Consistency Analysis of Detection Results of Two Herpes Simplex Virus (HSV) Type II Nucleic Acid Detection Kits

Objective: The objective of the study is to verify the clinical validity of the following kits with the comparative experimental analysis and evaluate whether their performance can meet the clinical requirements, i.e. Class III in vitro diagnostic reagent “Herpes Simplex Virus (HSV) Type II Nucleic Acid Detection Kit (PCR-Fluorescence Probe Method)” of Daan Gene Co., Ltd. (Daan kit for short) and “Herpes Simplex Virus (HSV) Type II Nucleic Acid Detection Kit (Fluorescence PCR Method)” of Wuhan Biot Gene Co., Ltd. (Biot kit for short). Method: In the study process, the samples were divided into positive and negative groups according to the control test results, and the clinical application performance of Daan kit and Biot kit was evaluated by comparing their test results. Results: The results show that two kits indicate the same test results, i.e. 26 positive and 107 negative samples in a total of 133 male urethral discharge samples, and 32 positive and 238 negative samples in a total of 270 female cervical secretion samples. Conclusion: It can be concluded from the clinical test that Daan and Biot Herpes Simplex Virus (HSV) Type II Nuc- leic Acid Test Kits are reliable, accurate, safe, convenient for use, stable and high-value in the clinical application.

Consistency Analysis of 2021 College Entrance Examination Chemistry Questions and Curriculum Standards Scientific Inquiry

The SRI analysis tool was used to comprehensively analyze the seven sets of chemistry questions in the 2021 college entrance examination paper from multiple dimensions such as exploratory test questions,various inquiry standards and exploratory levels.The study found that all test papers involve the examination of scientific inquiry literacy;from the perspective of examination objectives,the 2021 college entrance examination questions as a whole focus on the examination of a single inquiry objective;the questions of each examination paper mainly examine three standards:design scheme,evidence processing and obtaining.The conclusion is drawn;the exploratory level of the chemistry questions in several sets of test papers is mostly a high level.

Double stabilizations and convergence analysis of a second-order linear numerical scheme for the nonlocal Cahn-Hilliard equation

In this paper,we study a second-order accurate and linear numerical scheme for the nonlocal CahnHilliard equation.The scheme is established by combining a modified Crank-Nicolson approximation and the Adams-Bashforth extrapolation for the temporal discretization,and by applying the Fourier spectral collocation to the spatial discretization.In addition,two stabilization terms in different forms are added for the sake of the numerical stability.We conduct a complete convergence analysis by using the higher-order consistency estimate for the numerical scheme,combined with the rough error estimate and the refined estimate.By regarding the numerical solution as a small perturbation of the exact solution,we are able to justify the discrete?^(∞)bound of the numerical solution,as a result of the rough error estimate.Subsequently,the refined error estimate is derived to obtain the optimal rate of convergence,following the established?∞bound of the numerical solution.Moreover,the energy stability is also rigorously proved with respect to a modified energy.The proposed scheme can be viewed as the generalization of the second-order scheme presented in an earlier work,and the energy stability estimate has greatly improved the corresponding result therein.

Reliability and consistency assessment of land cover products atmacro and local scales in typical cities

Urban areas have higher heterogeneity compared to natural areas,it is crucial to assessfine-resolution land cover products and discover how they differ in urban areas so that they can be efficiently used for various application scenarios.In this study,five typical cities in China were chosen as study areas to evaluate four commonly used 30 m land cover products:GLC_FCS30-2020,FROM-GLC30-2017,Globeland30-2020,and CLCD-2019.We analyzed the reliability of these four products using validation samples as well as by examining their area and spatial pattern consistency.Given the limitations of traditional accuracy assessments at the macro level,we added a local area evaluation to further examine the classification details in these products.The macro results indicated that four land cover products within urban areas have a similar overall accuracy,surpassing 76%,but there was a low consistency among them,ranging from 42.21%to 61.13%.The local accuracy assessment illustrated that GLC_FCS30-2020 and FROM-GLC30-2017 performed well in reflecting the intricate details of the city,however,the four products exhibited varying degrees of misclassifications and omissions.These phenomena suggest that more sophisticated algorithms are needed to consider urban particularities sincefine-resolution land cover products may fail to capture complex urban details.

