bluuebunny/crossref_metadata_2025 huggingface dataset:
End-to-End Moving Target Indication for Airborne Radar Using Deep Learning
Authors: Gu Yao , Wu Jianxin , Fang Yuyuan , Zhang Lei , Zhang Qiang
Published: October 2022

Moving target indication (MTI) based on space–time adaptive processing (STAP) has been widely used in airborne radar due to its ability for clutter suppression performance. However, the existing MTI methods suffer from the problems of insufficient training samples and low detection probability in a non-homogeneous clutter environment. To address these issues, this paper proposes a novel deep learning framework to improve target indication capability. First, combined with the problems of target indication caused by the non-homogeneous clutter, the clutter-plus-target training dataset was modeled by simulation, where various non-ideal factors, such as aircraft crabbing, array errors and internal clutter motion (ICM), were considered. The dataset considers various realistic situations, making the proposed method more robust. Then, a five-layer two-dimensional convolutional neural network (D2CNN) was designed and applied to learn the clutter and target characteristics distribution. The proposed D2CNN can predict the target with a high resolution to implement an end-to-end moving target indication (ETE-MTI) with a higher detection accuracy. In this D2CNN, the input was obtained by the clutter-plus-target angle-Doppler spectrum with a low-resolution estimated only by a few samples. The label was given by the target angle-Doppler spectrum with a high-resolution obtained by the target’s exact angle and Doppler. Thirdly, the proposed method used a few samples to improve the target indication and detection probability, which solved the problem of insufficient samples in the non-homogeneous clutter environments. To elaborate, the proposed method directly implements ETE-MTI without the support of the conventional STAP algorithm to suppress the clutter. The results verify the validity and the robustness of the proposed ETE-MTI with a few samples in the non-homogeneous and low signal-to-clutter ratio (SCR) environments.
Image-to-Image Subpixel Registration Based on Template Matching of Road Network Extracted by Deep Learning
Authors: Hikosaka Shuhei , Tonooka Hideyuki
Published: October 2022

The vast digital archives collected by optical remote sensing observations over a long period of time can be used to determine changes in the land surface and this information can be very useful in a variety of applications. However, accurate change extraction requires highly accurate image-to-image registration, which is especially true when the target is urban areas in high-resolution remote sensing images. In this paper, we propose a new method for automatic registration between images that can be applied to noisy images such as old aerial photographs taken with analog film, in the case where changes in man-made objects such as buildings in urban areas are extracted from multitemporal high-resolution remote sensing images. The proposed method performs image-to-image registration by applying template matching to road masks extracted from images using a two-step deep learning model. We applied the proposed method to multitemporal images, including images taken more than 36 years before the reference image. As a result, the proposed method achieved registration accuracy at the subpixel level, which was more accurate than the conventional area-based and feature-based methods, even for image pairs with the most distant acquisition times. The proposed method is expected to provide more robust image-to-image registration for differences in sensor characteristics, acquisition time, resolution and color tone of two remote sensing images, as well as to temporal variations in vegetation and the effects of building shadows. These results were obtained with a road extraction model trained on images from a single area, single time period and single platform, demonstrating the high versatility of the model. Furthermore, the performance is expected to be improved and stabilized by using images from different areas, time periods and platforms for training.
Monitoring Seedling Emergence, Growth, and Survival Using Repeat High-Resolution Imagery
Authors: Morris Jesse R. , Petersen Steven L. , Madsen Matthew D. , McMillan Brock R. , Eggett Dennis L. , Lawrence C. Russell
Published: October 2022

Environmental factors often limit plant establishment and survival through increased seedling mortality. Understanding plant growth and the causes of mortality can be helpful in developing solutions that enhance seeding success and improve restoration monitoring. The purpose of our research was to assess the efficacy of time lapse and motion sensing cameras for monitoring seedling height, density, and fate. We conducted this study in a salt desert shrub community in northwest Utah, USA. In spring 2017, we placed 28 cameras in fenced and unfenced plots seeded with bottlebrush squirreltail and collected hourly images of the seedlings’ development for the initial four months post-seeding. The seedling attributes were recorded in-field and compared with camera images to determine accuracy and reliability. We found that the optimal period for capturing imagery occurred near the sun’s zenith when shadows were minimized. We were able to detect both the timing of the plant emergence, plant height, density, growth rate, and seedling death. The average seedling height and density were underestimated by 14% and 30% between the camera and field estimates, respectively. We recognize that it could be beneficial to adjust for the effect of the date. The reduced seedling density improved the measurement accuracy through a lower visual obscurity. Managers can utilize remote cameras to effectively measure vegetation that can provide an insight into environmental influences.
Comprehensive Analysis of PPP-B2b Service and Its Impact on BDS-3/GPS Real-Time PPP Time Transfer
Authors: Tang Jian , Lyu Daqian , Zeng Fangling , Ge Yulong , Zhang Runzhi
Published: October 2022

