The survey of serum retinol of the children aged 0~4 years in Zhejiang Province, China

<p>Abstract</p> <p>Background</p> <p>Vitamin A can have a positive impact on growth and development of children, but vitamin A deficiency (VAD) was found to be a public health problem in Zhejiang Province, China in 1998. There have been no studies on this topic in Zhejiang Province recently. This study was designed to evaluate the serum retinol levels of children aged 0~4 years in Zhejiang Province, southeast China. This epidemiological data will help design supplementation strategies for vitamin A in high-risk groups and improve their vitamin A status.</p> <p>Methods</p> <p>Children were randomly recruited for this study using a stratified sampling method. A blood sample was collected from each child. Assessment included C-reactive protein (CRP), serum retinol measured with HPLC and a questionnaire completed providing for family information and nutritional status. Logistic regression analysis was used to evaluate the risk factors for VAD in children.</p> <p>Results</p> <p>A group of 357 subjects aged 1 day to 4 years were recruited. The mean plasma retinol concentration was 1.653 (sd 0.47) μmol/L. There were 3.08% (11/357) of children affected with VAD, and 7.28% (26/357) of children had low vitamin A status, but none of the children showed any clinical symptoms of VAD. There was no significant difference in the levels of plasma retinol and the incidence rate of VAD between male and female children. Multivariate logistic regression analysis showed that living in urban region, having parents with good education and taking vitamin A capsule regularly prevented children from VAD, whereas being young (less than 2 years old) was a risk factor.</p> <p>Conclusion</p> <p>Low vitamin A status remains a nutritional problem in Zhejiang Province. The high-risk group in this study were young, dwelled in rural regions, had parents with poor education and did not take a regular vitamin A containing supplement.</p

Corrigendum to: The TianQin project: current progress on science and technology

In the originally published version, this manuscript included an error related to indicating the corresponding author within the author list. This has now been corrected online to reflect the fact that author Jun Luo is the corresponding author of the article

Edge detection guide network for semantic segmentation of remote-sensing images

The acquisition of high-resolution satellite and airborne remote sensing images has been significantly simplified due to the rapid development of sensor technology. Several practical applications of high-resolution remote sensing images (HRRSIs) are based on semantic segmentation. However, single-modal HRRSIs are difficult to classify accurately in the complex situation of some scene objects; therefore, the semantic segmentation of multi-source information fusion is gaining popularity. The inherent difference between multimodal features and the semantic gap between multi-level features typically affect the performance of existing multi-mode fusion methods. We propose a multimodal fusion network based on edge detection to address these issues. This method aids multimodal information fusion by utilizing spatial information contained in the boundary. An edge detection guide module is included in the feature extraction stage to realize the boundary information through the fusion of details and semantics between high-level and low-level features. The boundary information is extended into the well-designed multimodal adaptive fusion block (MAFB) to obtain the multimodal fusion features. Furthermore, a residual adaptive fusion block (RAFB) and a spatial position module (SPM) in the feature decoding stage have been designed to fuse multi-level features from the standpoint of local and global dependence. We compared our method to several state-of-the-art (SOTA) methods using the International Society for Photogrammetry and Remote Sensing's (ISPRS) Vaihingen and Potsdam datasets. The final results demonstrate that our method achieves excellent performance.This work was supported by the National Natural Science Foundation of China under Grant 61502429

GPU-Based Computation of Formation Pressure for Multistage Hydraulically Fractured Horizontal Wells in Tight Oil and Gas Reservoirs

A mathematical model for multistage hydraulically fractured horizontal wells (MFHWs) in tight oil and gas reservoirs was derived by considering the variations in the permeability and porosity of tight oil and gas reservoirs that depend on formation pressure and mixed fluid properties and introducing the pseudo-pressure; analytical solutions were presented using the Newman superposition principle. The CPU-GPU asynchronous computing model was designed based on the CUDA platform, and the analytic solution was decomposed into infinite summation and integral forms for parallel computation. Implementation of this algorithm on an Intel i5 4590 CPU and NVIDIA GT 730 GPU demonstrates that computation speed increased by almost 80 times, which meets the requirement for real-time calculation of the formation pressure of MFHWs

Cold Model Study on Melting of Ice Made by KCl Solution in Gas-Water Two-Phase Plume Area

With the increasing of scrap usage in steelmaking processes, the melting of scrap becomes a very important phenomenon that limits the productivity and tap-to-tap time. Ice-water systems have been widely used to study the melting of scrap and alloys. In this study, the melting rate of saturated KCl solution ice spheres in gas-water two-phase plume zone are studied as a function of height of location, gas flowrate, and melt temperature. The results show that the shape of the ice sphere gradually changes firstly from spherical to elliptical, and finally becomes an irregular state. 1) The decreasing of the distance between the ice sphere and the bottom plugs, 2) the increasing of the gas flowrate, 3) the slightly increasing of bath temperature will all benefits the melting rate of ice spheres