Regularity of optimal sets for some functional involving eigenvalues of an operator in divergence form

In this paper we consider minimizers of the functional$\min \{{\lambda }_1(\mathrm{\Omega })+\cdots +{\lambda }_k(\mathrm{\Omega })+\mathrm{\Lambda }|\mathrm{\Omega }|,:\mathrm{\Omega }\subset D\text{ open}\}$ where $D\subset {\mathbb{R}}^d$ is a bounded open set and where $0<{\lambda }_1(\mathrm{\Omega })\le \cdots \le {\lambda }_k(\mathrm{\Omega })$ are the first k eigenvalues on Ω of an operator in divergence form with Dirichlet boundary condition and with Hölder continuous coefficients. We prove that the optimal sets ${\mathrm{\Omega }}^{⁎}$ have finite perimeter and that their free boundary $\partial {\mathrm{\Omega }}^{⁎}\cap D$ is composed of a regular part, which is locally the graph of a $C^{1,\alpha }$-regular function, and a singular part, which is empty if $d<d^{⁎}$, discrete if $d=d^{⁎}$ and of Hausdorff dimension at most $d-d^{⁎}$ if $d>d^{⁎}$, for some $d^{⁎}\in \{5,6,7\}$.     

基于电子病历的乳腺癌群组与治疗方案可视分析

乳腺癌是当前最常见的恶性肿瘤之一，其电子病历数据可用于挖掘隐含规律，对治疗与预后分析有重要意义。通过与乳腺科医生合作，选择合适的预测模型和可视化方法，搭建了一个基于电子病历的乳腺癌群组和治疗方案可视分析系统。首先，对具有高维属性的病人进行降维和聚类处理，形成病人群组，并采用南丁格尔图、词云和时间轴可视化方法，直观展示病人群组间特征的差异；然后，用支持向量机（support vector machine，SVM）模型预测治疗方案，用平行坐标、矩阵热力图和分类图分别展示属性相关性、训练后的特征权重和预测结果；最后，用真实案例验证了系统在群组分析、治疗方案及病人属性关联分析中的有效性，从而较好地帮助医生选择合适的治疗方案。     

3.0T MRI检查结合X线钼靶诊断乳腺恶性肿瘤的研究

本研究探讨3.0T磁共振成像(MRI)结合X线钼靶诊断乳腺恶性肿瘤的价值。采用回顾性研究方法,选取乳腺肿块患者110例162个病灶,给予3.0T MRI及X线钼靶检查。经病理确诊为恶性病变101个;恶性病灶形态不规则、边缘毛刺、时间-信号强度曲线(TIC)类型Ⅲ型和早期增强率≥60%比例明显高于良性病灶(P<0.05),而分叶状比例和表观扩散系数(ADC)值明显低于良性病变(P<0.05);恶性病变X线钼靶表现:形态不规则、钙化、结构不对称和大导管征比例明显高于良性病变(P<0.05);MRI联合X线钼靶诊断乳腺恶性病变的灵敏性、准确性和阴性预测值明显高于MRI诊断(P<0.05)。3.0T MRI检查结合X线钼靶诊断乳腺恶性肿瘤有较好的价值。     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

Sensitivity improvement of aluminum-based far-ultraviolet nearly guided-wave surface plasmon resonance sensor

An aluminum (Al) based nearly guided-wave surface plasmon resonance (NGWSPR) sensor is investigated in the far-ultraviolet (FUV) region. By simultaneously optimizing the thickness of Al and dielectric films, the sensitivity of the optimized Al-based FUV-NGWSPR sensor increases from 183°/RIU to 309°/RIU, and its figure of merit rises from 26.47 RIU^-1 to 32.59 RIU^-1 when the refractive index of dielectric increases from 2 to 5. Compared with a traditional FUV-SPR sensor without dielectric, the optimized FUV-NGWSPR sensor can realize simultaneous improvement of sensitivity and figure of merit. In addition, the FUV-NGWSPR sensor with realistic materials (diamond, Ta₂O₅, and GaN) is also investigated, and 137.84%, 52.70%, and 41.89% sensitivity improvements are achieved respectively. This work proposes a method for performance improvement of FUV-SPR sensors by exciting nearly guided-wave, and could be helpful for the high-performance SPR sensor in the short-wavelength region.     

超声共振法测定圆柱体材料弹性常数的影响因素分析

为明确超声共振频谱分析法(RUS)测定圆柱体试样弹性常数的影响因素, 由此针对各向同性圆柱体开展实验, 观察圆柱体试样测量结果的分散性和稳定性, 且主要研究横纵比和有效模态数量对测量结果的影响, 并与拉伸试验的结果进行比较. 以测量结果标准差、变异系数和95%置信度下均值的区间估计3个指标来衡量结果的稳定性和分散性, 且从模态简并角度对实验结果进行分析. 最终结果表明, 当超声共振频谱分析法的有效模态数量在17左右、试样横纵比接近1时, 测量结果的稳定性和分散性较小.     

On the inflation and deflation dynamics of liquid-filled,hyperelastic balloons

We derive a reduced-order model describing the inflation and deflation dynamics of a liquid-filled hyperelastic balloon, focusing on inviscid laminar flow and the extensional motion of the balloon. We initially study the flow and pressure fields for dictated motion of the solid, which throughout deflation are obtained by solving the potential problem. However, during inflation, flow separation creates a jet within the balloon, requiring a different approach. The analyses of both flow regimes lead to a simple piecewise model, describing the fluidic pressure during inflation and deflation, which is verified by finite element computations. We then use a variational approach to derive the equation describing the interaction between the extensional mode of the balloon and the entrapped fluid, yielding a nonlinear hybrid oscillator equation. Analytical and graphical investigations of the suggested model are presented, shedding light on its static and dynamic behaviour under different operating conditions. Our simplified model and its underlying assumptions are verified utilizing a fully coupled finite element scheme, showing excellent agreement.     

Ammonia Oxidation Enhanced by Photopotential Generated by Plasmonic Excitation of a Bimetallic Electrocatalyst

We study how visible light influences the activity of an electrocatalyst composed of Au and Pt nanoparticles. The bimetallic composition imparts a dual functionality: the Pt component catalyzes the electrochemical oxidation of ammonia to liberate hydrogen and the Au component absorbs visible light by the excitation of localized surface plasmon resonances. Under visible-light excitation, this catalyst exhibits enhanced electrochemical ammonia oxidation kinetics, outperforming previously reported electrochemical schemes. We trace the enhancement to a photochemical potential resulting from electron–hole carriers generated in the electrocatalyst by plasmonic excitation. The photopotential responsible for enhanced kinetics scales linearly with the light intensity—a general design principle for eliciting superlative photoelectrochemical performance from catalysts comprised of plasmonic metals or hybrids. We also determine a photochemical conversion coefficient.     

The first excited single-proton resonance in 15F by complex-scaled Green's function method

The complex-scaled Green's function(CGF)method is employed to explore the single-proton resonance in 15F.Special attention is paid to the first excited resonant state 5/2+,which has been widely studied in both theory and experiments.However,past studies generally overestimated the width of the 5/2+state.The predicted energy and width of the first excited resonant state 5/2+by the CGF method are both in good agreement with the experimental value and close to Fortune's new estimation.Furthermore,the influence of the potential parameters and quadruple deformation effects on the resonant states are investigated in detail,which is helpful to the study of the shell structure evolution.