration of Chang’E-3 Obstacle Avoidance Lidar for Soft Landing
Authors: Wang Donghong , Chen Xingfeng , Liu Jun , Liu Zongqi , Zheng Fengjie , Zhao Limin , Li Jiaguo , Mi Xiaofei
Published: September 2022

Chang’E-3 is China’s first soft landing mission on an extraterrestrial celestial body. The laser Three-Dimensional Imaging (TDI) sensor is one of the key payloads of the Chang’E-3 lander. Its main task is to provide accurate 3D lunar surface information of the target landing area in real time for the selection of safe landing sites. Here, a simplified positioning model was constructed, to meet the accuracy and processing timeline requirements of the TDI sensor of Chang’E-3. By analyzing the influence of TDI intrinsic parameters, a permanent outdoor calibration field based on flat plates was specially designed and constructed, and a robust solution of the geometric calibration adjustment was realized by introducing virtual observation equations for unknowns. The geometric calibration and its absolute and relative positioning accuracy verification were carried out using multi-measurement and multi-angle imaging data. The results show that the error of TDI intrinsic parameters will produce a false obstacle with a maximum height of about 1.4 m on the plane, which will cause the obstacle avoidance system of Chang’E-3 to fail to find a suitable landing area or find a false flat area. Furthermore, the intrinsic parameters of the TDI have good stability and the accuracy of the reconstructed three-dimensional surface can reach about 4 cm after error calibration, which provides a reliable terrain guarantee for the autonomous obstacle avoidance of the Chang’E-3 lander.
Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images
Authors: Almalki Yassir Edrees , Din Amsa Imam , Ramzan Muhammad , Irfan Muhammad , Aamir Khalid Mahmood , Almalki Abdullah , Alotaibi Saud , Alaglan Ghada , Alshamrani Hassan A , Rahman Saifur
Published: September 2022

The teeth are the most challenging material to work with in the human body. Existing methods for detecting teeth problems are characterised by low efficiency, the complexity of the experiential operation, and a higher level of user intervention. Older oral disease detection approaches were manual, time-consuming, and required a dentist to examine and evaluate the disease. To address these concerns, we propose a novel approach for detecting and classifying the four most common teeth problems: cavities, root canals, dental crowns, and broken-down root canals, based on the deep learning model. In this study, we apply the YOLOv3 deep learning model to develop an automated tool capable of diagnosing and classifying dental abnormalities, such as dental panoramic X-ray images (OPG). Due to the lack of dental disease datasets, we created the Dental X-rays dataset to detect and classify these diseases. The size of datasets used after augmentation was 1200 images. The dataset comprises dental panoramic images with dental disorders such as cavities, root canals, BDR, dental crowns, and so on. The dataset was divided into 70% training and 30% testing images. The trained model YOLOv3 was evaluated on test images after training. The experiments demonstrated that the proposed model achieved 99.33% accuracy and performed better than the existing state-of-the-art models in terms of accuracy and universality if we used our datasets on other models.
Mechanical Characteristics of the Combination System of Medium-Diameter Anti-Slide Piles and Tunnel-Under-Landslide Loading
Authors: Li Tao , Chen Gang , Liu Yitong , Luo Bo , Zhu Baolong
Published: September 2022

