Success Probability Assessment Based on Information Entropy

The Bayesian method is superior to the classical statistical method on condition of small sample test. However, its evaluation results are not so good if subjective prior information is intervened. The success probability assessment about the success or failure tests of weapon products focussed in this paper, and a fusing evaluation method based on information entropy is proposed. Firstly, data from equivalent surrogate tests is converted into the prior information of an equivalent source by the information entropy theory. Secondly, the prior distribution of the success probability is identified via the Bootstrap method, and the posterior distribution is provided by the Bayesian method with the information of prototype tests in succession. Lastly, an example is given, and the results show that the proposed method is effective and valuable.Defence Science Journal, 2010, 60(3), pp.271-275, DOI:http://dx.doi.org/10.14429/dsj.60.35

Fabrication of a microresonator-fiber assembly maintaining a high-quality factor by CO2 laser welding

We demonstrate fabrication of a microtoroid resonator of a high-quality (high-Q) factor using femtosecond laser three-dimensional (3D) micromachining. A fiber taper is reliably assembled to the microtoroid using CO2 laser welding. Specifically, we achieve a high Q-factor of 2.12*10^6 in the microresonator-fiber assembly by optimizing the contact position between the fiber taper and the microtoroid.Comment: 7 pages, 5 figure

Can Domain Adaptation Improve Accuracy and Fairness of Skin Lesion Classification?

Deep learning-based diagnostic system has demonstrated potential in classifying skin cancer conditions when labeled training example are abundant. However, skin lesion analysis often suffers from a scarcity of labeled data, hindering the development of an accurate and reliable diagnostic system. In this work, we leverage multiple skin lesion datasets and investigate the feasibility of various unsupervised domain adaptation (UDA) methods in binary and multi-class skin lesion classification. In particular, we assess three UDA training schemes: single-, combined-, and multi-source. Our experiment results show that UDA is effective in binary classification, with further improvement being observed when imbalance is mitigated. In multi-class task, its performance is less prominent, and imbalance problem again needs to be addressed to achieve above-baseline accuracy. Through our quantitative analysis, we find that the test error of multi-class tasks is strongly correlated with label shift, and feature-level UDA methods have limitations when handling imbalanced datasets. Finally, our study reveals that UDA can effectively reduce bias against minority groups and promote fairness, even without the explicit use of fairness-focused techniques

MiR-200, a New Star miRNA In Human Cancer

MicroRNAs (miRNAs) are a set of non-coding small RNA molecules in control of gene expression at posttranscriptional/translational level. They not only play crucial roles in normal developmental progress, but also are commonly dysregulated in human diseases, including cancer. MiR-200 is a family of tumor suppressor miRNAs consisting of five members, which are significantly involved in inhibition of epithelial-to-mesenchymal transition (EMT), repression of cancer stem cells (CSCs) self-renewal and differentiation, modulation of cell division and apoptosis, and reversal of chemoresistance. In this article, we summarize the latest findings with regard to the tumor suppressor signatures of miR-200 and the regulatory mechanisms of miR-200 expression. The collected evidence supports that miR-200 is becoming a new star miRNA in study of human cancer. © 2013

Quasicrystal Formation, Structure and Indentation Behaviors in Pure Tantalum

Spontaneous quasicrystal (QC) formation has not been observed in pure metals either in computation or in experiments (excluding epitaxial growth of thin atomic layers on a QC template). In this thesis work, dodecagonal QC (DDQC) grains are first discovered to spontaneously form during thermal devitrification of pure tantalum (Ta) metallic glass simulated by molecular dynamics (MD). The electron diffraction pattern of the DDQC grain shows a perfect 12-fold symmetry, different from the β–Ta that also forms in the process. Analysis of the dynamic atomic configurations reveals that the DDQC grains are formed from both the supercooled liquid and the defected β–Ta phases. The DDQC grains are stable within the β–Ta phase upon complete solidification owing to a slightly lower potential energy, even at room temperature. Following this discovery of spontaneous DDQC formation, the effects of several factors, such as annealing time, temperature, and pressure on the population of the DDQC grains are investigated by MD. Nanoindentation tests are also conducted by MD to examine the hardness and elastic modulus of the DDQC grain, β–Ta, and BCC Ta. The atomic structures and load-displacement curves of the three are compared, which reveals that H_Q>H_β>H_B, whereas E_Q<E_β<E_B. This thesis work demonstrates for the first time that QC grains can, in theory, form spontaneously in pure metal, and the formation (population) of the QC grains can be enhanced by choosing the optimal processing conditions

An overview on nonlinear porous flow in low permeability porous media

AbstractThis paper gives an overview on nonlinear porous flow in low permeability porous media, reveals the microscopic mechanisms of flows, and clarifies properties of porous flow fluids. It shows that, deviating from Darcy's linear law, the porous flow characteristics obey a nonlinear law in a low-permeability porous medium, and the viscosity of the porous flow fluid and the permeability values of water and oil are not constants. Based on these characters, a new porous flow model, which can better describe low permeability reservoir, is established. This model can describe various patterns of porous flow, as Darcy's linear law does. All the parameters involved in the model, having definite physical meanings, can be obtained directly from the experiments

Flow Pattern and Mixing Characteristics of Highly Viscous Fluids in a Dynamic Mixer

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