A survey of parametric modelling methods for designing the head of a high-speed train

With the continuous increase of the running speed, the head shape of the high-speed train (HST) turns out to be a critical factor for further speed boost. In order to cut down the time used in the HST head design and improve the modelling efficiency, various parametric modelling methods have been widely applied in the optimization design of the HST head to obtain an optimal head shape so that the aerodynamic effect acting on the head of HSTs can be reduced and more energy can be saved. This paper reviews these parametric modelling methods and classifies them into four categories: 2D, 3D, CATIA-based, and mesh deformation-based parametric modelling methods. Each of the methods is introduced, and the advantages and disadvantages of these methods are identified. The simulation results are presented to demonstrate that the aerodynamic performance of the optimal models constructed by these parametric modelling methods has been improved when compared with numerical calculation results of the original models or the prototype models of running trains. Since different parametric modelling methods used different original models and optimization methods, few publications could be found which compare the simulation results of the aerodynamic performance among different parametric modelling methods. In spite of this, these parametric modelling methods indicate more local shape details will lead to more accurate simulation results, and fewer design variables will result in higher computational efficiency. Therefore, the ability of describing more local shape details with fewer design variables could serve as a main specification to assess the performance of various parametric modelling methods. The future research directions may concentrate on how to improve such ability

Epidemics in partially overlapped multiplex networks

Many real networks exhibit a layered structure in which links in each layer reflect the function of nodes on different environments. These multiple types of links are usually represented by a multiplex network in which each layer has a different topology. In real-world networks, however, not all nodes are present on every layer. To generate a more realistic scenario, we use a generalized multiplex network and assume that only a fraction $q$ of the nodes are shared by the layers. We develop a theoretical framework for a branching process to describe the spread of an epidemic on these partially overlapped multiplex networks. This allows us to obtain the fraction of infected individuals as a function of the effective probability that the disease will be transmitted $T$. We also theoretically determine the dependence of the epidemic threshold on the fraction $q > 0$ of shared nodes in a system composed of two layers. We find that in the limit of $q \to 0$ the threshold is dominated by the layer with the smaller isolated threshold. Although a system of two completely isolated networks is nearly indistinguishable from a system of two networks that share just a few nodes, we find that the presence of these few shared nodes causes the epidemic threshold of the isolated network with the lower propagating capacity to change discontinuously and to acquire the threshold of the other network.Comment: 13 pages, 4 figure

G-CSFR Ubiquitination Critically Regulates Myeloid Cell Survival and Proliferation

The granulocyte colony-stimulating factor receptor (G-CSFR) is a critical regulator of granulopoiesis. Mutations in the G-CSFR in patients with severe congenital neutropenia (SCN) transforming to acute myelogenous leukemia (AML) have been shown to induce hypersensitivity and enhanced growth responses to G-CSF. Recent studies have demonstrated the importance of the ubiquitin/proteasome system in the initiation of negative signaling by the G-CSFR. To further investigate the role of ubiquitination in regulating G-CSFR signaling, we generated a mutant form of the G-CSFR (K762R/G-CSFR) which abrogates the attachment of ubiquitin to the lysine residue at position 762 of the G-CSFR that is deleted in the Δ716 G-CSFR form isolated from patients with SCN/AML. In response to G-CSF, mono-/polyubiquitination of the G-CSFR was impaired in cells expressing the mutant K762R/G-CSFR compared to cells transfected with the WT G-CSFR. Cells stably transfected with the K762R/G-CSFR displayed a higher proliferation rate, increased sensitivity to G-CSF, and enhanced survival following cytokine depletion, similar to previously published data with the Δ716 G-CSFR mutant. Activation of the signaling molecules Stat5 and Akt were also increased in K762R/G-CSFR transfected cells in response to G-CSF, and their activation remained prolonged after G-CSF withdrawal. These results indicate that ubiquitination is required for regulation of G-CSFR-mediated proliferation and cell survival. Mutations that disrupt G-CSFR ubiquitination at lysine 762 induce aberrant receptor signaling and hyperproliferative responses to G-CSF, which may contribute to leukemic transformation

Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

Thermoelectric properties of Cu-dispersed bi0.5sb1.5te3

A novel and simple approach was used to disperse Cu nanoparticles uniformly in the Bi0.5Sb1.5Te3 matrix, and the thermoelectric properties were evaluated for the Cu-dispersed Bi0.5Sb1.5Te3. Polycrystalline Bi0.5Sb1.5Te3 powder prepared by encapsulated melting and grinding was dry-mixed with Cu(OAc)2 powder. After Cu(OAc)2 decomposition, the Cu-dispersed Bi0.5Sb1.5Te3 was hot-pressed. Cu nanoparticles were well-dispersed in the Bi0.5Sb1.5Te3 matrix and acted as effective phonon scattering centers. The electrical conductivity increased systematically with increasing level of Cu nanoparticle dispersion. All specimens had a positive Seebeck coefficient, which confirmed that the electrical charge was transported mainly by holes. The thermoelectric figure of merit was enhanced remarkably over a wide temperature range of 323-523 K

Silencing of IQGAP1 by shRNA inhibits the invasion of ovarian carcinoma HO-8910PM cells in vitro

