Improvement and Application of qPCR (Real-Time Quantitative Polymerase Chain Reaction) Data Processing Method for Home-Made Integrated Nucleic Acid Detection System

2020 ◽  
Vol 20 (12) ◽  
pp. 7369-7375
Author(s):  
Yile Fang ◽  
Pei Liao ◽  
Zhu Chen ◽  
Hui Chen ◽  
Yanqi Wu ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Data Processing ◽  
Real Time ◽  
Detection System ◽  
Disease Diagnosis ◽  
Processing Algorithm ◽  
Clinical Samples ◽  
Nucleic Acid Detection ◽  
Qpcr Data ◽  
Data Processing Algorithm

Because it has many advantages such as rapidity and accuracy, nucleic acid detection is applied to infectious disease diagnosis more and more. An automatic integrated nucleic acid detection system based on real-time PCR is developed by our research group to conduct point-of-care testing of infectious pathogens. The home-made detection system collects fluorescence data in each PCR cycle through an integrated dual-channel fluorescence detection module and then real-time fluorescence curves are drawn by the software, which can tell the results of the diagnostics after some processing and analysis. However, owing to the disturbance of the environment or the imperfect of nucleic acid extraction before PCR, the fluorescence curves sometimes may contain several abnormal points. For the purpose of enhancing its ability to deal with these iffy curves and improve the accuracy of the testing results, in this study, the SDM-based qPCR data processing algorithm was studied and 11 groups of qPCR data that have different flaws from the clinical samples detected by this system were chosen to prove the practicability of the method. In comparison with the conventional threshold-based method, the Cq values calculated by the SDM-based method were more close to the actual values, meaning it can overcome the shortcomings of the conventional methods such as being unable to accommodate noise and being unable to avoiding abnormal data. With the improvement of this data processing algorithm, the stability of our system and the reliability and accuracy of the results are greatly improved.

scholarly journals Rain Monitoring with Polarimetric GNSS Signals: Ground-Based Experimental Research

2019 ◽  
Vol 11 (19) ◽  
pp. 2293
Author(s):  
Hao An ◽  
Wei Yan ◽  
Shuangshuang Bian ◽  
Shuo Ma
Keyword(s):  
Phase Shift ◽  
Data Processing ◽  
Detection System ◽  
Experimental System ◽  
Weather Radar ◽  
Heavy Rain ◽  
Theoretical Research ◽  
Processing Algorithm ◽  
Data Processing Algorithm ◽  
Gps Satellites

In recent years, there has been a preliminary research on monitoring rainfall information based on polarimetric Global Navigation Satellite System (GNSS) signals, which is a quite novel concept. After previous theoretical research on monitoring rain based on polarimetric phase shift of GNSS signals, the paper aims to detect rain using polarimetric GNSS signals from a ground-based experiment. Firstly, a conical horn antenna specially designed for receiving dual-polarized (H, horizontal, and V, vertical) GNSS signals was developed, and an experimental system for polarimetric GNSS rain detection was built. Then, taking Global Positioning System (GPS) satellites as signal source, a ground-based experiment was carried out at a mountain in Nanjing, where heavy rain tends to occur frequently in rainy season. Additionally, a data processing algorithm mainly following Padullés et al. (2016) to solve the problems of quality control, unlocking, hardware effect, phase ambiguity, multipath effect was applied independently to this ground-based data from the polarimetric GNSS rain detection system. Also, the multi-source data from nearby weather radar and weather stations was used for verification. Results from 14 GPS satellites show that the obtained phase shift is zero in all no-rain days while it is not zero during rainy days, which is in accordance with the actual situation. Compared with weather radar and rain gauges’ data, the results verify that the phase shift is caused by rain. Besides, when individual cases are examined, many show that their tendencies of accumulated phase shift are quite similar to that of a weather station’s rainfall data, even some correlation coefficients are up to 0.99. These demonstrate the reliability of our experimental system and the feasibility of the data processing algorithm. This study will provide technical support for future spaceborne experiment, which has promising applications in global rain monitoring.

scholarly journals A First-Order Differential Data Processing Method for Accuracy Improvement of Complementary Filtering in Micro-UAV Attitude Estimation