2020 saw the official completion of the BDS-3 and the start of the PPP-B2b signal-based real-time precise point positioning (PPP) service to users in China and the neighboring areas. In this work, the quality of PPP-B2b products is first evaluated and compared with real-time products from the CNES and the differential code bias (DCB) from the Chinese Academy of Science (CAS). Then, a detailed performance evaluation of the PPP time transfer based on the PPP-B2b service (B2b-RTPPP) is conducted. Three solutions, namely, GPS-only (G), BDS-3-only (C), and GPS + BDS-3 (GC) B2b-RTPPP solutions, are compared and assessed. The results suggest that for the PPP-B2b products, BDS-3 satellites have better orbit and clock offset quality than GPS satellites, while the opposite is true for CNES products. The quality of the PPP-B2b orbit and clock offset is poorer than those of the CNES. The PPP-B2b DCB shows excellent agreement with the CAS DCB. The accuracy of the B2b-RTPPP solutions is sub-nanosecond level. The accuracy of B2b-RTPPP time transfer with DCB correction is approximately improved by 64% compared with that without DCB correction. The GC B2b-RTPPP solution has the greatest frequency stability, while G B2b-RTPPP solution has the poorest. Considering that the receiver may be blocked, the B2b-RTPPP time transfer performance is also evaluated at different cut-off elevation angles. As the angle increases, the B2b-RTPPP time transfer performance decreases. Additionally, the short-term frequency stability remains constant at different cut-off elevation angles, but deteriorates in the long term, especially when the angle is 40°.
Response of Vegetation to Different Climate Extremes on a Monthly Scale in Guangdong, China
Authors: Wang Leidi , Hu Fei , Zhang Caiyue , Miao Yuchen , Chen Huilin , Zhong Keyou , Luo Mingzhu
Published: October 2022

Climate extremes, particularly drought, often affect the ecosystem. Guangdong Province is one of the most vulnerable areas in China. Using the normalized difference vegetation index (NDVI) to capture vegetation dynamics, this study investigated vegetation responses to drought, temperature, and precipitation extremes on a monthly scale in the vegetation area of Guangdong without vegetation type changes from 1982 to 2015. As extreme temperatures rose, a drought trend occurred in most months, with a higher rate in February and April. The vegetation evenly showed a significant greening trend in all months except June and October. The vegetation activity was significantly positively correlated with the increased extreme temperatures in most months. However, it exerted a negative correlation with drought in February, April, May, June, and September, as well as precipitation extremes in February, April, and June. The response of vegetation to drought was the most sensitive in June. The vegetation tended to be more sensitive to short-term droughts (1–2 months) and had no time lag in response to drought. The results are helpful to provide references for ecological management and ecosystem protection.
A Novel Jamming Method against SAR Using Nonlinear Frequency Modulation Waveform with Very High Sidelobes
Authors: Song Chen , Wang Yu , Jin Guodong , Wang Yu , Dong Qinghai , Wang Bingnan , Zhou Liangjiang , Lu Pingping , Wu Yirong
Published: October 2022

Synthetic aperture radar (SAR) systems have the capacity for day-and-night and all-weather surveillance, which has become increasingly indispensable for military surveillance and global comprehensive environmental monitoring. With the development of the high-resolution SAR imaging technique, studies on SAR jamming have also received much interest. Traditional jamming methods are based on linear-frequency-modulated (LFM) signals, and this method can achieve high main-lobe jamming gain. However, its sidelobe jamming energy is very low. To solve this issue, a novel nonlinear frequency modulation (NLFM) waveform design method for SAR jamming is proposed in this paper. Compared with LFM waveforms, the designed waveforms have the same main-lobe jamming gain and very high sidelobes, which can significantly improve jamming performance. Moreover, detailed simulation experiments were carried out to verify the effectiveness of the newly proposed jamming scheme.
Mapping Coastal Aquaculture Ponds of China Using Sentinel SAR Images in 2020 and Google Earth Engine
Authors: Tian Peng , Liu Yongchao , Li Jialin , Pu Ruiliang , Cao Luodan , Zhang Haitao , Ai Shunyi , Yang Yunze
Published: October 2022

Aquaculture has enormous potential for ensuring global food security and has experienced rapid growth globally. Thus, the accurate monitoring and mapping of coastal aquaculture ponds is necessary for the sustainable development and efficient management of the aquaculture industry. Here, we developed a map of coastal aquaculture ponds in China using Google Earth Engine (GEE) and the ArcGIS platform, Sentinel-1 SAR image data for 2020, the Sentinel-1 Dual-Polarized Water Index (SDWI), and water frequency obtained by identifying the special object features of aquaculture ponds and postprocessing interpretation. Our map had an overall accuracy of 93%, and we found that the coastal aquaculture pond area in China reached 6937 km2 in 2020. The aquaculture pond area was highest in Shandong, Guangdong, and Jiangsu Provinces, and at the city level, Dongying, Binzhou, Tangshan, and Dalian had the most aquaculture pond area. Aquaculture ponds had spatial heterogeneity; the aquaculture pond area in north China was larger than in south China and seaside areas had more pond area than inland regions. In addition, aquaculture ponds were concentrated near river estuaries, coastal plains, and gulfs, and were most dense in the Huang-Huai-Hai Plain and Pearl River Delta. We showed that GEE cloud processing and ArcGIS local processing could facilitate the classification of coastal aquaculture ponds, which can be used to inform and improve decision-making for the spatial optimization and intelligent monitoring of coastal aquaculture, with certain potential for spatial migration.
Detection and Risk Analysis with Lane-Changing Decision Algorithms for Autonomous Vehicles
Authors: Mechernene Amin , Judalet Vincent , Chaibet Ahmed , Boukhnifer Moussa
Published: October 2022

