scholarly journals Measurement Time Reduction by Means of Mathematical Modeling of Enzyme Mediated RedOx Reaction in Food Samples Biosensors

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2990
Author(s):  
Arantzazu Florez ◽  
Elena Murga ◽  
Itziar Ortiz de Zarate ◽  
Arrate Jaureguibeitia ◽  
Arkaitz Artetxe ◽  
...  
Keyword(s):  
Real Time ◽  
Food Industry ◽  
Enzymatic Reaction ◽  
High Sensitivity ◽  
Least Square Method ◽  
Food Samples ◽  
Least Square ◽  
Measurement Time ◽  
Exponential Decay Model ◽  
Mathematical Approximation

The possibility of measuring in real time the different types of analytes present in food is becoming a requirement in food industry. In this context, biosensors are presented as an alternative to traditional analytical methodologies due to their specificity, high sensitivity and ability to work in real time. It has been observed that the behavior of the analysis curves of the biosensors follow a trend that is reproducible among all the measurements and that is specific to the reaction that occurs in the electrochemical cell and the analyte being analyzed. Kinetic reaction modeling is a widely used method to model processes that occur within the sensors, and this leads to the idea that a mathematical approximation can mimic the electrochemical reaction that takes place while the analysis of the sample is ongoing. For this purpose, a novel mathematical model is proposed to approximate the enzymatic reaction within the biosensor in real time, so the output of the measurement can be estimated in advance. The proposed model is based on adjusting an exponential decay model to the response of the biosensors using a nonlinear least-square method to minimize the error. The obtained results show that our proposed approach is capable of reducing about 40% the required measurement time in the sample analysis phase, while keeping the error rate low enough to meet the accuracy standards of the food industry.

scholarly journals Analysis of BDS/GPS Signals’ Characteristics and Navigation Accuracy for a Geostationary Satellite

2021 ◽  
Vol 13 (10) ◽  
pp. 1967
Author(s):  
Meng Wang ◽  
Tao Shan ◽  
Wanwei Zhang ◽  
Hao Huan
Keyword(s):  
Real Time ◽  
High Sensitivity ◽  
The United States ◽  
Satellite System ◽  
Least Square ◽  
Navigation Satellite ◽  
Position Accuracy ◽  
The Mean ◽  
Single Epoch ◽  
Global Navigation Satellite

The utilization of Global Navigation Satellite System (GNSS) is becoming an attractive navigation approach for geostationary orbit (GEO) satellites. A high-sensitivity receiver compatible with Global Position System (GPS) developed by the United States and BeiDou Navigation Satellite System (BDS) developed by China has been used in a GEO satellite named TJS-5 to demonstrate feasibility of real-time navigation. According to inflight data, the GNSS signal characteristics including availability, position dilution of precision (PDOP), carrier-to-noise ratio (C/N0), observations quantity and accuracy are analyzed. The mean number of GPS and GPS + BDS satellites tracked are 7.4 and 11.7 and the mean PDOP of GPS and GPS + BDS are 10.24 and 3.91, respectively. The use of BDS significantly increases the number of available navigation satellites and improves the PDOP. The number of observations with respect to C/N0 is illustrated in detail. The standard deviation of the pseudorange noises are less than 4 m, and the corresponding carrier phase noises are mostly less than 8 mm. We present the navigation performance using only GPS observations and GPS + BDS observations combination at different weights through comparisons with the precision reference orbits. When GPS combined with BDS observations, the root mean square (RMS) of the single-epoch least square position accuracy can improve from 32.1 m to 16.5 m and the corresponding velocity accuracy can improve from 0.238 m/s to 0.165 m/s. The RMS of real-time orbit determination position accuracy is 5.55 m and the corresponding velocity accuracy is 0.697 mm/s when using GPS and BDS combinations. Especially, the position accuracy in x-axis direction reduced from 7.24 m to 4.09 m when combined GPS with BDS observations.

scholarly journals Detection of E. coli O157:H7 in Food Using Automated Immunomagnetic Separation Combined with Real-Time PCR

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 908
Author(s):  
Ji Young Park ◽  
Min-Cheol Lim ◽  
Kisang Park ◽  
Gyeongsik Ok ◽  
Hyun-Joo Chang ◽  
...  
Keyword(s):  
Real Time ◽  
Real Time Pcr ◽  
Magnetic Beads ◽  
High Sensitivity ◽  
Immunomagnetic Separation ◽  
Sample Volume ◽  
Food Samples ◽  
Automated System ◽  
Bacterial Strains ◽  
Foodborne Bacteria

