bluuebunny/crossref_metadata_2025 huggingface dataset:
Shoreline Dynamics of Chongming Island and Driving Factor Analysis Based on Landsat Images
Authors: Wang Haobin , Xu Dandan , Zhang Dong , Pu Yihan , Luan Zhaoqing
Published: July 2022

Chongming Island, the third largest island in China, has experienced dramatic shoreline changes due to erosion, river deposits, and human activities. While previous studies have shown the capacity of Landsat series images to extract shoreline dynamics, the spatial variation of shoreline dynamics and their corresponding driving factors remain unclear. Therefore, we established a method to monitor the shoreline dynamics of Chongming Island from 1984 to 2020 and to evaluate the driving factors of shoreline changes using a novel approach to Landsat image analysis. The method, based on the LISA (local indicator of spatial autocorrelation) concept, automatically extracted the shoreline from Landsat imagery. The results show that the LISA method, based on the SWIR1 band, has a high capacity for shoreline extraction in Chongming Island. By distinguishing the responses of the eastern and northern shorelines to upstream sediment loads and comprehensively analyzing the driving factors of eastern and northern dynamics, we found that: (i) although upstream sediment loads decreased dramatically, the shoreline of Chongming Island is still expanding due to human activities (i.e., reclamation and an estuary project) and sediment re-suspension from near-shore or cross-shore currents; (ii) the expansion of Chongming Island was initially due to the dynamics at the eastern shoreline, but the expansion of the eastern shoreline slowed after 2008 as upstream sedimentation slowed, less construction of cofferdams took place, and the Qingcaosha Reservoir was constructed; (iii) the northern shoreline of Chongming Island expanded rapidly after 1999, due to the merger of Xinlongsha, Xincunsha, and Chongming Island, and the transport of coastal and offshore sediments by hydrodynamic processes; and (iv) the main driving factors of eastern shoreline movement on Chongming Island are cofferdam reclamation and coastal engineering, and the changes at the northern shoreline are mainly affected by reclamation projects, offshore sediment supplies, and upstream sediment inflow. The results of this study provide theoretical fundamentals for land reclamation and future urban planning for Chongming Island.
Meta-Analysis and Visualization of the Literature on Early Identification of Flash Floods
Authors: Yang Zhengli , Yuan Xinyue , Liu Chao , Nie Ruihua , Liu Tiegang , Dai Xiaoai , Ma Lei , Tang Min , Xu Yina , Lu Heng
Published: July 2022

Flash flood is one of the extremely destructive natural disasters in the world. In recent years, extreme rainfall events caused by global climate change have increased, and flash flood disasters are becoming the main types of natural disasters in the world. Due to the characteristics of strong suddenness, complex disaster-causing factors, great difficulty in prediction and forecast, and the lack of historical data, it is difficult to effectively prevent and control flash flood disaster. The early identification technology of flash floods is not only the basis of flash flood disaster prediction and early warning, but also an effective means of flash flood prevention and control. The paper makes a meta-analysis and visual analysis of 475 documents collected by the Web of Science Document Platform in the past 31 years by comprehensively using Citespace, Vosviewer, Origin, etc. We systematically summarize the research progress and development trend of early identification technology of flash flood disasters from five key research subfields: (1) precipitation, (2) sediment, (3) sensitivity analysis, (4) risk assessment, (5) uncertainty analysis. In addition, we analyze and discuss the main problems encountered in the current research of several subfields and put forward some suggestions to provide references for the prevention and control of flash flood disasters.
Research on the Applicability of DInSAR, Stacking-InSAR and SBAS-InSAR for Mining Region Subsidence Detection in the Datong Coalfield
Authors: Xu Yaozong , Li Tao , Tang Xinming , Zhang Xiang , Fan Hongdong , Wang Yuewen
Published: July 2022

Intensive and large-scale underground coal mining has caused geological disasters such as local ground subsidence, cracks and collapse in the Datong coalfield, China, inducing serious threats to local residents. Interferometric synthetic aperture radar (InSAR) has the capability of surface deformation detection with high precision in vast mountainous areas. DInSAR, stacking-InSAR and SBAS-InSAR are commonly used InSAR-related deformation analysis methods. They can provide effective support for mine ecological security monitoring and prevent disasters. We use the three methods to conduct the deformation observation experiments in the Datong coalfield. Sentinel-1A data from November 2020 to October 2021 are used. As a result, a total of 256 deformations in the Datong coalfield were successfully detected by the three methods, of which 218 are mining deformations, accounting for 85% of the total deformations. By comparing the results of the three methods, we found that DInSAR, stacking-InSAR, and SBAS-InSAR detected 130, 256, and 226 deformations in the Datong coalfield, respectively, while the deformations caused by coal mining were 128, 218, and 190. DInSAR results with long spatiotemporal baselines are seriously incoherent. SBAS-InSAR results of displacement rate are more precise than stacking-InSAR, and the mean standard deviation is 1.0 mm/a. However, for areas with lush vegetation or low coherence, SBAS-InSAR has poor performance. The detection deformation area results of DInSAR and SBAS-InSAR are subsets of stacking-InSAR. The displacement rates obtained by stacking-InSAR and SBAS-InSAR are consistent; the mean difference in the displacement rate between the two methods is 2.7 mm/a, and the standard deviation is 5.1 mm/a. The mining deformation locations and their shapes in the study area can be identified with high efficiency and power by stacking-InSAR. Therefore, with a comprehensive understanding of the advantages and limitations of the three methods, stacking-InSAR can be an effective and fast method to identify the level, location and range of mining deformation in lush mountainous areas.
Cyclic Global Guiding Network for Point Cloud Completion
Authors: Wei Ming , Zhu Ming , Zhang Yaoyuan , Sun Jiaqi , Wang Jiarong
Published: July 2022