Landslides have significant impacts on the stress and deformation of existing tunnel that can damage the existing tunnel lining structures and thus affect normal traffic operation. It is of importance to study the mechanical mechanism of tunnel–landslide support systems. However, there are few studies on the mechanical mechanism of existing tunnels in landslide areas. The combination of medium-diameter anti-slide piles (300 mm ≤ D ≤ 800 mm) overcomes the disadvantages of the complex construction process and higher site requirements for large-diameter anti-slide piles (D > 800 mm) and the disadvantage of lower support with micro anti-slide piles (D < 300 mm). In this study, considering the influence of landslides on existing tunnel deformation, a new type of medium-diameter anti-slide pile reinforcement system for existing tunnels is proposed based on the Nanping Tunnel project. In order to study the influence of pile spacing on tunnel support, first, the maximum pile spacing of 12.5 d (25 cm) was calculated by the mathematical geometric method, and then, three physical models were established for experimental comparison and analysis, including three different spacing cases of 7.5 d (15 cm), 10 d (20 cm), and 12.5 d (25 cm). In addition, numerical simulation was used to analyze the landslide and tunnel deformation under three pile spacing working conditions. The following conclusions are reached: As the distance between the combined pile increased, the deformation of the pile body and the tunnel lining structure also increased gradually, and the earth pressure and bending moments acting on the tunnel and the pile body increased progressively. However, when the pile spacing was increased from 7.5 d to 10 d, the increase in tunnel bending moment (52.9% increase in tunnel lining moment) was much more significant than when the pile spacing was increased from 10 d to 12.5 d (28.1% increase in tunnel lining moment). The results showed that if the landslide thrust is small, the pile spacing can be increased to 12.5 d or more in the design of combined medium-diameter anti-slide piles; if the landslide thrust is large, the pile spacing should be reduced to 7.5 d or less. Whether the landslide’s thrust is large or small, the combined medium-diameter anti-slide piles with a 10 d pile spacing are less cost-effective for landslide control. The new combined medium-diameter anti-slide piles have high loading capacity and stability, which can further improve the strength of existing tunnels.
The National Target Program for New Rural Development in Vietnam: An Understanding of People’s Participation and Its Determinants
Authors: Tung Diep Thanh , Diem Le Thi Thu , Luan Do Xuan , Linh Nguyen Hoang Khanh
Published: September 2022

This study proposes a participation scale of people in the national new rural program, namely the levels of know, discuss, implement, and monitor identifies participation and their determinants by employing Tobit regression models. From a dataset of 508 household respondents collected in seven regions across countries, we find that the highest level of participation is still at the level of know, while the lowest level is at the level of monitor. Additionally, in some areas of the program, people are mobilized to participate in certain activities, even though they do not have a good understanding nor thoroughly discuss how to carry it out. Considering the findings, we recommend increasing the active participation of the people in the bottom-up approach, associated with the practical needs of the people and the program’s sustainability.
Spatial Variation in Desert Spring Vegetation Biomass, Richness and Their Environmental Controls in the Arid Region of Central Asia
Authors: Zhou Shijie , Dong Yiqiang , Julihaiti Asitaiken , Nie Tingting , Jiang Anjing , An Shazhou
Published: September 2022

A precise evaluation of spatial patterns in desert vegetation biomass, species richness and their environmental controls is essential for a deeper comprehension of the potential carbon preservation and sustainability of grassland ecosystems. There are widespread reports suggesting robust associations among biomass, species richness and mean annual precipitation (MAP) or temperature (MAT) at different scales. However, these reports were inconsistent, and knowledge on the desert grasslands of Central Asia remains limited. In this study, we showed that spatial patterns of biomass and species richness along the zonal climate of the northern Tianshan Mountains exhibited substantial regional differences and the relationship among biomass, richness and elevation exhibited a substantial exponential decline. We discovered that functional groups of biomass, total biomass and species richness in the desert exhibited exponential growth along the MAP gradient and a quadratic relationship with MAT. Furthermore, the biomass–species richness relationships were bell-shaped in the desert zone. Accordingly, the biomass and species richness had spatial differences. At a regional scale, the spatial variation in the desert biomass and species richness was primarily dependent on climate. Our results demonstrated the specificity between the desert vegetation and climate in arid regions of Central Asia and revealed the regularity between biomass and species richness in desert areas. The research results emphasized the impact of precipitation on desert vegetation in arid regions of Central Asia and the relationship between biomass and plant species richness, which is of great significance for understanding desert ecosystems and protecting the ecological environment.
Optimal Extended Warranty Strategy: Provided by Manufacturer or E-Commerce Platform?
Authors: Hu Jiawei , Sun Suqin , Zhang Xuemei , Meng Qiang
Published: September 2022

