Growth of ultra-uniform graphene using a Ni/W bilayer metal catalyst

We investigated a bilayer catalyst system consisting of polycrystalline Ni and W films for growing mono-layer graphene over large areas. Highly uniform graphene was grown on Ni/W bilayer film with 100% coverage. The graphene grown on Ni/W bilayer film and transferred onto an insulating substrate exhibited average hole and electron mobilities of 727 and 340 cm(2)V(-1)s(-1), respectively. A probable growth mechanism is proposed based on X-ray diffractometry and transmission electron microscopy, which suggests that the reaction between diffused carbon and tungsten atoms results in formation of tungsten carbides. This reaction allows the control of carbon precipitation and prevents the growth of non-uniform multilayer graphene on the Ni surface; this has not been straightforwardly achieved before. These results could be of importance in better understanding mono-layer graphene growth, and suggest a facile fabrication route for electronic applications. (C) 2015 AIP Publishing LLCopen0

Effects of Chung-Pae Inhalation Therapy on a Mouse Model of Chronic Obstructive Pulmonary Disease

Chung-pae (CP) inhalation therapy is a method frequently used in Korea to treat lung disease, especially chronic obstructive pulmonary disease (COPD). This study investigated the effects of CP inhalation on a COPD animal model. C57BL/6 mice received porcine pancreatic elastase (PPE) and lipopolysaccharide (LPS) alternately three times for 3 weeks to induce COPD. Then, CP (5 or 20 mg/kg) was administered every 2 h after the final LPS administration. The effect of CP was evaluated by bronchoalveolar lavage (BAL) fluid analysis, histological analysis of lung tissue, and reverse transcription polymerase chain reaction analysis of mRNA of interleukin- (IL-) 1β, tumor necrosis factor- (TNF-) α, IL-6, and tumor growth factor- (TGF-) β. Intratracheal CP administration reduced the number of leukocytes and neutrophils in BAL fluid, inhibited the histological appearance of lung damage, and decreased the mRNA levels of the proinflammatory cytokines IL-1β, TNF-α, IL-6, and TGF-β. Intratracheal CP administration effectively decreased the chronic inflammation and pathological changes in a PPE- and LPS-induced COPD mouse model. Therefore, we suggest that CP is a promising strategy for COPD

Robust Discriminative Metric Learning for Image Representation

Metric learning has attracted significant attentions in the past decades, for the appealing advances in various realworld applications such as person re-identification and face recognition. Traditional supervised metric learning attempts to seek a discriminative metric, which could minimize the pairwise distance of within-class data samples, while maximizing the pairwise distance of data samples from various classes. However, it is still a challenge to build a robust and discriminative metric, especially for corrupted data in the real-world application. In this paper, we propose a Robust Discriminative Metric Learning algorithm (RDML) via fast low-rank representation and denoising strategy. To be specific, the metric learning problem is guided by a discriminative regularization by incorporating the pair-wise or class-wise information. Moreover, low-rank basis learning is jointly optimized with the metric to better uncover the global data structure and remove noise. Furthermore, fast low-rank representation is implemented to mitigate the computational burden and make sure the scalability on large-scale datasets. Finally, we evaluate our learned metric on several challenging tasks, e.g., face recognition/verification, object recognition, and image clustering. The experimental results verify the effectiveness of the proposed algorithm by comparing to many metric learning algorithms, even deep learning ones

Effects of Mixing on the Aggressive Behavior of Commercially Housed Pigs

In this study, we investigated the effects of mixing on the aggressive behavior of commercially housed pigs. The behavioral patterns of 36 groups of pigs (a total of 360 animals) were observed over 3 consecutive days directly after weaning (25±1.2 days of age), and 25 and 50 days later with the aid of video technology. Fight latency and total duration and frequency of fighting were significantly different among the age groups. The aggressive behaviors decreased in 75-day old pigs if compared to 25- and 50-day old animals. Moreover, dominance index (DI) was higher in 25-day old and lower in 75-day old pigs. A comparison of dominant (DI>0) and submissive (DI<0) pigs showed significant differences (p<0.05) for major aggressive behaviors in all age groups. Dominant pigs were involved in more aggressive interactions, had longer fights, and initiated more fights than submissive pigs. Post-mixing aggressive behavior was altered by previous experience of mixing. Aggressive behavior and DI are suitable methods for analyzing the effects of mixing on commercially housed growing pigs

Automatic mandibular canal detection using a deep convolutional neural network

The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging for clinicians. In accordance with the increasing demands in the healthcare industry, techniques for automatic prediction and detection are being widely researched. Particularly in dentistry, for various reasons, automated mandibular canal detection has become highly desirable. The positioning of the inferior alveolar nerve (IAN), which is one of the major structures in the mandible, is crucial to prevent nerve injury during surgical procedures. However, automatic segmentation using Cone beam computed tomography (CBCT) poses certain difficulties, such as the complex appearance of the human skull, limited number of datasets, unclear edges, and noisy images. Using work-in-progress automation software, experiments were conducted with models based on 2D SegNet, 2D and 3D U-Nets as preliminary research for a dental segmentation automation tool. The 2D U-Net with adjacent images demonstrates higher global accuracy of 0.82 than naïve U-Net variants. The 2D SegNet showed the second highest global accuracy of 0.96, and the 3D U-Net showed the best global accuracy of 0.99. The automated canal detection system through deep learning will contribute significantly to efficient treatment planning and to reducing patients’ discomfort by a dentist. This study will be a preliminary report and an opportunity to explore the application of deep learning to other dental fields.Peer reviewe

Learning to Quantize Deep Networks by Optimizing Quantization Intervals with Task Loss

Reducing bit-widths of activations and weights of deep networks makes it efficient to compute and store them in memory, which is crucial in their deployments to resource-limited devices, such as mobile phones. However, decreasing bit-widths with quantization generally yields drastically degraded accuracy. To tackle this problem, we propose to learn to quantize activations and weights via a trainable quantizer that transforms and discretizes them. Specifically, we parameterize the quantization intervals and obtain their optimal values by directly minimizing the task loss of the network. This quantization-interval-learning (QIL) allows the quantized networks to maintain the accuracy of the full-precision (32-bit) networks with bit-width as low as 4-bit and minimize the accuracy degeneration with further bit-width reduction (i.e., 3 and 2-bit). Moreover, our quantizer can be trained on a heterogeneous dataset, and thus can be used to quantize pretrained networks without access to their training data. We demonstrate the effectiveness of our trainable quantizer on ImageNet dataset with various network architectures such as ResNet-18, -34 and AlexNet, on which it outperforms existing methods to achieve the state-of-the-art accuracy

Surgical Treatment of Primary Malignant Melanoma of the Esophagus : A Case Report

Primary malignant melanoma of the esophagus (PMME) is an extremely rare tumor with only scattered cases reported. Although surgical resection has been considered as the best possible option, the prognosis has been nonetheless poor. We report a case of PMME which was treated by surgical resection and additionally followed by chemotherapy. A 60-yr-old man underwent an esophagoscopy due to a 3-month history of dysphagia and upper abdominal discomfort. A pigmented polypoid mass in the lower third of the esophagus was discovered, and a biopsy identified the mass as a malignant melanoma. Consequently, a subtotal esophagectomy and intrathoracic esophagogastrostomy was carried out. At follow-up four months after discharge, lymph node enlargements in the cervical area and celiac axis area were found. As a result, the patients was started on systemic chemotherapy treatment, which included Dacarbazine. The patient has been doing well and is now 35 months post-operative