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.     

Skeletal Muscle Health and Cognitive Function: A Narrative Review

Sarcopenia is the loss of skeletal muscle mass and function with advancing age. It involves both complex genetic and modifiable risk factors, such as lack of exercise, malnutrition and reduced neurological drive. Cognitive decline refers to diminished or impaired mental and/or intellectual functioning. Contracting skeletal muscle is a major source of neurotrophic factors, including brain-derived neurotrophic factor, which regulate synapses in the brain. Furthermore, skeletal muscle activity has important immune and redox effects that modify brain function and reduce muscle catabolism. The identification of common risk factors and underlying mechanisms for sarcopenia and cognition may allow the development of targeted interventions that slow or reverse sarcopenia and also certain forms of cognitive decline. However, the links between cognition and skeletal muscle have not been elucidated fully. This review provides a critical appraisal of the literature on the relationship between skeletal muscle health and cognition. The literature suggests that sarcopenia and cognitive decline share pathophysiological pathways. Ageing plays a role in both skeletal muscle deterioration and cognitive decline. Furthermore, lifestyle risk factors, such as physical inactivity, poor diet and smoking, are common to both disorders, so their potential role in the muscle–brain relationship warrants investigation.     

Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data

This research is concerned with the problem of 4 degrees of freedom (DOF) ship manoeuvring identification modelling with the full-scale trial data. To avoid the multi-innovation matrix inversion in the conventional multi-innovation least squares (MILS) algorithm, a new transformed multi-innovation least squares (TMILS) algorithm is first developed by virtue of the coupling identification concept. And much effort is made to guarantee the uniformly ultimate convergence. Furthermore, the auto-constructed TMILS scheme is derived for the ship manoeuvring motion identification by combination with a statistic index. Comparing with the existing results, the proposed scheme has the significant computational advantage and is able to estimate the model structure. The illustrative examples demonstrate the effectiveness of the proposed algorithm, especially including the identification application with full-scale trial data.     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.     

Identification of Host Cellular Protein Substrates of SARS-COV-2 Main Protease

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19) being associated with severe pneumonia. Like with other viruses, the interaction of SARS-CoV-2 with host cell proteins is necessary for successful replication, and cleavage of cellular targets by the viral protease also may contribute to the pathogenesis, but knowledge about the human proteins that are processed by the main protease (3CLpro) of SARS-CoV-2 is still limited. We tested the prediction potentials of two different in silico methods for the identification of SARS-CoV-2 3CLpro cleavage sites in human proteins. Short stretches of homologous host-pathogen protein sequences (SSHHPS) that are present in SARS-CoV-2 polyprotein and human proteins were identified using BLAST analysis, and the NetCorona 1.0 webserver was used to successfully predict cleavage sites, although this method was primarily developed for SARS-CoV. Human C-terminal-binding protein 1 (CTBP1) was found to be cleaved in vitro by SARS-CoV-2 3CLpro, the existence of the cleavage site was proved experimentally by using a His₆-MBP-mEYFP recombinant substrate containing the predicted target sequence. Our results highlight both potentials and limitations of the tested algorithms. The identification of candidate host substrates of 3CLpro may help better develop an understanding of the molecular mechanisms behind the replication and pathogenesis of SARS-CoV-2.     

Research on the identification performance of UHF RFID system considering the correlation of cascaded channel

The identification rate of UHF RFID system was restricted by multipath propagation effects.The system identification performance was studied considering the correlation coefficient between forward and reverse channels.Based on the generalized Rician fading channel model,the analytical expression of identification rate was derived under independent,full correlation and correlation cases.Compared with the existing analysis,the proposed uniform calculation formula of identification rate was for any correlation coefficient and kinds of channel conditions.The numerical computation and Monte-carlo simulations show that the influences of different correlation coefficients,channel conditions,sensitivity and distance on the identification rate.     

Application of the novel Droplet digital PCR technology for identification of meat species

The authenticity and traceability of meat products are issues of primary importance to ensure food safety. Unfortunately, food adulteration (e.g. the addition of inexpensive cuts to minced meat products) and mislabelling (e.g. the inclusion of meat from species other than those declared) happens frequently worldwide. The aim of this study was to apply a droplet digital PCR assay for the detection and quantification (copies μL⁻¹) of the beef, pork, horse, sheep, chicken and turkey in meat products. The analysis conducted on commercial meat showed the presence of traces of DNA from other animal species than those declared. We show that the method is highly sensitive, specific and accurate (accuracy = 100%). This method could be adopted by competent food safety authorities to verify compliance with the labelling of meat products and to ensure quality and safety throughout the meat supply chain, from primary production to consumption.     

