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Satellite remote sensing has become an important means of forest fire monitoring because it has the advantages of wide coverage, few ground constraints and high dynamics. When utilizing satellites for forest fire hotspot monitoring, two types of ground hotspots, agricultural and other fire hotspots can be ruled out through ground object features. False forest fire hotspots within forested areas must be excluded for a more accurate distinction between forest fires and non-forest fires. This study utilizes spatio-temporal data along with time-series classification to excavate false forest fire hotspots exhibiting temporal characteristics within forested areas and construct a dataset of such false forest fire hotspots, thereby achieving a more realistic forest fire dataset. Taking Hunan Province as the research object, this study takes the satellite ground hotspots in the forests of Hunan Province as the suspected forest fire hotspot dataset and excludes the satellite ground hotspots in the forests such as fixed heat sources, periodic heat sources and recurring heat sources which are excavated. The validity of these methods and results was then analyzed. False forest fire hotspots, from satellite ground hotspots extracted from 2019 to 2023 Himawari-8/9 satellite images, closely resemble the official release of actual forest fires data and the accuracy rate in the actual forest fire monitoring is 95.12%. This validates that the method employed in this study can improve the accuracy of satellite-based forest fire monitoring. [ABSTRACT FROM AUTHOR]

Improving the accuracy of zenith tropospheric delay (ZTD) models is an important task. However, the existing ZTD models still have limitations, such as a lack of appropriate vertical adjustment function and being unsuitable for China, which has a complex climate and great undulating terrain. A new approach that considers the time-varying vertical adjustment and delicate diurnal variations of ZTD was introduced to develop a new grid ZTD model (NGZTD). The NGZTD model employed the Gaussian function and considered the seasonal variations of Gaussian coefficients to express the vertical variations of ZTD. The effectiveness of vertical interpolation for the vertical adjustment model (NGZTD-H) was validated. The root mean squared errors (RMSE) of the NGZTD-H model improved by 58% and 22% compared to the global pressure and temperature 3 (GPT3) model using ERA5 and radiosonde data, respectively. The NGZTD model's effectiveness for directly estimating the ZTD was validated. The NGZTD model improved by 22% and 31% compared to the GPT3 model using GNSS-derived ZTD and layered ZTD at radiosonde stations, respectively. Seasonal variations in Gaussian coefficients need to be considered. Using constant Gaussian coefficients will generate large errors. The NGZTD model exhibited outstanding advantages in capturing diurnal variations and adapting to undulating terrain. We analyzed and discussed the main error sources of the NGZTD model using validation of spatial interpolation accuracy. This new ZTD model has potential applications in enhancing the reliability of navigation, positioning, and interferometric synthetic aperture radar (InSAR) measurements and is recommended to promote the development of space geodesy techniques. [ABSTRACT FROM AUTHOR]

The atmospheric weighted mean temperature (Tm) is a key parameter in global navigation satellite system (GNSS) water vapor retrieval and can convert the zenith wet delay (ZWD) into precipitable water vapor (PWV). However, there are some shortcomings in the existing Tm models, such as the detailed time-varying lapse rate not being considered. Additionally, the spatiotemporal characteristics of Tm need to be further refined. Therefore, we developed a new global high-precision and high-spatiotemporal-resolution Tm model considering time-varying lapse rate using the latest European Centre for Medium-Range Weather Forecasts ReAnalysis 5 (ERA5) atmospheric reanalysis data. Firstly, a global multidimensional Tm lapse rate model (NGGTm-H model) was developed using the sliding window algorithm. Secondly, the daily variation characteristics of Tm and its relationships with geographical situation were investigated. Finally, a hybrid-grid global Tm model considering time-varying lapse rate (NGGTm model) was developed. To verify the effectiveness of the proposed model, the NGGTm model was compared with the Bevis and GPT3 models using the Tm data recorded at 378 radiosonde stations in 2017 and the surface grid Tm data calculated from the ERA5 reanalysis data. The results show that taking the surface grid Tm data of ERA5 as reference values, the average root mean square error (RMSE) value predicted by the NGGTm model was 2.84 K, which was higher with 0.50 K, 0.18 K and 0.06 K than those of the Bevis, GPT3-5 and GPT3-1 models, respectively. Meanwhile, taking the Tm data from the radiosonde stations as the reference values, the mean bias and RMSE of the NGGTm model were 0.10 K and 3.30 K, respectively, which exhibit the best accuracy and stability among the Bevis, GPT3-5 and GPT3-1 models. [ABSTRACT FROM AUTHOR]

