Outlier Impact and Accommodation Methods: Multiple Comparisons of Type I Error Rates

A Monte Carlo simulation study was conducted to examine outliers’ influence on Type I error rates in ANOVA and Welch tests, and the effectiveness of two outlier accommodation methods: nonparametric rank based method and Winsorizing. The study also offered practical recommendations regarding outlier handling with different sample sizes and number of outliers

Outlier Impact and Accommodation on Power

The outliers’ influence on power rates in ANOVA and Welch tests at various conditions was examined and compared with the effectiveness of nonparametric methods and Winsorizing in minimizing the impact of outliers. Results showed that, considering both power and Type I error, a nonparametric test is the safest choice to control the inflation of Type I error with a decent sample size and yield relatively high power

Trends in HIV prevalence and risk behaviours among men who have sex with men from 2013 to 2017 in Nanjing, China: a consecutive cross-sectional survey.

OBJECTIVE:To examine the trends of HIV prevalence, risk behaviours and HIV testing among men who have sex with men (MSM) in Nanjing. DESIGN:Five consecutive cross-sectional surveys. SETTING:Nanjing, China. PRIMARY AND SECONDARY OUTCOME MEASURES:HIV and syphilis prevalence, HIV testing rate and factors associated with HIV infection; demographic characteristics and behaviours. RESULTS:649, 669, 577, 633, 503 MSM were recruited from 2013 to 2017. HIV prevalence was 9.9%, 12.3%, 12.5%, 9.8% and 10.1%, respectively. Syphilis prevalence decreased with a range from 10.6% to 5.6%. Risk behaviours like unprotected anal intercourse (UAI) and unprotected virginal sex in the past 6 months decreased, but multiple sex partners and ever used rush popper rose significantly. MSM tested for HIV in the previous year remained stable from 57.0% to 64.1% (P=0.633). Multivariate analysis showed that tested for HIV in the past year was protective factor against HIV infection. MSM who had UAI in the past 6 months, sex role as receptive and dual, diagnosed with sexually transmitted diseases (STDs) in the past year and currently syphilis infected were risk factors for HIV infection. CONCLUSIONS:We observed stable high HIV prevalence, a steady HIV testing rate, decreasing syphilis prevalence and UAI among MSM in Nanjing. However, rush popper use rose dramatically. The HIV preventive strategies for MSM including condom promotion, HIV testing expansion and reduction of rush popper use, STDs screening and standardised treatment should be strengthened

Direct Adversarial Training: A New Approach for Stabilizing The Training Process of GANs

Generative Adversarial Networks (GANs) are the most popular models for image generation by optimizing discriminator and generator jointly and gradually. However, instability in training process is still one of the open problems for all GAN-based algorithms. In order to stabilize training, some regularization and normalization techniques have been proposed to make discriminator meet the Lipschitz continuity constraint. In this paper, a new approach inspired by works on adversarial attack is proposed to stabilize the training process of GANs. It is found that sometimes the images generated by the generator play a role just like adversarial examples for discriminator during the training process, which might be a part of the reason of the unstable training. With this discovery, we propose to introduce a adversarial training method into the training process of GANs to improve its stabilization. We prove that this DAT can limit the Lipschitz constant of the discriminator adaptively. The advanced performance of the proposed method is verified on multiple baseline and SOTA networks, such as DCGAN, WGAN, Spectral Normalization GAN, Self-supervised GAN and Information Maximum GAN

Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering

With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users

High Precision Multi-parameter Weak Measurement with Hermite-Gaussian Pointer

The weak value amplification technique has been proved useful for precision metrology in both theory and experiment. To explore the ultimate performance of weak value amplification for multi-parameter estimation, we investigate a general weak measurement formalism with assistance of high-order Hermite-Gaussian pointer and quantum Fisher information matrix. Theoretical analysis shows that the ultimate precision of our scheme is improved by a factor of square root of 2n+1, where n is the order of Hermite-Gaussian mode. Moreover, the parameters' estimation precision can approach the precision limit with maximum likelihood estimation method and homodyne method. We have also given a proof-of-principle experimental setup to validate the H-G pointer theory and explore its potential applications in precision metrology

