Design of Ultra-compact Graphene-based Superscatterers

The energy-momentum dispersion relation is a fundamental property of plasmonic systems. In this paper, we show that the method of dispersion engineering can be used for the design of ultra-compact graphene-based superscatterers. Based on the Bohr model, the dispersion relation of the equivalent planar waveguide is engineered to enhance the scattering cross section of a dielectric cylinder. Bohr conditions with different orders are fulfilled in multiple dispersion curves at the same resonant frequency. Thus the resonance peaks from the first and second order scattering terms are overlapped in the deepsubwavelength scale by delicately tuning the gap thickness between two graphene layers. Using this ultra-compact graphene-based superscatterer, the scattering cross section of the dielectric cylinder can be enhanced by five orders of magnitude.Comment: This paper has been accepted by IEEE Journal of Selected topics in Quantum Electronic

Mental health resources and awareness of anxiety and depressive disorders in general hospitals in China

Background: Mental health disorders are common in China. There is a lack of knowledge and resources of mental health in China. Objectives: To assess the levels of psychiatric resources and services in general hospitals in China. Methods: Data regarding psychiatric departments, wards and staff were collected from 57 general hospitals in four provinces of China (Hubei, Zhejiang, Heilongjiang and Yunnan) between April 2014 and June 2014. Questionnaires were distributed to 1,200 non-psychiatric clinicians. Results: Among the 57 hospitals, 50 provided mental health services, 36 had mental health wards, and seven had neither mental health clinics nor wards. The median number of mental health clinicians was six per hospital. The median number of specialized nurses was 42 per hospital. A total of 1,152 non-psychiatric clinicians with a career duration of 9.4 ± 8.9 years returned completed questionnaires. Only 6.9% reported a good understanding of the manifestation of anxiety and depressive disorders, 4.5% reported a good understanding of the diagnostic criteria, and 3.8% reported a good understanding of the treatment protocols. Discussion: There is inadequate awareness of anxiety and depressive disorders among non-psychiatric clinicians in general hospitals in China. This awareness/understanding increased with increasing hospital level

A Weakly Supervised Gas-Path Anomaly Detection Method for Civil Aero-Engines Based on Mapping Relationship Mining of Gas-Path Parameters and Improved Density Peak Clustering

Gas-path anomalies account for more than 90% of all civil aero-engine anomalies. It is essential to develop accurate gas-path anomaly detection methods. Therefore, a weakly supervised gas-path anomaly detection method for civil aero-engines based on mapping relationship mining of gas-path parameters and improved density peak clustering is proposed. First, the encoder-decoder, composed of an attention mechanism and a long short-term memory neural network, is used to construct the mapping relationship mining model among gas-path parameters. The predicted values of gas-path parameters under the restriction of mapping relationships are obtained. The deviation degree from the original values to the predicted values is regarded as the feature. To force the extracted features to better reflect the anomalies and make full use of weakly supervised labels, a weakly supervised cross-entropy loss function under extreme class imbalance is deployed. This loss function can be combined with a simple classifier to significantly improve the feature extraction results, in which anomaly samples are more different from normal samples and do not reduce the mining precision. Finally, an anomaly detection method is deployed based on improved density peak clustering and a weakly supervised clustering parameter adjustment strategy. In the improved density peak clustering method, the local density is enhanced by K-nearest neighbors, and the clustering effect is improved by a new outlier threshold determination method and a new outlier treatment method. Through these settings, the accuracy of dividing outliers and clustering can be improved, and the influence of outliers on the clustering process reduced. By introducing weakly supervised label information and automatically iterating according to clustering and anomaly detection results to update the hyperparameter settings, a weakly supervised anomaly detection method without complex parameter adjustment processes can be implemented. The experimental results demonstrate the superiority of the proposed method

Quantitative Proteomics Analysis of Berberine-Treated Colon Cancer Cells Reveals Potential Therapy Targets

Colon cancer is one of the most lethal malignancies worldwide. Berberine has been found to exert potential anti-colon cancer activity in vitro and in vivo, although the detailed regulatory mechanism is still unclear. This study aims to identify the underlying crucial proteins and regulatory networks associated with berberine treatment of colon cancer by using proteomics as well as publicly available transcriptomics and tissue array data. Proteome profiling of berberine-treated colon cancer cells demonstrated that among 5130 identified proteins, the expression of 865 and 675 proteins were changed in berberine-treated HCT116 and DLD1 cells, respectively. Moreover, 54 differently expressed proteins that overlapped in both cell lines were mainly involved in mitochondrial protein synthesis, calcium mobilization, and metabolism of fat-soluble vitamins. Finally, GTPase ERAL1 and mitochondrial ribosomal proteins including MRPL11, 15, 30, 37, 40, and 52 were identified as hub proteins of berberine-treated colon cancer cells. These proteins have higher transcriptional and translational levels in colon tumor samples than that of colon normal samples, and were significantly down-regulated in berberine-treated colon cancer cells. Genetic dependency analysis showed that silencing the gene expression of seven hub proteins could inhibit the proliferation of colon cancer cells. This study sheds a light for elucidating the berberine-related regulatory signaling pathways in colon cancer, and suggests that ERAL1 and several mitochondrial ribosomal proteins might be promising therapeutic targets for colon cancer