Gold mineralization in the Jiaojia gold belt was formed in a structurally- dominant hydrothermal mineral system showing a close spatial association with the Jiaojia detachment fault. This study delves into the Jiaojia gold belt from the perspective of coupled spatial association and ore-forming processes by employing spatial analysis of three-dimensional (3D) models, 3D ore-forming numerical modeling, and 3D prospectivity modeling using machine learning techniques (random forest (RF) and multilayer perceptron (MLP)). The overarching goal is to gain insight into the structural-hydrothermal gold system and pinpoint potential areas of deep-seated gold deposits for future exploration endeavors. The spatial analysis of ore-controlling faults uncovers a close correlation between gold enrichment and specific fault geometrical attributes, including a dip angle ranging from 20° to 40°, minimal variations in dip angle (less than 5°), and convex topographical features. These attributes likely stem from the influence of fault morphology on the flow and pooling of fluids. In conjunction with this, 3D ore-forming numerical modeling of structural deformation and fluid flow reveals that gold mineralization is intertwined with moderate volumetric strain and shear strain of rock and fluid divergence. This interaction seems particularly pronounced in areas characterized by channel-like or gentle features. Consequently, it is plausible that gold distribution in the Jiaojia region is the outcome of a comprehensive coupling process involving strain localization, rock deformation, fluid flow, heat transfer and/or interaction. The deep gold prospectivity models of RF and MLP for the Jiaojia district jointly using the predictive variables of fault geometry features and ore-forming simulation data (volume strain, shear strain, temperature variation, and fluid flux) exhibit higher AUC (area under the curve) values compared to models employing individual predictor variable datasets. This improvement underscores their enhanced predictive capability. The prospectivity results thus were used for identifying gold potential within the Jiaojia region, where five promising gold targets at depth were ultimately determined. [ABSTRACT FROM AUTHOR]

Precipitable water vapor (PWV) with high precision and high temporal resolution estimated by Global Navigation Satellite System (GNSS) is widely used in atmospheric research and weather forecasting. However, most previous works are not consensual concerning the characteristics of the PWV at different time scales and the identification of active and break spells during summ er monsoon climate in Guangxi, China. Taking radiosonde (RS) observations as reference, a strong correlation (R > 0.97) exists between GNSS PWV and RS PWV with a mean root mean square error (RMSE) of 2.68 mm. The annual, seasonal, monthly, and diurnal PWV variations of three years (2017, 2018 and 2020) over Guangxi in were comprehensively investigated using 104 GNSS stations and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis (ERA5). The mean annual bias and RMSE between GNSS PWV and ERA5 PWV are −1.04 mm and 2.63 mm, respectively. The monthly bias and RMSE range are −0.77 to 3.87 mm, 1.32 to 4.45 mm, and the daily range is −1.41 to 1.07 mm and 1.11 to 5.02 mm, respectively. Additionally, the adopted average standardized rainfall anomaly criteria also identified 7/7/3 active spells and 5/3/7 break spells during the summer monsoon (June–September) from 2017 to 2020, respectively. During the three-year period, the daily amplitude ranges for active spells varied from 1.41 to 2.49 mm, 0.69 to 5.4 mm, and 0.88 to 1.41 mm, while the ranges for break spells were 2.45 to 6.76 mm, 1.66 to 8.17 mm, and 1.48 to 2.99 mm, respectively. The results show a superior performance of GNSS PWV compared to ERA5 PWV in Guangxi, and the maximum, minimum and occurrence time of PWV anomaly vary slightly with the season and the topography of stations. Despite temperature primarily exhibiting a negative correlation with rainfall, acting as a dampener, a positive correlation remains evident between PWV and rainfall. Therefore, densely distributed GNSS stations exhibit excellent capabilities in quantifying atmospheric water vapor and facilitating real-time monitoring of small and medium-scale weather phenomena. [ABSTRACT FROM AUTHOR]

