Search

The PIESAT-01 constellation is the world's first multi-baseline distributed synthetic aperture radar (SAR) constellation with a "Cartwheel" formation. The "Cartwheel" formation is a unique formation in which four satellites fly in companion orbits, ensuring that at any given moment, the main satellite remains at the center, with three auxiliary satellites orbiting around it. Due to this unique configuration of the PIESAT-01 constellation, four images of the same region and six pairs of baselines can be obtained with each shot. So far, there has been no imaging and interference research based on four-satellite constellation measured data, and there is an urgent need to explore algorithms for the "Cartwheel" configuration imaging and digital surface model (DSM) production. This paper introduces an improved bistatic SAR imaging algorithm under the four-satellites interferometric mode, which solves the problem of multi-orbit nonparallelism in imaging while ensuring imaging coherence and focusing ability. Subsequently, it presents an interferometric processing method for the six pairs of baselines, weighted fusion based on elevation ambiguity from different baselines, to obtain a high-precision DSM. Finally, this paper selects the Dingxi region of China and other regions with diverse terrains for imaging and DSM production and compares the DSM results with ICESat-2 global geolocated photon data and TanDEM DSM data. The results indicate that the accuracy of PIESAT-01 DSM meets the standards of China's 1:50,000 scale and HRTI-3, demonstrating a high level of precision. Moreover, PIESAT-01 data alleviate the reliance on simulated data for research on multi-baseline imaging and multi-baseline phase unwrapping algorithms and can provide more effective and realistic measured data. [ABSTRACT FROM AUTHOR]

Obtaining accurate and real-time spatial distribution information regarding crops is critical for enabling effective smart agricultural management. In this study, innovative decision fusion strategies, including Enhanced Overall Accuracy Index (E-OAI) voting and the Overall Accuracy Index-based Majority Voting (OAI-MV), were introduced to optimize the use of diverse remote sensing data and various classifiers, thereby improving the accuracy of crop/vegetation identification. These strategies were utilized to integrate crop/vegetation classification outcomes from distinct feature sets (including Gaofen-6 reflectance, Sentinel-2 time series of vegetation indices, Sentinel-2 time series of biophysical variables, Sentinel-1 time series of backscatter coefficients, and their combinations) using distinct classifiers (Random Forests (RFs), Support Vector Machines (SVMs), Maximum Likelihood (ML), and U-Net), taking two grain-producing areas (Site #1 and Site #2) in Haixi Prefecture, Qinghai Province, China, as the research area. The results indicate that employing U-Net on feature-combined sets yielded the highest overall accuracy (OA) of 81.23% and 91.49% for Site #1 and Site #2, respectively, in the single classifier experiments. The E-OAI strategy, compared to the original OAI strategy, boosted the OA by 0.17% to 6.28%. Furthermore, the OAI-MV strategy achieved the highest OA of 86.02% and 95.67% for the respective study sites. This study highlights the distinct strengths of various remote sensing features and classifiers in discerning different crop and vegetation types. Additionally, the proposed OAI-MV and E-OAI strategies effectively harness the benefits of diverse classifiers and multisource remote sensing features, significantly enhancing the accuracy of crop/vegetation classification. [ABSTRACT FROM AUTHOR]

