Robust optimization utilizing the second-order design sensitivity information

This paper presents an effective methodology for robust optimization of electromagnetic devices. To achieve the goal, the method improves the robustness of the minimum of the objective function chosen as a design solution by minimizing the second-order sensitivity information, called a gradient index (GI) and defined by a function of gradients of performance functions with respect to uncertain variables. The constraint feasibility is also enhanced by adding a GI corresponding to the constraint value. The distinctive feature of the method is that it requires neither statistical information on design variables nor calculation of the performance reliability during the robust optimization process. The validity of the proposed method is tested with the TEAM Workshop Problem 2

E-beam-enhanced solid-state mechanical amorphization of alpha-quartz: Reducing deformation barrier via localized excess electrons as mobile anions

Under hydrostatic pressure, alpha-quartz undergoes solid-state mechanical amorphization wherein the interpenetration of SiO4 tetrahedra occurs and the material loses crystallinity. This phase transformation requires a high hydrostatic pressure of 14 GPa because the repulsive forces resulting from the ionic nature of the Si-O bonds prevent the severe distortion of the atomic configuration. Herein, we experimentally and computationally demonstrate that e-beam irradiation changes the nature of the interatomic bonds in alpha-quartz and enhances the solid-state mechanical amorphization at nanoscale. Specifically, during in situ uniaxial compression, a larger permanent deformation occurs in alpha-quartz micropillars compressed during e-beam irradiation than in those without e-beam irradiation. Microstructural analysis reveals that the large permanent deformation under e-beam irradiation originates from the enhanced mechanical amorphization of alpha-quartz and the subsequent viscoplastic deformation of the amorphized region. Further, atomic-scale simulations suggest that the delocalized excess electrons introduced by e-beam irradiation move to highly distorted atomic configurations and alleviate the repulsive force, thus reducing the barrier to the solid-state mechanical amorphization. These findings deepen our understanding of electron-matter interactions and can be extended to new glass forming and processing technologies at nano- and microscale.Comment: 24 pages, 6 figure

Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology

IntroductionAutomatic nuclear segmentation in digital microscopic tissue images can aid pathologists to extract high-quality features for nuclear morphometrics and other analyses. However, image segmentation is a challenging task in medical image processing and analysis. This study aimed to develop a deep learning-based method for nuclei segmentation of histological images for computational pathology.MethodsThe original U-Net model sometime has a caveat in exploring significant features. Herein, we present the Densely Convolutional Spatial Attention Network (DCSA-Net) model based on U-Net to perform the segmentation task. Furthermore, the developed model was tested on external multi-tissue dataset – MoNuSeg. To develop deep learning algorithms for well-segmenting nuclei, a large quantity of data are mandatory, which is expensive and less feasible. We collected hematoxylin and eosin–stained image data sets from two hospitals to train the model with a variety of nuclear appearances. Because of the limited number of annotated pathology images, we introduced a small publicly accessible data set of prostate cancer (PCa) with more than 16,000 labeled nuclei. Nevertheless, to construct our proposed model, we developed the DCSA module, an attention mechanism for capturing useful information from raw images. We also used several other artificial intelligence-based segmentation methods and tools to compare their results to our proposed technique.ResultsTo prioritize the performance of nuclei segmentation, we evaluated the model’s outputs based on the Accuracy, Dice coefficient (DC), and Jaccard coefficient (JC) scores. The proposed technique outperformed the other methods and achieved superior nuclei segmentation with accuracy, DC, and JC of 96.4% (95% confidence interval [CI]: 96.2 – 96.6), 81.8 (95% CI: 80.8 – 83.0), and 69.3 (95% CI: 68.2 – 70.0), respectively, on the internal test data set.ConclusionOur proposed method demonstrates superior performance in segmenting cell nuclei of histological images from internal and external datasets, and outperforms many standard segmentation algorithms used for comparative analysis

Engineering the shape and structure of materials by fractal cut

In this paper we discuss the transformation of a sheet of material into a wide range of desired shapes and patterns by introducing a set of simple cuts in a multilevel hierarchy with different motifs. Each choice of hierarchical cut motif and cut level allows the material to expand into a unique structure with a unique set of properties. We can reverse-engineer the desired expanded geometries to find the requisite cut pattern to produce it without changing the physical properties of the initial material. The concept was experimentally realized and applied to create an electrode that expands to >800% the original area with only very minor stretching of the underlying material. The generality of our approach greatly expands the design space for materials so that they can be tuned for diverse applications.Korea Institute of Science and Technology (Internal Research Funding Grant 2Z04050)Korea Institute of Science and Technology (Internal Research Funding Grant 2V03320)National Research Council of Science and Technology (Grant NST-Yunghap-13-1)National Science Foundation (U.S.). Division of Materials Research (Grant 1120901)National Science Foundation (U.S.). Chemical, Bioengineering, Environmental, and Transport Systems (Grant 1240696

Investigation of the dorsolateral branch of the posterior intercostal artery for use as the pedicle of a free flap: A cadaveric study and case series

Background The dorsolateral branch of the posterior intercostal artery (DLBPI) can be easily found while harvesting a latissimus dorsi (LD) musculocutaneous flap for breast reconstruction. However, it remains unknown whether this branch can be used for a free flap and whether this branch alone can provide perfusion to the skin. We examined whether the DLBPI could be reliably found and whether it could provide sufficient perfusion. Methods We dissected 10 fresh cadavers and counted DLBPIs with a diameter larger than 2 mm. For each DLBPI, the following parameters were measured: distance from the lateral margin of the LD muscle, level of the intercostal space, distance from the spinal process, and distance from the inferior angle of the scapula. Results The DLBPI was easily found in all cadavers and was reliably located in the specified area. The average number of DLBPIs was 1.65. They were located between the seventh and eleventh intercostal spaces. The average length of the DLBPI between the intercostal space and the LD muscle was 4.82 cm. To assess the perfusion of the DLBPIs, a lead oxide mixture was injected through the branch and observed using X-rays, and it showed good perfusion. Conclusions The DLBPI can be used as a pedicle in free flaps for small defects. DLBPI flaps have some limitations, such as a short pedicle. However, an advantage of this branch is that it can be reliably located through simple dissection. For women, it has the advantage of concealing the donor scar underneath the bra band

'Big Tigers, Big Data:' Learning Social Reactions to China’s Anticorruption Campaign through Online Feedback

This study examines the effect of campaign-style anticorruption on political support using the case of China’s most recent anticorruption drive, which stands out for its harsh crackdown on high-ranking officials, or the “big tigers.” An exploratory text analysis of over 370,000 online comments on the downfall of the first 100 big tigers, from 2012 to 2015, reveals that public support for the top national leader who initiated the campaign significantly exceeds that afforded to anticorruption agencies and institutions. Further regression analyses show that support for the leaders vis-à-vis intuitions increases with the tigers’ party ranking. Findings suggest that while campaign-style enforcement can reinforce the central authority and magnify support for individual leaders, it may also marginalize the role of legal institutions crucial to long-term corruption control.published_or_final_versio