To meet the different needs of consumers in an E-commerce market environment, more and more enterprises have launched extended warranty services, which can reduce consumer risk and stimulate market demand in E-commerce supply chains. However, knowing who will launch the extended warranty services has become particularly important. To propose an optimal strategy of the extended warranty service provider and seller, three game models are constructed in an E-commerce supply chain consisting of a manufacturer and an E-commerce platform. In addition, this study investigated the effect of extended warranty strategy on consumers. The results show that when the extended warranty coverage and product failure probability are small, the extended warranty provided by the E-commerce platform can simulate the demand of products and extended warranty. The extended warranty provided by the manufacturer is the best choice for the manufacturer. On the other hand, the extended warranty provided by the E-commerce platform is always beneficial for the E-commerce platform and E-commerce supply chain system. The E-commerce platform should take some measures and control some parameters to make up for the losses of the manufacturer, so that the strategy of the extended warranty provided and sold by the E-commerce platform becomes the consistent choice of E-commerce supply-chain members, system, and consumers.
Hospitality Feedback System 4.0: Digitalization of Feedback System with Integration of Industry 4.0 Enabling Technologies
Authors: Narayan Ram , Gehlot Anita , Singh Rajesh , Akram Shaik Vaseem , Priyadarshi Neeraj , Twala Bhekisipho
Published: September 2022

Digitalization enables the realization of the resilient infrastructure in every application for achieving sustainability. In the context of the hospitality business, resilient infrastructure based on digital technologies is critical for gaining the best customer feedback on providing quality service. Digital technology has already proved to enhance hospitality services with intelligent decisions through real-time data. In the previous studies, the significance of digital technologies in the hotel sector has been extended in numerous theoretical and empirical studies, yet there is a lack of research that provides a discussion on feedback systems in hospitality with digital technologies applications. With the motivation from the above aspects, this study intends to present the importance and application of the Internet of Things (IoT), artificial intelligence (AI), cloud computing, and big data implementation in customer quality and satisfaction. Moreover, we have discussed each technology´s significance and application for realizing digital-based customer quality and satisfaction. It has been identified that the AI-based system collects the input data from different common websites and compares it with a different algorithm using a neural network. According to the findings of this study, AI and personnel quality of service have an impact on customer pleasure and loyalty. The study also concludes with the following recommendations, such as the design and development of dedicated hardware to gain the actual feedback from the customer on a large scale for improving the accuracy in the future.
Load Frequency Control and Automatic Voltage Regulation in a Multi-Area Interconnected Power System Using Nature-Inspired Computation-Based Control Methodology
Authors: Ali Tayyab , Malik Suheel Abdullah , Hameed Ibrahim A. , Daraz Amil , Mujlid Hana , Azar Ahmad Taher
Published: September 2022

The stability control of nominal frequency and terminal voltage in an interconnected power system (IPS) is always a challenging task for researchers. The load variation or any disturbance affects the active and reactive power demands, which badly influence the normal working of IPS. In order to maintain frequency and terminal voltage at rated values, controllers are installed at generating stations to keep these parameters within the prescribed limits by varying the active and reactive power demands. This is accomplished by load frequency control (LFC) and automatic voltage regulator (AVR) loops, which are coupled to each other. Due to the complexity of the combined AVR-LFC model, the simultaneous control of frequency and terminal voltage in an IPS requires an intelligent control strategy. The performance of IPS solely depends upon the working of the controllers. This work presents the exploration of control methodology based on a proportional integral–proportional derivative (PI-PD) controller with combined LFC-AVR in a multi-area IPS. The PI-PD controller was tuned with recently developed nature-inspired computation algorithms including the Archimedes optimization algorithm (AOA), learner performance-based behavior optimization (LPBO), and modified particle swarm optimization (MPSO). In the earlier part of this work, the proposed methodology was applied to a two-area IPS, and the output responses of LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD control schemes were compared with an existing nonlinear threshold-accepting algorithm-based PID (NLTA-PID) controller. After achieving satisfactory results in the two-area IPS, the proposed scheme was examined in a three-area IPS with combined AVR and LFC. Finally, the reliability and efficacy of the proposed methodology was investigated on a three-area IPS with LFC-AVR with variations in the system parameters over a range of Â ± 50%. The simulation results and a comprehensive comparison between the controllers clearly demonstrates that the proposed control schemes including LPBO-PI-PD, AOA-PI-PD, and MPSO-PI-PD are very reliable, and they can effectively stabilize the frequency and terminal voltage in a multi-area IPS with combined LFC and AVR.
Attitudes of Drivers towards Electric Vehicles in Kuwait
Authors: Ottesen Andri , Banna Sumayya , Alzougool Basil
Published: September 2022