Citrus plants are prone to phosphorus (P) deficiency, especially in acidic soil, making them more dependent on root-associated endophytic fungi for growth and development. Beni-Madonna, a hybrid of Citrus nanko × C. amakusa, is a citrus known as "tangor" that is highly popular in China and other parts of the world due to its deep red color and jelly-like flesh. In this study, the inoculation response to two arbuscular mycorrhizal fungi (Diversispora versiformis, Dv; Funneliformis mosseae, Fm) and an endophytic fungus (Serendipita indica, Si) with regard to the growth, leaf gas exchange, light energy efficiency, P levels, acid phosphatase activity, and expression of the purple acid phosphatase (PAP) and phosphate transporter (PT) genes through a potted experiment using Beni-Madonna (tangor) citrus plants grafted on trifoliate orange (Poncirus trifoliata) was studied. Two years following inoculation, the root fungal colonization rates of inoculated plants were significantly increased, accompanied by an increase in plant height and stem diameter, with Si presenting the best effect. Fungal inoculations also significantly increased the leaf chlorophyll index, nitrogen-balance index, photosynthesis rate, stomatal conductance, transpiration rate, photosynthetic efficiency, and quantum yield of PSII, while it reduced photoinhibition and heat dissipation, with Si having the best effect on light energy efficiency. Si significantly increased leaf and root P levels, as well as root CsPAP1‒3, CsPT2, CsPT3, and CsPT7 expression and soil acid phosphatase activity; Fm in mycorrhizal fungi significantly increased leaf and root P levels, as well as root CsPT1 and CsPT7 expression and root/soil acid phosphatase activity. These observations suggested an advantage of Si over the other two AMF in terms of improved plant growth and P acquisition, while Fm displayed prominent effects on increased photosynthetic efficiency. [ABSTRACT FROM AUTHOR]

Simple Summary: Giardia duodenalis is a common zoonotic intestinal protozoan and causes significant economic losses and potential risks to public health. China is among the several major producers of donkeys worldwide, with approximately 2.6 million donkeys being reared in 2019, but studies on G. duodenalis infection in donkeys were limited. Thus, in order to better understand the molecular epidemiology of G. duodenalis in donkeys in China, 815 fecal samples were collected from donkeys in three representative geographical locations in Shanxi Province, North China, to determine the presence and genotypes of G. duodenalis based on three established loci (tpi, bg, and gdh). A total of 137 out of 815 fecal samples were detected as G. duodenalis-positive with an overall prevalence of 16.81%. Among the detected assemblages A, B, and E, the most predominant assemblage was B in the three study areas. Three MLGs (MLG-novel-1 to 3) were identified with multilocus genotypes (MLGs) analysis and validated by a phylogenetic tree. This is the first report of G. duodenalis infection in donkeys in Shanxi Province, which not only enhances our understanding of the genetic diversity of G. duodenalis in donkeys in China but also provides essential baseline data for the prevention and control of G. duodenalis infection donkeys in the study areas. Giardia duodenalis is a ubiquitous flagellated protozoan, causing significant economic losses to animal husbandry and posing threats to public health. China ranks the world's sixth largest major producer of donkeys, rearing approximately 2.6 million donkeys in 2019, but limited investigation of G. duodenalis prevalence has been conducted in the past, and it is yet to be known whether donkeys in Shanxi Province are infected with G. duodenalis. In the present study, a total of 815 fecal samples collected from donkeys in representative regions of Shanxi Province, North China, were examined for G. duodenalis using nested PCR. Then, the assemblages and multilocus genotypes (MLGs) were examined based on three established loci: namely, β-giardin (bg), triosephosphate isomerase (tpi), and glutamate dehydrogenase (gdh). The overall prevalence of G. duodenalis in donkeys in Shanxi Province was 16.81% (137/815). The region was identified as the main risk factor for the observed difference in G. duodenalis prevalence in donkeys among the three study areas (χ2 = 21.611, p < 0.001). Assemblages A, E, and B were identified, with the latter as the predominant assemblage. Three MLGs (MLG-novel-1 to 3) were formed based on sequence variation among the three loci. The present study reveals the presence of G. duodenalis in donkeys in Shanxi Province, North China, for the first time, which not only enriches the data on the distribution of G. duodenalis in donkeys in China but also provides useful baseline data for planning control strategies against G. duodenalis infection in the sampled areas. [ABSTRACT FROM AUTHOR]