The application of 3D scenes has gradually expanded in recent years. A 3D point cloud is unreliable when it is acquired because of the performance of the sensor. Therefore, it causes difficulties in utilization. Point cloud completion can reconstruct and restore sparse and incomplete point clouds to a more realistic shape. We propose a cyclic global guiding network structure and apply it to point cloud completion tasks. While learning the local details of the whole cloud, our network structure can play a guiding role and will not ignore the overall characteristics of the whole cloud. Based on global guidance, we propose a variety of fitting planes and layered folding attention modules to strengthen the local effect. We use the relationship between the point and the plane to increase the compatibility between the network learning and the original sparse point cloud. We use the attention mechanism of the layer overlay to strengthen the local effect between the encode and decode. Therefore, point clouds are more accurate. Our experiments indicate the effectiveness of our method on the ShapeNet, KITTI, and MVP datasets and are superior to other networks.
Contributions of Various Sources to the Higher-Concentration Center of CO within the ASM Anticyclone Based on GEOS-Chem Simulations
Authors: Yang Yuepeng , Li Qian , Wang Haoyue , Bai Zhixuan , Li Dan , Wang Weiguo , Bian Jianchun
Published: July 2022

Satellite observations show that carbon monoxide (CO) concentration centers exist in the tropopause region of the Tibetan Plateau, while their sources and formation mechanism still remain uncertain. In this paper, the 3-D chemical transport model GEOS-Chem is used to conduct sensitivity analysis in 2016. Combined with the analysis data and satellite data, the contribution of three important emission sources (South Asia, East Asia and Southeast Asia) and two important chemical reaction species (CH4 and nonmethane volatile organic compounds (NMVOCs)) to CO in the upper troposphere and lower stratosphere (UTLS) are studied. The results show that in the Asian monsoon region CO emissions originating from the surface are transported to the upper troposphere via a deep convection process and then enter the Asian Summer Monsoon (ASM) anticyclone. The strong ASM anticyclone isolates the mixing process of air inside and outside the anticyclone, upon entry of carbon monoxide-rich air. In the lower stratosphere, the intensity of the ASM anticyclone declines and the air within the anticyclone flows southwestward with monsoon circulation. We found that in the summer Asian monsoon region, South Asia exhibited the highest carbon monoxide concentration transported to the UTLS. CH4 imposed the greatest influence on the CO concentration in the UTLS region. According to the model simulation results, the CO concentrations in the Asian monsoon region at 100 hPa altitudes were higher than those in other regions at the same latitudes. Regarding effects, 43.18% originated from CH4 chemical reactions, 20.81% originated from NMVOC chemical reactions, and 63.33% originated from surface CO emissions, while sinks yielded a negative contribution of −27.32%. Regarding surface CO emissions, East Asia contributed 13.56%, South Asia contributed 39.27%, and Southeast Asia contributed 7.15%.
Ground Moving Target Detection and Estimation for Airborne Multichannel Radar Based on Coherent Difference Processing
Authors: Song Chong , Wang Bingnan , Xiang Maosheng , Xu Weidi , Wang Zhongbin , Wang Yachao , Sun Xiaofan
Published: July 2022

Ground moving targets with slow velocity and low radar cross-section (RCS) are usually embedded in the clutter Doppler spectrum. To achieve the detection and estimation of such targets, a novel method operating in the range-Doppler domain is developed for airborne multichannel radar systems. The interferometric phases that are sensitive to moving targets are obtained by coherent difference processing (CDP) for target detection. Moreover, the amplitude is utilized as complementary information to improve the detection performance. Then, a matched filter bank is designed and applied to the CDP processed data to complete the parameter estimation. The proposed method provides the benefits of high efficiency and robustness, since it does not involve matrix inversion, and it does not require homogeneous clutter assumption unlike adaptive algorithms. Experiments on real data acquired by an airborne X-band four-channel radar system demonstrate its effectiveness.
Validation of NASA SMAP Satellite Soil Moisture Products over the Desert of Kuwait
Authors: AlJassar Hala , Temimi Marouane , Abdelkader Mohamed , Petrov Peter , Kokkalis Panagiotis , AlSarraf Hussain , Roshni Nair , Hendi Hamad Al
Published: July 2022