Although researchers have started to examine the landscape of electric vehicles (EVs) around the world, very little research has examined this phenomenon in Kuwait. In addition, limited research has explored it among drivers. Kuwait constitutes a very promising market for EVs because there is a need to lower GHG emissions and improve the air quality in Kuwait. This study therefore explored the attitudes of conventional car internal combustion engine (ICE) drivers towards EVs in Kuwait, particularly identifying attributes, features, enablers, and barriers of EVs that are considered important by potential consumers in Kuwait. This study utilized a mixed method approach in terms of quantitative data and qualitative data from a sample of 472 drivers to accomplish the main objectives of this study. The study showed that more than half of participants would buy an EV within the next 3 years, and they would buy if several conditions were met. That includes a cheaper purchase price with the assistance of policies controlled by the government along with the availability of suitable infrastructure for EVs relating to charging stations, fast lanes, and free parking spaces. More than 40% of participants would also seriously start thinking about buying an EV if the gas/fuel prices increased by between 50 and 199%. More than 40% of participants thought that EVs are safe in relation to fire and car crashes. Furthermore, approximately half of participants would pay 6–20% more for an EV that is both environmentally friendly and much quicker than gasoline cars. In addition, participants would also prefer EVs over gasoline cars in the future for their environmental, economic, and technological values. More importantly, the study yielded many significant findings, such as the demanded and preferred features of EVs and reflections on the readiness of the Kuwaiti market.
Corporate Sustainability and Market Response According to the Name Change Strategy: Focusing on Korean IT Industry Firms
Authors: Park Jungmi , Shin Yoojin
Published: September 2022

This study seeks to determine whether corporate sustainability increases due to the corporate name change strategy by analyzing the sample of IT companies listed on the KOSDAQ market from 2010 to 2019, through the event study methodology and OLS regression. This study has the following conclusions: first, the analysis results show that if the market response to an IT company’s corporate name change is positive, its financial constraint improves after the name change. Second, even if the companies’ financial constraint conditions before the corporate name change differ, their financial constraints improve after the name change if the market response to their announcements to change their corporate names is favorable. In other words, in terms of corporate sustainability, the financial constraint of a company improves depending on how it establishes the strategy to change its corporate name as well as the level of the market response to the announcement to change its corporate name. This implies that an IT company’s strategy to change its corporate name can affect corporate sustainability. Consequently, from the perspective of IT companies, this study serves as a guide for stakeholders’ decision-making processes and proves that the financial constraint can be improved through a corporate name change strategy.
The Influence of Aid for Trade on Human Development in South Asia
Authors: Sardar Sana , Khan Dilawar , Khan Alam , Magda Róbert
Published: September 2022