In this study, we describe the development of an automated immunomagnetic separation device combined with real-time polymerase chain reaction (PCR) for detecting foodborne bacteria. Immunomagnetic separation (IMS) is a well-known method for the separation and concentration of target bacteria from a large volume of food samples. Magnetic beads functionalized with an antibody provide selectivity for target bacteria such as Escherichia coli O157:H7. Moreover, compared to conventional methods, real-time PCR enables high-sensitivity detection of target bacteria. The method proposed in this study involves three steps: (1) pre-enrichment, (2) automated IMS and concentration of target bacteria, and (3) detection of target bacteria by real-time PCR. Using food samples with a working sample volume as large as 250 mL, the whole process only requires 3 h. As a result, target bacteria in the range of 101–102 colony-forming units per mg or g of sample can be detected in food samples, such as milk, ground beef, and cabbage, by using the proposed approach. We anticipate that the automated IMS system combined with real-time PCR will contribute to the development of a fully automated system for detecting foodborne bacteria and serve as a multi-tester for a variety of bacterial strains in the capacity of a sample-to-answer device in the near future.

Real-Time Identification of Ill-Conditioned Structures

1990 ◽  
Vol 112 (3) ◽  
pp. 181-186 ◽  
Author(s):  
Kamal A. F. Moustafa
Keyword(s):  
Real Time ◽  
Perturbation Technique ◽  
Mass Matrix ◽  
Least Square Method ◽  
Least Square ◽  
Singular Perturbation Technique ◽  
Response Measurement ◽  
Domain Identification ◽  
Stiffness Matrices ◽  
Identification Technique

The dynamical characteristics of structures, that could be ill-conditioned, is represented in this paper by a linear multi-degree of freedom canonical model. A time domain identification technique is suggested to estimate the mass, damping and stiffness matrices, in real-time, by using excitation-response measurement records. A singular perturbation technique is used to deal with ill-conditioning of the mass matrix. The least square method is applied to recover the unknown matrices. A numerical example is presented to verify the results. The possibility of applying the proposed technique to offshore towers is indicated.

Study on the Navigation of Patrol Robot of Transformer Substation Based on Color Vision and RFID

2011 ◽  
Vol 268-270 ◽  
pp. 1259-1264 ◽  
Author(s):  
Song Hai Fan ◽  
Dong Xue Xia
Keyword(s):  
Real Time ◽  
Color Vision ◽  
Radio Frequency Identification ◽  
Color Space ◽  
Least Square Method ◽  
Least Square ◽  
Image Process ◽  
Position Information ◽  
Time Performance ◽  
Transformer Substation

The robustness and real-time performance are of the greatest significance for the navigation of the patrol robot in the transformer substation. To meet this demand, a navigation and position approach is presented in this paper based on color vision and RFID(Radio Frequency Identification) technology. In the presented system, the position information is provided by RFID tags and navigation is completed by the extraction of guidelines. Based on the deep analysis of the advantages and shortcoming of different color space, a new approach integrating the good real-time performance of grayscale image process and rich information in color images process is presented to improve the robustness and real-time performance of navigation. Fast Hough transform is selected and combined with least square method to detect the navigation line. Experimental results show that the presented method can meet the real-time and robust demand of the navigation of patrol robot.

scholarly journals Detection of Sesame Allergen Traces with Two PCR Assays - The Challenge to Protect Food-Allergic Consumers

2015 ◽  
Vol 3 (4) ◽  
pp. 210
Author(s):  
Dimitra Panagiotis Houhoula ◽  
Vasilios Belsis ◽  
Leonidas Georgopoulos ◽  
Virginia Giannou ◽  
Vasiliki R. Kyrana ◽  
...  
Keyword(s):  
Food Allergy ◽  
Real Time ◽  
Real Time Pcr ◽  
Food Industry ◽  
Food Samples ◽  
Rt Pcr ◽  
Highly Sensitive ◽  
Pcr Method ◽  
Pcr Assays ◽  
Positive Results

