A Multimodal Analysis of Advertisement of Online Marketplace Shopee

High human mobility demands the world of commerce to be able to provide services and goods quickly according to consumer demand. To overcome this phenomenon, now appears transactions that use the internet media to connect producers and consumers known as online marketplace. This research studies the advertisement in online marketplace named Shopee by using multimodal analysis. Shopee is an online marketplace app for buying and selling on mobile phones with ease and quickly offering a wide range of products. This research deals with linguistic and visual analysis. This research is focused on the function of the advertisement realized in the offer goods for buyers interested to see and buy that found and dominates in the online marketplace named Shopee. Multimodal analysis method that is used in the research is text verbal analysis theory in language metafunction such as ideational, interpersonal, and textual metafunction by Halliday (1994), while visual text using multimodal analysis by Kress and Van Leuwen (1996, 2006) and Cheong (2004). The result of multimodal analysis of advertisement of online marketplace Shopee is described in linguistic and visual analysis.   Keywords: multimodal, metafunctions of language, advertisement, Shope

An overview of the Global Burden of Disease Study 2016 Results

This report explores the progress Portugal has experienced over the last 26 years, in terms of health, well-being, and development, and the new challenges it faces as its population grows and ages. This report provides information about the diseases and injuries that prevent Portuguese from living long and healthy lives. It also sheds light on risk factors that contribute to poor health. Finally, the report presents a country view with regard to the Sustainable Development Goals in 1990 and prospectively in 2030, and compares Portugal’s health performance to that of peer countries.info:eu-repo/semantics/publishedVersio

Expert consensus guidelines for the genetic diagnosis of Alport syndrome

Recent expert guidelines recommend genetic testing for the diagnosis of Alport syndrome. Here, we describe current best practice and likely future developments. In individuals with suspected Alport syndrome, all three COL4A5, COL4A3 and COL4A4 genes should be examined for pathogenic variants, probably by high throughput-targeted next generation sequencing (NGS) technologies, with a customised panel for simultaneous testing of the three Alport genes. These techniques identify up to 95% of pathogenic COL4A variants. Where causative pathogenic variants cannot be demonstrated, the DNA should be examined for deletions or insertions by re-examining the NGS sequencing data or with multiplex ligation-dependent probe amplification (MLPA). These techniques identify a further 5% of variants, and the remaining few changes include deep intronic splicing variants or cases of somatic mosaicism. Where no pathogenic variants are found, the basis for the clinical diagnosis should be reviewed. Genes in which mutations produce similar clinical features to Alport syndrome (resulting in focal and segmental glomerulosclerosis, complement pathway disorders, MYH9-related disorders, etc.) should be examined. NGS approaches have identified novel combinations of pathogenic variants in Alport syndrome. Two variants, with one in COL4A3 and another in COL4A4, produce a more severe phenotype than an uncomplicated heterozygous change. NGS may also identify further coincidental pathogenic variants in genes for podocyte-expressed proteins that also modify the phenotype. Our understanding of the genetics of Alport syndrome is evolving rapidly, and both genetic and non-genetic factors are likely to contribute to the observed phenotypic variability

Genome-Wide Association Studies of Grain Yield Components in Diverse Sorghum Germplasm

Citation: Boyles, R. E., Cooper, E. A., Myers, M. T., Brenton, Z., Rauh, B. L., Morris, G. P., & Kresovich, S. (2016). Genome-Wide Association Studies of Grain Yield Components in Diverse Sorghum Germplasm. Plant Genome, 9(2), 17. doi:10.3835/plantgenome2015.09.0091Grain yield and its primary determinants, grain number and weight, are important traits in cereal crops that have been well studied; however, the genetic basis of and interactions between these traits remain poorly understood. Characterization of grain yield per primary panicle (YPP), grain number per primary panicle (GNP), and 1000-grain weight (TGW) in sorghum [Sorghum bicolor (L.) Moench], a hardy C-4 cereal with a genome size of similar to 730 Mb, was implemented in a diversity panel containing 390 accessions. These accessions were genotyped to obtain 268,830 single-nucleotide polymorphisms (SNPs). Genome-wide association studies (GWAS) were performed to identify loci associated with each grain yield component and understand the genetic interactions between these traits. Genome-wide association studies identified associations across the genome with YPP, GNP, and TGW that were located within previously mapped sorghum QTL for panicle weight, grain yield, and seed size, respectively. There were no significant associations between GNP and TGW that were within 100 kb, much greater than the average linkage disequilibrium (LD) in sorghum. The identification of nonoverlapping loci for grain number and weight suggests these traits may be manipulated independently to increase the grain yield of sorghum. Following GWAS, genomic regions surrounding each associated SNP were mined for candidate genes. Previously published expression data indicated several TGW candidate genes, including an ethylene receptor homolog, were primarily expressed within developing seed tissues to support GWAS. Furthermore, maize (Zea mays L.) homologs of identified TGW candidates were differentially expressed within the seed between small- and large-kernel lines from a segregating maize population