Real-Time Duplex Applications of Loop-Mediated AMPlification (LAMP) by Assimilating Probes

Isothermal nucleic-acid amplification methods such as Loop-Mediated isothermal AMPlification (LAMP) are increasingly appealing alternatives to PCR for use in portable diagnostic system due to the low cost, weight, and power requirements of the instrumentation. As such, interest in developing new probes and other functionality based on the LAMP reaction has been intense. Here, we report on the development of duplexed LAMP assays for pathogen detection using spectrally unique Assimilating Probes. As proof of principle, we used a reaction for Salmonella enterica as a model coupled with a reaction for λ-phage DNA as an internal control, as well as a duplexed assay to sub-type specific quarantine strains of the bacterial wilt pathogen Ralstonia solanacearum. Detection limits for bacterial DNA analyzed in individual reactions was less than 100 genomic equivalents in all cases, and increased by one to two orders of magnitude when reactions were coupled in duplexed formats. Even so, due to the more robust activity of newly available strand-displacing polymerases, the duplexed assays reported here were more powerful than analogous individual reactions reported only a few years ago, and represent a significant advance for incorporation of internal controls to validate assay results in the field.     

Visual Detection of Adenosine Triphosphate by Taylor Rising: A Simple Point-of-Care Testing Method Based on Rolling Circle Amplification

Rapid and sensitive point-of-care testing (POCT) is an extremely critical mission in practical applications, especially for rigorous military medicine, home health care, and in the third world. Here, we report a visual POCT method for adenosine triphosphate (ATP) detection based on Taylor rising in the corner of quadratic geometries between two rod surfaces. We discuss the principle of Taylor rising, demonstrating that it is significantly influenced by contact angle, surface tension, and density of the sample, which are controlled by ATP-dependent rolling circle amplification (RCA). In the presence of ATP, RCA reaction effectively suppresses Taylor-rising behavior, due to the increased contact angle, density, and decreased surface tension. Without addition of ATP, untriggered RCA reaction is favorable for Taylor rising, resulting in a significant height. With this proposed method, visual sensitive detection of ATP without the aid of other instruments is realized with only a 5 μL droplet, which has good selectivity and a low detection limit (17 nM). Importantly, this visual method provides a promising POCT tool for user-friendly molecular diagnostics.     

ECG heart beat classification method based on modified ABC algorithm

Electrocardiogram is the most commonly used tool for the diagnosis of cardiologic diseases. In order to help cardiologists to diagnose the arrhythmias automatically, new methods for automated, computer aided ECG analysis are being developed. In this paper, a Modified Artificial Bee Colony (MABC) algorithm for ECG heart beat classification is introduced. It is applied to ECG data set which is obtained from MITBIH database and the result of MABC is compared with seventeen other classifier's accuracy.In classification problem, some features have higher distinctiveness than others. In this study, in order to find higher distinctive features, a detailed analysis has been done on time domain features. By using the right features in MABC algorithm, high classification success rate (99.30%) is obtained. Other methods generally have high classification accuracy on examined data set, but they have relatively low or even poor sensitivities for some beat types. Different data sets, unbalanced sample numbers in different classes have effect on classification result. When a balanced data set is used, MABC provided the best result as 97.96% among all classifiers.Not only part of the records from examined MITBIH database, but also all data from selected records are used to be able to use developed algorithm on a real time system in the future by using additional software modules and making adaptation on a specific hardware.     

Effect of stoichiometry and Cu-substitution on the phase structure and hydrogen storage properties of Ml-Mg-Ni-based alloys

To improve the electrochemical properties of rare-earth–Mg–Ni-based hydrogen storage alloys, the effects of stoichiometry and Cu-substitution on the phase structure and thermodynamic properties of the ...     

