Characteristics of Atrial Premature Beat ECG Signals on Variant Maps

Premature heartbeat is also known as extrasystole. It means the foundation of sinus or ectopic heart rhythm, a certain pacemaker in the heart excitable earlier than the basic rhythm, cause the heart to be local or all happening prematurely remove pole. Premature atrial beats may lead to cardiomyopathy. The experimental data in this chapter are provided by Xishan People’s Hospital of Wuxi city, including normal ECG signals and abnormal ECG signals (atrial premature beat). The two types of ECG data sequences are processed experimentally through the variant measurement model, and the differences in the variant maps are compared

Management of Primary Hepatic Carcinoma by Traditional Chinese Medicine

Primary hepatic carcinoma is one of the types with high incidence of cancer. It has the characteristics of hidden disease, long incubation period, rapid development and easy metastasis, and the prognosis is poor, which seriously affects the quality of life of patients. Although much progress has been made in its research, the complex mechanisms of its onset and deterioration are not fully understood. This article summarizes the diagnosis and treatment of primary liver cancer in modern medicine and traditional Chinese medicine and provides the future prospects for the treatment of primary liver cancer from the perspective of overall and personalized Chinese medicine

Tacholess order tracking method for gearbox based on time-varying filter and energy centrobaric correction method

Under the premise that the instantaneous speed can be accurately measured or precise estimated, order tracking is considered to be a classical and effective technique for non-stationary vibration analysis of rotating machinery. The meshing frequency components of the vibration signal measured from complex gearbox system interfere with each other mutually. The energy centrobaric correction method exhibits exact instantaneous frequency estimation (IFE) ability under the interference, but is susceptible to strong noise. Combining with time-varying filter and energy centrobaric correction method, a tacholess order tracking technique for gear fault diagnosis under the rotating frequency multi-linear fluctuation is proposed. The time-varying filter is designed to filter the strong noise signal, and then IFE could be accurately calculated from the filtered signal by energy centrobaric correction method. The instantaneous phase of reference shaft based on the Vold-Kalman filter (VKF) is used for angular resampling of the original vibration signal. The results show that the shaft rotating speed could be accurately identified from extracted gear meshing components. The order spectrum obtained by the proposed method with tacholess is substantially the same as the order spectrum obtained by a tachometer. Simulation analysis and experimental results verify the advantages of proposed tacholess order tracking technology for monitoring and fault diagnosis of gearbox vibration under the condition of strong noise and large speed variation

DATDroid: Dynamic Analysis Technique in Android Malware Detection

Android system has become a target for malware developers due to its huge market globally in recent years. The emergence of 5G in the market and limited protocols post a great challenge to the security in Android. Hence, various techniques have been taken by researchers to ensure high security in Android devices. There are three types of analysis namely static, dynamic and hybrid analysis used to detect and analyze the malicious application in Android. Due to evolving nature of the malware, it is very challenging for the existing techniques to detect and analyze it efficiently and accurately. This paper proposed a Dynamic Analysis Technique in Android Malware detection called DATDroid. The proposed technique consists of three phases, which includes feature extraction, feature selection and classification phases. A total of five features namely system call, errors and time of system call process, CPU usage, memory and network packets are extracted. During the classification 70% of the dataset was allocated for training phase and 30% for testing phase using machine learning algorithm. Our experimental results achieved an overall accuracy of 91.7% with lower false positive rates as compared to benchmarked method. DATDroid also achieved higher precision and recall rate of 93.1% and 90.0%, respectively. Hence our proposed technique has proven to be able to classify malware more accurately and reduce misclassification of malware application as benign significantly

Arsenic bioleaching in medical realgar ore and arsenicbearing refractory gold ore by combination of Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans

Purpose: To develop a novel biotechnological method for removing toxic arsenic from two kinds of representative arsenic-containing ores using different mixed mesophilic acidophiles.Methods: Bioleaching of the two types of arsenic-containing ores by mixed arsenic-unadapted Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans or mixed arsenic-adapted cultures, were carried out. Arsenic bioleaching ratios in the various leachates were determined and compared.Results: The results showed that the maximum arsenic leaching ratio obtained from realgar in the presence of mixed adapted cultures was 28.6 %. However, the maximum arsenic leaching ratio from realgar in the presence of mixed unadapted strains was only 12.4 %. Besides, maximum arsenic leaching ratios from arsenic-bearing refractory gold ore by mixed adapted strains or unadapted strains were 45.0 and 22.9 %, respectively. Oxidation of these two ores by sulfuric acid was insignificant, as maximum arsenic leaching ratios of realgar and arsenic-bearing refractory gold ore in the absence of any bacterium were only 2.8 and 11.2 %, respectively.Conclusion: Arsenic leaching ratio of realgar and refractory gold ore can be enhanced significantly in the presence of arsenic-adapted mesophilic acidophiles.Keywords: Adaptation, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Realgar, Arsenicbearing refractory gold ore, Arsenic leaching rati

IQSeq: Integrated Isoform Quantification Analysis Based on Next-Generation Sequencing

With the recent advances in high-throughput RNA sequencing (RNA-Seq), biologists are able to measure transcription with unprecedented precision. One problem that can now be tackled is that of isoform quantification: here one tries to reconstruct the abundances of isoforms of a gene. We have developed a statistical solution for this problem, based on analyzing a set of RNA-Seq reads, and a practical implementation, available from archive.gersteinlab.org/proj/rnaseq/IQSeq, in a tool we call IQSeq (Isoform Quantification in next-generation Sequencing). Here, we present theoretical results which IQSeq is based on, and then use both simulated and real datasets to illustrate various applications of the tool. In order to measure the accuracy of an isoform-quantification result, one would try to estimate the average variance of the estimated isoform abundances for each gene (based on resampling the RNA-seq reads), and IQSeq has a particularly fast algorithm (based on the Fisher Information Matrix) for calculating this, achieving a speedup of times compared to brute-force resampling. IQSeq also calculates an information theoretic measure of overall transcriptome complexity to describe isoform abundance for a whole experiment. IQSeq has many features that are particularly useful in RNA-Seq experimental design, allowing one to optimally model the integration of different sequencing technologies in a cost-effective way. In particular, the IQSeq formalism integrates the analysis of different sample (i.e. read) sets generated from different technologies within the same statistical framework. It also supports a generalized statistical partial-sample-generation function to model the sequencing process. This allows one to have a modular, “plugin-able” read-generation function to support the particularities of the many evolving sequencing technologies