The goal of this study is to validate and analyze NASA’s Soil Moisture Active Passive (SMAP) products over the desert of Kuwait. The study period was between April 2015 and April 2020. The study domain includes a mission candidate calibration/validation (Cal/Val) site that comprises six permanent soil moisture stations used to verify SMAP estimates. In addition, intensive field campaigns were conducted within and around the candidate Cal/Val site during the study period to collect additional thermogravimetric samples. The mean difference (MD), root mean squared difference (RMSD), unbiased root mean square difference (ubRMSD), and correlation coefficient (R) were computed to assess the agreement between SMAP SM products and in situ observations. The comparison of the six ground station sensors’ observations with the thermogravimetric samples led to an absolute mean bias (AMB) of 0.034 m3 m−3, which was then used to calibrate the sensors and bias-correct their measurements. The temporal consistency of the readings from the test site and calibrated sensors was assessed using the mean relative difference (MRD) and its standard deviation of relative difference (SDRD). Using a sampling density analysis, it was determined that a minimum of four ground stations would be required to validate the test site. Furthermore, the consistency between SMAP satellite soil moisture data and those derived from the Soil Moisture and Ocean Salinity (SMOS) satellite operated by the European Space Agency, and their agreement with in situ samples, was analyzed. The comparison of SMAP and SMOS soil moisture data with in situ observations showed that both satellites successfully captured the spatial and temporal distribution of soil moisture. For SMAP and SMOS, the lowest ubRMSE statistics were 0.043 m3 m−3 and 0.045 m3 m−3, respectively, which are slightly higher than the mission target of 0.04 m3 m−3.
Benefit–Risk Perceptions of FinTech Adoption for Sustainability from Bank Consumers’ Perspective: The Moderating Role of Fear of COVID-19
Authors: Abdul-Rahim Ruzita , Bohari Siti Aisah , Aman Aini , Awang Zainudin
Published: July 2022

Industry 4.0 technologies, designed to optimize efficiencies, are indisputable change agents for sustainability. In the context of financial technology (FinTech), the burgeoning question concerns how to create FinTech natives from the COVID-19-pandemic-induced adoption and realize FinTech’s impact on sustainability? Thus, this study had the following purposes: (1) to examine whether perceived benefits and risks affect FinTech services adoption; (2) to test the role of fear of COVID-19 in FinTech adoption; and (3) to investigate whether FinTech adoption contributes to sustainability. The hypotheses derived from the net valence framework, sustainable information society theory, and protection motivation theory were tested using structural equation modeling (SEM). Our online survey of bank consumers in Malaysia between December 2021 and February 2022 yielded 1279 usable questionnaires, randomly selected to generate 400 respondents. The results revealed that: (1) the perceived benefits significantly influence FinTech adoption, whereas perceived risk does not; (2) fear of COVID-19 moderates the perceived benefits–FinTech adoption relationship and fully mediates the perceived risk–FinTech adoption relationship; and (3) FinTech adoption significantly affects sustainability. This study demonstrates that FinTech adoption models must exploit consumer sentiment (e.g., fear) to optimize FinTech’s benefits and risks, thereby creating FinTech natives to realize its impacts on economic, environmental, and social sustainability.
Education Partnership Assistance to Promote the Balanced and Sustainable Development of Higher Education: Lessons from China
Authors: Ding Ruichang , You Zheng
Published: July 2022

The Education Partnership Assistance (EPA) is an institutional arrangement that has played an important role in the balanced and sustainable development of higher education in China, in which universities of East China provide the paired universities in West China with various assistance. EPA is part of the political commitment made by the Chinese government to fulfil sustainable and balanced development. By applying a policy process framework and qualitative text analysis to the government and universities’ official documents, we find EPA is primarily based on the Communist Party of China (CPC)’s ideological cornerstones of “common prosperity”. Over the past two decades, by conducting leadership secondment, faculty and student training, and ICT and library development, EPA has improved the development of universities in West China, and the central government’s current emphasis remains on the continuation of EPA. However, this paper argues that EPA cannot be going on indefinitely and that true sustainability is contingent on the capacity building of the recipient universities, rather than on the endless assistance from supporting universities. EPA is a localized action to achieve the Sustainable Development Goals (SDGs) in China. It sheds light on the connections between domestic aid and the SDGs from a supplementary perspective.
A Comparison of Simple Closed-Form Solutions for the EOQ Problem for Exponentially Deteriorating Items
Authors: Çalışkan Cenk
Published: July 2022

Some inventory items deteriorate and lose their useful life while in storage due to evaporation, spoilage, pilferage, and chemical or mechanical breakdown. Some examples of this phenomenon are the inventories of fresh food, batteries, electronic items, and petroleum products (such as gasoline and turpentine). Economic and environmental sustainability requires minimizing deterioration losses in inventories throughout the supply chain while optimizing the ordering decisions. This is especially important for food items because, globally, about one third of the food that is produced for human consumption is wasted, causing economic, environmental, political, and societal problems. Food production consumes large amounts of resources such as land, freshwater, fossil fuels, and labor. The same is true for items such as petroleum and chemical products. Exponential deterioration is a commonly used approach to model this phenomenon, which results in an exponentially decreasing inventory level function. An important extension of the basic economic order quantity (EOQ) model is its application to exponentially deteriorating items. In the exponentially deteriorating items model, the rate of deterioration per unit time for the stocked items is proportional to the amount of available physical inventory at any given time. This results in an exponentially declining inventory level over time. This problem normally does not lend itself to a closed-form optimal solution due to the coexistence of polynomial and exponential terms; hence, approximations are used, but the existing approximations yield closed-form solutions that are far from intuitive. In this research, we develop new approximate closed-form solutions for the basic problem and its backordering extensions that are intuitive and very easy to interpret, as well as more accurate; therefore, they are very attractive to practitioners. We provide extensive experimental results to demonstrate superiority of our approximate closed-form solutions.
Sustainability (Is Not) in the Boardroom: Evidence and Implications of Attentional Voids
Authors: Mazutis Daina , Hanly Katherine , Eckardt Anna
Published: July 2022