Despite the great technological advances in ADAS, autonomous driving still faces many challenges. Among them is improving decision-making algorithms so that vehicles can make the right decision inspired by human driving. Not only must these decisions ensure the safety of the car occupants and the other road users, but they have to be understandable by them. This article focuses on decision-making algorithms for autonomous vehicles, specifically for lane changing on highways and sub-urban roads. The challenge to overcome is to develop a decision-making algorithm that combines fidelity to human behavior and that is based on machine learning, with a global structure that allows understanding the behavior of the algorithm and that is not opaque such as black box algorithms. To this end, a three-step decision-making method was developed: trajectory prediction of the surrounding vehicles, risk and gain computation associated with the maneuver and based on the predicted trajectories, and finally decision making. For the decision making, three algorithms: decision tree, random forest, and artificial neural network are proposed and compared based on a naturalistic driving database and a driving simulator.
A Distributed Anti-Jamming Algorithm Based on Actor–Critic Countering Intelligent Malicious Jamming for WSN
Authors: Chen Yuheng , Niu Yingtao , Chen Changxing , Zhou Quan , Xiang Peng
Published: October 2022

In this paper, in order to solve the problem of wireless sensor networks’ reliable transmission in intelligent malicious jamming, we propose a Distributed Anti-Jamming Algorithm (DAJA) based on an actor–critic algorithm for a multi-agent system. The Multi-Agent Markov Decision Process (MAMPD) is introduced to model the progress of wireless sensor networks’ anti-jamming communication, and the multi-agent system learns the intelligent jamming from the external environment by using an actor–critic algorithm. On the basis of coping with the influence of external and internal factors effectively, each sensor in networks selects the appropriate channels for transmission and finally realizes the optimal transmission of the system overall in a unit time period. In the environment of probabilistic intelligent jamming with tracking properties set in this paper, the simulation shows that the algorithm proposed can outperform the algorithm based on joint Q-learning and the conventional scheme based on orthogonal frequency hopping in terms of transmission. In addition, the proposed algorithm completes two updates of strategy evaluation and action selection in one iteration, which means that the system has higher efficiency of action selection and better adaptability to the environment through the interaction with the external environment, resulting in the better performance of transmission and convergence.
A Histone Deacetylase Inhibitor Manifests Synergistic Interaction with Artesunate by Suppressing DNA Repair Activity
Authors: Raza Asif , Kandimalla Raghuram , Kalita Sanjeeb , Ghosh Siddhartha Sankar
Published: October 2022

Artesunate (ART), a plant based semi-synthetic antimalarial drug, is emerging as a new class of effective cancer chemotherapeutics. However, the dosage of ART required to have an anti-cancer effect on cancer cells is greater than that needed to exterminate malarial parasites. The goal of this study was to develop an effective combination therapy to reduce the dose-dependent side effects of ART both in vitro and in vivo. In our study, 4-phenylbutyrate (4-PB), a histone deacetylase inhibitor (HDAC), exhibited significant synergistic induction of apoptosis in MCF-7 cells in combination with ART. The IC50 of ART decreased significantly from 55.56 ± 5.21 µM to 24.71 ± 3.44 µM in MCF-7 cells. ART treatment increased cellular oxidative stress, and the resulting generation of intracellular reactive oxygen species (ROS) caused extensive DNA damage in the cell. The extent of ROS production and cell cycle arrest were further enhanced by 4-PB treatment. In further investigation, we found that 4-PB attenuated mRNA expression of crucial DNA damage response (DDR) elements of the nonhomologous end-joining (NHEJ) pathway, consequently enhancing the DNA damaging effect of ART. Furthermore, the combination therapy resulted in improvement in the life expectancy of the treated mice and a prominent reduction in tumour volume without interfering with the normal biochemical, haematological and histological parameters of the mice. Overall, our study revealed a novel combination therapy in which 4-PB potentiated the cytotoxicity of ART synergistically and provided a promising combination drug for effective cancer therapy.
Gas Chromatography—High-Temperature Proton-Transfer Reaction Mass Spectrometry as a Novel Tool for Forensic Drug Testing
Authors: Reinstadler Vera , Gutmann Rene , Pitterl Florian , Winkler Klaus , Oberacher Herbert
Published: October 2022

