A Coupled Compressive Sensing Scheme for Unsourced Multiple Access

This article introduces a novel paradigm for the unsourced multiple-access communication problem. This divide-and-conquer approach leverages recent advances in compressive sensing and forward error correction to produce a computationally efficient algorithm. Within the proposed framework, every active device first partitions its data into several sub-blocks, and subsequently adds redundancy using a systematic linear block code. Compressive sensing techniques are then employed to recover sub-blocks, and the original messages are obtained by connecting pieces together using a low-complexity tree-based algorithm. Numerical results suggest that the proposed scheme outperforms other existing practical coding schemes. Measured performance lies approximately $4.3$~dB away from the Polyanskiy achievability limit, which is obtained in the absence of complexity constraints

Functional Genomic Analysis of Human Mitochondrial RNA Processing

SummaryBoth strands of human mtDNA are transcribed in continuous, multigenic units that are cleaved into the mature rRNAs, tRNAs, and mRNAs required for respiratory chain biogenesis. We sought to systematically identify nuclear-encoded proteins that contribute to processing of mtRNAs within the organelle. First, we devised and validated a multiplex MitoString assay that quantitates 27 mature and precursor mtDNA transcripts. Second, we applied MitoString profiling to evaluate the impact of silencing each of 107 mitochondrial-localized, predicted RNA-binding proteins. With the resulting data set, we rediscovered the roles of recently identified RNA-processing enzymes, detected unanticipated roles of known disease genes in RNA processing, and identified new regulatory factors. We demonstrate that one such factor, FASTKD4, modulates the half-lives of a subset of mt-mRNAs and associates with mtRNAs in vivo. MitoString profiling may be useful for diagnosing and deciphering the pathogenesis of mtDNA disorders

A Literature review on Balancing Workload in Cloud Computing

Cloud computing is the realistic evolution of information technology in a world that is learning to be more and more based on the division of work. Cloud computing offers many principles that are long accomplished in other industries to the IT. We focus on basic characteristics of cloud computing help you understand them. A pattern language is used to interconnecting set of cloud patterns. A cloud pattern is a small human readable document of a well-defined format describing a good solution to a cloud related problem. We studied and captured such patterns describing different types of clouds, the offerings they provide and how to build application with them. In this paper we mainly focus on different types of application workload patterns. Pattern for application workloads describe different user behavior resulting in changing utilization of IT resources hosting an application. Having motivated the need for cloud offerings to handle different workloads we introduce common cloud service models that describe different styles to offer IT resources on different levels of an application stack. Furthermore we also discuss how the corresponding service models and cloud deployment models enable the cloud computing properties