Electron Flavored Dark Matter

In this paper we investigate the phenomenology of the electron flavored Dirac dark matter with two types of portal interactions. We analyze constraints from the electron magnetic moment anomaly, LHC searches of singly charged scalar, dark matter relic abundance as well as direct and indirect detections. Our study shows that the available parameter space is quite constrained, but there are parameter space that is compatible with the current data. We further show that the DAMPE cosmic ray electron excess, which indicates cosmic ray excess at around 1.5 TeV, can be interpreted as the annihilation of dark matter into electron positron pairs in this model.Comment: 6 pages, 5 figure

A Survey and Empirical Evaluation of Parallel Deep Learning Frameworks

The field of deep learning has witnessed a remarkable shift towards extremely compute- and memory-intensive neural networks. These newer larger models have enabled researchers to advance state-of-the-art tools across a variety of fields. This phenomenon has spurred the development of algorithms for distributed training of neural networks over a larger number of hardware accelerators. In this paper, we discuss and compare current state-of-the-art frameworks for large scale distributed deep learning. First, we survey current practices in distributed learning and identify the different types of parallelism used. Then, we present empirical results comparing their performance on large image and language training tasks. Additionally, we address their statistical efficiency and memory consumption behavior. Based on our results, we discuss algorithmic and implementation portions of each framework which hinder performance

A Method of Information Fusion Based on Fuzzy Neural Network and Its Application

In view of the limitation of fault diagnosis methods in substation intelligent patrol system, a fault diagnosis method based on multi-sensors information fusion is proposed. In the field of fault diagnosis, this method can deal with uncertain and imprecise information by using fuzzy theory, and has a high self-study capability based on neural network. Collecting samples of data through establishing many sensors in the scene of the intelligent patrol system, and then through the BP algorithm of fuzzy neural network training to achieve accurate fault diagnosis function of the intelligent patrol system. By comparing the result of an example, it shows that, compared with using single information, using multi-sensors information as the diagnosis method is more accurate and reliable in the intelligent patrol system

Novel intronic microRNA represses zebrafish myf5 promoter activity through silencing dickkopf-3 gene

A strong, negative cis-element located at the first intron +502/+835 (I300) of zebrafish myf5 has been reported. To elucidate the molecular mechanism underlying this repression network, we microinjected zebrafish single-cell embryos with I300 RNA, resulting in the dramatic reduction of luciferase activity driven by the myf5 promoter. Within this I300 segment, we identified an intronic microRNA (miR-In300) located at +609/+632 and found that it was more highly expressed in the older mature somites than those newly formed, which negatively correlated with the distribution of zebrafish myf5 transcripts. We proved that miR-In300 suppressed the transcription of myf5 through abolishing myf5 promoter activity, and we subsequently identified the long isoform of the Dickkopf-3 gene (dkk3) as the target gene of miR-In300. We further found that injection of the dkk3-morpholinos (MOs) resulted in downregulation of myf5 transcripts in somites, whereas co-injection of myf5 mRNA with dkk3-MO1 enabled rescue of the defects induced by dkk3-MO1 alone. Finally, injection of miR-In300-MO enhanced both myf5 transcripts in somites and the level of Dkk3 protein in zebrafish embryos. Based on these findings, we concluded that miR-In300 binds to its target gene dkk3, which inhibits the translation of dkk3 mRNA and, in turn, suppresses zebrafish myf5 promoter activity

New Perspectives on Host-Parasite Interplay by Comparative Transcriptomic and Proteomic Analyses of Schistosoma japonicum

Schistosomiasis remains a serious public health problem with an estimated 200 million people infected in 76 countries. Here we isolated ~ 8,400 potential protein-encoding cDNA contigs from Schistosoma japonicum after sequencing circa 84,000 expressed sequence tags. In tandem, we undertook a high-throughput proteomics approach to characterize the protein expression profiles of a number of developmental stages (cercariae, hepatic schistosomula, female and male adults, eggs, and miracidia) and tissues at the host-parasite interface (eggshell and tegument) by interrogating the protein database deduced from the contigs. Comparative analysis of these transcriptomic and proteomic data, the latter including 3,260 proteins with putative identities, revealed differential expression of genes among the various developmental stages and sexes of S. japonicum and localization of putative secretory and membrane antigens, enzymes, and other gene products on the adult tegument and eggshell, many of which displayed genetic polymorphisms. Numerous S. japonicum genes exhibited high levels of identity with those of their mammalian hosts, whereas many others appeared to be conserved only across the genus Schistosoma or Phylum Platyhelminthes. These findings are expected to provide new insights into the pathophysiology of schistosomiasis and for the development of improved interventions for disease control and will facilitate a more fundamental understanding of schistosome biology, evolution, and the host-parasite interplay

Yersinia pseudotuberculosis Exploits CD209 Receptors for Promoting Host Dissemination and Infection

Yersinia pseudotuberculosis is a Gram-negative enteropathogen and causes gastrointestinal infections. It disseminates from gut to mesenteric lymph nodes (MLNs), spleen, and liver of infected humans and animals. Although the molecular mechanisms for dissemination and infection are unclear, many Gram-negative enteropathogens presumably invade the small intestine via Peyer's patches to initiate dissemination. In this study, we demonstrate that Y. pseudotuberculosis utilizes its lipopolysaccharide (LPS) core to interact with CD209 receptors, leading to invasion of human dendritic cells (DCs) and murine macrophages. These Y. pseudotuberculosis CD209 interactions result in bacterial dissemination to MLNs, spleens, and livers of both wild-type and Peyer's patch-deficient mice. The blocking of the Y. pseudotuberculosis CD209 interactions by expression of 0-antigen and with oligosaccharides reduces infectivity. Based on the well-documented studies in which HIV-CD209 interaction leads to viral dissemination, we therefore propose an infection route for Y. pseudotuberculosis where this pathogen, after penetrating the intestinal mucosal membrane, hijacks the Y. pseudotuberculosis CD209 interaction antigen-presenting cells to reach their target destinations, MLNs, spleens, and livers.Peer reviewe