Emigration from China in Comparative Perspective

Comparative research on international migration has increasingly focused on immigrant integration rather than the process of emigration. By investigating the different streams of Chinese migration to the United States and Europe, as well as the different stages of Chinese migration to the United States, this study examines the way in which both receiving and sending contexts combine to shape the process of emigration. Using data from a 2002–2003 survey of emigration from China's Fujian Province, we demonstrate that under restrictive exit and entry policies and high barriers to migration (i.e., clandestine migration from Fuzhou to the United States), resources such as migrant social capital, political capital (cadre resources), and human capital all play a crucial role in the emigration process. However, the roles of these resources in the migration process are limited when migration barriers are sufficiently low and when local governments adopt proactive policies promoting emigration (i.e., legal migration from Mingxi to Europe). Comparisons over time suggest that the importance of migrant social capital, political capital, and human capital has strongly persisted for Fuzhou-US emigration, as a result of tightening exit and entry policies. Despite these marked differences between Fuzhou and Mingxi emigration, the results also point to two general processes that are highly consistent across settings and over time—the cumulative causation of migration and the advantage conferred by traditional positional power (cadre status)

When Mining Electric Locomotives Meet Reinforcement Learning

As the most important auxiliary transportation equipment in coal mines, mining electric locomotives are mostly operated manually at present. However, due to the complex and ever-changing coal mine environment, electric locomotive safety accidents occur frequently these years. A mining electric locomotive control method that can adapt to different complex mining environments is needed. Reinforcement Learning (RL) is concerned with how artificial agents ought to take actions in an environment so as to maximize reward, which can help achieve automatic control of mining electric locomotive. In this paper, we present how to apply RL to the autonomous control of mining electric locomotives. To achieve more precise control, we further propose an improved epsilon-greedy (IEG) algorithm which can better balance the exploration and exploitation. To verify the effectiveness of this method, a co-simulation platform for autonomous control of mining electric locomotives is built which can complete closed-loop simulation of the vehicles. The simulation results show that this method ensures the locomotives following the front vehicle safely and responding promptly in the event of sudden obstacles on the road when the vehicle in complex and uncertain coal mine environments

Glucagon Receptor Antagonism Ameliorates Progression of Heart Failure.

Mice were treated with a fully human monoclonal glucagon receptor antagonistic antibody REMD2.59 following myocardial infarction or pressure overload. REMD2.59 treatment blunted cardiac hypertrophy and fibrotic remodeling, and attenuated contractile dysfunction at 4 weeks after myocardial infarction. In addition, REMD2.59 treatment at the onset of pressure overload significantly suppressed cardiac hypertrophy and chamber dilation with marked preservation of cardiac systolic and diastolic function. Initiation of REMD2.59 treatment 2 weeks after pressure overload significantly blunted the progression of cardiac pathology. These results provide the first in vivo proof-of-concept evidence that glucagon receptor antagonism is a potentially efficacious therapy to ameliorate both onset and progression of heart failure

CSNE: Conditional Signed Network Embedding

Signed networks are mathematical structures that encode positive and negative relations between entities such as friend/foe or trust/distrust. Recently, several papers studied the construction of useful low-dimensional representations (embeddings) of these networks for the prediction of missing relations or signs. Existing embedding methods for sign prediction generally enforce different notions of status or balance theories in their optimization function. These theories, however, are often inaccurate or incomplete, which negatively impacts method performance. In this context, we introduce conditional signed network embedding (CSNE). Our probabilistic approach models structural information about the signs in the network separately from fine-grained detail. Structural information is represented in the form of a prior, while the embedding itself is used for capturing fine-grained information. These components are then integrated in a rigorous manner. CSNE's accuracy depends on the existence of sufficiently powerful structural priors for modelling signed networks, currently unavailable in the literature. Thus, as a second main contribution, which we find to be highly valuable in its own right, we also introduce a novel approach to construct priors based on the Maximum Entropy (MaxEnt) principle. These priors can model the \emph{polarity} of nodes (degree to which their links are positive) as well as signed \emph{triangle counts} (a measure of the degree structural balance holds to in a network). Experiments on a variety of real-world networks confirm that CSNE outperforms the state-of-the-art on the task of sign prediction. Moreover, the MaxEnt priors on their own, while less accurate than full CSNE, achieve accuracies competitive with the state-of-the-art at very limited computational cost, thus providing an excellent runtime-accuracy trade-off in resource-constrained situations

Panax Quinquefolius Saponin of Stem and Leaf Attenuates Intermittent High Glucose-Induced Oxidative Stress Injury in Cultured Human Umbilical Vein Endothelial Cells via PI3K/Akt/GSK-3 β