一款紧凑增强型可变阻抗电磁带隙结构

基于传统AI-EBG结构,提出了一种小尺寸的增强型电磁带隙结构,实现了从0.5~9.4 GHz的宽频带-40 dB噪声抑制深度,且下截止频率减少到数百MHz,可有效抑制多层PCB板间地弹噪声。文中同时研究了EBG结构在高速电路应用时的信号完整性问题,使用差分信号方案可改善信号完整性。     

The implementation of a smartphone-based fall detection system using a high-level fuzzy Petri net

The falling down problem has become one of the very important issues of global public health in an aging society. The specific equipment was adopted as the detection device of falling-down in the early studies, but it is inconvenient for the elderly and difficult for future application. The smart phone more commonly used than the specific fall detection equipment is selected as a mobile device for human fall detection, and a fall detection algorithm is developed for this purpose. What the user has to do is to put the smart phone in his/her thigh pocket for falling down detection. The signals detected by the tri-axial G-sensor are converted into signal vector magnitudes as the basis of detecting a human body in a stalling condition. The Z-axis data sets are captured for identification of human body inclination and the occurrence frequencies at the peak of the area of use are used as the input parameters. A high-level fuzzy Petri net is used for the analysis and the development of identifying human actions, including normal action, exercising, and falling down. The results of this study can be used in the relevant equipments or in the field of home nursing.     

Study on metamerism degree evaluation based on wavelength sensitive cone weighting algorithm

Metamerism phenomenon can be used in illuminant detection to ensure the accuracy of light source. A method based on Long‐, Middle‐, Short‐ wavelength cones(LMS) weighting algorithm to evaluate metamerism degree is proposed. The chromatic relationship between the degree of metamerism mismatch and the light source is studied. Herein, the consistency between the metameric indices (MIs) and CIE1976 L*a*b* color difference ranking is analyzed by SRCC, KRCC, PLCC and RMSE. A statistically sampling method to obtain practical LMS cone fundamentals to evaluate metamerism degree is employed. The analysis results obtained show that the method based on LMS weighting algorithm has good evaluation ability and stability in simulation experiments and statistically sampling experiments, which are in line with visual characteristics of human. Proposed method meets the requirements of selecting metameric pairs used in light source detection. The analysis results have certain guiding significance.     

Structural dependence of microwave dielectric properties of spinel structured Mg2(Ti1-xSnx)O4 solid solutions: Crystal structure refinement,Raman spectra study and complex chemical bond theory

Mg₂(Ti_1-xSn_x)O₄ (x?=?0–1) ceramics were prepared through conventional solid-state method. This paper focused on the dependence of microwave dielectric properties on crystal structural characteristics via crystal structure refinement, Raman spectra study and complex chemical bond theory. XRD spectrums delineated the phase information of a spinel structure, and structural characteristic of these compositions were achieved with the help of Rietveld refinements. Raman spectrums were used to depict the correlations between vibrational phonon modes and dielectric properties. The variation of permittivity is ascribed to the Mg₂(Ti_1-xSn_x)O₄ average bond covalency. The relationship among the B-site octahedral bond energy, tetrahedral bond energy and temperature coefficient are discussed by defining on the change rate of bond energy and the contribution rate of octahedral bond energy. The quality factor is affected by systematic total lattice energy, and the research of XPS patterns illustrated that oxygen vacancies can be effectively restrained in rich oxygen sintering process. Obviously, the microwave dielectric properties of Mg₂(Ti_1-xSn_x)O₄ compounds were obtained (${\epsilon }_r$= 12.18, $Q\times f$?=?170,130?GHz, ${\tau }_f$?=??53.1?ppm/°C, x?=?0.2).     

Classification and regression models of audio and vibration signals for machine state monitoring in precision machining systems

We present a data-driven method for monitoring machine status in manufacturing processes. Audio and vibration data from precision machining are used for inference in two operating scenarios: (a) variable machine health states (anomaly detection); and (b) settings of machine operation (state estimation). Audio and vibration signals are first processed through Fast Fourier Transform and Principal Component Analysis to extract transformed and informative features. These features are then used in the training of classification and regression models for machine state monitoring. Specifically, three classifiers (K-nearest neighbors, convolutional neural networks and support vector machines) and two regressors (support vector regression and neural network regression) were explored, in terms of their accuracy in machine state prediction. It is shown that the audio and vibration signals are sufficiently rich in information about the machine that 100% state classification accuracy could be accomplished. Data fusion was also explored, showing overall superior accuracy of data-driven regression models.