Strategic leadership and corporate governance scholars have long been interested in how boards of directors make decisions pertaining to important strategic issues that can have a material impact on their organizations. To date, however, research on board decision-making, especially as it relates to issues of corporate social responsibility (CSR), environmental management, or sustainability, has concentrated almost exclusively on structural, demographic, or ownership factors of boards and their impact on various aspects of corporate social or environmental performance. Even still, many reputable corporations with exemplary corporate governance structures continue to make questionable strategic decisions with regards to environmental sustainability. As such, this research seeks to look into the “black box” of corporate governance to understand exactly how boards of directors are dealing (or not) with issues related to environmental sustainability. To do so, we conducted a series of qualitative interviews with directors and were surprised to find that social and environmental sustainability was simply not debated in the boardroom. Using an attention-based view of the firms (ABV), we present a process-based model that explains this phenomenon and introduce the new construct of attentional voids so as to contribute to our understanding of governing for social and environmental sustainability.
Sustainable Product Innovation and Consumer Communication
Authors: Wang Shuyi , Su Daizhong
Published: July 2022

Sustainable product innovation and its communication with consumers are essential for the realisation of sustainability through sustainable consumption. This research conducted a structured review addressing sustainable product innovation, including sustainable product development and service, environmental and socio-economic impacts, communication of the sustainable product innovation to consumers via ecolabelling and declarations, and sustainability benchmarking. The review revealed that current research in sustainable product development and service focuses more on environmental and economic aspects, but the social aspect has not been given enough attention, and the interconnection between product development and service needs to be further addressed. Systematic sustainable innovation, considering the whole life cycle of the product to control and improve overall sustainability in the early product development stages should be paid more attention. To overcome the gaps, a framework for sustainable product development and services (SPDS) was developed and presented. Furthermore, this review found that communicating understandable environmental and socio-economic performance of products and services with consumers is still challenging. Barriers are identified in deriving benchmarks through sustainability performance assessments. This paper also provides examples of overcoming the barriers in sustainable benchmarking and communication with the “eco-cost” method, which engages both B2B and B2C customers to promote sustainable consumption.
Distinguishing the Impacts of Human Activities and Climate Change on the Livelihood Environment of Pastoralists in the Qinghai Lake Basin
Authors: Song Zhiyuan , Gao Ziyi , Yang Xianming , Ge Yuejing
Published: July 2022

Grassland vegetation is the largest terrestrial ecosystem in the Qinghai Lake Basin (QLB), and it is also the most important means of production for herders’ livelihoods. Quantifying the impact of climate change and human activities on grassland vegetation changes is an essential task for ensuring the sustainable livelihood of pastoralists. To this end, we investigated vegetation cover changes in the QLB from 2000 to 2020 using the normalized difference vegetation index (NDVI), meteorological raster data, and digital elevation and used residual analysis of multiple linear regression to evaluate the residuals of human activities. The residual analysis of partial derivatives was used to quantify the contribution of climate change and human activities to changes in vegetation cover. The results showed that: (1) The vegetation coverage of the QLB increased significantly (0.002/a, p < 0.01), with 91.38% of the area showing a greening trend, and 8.62% of the area suffering a degrading trend. The NDVI decreased substantially along the altitude gradient (−0.02/a, p < 0.01), with the highest vegetation coverage at 3600–3700 m (0.37/a). The vegetation degraded from 3200–3300 m, vegetation greening accelerated from 3300–3500 m, and vegetation greening slowed above 3500 m. (2) The contribution of climate change, temperature (T), and precipitation (P) to vegetation cover change were 1.62/a, 0.005/a, and 1.615/a, respectively. Below 3500 m, the vegetation greening was more limited by P. Above 3500 m, the vegetation greening was mainly limited by T. (3) Residual analysis showed that the contribution of human activities to vegetation cover was −1.618/a. Regarding the altitude gradient, at 3300–3500 m, human activities had the highest negative contribution to vegetation coverage (−2.389/a), and at 3200–3300 m, they had the highest positive contribution (0.389/a). In the past 21 years, the impact of human activities on vegetation coverage changed from negative to positive. Before 2009, the annual average NDVIres value was negative; after 2010, the average yearly NDVIres value turned positive. In general, the vegetation greening of the QLB depends on climate warming and humidification. The positive impact of human activities over the past decade was also essential for vegetation greening. These findings deepen our understanding of the QLB vegetation changes under climate change and human activities.
Towards Sustainable Sources of Omega-3 Long-Chain Polyunsaturated Fatty Acids in Northern Australian Tropical Crossbred Beef Steers through Single Nucleotide Polymorphisms in Lipogenic Genes for Meat Eating Quality
Authors: Mwangi Felista W. , Pewan Shedrach B. , Otto John R. , Adegboye Oyelola A. , Charmley Edward , Gardiner Christopher P. , Malau-Aduli Bunmi S. , Kinobe Robert T. , Malau-Aduli Aduli E. O.
Published: July 2022