Proton-transfer reaction mass spectrometry (PTR-MS) is a versatile tool for the mass spectrometric analysis of organic molecules in gaseous samples. Due to its operation principle, PTR-MS is a soft ionization technique generating spectral data typically rich in protonated molecule information. Most of the currently reported PTR-MS applications are designed to determine volatile compounds. Herein, we present a redesigned instrumental setup termed “high-temperature (HT)-PTR-MS” with improved capabilities for the analysis of low-volatile compounds. The developed HT-PTR-MS prototype was successfully hyphenated with gas chromatography (GC) to enable qualitative and quantitative analysis of licit and illicit drugs in human blood/plasma samples. Different kinds of spiked and authentic samples were used to evaluate the performance of the GC-HT-PTR-MS in forensic drug testing. Benchmarking against GC-MS with electron ionization demonstrated the improved detection capabilities of GC-HT-PTR-MS in screening applications. On average, one order of magnitude lower limits of detection/identification were reached. Clearly, GC-HT-PTR-MS has the vast potential to complement or even replace established mass spectrometric techniques in forensic drug analysis.
Digital Divide: An Inquiry on the Native Communities of Sabah
Authors: Fang Yi Xue , Gill Sarjit S. , Kunasekaran Puvaneswaran , Rosnon Mohd Roslan , Talib Ahmad Tarmizi , Abd Aziz Azureen
Published: October 2022

ICT development has become the development pulse of the global nation. Malaysia, as a developing nation, has invested heavily in ICT development across the country to ensure no one is left behind. The policymakers have also claimed a positive result in closing the digital gap among their people. In this study, Van Dijk’s theory of digital divide is explored on the four dimensions of digital divide (motivation, physical, skill, and usage) among the native people in Sabah. A focus group discussion (FGD) was conducted among 21 key informants from seven different ethnic groups to identify the issues of ICT development in their community. The findings showed that the existence of a digital gap between the rural and the urban area community caused the community to be saddled with the connection to telecommunication service, including landline and internet. Despite lacking, the native community were receptive and willing to adopt the ICT positively for their daily activities. While the theory of digital divide observes that the physical access divide is narrowing in most developed nations, this study shows that is not the case for developing countries, such as Malaysia. The inequality in digital access is prevalent among the natives in Sabah, which could result in the opportunity to participate in important democratic decision-making.
The Challenges and Opportunities of Era 5.0 for a More Humanistic and Sustainable Society—A Literature Review
Authors: Tavares Maria C , Azevedo Graça , Marques Rui P.
Published: October 2022

We are in an increasingly disruptive context, in an Era in which the world presents challenging and growing levels of uncertainty, unpredictability, and complexity. As a result, society is facing, at all levels and in all areas, more and more global challenges, challenging its stability and prosperity, whether at a technological, economic, social, environmental, or educational level. The new Era, Era 5.0, which places the human being at the center of innovation and technological transformation, can and must make its contribution to improving the quality of life, solving social problems, and human well-being, with the support of technology. Thus, this work intends, based on a systematic review of the literature, to analyze the challenges of Era 5.0 and its impacts on industry, society, and education as engines and promoters of the path to sustainable development. The results of this work show that the challenges for industry and education on the road to a “new” society are immense, in order to achieve a more humanistic society, centered on human beings, quality of life, and sustainability. We believe in contributing to the state of the art in Era 5.0 and providing an analytical reflection in the field of education and industry, on the path towards a society that places the human being at the center of innovation and technological transformation.
GIS Modeling to Climate Change Adaptation by Reducing Evaporation in Water Reservoirs: Smart Location Technique of Minimal Evaporation Reservoirs (GIS-MER)
Authors: Fernández-Enríquez Alfredo , Pérez-Cayeiro María Luisa , Anfuso Giorgio
Published: October 2022

The ideal emplacement of reservoirs has been traditionally determined by means of GIS tools to prospect large areas applying criteria related to rainfall, substrate impermeability or economic and social viability. More recently, geomorphometric characteristics have been added to determine more suitable locations for dams and reservoirs depending on their dimensions. This study presents a fully automatized ArcGIS Pro model, suitable for working with several digital elevation model resolutions and for evaluating best potential reservoir locations to reduce evaporation losses. Here, a smart location strategy to preserve water resources is used based on the premise that the higher the ratio of water stored to water surface area of the reservoir, the lower the water evaporation. The model was tested in two dissimilar basins in the province of Cadiz (SW Spain) and the results are compared with the nearby existing reservoirs. The methodology presented in this paper allows selecting the most suitable sites where it is possible to build a reservoir with a water surface smaller than other reservoirs but also able to hold an equal or greater volume of water; this also allows reducing the area occupied by the reservoir. As an example, in the first study case presented in this paper, a new reservoir could store 30.7 m3/m2 versus the current 9 m3/m2 stored in the nearby existing reservoir. This may reduce the flooded area from 25.4 to just 6.7 km2.
Capturing Unobserved Tourists: Challenges and Opportunities of Processing Mobile Positioning Data in Tourism Research
Authors: Kovalcsik Tamás , Elekes Ábel , Boros Lajos , Könnyid László , Kovács Zoltán
Published: October 2022