Although South Asia has made some progress in human development over the last century, it still lags behind some other Asian countries. It is necessary to explore the factors that contribute to human development but have not yet been explored. Thus, the aim of this study is to explore the influence of aid for trade on human development in South Asia for the period 2005 to 2019. First, the study detected the unit root problem in the data using panel unit root tests and found that all data series (human development, aid for trade, population and remittances) are stationary at the level except foreign direct investment, which is stationary at the first difference. Second, the pooled mean group-autoregressive distributed lag (PMG-ARDL) model was employed to examine the short- and long-term influence of aid for trade on human development. The findings of the PMG-ARDL approach explored that aid for trade has a positive and significant influence on human development, both in the short and long run. Finally, this study prescribed some policy suggestions to improve human development in the region.
Reduction of Graphene Oxide Using Citrus hystrix Peels Extract for Methylene Blue Adsorption
Authors: Priliana Veronika , Sucitro Clarissa , Wijaya Ronald , Lunardi Valentino Bervia , Santoso Shella Permatasari , Yuliana Maria , Gunarto Chintya , Angkawijaya Artik Elisa , Irawaty Wenny
Published: September 2022

Kaffir lime peels extract was used as an agent for the reduction of graphene oxide (GO) into reduced graphene oxide (rGO) via a simple room temperature-dispersion process. The GO obtained from the Hummers process is dispersed in polyphenols rich extract at a varied GO-to-extract ratio of 1:1, 1:2, 1:3, and 1:4. The formation of rGO was confirmed through SEM, FTIR, XPS, XRD, and N2 sorption characterization. The restoration of C=C group and the reduction of several oxygen-containing groups confirmed the successful formation of rGO from GO. The resultant rGOs were used in the adsorption system for methylene blue uptake. The results indicated that the rGOs prepared at a GO-to-extract ratio of 1:2 had the highest adsorption capacity than rGO at other ratios. The XPS spectrum analysis of rGO 1:2 showed a higher C-C/C-O ratio than the other rGOs, indicating a higher number of adsorption sites which aid in improving the adsorption performance. The adsorption isotherm and kinetic studies were conducted to gain insight into the mechanism and rate of methylene blue uptake by the rGOs. The adsorption isotherm systems were consistent with Langmuir isotherm model with the highest adsorption capacity of 118 mg g–1 by rGO 1:2. The kinetic adsorption data are well represented by the pseudo-second order model, the adsorption equilibrium was achieved within 400 min with the overall uptake rate of 0.3 mg g–1 min–1.
Does Public Participation Matter to Planning? Urban Sculpture Reception in the Context of Elite-Led Planning in Shanghai
Authors: Zheng Jane , Zheng Xiaohua
Published: September 2022

Scholars have long debated how effective public participation is in urban planning. While most research was designed to assess the effect of public participation, the knowledge gap concerns whether urban planning would receive negative reception without public participation due to failure in managing people’s emotions. One of the underlying reasons is that public participation is crucial to public emotion management. In this paper, we evaluate the impact of a case of public planning, and more specifically, the effects on public art reception when the planning project is developed by elites, without the involvement and participation of residents. Public art planning involves substantial symbolic and emotional components, and therefore constitutes a suitable case study. This research examines urban sculpture planning in Shanghai. The primary research method is a questionnaire survey, completed by 244 respondents. We argue that public participation is not the sole determinant of public art reception; other factors, particularly locality, also matter: an authoritarian-style urban sculpture planning creates a unanimous reverence and appreciation for flagship art projects on prominent public venues in central cities. However, people’s feelings towards sculptures vary in neighborhoods; people are more likely to resist imposed artworks in the environment of their everyday life. Finally, we conclude that a lack of public participation does not always result in a negative reception to cultural projects on the part of the public; however, this lack of public participation is, nevertheless, culturally unsustainable.
Green Bonds as an Instrument for Financing Ecological Investments in the V4 Countries
Authors: Hadaś-Dyduch Monika , Puszer Blandyna , Czech Maria , Cichy Janusz
Published: September 2022

