Autonomous topological modeling of a home environment and topological localization using a sonar grid map

This paper presents a method of autonomous topological modeling and localization in a home environment using only low-cost sonar sensors. The topological model is extracted from a grid map using cell decomposition and normalized graph cut. The autonomous topological modeling involves the incremental extraction of a subregion without predefining the number of subregions. A method of topological localization based on this topological model is proposed wherein a current local grid map is compared with the original grid map. The localization is accomplished by obtaining a node probability from a relative motion model and rotational invariant grid-map matching. The proposed method extracts a well-structured topological model of the environment, and the localization provides reliable node probability even when presented with sparse and uncertain sonar data. Experimental results demonstrate the performance of the proposed topological modeling and localization in a real home environment.     

BSPNN: boosted subspace probabilistic neural network for email security

In the modern age of Internet connectivity, advanced information systems have accumulated huge volumes of data. Such fast growing, tremendous amount of data, collected and stored in large databases has far exceeded our human ability to comprehend without proper tools. There has been a great deal of research conducted to explore the potential applications of Machine Learning technologies in Security Informatics. This article studies the Network Security Detection problems in which predictive models are constructed to detect network security breaches such as spamming. Due to overwhelming volume of data, complexity and dynamics of computer networks and evolving cyber threats, current security systems suffer limited performance with low detection accuracy and high number of false alarms. To address such performance issues, a novel Machine Learning algorithm, namely Boosted Subspace Probabilistic Neural Network (BSPNN), has been proposed which combines a Radial Basis Function Neural Network with an innovative diversity-based ensemble learning framework. Extensive empirical analyses suggested that BSPNN achieved high detection accuracy with relatively small computational complexity compared with other conventional detection methods.     

Localizing slab identification numbers in factory scene images

This paper deals with algorithms for text localization and character segmentation in images for process automation in the steel-making industry. Each character which comprises slab identification numbers may be corrupted severely before it is captured by network cameras. Therefore, proper processing is required to localize the target texts successfully. In this paper, we propose (1) a method to evaluate the closeness of an edge patch to the form of a closed contour, (2) an edge inspection method to determine character colors and estimate font thickness, and (3) three reasonable binarization methods to increase the performance of the algorithm for the detection of the left and right boundaries of the text rectangle. The experimental results show that the proposed algorithms are reliable.     

Dynamic deformation behavior of ultrafine-grained low-carbon steels fabricated by equal-channel angular pressing

The dynamic deformation behavior of ultrafine-grained low-carbon steels fabricated by equal-channel angular pressing (ECAP) was investigated in this study. Dynamic torsional tests, using a torsional Kolsky bar, were conducted on four steel specimens, two of which were annealed at 480 °C after ECAP, and then the test data were compared in terms of microstructures, tensile properties, and adiabatic shear-band formation. The equal-channel angular pressed specimen consisted of very fine, equiaxed grains of 0.2 to 0.3 μm in size, which were slightly coarsened after annealing. The dynamic torsional test results indicated that maximum shear stress decreased with increasing annealing time, whereas fracture shear strain increased. Some adiabatic shear bands were observed at the gage center of the dynamically deformed torsional specimen. Their width was smaller in the equal-channel angular pressed specimen than in the 1-hour-annealed specimen, but they were not found in the 24-hour-annealed specimen. Ultrafine, equiaxed grains of 0.05 to 0.2 μm in size were formed inside the adiabatic shear band, and their boundaries had characteristics of high-angle grain boundaries. These phenomena were explained by dynamic recrystallization due to a highly localized plastic strain and temperature rise during dynamic deformation.     

Modeling and finite element analysis of rod and wire steel rolling process

Two thermomechanical coupled elastic-plastic finite element （FE） models were developed for predicting the 12-pass continuous rolling process of GCrl 5 rod and wire steel. The distances between stands in the proposed models were set according to the actual values, and the billets were shortened in the models to reduce the calculation time. To keep the continuity of simulation, a technique was developed to transfer temperature data between the meshes of different models in terms of nodal parameters by interpolation functions. The different process variables related to the rolling process, such as temperature, total equivalent plastic strain, equivalent plastic strain rate, and contact friction force, were analyzed. Also, the proposed models were applied to analyze the reason for the occurrence of an excessive spread in width. Meanwhile, it was also utilized to assess the influence of the roll diameter change on the simulated results such as temperature and rolling force. The simulated results of temperature are found to agree well with the measured results.     

