Short-Packet Downlink Transmission with Non-Orthogonal Multiple Access

This work introduces downlink non-orthogonal multiple access (NOMA) into short-packet communications. NOMA has great potential to improve fairness and spectral efficiency with respect to orthogonal multiple access (OMA) for low-latency downlink transmission, thus making it attractive for the emerging Internet of Things. We consider a two-user downlink NOMA system with finite blocklength constraints, in which the transmission rates and power allocation are optimized. To this end, we investigate the trade-off among the transmission rate, decoding error probability, and the transmission latency measured in blocklength. Then, a one-dimensional search algorithm is proposed to resolve the challenges mainly due to the achievable rate affected by the finite blocklength and the unguaranteed successive interference cancellation. We also analyze the performance of OMA as a benchmark to fully demonstrate the benefit of NOMA. Our simulation results show that NOMA significantly outperforms OMA in terms of achieving a higher effective throughput subject to the same finite blocklength constraint, or incurring a lower latency to achieve the same effective throughput target. Interestingly, we further find that with the finite blocklength, the advantage of NOMA relative to OMA is more prominent when the effective throughput targets at the two users become more comparable.Comment: 15 pages, 9 figures. This is a longer version of a paper to appear in IEEE Transactions on Wireless Communications. Citation Information: X. Sun, S. Yan, N. Yang, Z. Ding, C. Shen, and Z. Zhong, "Short-Packet Downlink Transmission with Non-Orthogonal Multiple Access," IEEE Trans. Wireless Commun., accepted to appear [Online] https://ieeexplore.ieee.org/document/8345745

Population and allelic variation of A-to-I RNA editing in human transcriptomes.

BackgroundA-to-I RNA editing is an important step in RNA processing in which specific adenosines in some RNA molecules are post-transcriptionally modified to inosines. RNA editing has emerged as a widespread mechanism for generating transcriptome diversity. However, there remain significant knowledge gaps about the variation and function of RNA editing.ResultsIn order to determine the influence of genetic variation on A-to-I RNA editing, we integrate genomic and transcriptomic data from 445 human lymphoblastoid cell lines by combining an RNA editing QTL (edQTL) analysis with an allele-specific RNA editing (ASED) analysis. We identify 1054 RNA editing events associated with cis genetic polymorphisms. Additionally, we find that a subset of these polymorphisms is linked to genome-wide association study signals of complex traits or diseases. Finally, compared to random cis polymorphisms, polymorphisms associated with RNA editing variation are located closer spatially to their respective editing sites and have a more pronounced impact on RNA secondary structure.ConclusionsOur study reveals widespread cis variation in RNA editing among genetically distinct individuals and sheds light on possible phenotypic consequences of such variation on complex traits and diseases

An expert system based on 1 H NMR spectroscopy for quality evaluation and adulteration identification of edible oils

Abstract(#br)The advantages of nuclear magnetic resonance (NMR) such as nondestructive and simultaneous detection, high reproducibility and rapidity make it easily develop the objective and credible methods for food analysis and identification. In this study, we developed a computer-aided, MATLAB-scripted expert system which enables NMR data to distinguish different edible oils and evaluate the quality of edible oils. The NMR spectral data of seven species of most popular vegetable edible oils in China were used to establish the assessment criterions including the content percentage of fatty acids and the quality parameters of edible oils. In our case, the identification accuracy of vegetable origin for the pure edible oils is 95.83% and that for the mixed edible oils is 89.58%, and all the recycled waste cooking oils and fried oils were correctly screened out and identified by the expert system. Further, the quality information of the edible oils was also provided. Our results show that the current expert system is a fast, easy-operated and convenient tool for the adulteration identification and quality control of edible oils

Intracoronary artery retrograde thrombolysis combined with percutaneous coronary interventions for ST-segment elevation myocardial infarction complicated with diabetes mellitus: A case report and literature review

BackgroundThe management of a large thrombus burden in patients with acute myocardial infarction and diabetes is still a worldwide problem.Case presentationA 74-year-old Chinese woman presented with ST-segment elevation myocardial infarction (STEMI) complicated with diabetes mellitus and hypertension. Angiography revealed massive thrombus formation in the mid-segment of the right coronary artery leading to vascular occlusion. The sheared balloon was placed far from the occlusion segment and urokinase (100,000 u) was administered for intracoronary artery retrograde thrombolysis, and thrombolysis in myocardial infarction (TIMI) grade 3 blood flow was restored within 7 min. At last, one stent was accurately implanted into the culprit’s vessel. No-reflow, coronary slow flow, and reperfusion arrhythmia were not observed during this process.ConclusionIntracoronary artery retrograde thrombolysis (ICART) can be effectively and safely used in patients with STEMI along with diabetes mellitus and hypertension, even if the myocardial infarction exceeds 12 h (REST or named ICART ClinicalTrials.gov number, ChiCTR1900023849)

MATS: a Bayesian framework for flexible detection of differential alternative splicing from RNA-Seq data

Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (multivariate analysis of transcript splicing), a Bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the between-sample correlation in exon splicing patterns, and a Markov chain Monte Carlo (MCMC) method coupled with a simulation-based adaptive sampling procedure to calculate the P-value and false discovery rate (FDR) of differential alternative splicing. Importantly, the MATS approach is applicable to almost any type of null hypotheses of interest, providing the flexibility to identify differential alternative splicing events that match a given user-defined pattern. We evaluated the performance of MATS using simulated and real RNA-Seq data sets. In the RNA-Seq analysis of alternative splicing events regulated by the epithelial-specific splicing factor ESRP1, we obtained a high RT–PCR validation rate of 86% for differential exon skipping events with a MATS FDR of <10%. Additionally, over the full list of RT–PCR tested exons, the MATS FDR estimates matched well with the experimental validation rate. Our results demonstrate that MATS is an effective and flexible approach for detecting differential alternative splicing from RNA-Seq data