This study aimed to identify single nucleotide polymorphisms (SNP) in lipogenic genes of northern Australian tropically adapted crossbred beef cattle and to evaluate associations with healthy lipid traits of the Longissimus dorsi (loin eye) muscle. The hypothesis tested was that there are significant associations between SNP loci encoding for the fatty acid binding protein 4 (FABP4), stearoyl-CoA desaturase (SCD) and fatty acid synthase (FASN) genes and human health beneficial omega-3 long-chain polyunsaturated fatty acids (ω3 LC-PUFA) within the loin eye muscle of northern Australian crossbred beef cattle. Brahman, Charbray, and Droughtmaster crossbred steers were fed on Rhodes grass hay augmented with desmanthus, lucerne, or both, for 140 days and the loin eye muscle sampled for intramuscular fat (IMF), fat melting point (FMP), and fatty acid composition. Polymorphisms in FABP4, SCD, and FASN genes with significant effects on lipid traits were identified with next-generation sequencing. The GG genotype at the FABP4 g.44677239C>G locus was associated with higher proportion of linoleic acid than the CC and CG genotypes (p < 0.05). Multiple comparisons of genotypes at the SCD g.21266629G>T locus indicated that the TT genotype had significantly higher eicosapentaenoic, docosapentaenoic, and docosahexaenoic acids than GG genotype (p < 0.05). Significant correlations (p < 0.05) between FASN SNP and IMF, saturated and monounsaturated fatty acids were observed. These results provide insights into the contribution of lipogenic genes to intramuscular fat deposition and SNP marker-assisted selection for improvement of meat-eating quality, with emphasis on alternate and sustainable sources of ω3 LC-PUFA, in northern Australian tropical crossbred beef cattle, hence an acceptance of the tested hypothesis.
Fair Models for Impartial Policies: Controlling Algorithmic Bias in Transport Behavioural Modelling
Authors: Vega-Gonzalo María , Christidis Panayotis
Published: July 2022

The increasing use of new data sources and machine learning models in transport modelling raises concerns with regards to potentially unfair model-based decisions that rely on gender, age, ethnicity, nationality, income, education or other socio-economic and demographic data. We demonstrate the impact of such algorithmic bias and explore the best practices to address it using three different representative supervised learning models of varying levels of complexity. We also analyse how the different kinds of data (survey data vs. big data) could be associated with different levels of bias. The methodology we propose detects the model’s bias and implements measures to mitigate it. Specifically, three bias mitigation algorithms are implemented, one at each stage of the model development pipeline—before the classifier is trained (pre-processing), when training the classifier (in-processing) and after the classification (post-processing). As these debiasing techniques have an inevitable impact on the accuracy of predicting the behaviour of individuals, the comparison of different types of models and algorithms allows us to determine which techniques provide the best balance between bias mitigation and accuracy loss for each case. This approach improves model transparency and provides an objective assessment of model fairness. The results reveal that mode choice models are indeed affected by algorithmic bias, and it is proven that the implementation of off-the-shelf mitigation techniques allows us to achieve fairer classification models.
The Analysis of Carbon Emission’s Characteristics and Dynamic Evolution Based on the Strategy of Unbalanced Regional Economic Development in China
Authors: Guo Quan , Liang Zijing , Bai Xiang , Lv Mengnan , Zhang Anying
Published: July 2022

Analyzing the evolution law of carbon emissions is particularly important for the designation of policies on energy conservation and emission reduction. Based on the regional division of China, this paper uses a spatial panel model to find the causes of the differences in carbon emission, and the non-parametric model, logarithmic mean Divisia index (LMDI) model and the extended STIRPAT model to analyze the relevant influencing factors in detail. From the studies in this paper, there come the following conclusions: (1) The environmental Kuznets curve (EKC) in the eastern region resembles the national EKC, demonstrating the same “N” pattern. However, the “upside-down U” pattern in the middle and western regions not only confirms the assumption of EKC in some Chinese regions but also demonstrates the effective restraint in high energy consumption and high emission levels when narrowing down the gaps between the central and western regions and the eastern regions. (2) In addition, good education can effectively suppress the increase in carbon emission, and every 1% increase in the proportion of educated people (college and above) results in emission reduction, respectively, by 0.22%, 0.51% and 0.44% in the eastern, central and western regions of China. (3) Significantly, the effect of tertiary industry structure on carbon emissions is positive, reflecting the trend of “deterioration” of China’s industrial structure over long time scales. This study functions positively in understanding the evolutionary pattern of regional carbon emissions and proposing differentiated policies on emission reduction.
Coupling Analysis of the Road-Network Spatiotemporal Distribution and the Economy in B&R Countries Based on GIS
Authors: Tong Yao , Zhou Cui , Lin Jingying , Tan Chengkai , Tang Wenjian
Published: July 2022