Increasing human activities have greatly influenced the ecosystem and the use of ecological resources, and the unbalanced urban–rural development in China (urban and rural areas being two major bases of human activities) has always been accompanied by heterogeneous ecological effects. Human appropriation of net primary production (HANPP) is an integrated indicator quantifying the human domination of productivity and harvest in the biosphere. Identifying the unbalanced constraints of urban and rural development on HANPP has become necessary for improving human–land relationships. This study analyzed the spatial distribution and regional differentiations of the HANPP in China in 2015 and investigated how HANPP and its components responded to unbalanced regional urban–rural development. The results show that the total amount of HANPP was 2.68 PgC and gradually decreased from the southeast to the northwest of China in 2015, representing 60.33% of the NPPpot. In addition, HANPPluc, harvest through cropland, livestock grazing, and forestry contributed 60.70%, 29.86%, 8.53%, and 0.91%, respectively, to the total HANPP, with HANPPluc playing the dominant role in 21 provinces. There was a significant differentiation (p < 0.05) in the spatial distribution of HANPP (gC/m2), HANPPharv (gC/m2), and HANPPluc (gC/m2), especially between the Huanyong Hu Line and the western–eastern part of China, fundamentally resulting from uneven regional development. In addition, biomass production–consumption decoupling existed in most regions in China, 17 provinces were identified as consumption type, and a universal positive correlation (p < 0.05) was identified between the production–consumption ratio of occupied biomass and HANPPharv (%HANPP). Different drive mechanisms were found between urban–rural development and HANPP, and each HANPP index was more likely to be affected by urban economy (UE), rural population (RP), and rural agricultural technology (RA) in China. The higher regional average nighttime light intensity, the proportion of the built-up area, and the urban road area corresponded with a large HANPPluc value. Conversely, HANPP would decrease as the proportion of urban green spaces increased. Furthermore, HANPP (%NPPpot) and HANPP (gC/m2) mostly depended on the rural development index, while HANPPluc and HANPPharv were mainly controlled by urban and rural development, respectively. Our findings help understand, first, how unbalanced regional development influences human-induced biomass occupation, the comprehensive urban ecological construction, and rural ecological restoration and, second, that the overall planning of urban–rural integration development must be strengthened to face greater ecological pressures in the future. [ABSTRACT FROM AUTHOR]

Long-span cable-stayed bridge is a typical wind-sensitive structure because of its light weight and great flexibility. The reliability evaluation of the cable-stayed bridge under wind action becomes a key issue during bridge design and operation. In this paper, taking Xiangshan Harbor highway cable-stayed bridge in Ningbo City in China as the engineering background, ANSYS 15.0 is used to build a finite element model of this bridge to explore its aerostatic stability and influencing parameters, then the static wind reliability of this bridge is analyzed. Firstly, considering the structural nonlinearity and the nonlinearity of static wind load comprehensively, the critical wind speed of aerostatic instability of the Xiangshan Harbor cable-stayed bridge is calculated by the internal and external double iteration method. Then the influence of the initial wind attack angle, steel wire breakage rate of the stay cables, static three-component force coefficients, and cable broken position on the static wind stability of this bridge are discussed. Thus, the variation rule of the critical aerostatic instability wind speed is obtained, and the parameter that has the greatest impact on the static wind stability of the cable-stayed bridge in service is determined. Finally, considering the randomness of these key parameters, they are treated as random variables, Latin hypercube sampling (LHS) method is used to obtain samples of random variables to calculate aerostatic instability wind speed for a given sample by self-written calculation program, and on this basis, static wind reliability analysis is conducted by the checking point method, which provides strong support for the static wind risk evaluation of the existing long-span cable-stayed bridge. [ABSTRACT FROM AUTHOR]

With the development of bridge structures towards being light weight and having a large span , the overall flexibility, and, hence, wind sensitivity, of the bridge increases. Flutter is one of the pivotal factors considered in the design and operation stage for long-span cable-stayed bridges due to its devastating impact, often intrigued by relatively low instability caused by wind speed. This paper presents a reliability theory-based numerical analysis on bridge flutter stability and its influence law of key parameters using a real bridge, the Xiangshan Harbor highway cable-stayed bridge in China. The analysis starts with creating a full scale of finite element model for the bridge in service to calculate the flutter derivative and time-dominated combining rational function in order to obtain the critical-flutter wind speed, and then the aerodynamic self-excited forces on the bridge and flutter time-history response are calculated to identify the flutter critical wind speed. Further, the influence of key parameters for flutter reliability, including the stiffness of the main girder, wire breaking rate, damping ratio and cable breakage location are analyzed comprehensively to achieve the change law of critical flutter wind speed with these parameters. Considering the uncertainty of the actual parameters, these parameters are taken as random variables, and the reliability index and failure probability of bridge flutter are calculated according to their probability distribution and the Latin hypercube sampling method. On this basis, a few suggestions are put forward for flutter risk-control during the service of this cable-stayed bridge, which can further enhance the design theory for long-span flexible bridges. [ABSTRACT FROM AUTHOR]

