Fabrication and microstructural characterization of silica aerogel by aging additional pressurization

SiO2 aerogel with Light-weight and low thermal conductivity is a promising candidate for thermal insulator used for aerospace vehicles. In this paper, we report the preparation and microstructural characterization of SiO2 aerogel by aging pressurization using supercritical drying method. The results showed that the aging pressurization can rapid increase the bulk density from 0.1g/cm3 to 0.45g/cm3 with the pressure changing from 200Pa to 600Pa. When the pressure increases to 800Pa, the density was increased to 0.46g/cm3 slowly. Further polycondensation is driven by the increasing of contact area between skeleton particles when the aging pressure increased. The grid structure became densification and saturation when the aging pressure approached 800Pa. SEM method gives the evidence of increase of aging pressure, which can help to increase the size of secondary grains. Nitrogen sorption-desorption measurements exhibit an unimodal pore distribution and low specific area and porosity with the increase of aging pressure. Real density test showed that the bulk density increased by pressure. Bulk density, gain size and pore structure distribution can be controlled effectively by aging pressurization

Stanniocalcin 2 Ameliorates Hepatosteatosis Through Activation of STAT3 Signaling

Stanniocalcin 2 (STC2), a secreted glycoprotein hormone, regulates many biological processes, including cell proliferation, apoptosis, tumorigenesis, and atherosclerosis. However, its role in hepatic triglyceride metabolism remains unknown. In the present study, we found that expression levels of STC2 were significantly reduced in the livers of leptin-deficient and high fat diet-induced obese mice. Systemic administration of STC2 recombinant protein or adenovirus-mediated overexpression of STC2 markedly attenuated hepatosteatosis and hypertriglyceridemia in obese mice. At the molecular level, we found that STC2 activated the STAT3 signaling pathway to inhibit lipogenic gene expression. Consistently, in vitro studies further showed that inhibition of STAT3 signaling abolished the anti-steatotic effects of STC2. Together, our results revealed an important role of STC2 in the regulation of hepatic triglyceride metabolism, which might provide a potential therapeutic target for the treatment of fatty liver and related metabolic disorders

Multi-Task Recommendations with Reinforcement Learning

In recent years, Multi-task Learning (MTL) has yielded immense success in Recommender System (RS) applications. However, current MTL-based recommendation models tend to disregard the session-wise patterns of user-item interactions because they are predominantly constructed based on item-wise datasets. Moreover, balancing multiple objectives has always been a challenge in this field, which is typically avoided via linear estimations in existing works. To address these issues, in this paper, we propose a Reinforcement Learning (RL) enhanced MTL framework, namely RMTL, to combine the losses of different recommendation tasks using dynamic weights. To be specific, the RMTL structure can address the two aforementioned issues by (i) constructing an MTL environment from session-wise interactions and (ii) training multi-task actor-critic network structure, which is compatible with most existing MTL-based recommendation models, and (iii) optimizing and fine-tuning the MTL loss function using the weights generated by critic networks. Experiments on two real-world public datasets demonstrate the effectiveness of RMTL with a higher AUC against state-of-the-art MTL-based recommendation models. Additionally, we evaluate and validate RMTL's compatibility and transferability across various MTL models.Comment: TheWebConf202

Genome-Wide Association Studies for Dynamic Plant Height and Number of Nodes on the Main Stem in Summer Sowing Soybeans

Plant height (PH) and the number of nodes on the main stem (NN) serve as major plant architecture traits affecting soybean seed yield. Although many quantitative trait loci for the two traits have been reported, their genetic controls at different developmental stages in soybeans remain unclear. Here, 368 soybean breeding lines were genotyped using 62,423 single nucleotide polymorphism (SNP) markers and phenotyped for the two traits at three different developmental stages over two locations in order to identify their quantitative trait nucleotides (QTNs) using compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM) approaches. As a result, 11 and 13 QTNs were found by CMLM to be associated with PH and NN, respectively. Among these QTNs, 8, 3, and 4 for PH and 6, 6, and 8 for NN were found at the three stages, and 3 and 6 were repeatedly detected for PH and NN. In addition, 34 and 30 QTNs were found by mrMLM to be associated with PH and NN, respectively. Among these QTNs, 11, 13, and 16 for PH and 11, 15, and 8 for NN were found at the three stages. A majority of these QTNs overlapped with the previously reported loci. Moreover, one QTN within the known E2 locus for flowering time was detected for the two traits at all three stages, and another that overlapped with the Dt1 locus for stem growth habit was also identified for the two traits at the mature stage. This may explain the highly significant correlation between the two traits. Our findings provide evidence for mixed major plus polygenes inheritance for dynamic traits and an extended understanding of their genetic architecture for molecular dissection and breeding utilization in soybeans