Even though tourism (both domestic and international) is one of the main triggering factors of human mobility worldwide, some of its forms are unexplored. This can be partly linked with the lack of reliable data and obstacles related to data processing and interpretation. Mobile Positioning Data (MPD) allows us to identify various forms of tourism that are undetectable through traditional data sources such as accommodation statistics. Using MPD, not only same-day tourists but also the real time mobility patterns of tourists among various destinations can be revealed, and even hidden (i.e., unobserved) forms of tourism can be detected. However, despite the obvious benefits of such data, very few comprehensive studies exist to date on the processing, and interpretation of MPD in tourism research. In this paper, a case study is presented on the challenges and opportunities of processing MPD from raw to good quality researchable data offering a baseline tool for MPD-based research in the field of tourism. With the methodology introduced in this paper, it is possible to provide a more accurate picture of tourist flows regarding unobserved tourists, including same-day visitors.
Game-Based Formative Assessment of Analogical Reasoning in Preschool Children: Support from the Internet of Things Technology
Authors: Lv Xue , Li Li , Guo Liping , He Ting , Liu Sirui
Published: October 2022

Emerging information technology such as Internet of Things (IoT) has been continuously applied and deepened in the field of education, and the learning analytics technology based on children’s games is gradually moving toward practical application research, but there are few empirical studies on the micro level of emerging information technology and learning analytics methods in the evaluation of young children’s learning process and learning effects. As the research content, the study examines preschool children’s analogical reasoning abilities, reflecting their thinking levels and processing abilities. Using a decision tree model in learning analytics, the process data and result data of children’s analogical reasoning games based on Internet of Things technology are analyzed, and the classification model of preschool children’s analogical reasoning is constructed. The study found that the learning analysis of analogical reasoning based on games mediated by IoT technology is feasible and effective.
The Impact on Bed and Breakfast Prices: Evidence from Airbnb in China
Authors: Tian Feifei , Sun Fengzhi , Hu Beibei , Dong Zhitao
Published: October 2022

As a new type of accommodation and a new way of life, it is of great significance for the spatial optimization and price management of the tourist accommodation market to explore the spatial differentiation characteristics of and influencing factors on bed and breakfast (B&B) house prices. Taking Shandong B&B merchants on the Airbnb website as the research object, this paper discusses the spatial characteristics of and influencing factors on B&B prices in the Shandong province, combining spatial autocorrelation analysis and interpolation analysis to identify the B&B cluster region. Quantile regression was used to reveal the main influencing factors. The results show that: (1) the spatial agglomeration effect of B&B prices in the Shandong province is obvious, and the high value areas form a new pattern between the provincial economic circle and the Jiaodong Economic Circle; (2) the influence of different factors on B&B house prices is very uneven in space. From the regional point of view, there are “sub-regional effects” on the spatial distribution of the influences of various factors on B&B house prices. The results of the study provide references for reasonable pricing, scientific site selection, and spatial optimization of B&Bs.
Exploring the Visual Guidance of Motor Imagery in Sustainable Brain–Computer Interfaces
Authors: Yang Cheng , Kong Lei , Zhang Zhichao , Tao Ye , Chen Xiaoyu
Published: October 2022

Motor imagery brain–computer interface (MI-BCI) systems hold the possibility of restoring motor function and also offer the possibility of sustainable autonomous living for individuals with various motor and sensory impairments. When utilizing the MI-BCI, the user’s performance impacts the system’s overall accuracy, and concentrating on the user’s mental load enables a better evaluation of the system’s overall performance. The impacts of various levels of abstraction on visual guidance of mental training in motor imagery (MI) may be comprehended. We proposed hypotheses about the effects of visually guided abstraction on brain activity, mental load, and MI-BCI performance, then used the event-related desynchronization (ERD) value to measure the user’s brain activity, extracted the brain power spectral density (PSD) to measure the brain load, and finally classified the left- and right-handed MI through a support vector machine (SVM) classifier. The results showed that visual guidance with a low level of abstraction could help users to achieve the highest brain activity and the lowest mental load, and the highest accuracy rate of MI classification was 97.14%. The findings imply that to improve brain–computer interaction and enable those less capable to regain their mobility, visual guidance with a low level of abstraction should be employed when training brain–computer interface users. We anticipate that the results of this study will have considerable implications for human-computer interaction research in BCI.
COVID-19 Impacts on Whale-Watching Collaboration Networks
Authors: Langle-Flores Alfonso , López-Vázquez Zinthia , Chávez-Dagostino Rosa María , Aguilar-Rodríguez Adriana
Published: October 2022

