Graph theoretical analysis of functional network for comprehension of sign language

This work was supported by grants from the National Natural Science Foundation of China (NSFC: 31571158, 31170969) and National Key Basic Research Program of China (2014CB846102), and a grant from the National Institutes of Health (R01 DC010997). We thank Yong He and Roel Willems for providing insightful comments to this study and Amie Fairs for proofreading the manuscript. No conflict of interest is declared.Peer reviewedPostprin

Study of stability against deep sliding of gravity dam based on JC method

In this study, stability against deep sliding of gravity dam is analysed in order to provide guidance for ensuring stability against sliding of gravity dam during the construction and operation periods. Based on checking-point method (JC method), the study proposes an analysis model for stability against deep sliding of gravity dams. In addition, the rigid body limit equilibrium method is utilized to construct the limit state function of deep anti-sliding stability. With sliding plane anti-shear friction coefficient and anti-shear cohesion calculated as random variables, safety degree of stability against deep sliding is analysed. With JC method employed, the calculation program is compiled to calculate the stability against deep sliding of gravity dam and analyse the non-overflow section of gravity dam under normal storage level. According to calculation program, the reliability index β of stability against deep sliding of gravity dam is 4.36, and the failure risk Pf is approximately zero. Additionally, based on the traditional rigid body limit equilibrium method, the safety factor K is 3.23, which meets the requirements of the design specification. According to the above methods, stability against deep sliding of the dam section meets the requirement. In conclusion, JC method provides a calculation and analysis model for gravity dam’s stability against deep sliding, serving as references in the design of gravity dams based on reliability theory

Study of stability against deep sliding of gravity dam based on JC method

In this study, stability against deep sliding of gravity dam is analysed in order to provide guidance for ensuring stability against sliding of gravity dam during the construction and operation periods. Based on checking-point method (JC method), the study proposes an analysis model for stability against deep sliding of gravity dams. In addition, the rigid body limit equilibrium method is utilized to construct the limit state function of deep anti-sliding stability. With sliding plane anti-shear friction coefficient and anti-shear cohesion calculated as random variables, safety degree of stability against deep sliding is analysed. With JC method employed, the calculation program is compiled to calculate the stability against deep sliding of gravity dam and analyse the non-overflow section of gravity dam under normal storage level. According to calculation program, the reliability index β of stability against deep sliding of gravity dam is 4.36, and the failure risk Pf is approximately zero. Additionally, based on the traditional rigid body limit equilibrium method, the safety factor K is 3.23, which meets the requirements of the design specification. According to the above methods, stability against deep sliding of the dam section meets the requirement. In conclusion, JC method provides a calculation and analysis model for gravity dam’s stability against deep sliding, serving as references in the design of gravity dams based on reliability theory

An Improved Gradient Boosting Regression Tree Estimation Model for Soil Heavy Metal (Arsenic) Pollution Monitoring Using Hyperspectral Remote Sensing

Hyperspectral remote sensing can be used to effectively identify contaminated elements in soil. However, in the field of monitoring soil heavy metal pollution, hyperspectral remote sensing has the characteristics of high dimensionality and high redundancy, which seriously affect the accuracy and stability of hyperspectral inversion models. To resolve the problem, a gradient boosting regression tree (GBRT) hyperspectral inversion algorithm for heavy metal (Arsenic (As)) content in soils based on Spearman’s rank correlation analysis (SCA) coupled with competitive adaptive reweighted sampling (CARS) is proposed in this paper. Firstly, the CARS algorithm is used to roughly select the original spectral data. Second derivative (SD), Gaussian filtering (GF), and min-max normalization (MMN) pretreatments are then used to improve the correlation between the spectra and As in the characteristic band enhancement stage. Finally, the low-correlation bands are removed using the SCA method, and a subset with absolute correlation values greater than 0.6 is retained as the optimal band subset after each pretreatment. For the modeling, the five most representative characteristic bands were selected in the Honghu area of China, and the nine most representative characteristic bands were selected in the Daye area of China. In order to verify the generalization ability of the proposed algorithm, 92 soil samples from the Honghu and Daye areas were selected as the research objects. With the use of support vector machine regression (SVMR), linear regression (LR), and random forest (RF) regression methods as comparative methods, all the models obtained a good prediction accuracy. However, among the different combinations, CARS-SCA-GBRT obtained the highest precision, which indicates that the proposed algorithm can select fewer characteristic bands to achieve a better inversion effect, and can thus provide accurate data support for the treatment and recovery of heavy metal pollution in soils

Mucoepidermoid carcinoma arising in Warthins tumor of the upper lip: a case report and review