The aim of this paper is to characterise the green bond market in the Visegrad Group of countries (V4) and to identify the determinants and benefits of issuing green bonds. The specific objective is a spatial–temporal analysis of the green bond yield in V4 countries. The following research methods were used in the paper: a source literature analysis and report analysis, statistical data analysis (from international financial markets), and the Dynamic Time Warping method (DTW). DTW comprises a class of algorithms that are used to compare both equal and unequal time series. The DTW method allows the smallest distance between two time series of different lengths to be found while allowing for the transformation over time of both series. As the method is highly efficient, it is used to provide a thorough spatial–temporal analysis of green bonds. The research process confirmed that green bonds are an instrument with potential in the global debt market. Among the most important stimulants for the issuance of green government bonds are capital mobilisation, the development of the green financial market, investor demand, and reputational benefits.
Durability Assessment Method of Hollow Thin-Walled Bridge Piers under Rockfall Impact Based on Damage Response Surface
Authors: Li Fei , Liu Yikang , Yang Jian
Published: September 2022

Continuous rigid-frame bridges across valleys are often at risk of rockfalls caused by heavy rainfalls, earthquakes, and debris flow in a mountainous environment. Hollow thin-walled bridge piers (HTWBP) in valleys are exposed to the threat of impact from accidental rockfalls. In the current research, ANSYS/LS-DYNA is used to establish a high-precision rockfall-HTWBP model. The rockfall-HTWBP model is verified against a scaled impact test performed in previously published research. A mesh independence test is also performed to obtain an appropriate mesh size. Based on the rockfall-HTWBP model, the impact force, damage, and dynamic response characteristics of HTWBP under a rockfall impact are studied. In addition, a damage assessment criterion is proposed, based on the response surface model, combined with the central composite design method and Box–Behnken design method. The main conclusions are as follows: (1) the impact force of the rockfall has a substantial impulse characteristic, and the duration of the impulse load is approximately 0.01 s. (2) The impacted surface of the pier is dominated by the final elliptic damage, with conical and strip damage areas as the symmetry axis. The cross-sectional damage mode is from compression failure in the impact area and shear failure at the corner. (3) The maximum displacement occurs in the middle height of the pier. The maximum displacement increases with impact height, impact velocity, and rockfall diameter and decreases with the uniaxial compressive strength of the concrete. (4) The initial impact velocity and diameter of the rockfall are the most significant parameters affecting the damage indices. In addition, a damage assessment method, with a damage zoning diagram based on the response surface method, is established for the fast assessment of the damage level of impacted HTWBP.
Effects of Food Cooperative Membership on What Consumers Buy and Where They Buy: Evidence from Korean Household Panel Data 2015–2019
Authors: Lee Dongmin
Published: September 2022

Alternative food networks (AFNs) have emerged in response to the conventional industrial food system, which distances and detaches food production from food consumption. Food cooperatives are representative of AFNs where relationships between food producers and consumers are reconfigured. This study examines household food cooperative membership and changes in food purchase behavior using household panel data gathered by the Rural Development Administration of Korea. In particular, it aims to provide insight into the effect of AFNs on consumer food purchase behavior, including expenditure per food category and visit frequency ratio per store format. The ordinary least squares regression model was used. The findings show that depending on the ownership of AFNs, expenditure per food category and visit frequency ratio per store format vary. Food cooperative members tend to purchase less processed food and more fresh vegetables and fruits than nonmembers. Moreover, food cooperative membership significantly influences the decrease in visits to small supermarkets and traditional markets when purchasing groceries.
Estimating the Role of Climate Internal Variability and Sources of Uncertainties in Hydrological Climate-Impact Projections
Authors: Cai Wenjun , Liu Jia , Zhu Xueping , Zhao Xuehua , Zhang Xiaoli
Published: September 2022