Whale-watching tourism generates high-income seasonal livelihoods in coastal communities on the Mexican Pacific Coast; however, this sector is at risk from accelerated global changes. We evaluated the responses of a collaboration of tourism networks regarding the impacts COVID-19 using a longitudinal social network approach. We used a two-wave snowball method to identify potential interviewees and followed geographic and jurisdictional criteria using a face-to-face survey to map collaboration ties between 38 stakeholders involved in whale-watching tourism before and after the second wave of the pandemic. We also asked this group of stakeholders about their perceived impacts of COVID-19. We found slightly higher connectivity and centralization levels in the social networks after the pandemic. Loss of income and reservations, a decrease in both conservations and pollution, and an increase in the reduction in wildlife tourism were the main self-reported impacts. We also detected harmful pandemic legacies, such as whale-watching tours conducted using unregulated private boats. This research directly informs Mexico’s whale-watching tourism policy by showing the management and coordination challenges that stakeholders face in a post-pandemic context. While the social fabric of coastal communities has been resilient to the COVID-19 pandemic, we found indications that the governance of marine resources can easily unravel if rule of law is absent.
Synthesis of Poly(styrene-vinyl sodium sulfonate-butyl acrylate-ethyl methacrylate) and Its Blocking Mechanism as a Nanometer Material in Water-Based Drilling Fluid
Authors: Yu Jiantao , Chen Yu , Li Jingying , Sheng Chen , Sheng Jiaxun , Wu Zhengtian , Zhou Ye , Li Xiaodong , Xie Gang
Published: October 2022

Nano-blocking technology has become a key to overcoming a prominent bottleneck in shale gas development. In this paper, poly(ST-VS-B-E) was synthesized by Michael addition reaction using styrene, vinyl sodium sulfonate, ethyl methacrylate, and butyl acrylate. Poly(ST-VS-B-E) was characterized by infrared spectroscopy analysis, laser scattering analysis, and thermogravimetric analysis. The rheological properties of drilling fluid with poly(ST-VS-B-E) were studied by testing the drilling fluid’s properties. The results showed that the median particle size of poly(ST-VS-B-E) was 79.15 nm and it resisted a 359.25 °C high temperature. The yield point of the water-based drilling fluid with 2.5 wt% poly(ST-VS-B-E) added was 27 Pa, and the fluid loss was 3.1 mL, with good drilling fluid performance. Further test results from simulated mud cake filtration and the simulated core penetration showed that when the mass concentration of poly(ST-VS-B-E) was 2.5 wt%, the blocking rates were 66.67% and 93.33%, respectively, and the blocking performance increased gradually with the addition of poly(ST-VS-B-E). Poly(ST-VS-B-E) can be squeezed into the nano-pores of a shale formation under the action of pressure difference, so as to block the formation and prevent the entry of water-based drilling fluid filtrate. Poly(ST-VS-B-E) can serve as a potential nano-blocking material in water-based drilling fluids.
Advancing SDG No 16 via Corporate Governance Disclosure: Evidence from Indonesian and Malaysian Fintech Companies’ Websites
Authors: Susilowati Endah , Joseph Corina , Vendy Vicky , Yuhertiana Indrawati
Published: October 2022

The aims of this paper are: (1) to examine the extent of corporate governance disclosure on the websites of Indonesian and Malaysian FinTech companies using the coercive isomorphism tenet, and (2) to determine whether variation in the extent of corporate governance disclosure is influenced by the country and type of FinTech services. The websites of 148 Indonesian and 159 Malaysian corporations were subjected to content analysis using a Modified Corporate Governance Disclosure Index (MoCGOvDi). The MoCGovDi was constructed using the ASEAN Corporate Governance Scorecard and previous research. The level of corporate governance disclosure is higher among Malaysian FinTech companies, possibly due to stronger coercive pressure by government regulation in Malaysia. Overall, the level of corporate governance disclosure is low in both countries (7 and 9 items out of 50 total items for Indonesia and Malaysia, respectively), which may delay the achievement of SDG No 16. Several implications are provided in this paper to advocate the corporate governance disclosure of FinTech companies in Indonesia and Malaysia to achieve SDG No 16.
The Role of Organizational Climate, and Work–Family Conflict in Burnout: The Case of Teachers
Authors: Junça-Silva Ana , Freire Mara
Published: October 2022

Burnout is a major concern for the scientific and educational community, as it leads to harmful consequences, both at a personal and organizational level. Several studies showed that burnout is influenced by multiple factors, including organizational climate and work–family conflict. However, studies analyzing these three variables together in the educational sector are scarce. Thus, this study aimed to analyze whether the organizational climate influenced burnout through work–family conflict. We collected data in two-time points with 253 teachers. The results showed that only the organizational climate dimensions of involvement, control, autonomy, task orientation, and physical comfort were associated with burnout. Plus, only the physical comfort and autonomy climates significantly reduced burnout via the decreases in work–family conflict. Thus, these organizational climates’ dimensions seem to be essential factors to reduce not only work–family conflict but also burnout in the educational sector. This study tested the mediating role of work–family conflict on the link between organizational climate and burnout, with a group of teachers. Additionally, the data was collected during the pandemic crisis of COVID-19.
Sustainable Development Goals for the Circular Economy and the Water-Food Nexus: Full Implementation of New Drip Irrigation Technologies in Upper Egypt
Authors: Abdelzaher M. A. , Awad Mohamed M.
Published: October 2022

