Understanding the Values of Live Game Streaming: a Value-Focused Thinking Approach

Today, along with the development of information communication technology, live streaming is getting more and more popular in China. It has established an integrated industrial chain. There are a large number of users watching different live streams (e.g., games. sports, live shows) through personal computers and mobile devices. In this paper, we aim to investigate the values of live game streaming using the Value-Focused Thinking (VFT) approach. We analyze the values of live game streaming from the perspectives of both streamers and spectators. The identified values are represented in the form of a means-ends objective network. The means-ends objective network derived from this research can serve as a conceptual foundation for future studies and provide useful guidelines for practitioners to better operate live game streaming applications

Chromosomal mapping, differential origin and evolution of the S100 gene family

S100 proteins are calcium-binding proteins, which exist only in vertebrates and which constitute a large protein family. The origin and evolution of the S100 family in vertebrate lineages remain a challenge. Here, we examined the synteny conservation of mammalian S100A genes by analysing the sequence of available vertebrate S100 genes in databases. Five S100A gene members, unknown previously, were identified by chromosome mapping analysis. Mammalian S100A genes are duplicated and clustered on a single chromosome while two S100A gene clusters are found on separate chromosomes in teleost fish, suggesting that S100A genes existed in fish before the fish-specific genome duplication took place. During speciation, tandem gene duplication events within the cluster of S100A genes of a given chromosome have probably led to the multiple members of the S100A gene family. These duplicated genes have been retained in the genome either by neofunctionalisation and/or subfunctionalisation or have evolved into non-coding sequences. However in vertebrate genomes, other S100 genes are also present i.e. S100P, S100B, S100G and S100Z, which exist as single copy genes distributed on different chromosomes, suggesting that they could have evolved from an ancestor different to that of the S100A genes

Automatic verification of multi-threaded programs by inference of rely-guarantee specifications

Ministry of Education, Singapore under its Academic Research Funding Tier 2; National Research Foundation (NRF) Singapor

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

Models and estimators linking individual-based and sample-based rarefaction, extrapolation and comparison of assemblages

Aims: In ecology and conservation biology, the number of species counted in a biodiversity study is a key metric but is usually a biased underestimate of total species richness because many rare species are not detected. Moreover, comparing species richness among sites or samples is a statistical challenge because the observed number of species is sensitive to the number of individuals counted or the area sampled. For individual-based data, we treat a single, empirical sample of species abundances from an investigator-defined species assemblage or community as a reference point for two estimation objectives under two sampling models: estimating the expected number of species (and its unconditional variance) in a random sample of (i) a smaller number of individuals (multinomial model) or a smaller area sampled (Poisson model) and (ii) a larger number of individuals or a larger area sampled. For sample-based incidence (presence-absence) data, under a Bernoulli product model, we treat a single set of species incidence frequencies as the reference point to estimate richness for smaller and larger numbers of sampling units. Methods: The first objective is a problem in interpolation that we address with classical rarefaction (multinomial model) and Coleman rarefaction (Poisson model) for individual-based data and with sample-based rarefaction (Bernoulli product model) for incidence frequencies. The second is a problem in extrapolation that we address with sampling-theoretic predictors for the number of species in a larger sample (multinomial model), a larger area (Poisson model) or a larger number of sampling units (Bernoulli product model), based on an estimate of asymptotic species richness. Although published methods exist for many of these objectives, we bring them together here with some new estimators under a unified statistical and notational framework. This novel integration of mathematically distinct approaches allowed us to link interpolated (rarefaction) curves and extrapolated curves to plot a unified species accumulation curve for empirical examples. We provide new, unconditional variance estimators for classical, individual-based rarefaction and for Coleman rarefaction, long missing from the toolkit of biodiversity measurement. We illustrate these methods with datasets for tropical beetles, tropical trees and tropical ants. Important Findings: Surprisingly, for all datasets we examined, the interpolation (rarefaction) curve and the extrapolation curve meet smoothly at the reference sample, yielding a single curve. Moreover, curves representing 95% confidence intervals for interpolated and extrapolated richness estimates also meet smoothly, allowing rigorous statistical comparison of samples not only for rarefaction but also for extrapolated richness values. The confidence intervals widen as the extrapolation moves further beyond the reference sample, but the method gives reasonable results for extrapolations up to about double or triple the original abundance or area of the reference sample. We found that the multinomial and Poisson models produced indistinguishable results, in units of estimated species, for all estimators and datasets. For sample-based abundance data, which allows the comparison of all three models, the Bernoulli product model generally yields lower richness estimates for rarefied data than either the multinomial or the Poisson models because of the ubiquity of non-random spatial distributions in nature. © 2012 The Author. Published by Oxford University Press on behalf of the Institute of Botany, Chinese Academy of Sciences and the Botanical Society of China. All rights reserved

A study on non-invasive prenatal screening for the detection of aneuploidy

Objectives: To explore the feasibility of clinical application of non-invasive prenatal screening to detect aneuploidy diseases. Material and methods: A total of 14,574 singleton pregnant women who underwent Non-invasive prenatal testing (NIPT) in the Southern Hospital from 2015 to June 2017 were selected, and 6471 pregnant women with twin pregnancy who underwent NIPT in the laboratory of Bei Rui He Kang Southern Hospital from June 2016 to October 2017 were included in this study. We analyzed NIPT screening efficiency (sensitivity, specificity) in twin pregnancies and singleton pregnancies, compared the positive detection rate of NIPT in patients with or without clinical symptoms. All NIPT high-risk results were validated by karyotyping, which were further verified by the follow-up physical examination of the neonatal. Results: A total of 68 cases of twin pregnancy abnormalities were detected by NIPT, including 18 cases of trisomy 21, 6 cases of trisomy 18, 1 case of trisomy 13, 39 cases of Spinocerebellar ataxias (SCAs), and 4 cases of other chromosomal abnormalities. The sensitivity for trisomy 21, 18, and 13 and sex chromosome abnormality was 100%; the specificity for trisomy 21, 18, and 13 and sex chromosome abnormality was 99.97%, 99.95%, 99.97%, and 99.91% respectively. The screening efficiency was similar to that of singleton pregnancy, indicating that the NIPT technology in our laboratory for screening for aneuploidy diseases in twin pregnancy has reached the accuracy level of singleton pregnancy screening. There was a statistical difference between the risk group and the non-risk group in pregnant women with singleton pregnancy. The screening efficiency of NIPT was higher in pregnant women in the risk group, which implies that the clinical application of NIPT is inclined to detect high-risk group. Conclusions: Non-invasive prenatal testing (NIPT) is a rapid and safe screening method with high efficiency. Non-invasive prenatal testing (NIPT) is used for the screening of aneuploidy in twin pregnancy. The efficiency is similar to that of singleton pregnancy, indicating the feasibility of clinical application. However, the efficiency of NIPT screening tends to favor the detection in high-risk groups