Distinction Between Inflection and Derivation of Learning Reduplication in Mandarin

Reduplication as a word-formation process in Mandarin, which is one of the most difficult knowledge to comprehend for scholar and student. Theoretically this research offers an approach that is different from what has been made by previous researchers. Using the M.D.S Simatupang free context approach this research contrasts the reduplicative forms of all word classes and shows the relationships between them (AA, AABB, ABAB, ABB) and their basic forms (A, AB), then based on test of categorical word and test of lexical decomposition as proposed by J.W.M Verhaar, this study analyzes and explains reduplication and inflectional reduplication in Mandarin in order to students understand as their meaning vocabularies. As a result, this research examines the derivational and inflectional reduplication in Mandarin all at once can disseminate the use of morphological theory. In addition, this study discusses Mandarin reduplication based on various word classes that are contained as a basis for the relevant form of reduplication. Beginner research results will be presented in this study in order to stimulate more complete writing, it will be better if this research can be disseminated in order to add learning and reading material for future research

Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications

This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are further used to adjust the similarity matrix for constrained spectral clustering. Other than the traditional constraint propagation on single-source data, our approach is also extended to more challenging constraint propagation on multi-source data where each pairwise constraint is defined over a pair of data points from different sources. This multi-source constraint propagation has an important application to cross-modal multimedia retrieval. Extensive results have shown the superior performance of our approach.Comment: The short version of this paper appears as oral paper in ECCV 201

Association of Adiponectin SNP+45 and SNP+276 with Type 2 Diabetes in Han Chinese Populations: A Meta-Analysis of 26 Case-Control Studies

Recently, many studies have reported that the SNP+45(T>G) and SNP+276(G>T) polymorphisms in the adiponectin gene are associated with type 2 diabetes (T2DM) in the Chinese Han population. However, the previous studies yielded many conflicting results. Thus, a meta-analysis of the association of the adiponectin gene with T2DM in the Chinese Han population is required. In the current study, we first determined the distribution of the adiponectin SNP+276 polymorphism in T2DM and nondiabetes (NDM) control groups. Our results suggested that the genotype and allele frequencies for SNP+276 did not differ significantly between the T2DM and NDM groups. Then, a meta-analysis of 23 case-control studies of SNP+45, with a total of 4161 T2DM patients and 3709 controls, and 11 case-control studies of SNP+276, with 2533 T2DM patients and 2212 controls, was performed. All subjects were Han Chinese. The fixed-effects model and random-effects model were applied for dichotomous outcomes to combine the results of the included studies. The results revealed a trend towards an increased risk of T2DM for the SNP+45G allele as compared with the SNP+45T allele (OR = 1.34; 95% CI, 1.11–1.62; P<0.01) in the Chinese Han population. However, there was no association between SNP+276 and T2DM (OR = 0.90; 95% CI, 0.73–1.10; P = 0.31). The results of our association study showed there was no association between the adiponectin SNP+276 polymorphism and T2DM in the Yunnan Han population. The meta-analysis results suggested that the SNP+45G allele might be a susceptibility allele for T2DM in the Chinese Han population. However, we did not observe an association between SNP+276 and T2DM

The Genome of Ganderma lucidum Provide Insights into Triterpense Biosynthesis and Wood Degradation

BACKGROUND: Ganoderma lucidum (Reishi or Ling Zhi) is one of the most famous Traditional Chinese Medicines and has been widely used in the treatment of various human diseases in Asia countries. It is also a fungus with strong wood degradation ability with potential in bioenergy production. However, genes, pathways and mechanisms of these functions are still unknown. METHODOLOGY/PRINCIPAL FINDINGS: The genome of G. lucidum was sequenced and assembled into a 39.9 megabases (Mb) draft genome, which encoded 12,080 protein-coding genes and ∼83% of them were similar to public sequences. We performed comprehensive annotation for G. lucidum genes and made comparisons with genes in other fungi genomes. Genes in the biosynthesis of the main G. lucidum active ingredients, ganoderic acids (GAs), were characterized. Among the GAs synthases, we identified a fusion gene, the N and C terminal of which are homologous to two different enzymes. Moreover, the fusion gene was only found in basidiomycetes. As a white rot fungus with wood degradation ability, abundant carbohydrate-active enzymes and ligninolytic enzymes were identified in the G. lucidum genome and were compared with other fungi. CONCLUSIONS/SIGNIFICANCE: The genome sequence and well annotation of G. lucidum will provide new insights in function analyses including its medicinal mechanism. The characterization of genes in the triterpene biosynthesis and wood degradation will facilitate bio-engineering research in the production of its active ingredients and bioenergy

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead