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Jianji Dong, Ting Yang, Aoling Zheng, and Xinliang Zhang Huazhong University of Science and Technology Wuhan, China Jianji Dong received his PhD in 2008 and is currently a professor in Wuhan National Lab ... Yang, X. Xiao, Q. Yang, X. Zhang, and J. ...arXiv:1409.2633v1 fatcat:2lhzag5bwjalffydfllkn4iinm
By constructing a pillar–cone double-structure surface on SiC, a near-perfect absorption is realized in the whole reststrahlen band of SiC.doi:10.1039/c8nr01706a pmid:29749414 fatcat:xh3olp7vyncjbdnk5zctlisopq
Supplement 1 for the articledoi:10.6084/m9.figshare.7354940 fatcat:q4et7kbxrrcmzk4jfmh3ke74yu
Encyclopedia of Biometrics
A Universal Background Model (UBM) is a model used in a biometric verification system to represent general, personindependent feature characteristics to be compared against a model of person-specific feature characteristics when making an accept or reject decision. For example, in a speaker verification system, the UBM is a speaker-independent Gaussian Mixture Model (GMM) trained with speech samples from a large set of speakers to represent general speech characteristics. Using adoi:10.1007/978-0-387-73003-5_197 fatcat:tznfvid3g5hxnlqaxewefzvk3i
more »... c GMM trained with speech samples from a particular enrolled speaker, a likelihood-ratio test for an unknown speech sample can be formed between the match score of the speaker-specific model and the UBM. The UBM may also be used when training the speaker-specific model by acting as a the prior model in MAP parameter estimation.
Juntao Tan and Yang Yang have contributed equally to this work. & Jianfeng Zhang firstname.lastname@example.org & Jianji Guo email@example.com & Nuo Yang firstname.lastname@example.org in females Table 1 1 Demographic ...doi:10.1007/s00268-016-3848-8 pmid:27909771 pmcid:PMC5394140 fatcat:75u7ibjgh5fzfnk54craoyebli
A long-standing challenge with metasurface design is identifying computationally efficient methods that produce high performance devices. Design methods based on iterative optimization push the performance limits of metasurfaces, but they require extensive computational resources that limit their implementation to small numbers of microscale devices. We show that generative neural networks can learn from a small set of topology-optimized metasurfaces to produce large numbers of high-efficiency,arXiv:1811.12436v1 fatcat:jaakmtub6ra4zfvq4vresyjoie
more »... topologically-complex metasurfaces operating across a large parameter space. This approach enables considerable savings in computation cost compared to brute force optimization. As a model system, we employ conditional generative adversarial networks to design highly-efficient metagratings over a broad range of deflection angles and operating wavelengths. Generated device designs can be further locally optimized and serve as additional training data for network refinement. Our design concept utilizes a relatively small initial training set of just a few hundred devices, and it serves as a more general blueprint for the AI-based analysis of physical systems where access to large datasets is limited. We envision that such data-driven design tools can be broadly utilized in other domains of optics, acoustics, mechanics, and electronics.
Tools to automatically summarize functional gene group information from the biomedical literature will help genomics researchers both better interpret gene expression data and understand biological pathways. In this study, we built a system that takes in a set of genes and MEDLINE records and outputs clusters of genes along with summaries of each cluster by sentence extraction from MEDLINE abstracts. Our preliminary use-case evaluation shows that this approach can identify gene clusters similar to manually generated groupings.pmid:17238770 pmcid:PMC1839753 fatcat:f6t73tohirfxvexk5tfaal4c74
The present prediction tot rad Supporting Information ofQuenching, plasmonic and radiative decays in nanogap emitting devices Rémi Faggiani, Jianji Yang # , and Philippe Lalanne* Laboratoire ... Yang, J.; Hugonin, J.-P.; Lalanne, P. ...arXiv:1510.06693v2 fatcat:qsaoh64hsjdgti6oixgwuhyddi
This paper proposes an image textural analytical method for estimating the crowd density and counting. At first, the target detection is conducted to obtain the foreground image. This crowd image is used to calculate the gray level co-occurrence matrix (GLCM). Then, according to the characteristic values of the gray level co-occurrence matrix, i.e., energy, entropy, contrast, homogeneity, we use support vector machine (SVM) to estimate crowd density. Simultaneously, the method of lineardoi:10.4304/jmm.9.10.1152-1159 fatcat:6s464txqsfbolj7uhfvfnkd42a
more »... on is used to estimate the crowd counting. The accuracy of evaluation is improved since we extract the target image textural traits to overcome the influence of background for estimation results. Finally, the experimental results show that the proposed approaches of crowd density and counting are feasible and effective.