Panax quinquefolius saponin of stem and leaf (PQS), the effective parts of American ginseng, is widely used in China as a folk medicine for diabetes and cardiovascular diseases treatment. In our previous studies, we have demonstrated that PQS could improve the endothelial function of type II diabetes mellitus (T2DM) rats with high glucose fluctuation. In the present study, we investigated the protective effects of PQS against intermittent high glucose-induced oxidative damage on human umbilical vein endothelial cells (HUVECs) and the role of phosphatidylinositol 3-kinase kinase (PI3K)/Akt/GSK-3β pathway involved. Our results suggested that exposure of HUVECs to a high glucose concentration for 8 days showed a great decrease in cell viability accompanied by marked MDA content increase and SOD activity decrease. Moreover, high glucose significantly reduced the phosphorylation of Akt and GSK-3β. More importantly, these effects were even more evident in intermittent high glucose condition. PQS treatment significantly attenuated intermittent high glucose-induced oxidative damage on HUVECs and meanwhile increased cell viability and phosphorylation of Akt and GSK-3β of HUVECs. Interestingly, all these reverse effects of PQS on intermittent high glucose-cultured HUVECs were inhibited by PI3K inhibitor LY294002. These findings suggest that PQS attenuates intermittent-high-glucose-induced oxidative stress injury in HUVECs by PI3K/Akt/GSK-3β pathway

Long-Term Exposure of Fine Particulate Matter Causes Hypertension by Impaired Renal D1 Receptor-Mediated Sodium Excretion via Upregulation of G-Protein-Coupled Receptor Kinase Type 4 Expression in Sprague-Dawley Rats.

BACKGROUND: Epidemiological evidence supports an important association between air pollution exposure and hypertension. However, the mechanisms are not clear. METHODS AND RESULTS: Our present study found that long-term exposure to fine particulate matter (PM2.5) causes hypertension and impairs renal sodium excretion, which might be ascribed to lower D1 receptor expression and higher D1 receptor phosphorylation, accompanied with a higher G-protein-coupled receptor kinase type 4 (GRK4) expression. The in vivo results were confirmed in in vitro studies (ie, PM2.5 increased basal and decreased D1 receptor mediated inhibitory effect on Na+-K+ ATPase activity, decreased D1 receptor expression, and increased D1 receptor phosphorylation in renal proximal tubule cells). The downregulation of D1 receptor expression and function might be attributable to a higher GRK4 expression after the exposure of renal proximal tubule cells to PM2.5, because downregulation of GRK4 by small-interfering RNA reversed the D1 receptor expression and function. Because of the role of reactive oxygen species on D1 receptor dysfunction and its relationship with air pollution exposure, we determined plasma reactive oxygen species and found the levels higher in PM2.5-treated Sprague-Dawley rats. Inhibition of reactive oxygen species by tempol (4-hydroxy-2,2,6,6-tetramethylpiperidin-1-oxyl) reduced blood pressure and increased sodium excretion in PM2.5-treated Sprague-Dawley rats, accompanied by an increase in the low D1 receptor expression, and decreased the hyperphosphorylated D1 receptor and GRK4 expression. CONCLUSIONS: Our present study indicated that long-term exposure of PM2.5 increases blood pressure by decreasing D1 receptor expression and function; reactive oxygen species, via regulation of GRK4 expression, plays an important role in the pathogenesis of PM2.5-induced hypertension

Mutation of brain aromatase disrupts spawning behavior and reproductive health in female zebrafish

Aromatase (Cyp19a1) is the steroidogenic enzyme that converts androgens into bioactive estrogens, and hence is in a pivotal position to mediate reproduction and sexual behavior. In teleosts, there are two aromatase paralogs: cyp19a1a that is highly expressed in granulosa and Leydig cells in the gonads with critical function in sexual differentiation of the ovary, and cyp19a1b that is highly expressed in radial glial cells in the brain with unknown roles in reproduction. Cyp19a1-/- mutant zebrafish lines were used to investigate the importance of the cyp19a1 paralogs for spawning behavior and offspring survival and early development. Mutation of cyp19a1b was found to increase the latency to the first oviposition in females. Mutation of cyp19a1b in females also increased the number of eggs spawned; however, significantly more progeny died during early development resulting in no net increase in female fecundity. This finding suggests a higher metabolic cost of reproduction in cyp19a1b-/- mutant females. In males, the combined mutation of both cyp19a1 paralogs resulted in significantly lower progeny survival rates, indicating a critical function of cyp19a1 during early larval development. These data establish the specific importance of cyp19a1b for female spawning behavior and the importance of the cyp19a1 paralogs for early larval survival