Carbon Capture, Utilization and Storage, also referred to as Carbon Capture, Utilization and Sequestration (CCUS), is one of the novel climate mitigation technologies by which CO2 emissions are captured from sources, such as fossil power generation and industrial processes, and further either reused or stored with more attention being paid on the utilization of captured CO2. In the whole CCUS process, the dominant migration pathway of CO2 after being injected underground becomes very important information to judge the possible storage status as well as one of the essential references for evaluating possible environmental affects. Interferometric Synthetic Aperture Radar (InSAR) technology, with its advantages of extensive coverage in surface deformation monitoring and all-weather traceability of the injection processes, has become one of the promising technologies frequently adopted in worldwide CCUS projects. In this study, taking the CCUS sequestration area in Shizhuang Town, Shanxi Province, China, as an example, unmanned aerial vehicle (UAV) photography measurement technology with a 3D surface model at a resolution of 5.3 cm was applied to extract the high-resolution digital elevation model (DEM) of the study site in coordination with InSAR technology to more clearly display the results of surface deformation monitoring of the CO2 injection area. A 2 km surface heaving dynamic processes before and after injection from June 2020 to July 2021 was obtained, and a CO2 migration pathway northeastward was observed, which was rather consistent with the monitoring results by logging and micro-seismic studies. Additionally, an integrated monitoring scheme, which will be the trend of monitoring in the future, is proposed in the discussion. [ABSTRACT FROM AUTHOR]

Recent research on marine environment pollution (MEP) has primarily focused on legislative and market-based instruments rather than on understanding related knowledge, attitudes, and behaviors. Within this context, we used a survey of university students in China to investigate attitudes and behaviors related to MEP. Specifically, we employed a tri-component attitude model to analyze questionnaire data from 446 randomly selected students. Our results indicate that participants had a good knowledge of MEP. Furthermore, our data revealed the following three MEP-related attitudinal clusters: activists, supporters, and onlookers. Activists showed negative attitudes toward MEP with strong anti-MEP behaviors. Supporters also had negative attitudes toward MEP but performed less anti-MEP behaviors. Finally, onlookers exhibited indifferent attitudes with neutral MEP-related behaviors. Each of the three attitudinal clusters varied according to the demographic characteristics of the participants. The implications of these results on the reduction in MEP were discussed.

This study aimed to examine the profile of COVID-19-related public stigma and its correlates in the general population of China. A cross-sectional online survey was conducted in China from 7 May to 25 May in 2020. A total of 1212 participants from the general population completed the survey measuring their stigmatizing attitudes towards COVID-19, as well as knowledge and causal attributions of COVID-19. Univariate and multivariate analyses were performed to examine the correlates of COVID-19-related public stigma. A total of 31.8% of participants endorsed stigmatization towards people with COVID-19. Those who were of older age (t = -3.97, p < 0.001), married (F = 3.04, p < 0.05), had a lower level of education (F = 8.11, p < 0.001), and a serious psychological response (F = 3.76, p < 0.05) reported significantly higher scores of public stigma. Dangerousness ( B = 0.047, p < 0.001), fear ( B = 0.059, p < 0.001), anger ( B = 0.038, p < 0.01), and responsibility ( B = 0.041, p < 0.001) were positively associated with public stigma. This study shows that public stigma related to COVID-19 is prevalent in the general population of China. Actions against public stigma need to contain the spread of misinformation about COVID-19, alter inappropriate attributions, alleviate unfavorable reactions, and provide psychosocial support for the public.