Variants of the low oxygen sensors EGLN1 and HIF-1AN associated with acute mountain sickness.

Two low oxygen sensors, Egl nine homolog 1 (EGLN1) and hypoxia-inducible factor 1-α inhibitor (HIF-1AN), play pivotal roles in the regulation of HIF-1α, and high altitude adaption may be involved in the pathology of acute mountain sickness (AMS). Here, we aimed to analyze single nucleotide polymorphisms (SNPs) in the untranslated regions of the EGLN1 and HIF-1AN genes and SNPs chosen from a genome-wide adaptation study of the Han Chinese population. To assess the association between EGLN1 and HIF-1AN SNPs and AMS in a Han Chinese population, a case-control study was performed including 190 patients and 190 controls. In total, thirteen SNPs were genotyped using the MassARRAY® MALDI-TOF system. Multiple genetic models were tested; The Akaike's information criterion (AIC) and Bayesian information criterion (BIC) values indicated that the dominant model may serve as the best-fit model for rs12406290 and rs2153364 of significant difference. However, these data were not significant after Bonferroni correction. No significant association was noted between AMS and rs12757362, rs1339894, rs1361384, rs2009873, rs2739513 or rs2486729 before and after Bonferroni correction. Further haplotype analyses indicated the presence of two blocks in EGLN1; one block consists of rs12406290-rs2153364, located upstream of the EGLN1 gene. Carriers of the "GG" haplotype of rs12406290-rs2153364 exhibited an increased risk of AMS after adjustments for age and smoking status. However, no significant association was observed among HIF-1AN 3'-untranslated region (3'-UTR) polymorphisms, haplotype and AMS. Our study indicates that variants in the EGLN1 5'-UTR influence the susceptibility to AMS in a Han Chinese population

The Financial Deepening-Productivity Nexus in China: 1987-2001

The financial intermediation-growth nexus is a widely studied topic in the literature of development economics. Deepening financial intermediation may promote economic growth by mobilizing more investments, and lifting returns to financial resources, which raises productivity. Relying on provincial panel data from China, this paper attempts to examine if regional productivity growth is accounted for by the deepening process of financial development. Towards this end, an appropriate measurement of financial depth is constructed and then included as a determinant of productivity growth. It finds that a significant and positive nexus exists between financial deepening and productivity growth. Given the divergent pattern of financial deepening between coastal and inland provinces, this finding also helps explain the rising regional disparity in China.growth, financial development, productivity, China

Spin Correlations in top quark pair production near threshold at the e−e+ e^- e^+ Linear Collider

We investigate the spin correlations in top quark pair production near threshold at the $e^- e^+$ linear collider. Comparing with the results above the threshold region, we find that near the threshold region the off-diagonal basis, the optimized decomposition of the top quark spins above the threshold region, does not exist, and the beamline basis is the optimal basis, in which there are the dominant spin components: the up-down (UD) component for $e_L^- e^+$ scattering and the down-up (DU) component for $e_R^- e^+$ scattering can make up more than 50% of the total cross section, respectively.Comment: 12 pages, 3 figures, minor modification

Robot eye-hand coordination learning by watching human demonstrations: a task function approximation approach

We present a robot eye-hand coordination learning method that can directly learn visual task specification by watching human demonstrations. Task specification is represented as a task function, which is learned using inverse reinforcement learning(IRL) by inferring differential rewards between state changes. The learned task function is then used as continuous feedbacks in an uncalibrated visual servoing(UVS) controller designed for the execution phase. Our proposed method can directly learn from raw videos, which removes the need for hand-engineered task specification. It can also provide task interpretability by directly approximating the task function. Besides, benefiting from the use of a traditional UVS controller, our training process is efficient and the learned policy is independent from a particular robot platform. Various experiments were designed to show that, for a certain DOF task, our method can adapt to task/environment variances in target positions, backgrounds, illuminations, and occlusions without prior retraining.Comment: Accepted in ICRA 201