In order to solve the power quality problems and eliminate the neutral sections in the railway, the implementation of the continuous co‐phase traction power supply system (CCTPSS) is the development trend of the future. However, various parameters of the compensator in CCTPSS have a huge impact on the resonance, which will possibly change the original resonance characteristic of the railway. Therefore, the parameters design of the compensator has become a difficult problem to be solved. An optimization mode method is proposed in this paper to obtain the influence of the compensator on the resonance characteristic of CCTPSS and the optimal solution of each parameter is obtained with the goal of suppressing resonance and minimizing the cost. Firstly, the impedance analysis and transfer function analysis are used to establish models for CCTPSS. It is found that the equivalent harmonic impedance of the traction substation decreases after adding the compensator, which will inevitably cause the resonance frequency to increase. By comparing the resonance points of the original traction power supply system (TPSS) and CCTPSS, the results show that the parameters of the compensator have a greater influence on the resonance point in CCTPSS. At last, taking the CCTPSS based on LCL‐type reactive power comprehensive compensator (RPCC) as an example to carry out the optimization mode method, the result proves that this method is not only beneficial to the suppression of harmonic resonance, but also helpful for reducing the cost of the RPCC. [ABSTRACT FROM AUTHOR]

This paper proposes a novel glass fiber‐reinforced polymer (GFRP)‐timber‐steel tube‐concrete composite column (GTSC) that combines an outer steel tube with GFRP fabric reinforcement, an inner timber core, and concrete for the rest of the space. The mechanical behavior of eight specimens of novel composite columns was investigated considering diameters of timber cores, layer numbers, and angles of GFRP laminates. The results showed that as the size of the timber core increased from 0 to 50 mm, the ductility and the energy dissipation capacity of the composite column maximum increased by 61.5% and 63.4%, respectively. Conversely, the ultimate load carrying capacity and stiffness decreased. It was also found that the timber core weakened the strength of the confined concrete. However, timber core reduced the weight of columns, which slowed down the reduction of the ultimate load carrying capacity of per unit GTSCs, with the stiffness remains unchanged. GFRP laminates with an angle of 60° provide the best stiffness and ductility, and the layer numbers of GFRP has a positive effect on GTSC's mechanical performance. In addition, an analytical model was proposed based on the ultimate equilibrium method, which accounts for the ultimate bearing capacity of GTSC based on the influence of timber. Analyses revealed a good correlation between analytical and experimental results. [ABSTRACT FROM AUTHOR]

In recent years, geographically weighted regression (GWR) models have been widely used to address the spatial heterogeneity and spatial autocorrelation of PM2.5, but these studies have not fully considered the effects of all potential variables on PM2.5 variation and have rarely optimized the models for residuals. Therefore, we first propose a modified GWR model based on principal component analysis (PCA-GWR), then introduce five different spatial interpolation methods of radial basis functions to correct the residuals of the PCA-GWR model, and finally construct five combinations of residual correction models to estimate regional PM2.5 concentrations. The results show that (1) the PCA-GWR model can fully consider the contributions of all potential explanatory variables to estimate PM2.5 concentrations and minimize the multicollinearity among explanatory variables, and the PM2.5 estimation accuracy and the fitting effect of the PCA-GWR model are better than the original GWR model. (2) All five residual correction combination models can better achieve the residual correction optimization of the PCA-GWR model, among which the PCA-GWR model corrected by Multiquadric Spline (MS) residual interpolation (PCA-GWRMS) has the most obvious accuracy improvement and more stable generalizability at different time scales. Therefore, the residual correction of PCA-GWR models using spatial interpolation methods is effective and feasible, and the results can provide references for regional PM2.5 spatial estimation and spatiotemporal mapping. (3) The PM2.5 concentrations in the study area are high in winter months (January, February, December) and low in summer months (June, July, August), and spatially, PM2.5 concentrations show a distribution of high north and low south. [ABSTRACT FROM AUTHOR]