The Belt and Road (B&R) is a new strategy and measure for China to extend its opening up. To explore the influence of the spatiotemporal distribution of the national road network along the B&R on economic growth, this paper adopts the subjective and objective integrated weighting method to build a regional economic evaluation model, a transportation network evaluation model, and an economy–transportation coupling coordination degree model (E-T model). We also quantitatively analyze and evaluate the coordinated development of the economy and transportation in the countries along the B&R. Our results show that: (1) There are some differences in the comprehensive scores of economic level and transportation network in different countries, and the B&R has promoted the general economic and transportation level of various countries. (2) Approximately 84% of the countries have not reached a good coordination level, and the regional differences are significant, which indicates that the overall economic and transportation coupling coordination needs to be improved. (3) In recent years, driven by the B&R, the coupling coordination of approximately 30% of the countries has improved significantly. Therefore, the B&R not only has a positive impact on the economy and transportation of countries along the belt but also plays an important role in coordinating the economic and transportation development of countries, which is of great strategic significance.
Isolation and Characterisation of Hordatine-Rich Fractions from Brewer’s Spent Grain and Their Biological Activity on α-Glucosidase and Glycogen Phosphorylase α
Authors: Becker Daniela , Permann Sandra , Bakuradze Tamara , Stegmüller Simone , Richling Elke
Published: July 2022

Hordatines are a characteristic class of secondary metabolites found in barley which have been reported to be present in barley malt, beer and, recently, brewer´s spent grain (BSG). However, little is known about their biological activities such as antioxidative effects in beer or antifungal activity as their main task within the plants. We conducted an in vitro investigation of the activity of hordatines isolated from BSG towards enzymes of glucose metabolism. Hordatine-rich fractions from BSG were prepared by solid-liquid extraction (SLE) with 60% acetone followed by purification and fractionation. The fractions were characterised and investigated for their in vitro inhibitory potential on α-glucosidase and glycogen phosphorylase α (GPα). Both enzymes are relevant within the human glucose metabolism regarding the digestion of carbohydrates as well as the liberation of glucose from the liver. In total, 10 hordatine-rich fractions varying in the composition of different hordatines were separated and analysed by mass spectrometry. Hordatine A, B and C, as well as hydroxylated aglycons and many glycosides, were detected in the fractions. The total hordatine content was analysed by HPLC-DAD using a semi-quantitative approach and ranged from 60.7 ± 3.1 to 259.6 ± 6.1 µg p-coumaric acid equivalents/mg fraction. Regarding the biological activity of fractions, no inhibitory effect on GPα was observed, whereas an inhibitory effect on α-glucosidase was detected (IC50 values: 77.5 ± 6.5–194.1 ± 2.6 µg/mL). Overall, the results confirmed that hordatines are present in BSG in relatively high amounts and provided evidence that they are potent inhibitors of α-glucosidase. Further research is needed to confirm these results and identify the active hordatine structure.
Assessing Landslide Susceptibility by Coupling Spatial Data Analysis and Logistic Model
Authors: Ganga Antonio , Elia Mario , D’Ambrosio Ersilia , Tripaldi Simona , Capra Gian Franco , Gentile Francesco , Sanesi Giovanni
Published: July 2022

Landslides represent one of the most critical issues for landscape managers. They can cause injuries and loss of human life and damage properties and infrastructure. The spatial and temporal distribution of these detrimental events makes them almost unpredictable. Studies on landslide susceptibility assessment can significantly contribute to prioritizing critical risk zones. Further, landslide prevention and mitigation and the relative importance of the affecting drivers acquire even more significance in areas characterized by seismicity. This study aimed to investigate the relationship between a set of environmental variables and the occurrence of landslide events in an area of the Apulia Region (Italy). Logistic regression was applied to a landslide-prone area in the Apulia Region (Italy) to identify the main causative factors using a large dataset of environmental predictors (47). The results of this case study show that the logistic regression achieved a good performance, with an AUC (Area Under Curve) >70%. Therefore, the model developed would be a useful tool to define and assess areas for landslide occurrence and contribute to implementing risk mitigation strategy and land use policy.
Features of Plant Community and Driving Forces of Plant Community Succession in the Typical Desert Wetlands
Authors: Zhang Liping , Deng Longzhou , Sun Tianyu , Fei Kai , Song Naiping , Wang Xing
Published: July 2022

