建筑物掏土纠倾法单孔与多孔塑性区特性研究及工程应用

在建筑物水平掏土纠倾工程中，掏土孔间距是影响纠倾工程安全与工期的重要因素。为了快速准确地确定纠倾工程中的水平掏土孔间距，研究了单个掏土孔和多个掏土孔情况下孔周边土体塑性区发展特性。利用土体塑性力学分析计算得到了单孔下的孔周土塑性区半径，而后通过有限元模拟得到孔周土体塑性区半径的数值解，将孔周塑性区半径解析解与数值解进行了对比。并通过有限元数值模型研究了多个掏土孔相互影响情况下的塑性区发展规律，以孔间土体塑性区贯通时的距离作为掏土孔间距。考虑土体参数随机特性的影响，研究不同上部荷载作用下掏土孔间距的取值变化规律，上部面荷载与地基承载力特征值比值用p表示，孔间距与掏土孔直径比值用n表示。研究发现：多孔塑性区半径（孔间塑性区贯通时）是单孔塑性区半径的1.3倍左右;标准化荷载p与孔间距比值n二者呈线性关系;通过不同土体参数及上部荷载的不同情况下的p-n曲线，给出了掏土孔间距建议值。同时，将研究结果与三个实际工程进行对比，发现p-n曲线法与实际结果更为接近。     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

Thermal shock effects on the impact resistance,tolerance and flexural strength of alumina based oxide/oxide ceramic matrix composites

In this study the effects of thermal shock on the impact damage resistance, damage tolerance and flexural strength of Nextel 610/alumina silicate ceramic matrix composites were experimentally evaluated. Composite laminates with balanced and symmetric layup were gradually heated to 1200°C in an air-based furnace and held for at least 30 min before being removed and immersed in water at room temperature. The laminates were then subjected to low velocity impacts via a hemispherical steel impactor. The resultant damage was characterized non-destructively, following which the laminates were subjected to compression tests. Three-point bend tests were also performed to evaluate the effect of thermal shock on the flexural strength and related failure modes of the laminates. Thermally shocked laminates showed smaller internal damage and larger external damage areas in comparison to their pristine counterparts. For the impact energy and resultant damage size considered, the residual compressive strengths for the thermally shocked and pristine laminates were similar.     

基于数值模拟的挤压参数对AZ91镁合金管转角焊合室分流挤压焊合压力的影响规律研究

提出了一种镁合金管材转角焊合室分流挤压新工艺，该工艺可在有效延长焊合室长度和焊合时间前提下保证舌针刚度，从而保证管材尺寸精度，并且可通过转角剪切变形机制增加预焊合金属变形量和动态再结晶程度，从而有利于提高管材性能和焊缝焊合性能。利用有限元法揭示了转角焊合室分流挤压成形过程中金属的流动特征，应变分布特征和焊合室内的静水压力分布特征。结果表明，整个挤压过程无金属折叠，从而保证管材的表面质量；流经转角后预焊合金属变形量明显增加，有利于提高管材质量和焊缝质量。最后，研究揭示了坯料初始温度，挤压速度和模具转角对焊合室内静水压力的影响规律。结果表明，随着挤压速度的增加和模具转角的增大，转角焊合室内静水压力增大；随着坯料预热温度的增加，转角焊合室内静水压力呈先增大后减小的趋势。     

In Vivo Simultaneous Analysis of Gene Expression by Dual-Color Luciferases in Caenorhabditis elegans

Both fluorescent and luminescent observation are widely used to examine real-time gene expression patterns in living organisms. Several fluuorescent and luminescent proteins with specific optical properties have been developed and applied for simultaneous, multi-color observation of more than two gene expression profiles. Compared to fluorescent proteins, however, the application of multi-color luminescent imaging in living organisms is still limited. In this study, we introduced two-color luciferases into the soil nematode C. elegans and performed simultaneous analysis of two gene expression profiles. Using a green-emitting luciferase Eluc (emerald luciferase) and red-emitting luciferase SLR (stable luciferase red), the expression patterns of two genes were simultaneously observed in single animals from embryonic to adult stages over its whole life span. In addition, dual gene activities were observed at the single embryo level, with the simultaneous observation of morphological changes. These are the first application of a two-color luciferase system into a whole animal and suggest that precise relationship of expression patterns of multiple genes of interest can be analyzed over the whole life of the animal, dependent on the changes in genetic and/or environmental conditions.     

