Unsupervised Semantic Representation Learning of Scientific Literature Based on Graph Attention Mechanism and Maximum Mutual Information

Since most scientific literature data are unlabeled, this makes unsupervised graph-based semantic representation learning crucial. Therefore, an unsupervised semantic representation learning method of scientific literature based on graph attention mechanism and maximum mutual information (GAMMI) is proposed. By introducing a graph attention mechanism, the weighted summation of nearby node features make the weights of adjacent node features entirely depend on the node features. Depending on the features of the nearby nodes, different weights can be applied to each node in the graph. Therefore, the correlations between vertex features can be better integrated into the model. In addition, an unsupervised graph contrastive learning strategy is proposed to solve the problem of being unlabeled and scalable on large-scale graphs. By comparing the mutual information between the positive and negative local node representations on the latent space and the global graph representation, the graph neural network can capture both local and global information. Experimental results demonstrate competitive performance on various node classification benchmarks, achieving good results and sometimes even surpassing the performance of supervised learning

QKI is a critical pre-mRNA alternative splicing regulator of cardiac myofibrillogenesis and contractile function

The RNA-binding protein QKI belongs to the hnRNP K-homology domain protein family, a well-known regulator of pre-mRNA alternative splicing and is associated with several neurodevelopmental disorders. Qki is found highly expressed in developing and adult hearts. By employing the human embryonic stem cell (hESC) to cardiomyocyte differentiation system and generating QKI-deficient hESCs (hESCs-QKIdel) using CRISPR/Cas9 gene editing technology, we analyze the physiological role of QKI in cardiomyocyte differentiation, maturation, and contractile function. hESCs-QKIdel largely maintain normal pluripotency and normal differentiation potential for the generation of early cardiogenic progenitors, but they fail to transition into functional cardiomyocytes. In this work, by using a series of transcriptomic, cell and biochemical analyses, and the Qki-deficient mouse model, we demonstrate that QKI is indispensable to cardiac sarcomerogenesis and cardiac function through its regulation of alternative splicing in genes involved in Z-disc formation and contractile physiology, suggesting that QKI is associated with the pathogenesis of certain forms of cardiomyopathies

Blocking Mammalian Target of Rapamycin (mTOR) Attenuates HIF-1α Pathways Engaged-Vascular Endothelial Growth Factor (VEGF) in Diabetic Retinopathy

Background/Aims: Prior studies demonstrate that hypoxia inducible factor subtype 1α (HIF-1α) in retinal tissues is involved in development of diabetic retinopathy (DR). In this report, we particularly examined the role played by mammalian target of rapamycin (mTOR) in regulating expression of HIF-1α and its downstream pathway, namely vascular endothelial growth factor (VEGF). Methods: Streptozotocin (STZ) was systemically injected to induce hyperglycemia in rats. ELISA and Western Blot analysis were employed to determine the levels of HIF-1α and VEGF as well as expression of mTOR pathways in retinal tissues of control rats and STZ rats. Results: Our results show that HIF-1α and VEGF as well as VEGF receptor subtype 2 (VEGFR-2) were increased in STZ rats. Also, the protein expression of p-mTOR, mTOR-mediated phosphorylation of 4E-binding protein 4 (4E-BP1), p70 ribosomal S6 protein kinase 1 (S6K1) pathways were amplified in diabetic retina compared with controls. Blocking mTOR by using rapamycin significantly attenuated activities of HIF-1α and VEGF signaling pathways. Conclusion: Our data for the first time revealed specific signaling pathways engaged in the development of DR, including the activation of mTOR and HIF-1α -VEGF mechanism. Targeting one or more of these signaling molecules may present new opportunities for treatment and management of DR often observed in clinics

An Urban Scaling Estimation Method in a Heterogeneity Variance Perspective

Urban scaling laws describe powerful universalities of the scaling relationships between urban attributes and the city size across different countries and times. There are still challenges in precise statistical estimation of the scaling exponent; the properties of variance require further study. In this paper, a statistical regression method based on the maximum likelihood estimation considering the lower bound constraints and the heterogeneous variance of error structure, termed as CHVR, is proposed for urban scaling estimation. In the CHVR method, the heterogeneous properties of variance are explored and modeled in the form of a power-of-the-mean variance model. The maximum likelihood fitting method is supplemented to satisfy the lower bound constraints in empirical data. The CHVR method has been applied to estimating the scaling exponents of six urban attributes covering three scaling regimes in China and compared with two traditional methods. Method evaluations based on three different criteria validate that compared with both classical methods, the CHVR method is more effective and robust. Moreover, a statistical test and long-term variations of the parameter in the variance function demonstrate that the proposed heterogeneous variance function can not only describe the heterogeneity in empirical data adequately but also provide more meaningful urban information. Therefore, the CHVR method shows great potential to provide a valuable tool for effective urban scaling studies across the world and be applied to scaling law estimation in other complex systems in the future