Desert wetlands play a significant role in flood regulation, water purification, biodiversity maintenance, and regional ecological environment improvement. Vegetation is a key factor affecting wetland function and it is important to study the features of plant community and the driving forces of plant community succession. The Ningxia Habahu National Nature Reserve, a typical desert wetland ecosystem, was selected to study the features of wetland plant communities including plant density, biomass and frequency, and vegetation coverage, as well as the habitats, structural characteristics, species composition, dominant population structure, and other characteristics of different ecosystems. Data was collected using long-term fixed-point observation, sampling monitoring, and other methods. The results showed that the total plant density, total biomass, Magalef index and Shannon–Wiener index of the different desert wetlands in the reserve area were all relatively low, which was caused by the poor habitat and salinization of the arid environment. There was no significant difference between the root–shoot ratio of the wetland plants in the reserve area and that of the construct species of other ecosystems. The specific leaf area of the wetland plants was also not significantly different from that of the construct species of other ecosystems. Vegetation nitrogen-to-phosphorus (N/P) ratios were found to be the key driving force for the succession of plant community in the desert wetlands. These results not only provide underlying insights for the improvement of species diversity and ecological environment, but also provide a scientific basis for the sustainable protection and restoration of typical desert wetlands.
Convolution Properties of q-Janowski-Type Functions Associated with (x,y)-Symmetrical Functions
Authors: Alsarari Fuad , Alzahrani Samirah
Published: July 2022

The purpose of this paper is to define new classes of analytic functions by amalgamating the concepts of q-calculus, Janowski type functions and (x,y)-symmetrical functions. We use the technique of convolution and quantum calculus to investigate the convolution conditions which will be used as a supporting result for further investigation in our work, we deduce the sufficient conditions, Po´lya-Schoenberg theorem and the application. Finally motivated by definition of the neighborhood, we give analogous definition of neighborhood for the classes S˜qx,y(α,β) and K˜qx,y(α,β), and then investigate the related neighborhood results, which are also pointed out.
An Asymptotic Expansion for the Generalized Gamma Function
Authors: Mahmoud Mansour , Almuashi Hanan , Moustafa Hesham
Published: July 2022

The symmetric patterns that inequalities contain are reflected in researchers’ studies in many mathematical sciences. In this paper, we prove an asymptotic expansion for the generalized gamma function Γμ(v) and study the completely monotonic (CM) property of a function involving Γμ(v) and the generalized digamma function ψμ(v). As a consequence, we establish some bounds for Γμ(v), ψμ(v) and polygamma functions ψμ(r)(v), r≥1.
Sampling Techniques and Error Estimation for Linear Canonical S Transform Using MRA Approach
Authors: Bhat Mohammad Younus , Alnssyan Badr , Dar Aamir H. , Dar Javid G.
Published: July 2022

A linear canonical S transform (LCST) is considered a generalization of the Stockwell transform (ST). It analyzes signals and has multi-angle, multi-scale, multiresolution, and temporal localization abilities. The LCST is mostly suitable to deal with chirp-like signals. It aims to possess the characteristics lacking in a classical transform. Our aim in this paper was to derive the sampling theorem for the LCST with the help of a multiresolution analysis (MRA) approach. Moreover, we discuss the truncation and aliasing errors for the proposed sampling theory. These types of sampling results, as well as methodologies for solving them, have applications in a wide range of fields where symmetry is crucial.
RIPpore: A Novel Host-Derived Method for the Identification of Ricin Intoxication through Oxford Nanopore Direct RNA Sequencing
Authors: Ryan Yan , Harrison Abbie , Trivett Hannah , Hartley Catherine , David Jonathan , Clark Graeme C. , Hiscox Julian A.
Published: July 2022

Ricin is a toxin which enters cells and depurinates an adenine base in the sarcin-ricin loop in the large ribosomal subunit, leading to the inhibition of protein translation and cell death. We postulated that this depurination event could be detected using Oxford Nanopore Technologies (ONT) direct RNA sequencing, detecting a change in charge in the ricin loop. In this study, A549 cells were exposed to ricin for 2–24 h in order to induce depurination. In addition, a novel software tool was developed termed RIPpore that could quantify the adenine modification of ribosomal RNA induced by ricin upon respiratory epithelial cells. We provided demonstrable evidence for the first time that this base change detected is specific to RIP activity using a neutralising antibody against ricin. We believe this represents the first detection of depurination in RNA achieved using ONT sequencers. Collectively, this work highlights the potential for ONT and direct RNA sequencing to detect and quantify depurination events caused by ribosome-inactivating proteins such as ricin. RIPpore could have utility in the evaluation of new treatments and/or in the diagnosis of exposure to ricin.
Impact of Chemical Properties of Human Respiratory Droplets and Aerosol Particles on Airborne Viruses’ Viability and Indoor Transmission
Authors: Ahlawat Ajit , Mishra Sumit Kumar , Herrmann Hartmut , Rajeev Pradhi , Gupta Tarun , Goel Vikas , Sun Yele , Wiedensohler Alfred
Published: July 2022

The airborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified as a potential pandemic challenge, especially in poorly ventilated indoor environments, such as certain hospitals, schools, public buildings, and transports. The impacts of meteorological parameters (temperature and humidity) and physical property (droplet size) on the airborne transmission of coronavirus in indoor settings have been previously investigated. However, the impacts of chemical properties of viral droplets and aerosol particles (i.e., chemical composition and acidity (pH)) on viability and indoor transmission of coronavirus remain largely unknown. Recent studies suggest high organic content (proteins) in viral droplets and aerosol particles supports prolonged survival of the virus by forming a glassy gel-type structure that restricts the virus inactivation process under low relative humidity (RH). In addition, the virus survival was found at neutral pH, and inactivation was observed to be best at low (<5) and high pH (>10) values (enveloped bacteriophage Phi6). Due to limited available information, this article illustrates an urgent need to research the impact of chemical properties of exhaled viral particles on virus viability. This will improve our fundamental understanding of indoor viral airborne transmission mechanisms.
Avian IRF1 and IRF7 Play Overlapping and Distinct Roles in Regulating IFN-Dependent and -Independent Antiviral Responses to Duck Tembusu Virus Infection
Authors: Xiang Chengwei , Yang Zekun , Xiong Ting , Wang Ting , Yang Jie , Huang Mei , Liu Dingxiang , Chen Ruiai
Published: July 2022