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1340 ◽  
Author(s):  
Xudong Wen ◽  
Chunwu Liu ◽  
Zhiping Huang ◽  
Shaojing Su ◽  
Xiaojun Guo ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Low Cost ◽  
Attitude Estimation ◽  
Sensor Data ◽  
Processing Algorithm ◽  
Estimation Accuracy ◽  
First Order ◽  
Data Processing Algorithm ◽  
Adjustment Strategy

There are many algorithms that can be used to fuse sensor data. The complementary filtering algorithm has low computational complexity and good real-time performance characteristics. It is very suitable for attitude estimation of small unmanned aerial vehicles (micro-UAVs) equipped with low-cost inertial measurement units (IMUs). However, its low attitude estimation accuracy severely limits its applications. Though, many methods have been proposed by researchers to improve attitude estimation accuracy of complementary filtering algorithms, there are few studies that aim to improve it from the data processing aspect. In this paper, a real-time first-order differential data processing algorithm is proposed for gyroscope data, and an adaptive adjustment strategy is designed for the parameters in the algorithm. Besides, the differential-nonlinear complementary filtering (D-NCF) algorithm is proposed by combine the first-order differential data processing algorithm with the basic nonlinear complementary filtering (NCF) algorithm. The experimental results show that the first-order differential data processing algorithm can effectively correct the gyroscope data, and the Root Mean Square Error (RMSE) of attitude estimation of the D-NCF algorithm is smaller than when the NCF algorithm is used. The RMSE of the roll angle decreases from 1.1653 to 0.5093, that of the pitch angle decreases from 2.9638 to 1.5542, and that of the yaw angle decreases from 0.9398 to 0.6827. In general, the attitude estimation accuracy of D-NCF algorithm is higher than that of the NCF algorithm.

Identifying the etiologic role of Parvovirus B19 in non-immune hydrops fetalis by histopathology, immunohistochemistry and nucleic acid testing: a retrospective study

Open Medicine ◽  
2007 ◽  
Vol 2 (3) ◽  
pp. 271-279 ◽  
Author(s):  
Koray Ergunay ◽  
Gulcin Altinok ◽  
Bora Gurel ◽  
Ahmet Pinar ◽  
Arzu Sungur ◽  
...  
Keyword(s):  
Nucleic Acid ◽  
Real Time ◽  
San Francisco ◽  
Real Time Pcr ◽  
Nested Pcr ◽  
Parvovirus B19 ◽  
Etiologic Agent ◽  
Hydrops Fetalis ◽  
Nucleic Acid Detection

AbstractIntrauterine Parvovirus B19 infections may cause fetal anemia, non-immune hydrops fetalis or abortion. This study focuses on the pathogenic role of Parvovirus B19 in non-immune hydrops fetalis at Hacettepe University, a major reference hospital in Turkey. Twenty-two cases of non-immune hydrops fetalis were retrospectively selected out of a total of 431 hydrops fetalis specimens from the Department of Pathology archieves. Paraffine embedded tissue sections from placental and liver tissues from each case were evaluated by histopathology, immunohistochemistry, nested PCR and commercial quantitative Real-time PCR. Viral DNA was detected in placental tissues by Real-time PCR in 2 cases (2/22, 9.1%) where histopathology also revealed changes suggestive of Parvovirus B19 infection. No significant histopathologic changes were observed for the remaining sections. Nested PCR that targets the VP1 region of the viral genome and immunohistochemistry for viral capsid antigens were negative for all cases. As a result, Parvovirus B19 is identified as the etiologic agent for the development of non-immune hydrops fetalis for 9.1% of the cases in Hacettepe University, Turkey. Real-time PCR is observed to be an effective diagnostic tool for nucleic acid detection from paraffine embedded tissues. Part of this study was presented as a poster at XIIIth International Congress of Virology, San Francisco, USA (Abstract V-572).

The PPP data processing algorithm to create geodetic networks

2021 ◽  
pp. 464-468
Author(s):  
A.D. Tikhonov ◽  
A.A. Kochiev
Keyword(s):  
Data Processing ◽  
Processing Algorithm ◽  
Navigation Systems ◽  
Geodetic Networks ◽  
Data Processing Algorithm ◽  
Global Navigation ◽  
Global Navigation Systems

The article deals with determination of coordinates using global navigation systems, and application of the PPP data processing algorithm to obtain coordinates. The authors conducted an experiment illustrating the algorithm accuracy.

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