Portfolio Selection and Risk Control for an Insurer With Uncertain Time Horizon and Partial Information in an Anticipating Environment

Methodology and Computing in Applied Probability - This paper is devoted to the study of an optimal investment and risk control problem for an insurer. The risky asset process and the insurance...     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

基于电化学老化衰退模型的锂离子动力电池外特性

当前锂离子动力电池电化学模型存在模型复杂、建模难度大、计算效率低、老化评估效果差的问题,本文提出一种考虑电池衰退老化的机理模型(ADME).本文首先通过有限差分法对伪二维(P2D)电化学模型进行离散降阶处理,得到简化伪二维(SP2D)模型.在SP2D模型的基础上,基于阴阳两极发生的副反应导致的衰退老化现象,提出一种考虑电池衰退老化的机理模型.其次,使用多变量偏差补偿最小二乘法实现模型参数辨识.最后通过动力电池衰退老化性能循环实验,对比分析了恒流、脉冲工况下SP2D模型和ADME模型的终端电压输出.结果表明:ADME模型较为简单、计算效率和估算精度高,可以有效评估电池容量老化衰退,得到理想的锂离子动力电池外特性曲线.     

An improved LC–MS/MS method for determination of docetaxel and its application to population pharmacokinetic study in Chinese cancer patients

Because of its unpredictable side effects and efficacy, the anticancer drug docetaxel (DTX) requires improved characterisation of its pharmacokinetic profiles through population pharmacokinetic studies. A sensitive and rugged LC–MS/MS method for the detection of DTX in human plasma was developed and optimised using paclitaxel as an internal standard (IS). The plasma samples underwent rapid extraction using hybrid solid-phase extraction-protein precipitation. The analyte and IS were separated with an isocratic system on a Zorbax Eclipse Plus C₁₈ column using water containing 0.05% acetic acid along with 20 μM of sodium acetate and methanol (30/70, v/v) as the mobile phase. Quantification was performed using a triple quadrupole mass spectrometer through multiple reaction monitoring in positive mode, using the m/z 830.3 → 548.8 and m/z 876.3 → 307.7 transitions for DTX and paclitaxel, respectively. The range of the calibration curve was 1–500 ng/mL for DTX, and the linear correlation coefficient was >0.99. The accuracies ranged from −4.6 to 4.2%, and the precision was no higher than 7.0% for the analytes. No significant matrix effect was observed. Both DTX and the IS showed considerable recovery. This method was finally applied to the establishment of a population pharmacokinetic model to optimise the clinical use of DTX.