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Background: Wenzhou virus (WENV), a member of the Mammarenavirus genus in the Arenaviridae family, has been detected in wild rodents from eight provinces in China and Southeast Asia. The IgG-antibodies to WENV have been detected in healthy people and patients with unknown fever andrespiratory symptoms. However, since WENV was discovered, its potential harmfulness has been underestimated due to its mild symptoms after human infection, similar to respiratory diseases. Thus, it is imperative to further understand the pathogenicity of WENV and its mechanisms, to improve WENV surveillance in wild rodents, particularly Rattus norvegicus, and to detect the prevalence of WENV as needed. Results: During 2017-2021, a total of 390 wild rodents were collected from six provinces in eastern and southern coastal areas, containing nine species of rats, of which 36.4% were Rattus norvegicus. Samples of each tissue were collected and PCR amplification was performed. Four WENV-positive samples were detected, all from Rattus norvegicus. No genomic sequence of WENV was detected in Rattus flavipectus, Rattus losea, Suncus murinus, Apodemus agrarius, Mus musculus, Microtus fortis, Micromys minutus, and Niviventer niviventer from Jiangsu, Zhejiang, Fujian, Hainan, Guangdong and Guangxi Provinces. The full-length strain of WENV (HNHKW40/2020) was amplified from Rattus norvegicus in Hainan, which was most closely related to Wufeng/ WFS. The nucleotide sequence homology was 84.5-89.4% and the amino acid sequence homology was 91.6-98.9%. The sequences obtained in Xiamen, Fujian Provinces had more than 90% homology with WENV, which may be a strain of WENV. 83% of the positive sequences detected in Wuxi, Jiangsu Province were homologous to Lassa virus (LASV), which may be a member of LASV. Phylogenetic analysis indicated that all WENVs clustered together to form the Old World group with LASV and Loei River virus (LORV). Conclusions: In this study, we systematically examined the prevalence of WENV amongrodents inthe southeast coast of China and characterized the genome of a newly discovered WENV strain, confirming that rodents of Rattus norvegicus played a main role in WENV transmission. The need to enhance WENV surveys in wild rodents and humans was emphasized.

The flammability limit of fuel is an important property in determining the explosivity characteristics. In order to improve the safety in the use of hydrogen in O2/CO2 atmosphere, the lower flammability limits of oxy-hydrogen mixture were studied experimentally. The lower flammability limits of hydrogen-oxygen diluted by CO2 were measured using a 5 L cylindrical reactor. In this method, the lower flammability limit was determined by the minimum hydrogen concentration that allows flame propagation. The upward flame was used for the critical criterion of the flame propagation. The measured lower flammability limits of H2/O2/CO2 increased from 4.25% to 6.5% with the diluted gas (CO2, N2) concentration rising from 0 to 85%, while the lower flammability limits of H2/O2/N2 mixture increased from 4.25% to 4.5%. Compared with N2, the lower flammability limits of H2 were raised by the adding CO2. The main reason is that the specific heat of CO2 is higher than that of N2. Moreover, CO2 directly participates in chemical reactions and heat radiation. The theoretical calculation results show that the thermal physical endothermic accounts for more than 90% of the total heat dissipation, which is the main factor affecting the lower flammability limits of hydrogen under O2/CO2 atmosphere. The experimental results are very helpful for developing a prediction model of the LFL for H2 in O2/CO2 atmosphere and theory results improve the understanding of the effect of CO2 on the LFL.

The paper presents the results of the lower flammability limit (LFL) of C3H8/O2/CO2 at normal temperature and pressure. The LFL of C3H8/O2/CO2 mixture was measured with an explosion vessel. The mea...

