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To establish a reliable method for measuring the radiochemical purity of technetium[99mTc] methylenediphosphonate injection, analysis conditions such as stationary phase and developing solvent were studied. The analytical method was methodologically verified in accordance with the Chinese Pharmacopoeia and other relevant provisions. The results showed that the analytical method of single-system thin-layer chromatography, in which polyamide-6 thin-layer plate was used as the stationary phase, V (1 mol/L sodium acetate solution): V (0.1 mol/L hydrochloric acid solution) =1∶1 mixed solution was used as the developing solvent, could improve the tailing problem of the main peak of technetium[99mTc] methylenediphosphonate injection. The resolution of radioactive main peak and potential impurities including pertechnetate[99mTc] and colloidal technetium[99mTc] was greater than 1.0. The method had a good linear relationship in the radioactivity range of 2.7×10-2 μCi to 42.4 μCi, and the correlation coefficient r was 0.997, with good specificity, good durability and intermediate precision. Compared with the analytical method of the pharmacopoeias, the relative error of radiochemical purity met the requirement of less than 2.0%. The established thin-layer chromatography is suitable for determination of the radiochemical purity of technetium[99mTc] methylenediphosphonate injection.

BACKGROUND In recent years, with the improvement of people's quality of life, people pay more and more attention to health, and thus endemic fluorosis attracts more and more attention. While paying attention to the analysis of the fluorine pollution source and research on exposure pathways, it is also necessary to carry out health risk evaluations of fluorine exposure pathways. According to the survey, the fluorine content in the surface soil of Pengbao Town, Yuanzhou District, and Guyuan City is higher than the local background value. OBJECTIVES To investigate the effect of fluorine on human health. METHODS The health risk assessment model recommended by the US Environmental Protection Agency was used to assess the human health risk. According to the actual situation of endemic diseases caused by excessive fluorine, the samples of surface soil, stratum rocks, crops and groundwater in Pengbao Town, Yuanzhou District, and Guyuan City were collected. The related elements were analyzed by inductively coupled plasma-optical emission spectrometry, atomic fluorescence spectrometry and other analytical methods to study the influence of excessive fluorine on human health in Pengbao Town of Yuanzhou District, and Guyuan City. RESULTS The evaluation results showed that the health risk index (HQ) of fluorine exposure pathways in cereals and vegetables was less than 1, and there was no non-carcinogenic risk. The main way of exposure risk of local fluorine was drinking groundwater, and the related health risk index (HQ) was more than 1, which indicated that drinking groundwater with excessive fluorine may have potential non-carcinogenic risk. The annual total health risk was 1.69×10-8, which was lower than the maximum acceptable annual health risk level of 5.0×10-5 recommended by the International Commission for Radiological Protection (ICRP). CONCLUSIONS Based on the results of the fluorine health risk assessment, it is proposed that the safety of drinking water in this area needs more attention.

We investigate several important properties of an Adaptive Energy Detector (AED), which is originally proposed according to the Generalized Likelihood Ratio Test (GLRT), under the assumption that the signal steering vector is completely unknown. We show that the AED coincides with the Rao and Wald tests. We also give the exact statistical distribution, according to which one can easily derive the Probabilities of Detection (PD) and False Alarm (PFA), and we use the AED to design a parametrically tunable signal-mismatch detector. Compared to existing tunable detectors, the novel tunable detector is more flexible in governing the rejection of the mismatched signal; moreover, for the matched signal, the tunable detector can provide a higher PD than existing detectors. Two scalars, called the tunable parameters, control this functionality.

Compared with Space-Time Adaptive Processing (STAP), Space-Time Adaptive Detection (STAD) employs the data in the cell under test and those in the training to form reasonable detection statistics and consequently decides whether the target exists or not. The STAD has concise processing procedure and flexible design. Furthermore, the detection statistics usually possess the Constant False Alarm Rate (CFAR) property, and hence it needs no additional CFAR processing. More importantly, the STAD usually exhibits improved detection performance than that of the conventional processing, which first suppresses the clutter then adopts other detection strategy. In this paper, we first summarize the key strongpoint of the STAD, then make a classification for the STAD, and finally give some future research tracks.

Sparse recovery Space-Time Adaptive Processing (STAP) methods for obtaining the clutter spectrum require few training samples and can effectively suppress clutter in nonhomogeneous clutter environments. However, presently available sparse recovery STAP methods only use single training samples to recover the clutter spectrum, neglecting information from multiple samples. Moreover, the recovery performance of the abovementioned methods is sensitive to noise. In this study, a subspace-based jointly sparse recovery method is proposed. The information from multiple training samples is fully used and robust clutter suppression performance in noisy environments is achieved. Simulation results show the effectiveness of the proposed method.

For adaptive multichannel radar detection in the framework of multiple alternative hypotheses, where either the target or jamming could be present, a kind of two‐stage detector and classifier is proposed. Precisely, in the first stage, a decision is made on whether a target or a jamming exists. In the second stage, the decision is determined whether it is a target or a jamming. The detector is chosen as subspace‐based adaptive matched filter (SAMF) or adaptive energy detector (AED), while the classifier is selected as the subspace‐based adaptive beamformer orthogonal rejection test (SABORT), whitened SABORT (W‐SABORT), or orthogonal subspace‐based generalised likelihood ratio test (OSGLRT). Among these detectors and classifiers, the OSGLRT is proposed specially for classification in the scheme. Numerical experiments indicate that the proposed methods can achieve better detection and classification performance. [ABSTRACT FROM AUTHOR]