The Dayingezhuang orogenic gold deposit, located in the northwestern Jiaodong Peninsula, is hosted by the Zhaoping detachment fault, but the paleostress regime during the mineralization period remains poorly understood. In this study, a series of numerical modeling experiments with variable stress conditions were carried out using FLAC3D software to determine the orientation of paleostress and the fluid migration processes during the ore-forming period. The results show that the simple compression or tension stress model led to fluid downward or upward flow along the fault, respectively, accompanying the expansion deformation near the hanging wall or footwall of the Zhaoping fault, which is inconsistent with the known NE oblique mineralization distribution at Dayingezhuang. The reverse and strike-slip model shows that the shear stress was distributed in the gentle dip sites of the fault, and the expansion space occurred in the geometric depression sites of the fault, which is also inconsistent with the known mineralization distribution. The normal and strike-slip model shows that shear stress was distributed in the sites where the fault geometry transforms from steep to gentle. In addition, the expansion deformation zones appeared at sites with dip angles of 35~60° in the footwall and extended along with the NE-trending distribution from shallow to deep levels. The numerical results are quite consistent with the known mineralization, suggesting that the fault movement during the mineralization stage is a combination of the local strike-slip and the NW–SE extension in the Dayingezhuang deposit. Under this stress regime (σ1 NE–SW, σ2 vertical, σ3 NW–SE), the NE dilation zones associated with fault deformation served as channels for the ore-forming fluid migration. Based on the numerical modeling results, the deeper NE levels of the No. 2 orebody in the Dayingezhuang deposit have good prospecting potential. Thus, our study not only highlights that gold mineralization at Dayingezhuang is essentially controlled by the detachment fault geometry associated with certain stress directions but also demonstrates that numerical modeling is a robust tool for identifying potential mineralization. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite System (GNSS) has become a powerful tool for sensing precipitable water vapor (PWV), which is important in investigating long‐term climate or nowcasting. Zenith hydrostatic delay (ZHD) and weighted mean temperature (Tm) are the two key parameters for retrieving PWV GNSS observations. ZHD is generally derived from the Saastamoinen model by using surface pressure or numerical weather model (NWM). However, the lack of meteorological observations located at or near the GNSS sites is a big challenge for the calculation of accurate ZHD, leading to inconvenience in GNSS‐derived PWV. In this study, a method for GNSS retrieval in China by using ZHD from the NWM and Tm derived from IGPT2w is proposed. First, a new grid model, namely CGZHD model, is developed for the vertical adjustment of ZHD in China. Then, two types of ZHD products derived from NWM data, that is, postprocessing and forecast ones, namely ZHD and ZHDFC, respectively. Finally, the performance of GNSS PWV estimation for 18 GNSS sites is evaluated with PWVs from collocated radiosonde sites for China. Results show that the CGZHD model has excellent performance against the GPT2w model and previous studies. ZHD and ZHDFC from NWM present high precision after vertical adjustment. In terms of GNSS PWV retrieval, two modes of GNSS PWV estimation results, that is, ZHD and ZHDFC obtained from postprocessing and forecast ones, respectively, show excellent performance in China. The proposed method does not require any in situ meteorological information as input and thus has potential applications for high‐precision and real‐time GNSS PWV retrieval in China. Key Points: A new grid model is developed for the vertical adjustment of zenith hydrostatic delay (ZHD) in ChinaThe performances of postprocessing and forecast ZHD products from numerical weather model are assessedTwo approaches are proposed for retrieving precipitable water vapor in China [ABSTRACT FROM AUTHOR]