Illegal Intrusion Detection of Internet of Things Based on Deep Mining Algorithm

In this study, to reduce the influence of The Internet of Things (IoT) illegal intrusion on the transmission effect, and ensure IoT safe operation, an illegal intrusion detection method of the Internet of Things (IoT) based on deep mining algorithm was designed to accurately detect IoT illegal intrusion. Moreover, this study collected the data in the IoT through data packets and carries out data attribute mapping on the collected data, transformed the character information into numerical information, implemented standardization and normalization processing on the numerical information, and optimized the processed data by using a regional adaptive oversampling algorithm to obtain an IoT data training set. The IoT data training set was taken as the input data of the improved sparse auto-encoder neural network. The hierarchical greedy training strategy was used to extract the feature vector of the sparse IoT illegal intrusion data that were used as the inputs of the extreme learning machine classifier to realize the classification and detection of the IoT illegal intrusion features. The experimental results indicate that the feature extraction of the illegal intrusion data of the IoT can effectively reduce the feature dimension of the illegal intrusion data of the IoT to less than 30 and the dimension of the original data. The recall rate, precision, and F1 value of the IoT intrusion detection are 98.3%, 98.7%, and 98.6%, respectively, which can accurately detect IoT intrusion attacks. The conclusion demonstrates that the intrusion detection of IoT based on deep mining algorithm can achieve accurate detection of IoT illegal intrusion and reduce the influence of IoT illegal intrusion on the transmission effect

Reducing toxicity and increasing efficiency: aconitine with liquiritin and glycyrrhetinic acid regulate calcium regulatory proteins in rat myocardial cell

Background: Compatibility of Radix Aconiti Carmichaeli and Liquorice is known to treat heart diseases such as heart failure and cardiac arrhythmias. This work answers the question that whether the active components (Aconitine, Liquiritin and Glycyrrhetinic Acid) of Radix Aconiti Carmichaeli and Liquorice could result in regulating intracellular calcium homeostasis and calcium cycling, and thereby verifies the therapeutic material basis.Materials and Methods: The myocardial cells were divided into twelve groups randomly as control group, Aconitine group, nine different dose groups that orthogonal combined with Aconitine, Liquiritin and Glycyrrhetinic Acid, and Verapamil group. The myocardial cellular survival rate and morphology were assessed. The expression of calcium regulation protein(RyR2、NCX1、DHPR-a1) in the myocardial cell by Western-blotting.Results: The results exhibited that Aconitine (120 uM) significantly damaged on myocardial cell, decreased the survival rate and expression of Na+/Ca2+ exchangers (NCX1) and dihydropteridine reducta-α1 (DHPR-a1), and increased the expression of ryanodine receptor type2 (RyR2) obviously. The compatibility groups (Aconitine, Liquiritin and Glycyrrhetinic Acid) all could against the damage on the myocardial cell by Aconitine at different levels.Conclusion: Aconitine with Liquiritin and Glycyrrhetinic Acid may regulate the expression of calcium-regulated proteins to protect myocardial cells from damage.Keywords: Aconitine, Liquiritin, Glycyrrhetinic Acid, myocardial cell, calcium regulator

Selection of the Composition with High Glass Forming Ability in Zr-Cu-Ni-Al Bulk Metallic Glasses

Three new Zr-Cu-Ni-Al bulk metallic glasses were developed through appropriate mixing of three binary eutectics Zr38.2Cu61.8, Zr51Al49, and Zr64Ni36. By suppressing solidification of competing crystalline phases, a new glass forming alloy Zr51Cu24.22Ni14.06Al10.72 with the critical diameter of up to 10 mm is obtained