Hydrological climate-impact projections in the future are limited by large uncertainties from various sources. Therefore, this study aimed to explore and estimate the sources of uncertainties involved in climate change-impacted assessment, in a representative watershed of Northeastern China. Moreover, recent studies have indicated that the climate internal variability (CIV) plays an important role in various hydrological climate-impact projections. Six downscaled global climate models (GCMs) under two emission scenarios, and a calibrated Soil and Water Assessment Tool (SWAT) model were used to obtain hydrological projections in future periods. The CIV and signal-to-noise ratio (SNR) are investigated to analyze the role of internal variability in hydrological projections. The results shows that the internal variability shows a considerable influence on hydrological projections, which need to be particularly partitioned and quantified. Moreover, it is worth noting the CIV can propagate from precipitation and ET to runoff projections through the hydrological simulation process. In order to partition the CIV and the sources of uncertainties, the uncertainty decomposed frameworks based on analysis of variance (ANOVA) are established. The results demonstrate that the CIV and GCMs are the dominant contributors of runoff in the rainy season. In contrast, the CIV and SWAT model parameter sets provided obvious uncertainty to the runoff in January to May, and October to December. The findings of this study advised that the uncertainty is complex in the hydrological simulation process; hence, it is meaningful and necessary to estimate the uncertainty in the climate simulation process. The uncertainty analysis results can effectively provide efforts for reducing uncertainty, and then give some positive suggestions to stakeholders for adaption countermeasures under climate change.
Key Logistics Performance Indicators in Low-Income Countries: The Case of the Import–Export Chain in Ethiopia
Authors: Tadesse Mahlet Demere , Kine Helen Zewdie , Gebresenbet Girma , Tavasszy Lóránt , Ljungberg David
Published: September 2022

Performance evaluation in logistics is crucial in identifying improvement opportunities. This study assessed performance indicators (PIs) for import–export logistics chains, including transport, dry ports, transhipment and warehouses, focusing on Ethiopia. PIs were identified by means of a literature review. An expert survey based on the analytical hierarchy process (AHP) was used to obtain weightings for the indicators to allow an evaluation of the overall performance of the country’s import–export chains. Key challenges faced in the sector were also identified. Indicators such as turnaround time and damage frequency were given high weightings by experts for dry port PIs, security was given the highest weighting for transport PIs, and order lead time was given the highest weighting for warehouse PIs. Technological advancements, human resource capacity building and government policies were found to be the main areas that could improve the performance of logistics operations and address the challenges faced by the sector. These findings could provide a new and comprehensive picture of the key performance indicators of Ethiopian import–export logistics chains.
Potential Role of Combined Microbial Inoculants and Plant of Limnocharis flava on Eliminating Cadmium from Artificial Contaminated Soil
Authors: Lam Nguyen Thi , Song Shaoxian , Dung Bui Thi Ngoc , Binh Tran Ngoc , Maleki Afshin , Godini Kazem , Tang Van Tai
Published: September 2022

This study aimed to investigate the possibility of eliminating cadmium (Cd) from contaminated agricultural soil using a combination of microbial inoculants of Penicillium chrysogenum fungus and Bacillus licheniformis with Limnocharis flava plants. Limnocharis flava (L. flava) and microbial inoculants with four Cd levels, including 2.05 (T1 control), 5 (T2), 10 (T3), and 20 mg/kg (T4), respectively, were tested in green house conditions. Cd accumulation was evaluated to assess the safety limit of the Cd concentration in the edible parts of L. flava. The results showed that the application of the microbial inoculants facilitated the stress tolerance of the plants caused by a Cd accumulation in the soil matrix. The use of Penicillium chrysogenum and Bacillus licheniform in combination with L. flava increased the Cd accumulation in plant biomass. The total Cd after the experiment varied between 4.86 and 18.44 mg/kg in dry, clean soil, equivalent to reduction rates of 2.80, 4.40, and 7.80%, respectively. Meanwhile, the availability of Cd in soil was significantly reduced by 12.50, 13.04, 13.33, and 13.93%, respectively. Consequently, the microbial inoculants helped the plants to grow healthily, increased the yield, and reduced the total and available Cd content of contaminated agricultural land up to a concentration level of 5 mg/kg.
Temporal and Spatial Characteristics of Meteorological Elements in the Vertical Direction at Airports and Hourly Airport Visibility Prediction by Artificial Intelligence Methods
Authors: Ding Jin , Zhang Guoping , Yang Jing , Wang Shudong , Xue Bing , Du Xiangyu , Tian Ye , Wang Kuoyin , Jiang Ruijiao , Gao Jinbing
Published: September 2022