腹腔手术后重症患者心肌损伤的危险因素

目的探讨腹腔手术后重症患者心肌损伤的发生情况及可能的危险因素。方法回顾性分析北京大学人民医院2017年1月至2019年1月腹腔手术后重症患者的一般临床资料及心肌损伤情况,收集并观察基础病史、术中(手术时间、是否急诊手术、术中出血>800 ml和术中低血压等)及术后指标(改良氧合指数、血乳酸、急性肾损伤和术后24 h内使用升压药情况等)。根据术后是否发生心肌损伤,将患者分为心肌损伤组和非心肌损伤组,采用Logistic回归分析腹腔手术后重症患者心肌损伤的危险因素。结果在纳入的803例腹腔手术后重症患者中,心肌损伤发生率为17. 2%(138/803),而急性心肌梗死发生率仅为0. 9%(7/803)。单因素分析显示,慢性肾功能不全病史、手术时间、急诊手术、术中低血压、术后24 h内使用升压药、高APACHEⅡ评分及术后即刻急性肾损伤与术后重症患者心肌损伤相关(P<0. 05)。多因素回归分析显示,急诊手术(OR=3. 14,95%CI:1. 76～5. 60,P<0. 001)、术后24 h内使用升压药(OR=2. 26,95%CI:1. 23～4. 15,P=0. 008)、APACHEⅡ评分(OR=1. 05,95%CI:1. 01～1. 09,P=0. 008)和术后急性肾损伤(OR=3. 18,95%CI:1. 78～5. 69,P <0. 001)与腹腔手术后重症患者发生心肌损伤独立相关。结论重症患者腹腔手术后心肌损伤发生率高,急诊手术、术后24 h内使用升压药、高APACHEⅡ评分和术后急性肾损伤是导致腹腔手术后重症患者发生心肌损伤的独立危险因素。     

Survey of domestic food purchases and related home handling practices in the Abruzzo region (central Italy): Data collection and analysis through a language-independent classification system

A telephone survey was carried out on 13,486 randomly selected households located in the Abruzzo region (central Italy). Three questionnaires were specifically designed in relation to three different groups of foods (Meat and meat products, Fishery products, Fruit and vegetables). Questions were mainly focused on the amount and number of purchases, type of retailer, and home food handling practices with respect to the week prior to the interview. Data were classified according to a multilingual thesaurus system (LanguaL). Results allowed to estimate domestic purchases (in kg) per capita for different food categories. The category “Red meat/Cattle” accounted for a large part of purchases in the “meat and meat products” group (10.9 kg per capita/year; 32.2% of purchases in the group) while the category “Fish or related organism/Fish” was the most purchased in the “fishery products” group (6.9 kg per capita/year; 63.3%). The aggregation of more detailed characteristics enabled the identification of popular categories of foods, such as “Red meat/Cattle/Divided into pieces” (25% of the “meat and meat products” group). Significant differences (p < 0.05) were found between the four different provinces (L'Aquila, Chieti, Pescara and Teramo) with respect to “Poultry/Chicken” and “Red meat/Cattle” categories. Householders were also asked about post-purchase food handling practices that might be hazardous to food safety. More than 20% of those surveyed stated that they thawed frozen meat at room temperature. The degree of doneness after cooking of different food categories was generally high: over 90% of products purchased in the majority of meat and fish categories were properly cooked. However a noticeable proportion of householders (about 15%) reported medium or rare cooking of “Red meat/Cattle” and “Red meat/Swine”. Differences (p < 0.05) were also found between consumers of different ages, with people over 65 years old being more prone to freeze meat and cook it thoroughly.The survey was carried out in a specific geographic area and on a statistically significant sample of households, thus allowing a collection of data on domestic habits relating to food purchases and home food handling practices. This information should be included in the framework of quantitative microbial risk assessment (QMRA) models as a measure of the actual exposure of consumers to pathogenic microorganism. The LanguaL system also proved to be a practical language-independent method useful not only to identify and describe food items but also to classify them according to specific food safety characteristics.     

Word length and lexical activation: Longer is better.

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a system, long words should produce stronger lexical activation than short words, for 2 reasons: Long words provide more bottom-up evidence than short words, and short words are subject to greater inhibition due to the existence of more similar words. Four experiments provide evidence for this view. In addition, reaction-time-based partitioning of the data shows that long words generate greater activation that is available both earlier and for a longer time than is the case for short words. As a result, lexical influences on phoneme identification are extremely robust for long words but are quite fragile and condition-dependent for short words. Models of word recognition must consider words of all lengths to capture the true dynamics of lexical activation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)