Compressible Rayleigh-Taylor Instability with Preheat in Inertial Confinement Fusion

The compressible Rayleigh-Taylor instability of accelerated ablation front is analysed in consideration of the preheat effects, and the corresponding eigen-problem is solved numerically using the fourth-order accurate two- point compact difference scheme. Both the growth rate and perturbation profiles are obtained, and the obtained growth rate is close to the results of direct numerical simulation. Our results show that the growth rate is more reduced and the cutoff wave length becomes longer as preheat increases.

Weak Nonlinearity of Ablative Rayleigh-Taylor Instability

The weakly nonlinear regime of single mode ablative Rayleigh-Taylor instability is studied, with consideration of preheat effect and the width of the ablation front. The Rayleigh-Taylor linear growth rate agrees well with the direct numerical simulation. For the density perturbation, the amplitude distribution of the fundamental mode has one peak value whereas those of the second and third harmonics have two and three peak values, respectively. Harmonics generation versus wave number is also given and it is close to the result of direct numerical simulation.

A novel multimode process monitoring method integrating LCGMM with modified LFDA

Complex processes often work with multiple operation regions, it is critical to develop effective monitoring approaches to ensure the safety of chemical processes. In this work, a discriminant local consistency Gaussian mixture model(DLCGMM) for multimode process monitoring is proposed for multimode process monitoring by integrating LCGMM with modified local Fisher discriminant analysis(MLFDA). Different from Fisher discriminant analysis(FDA) that aims to discover the global optimal discriminant directions, MLFDA is capable of uncovering multimodality and local structure of the data by exploiting the posterior probabilities of observations within clusters calculated from the results of LCGMM. This may enable MLFDA to capture more meaningful discriminant information hidden in the high-dimensional multimode observations comparing to FDA. Contrary to most existing multimode process monitoring approaches, DLCGMM performs LCGMM and MFLDA iteratively, and the optimal subspaces with multi-Gaussianity and the optimal discriminant projection vectors are simultaneously achieved in the framework of supervised and unsupervised learning. Furthermore, monitoring statistics are established on each cluster that represents a specific operation condition and two global Bayesian inference-based fault monitoring indexes are established by combining with all the monitoring results of all clusters. The efficiency and effectiveness of the proposed method are evaluated through UCI datasets, a simulated multimode model and the Tennessee Eastman benchmark process.

A Novel Divide and Conquer Solution for Long-term Video Salient Object Detection

Recently,a new research trend in our video salient object detection(VSOD)research community has focused on enhancing the detection results via model self-fine-tuning using sparsely mined high-quality keyframes from the given sequence.Although such a learning scheme is generally effective,it has a critical limitation,i.e.,the model learned on sparse frames only possesses weak generalization ability.This situation could become worse on“long”videos since they tend to have intensive scene variations.Moreover,in such videos,the keyframe information from a longer time span is less relevant to the previous,which could also cause learning conflict and deteriorate the model performance.Thus,the learning scheme is usually incapable of handling complex pattern modeling.To solve this problem,we propose a divide-and-conquer framework,which can convert a complex problem domain into multiple simple ones.First,we devise a novel background consistency analysis(BCA)which effectively divides the mined frames into disjoint groups.Then for each group,we assign an individual deep model on it to capture its key attribute during the fine-tuning phase.During the testing phase,we design a model-matching strategy,which could dynamically select the best-matched model from those fine-tuned ones to handle the given testing frame.Comprehensive experiments show that our method can adapt severe background appearance variation coupling with object movement and obtain robust saliency detection compared with the previous scheme and the state-of-the-art methods.

On the Arc Consistency Problem

In this paper, we propose a new arc consistency algorithm, AC-8,which requires less computation time and space than AC-6 and AC-7. The main ideaof the optimization is the divide-and-conquer strategy, thereby decomposing an arcconsistency problem into a series of smaller ones and trying to solve them in sequence.In this way, not only the space complexity but also the time complexity can be reduced. The reason for this is that due to the ahead of time performed inconsistencypropagation (in the sense that some of them are executed before the entire inconsis-tency checking has been finished), each constraint subnetwork will be searched with agradually shrunk domain. In addition, the technique of AC-6 can be integrated intoour algorithm, leading to a further decrease in computational complexity.