Model-based polarimetric decomposition can separate to some extent the backscattered radar signals from the vegetation canopy and the underlying ground, hence enabling a strategy for soil moisture retrieval in vegetated agricultural fields. However, the volume scattering models used in previous studies are only applicable to specific cases, making it difficult to completely remove the volume component induced by the vegetation layer. In this paper, three generalized volume scattering models (i.e., generalized volume scattering model (GVSM), simplified adaptive volume scattering model (SAVSM), and simplified Neumann volume scattering model (SNVSM)) are incorporated in the decomposition and evaluated for soil moisture retrieval. Considering the complexity and descriptive ability of the available physical models, a modified two-component model-based decomposition is proposed as the basic decomposition framework. This decomposition is also based on the physical constraint of the dielectric constants included in the model. The employed models combine an X-Bragg surface scattering model with three continuous generalized volume scattering models. The analytic solution of the parameters is obtained, and the minimum power criterion is used to determine the optimal solution to fit the model. By using the proposed model-based decomposition framework, the performance of the three models to simulate the canopy scattering and, as a result, to later estimate soil moisture under agricultural vegetation is evaluated. Fully polarimetric RADARSAT-2 C-band images acquired on eight dates in 2013 and 2015 over fields covered by two crops (wheat and soybean) were employed for validation. Results show that the proposed decomposition method, using any of the three volume scattering models, can provide promising inversion results of soil moisture, with RMSEs ranging from 2.89 to 7.43 [vol.%]. Compared with the other two models, the SNVSM simulates the vegetation contribution more accurately in this framework, and it provides a stable soil moisture inversion performance at different crop phenological stages, with an optimal overall accuracy of RMSE=4.99 [vol.%] and a correlation coefficient of R=0.78. This work was supported in part by the National Natural Science Foundation of China (Grant No. 41820104005, 42171387, 41804004, 42101400), the Canadian Space Agency SOAR-E Program (Grant No. SOAR-E-5489), and the Spanish Ministry of Science and Innovation (AEI Grant No. PID2020-117303GB-C22).

Esta tesis trata de la aplicación en agricultura de los datos polarimétricos obtenidos mediante satélites de observación de la Tierra eqipados con radar de apertura sintética. Los principales objetivos de la tesis se centran en dos productos finales: la clasificación de tipo de cultivo y la estimación de la altura de los cultivos. Para ello se hace uso de técnicas de descomposición polarimétrica basadas en modelos con datos SAR polarimétricos multi-temporales, medidos con RADARSAT-2 en banda C. Las contribuciones de esta tesis se resumen a continuación: 1. Se ha investigado por primera vez la aplicación de la descomposición de Neumann a la clasificación de cultivos. En este estudio se propone un método de clasificación supervisado basado en la descomposición de Neumann y el clasificador de bosque aleatorios (denominado "ND-RF") para la clasificación de cultivos. Las relaciones entre los tres parámetros de la descomposición de Neumann y los tres parámetros de la descomposición de Cloude-Pottier se han validado en esta aplicación empleando datos reales. Se ha hecho un amplio estudio sobre la importancia de los diversos parámetros en la clasificación de cultivos y se han comparado de forma completa las dos descomposiciones. 2. Se ha presentado una demostración y validación exhaustivas sobre la estimación de la altura del cultivo de maíz mediante observables polarimétricos con métodos de regresión de aprendizaje automático. En este estudio se explota un gran conjunto de datos formado por imágenes multi-temporales de banda C y mediciones in situ casi síncronas de la altura de los cultivos a lo largo de tres años en dos zonas de Canadá. Se utilizaron dos métodos típicos de regresión de aprendizaje automático: RFR y SVR. Se ha investigado la importancia de las características de entrada y el rendimiento después de filtrar la selección de observables. Work supported by the Spanish Ministry of Science and Innovation, Research State Agency (AEI) and European Regional Development Funds under project TEC2017-85244-C2-1-P.

Polarization Coherence Tomography (PCT) method has the good performance in deriving the vegetation vertical structure. However, Errors caused by temporal decorrelation and vegetation height and ground phase always propagate to the data analysis and contaminate the results. In order to overcome this disadvantage, we exploit Complex Least Squares Adjustment Method to compute vegetation height and ground phase based on Random Volume over Ground and Volume Temporal Decorrelation (RVoG + VTD) model. By the fusion of different polarimetric InSAR data, we can use more observations to obtain more robust estimations of temporal decorrelation and vegetation height, and then, we introduce them into PCT to acquire more accurate vegetation vertical structure. Finally the new approach is validated on E-SAR data of Oberpfaffenhofen, Germany. The results demonstrate that the robust method can greatly improve accusation of vegetation vertical structure.