Elevated Serum Growth Differentiation Factor 15 Levels in Hyperthyroid Patients

Background: Recent studies have shown that growth differentiation factor 15 (GDF15), a member of the transforming growth factor-β (TGF-β)/bone morphogenetic protein (BMP) superfamily, plays an important role in appetite, type 2 diabetes, and cardiovascular diseases. Since thyroid hormone has pleiotropic effects on whole-body energy metabolism, we aimed to explore the effect of thyroid hormone on circulating GDF15 levels in humans and GDF15 genes expression in C57BL/6 mice.Methods: A total of 134 hyperthyroid patients and 105 healthy subjects were recruited. Of them, 43 hyperthyroid patients received thionamide treatment for 3 months until euthyroidism. Serum GDF15 levels were determined using the enzyme-linked immunosorbent assay (ELISA) method. To determine the source for the increased circulating GDF15, C57BL/6 mice were treated with T3, and GDF15 gene expressions in the liver, skeletal muscle, brown adipose tissue (BAT), inguinal white adipose tissue (iWAT), epididymal white adipose tissue (eWAT) were analyzed by quantitative real-time polymerase chain reaction (PCR).Results: Serum GDF15 levels were significantly elevated in hyperthyroid patients as compared with healthy subjects (326.06 ± 124.13 vs. 169.24 ± 82.96 pg/mL; P < 0.001). After thionamide treatment, GDF15 levels in hyperthyroid patients declined markedly from 293.27 ± 119.49 to 118.10 ± 71.83 pg/mL (P < 0.001). After adjustment for potential confounders, serum GDF15 levels were independently associated with hyperthyroidism. T3 treatment increased GDF15 expression in the brown adipose tissue of C57BL/6 mice.Conclusions: Serum GDF15 levels were elevated in patients with hyperthyroidism and declined after thionamide treatment. Thyroid hormone treatment upregulated GDF15 expression in mice. Therefore, our results present the clinical relevance of GDF15 in humans under the condition of hyperthyroidism

Etching Phosphate Glass-Ceramic with Phosphoric Acid to the Recyclable Synthesis of Porous Materials

HCl, H2SO4, or HNO3 was traditionally used to selectively etch phosphate glass-ceramic to form porous skeleton materials. Herein, the feasibility of using H3PO4 to etch phosphate-based glass ceramics was confirmed. The innovative selection of H3PO4 as the etching medium made the waste solution generated during the etching process fully recyclable in the material reproduction. The composition, crystallization, microstructure, and performance of the glass synthesized with the collected waste etching solution as well as the resultant glass-ceramic and the final porous material were fully compared with those of the originally prepared one using pure H3PO4 reagent as the starting raw material. This study not only provides a protocol to eliminate the release of wastewater in the chemical etching route but also to save valuable resources for material synthesis. Moreover, the resynthesized porous material has a larger surface area and thus better adsorption and photocatalytic efficiencies than the originally synthesized one

Research on Extraction Method of Financial Knowledge Based on How Net

In order to obtain the knowledge information of financial texts more efficiently and make the extracted information such as entity relation attribute more accurate, this paper studies the grammatical features of financial news texts and the semantic features of How Net, and puts forward the scheme of financial information extraction based on How Net. First, the phrase matching is carried out in the dictionary. Then the neural network is used for weighting, BiLSTM is used for character vector feature enhancement training, and then conditional random field (CRF) is used to complete named entity recognition, and then the relationship extraction of entity pairs from the dependency syntax is carried out to complete the research on the construction method of knowledge extraction of text in the financial field. The experimental results show that this model is superior to the other three models in entity recognition, and the overall performance is improved by about 1.2%. In relation extraction, the accuracy and recall rate of the model algorithm adopted in this paper are improved by 5% and 1.5% respectively, which shows that the improvement of the algorithm is effective

Multisource Data-Driven Modeling Method for Estimation of Intercity Trip Distribution

Traditional intercity trip distribution modeling methods are merely derived from household travel survey due to its limitation to partial or inaccurate information. With the development of information construction, reliable historical data can be easily collected from different sources, such as sensor and statistical data. In this study, a data-driven method based on Poisson distribution theory is proposed to estimate intercity trip distribution using sensor data and various city features. A Poisson model, which reveals the deep correlation between city feature variables and trip distribution, is initially formulated. The L1-norm approach and the coordinate descent algorithm are then adopted in selecting related features and estimating model parameters, respectively, to reduce the complexity of the model. Finally, a k-means clustering method is used to analyze the latent correlation between city features and improve the availability of the model. The methodology is tested on a realistic dataset containing the highway trips of 17 cities in Shandong Province, China. The city feature variables have 66 dimensions, including economic index and population indicator. In comparison with traditional gravity model, which regards population as the most important factor affecting city attraction, our result shows that one of the core positive factors is the economic feature, such as gross regional domestic product. Moreover, the dimension of city features in the developed model decreases from 66 to 13 dimensions. The model developed in this study performs well in replicating the observed intercity origin-destination matrix