Based on second-level L-band sounding data, the vertical distribution and variation of meteorological elements at airports in 2010–2020 are investigated. At the same time, the relationships between airport visibility and meteorological elements at different potential heights are also investigated. Then, based on hourly measurements of 26 meteorological elements in 2018–2020, the hourly visibility of airports is predicted by 9 artificial intelligence algorithm models. The analyses show: (1) For the vertical changes in four meteorological elements of the airports, the negative vertical trends of temperature and relative humidity increase clearly from northwestern to southeastern China. The significant negative trend of air pressure in the vertical direction in the eastern China is greater. (2) Within about 2000 geopotential metres (gpm) from the ground, the visibility has a strong correlation with the air pressure, and most of them are negative. Within 400 gpm from the ground, airport visibility is negatively correlated with the relative humidity. At 8:00 a.m., airport visibility is positively correlated with the wind speed within 2000 gpm from the ground at most airports, while at 20:00 p.m., the positive correlation mainly appears within 400 gpm from the ground. (3) The passive aggressive regression-(PAR) and isotonic regression-(IST) based models have the worst effect on airport visibility prediction. The dispersion degree of the visibility simulation results obtained by Huber regression-(HBR) and random sample consensus regression-(RANSAC) based models is relatively consistent with the observations.
Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting
Authors: Neves-Silva Rui , Camarinha-Matos Luis M.
Published: September 2022

The implementation of building retrofitting processes targeting higher energy efficiency is greatly influenced by the investor’s expectations regarding the return on investment. The baseline of this work is the assumption that it is possible to improve the predictability of the post-retrofit scenario, both in energy and financial terms, using data gathered on how a building is being used by its occupants. The proposed approach relies on simulation to estimate the impact of available energy-efficient solutions on future energy consumption, using actual usage data. Data on building usage are collected by a wireless sensor network, installed in the building for a minimum period that is established by the methodology. The energy simulation of several alternative retrofit scenarios is then the basis for the decision support process to help the investor directing the financial resources, based on both tangible and intangible criteria. The overall process is supported by a software platform developed in the scope of the EnPROVE project. The platform includes building audit, energy consumption prediction, and decision support. The decision support follows a benefits, opportunities, costs, and risks (BOCR) analysis based on the analytic hierarchy process (AHP). The proposed methodology and platform were tested and validated in a real business case, also within the scope of the project, demonstrating the expected benefits of alternative retrofit solutions focusing on lighting and thermal comfort.
A Systematic Review of Water Resources Assessment at a Large River Basin Scale: Case of the Major River Basins in Madagascar
Authors: Zy Harifidy Rakotoarimanana , Zy Misa Harivelo Rakotoarimanana , Hiroshi Ishidaira , Jun Magome , Kazuyoshi Souma
Published: September 2022

Assessing water resources at a large river basin scale is important for having an idea of the water situation and efficient water resources management. What is the most appropriate approach to assess the water resources at a large river basin scale? This paper aims to develop a systematic review on water resources assessment at a large river basin scale, intending to present a new assessment method for the major river basins in Madagascar. This review investigates 40 articles from Google Scholar, Web of Science, and PubMed databases, from 2000 to 2022. This review has demonstrated the necessity of water resources assessment at a large river basin scale in Madagascar. An improvement in the use of multiple GCMs and SWAT models for water resources assessment within the basin was found necessary for appropriate water allocating regimes among upper and lower reaches. Water allocation and water scarcity at the basin level could be addressed by using the inter- and intra-basin approaches. The review concludes that a combination of the SWAT, multiple GCMs, and inter- and intra-basin approaches could be efficiently applied for assessing the water resources at a large basin scale. This review may be of benefit to scientists and water specialists.