Saving fresh water is a big challenge for the next generation due to enhanced living standards and population growth. In addition, the expansion of agricultural and industrial activities is causing unmatched demands for fresh water supplies across Egypt. The Nile River is Egypt’s main water resource, representing 69.4% of the total water resources, while rainwater, torrential water and groundwater, as well as recycled agricultural and sanitary drainage water and desalinated seawater, are estimated at about 30.6%. Smart drip irrigation systems are in great demand, especially in Upper Egypt. SDG’s of the circular economy and the WEF nexus lead to full implementation of drip irrigation systems, achieving ~6.6 BM3/year of direct saving from fresh water and/or doubling the cultivated area. In addition to PV tubes and other utilities, renewable energy, e.g, photovoltaic panels, will posses an important role in low-energy driven drip irrigation systems, reducing fossil-uses, CO2 emissions and devolving more sustainable processes that are less dependent on conventional energy sources. The current research work is a case study of the substitution of flood with drip irrigation, and its positive advantages for the Egyptian agricultural economy and capital expenditures (capex), which depends on the country’s infrastructure and availability of utilities.
Research on Waste Recycling Network Planning Based on the “Pipeline–Vehicle” Recycling Mode
Authors: Qu Chenrui , Liu Lenan , Wang Zhenxia
Published: October 2022

To achieve the principles of reduction, resource, and harmless disposal of domestic waste, the circular economy prolongs the life cycle of resources by converting waste into renewable resources through sorting, recycling, and other ways. There are still noticeable problems in domestic waste recycling in China, such as poor waste classification and low recovery rate of resource-based waste with no or low economic value. In this paper, Van Waden’s seven-dimensional classification model of policy networks is adopted to analyze and compare domestic waste recycling (DWR) management modes at home and abroad. The domestic waste recycling mode of “pipeline collection and vehicle transfer” based on China’s national conditions is proposed. Then, the planning model of the domestic waste recycling network is further built. Taking Xiaolan Town, Zhongshan City as an example, the pipeline laying design and route planning of the pneumatic transportation and collection system for material in the new recycling mode are optimized. The examples verify the superiority of the greedy dropping heuristic algorithm in solving large-scale recycling network planning problems. This paper is of great significance to improve the recycling of renewable resources in domestic waste and realize the circular economy.
Recent Developments in the Vacuum Preloading Technique in China
Authors: Zhou You , Chen Shuli , Guo Wei , Ren Yuxiao , Xu Guizhong
Published: October 2022

A series of studies have confirmed that vacuum preloading can effectively accelerate the consolidation process of soft soil. In recent years, further improvement in the efficiency of this method is still the continuing goal of scholars. This paper reviews the recent improvements in the vacuum preloading techniques as well as their practical applications in China. The advantages and disadvantages of each method are discussed. It is found that replacing or eliminating one or more components of the vacuum preloading system, such as sand-free, membrane-free, horizontal drain, multiple-step, and air booster vacuum preloading methods, achieved similar soil improvement effects to those of the traditional vacuum preloading method. Vacuum preloading combined with other soil improvement methods could improve the soil with the lower average water content and the higher average shear strength.
Cyclone-Induced Disaster Loss Reduction by Social Media: A Case Study on Cyclone Amphan in Koyra Upazila, Khulna District, Bangladesh
Authors: Sultan S M Nadim , Maharjan Keshav Lall
Published: October 2022

This study aims to examine the role of social media use in reducing household cyclone-induced disaster loss by obtaining warning and preparedness information. Data were collected following the aftermath of cyclone Amphan in affected households of the Koyra sub-district, Khulna district of Bangladesh using random sampling. Data from 150 households using only traditional media and 150 from those using both social and traditional media were collected through semi-structured questionnaires. Using propensity score matching, it was found that households using both social media and traditional media were able to reduce loss by more than 47,494.31 Bangladeshi Taka compared to households using traditional media. Moreover, households using both media received more important timely information than households using only traditional media. This helped them to work more efficiently and timely, such as cutting ripe crops from fields and keeping them in a safe place, taking domestic animals and poultry to the nearest safe places, putting higher fences using necessary material around ponds to prevent fish being washed away, and so on, to reduce cyclone-induce disaster loss. For obtaining information, problems coastal people faced included less internet bandwidth, the absence of a unified Facebook page and a common YouTube channel, and rumors. Possible solutions for these problems, stated by the respondents, were government-managed free internet before cyclones, a single Facebook page and a single YouTube channel for this purpose. Thus, this research shows social media as a good tool for reducing cyclone-induced disaster loss in Bangladesh coastal areas.
Local Sustainability Performance and Its Spatial Interdependency in Urbanizing Java Island: The Case of Jakarta-Bandung Mega Urban Region
Authors: Pravitasari Andrea Emma , Priatama Rista Ardy , Mulya Setyardi Pratika , Rustiadi Ernan , Murtadho Alfin , Kurnia Adib Ahmad , Saizen Izuru , Widodo Candraningratri Ekaputri
Published: October 2022