Defect-induced efficient dry reforming of methane over two-dimensional Ni/h-boron nitride nanosheet catalysts

Efficient enhancement of catalytic stability and coke-resistance is a crucial aspect for dry reforming of methane. Here, we report Ni nanoparticles embedded on vacancy defects of hexagonal boron nitride nanosheets (Ni/h-BNNS) can optimize catalytic performance by taming two-dimensional (2D) interfacial electronic effects. Experimental results and density functional theory calculations indicate that surface engineering on defects of Ni/h-BNNS catalyst can strongly influence metal-support interaction via electron donor/acceptor mechanisms and favor the adsorption and catalytic activation of CH4 and CO2. The Ni/h-BNNS catalyst exhibits superior catalytic performance during a 120 h durability test. Furthermore, in situ techniques further reveal possible recovery mechanism of the active Ni sites, identifying the enhanced catalytic activities of the Ni/h-BNNS catalyst. This work highlights promotional mechanism of defect-modified interface and should be equally applicable for design of thermochemically stable catalysts

Managing facial infiltrating lipomatosis associated with PIK3CA mutation: From surgery to targeted therapy

Facial infiltrating lipomatosis (FIL) is a congenital asymmetrical deformity of the maxillofacial region that can significantly affect a patient’s facial appearance and function. With the development of sequencing technologies, PIK3CA mutations are considered among the potential etiologies of FIL. The management and treatment of FIL involves plastic surgery; more recently, an improved understanding of its pathogenesis has given rise to new treatment options, including targeted therapy. Here we report the clinical data of two patients diagnosed with FIL and present current curative concepts

Numerical calculation of the lightning transient voltage distribution on converter transformer winding based a dual winding model

The insulation co-ordination of converter transformer winding has a great influence on power system security. An equivalent circuit of a 500 kV converter transformer winding structure, including a LC equivalent network circuit and an ideal transformer in parallel, was firstly established. A combined 12-pulse rectifier equivalent circuit model, mainly consisting of six single-phase converter transformer and 12 converter valves, was built in Power Systems Computer Aided Design (PSCAD) software. In certain operating states of the converter value, the transient voltage distribution was analysed when lightning strokes the DC bus of a typical converter station. The results show that the dual winding model can present the transient voltage characteristics of the converter transformer. The maximum lightning transient voltage is located at the end of the star-connected winding near the neutral point and reaches 1270 kV, and also the maximum gradient voltage occurs at the winding near the terminal point. In different operating states for the converter valve, the transient voltages of a three-phase winding behave as per the similar distributing rules. For the star-connected phase winding, the lightning transient voltage of the winding disc reaches the maximum magnitude when lightning strike occurs at the peak of the phase voltage on the valve side

Exploring the Direct Rebound Effect of Energy Consumption: A Case Study

Technological innovation plays a crucial role for improving energy efficiency. But the excessive energy consumption has presented a significant challenge at the same time, which indicates that the direct energy rebound effect exists in China. Cobb-Douglas production function and Logarithmic Mean Divisia Index decomposition model are employed to analyze the rebound effect of energy consumption of all three main industries sector in China. The results show that total technological effect curve and total substitution effect curve fluctuated more significantly than total structure effect curve from 1991 to 2014.The first two curves were the most critical factors for the energy consumption intensity. Stabilizing energy prices, developing new and renewable energy and implementing policies related to energy conservation and emission reduction are effective measures to reduce energy consumption intensity. More attention should be paid to the growing demand for living energy consumption derived from the rapid development of the tertiary industry. The direct rebound effect of energy consumption in China showed an overall descending trend. This shows that technological effect has well prevented the growth of energy consumption. Direct energy rebound effect can be controlled effectively by means of formulating and implementing the corresponding energy related policies