Protein Fractions from Korean Mistletoe ( Viscum Album coloratum

Mistletoe (Viscum Album coloratum) has been known as a medicinal plant in European and Asian countries. Recent data show that biological activity of mistletoe alleviates hypertension, heart disease, renal failure, and cancer development. In this study, we report the antidiabetic effect of Korean mistletoe extract (KME). KME treatments enhanced the insulin secretion from the pancreatic β-cell without any effects of cytotoxicity. PDX-1 and beta2/neuroD known as transcription factors that regulate the expression of insulin gene were upregulated by treatment of the KME protein fractions isolated by ion-exchange chromatography after ammonium sulfate precipitation. Furthermore, these KME protein fractions significantly lowered the blood glucose level and the volume of drinking water in alloxan induced hyperglycemic mice. Taken together with the findings, it provides new insight that KME might be served as a useful source for the development of medicinal reagent to reduce blood glucose level of type I diabetic patients

Highway Construction Productivity Measurement with a Wireless Real-Time Productivity Measurement System

Seonghoon Kim, Yong Bai, Yang-Ki Jung, and Dukgeun Yun, Highway Construction Productivity Measurement with a Wireless Real-Time Productivity Measurement System, Transportation Research Record: Journal of the Transportation Research Board (Volume: 2228 issue: 1) pp. 26-33. Copyright © 2011 SAGE Publications. DOI: 10.3141/2228-04.Improving the quality of construction schedules calls for development of an advanced productivity measurement system. Existing on-site construction productivity measurement methods have some common limitations, such as not providing data necessary for engineers and project managers to conduct real-time analyses and share data with other project participants. A wireless real-time productivity measurement (WRITE) system was developed to address those shortfalls. The field experiment was conducted at two different stages: asphalt paving projects, including hot-mix asphalt and hot-in-place recycling, and a bridge reconstruction project. Productivity data collected from the WRITE system were also compared with productivity data collected from construction documents, such as contractors' daily logs and pay estimate documents, to identify the feasibility of this system for measuring the performance of construction projects. For data analyses, statistical methods such as normality test, paired t-test, and Wilcoxon signed-rank test were used. The result of statistical analyses proved that the developed system generated identical productivity measurements compared with the stopwatch method and construction documents. The success of this research project made several major contributions to the advancement of the construction industry. First, the research advanced the application of wireless technology in highway construction operations. Second, it provided an advanced technology for engineers and project managers to determine productivity in real time. Third, productivity data can be shared between project participants via the Internet. With these advancements, communication and coordination will be improved at construction sites. Consequently, the WRITE system will enhance owners' and contractors' ability to manage construction projects

Role of generic scale invariance in a Mott transition from a U(1) spin-liquid insulator to a Landau Fermi-liquid metal

We investigate the role of generic scale invariance in a Mott transition from a U(1) spin-liquid insulator to a Landau Fermi-liquid metal, where there exist massless degrees of freedom in addition to quantum critical fluctuations. Here, the Mott quantum criticality is described by critical charge fluctuations, and additional gapless excitations are U(1) gauge-field fluctuations coupled to a spinon Fermi surface in the spin-liquid state, which turn out to play a central role in the Mott transition. An interesting feature of this problem is that the scaling dimension of effective leading local interactions between critical charge fluctuations differs from that of the coupling constant between U(1) gauge fields and matter-field fluctuations in the presence of a Fermi surface. As a result, there appear dangerously irrelevant operators, which can cause conceptual difficulty in the implementation of renormalization group (RG) transformations. Indeed, we find that the curvature term along the angular direction of the spinon Fermi surface is dangerously irrelevant at this spin-liquid Mott quantum criticality, responsible for divergence of the self-energy correction term in U(1) gauge-field fluctuations. Performing the RG analysis in the one-loop level based on the dimensional regularization method, we reveal that such extremely overdamped dynamics of U(1) gauge-field fluctuations, which originates from the emergent one-dimensional dynamics of spinons, does not cause any renormalization effects to the effective dynamics of both critical charge fluctuations and spinon excitations. However, it turns out that the coupling between U(1) gauge-field fluctuations and both matter-field excitations still persists at this Mott transition, which results in novel mean-field dynamics to explain the nature of the spin-liquid Mott quantum criticality

Effective thermal conductivity of wire-woven bulk Kagome sandwich panels

AbstractThermal transport in a highly porous metallic wire-woven bulk Kagome (WBK) is numerically and analytically modeled. Based on topology similarity and upon introducing an elongation parameter in thermal tortuosity, an idealized Kagome with non-twisted struts is employed. Special focus is placed upon quantifying the effect of topological anisotropy of WBK upon its effective conductivity. It is demonstrated that the effective conductivity reduces linearly as the porosity increases, and the extent of the reduction is significantly dependent on the orientation of WBK. The governing physical mechanism of anisotropic thermal transport in WBK is found to be the anisotropic thermal tortuosity caused by the intrinsic anisotropic topology of WBK

Single Image Super-Resolution Using Multi-Scale Convolutional Neural Network

Methods based on convolutional neural network (CNN) have demonstrated tremendous improvements on single image super-resolution. However, the previous methods mainly restore images from one single area in the low resolution (LR) input, which limits the flexibility of models to infer various scales of details for high resolution (HR) output. Moreover, most of them train a specific model for each up-scale factor. In this paper, we propose a multi-scale super resolution (MSSR) network. Our network consists of multi-scale paths to make the HR inference, which can learn to synthesize features from different scales. This property helps reconstruct various kinds of regions in HR images. In addition, only one single model is needed for multiple up-scale factors, which is more efficient without loss of restoration quality. Experiments on four public datasets demonstrate that the proposed method achieved state-of-the-art performance with fast speed