Objective: The objective was to assess the association between 25-hydroxyvitamin D (25OHD) level and diabetic kidney disease (DKD) in Chinese patients with type 2 diabetes. Methods: Data pertaining to 351 in-patients with type 2 diabetes were collected. Subjects were classified into three groups based on the level of urinary albumin-to-creatinine ratio (UACR). UACR < 30 mg/g was defined as normoalbuminuria, while UACR levels of 30–300 mg/g and ≥ 300 mg/g were defined as microalbuminuria and macroalbuminuria, respectively. Serum 25OHD and other clinical characteristics among various UACR groups were compared. The relationship between albuminuiria and 25OHD was analyzed. Results: The prevalence of 25OHD insufficiency in the microalbuminuria group was significantly higher than that in the normoalbuminuria group (25.1% vs. 19.6%; P < 0.05); patients with macroalbuminuria had the highest prevalence of 25OHD deficiency (37.8%; P < 0.01 versus normoalbuminuria). Logistic regression analyses demonstrated that low 25OHD levels were associated with DKD [odds ratio (OR) = 1.51, 95% confidence interval (CI) 1.16–1.97). The association was more robust after adjusting for sex, hypertension, increased systolic blood pressure, glycemic status, and hyperuricemia (OR = 1.62, 95% CI 1.19–2.20). Conclusions: The prevalence of vitamin D insufficiency/deficiency in patients with albuminuria was overtly higher than that in patients without albuminuria among Chinese adults with type 2 diabetes. Vitamin D insufficiency/deficiency was independently associated with DKD in type 2 diabetes. [ABSTRACT FROM AUTHOR]

Key Clinical Message: A rare case of resistance to thyroid hormone (RTH) complicated with Graves’ hyperthyroidism was reported. The management of this disease is similar to that of Graves’ disease. Antithyroid drug therapy is the first choice, and iodine therapy and surgery are not recommended due to the possibility of severe hypothyroidism and enlargement of the pituitary gland. [ABSTRACT FROM AUTHOR]

Introduction The synthetic oligonucleotide field is developing rapidly, with applications in medicine (antigen drugs), molecular biology (gene isolation probes) and biochemistry (diagnostics). They also are used as primers in polymerase [...]

This paper models and analyzes the cable traction network (CTN) of a novel AC 110 kV-50 Hz cable traction power supply system (TPSS). First, we propose an equivalent model of the CTN that considers the charging current of the cables, in order to research the capacitance effect of the CTN. Then, three cases based on the novel TPSS are used to validate the proposed model, and to investigate the characteristics of the CTN. Simulation results show that the proposed model is effective in calculating both the charging current and the voltage on the cable system. Calculation results from case 2 show that the capacitance effect is mainly caused by the charging current flowing through the system's reactance, which consists of the reactance of the power system and the reactance of the main transformer. The reactance of the system, compensation coefficient and cable length can each influence the charging current and capacitance effect of the cable. Case 3 illustrates that the novel TPSS is very effective in supplying power and can greatly reduce the number of neutral sections; thus, it is suitable for application in future railway designs. [ABSTRACT FROM AUTHOR]

With the increase in workload from a variety of in vivo and in vitro screening procedures, new analytical methodologies to perform bioseparations in an accurate and high-throughput manner are in [...]

Unbalance and reactive power currents of electric railway will result in poor power quality of three-phase industrial power grid. A co-phase traction power supply system is introduced in this paper to solve these problems by adopting single-phase ac-dc-ac converter. The converter is connected between two secondary windings of traction transformer with abilities of active power transmission and reactive power compensation. Because of the power conversion, the co-phase supply system can utilize single-phase feeding connection scheme instead of traditional two-phase feeding scheme. An actual 10 MVA/27.5 kV co-phase system with impedance-matching balance transformer is designed, developed, and tested. Its real-time detection, control, and distribution algorithms with field programmable gate array-based implementation are introduced. Some test running results validate the performance of the digital controller and demonstrate the feasibility of the proposed co-phase power supply system. [ABSTRACT FROM PUBLISHER]

An active power compensator (APC) based on single-phase back-to-back power converter is proposed in this paper to solve problems of power quality of electric railway power supply system. This system adopts a single-phase feeding connection, which is called cophase power supply scheme. In this scheme, APC connects the balance transformer between feeding phase for power supply and another phase for compensation. It has some characteristics, such as active power balancing, reactive power compensating, and harmonics filtering. In order to achieve these characteristics, the control scheme requires seven combination models. In this paper, a multifunctional control algorithm is proposed to realize every conceivable model. A cophase system with APC based on field programmable gate array (FPGA) and YNvd balance transformer is also designed and evaluated. The experimental results obtained from this prototype illustrate that the compensating ability is extremely high in steady-state and dynamic responses, and the power quality of a substation with distorted loads can be improved integrally. [ABSTRACT FROM PUBLISHER]

Tropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (Tm) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim) data have been used to calculate and model the tropospheric delay, Tm, and PWV, the limitations of the temporal and spatial resolutions of the reanalysis data have affected their performance. The release of the fifth-generation accurate global atmospheric reanalysis (ERA5) and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provide the opportunity to overcome these limitations. The performances of the zenith tropospheric delay (ZTD), zenith wet delay (ZWD), Tm, and zenith hydrostatic delay (ZHD) of ERA5 and MERRA-2 data from 2016 to 2017 were evaluated in this work using GNSS ZTD and radiosonde data over the globe. Taking GNSS ZTD as a reference, the ZTD calculated from MERRA-2 and ERA5 pressure-level data were evaluated in temporal and spatial scales, with an annual mean bias and root mean square (RMS) of 2.3 and 10.9 mm for ERA5 and 4.5 and 13.1 mm for MERRA-2, respectively. Compared to radiosonde data, the ZHD, ZWD, and Tm derived from ERA5 and MERRA-2 data were also evaluated on temporal and spatial scales, with annual mean bias values of 1.1, 1.7 mm, and 0.14 K for ERA5 and 0.5, 4.8 mm, and –0.08 K for MERRA-2, respectively. Meanwhile, the annual mean RMS was 4.5, 10.5 mm, and 1.03 K for ERA5 and 4.4, 13.6 mm, and 1.17 K for MERRA-2, respectively. Tropospheric parameters derived from MERRA-2 and ERA5, with improved temporal and spatial resolutions, can provide a reference for GNSS positioning and PWV retrieval. [ABSTRACT FROM AUTHOR]

Power quality and neutral section are two technical problems that hinder the development of electrified railway to high-speed and heavy railway. The co-phase power supply technology is one of the best ways to solve these two technical problems. At present, a V type connection traction transformer is widely used in a power frequency single-phase AC traction power supply system, especially in high-speed railway. In this paper, a new type of co-phase power supply system for electrified railway based on V type connection traction transformer is proposed. One single-phase winding in the V type connection traction transformer is used as main power supply channel, and three ports are used as compensation ports. Neutral section is no longer set with traction substation, and the train is continuously powered through. The independent single-phase Static Var Generators (SVGs) are used to compensate the three-phase imbalance caused by single-phase traction load. When necessary, the power factor can be improved at the same time. The principle, structure, control strategy, and capacity configuration of the technical scheme are analyzed in this paper, and the effectiveness of the scheme is verified by using the measured data of electrified railway. The advantage of this scheme lies in the universal applicability of the V type connection traction transformer, and the flexibility of the SVG device. [ABSTRACT FROM AUTHOR]

Tropospheric delay is one of the main errors affecting high-precision positioning and navigation and is a key parameter of water vapor detection in the Global Navigation Satellite System (GNSS). The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is the latest generation of reanalysis data collected by the National Aeronautics and Space Administration (NASA), which can be used to calculate tropospheric delay products with high spatial and temporal resolution. However, there is no report analyzing the accuracy of the zenith tropospheric delay (ZTD) and zenith wet delay (ZWD) calculated from MERRA-2 data. This paper evaluates the performance of the ZTD and ZWD values derived from global MERRA-2 data using global radiosonde data and International GNSS Service (IGS) precise ZTD products. The results are as follows: (1) Taking the precision ZTD products of 316 IGS stations from around the world from 2015 to 2017 as the reference, the average root mean square (RMS) of the ZTD values calculated from the MERRA-2 data is better than 1.35 cm, and the accuracy difference between different years is small. The bias and RMS of the ZTD values show certain seasonal variations, with a higher accuracy in winter and a lower accuracy in summer, and the RMS decreases from the equator to the poles. However, those of the ZTD values do not show obvious variations according to elevation. (2) Relative to the radiosonde data, the RMS of the ZWD and ZTD values calculated from the MERRA-2 data are better than 1.37 cm and 1.45 cm, respectively. Furthermore, the bias and RMS of the ZWD and ZTD values also show some temporal and spatial characteristics, which are similar to the test results of the IGS stations. It is suggested that MERRA-2 data can be used for global tropospheric vertical profile model construction because of their high accuracy and good stability in the global calculation of the ZWD and ZTD. [ABSTRACT FROM AUTHOR]