Modeling and correction analysis of regional ionospheric modeling

The Global Navigation Satellite System (GNSS), due to its all-weather lobal monitoring and high precision, makes it possible to use GNSS observation data to accurately extract the total electron content (TEC) of the ionosphere and to study ionospheric activities. At the same time, the delay error caused by the ionosphere to GNSS signals is also one of the main sources of error in GNSS positioning. For regional users, using as few stations as possible to establish an ionospheric TEC model within the region has higher efficiency and range practicability. This paper realizes the establishment of a regional ionospheric TEC model based on spherical harmonics, and establishes an ionospheric TEC model in the 15∼45°N and 105°∼135°E regions, which is compatible with IGS (International GNSS Service, IGS) and CAS (Chinese Academy of Sciences, CAS), the overall difference is more than 70% within ±3TECU

Complex Dynamical Sampling Mechanism for the Random Pulse Circulation Model and Its Application

The fast multi-pulse spectrum is a spectrum acquisition method that obtains an average pulse amplitude in a dynamic window, which improves the energy resolution by sharpening peaks in the acquired spectra, but produces the counting loss. Owing to the counting loss problem, a counting rate multiplication method based on uniform sampling, also called the pulse circulation method, is presented in this paper. Based on the theory of mathematical statistics and uniform sampling, this method adopted a dynamic sample pool to update the pulse amplitude sample in real time. Random numbers from the uniform distribution were sampled from the sample pool, and the sampled results were stored in the random pulse circulator so that the pulse amplitude information used for spectrum generation was uniformly expanded. In the experiment section, the obtained spectrum was analyzed to verify the multiplication effect of the pulse circulation method on the counting rate and the compensation effect of the fast multi-pulse spectrum algorithm on the counting rate loss. The results indicated that the characteristic peaks of each element in the X-ray spectrogram obtained by the pulse circulation method could realize counting rate multiplication uniformly, and the multiplication ratio of every element was approximately equal. This is of great significance for obtaining an accurate X-ray fluorescence spectrum

Complex Dynamical Sampling Mechanism for the Random Pulse Circulation Model and Its Application

The fast multi-pulse spectrum is a spectrum acquisition method that obtains an average pulse amplitude in a dynamic window, which improves the energy resolution by sharpening peaks in the acquired spectra, but produces the counting loss. Owing to the counting loss problem, a counting rate multiplication method based on uniform sampling, also called the pulse circulation method, is presented in this paper. Based on the theory of mathematical statistics and uniform sampling, this method adopted a dynamic sample pool to update the pulse amplitude sample in real time. Random numbers from the uniform distribution were sampled from the sample pool, and the sampled results were stored in the random pulse circulator so that the pulse amplitude information used for spectrum generation was uniformly expanded. In the experiment section, the obtained spectrum was analyzed to verify the multiplication effect of the pulse circulation method on the counting rate and the compensation effect of the fast multi-pulse spectrum algorithm on the counting rate loss. The results indicated that the characteristic peaks of each element in the X-ray spectrogram obtained by the pulse circulation method could realize counting rate multiplication uniformly, and the multiplication ratio of every element was approximately equal. This is of great significance for obtaining an accurate X-ray fluorescence spectrum

Design and evaluation of 32P-labeled hydroxyapatite nanoparticles for bone tumor therapy

AbstractThe clinical diagnosis and treatment of malignant bone tumors are still major clinical challenges due to their high incidence are difficulty. Targeted therapies have become a critical approach to treat bone tumors. In recent years, radiopharmaceuticals have been used widely and have shown potent and efficient results in treating bone tumors, among which 32P and the labeled radiopharmaceuticals play an essential role. In this study, the 32P-labeled hydroxyapatite (HA) was prepared through chemical synthesis (32P-Hap) and physical adsorption (32P-doped-Hap). The in vitro stability of 32P-labeled HA was analyzed to assess the superiority of the new-found chemical synthesis. The radiolabeling yield and stability of chemical synthesis (97.6 ± 0.5%) were significantly improved compared with physical adsorption (92.7 ± 0.4%). Furthermore, the CT results corroborate that 32P-Hap (100 μCi) +DOX group has the highest tumor suppression rate and can effectively reduce bone destruction. The results corroborate the effectiveness of the chemical synthesis and validate the application of 32P-Hap in bone tumors. Therefore, 32P-Hap (100 μCi) + DOX may be an effective strategy for bone metastasis treatments

Application of an Improved Seeds Local Averaging Algorithm in X-ray Spectrum

As an element content analysis technology, X-ray fluorescence spectrometry can be used for quantitative or semiquantitative analysis of the element content in the sample, which is of great significance for mineral census and spent fuel reprocessing. Due to the limitation of the inherent energy resolution of the detector itself, the accuracy of X-ray fluorescence analysis is difficult to be greatly improved. In some applications, even if the semiconductor detector with the best energy resolution is used, the characteristic peaks of different elements cannot be completely separated. Therefore, greatly improving the energy resolution of the detection system is a hot issue in the existing research field. To solve these problems, this paper analyzes the advantages and disadvantages of the traditional MCA (multichannel analyzer) and SLA (seeds local averaging) algorithm and proposes an ISLA (improved seeds local averaging) algorithm based on mathematical statistics. In the section of theoretical derivation, the principle of ISLA algorithm is described, whose theoretical characteristics and spectral results with different parameters are derived and simulated. In the application effect evaluation, the spectrum obtained by each method is analyzed in detail. Simulation and experimental results show that the spectrum obtained by SLA algorithm has a smaller full width at half maximum than that obtained by MCA, but the seed average process in SLA algorithm also reduces its counting rate. The optimized ISLA algorithm can not only effectively reduce the full width at half maximum of the spectral line and sharpen the spectrum peak but also compensate for the loss of the count rate of SLA algorithm