Jakarta–Bandung Mega Urban Region (JBMUR), located in the western part of Java Island, Indonesia, is experiencing rapid regional development which can be observed from its increase in population density, massive changes of land-use from agricultural land into built-up area, rapid development of infrastructure and facilities, and advances in economic activities. Unfortunately, problems related to sustainability emerge along with this rapid regional development, primarily in decrease in environmental quality and social performance, leading to unsustainable development. This study aims: (1) to develop indicators promoting sustainable development at the subdistrict level, named the local sustainability index (LSI), utilizing factor analysis; (2) to observe local-scale spatial interdependency by employing local indicator of spatial association (LISA) statistics; and (3) to identify regional clusters based on LSI scores using K-means clustering method. Our LISA results show that spatial interdependency of local sustainability performances exists between local-scale spatial units: the LSI of a subdistrict is influenced by the sustainability state of the surrounding areas. Meanwhile, the clustering results show that most subdistricts in JBMUR are categorized as members of cluster 1 with low LSI values in economic and social dimensions but moderate in environmental dimensions.
A Literature Review on the Use of Recycled Construction and Demolition Materials in Unbound Pavement Applications
Authors: Pereira Paulo Miguel , Vieira Castorina Silva
Published: October 2022

The construction industry is one of the biggest sectors of economic activity in the European Union, consuming more energy and natural resources than any other industrial activity. Additionally, construction and demolition (C&D) waste is the most common waste produced throughout the European Union. A more efficient and effective use of natural resources and the attenuation of environmental impacts provoked by their extraction could be accomplished if correct construction and demolition waste management and recycling policies were implemented. The use of recycled C&D waste in road pavement layers is a solution with economic and environmental benefits that has been widely studied in recent decades. This paper provides a literature review on the relevant engineering properties of different types of recycled aggregates coming from C&D waste, a comparison with the properties of natural aggregates, and how these recycled aggregates perform in the long-term when used in unbound pavement applications. An analysis of the current status of C&D waste generation and recovery practices in the European Union is also presented. The aim of this review is to further encourage the use of recycled materials coming from C&D waste, particularly in unbound pavement applications, since, in general, research conducted worldwide has proven their good performance in the short and long-term.
Shadow Cast of Rotating Charged Black Hole with Scalar Q-Hair
Authors: Wu Meng-He , Guo Hong , Kuang Xiao-Mei
Published: October 2022

In this paper, we investigate the shadow cast by non-rotating and rotating charged black holes with scalar Q-hair. We find that in addition to the spin parameter of black hole and inclination angle of the observer, the charge parameter and the self-interaction parameters of the scalar hair also influence the shape of the black hole shadow. Our studies show that the charged black holes with scalar Q-hair always have smaller shadow size compared to those without hair. Moreover, it is found that the parameters significantly affect the shadow observables. In particular, for the fixed spin parameter and inclination angle, a larger charge parameter will increase the shadow size but decrease the shadow distortion, whilst stronger self-interaction parameters have the opposite influence. In short, the shadow of the charged black hole with scalar Q-hair can be distinguished from the Reissner–Nordstro¨m (RN) black hole or Kerr–Newmann (KN) black hole, and they indeed generate new templates with large deviations from general relativity those are invariably smaller in size.
Symmetric Functional Set-Valued Integral Equations and Bihari–LaSalle Inequality
Authors: Malinowski Marek T.
Published: October 2022

In the paper, we consider functional set-valued integral equations whose representation contains set-valued integrals occurring symmetrically on both sides of the equation. On the coefficients of the equation, we impose certain conditions, more general than the standard Lipschitz condition, which allow the application of the Bihari–LaSalle inequality in the proofs of the obtained theorems. In this way, we obtain a result about the existence and uniqueness of the solution of the equation under consideration and the insensitivity of the solution in the case of minor changes in the parameters of the equation.
Digital Hydraulic Design for Low-Specific-Speed Propeller Runners with Fixed Blades
Authors: Liu Youyu , Wang Qijie , Xu Dezhang , Chen Qing
Published: October 2022

The operating point of a propeller hydropower station will deviate from the effective workspace while the discharge reduces excessively during dry seasons. It usually leads to a decrease in efficiency and even to being unable to work. To solve the above problem, a scheme named decreasing capacity to increase efficiency was presented in this article. A low-specific-speed propeller runner with fixed blades that has the same installing dimensions as the original one was redesigned and equipped in dry seasons. A positive circulation at the outlet of the blades bigger than in conventional runners is allowed. Some key technologies about hydraulic design for runner blades were researched, which include distribution of velocity circulation at the inlet and outlet of the runner, thickening of the epiphyseal line of an aerofoil, unfolding aerofoil being converted to a cylindrical section, etc. In the section on digital modeling for runner blades, aerofoils on the cylindrical sections at the rim and at the hub were constructed employing the trend extrapolation method. Moreover, a blade digital model was built at one time according to the aerofoils on all cylindrical sections by means of a successful redevelopment to UniGraphics, and it has perfect symmetry. A case presented indicates that the method of decreasing capacity to increase efficiency is feasible. Using the method, the turbine efficiency increased from less than 28.6% to 83.4% while the discharge decreased from 3.20 m3s−1 to 1.00 m3s−1, and then the hydropower unit was able to work properly.