甲烷中四氢噻吩气体标准物质制备及应用

目的 为天然气加臭剂的测量活动提供可追溯性,以保证检测结果的准确可靠。方法 采用称量法研制了摩尔分数为1.00～20.00μmol/mol的甲烷中四氢噻吩气体标准物质,考查了该气体标准物质的均匀性和稳定性。依据该标准物质建立了硫化学发光检测器气相色谱仪(GC-SCD)测定甲烷中四氢噻吩的方法。结果 制得的气体标准物质相对扩展不确定度为2%,k=2,国家标准物质证书编号为GBW(E)062460,采用GC-SCD测定甲烷中四氢噻吩的方法,在摩尔分数为0～5.00μmol/mol的范围内,线性良好,相关系数r=1.000,检出限低至0.03μmol/mol,并应用于天然气样品的测试,7次测量的相对标准偏差为2.1%～3.4%。结论 基于有证标准物质进行量值溯源的GC-SCD测定甲烷中四氢噻吩的方法准确可靠,为天然气中加臭剂四氢噻吩的测量提供技术保障。     

Neuronal ApoE Regulates the Cell-to-Cell Transmission of α-Synuclein

The presence of protein inclusions, called Lewy bodies (LBs) and Lewy neurites (LNs), in the brain is the main feature of Parkinson’s disease (PD). Recent evidence that the prion-like propagation of α-synuclein (α-syn), as a major component of LBs and LNs, plays an important role in the progression of PD has gained much attention, although the molecular mechanism remains unclear. In this study, we evaluated whether neuronal ApoE regulates the cell-to-cell transmission of α-syn and explored its molecular mechanism using in vitro and in vivo model systems. We demonstrate that neuronal ApoE deficiency attenuates both α-syn uptake and release by downregulating LRP-1 and LDLR expression and enhancing chaperone-mediated autophagy activity, respectively, thereby contributing to α-syn propagation. In addition, we observed that α-syn propagation was attenuated in ApoE knockout mice injected with pre-formed mouse α-syn fibrils. This study will help our understanding of the molecular mechanisms underlying α-syn propagation.     

Fine Mapping and Functional Analysis of Major Regulatory Genes of Soluble Solids Content in Wax Gourd (Benincasa hispida)

Soluble solids content (SSC) is an important quality trait of wax gourd, but reports about its regulatory genes are scarce. In this study, the SSC regulatory gene BhSSC2.1 in wax gourd was mined via quantitative trait locus (QTL) mapping based on high-density genetic mapping containing 12 linkage groups (LG) and bulked segregant analysis (BSA)-seq. QTL mapping and BSA-seq revealed for the first time that the SSC QTL (107.658–108.176 cM) of wax gourd was on Chr2 (LG2). The interpretable phenotypic variation rate and maximum LOD were 16.033% and 6.454, respectively. The QTL interval contained 13 genes. Real-time fluorescence quantitative expression analysis, functional annotation, and sequence analysis suggested that Bch02G016960, named BhSSC2.1, was a candidate regulatory gene of the SSC in wax gourd. Functional annotation of this gene showed that it codes for a NADP-dependent malic enzyme. According to BhSSC2.1 sequence variation, an InDel marker was developed for molecular marker-assisted breeding of wax gourd. This study will lay the foundation for future studies regarding breeding and understanding genetic mechanisms of wax gourd.     

HDAC8-Selective Inhibition by PCI-34051 Enhances the Anticancer Effects of ACY-241 in Ovarian Cancer Cells

HDAC6 is overexpressed in ovarian cancer and is known to be correlated with tumorigenesis. Accordingly, ACY-241, a selective HDAC6 inhibitor, is currently under clinical trial and has been tested in combination with various drugs. HDAC8, another member of the HDAC family, has recently gained attention as a novel target for cancer therapy. Here, we evaluated the synergistic anticancer effects of PCI-34051 and ACY-241 in ovarian cancer. Among various ovarian cancer cells, PCI-34051 effectively suppresses cell proliferation in wild-type p53 ovarian cancer cells compared with mutant p53 ovarian cancer cells. In ovarian cancer cells harboring wild-type p53, PCI-34051 in combination with ACY-241 synergistically represses cell proliferation, enhances apoptosis, and suppresses cell migration. The expression of pro-apoptotic proteins is synergistically upregulated, whereas the expressions of anti-apoptotic proteins and metastasis-associated proteins are significantly downregulated in combination treatment. Furthermore, the level of acetyl-p53 at K381 is synergistically upregulated upon combination treatment. Overall, co-inhibition of HDAC6 and HDAC8 through selective inhibitors synergistically suppresses cancer cell proliferation and metastasis in p53 wild-type ovarian cancer cells. These results suggest a novel approach to treating ovarian cancer patients and the therapeutic potential in developing HDAC6/8 dual inhibitors.