Capital Normal University

About: Capital Normal University is a education organization based out in Beijing, China. It is known for research contribution in the topics: Terahertz radiation & Quantum entanglement. The organization has 11441 authors who have published 11988 publications receiving 159071 citations. The organization is also known as: Shǒudū Shīfàn Dàxué.

Compositional (km,kn)-Shuffle Conjectures

Abstract: In 2008, Haglund, Morse and Zabrocki formulated a Compositional form of the Shuffle Conjecture of Haglund et al. In very recent work, Gorsky and Negut by combining their discoveries with the work of Schiffmann-Vasserot on the symmetric function side and the work of Hikita and Gorsky-Mazin on the combinatorial side, were led to formulate an infinite family of conjectures that extend the original Shuffle Conjecture of Haglund et al. In fact, they formulated one conjecture for each pair (m,n) of coprime integers. This work of Gorsky-Negut leads naturally to the question as to where the Compositional Shuffle Conjecture of Haglund-Morse-Zabrocki fits into these recent developments. Our discovery here is that there is a compositional extension of the Gorsky-Negut Shuffle Conjecture for each pair (km,kn), with (m,n) co-prime and k > 1.

An integrated assessment of the impact of precipitation and groundwater on vegetation growth in arid and semiarid areas

Abstract: Increased demand for water resources together with the influence of climate change has degraded water conditions which support vegetation in many parts of the world, especially in arid and semiarid areas. This study develops an integrated framework to assess the impact of precipitation and groundwater on vegetation growth in the Xiliao River Plain of northern China. The integrated framework systematically combines remote sensing technology with water flow modeling in the vadose zone and field data analysis. The vegetation growth is quantitatively evaluated with the remote sensing data by the normalized difference vegetation index (NDVI) and the simulated plant water uptake rates. The correlations among precipitation, groundwater depth and NDVI are investigated using Pearson correlation equations. The results provide insights for understanding interactions between precipitation and groundwater and their contributions to vegetation growth. Strong correlations between groundwater depth, plant water uptake and NDVI are found in parts of the study area during a ten-year drought period. The numerical modeling results indicate that there is an increased correlation between the groundwater depth and vegetation growth and that groundwater significantly contributes to sustaining effective soil moisture for vegetation growth during the long drought period. Therefore, a decreasing groundwater table might pose a great threat to the survival of vegetation during a long drought period.

Lower bounds of concurrence for tripartite quantum systems

Abstract: We derive an analytical lower bound for the concurrence of tripartite quantum mixed states. A functional relation is established relating concurrence and the generalized partial transpositions.

Comparative Phosphoproteome Analysis of the Developing Grains in Bread Wheat (Triticum aestivum L.) under Well-Watered and Water-Deficit Conditions

Abstract: Wheat (Triticum aestivum), one of the most important cereal crops, is often threatened by drought. In this study, water deficit significantly reduced the height of plants and yield of grains. To explore further the effect of drought stress on the development and yield of grains, we first performed a large scale phosphoproteome analysis of developing grains in wheat. A total of 590 unique phosphopeptides, representing 471 phosphoproteins, were identified under well-watered conditions. Motif-X analysis showed that four motifs were enriched, including [sP], [Rxxs], [sDxE], and [sxD]. Through comparative phosphoproteome analysis between well-watered and water-deficit conditions, we found that 63 unique phosphopeptides, corresponding to 61 phosphoproteins, showed significant changes in phosphorylation level (≥2-fold intensities). Functional analysis suggested that some of these proteins may be involved in signal transduction, embryo and endosperm development of grains, and drought response and defense under water-deficit conditions. Moreover, we also found that some chaperones may play important roles in protein refolding or degradation when the plant is subjected to water stress. These results provide a detailed insight into the stress response and defense mechanisms of developmental grains at the phosphoproteome level. They also suggested some potential candidates for further study of transgenosis and drought stress as well as incorporation into molecular breeding for drought resistance.

Identification of metabolic biomarkers in patients with type 2 diabetic coronary heart diseases based on metabolomic approach.

Abstract: Type 2 diabetic coronary heart disease (T2DM-CHD) is a kind of serious and complex disease. Great attention has been paid to exploring its mechanism; however, the detailed understanding of T2DM-CHD is still limited. Plasma samples from 15 healthy controls, 13 coronary heart disease (CHD) patients, 15 type 2 diabetes mellitus (T2DM) patients and 28 T2DM-CHD patients were analyzed in this research. The potential biomarkers of CHD and T2DM were detected and screened out by (1)H NMR-based plasma metabolic profiling and multivariate data analysis. About 11 and 12 representative metabolites of CHD and T2DM were identified respectively, mainly including alanine, arginine, proline, glutamine, creatinine and acetate. Then the diagnostic model was further constructed based on the previous metabolites of CHD and T2DM to detect T2DM-CHD with satisfying sensitivity of 92.9%, specificity of 93.3% and accuracy of 93.2%, validating the robustness of (1)H NMR-based plasma metabolic profiling to diagnostic strategy. The results demonstrated that the NMR-based metabolomics approach processed good performance to identify diagnostic plasma biomarkers and most identified metabolites related to T2DM and CHD could be considered as predictors of T2DM-CHD as well as the therapeutic targets for prevention, which provided new insight into diagnosing and forecasting of complex diseases.