Atomic Dipole Squeezing in the Correlated Two-Mode Two-Photon Jaynes-Cummings Model

In this paper, we study the atomic dipole squeezing in the correlated two-mode two-photon JC model with the field initially in the correlated two-mode SU(1,1) coherent state. The effects of detuning, field intensity and number difference between the two field modes are investigated through numerical calculation

ATRank: An Attention-Based User Behavior Modeling Framework for Recommendation

A user can be represented as what he/she does along the history. A common way to deal with the user modeling problem is to manually extract all kinds of aggregated features over the heterogeneous behaviors, which may fail to fully represent the data itself due to limited human instinct. Recent works usually use RNN-based methods to give an overall embedding of a behavior sequence, which then could be exploited by the downstream applications. However, this can only preserve very limited information, or aggregated memories of a person. When a downstream application requires to facilitate the modeled user features, it may lose the integrity of the specific highly correlated behavior of the user, and introduce noises derived from unrelated behaviors. This paper proposes an attention based user behavior modeling framework called ATRank, which we mainly use for recommendation tasks. Heterogeneous user behaviors are considered in our model that we project all types of behaviors into multiple latent semantic spaces, where influence can be made among the behaviors via self-attention. Downstream applications then can use the user behavior vectors via vanilla attention. Experiments show that ATRank can achieve better performance and faster training process. We further explore ATRank to use one unified model to predict different types of user behaviors at the same time, showing a comparable performance with the highly optimized individual models.Comment: AAAI 201

Expression and Contribution of Insulin Signaling Pathway to the Development of Polycystic Ovary Syndrome

Our previous studies have demonstrated that insulin signaling pathway has an important role in the pathophysiology of polycystic ovary syndrome (PCOS), including phosphatidylinositol 3-kinase and protein kinase B signaling, which is critically implicated in insulin resistance, androgen secretion, obesity, and follicular development. PCOS manifests as defective ovarian steroid biosynthesis and hyperandrogenemia, and 50–70% of women with PCOS exhibit insulin resistance and are hyperinsulinemic, indicating that insulin resistance and hyperinsulinism may have an important role in the pathophysiology of PCOS. Therefore, the present article will review the contribution of insulin signaling pathway to the abnormal regulation of follicular growth and ovulation, which can cause corresponding reproductive endocrine diseases and affect women’s reproductive health. Exploring the mechanism of insulin signaling pathway in PCOS will help not only to understand the physiology and pathology of follicular development but also to provide theoretical basis for the treatment of PCOS

Design of a denoising hybrid fuzzy-pid controller for active suspension systems of heavy vehicles based on model adaptive wheelbase preview strategy

Active suspension is an effective approach to improve vehicle performance, and it is of great importance to attenuate the vibration of the rear part of heavy vehicles with freight. This paper proposes a new hybrid fuzzy proportional-integral-derivative (PID) controller with model adaptive wheelbase preview and wavelet denoising filter in an active suspension system for heavy vehicles with freight. A half vehicle model is first built, followed with the construction of the road excitation profiles of the shock and vibration pavement. After the design and implementation of the control method, four performance indices of the vehicle are evaluated. To verify the effectiveness of the proposed method, the control performance of the integrated controller and the separate function of every single controller are evaluated respectively. Numerical results show that the integrated control algorithm is superior to the single controllers and is effective in improving the vehicle performance as compared with other methods. Moreover, the wavelet denoising filter is shown to be an effective way to improve the vehicle performance and enable the stability of the system against noise

Design of a Road Friendly SAS System for Heavy-Duty Vehicles Based on a Fuzzy-Hybrid-ADD and GH-Control Strategy