<p>Abstract</p> <p>Background</p> <p>IQGAP1 is a scaffolding protein and overexpressed in many human tumors, including ovarian cancer. However, the contribution of IQGAP1 to invasive properties of ovarian cancer cells remains unknown. Here, we investigated the effect of IQGAP1-specific short hairpin RNA (shRNA) expressing plasmids on metastatic potential of ovarian cancer HO-8910PM cells.</p> <p>Methods</p> <p>We used RT-PCR and Western blot analysis to characterize expression of IQGAP1 in three human ovarian cancer-derived cell lines SK-OV-3, HO-8910 and HO-8910PM. We then determined whether expression of endogenous IQGAP1 correlated with invasive and migratory ability by using an in vitro Matrigel assay and cell migration assay. We further knocked down IQGAP1 using shRNA expressing plasmids controlled by U1 promoter in HO-8910PM cells and examined the proliferation activity, invasive and migration potential of IQGAP1 shRNA transfectants using MTT assay, in vitro Matrigel-coated invasion assay and migration assay.</p> <p>Results</p> <p>IQGAP1 expression level seemed to be closely associated with the enhanced invasion and migration in ovarian cancer cell lines. Levels of both IQGAP1 mRNA and protein were significantly reduced in HO-8910PM cells transfected with plasmid-based IQGAP1-specific shRNAs. RNAi-mediated knockdown of IQGAP1 expression in HO-8910PM cells resulted in a significant decrease in cell invasion and migration.</p> <p>Conclusion</p> <p>Our findings support the hypothesis that IQGAP1 promotes tumor progression and identify IQGAP1 as a potential therapeutic strategy for ovarian cancer and some other tumors with over-expression of the IQGAP1 gene.</p

Assessing Internet addiction using the parsimonious Internet addiction components model - a preliminary study [forthcoming]

Internet usage has grown exponentially over the last decade. Research indicates that excessive Internet use can lead to symptoms associated with addiction. To date, assessment of potential Internet addiction has varied regarding populations studied and instruments used, making reliable prevalence estimations difficult. To overcome the present problems a preliminary study was conducted testing a parsimonious Internet addiction components model based on Griffiths’ addiction components (2005), including salience, mood modification, tolerance, withdrawal, conflict, and relapse. Two validated measures of Internet addiction were used (Compulsive Internet Use Scale [CIUS], Meerkerk et al., 2009, and Assessment for Internet and Computer Game Addiction Scale [AICA-S], Beutel et al., 2010) in two independent samples (ns = 3,105 and 2,257). The fit of the model was analysed using Confirmatory Factor Analysis. Results indicate that the Internet addiction components model fits the data in both samples well. The two sample/two instrument approach provides converging evidence concerning the degree to which the components model can organize the self-reported behavioural components of Internet addiction. Recommendations for future research include a more detailed assessment of tolerance as addiction component

In silico analysis and verification of S100 gene expression in gastric cancer

<p>Abstract</p> <p>Background</p> <p>The S100 protein family comprises 22 members whose protein sequences encompass at least one EF-hand Ca²⁺binding motif. They were involved in the regulation of a number of cellular processes such as cell cycle progression and differentiation. However, the expression status of S100 family members in gastric cancer was not known yet.</p> <p>Methods</p> <p>Combined with analysis of series analysis of gene expression, virtual Northern blot and microarray data, the expression levels of S100 family members in normal and malignant stomach tissues were systematically investigated. The expression of S100A3 was further evaluated by quantitative RT-PCR.</p> <p>Results</p> <p>At least 5 S100 genes were found to be upregulated in gastric cance by in silico analysis. Among them, four genes, including S100A2, S100A4, S100A7 and S100A10, were reported to overexpressed in gastric cancer previously. The expression of S100A3 in eighty patients of gastric cancer was further examined. The results showed that the mean expression levels of S100A3 in gastric cancer tissues were 2.5 times as high as in adjacent non-tumorous tissues. S100A3 expression was correlated with tumor differentiation and TNM (Tumor-Node-Metastasis) stage of gastric cancer, which was relatively highly expressed in poorly differentiated and advanced gastric cancer tissues (<it>P </it>< 0.05).</p> <p>Conclusion</p> <p>To our knowledge this is the first report of systematic evaluation of S100 gene expressions in gastric cancers by multiple in silico analysis. The results indicated that overexpression of S100 gene family members were characteristics of gastric cancers and S100A3 might play important roles in differentiation and progression of gastric cancer.</p

To share or not to share: the optimal advertising effort with asymmetric advertising effectiveness

In this paper, we study a two-stage model in which a manufacturer expands to a new market through a local retailer and has private information on the advertising effectiveness. The manufacturer chooses the information sharing format with the retailer, either no information sharing or mandatory information sharing. Under no information sharing format, the manufacturer and the retailer play a signaling game. We derive both separating and pooling equilibria and conduct equilibrium refinements for the signaling game. Under mandatory information sharing format, the manufacturer simply informs the retailer the advertising effectiveness. We also establish the stylized model and derive the optimal advertising effort. By comparing the manufacturer’s ex ante profit under the two information sharing formats, we find that the manufacturer always prefers mandatory information sharing, under which both the advertising effort and profit can be higher. We also observe that unlike the common case that the channel members may have different preference over the information sharing formats, the manufacturer and the retailer can actually achieve alignment. While some previous studies suggest that the manufacturer and the retailer may have different preference over the information sharing formats, we find that they can actually achieve alignment with asymmetric information on advertising effectiveness

Multiple perspectives on the attribution of the extreme European summer of 2012 to climate change

Summer 2012 was very wet in northern Europe, and unusually dry and hot in southern Europe. We use multiple approaches to determine whether anthropogenic forcing made the extreme European summer of 2012 more likely. Using a number of observation- and model-based methods, we find that there was an anthropogenic contribution to the extremes in southern Europe, with a qualitative consensus across all methodologies. There was a consensus across the methodologies that there has been a significant increase in the risk of hot summers in southern Europe with climate change. Most approaches also suggested a slight drying, but none of the results were statistically significant. The unusually wet summer in northern Europe was made more likely by the observed atmospheric circulation pattern in 2012, but no evidence was found for a long-term trend in circulation