We propose and experimentally demonstrate a tunable fractional order photonic differentiator using an on-chip electrically tuned Mach-Zehnder interferometer (MZI) structure. The phase shift at the resonant frequency of the MZI varies when applying different voltages, which can implement the fractional differentiation. Due to the large 3-dB bandwidth of the MZI, the differentiator is expected to have an operation bandwidth of several hundred GHz. The proposed fractional order differentiator isdoi:10.1364/oe.22.018232 pmid:25089442 fatcat:qiizhgym3zet7ikknb2avv4dfa
more »... monstrated experimentally. A Gaussian-like pulse with a bandwidth of about 200 GHz is temporally differentiated with a tunable order range from 0.83 to 1.03.
Tiny metal nanogaps may offer a unique platform for achieving extremely larger spontaneous decay rate with high quantum yield.doi:10.1039/c5nh00059a pmid:32260597 fatcat:qeuc4zmrxjgmlargpaf65foo4y
Alzheimer's disease (AD) is the most common fatal neurodegenerative disease of the elderly worldwide. The identification of AD biomarkers will allow for earlier diagnosis and thus earlier intervention. The aim of this study was to find such biomarkers. It was observed that the expression of Alix was significantly decreased in brain tissues and serum samples from AD patients compared to the controls. A significant correlation between Alix levels and cognitive decline was observed (r = 0.80; pdoi:10.3389/fnagi.2021.669612 fatcat:dpgyq6hi7rggvfzthwntnszrha
more »... ; 0.001) as well as a significant negative correlation between Alix and Aβ40 in serum levels (r =−0.60, p < 0.001). The receiver operating characteristic curve (ROC) analysis showed the area under the curve (AUC) of Alix was 0.80, and the optimal cut-off point of 199.5 pg/ml was selected with the highest sum of sensitivity and specificity. The diagnostic accuracy for serum Alix was 74%, with 76% sensitivity and 71% specificity respectively, which could differentiate AD from controls. In addition, the expression of Alix was found to be significantly decreased in AD compared to vascular dementia (VaD). ROC analysis between AD and VaD showed that the AUC was 0.777, which could be indicative of the role of serum Alix as a biomarker in the differential diagnosis between AD and VaD. Most surprisingly, the decreased expression of Alix was attenuated after the treatment of Memantine in different AD animal models. In conclusion, our results indicate the possibility of serum Alix as a novel and non-invasive biomarker for AD for the first time.
This large-area hierarchical Ag@BiOCl NSs SERS chip with a super-hydrophobic surface offers a great advantage in further enhancing SERS detection sensitivity.doi:10.1039/d0ra01226b pmid:35496623 pmcid:PMC9050507 fatcat:7zmubquxnfgbrb5wgfdtezfbxa
Yang et al. © 2019 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd Thoracic Cancer 10 (2019) 2081-2087 © 2019 The Authors. ...doi:10.1111/1759-7714.13181 pmid:31574576 pmcid:PMC6825903 fatcat:npdvtplptjhh3jfika2uj2hssq
Hepatic cancer is the most common primary liver malignancy, with high incidence and mortality worldwide. Atractylon is an active constituent isolated from Atractylodes lancea (Thunb.) DC. and Atractylodes chinensis (DC.) Koidz., which proved to have multiple activities. Methods: In this study, we evaluated the antihepatic cancer (HCC) effect of atractylon in vitro and in vivo and investigated its underlying mechanism. Cell proliferation, colony formation, cell apoptosis, migration and invaisondoi:10.2147/cmar.s194795 pmid:31388314 pmcid:PMC6607983 fatcat:yj2wrqkuqffuxgrhu3aupqf7ya
more »... nd was identified by MTT, crystal violet staining, flow cytometry analysis, and Transwell assay. The ∆Ψm of HepG2 and MHCC97H cells were detected by Rhodamine 123. The ROS level was determined by 2,7-Dichlorodi-hydrofluorescein diacetate (DCFH-DA) method. Protein expression was identified by Western blot analysis. The anti-HCC effect of atractylon in vivo was evaluated by a subcutaneous tumor model. Results: The results suggested that atractylon significantly inhibits the proliferation and promotes apoptosis of hepatic cancer cell lines, including HepG2, SMCC7721, and MHCC97H. Moreover, the results showed that atractylon reduces the mitochondrial membrane potential (∆Ψm), increases ROS level, inhibits the expression of Bcl-2, and promotes the expression of Bax and cleaved caspase-3, indicating that atractylon induces HCC apoptosis through the mitochondrial apoptotic pathway. Our results also demonstrated that atractylon inhibits migration and invasion of hepatic cancer cells by inhibiting the epithelial-mesenchymal transition (EMT) process and downregulating MMP-2 and MMP-9 expression. In addition, atractylon inhibited the growth of hepatic cancer and showed an inhibition effect on EMT process in vivo. Conclusion: In all, this study suggested that atractylon showed a promising anti-HCC effect with inhibiting proliferation, inducing apoptosis, and blocking invasion in vitro and inhibiting growth in vivo.
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