Semiactive suspension (SAS) system has been widely used for its outstanding performance in offering competent ride quality, road holding, and handling capacity. However, the road friendliness is also one of the crucial factors that should be attached in the design of the SAS system for heavy-duty vehicles. In this study, a fuzzy controlled hybrid-acceleration driven damper (ADD) and ground hook- (GH-) control strategy is proposed for SAS system of heavy-duty vehicles. Firstly, a quarter-vehicle model with SAS system is constructed. Then, aiming to improve the ride quality and road friendliness, a hybrid-ADD and GH-control strategy is proposed under the coordination of the fuzzy controller. Numerical results show that the ride quality and road friendliness of the SAS system with the proposed control strategy outperform those with traditional hybrid-sky hook and ground hook-control strategy. It is also verified that the proposed strategy is superior to the sole ADD approach and sole ground hook approach in improving the vehicle overall performance

An entropy and MRF model-based CNN for large-scale Landsat image classification

Large-scale Landsat image classification is essential for the production of land cover maps. The rise of convolutional neural networks (CNNs) provides a new idea for the implementation of Landsat image classification. However, pixels in Landsat images have higher uncertainty compared with high-resolution images due to its 30-m spatial resolution. In addition, the current deep learning methods tend to lose detailed information such as boundaries along with the stacking of convolutional and pooling layers. To solve these problems, we propose a new method called entropy and MRF model (EMM)-CNN based on Pyramid Scene Parsing Network. The EMM-CNN uses entropy to decrease the uncertainty of pixels. Then, the Markov random filed (MRF) model is employed to construct the connections between neighboring pixels and defined a prior distribution to prevent the cross entropy from sacrificing detailed information for the overall accuracy. Finally, transfer learning based on the pretrained ImageNet is introduced to overcome the shortage of training samples and boost the speed of the training process. Experimental results demonstrate that the proposed EMM-CNN is able to obtain classification results with fine structure by decreasing the uncertainty and retaining detailed information of the detected image

A third (booster) dose of the inactivated SARS-CoV-2 vaccine elicits immunogenicity and T follicular helper cell responses in people living with HIV

IntroductionThis study sought to explore the immunogenicity of a booster dose of an inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in people living with human immunodeficiency virus (HIV) and identify the factors affecting the magnitude of anti-SARS-CoV-2 antibody levels.Materials and methodsA total of 34 people living with HIV (PLWH) and 34 healthy donors (HD) were administered a booster dose of the same SARS-CoV-2 vaccine. Anti-SARS-CoV-2 antibody and immunoglobulin G (IgG) levels were measured using the SARS-CoV-2 S protein neutralizing antibody Enzyme-Linked Immunosorbent Assay (ELISA) and 2019-nCov IgG Chemiluminescent Immunoassay Microparticles, respectively. Spearman correlation analysis was used to measure the correlation between laboratory markers and neutralizing antibody and IgG levels. Peripheral blood mononuclear cells (PBMCs) were extracted from each subject using density gradient centrifugation and the numbers of memory T and T follicular helper (Tfh) cells were determined using flow cytometry.ResultsPLWH had a marked reduction in CD4 and B cell levels that was accompanied by a lower CD4/CD8 T cell ratio. However, those who received a supplementary dose of inactivated SARS-CoV-2 vaccines exhibited antibody positivity rates that were analogous to levels previously observed. The booster vaccine led to a reduction in IgG and neutralizing antibody levels and the amplitude of this decline was substantially higher in the PLWH than HD group. Correlation analyses revealed a strong correlation between neutralizing antibody levels and the count and proportion of CD4 cells. Anti-SARS-CoV-2 IgG antibody levels followed a similar trend. The expression of memory T and Tfh cells was considerably lower in the PLWH than in the HD group.DiscussionPLWH had an attenuated immune response to a third (booster) administration of an inactivated SARS-CoV-2 vaccine, as shown by lower neutralizing antibody and IgG levels. This could be attributed to the reduced responsiveness of CD4 cells, particularly memory T and cTfh subsets. CD4 and cTfh cells may serve as pivotal markers of enduring and protective antibody levels. Vaccination dose recalibration may be critical for HIV-positive individuals, particularly those with a lower proportion of CD4 and Tfh cells