Controllable terahertz radiation from a linear-dipole-array formed by a two-color laser filament in air

We have demonstrated the effective control on carrier-envelope phase, angular distribution as well as peak intensity of a nearly single-cycle terahertz pulse emitted from a laser filament formed by two-color, the fundamental and the corresponding second harmonics, femtosecond laser pulses propagating in air. Experimentally, such control has been performed by varying the filament length and the initial phase difference between the two-color laser components. A linear-dipole-array model, including the descriptions of the both generation (via laser field ionization) and propagation of the emitted terahertz pulse, is proposed to present a quantitative interpretation of the observations. Our results contribute to the understanding of terahertz generation in a femtosecond laser filament and suggest a practical way to control the electric field of terahertz pulse for potential applications

Multi-Stage Tuberculosis Subunit Vaccine Candidate LT69 Provides High Protection against Mycobacterium tuberculosis Infection in Mice

Effective tuberculosis (TB) vaccine should target tubercle bacilli with various metabolic states and confer long-term protective immunity. In this study, we constructed a novel multi-stage TB subunit vaccine based on fusion protein ESAT6-Ag85B-MPT64(190-198)-Mtb8.4-HspX (LT69 for short) which combined early expressed antigens and latency-associated antigen. The fusion protein was mixed with an adjuvant being composed of N, N’-dimethyl-N, N’-dioctadecylammonium bromide (DDA) and polyriboinosinic polyribocytidylic acid (PolyI:C) to construct subunit vaccine, whose immunogenicity and protective ability were evaluated in C57BL/6 mice. The results showed that LT69 had strong immunogenicity and high protective effect against Mycobacterium tuberculosis (M. tuberculosis) H37Rv aerosol challenge. Low-dose (2 μg) of LT69 generated long-term immune memory responses and provided effective protection, which was even higher than traditional vaccine BCG did at 30 weeks post the last vaccination. In conclusion, multistage subunit vaccine LT69 showed high and long-term protection against M. tuberculosis infection in mice, whose effect could be enhanced by using a relative low dosage of antigen.National Major Science and Technology Projects (China) (2012ZX10003-008-006)National Natural Science Foundation (China) (31470895)National Natural Science Foundation (China) (81072499)China. Ministry of Education (Doctoral Fund 20120211110038

RGMb is a novel binding partner for PD-L2 and its engagement with PD-L2 promotes respiratory tolerance

We report that programmed death ligand 2 (PD-L2), a known ligand of PD-1, also binds to repulsive guidance molecule b (RGMb), which was originally identified in the nervous system as a co-receptor for bone morphogenetic proteins (BMPs). PD-L2 and BMP-2/4 bind to distinct sites on RGMb. Normal resting lung interstitial macrophages and alveolar epithelial cells express high levels of RGMb mRNA, whereas lung dendritic cells express PD-L2. Blockade of the RGMb–PD-L2 interaction markedly impaired the development of respiratory tolerance by interfering with the initial T cell expansion required for respiratory tolerance. Experiments with PD-L2–deficient mice showed that PD-L2 expression on non–T cells was critical for respiratory tolerance, but expression on T cells was not required. Because PD-L2 binds to both PD-1, which inhibits antitumor immunity, and to RGMb, which regulates respiratory immunity, targeting the PD-L2 pathway has therapeutic potential for asthma, cancer, and other immune-mediated disorders. Understanding this pathway may provide insights into how to optimally modulate the PD-1 pathway in cancer immunotherapy while minimizing adverse events

Positive Solutions for a Class of Singular Boundary Value Problems with Fractional q

We discuss a class of singular boundary value problems of fractional q-difference equations. Some existence and uniqueness results are obtained by a fixed point theorem in partially ordered sets. Finally, we give an example to illustrate the results

Information retrieval and visualization from literature and genomic databases using gene names

In this thesis, I develop a new prototype of information retrieval and visualization tool to represent the gene relations. The system is implemented using web language PHP, database MySQL and Java technology Java Applet. Within the implementation, there will be a graphics user interface (GUI) including a gene matrix and a network graph. The first one provides links to literature from Medline or Saccharomyces cerevisiae database (SGD), while the later one is a network graph with nodes as genes and edges as the coexistence of both genes within the same Medline documents. Edge length represents the correlation between two genes: a short distance means that they appear more in various documents while a far distance means a weak relation. Finally, I will compare the new design with the old design of an existing system. I strongly believe that my work will be advanced for the following reasons: the implementation is much easier; relational database provides more efficient way to store and query data.California State University, Northridge. Department of Computer Science.Includes bibliographical references (leaves 45-46

Augmented semi-supervised learning for salient object detection with edge computing

[EN] Salient object detection (SOD) from raw sensor images in the edge networks can effectively speed up the decision-making process in the complex environments, because it simulates the mechanism of human attention to identify salient objects from images. The success of supervised deep learning approaches have been widely proved SOD field. However, the imbalanced and limited training data at each edge device pose a huge challenge for us to deploy deep learning methods in the edge computing environments. In this article, we propose a cloud-edge distributed augmented semi-supervised learning architecture for SOD over the edge networks. The framework consists of two components: the base classification networks are employed in different edge nodes, and the reverse augmented network is employed in cloud. First, the base classification networks are trained with data from edge nodes while the reverse augmented network is trained with the whole data. Then, we concatenate each base classification network with reverse augmented network, thus the latter network can help the training of former network. Finally, we integrate the outputs of all base classification network to generate the pseudo-labels, which are used for semi-supervised learning of the augment network. We demonstrated a convincing performance of our semi-supervised learning framework on four bench-marked data-sets. These results show that our augmented semi-supervised learning framework can outperform other optimization strategies on deep learning for the edge computing.Yu, C.; Zhang, Y.; Mukherjee, M.; Lloret, J. (2022). Augmented semi-supervised learning for salient object detection with edge computing. IEEE Wireless Communications. 29(3):109-114. https://doi.org/10.1109/MWC.2020.200035110911429