Objective To provide a reference for the diagnosis and treatment of mucoepidermoid carcinoma arising in Warthins tumor of the lip by investigating the diagnosis, treatment and prognosis of the disease. Methods A case of mucoepidermoid carcinoma arising in Warthins tumor of lip was reported, including the clinical manifestation, treat⁃ ment, pathological characteristics and prognosis. The related literature was also reviewed and analyzed. Results A painless mass on the left lip lasting more than one month was found. Resection of the left lip was performed. Pathologi⁃ cal examination showed that the tumor was a hybridoma composed of mucoepidermoid carcinoma and Warthins tumor. There was no recurrence or distant metastasis after 34 months. To date, this type of disease has been rarely reported. Af⁃ ter thorough resection, the prognosis and survival rate are promising in most cases, with no recurrence or metastasis. Conclusion Mucoepidermoid carcinoma in Warthins tumor of the lip is rare. Clinical manifestations, imaging features and histological examination are useful when diagnosing the disease. Thorough resection will reduce the risk of disease recurrence

Role of Structure and Microporosity in Phenanthrene Sorption by Natural and Engineered Organic Matter

Natural sorbents including one humic acid (HA), humins (HMs), nonhydrolyzable carbons (NHCs), and engineered sorbents (biochars) were subject to bleaching to selectively remove a fraction of aromatic C. The structural properties and sorption isotherm data of phenanthrene (Phen) by original and bleached sorbents were obtained. Significant correlations between Phen <i>K</i>_oc values by all sorbents and their organic carbon (OC)-normalized CO₂ cumulative surface area (CO₂–SA/OC) suggested that nanopore-filling mechanism could dominate Phen sorption. After bleaching, natural sorbents still contained large amounts of aromatic C, which are resistant to bleaching, suggesting that they are derived from condensed or nonbiodegradable organic matter (OM). After eliminating the effect of aromatic C remaining in the bleached samples, a general trend of increasing CO₂–SA/OC of natural sorbents with increasing aliphaticity was observed, suggesting that nanopores of natural sorbents are partially derived from their aliphatic moieties. Conversely, positive relationships between CO₂–SA/OC or Phen log<i>K</i>_oc of engineered sorbents and their aromaticity indicated the aromatic structures of engineered sorbents primarily contribute to their nanopores and dominate their sorption of HOCs. Therefore, this study clearly demonstrated that the role of structure and microporosity in Phen sorption is dependent on the sources of sorbents

Characterization of the Expression of the RNA Binding Protein eIF4G1 and Its Clinicopathological Correlation with Serous Ovarian Cancer

<div><p>Background</p><p>Ovarian cancer is the most lethal type of malignant tumor in gynecological cancers and is associated with a high percentage of late diagnosis and chemotherapy resistance. Thus, it is urgent to identify a tumor marker or a molecular target that allows early detection and effective treatment. RNA-binding proteins (RBPs) are crucial in various cellular processes at the post-transcriptional level. The eukaryotic translation initiation factor 4 gamma, 1(eIF4G1), an RNA-binding protein, facilitates the recruitment of mRNA to the ribosome, which is a rate-limiting step during the initiation phase of protein synthesis. However, little is known regarding the characteristics of eIF4G1 expression and its clinical significance in ovarian cancer. Therefore, we propose to investigate the expression and clinicopathological significance of eIF4G1 in ovarian cancer patients.</p><p>Methods</p><p>We performed Real-time PCR in 40 fresh serous ovarian cancer tissues and 27 normal ovarian surface epithelial cell specimens to assess eIF4G1mRNA expression. Immunohistochemistry (IHC) was used to examine the expression of eIF4G1 at the protein level in 134 patients with serous ovarian cancer and 18 normal ovarian tissues. Statistical analysis was conducted to determine the correlation of the eIF4G1 protein levels with the clinicopathological characteristics and prognosis in ovarian cancer.</p><p>Results</p><p>The expression of eIF4G1 was upregulated in serous ovarian cancer tissues at both the mRNA (P = 0.0375) and the protein (P = 0.0007) levels. The eIF4G1 expression was significantly correlated with the clinical tumor stage (P = 0.0004) and omentum metastasis (P = 0.024). Moreover, patients with low eIF4G1 protein expression had a longer overall survival time (P = 0.026).</p><p>Conclusions</p><p>These data revealed that eIF4G1 is markedly expressed in serous ovarian cancer and that upregulation of the eIF4G1 protein expression is significantly associated with an advanced tumor stage. Besides, the patients with lower expression of eIF4G1 tend to have a longer overall survival time. Thus, eIF4G1 may contribute to the occurrence and metastasis of ovarian cancer and can serve as a potential therapeutic target for the treatment of ovarian cancer.</p></div

Associations of cancerous eIF4G1 expression with clinicopathologic characteristics of ovarian cancer.

<p>Associations of cancerous eIF4G1 expression with clinicopathologic characteristics of ovarian cancer.</p

Correlation of eIF4G1 protein expression with clinicopathological stage of ovarian cancer tissues used for eIF4G1 expression analysis.

<p>Immunohistochemical analysis of eIF4G1 with stage I and II of ovarian cancer samples (n = 31) and stage III and IV of ovarian cancer samples (n = 102). P = 0.004.</p