Use of Fourier-Transform Infrared Spectroscopy (FT-IR) for Monitoring Experimental Helicobacter pylori Infection and Related Inflammatory Response in Guinea Pig Model

Infections due to Gram-negative bacteria Helicobacter pylori may result in humans having gastritis, gastric or duodenal ulcer, and even gastric cancer. Investigation of quantitative changes of soluble biomarkers, correlating with H. pylori infection, is a promising tool for monitoring the course of infection and inflammatory response. The aim of this study was to determine, using an experimental model of H. pylori infection in guinea pigs, the specific characteristics of infrared spectra (IR) of sera from H. pylori infected (40) vs. uninfected (20) guinea pigs. The H. pylori status was confirmed by histological, molecular, and serological examination. The IR spectra were measured using a Fourier-transform (FT)-IR spectrometer Spectrum 400 (PerkinElmer) within the range of wavenumbers 3000–750 cm⁻¹ and converted to first derivative spectra. Ten wavenumbers correlated with H. pylori infection, based on the chi-square test, were selected for a K-nearest neighbors (k-NN) algorithm. The wavenumbers correlating with infection were identified in the W2 and W3 windows associated mainly with proteins and in the W4 window related to nucleic acids and hydrocarbons. The k-NN for detection of H. pylori infection has been developed based on chemometric data. Using this model, animals were classified as infected with H. pylori with 100% specificity and 97% sensitivity. To summarize, the IR spectroscopy and k-NN algorithm are useful for monitoring experimental H. pylori infection and related inflammatory response in guinea pig model and may be considered for application in humans.     

AP2M1 Supports TGF-β Signals to Promote Collagen Expression by Inhibiting Caveolin Expression

The extracellular matrix (ECM) is important for normal development and disease states, including inflammation and fibrosis. To understand the complex regulation of ECM, we performed a suppressor screening using Caenorhabditis elegans expressing the mutant ROL-6 collagen protein. One cuticle mutant has a mutation in dpy-23 that encodes the μ2 adaptin (AP2M1) of clathrin-associated protein complex II (AP-2). The subsequent suppressor screening for dpy-23 revealed the lon-2 mutation. LON-2 functions to regulate body size through negative regulation of the tumor growth factor-beta (TGF-β) signaling pathway responsible for ECM production. RNA-seq analysis showed a dominant change in the expression of collagen genes and cuticle components. We noted an increase in the cav-1 gene encoding caveolin-1, which functions in clathrin-independent endocytosis. By knockdown of cav-1, the reduced TGF-β signal was significantly restored in the dpy-23 mutant. In conclusion, the dpy-23 mutation upregulated cav-1 expression in the hypodermis, and increased CAV-1 resulted in a decrease of TβRI. Finally, the reduction of collagen expression including rol-6 by the reduced TGF-β signal influenced the cuticle formation of the dpy-23 mutant. These findings could help us to understand the complex process of ECM regulation in organism development and disease conditions.     

Korean automatic spacing using pretrained transformer encoder and analysis

Automatic spacing in Korean is used to correct spacing units in a given input sentence. The demand for automatic spacing has been increasing owing to frequent incorrect spacing in recent media, such as the Internet and mobile networks. Therefore, herein, we propose a transformer encoder that reads a sentence bidirectionally and can be pretrained using an out-of-task corpus. Notably, our model exhibited the highest character accuracy (98.42%) among the existing automatic spacing models for Korean. We experimentally validated the effectiveness of bidirectional encoding and pretraining for automatic spacing in Korean. Moreover, we conclude that pretraining is more important than fine-tuning and data size.