Vegetation height is an important parameter in quantifying the terrestrial carbon cycle effectively. P band synthetic aperture radar (SAR) is good at monitoring forest areas, which is sensitive to the contributions from vegetation layer and ground. Random Volume over Ground (RVoG) model has been widely applied to forest height inversion. Corresponding single baseline or muti-baseline methods have been established, such as three-stage and nonlinear iteration methods, whose good performance have been test with differential wavelength and areas. However, all the methods do not pay much attention to the complex coherence errors, and take measure to reduce the errors. In this paper, a new dual-baseline polarimetric SAR interferometry vegetation height inversion method, dual-baseline complex least squares adjustment (DBCLSA), is proposed. The DBCLSA method behind the concept of complex least squares adjustment. The main idea of DBCLSA method is as follow. Firstly, the adjustment model is summarized as combined adjustment of complex real and imagine parts. And then, stochastic model is established based on Cramer-Rao bounds. After that, we show the linearization method and parameter solving method. At last, the obtained volume-only coherence values are used to vegetation height retrieval. The DBCLSA is validated on E-SAR P band data of BioSAR2008 in Sweden. The results of Cloude dual-baseline method are computed at the same time. Compared with ground true measurement data, the result of new approach is more accurate.

This article analyzes FDI (Foreign direct investment)’s Overflow Effect on High-tech Enterprises of Shannxi Province typically in two aspects of qualitative analysis and quantitative analysis on the basis of the review and summary of the general situation of FDI in the Hign-tech Enterprises of Shannxi Province. On the aspect of qualitative analysis, researches have been carried on in angles of economic growth, international trade, tax, employment, industrial structure and local enterprise competitive power. On the aspect of quantitative analysis, the researches have applied the improvable Cobb-Douglas productive function model, which was set forth by Solow in 1957, as the basic model and the method of Johansen Co-integration test. It provides policies and advices relating to the results of analysis and demonstration.

Micro-sources mostly connect to converters to output voltage and frequency demanded. PWM converters can improve the generatorspsila power factor to be unit, and produce less harmonics. So PWM converters have good effects on improving the power quality. By changing voltage amplitude and phase of PWM converter, generators may create active and reactive power neatly to meet the load demand. And thus maintain the voltage and frequency stability. In this paper, a PWM converter model is given and a kind of software named PSCAD is used to simulate. The simulation results show that the conclusions above are right.

Centro de Investigación Forestal (CIFOR), Canopy height is an essential feature in forest inventory, and for the assessment of biomass and carbon budgets. Spatially explicit maps of forest height over large areas can be derived from satellite synthetic aperture radar data. We aimed to evaluate the capacity of TanDEM-X (TDX) data to assess canopy height in Mediterranean forests of Spain, which are of relatively short height (typically < 20 m), diverse in species and structure, and adapted to summer drought. Interferogram coherence was retrieved from single-pol image pairs. Forest height estimation was carried out by previously fitting a sinc-type function, with two empirical parameters, to the data measured. Six types of forest were defined to assess the convenience of stratification for model implementation. The influence of terrain slope, forest type, and interferometric baseline on model performance was evaluated, and a strategy for large area mapping was proposed and tested. TDX-derived heights were compared to a contemporaneous LiDAR-derived canopy height model for assessment of quality. Results limited to slopes below 10° provided the best results, reaching R2 = 0.91 and root-mean-square error = 1.24 m in one of the study sites. However, in some areas the results were much worse, especially in regions characterized by rugged terrain with broadleaved species. This work demonstrates the feasibility of deriving a forest height map over the entire area of Spain from TDX data. Stratification per slope interval and selection of long interferometric baselines are recommended., This work was supported in part by the Spanish Ministry of Science, Innovation, and University and EU EFDR funds under Project TEC2017-85244-C2-1-P, and in part by the National Natural Science Foundation of China under Grant 41820104005, Grant 41804004, and Grant 41904004. The work of Cristina Gómez was supported under Project FORESTCHANGE (AGL2016-76769-C2-1-R) German Aerospace Center (DLR) provided all the TanDEM-X data under Project OTHER7349, 10 Pág