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3,109 results on '"Zhang, Junying"'

51. The Late Stage of Abnormal Aging: Dementia

Author

Gao, Shudan, Wang, Yun, Ma, Tao, Zhang, Junying, Crusio, Wim E., Series Editor, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, and Zhang, Zhanjun, editor

Published
2023
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52. The Early Stage of Abnormal Aging: Cognitive Impairment

Author

Shang, Huajie, Xu, Chang, Lu, Hui, Zhang, Junying, Crusio, Wim E., Series Editor, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, and Zhang, Zhanjun, editor

Published
2023
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53. A Study on English Proficiency of University Graduates and Its Influencing Factors Based on the 3E Model

Author

Tang, Chuanlan, Zhang, Junying, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Ying, Loo Fung, editor, Halili, Ts. Dr. Siti Hajar, editor, and Mishra, Deepanjali, editor

Published
2023
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57. Identification and Validation of the SNV Biomarkers Based on Multi-Dimensional Patterns

Author

Li, Bo, Zhang, Junying, and Yu, Liang

Subjects
Quantitative Biology - Quantitative Methods, Quantitative Biology - Genomics
Abstract

Background: Single nucleotide variants (SNVs) are detected as different distributions of DNA samples of distinct types of cancer patients. Even though, it is an exacting task to select the appropriate method to identify cancer to the greatest extent of SNVs. Results: In this paper, we proposed a biomarker concept based on SNV patterns in different feature dimensions. Raw dataset (2761 samples) consisting of twelve different cancers was obtained from TCGA (The Cancer Genome Atlas). After preliminary screening of 562,321 DNA mutation sites in the samples, the mutation sites were extracted and characterized by cancer types in six different SNV feature dimensions. In this study, we found that the extracted features showed similar distribution in the cluster center of the disease type of the samples. After the initial processing of the raw data, the sample was more focused on the subtype distribution of the cancer or the cancer at the SNV level. We used k-nearest neighbors (KNN) to classify the extracted features and Leave-One-Out cross verified them. The accuracy of classifying is stable at around 97% and reached 97.43% at the highest. During the validation phase, we found validated oncogenes in the loci of the features with the highest importance among nine cancers. Conclusions: In summary, the samples showed consistent patterns according to the cancer in which it belongs. It is feasible to classify the cancer of the sample by the distribution of different dimensions of the SNVs and has a high accuracy. And has potential implications for the discovery of cancer-causing genes.

Published
2020

81. High performance selective light absorber based on nickel nanopillar array for photothermal conversion.

Author

Cai, Jianing, Li, Linhao, Chen, Zhao, Zhang, Junying, and Hou, Zhi-Ling

Subjects
PHOTOTHERMAL conversion, PHOTOTHERMAL effect, SOLAR energy conversion, RADIATION absorption, SURFACE plasmon resonance, LIGHT absorption, EMISSIVITY
Abstract

Efficient absorption of solar radiation holds the key to photothermal utilization; however, realizing solar absorber designs with high absorption efficiency remains challenging. Herein, a nickel-based metamaterial selective solar absorber with a nanopillar array structure was proposed to realize nearly perfect optical absorption over a broad spectrum. The average absorbance is up to 96% in the 300–2033 nm wavelength range. Notably, a reasonably detailed analysis of the physical mechanism of the proposed absorber was performed in this paper, attributing the exceptional broadband absorption to the concurrent interaction with surface plasmon resonance, quarter-wavelength resonance, and electric dipole resonance. The absorption efficiency declines significantly when λ > 2.5 μm, with only 20% absorptivity at λ = 6 μm in the radiation-absorbing transition region. This decline is desirable, as it contributes to reducing the emissivity in the mid-infrared range and, therefore, prevents self-radiation. The results demonstrate that the selective absorber possesses the potential to capture solar energy within a broadband, while avoiding undesirable self-radiation, thereby enhancing the integral efficiency of the solar energy conversion system. Moreover, the absorption spectrum shows insensitivity to polarization and angle of incidence. The selective solar absorber proposed here offers excellent performance with a simple structure, showing great promise in the field of photothermal conversion. [ABSTRACT FROM AUTHOR]

Published
2023
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