Avian interferon regulatory factors 1 and 7 (IRF1 and IRF7) play important roles in the host’s innate immunity against viral infection. Our previous study revealed that duck tembusu virus (DTMUV) infection of chicken fibroblasts (DF1) and duck embryo fibroblasts (DEFs) induced the expression of a variety of IFN-stimulated genes (ISGs), including VIPERIN, IFIT5, CMPK2, IRF1, and IRF7. IRF1 was further shown to play a significant role in regulating the up-expression of VIPERIN, IFIT5, and CMPK2 and inhibiting DTMUV replication. In this study, we confirm, through overexpression and knockout approaches, that both IRF1 and IRF7 inhibit DTMUV replication, mainly via regulation of type I IFN expression, as well as the induction of IRF1, VIPERIN, IFIT5, CMPK2, and MX1. In addition, IRF1 directly promoted the expression of VIPERIN and CMPK2 in an IFN-independent manner when IRF7 and type I IFN signaling were undermined. We also found that non-structural protein 2B (NS2B) of DTMUV was able to inhibit the induction of IFN-β mRNA triggered by Newcastle disease virus (NDV) infection or poly(I:C) treatment, revealing a strategy employed by DTMUV to evade host’s immunosurveillance. This study demonstrates that avian IRF7 and IRF1 play distinct roles in the regulation of type I IFN response during DTMUV infection.
Cell and Animal Models for SARS-CoV-2 Research
Authors: Bestion Eloïne , Halfon Philippe , Mezouar Soraya , Mège Jean-Louis
Published: July 2022

During the last two years following the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, development of potent antiviral drugs and vaccines has been a global health priority. In this context, the understanding of virus pathophysiology, the identification of associated therapeutic targets, and the screening of potential effective compounds have been indispensable advancements. It was therefore of primary importance to develop experimental models that recapitulate the aspects of the human disease in the best way possible. This article reviews the information concerning available SARS-CoV-2 preclinical models during that time, including cell-based approaches and animal models. We discuss their evolution, their advantages, and drawbacks, as well as their relevance to drug effectiveness evaluation.
Climate Change Impacts on Stream Water Temperatures in a Snowy Cold Region According to Geological Conditions
Authors: Suzuki Hiroaki , Nakatsugawa Makoto , Ishiyama Nobuo
Published: July 2022

This study clarifies how climate change affects stream temperatures in snowy cold regions, where groundwater impacts vary with geological conditions. We developed a physics-based water circulation model that incorporates an atmospheric and land surface process model considering snow processes, a runoff model, and a water temperature estimation model. Small watersheds in the mountainous area of Hokkaido formed the study area, and the runoff model was assigned different parameters depending on the geological characteristics. Using these parameters, changes in water temperature were calculated with respect to changes in the meteorological data in historical and future simulations. Current water temperatures were effectively reproduced by the model, and following the IPCC RCP 8.5 scenario, future water temperatures in the distribution area for new pyroclastic flows were predicted to remain lower in summer than in the distribution area of older formations. The findings of this study will be useful in informing conservation measures for river ecosystems, including the prioritization of streams where cold-water fish need to be conserved.
A Case Study of Tidal Analysis Using Theory-Based Artificial Intelligence Techniques for Disaster Management in Taehwa River, South Korea
Authors: Kareem Kola Yusuff , Seong Yeonjeong , Kim Kyungtak , Jung Younghun
Published: July 2022

Monitoring tidal dynamics is imperative to disaster management because it requires a high level of precision to avert possible dangers. Good knowledge of the physical drivers of tides is vital to achieving such a precision. The Taehwa River in Ulsan City, Korea experiences tidal currents in the estuary that drains into the East Sea. The contribution of wind to tide prediction is evaluated by comparing tidal predictions using harmonic analysis and three deep learning models. Harmonic analysis is conducted on hourly water level data from 2010–2021 using the commercial pytides toolbox to generate constituents and predict tidal elevations. Three deep learning models of long short-term memory (LSTM), gated recurrent unit (GRU), and bi-directional lstm (BiLSTM) are fitted to the water level and wind speed to evaluate wind and no-wind scenarios. Results show that Taehwa tides are categorized as semidiurnal tides based on a computed form ratio of 0.2714 in a 24-h tidal cycle. The highest tidal range of 0.60 m is recorded on full moon spring tide indicating the significant lunar pull. Wind effect improved tidal prediction NSE of optimal LSTM model from 0.67 to 0.90. Knowledge of contributing effect of wind will inform flood protection measures to enhance disaster preparedness.