The purpose of this study was to investigate the possible presence of sesame in commercial foods normally carrying no warning for the allergen, but which may have been subjected to contamination during processing. One hundred units of widely consumed goods with high potential to contain allergenic substances deriving from nuts were analyzed, using sensitive and capable PCR (C-PCR) and Real Time PCR (RT-PCR) methodologies. Of the products examined, 15 (15.0%) declared the presence of sesame, 36 (36.0%) carried no food allergy label, 44 (44.0%) were marked by the phrase “may contain traces of nuts” and 5 (5.0%) carried the indication “may contain sesame traces”. The sesame-positive products detected using the C-PCR method were 15 (100%), 12 (33.3%), 14 (31.8%) and 3 (60%), respectively. Using the RT-PCR technique, positive results were obtained for 15 (100%), 18 (50.0%), 18 (20.5%) and 5 (100%) samples, respectively. The results indicate that the PCR methods applied are highly sensitive and selective, which makes them suitable for the detection of sesame traces in food samples. In addition, they can be useful for monitoring the effectiveness of cleaning processes in the production units of the food industry.

Real-Time Monitoring for Vehicle Brake Temperature Rise in Continuous Long Downhill

2013 ◽  
Vol 300-301 ◽  
pp. 916-919
Author(s):  
Wen Liang Li ◽  
Wei Zhou ◽  
Li Gao ◽  
Ying Chen
Keyword(s):  
Real Time ◽  
Test Data ◽  
Temperature Rise ◽  
Least Square Method ◽  
Energy Balance Equation ◽  
Calculation Model ◽  
Least Square ◽  
Real Time Monitoring ◽  
Dissipation Energy ◽  
Monitoring Method

A real-time monitoring method for brake temperature rise in continuous long downhill with constant velocity braking is proposed. Longitudinal equilibrium equation and energy balance equation are built, and the proportion of brake dissipation energy in total is analyzed. The influence of velocity on brake dissipation energy is studied, then, the calculation model for brake temperature rise is built with the empirical formula of the proportion of bake absorption energy in dissipation energy. Finally, the undetermined coefficient of the calculation model for brake temperature rise is determined with least square method based on test data. The studies show that temperature rise calculated by the built model is similar to the test data both in magnitude and variation trend.

An Algorithm Based on SURF for Surveillance Video Mosaicing

2011 ◽  
Vol 267 ◽  
pp. 746-751 ◽  
Author(s):  
Ke You Guo ◽  
Song Ye ◽  
Hu Ming Jiang ◽  
Chun Yu Zhang ◽  
Kai Han
Keyword(s):  
Real Time ◽  
Least Square Method ◽  
Least Square ◽  
Surveillance Video ◽  
Sift Algorithm ◽  
Related Function ◽  
Accuracy Requirement ◽  
Video Mosaicing ◽  
Wide Range ◽  
The Ideal

Using the SIFT algorithm for image mosaicing is the study hotspot in recent years, which is in a wide range of applications. SIFT algorithm of large amount of data and the time-consuming calculation method is not applicable in higher real-time video mosaicing. Firstly using SURF extracts feature points, secondly using the nearest matching method, RANSAC and least-square method solve the homography matrix between images, and finally using normalized covariance related function for obtaining the best effect of the homography matrix. The algorithm not only meets the accuracy requirement of parameter estimation, but also has smaller computation and faster speed than SIFT. It has proved that the algorithm used in this paper has good real-time performance, high accuracy and the ideal effect, which can satisfy the requirement of real-time mosaicking.

A Design of Algorithm for Excimer Laser Coaxial Observation Automatic Tracking Processing System

2013 ◽  
Vol 706-708 ◽  
pp. 589-592 ◽  
Author(s):  
Zheng Yang Xie ◽  
Tao Chen ◽  
Ning Liu ◽  
Shi Bing Liu ◽  
Ji Ming Chen
Keyword(s):  
Real Time ◽  
Excimer Laser ◽  
Processing System ◽  
Least Square Method ◽  
Stability Control ◽  
Least Square ◽  
Line Center ◽  
Straight Line ◽  
Real Time Tracking ◽  
Processing Platform

This paper proposed a design of algorithm of an excimer laser coaxial observation processing system which can automatically track preset line. With using of the Visual C + + image processing technology and the least square method, the XY axis in both directions of processing platform can obtain accurate processing displacement, and stability control platform for real-time tracking a straight line center. Processing system can acquire the coordinate of processing place where can get the distance from the centre of image in order to achieve real-time tracking.

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