A new method for providing a model to analyze a kite wind turbine

The ultimate purpose of simulating kite wind turbine is to predict the kite movement and the power generated by its mechanism. To simulate because when the initial estimate of the intended values is found, we may have to manipulate the simulation to find the most efficient design for manufacturing our system and then predict the final power generated for our mechanism. Simulation for the system is based on two parts: Simulation of steady-state and dynamic model, which include differential equations. In this paper, we have presented a novel idea for a proper simulation of the system based on the two static and dynamic parts in order to numerical solution of the required amount and to calculate the output power.Keywords: Kite wind turbine; Simulation; Static model; Dynamic model;Winch; Torqu

Statistical Inference via Bootstrapping for Measures of Inequality

In this paper we consider the use of bootstrap methods to compute interval estimates and perform hypothesis tests for decomposable measures of economic inequality. The bootstrap potentially represents a significant gain over available asymptotic intervals because it provides an easily implemented solution to the Behrens-Fisher problem. Two applications of this approach, using the PSID (for the study of taxation) and the NLSY (for the study of youth inequality), to the Gini coefficient and Theil's entropy measures of inequality, are provided. The results suggest that (i) statistical inference is essential even when large samples are available, and (ii) the bootstrap appears to perform well in this setting.

Differentiating Noninvasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features from Classic Papillary Thyroid Carcinoma: Analysis of Cytomorphologic Descriptions Using a Novel Machine-Learning Approach.

Background:Recent studies show various cytomorphologic features that can assist in the differentiation of classic papillary thyroid carcinoma (cPTC) from noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Differentiating these two entities changes the clinical management significantly. We evaluated the performance of support vector machine (SVM), a machine learning algorithm, in differentiating cases of NIFTP and encapsulated follicular variant of papillary thyroid carcinoma with no capsular or lymphovascular invasion (EFVPTC) from cases of cPTC with the use of microscopic descriptions. SVM is a supervised learning algorithm used in classification problems. It assigns the input data to one of two categories by building a model based on a set of training examples (learning) and then using that learned model to classify new examples. Methods:Surgical pathology cases with the diagnosis of cPTC, NIFTP, and EFVPTC, were obtained from the laboratory information system. Only cases with existing fine-needle aspiration matching the tumor and available microscopic description were included. NIFTP cases with ipsilateral micro-PTC were excluded. The final cohort consisted of 59 cases (29 cPTCs and 30 NIFTP/EFVPTCs). Results:SVM successfully differentiated cPTC from NIFTP/EFVPTC 76.05 ± 0.96% of times (above chance, P \u3c 0.05) with the sensitivity of 72.6% and specificity of 81.6% in detecting cPTC. Conclusions:This machine learning algorithm was successful in distinguishing NIFTP/EFVPTC from cPTC. Our results are compatible with the prior studies, which show cytologic features are helpful in differentiating these two entities. Furthermore, this study shows the power and potential of this approach for clinical use and in developing data-driven scoring systems, which can guide cytopathology and surgical pathology diagnosis

Germline BRCA2 mutations and the risk of esophageal squamous cell carcinoma

The incidence of esophageal squamous cell carcinoma (ESCC) is very high among the Turkmen population of Iran. Family studies suggest a genetic component to the disease. Turkmen are ethnically homogenous and are well suited for genetic studies. A previous study from China suggested that BRCA2 might play a role in the etiology of ESCC. We screened for mutations in the coding region of the BRCA2 gene in the germline DNA of 197 Turkmen patients with ESCC. A nonsense variant, K3326X, was identified in 9 of 197 cases (4.6) vs 2 of 254 controls (0.8) (OR=6.0, 95 CI=1.3-28; P=0.01). This mutation leads to the loss of the C-terminal domain of the BRCA2 protein, a part of the region of interaction with the FANCD2 protein. We observed nine other BRCA2 variants in single cases only, including two deletions, and seven missense mutations. Six of these were judged to be pathogenic. In total, a suspicious deleterious BRCA2 variant was identified in 15 of 197 ESCC cases (7.6). © 2008 Nature Publishing Group All rights reserved

The prevalence of BRCA1 mutations among young women with triple-negative breast cancer

<p>Abstract</p> <p>Background</p> <p>Molecular screening for BRCA1 and BRCA2 mutations is now an established component of risk evaluation and management of familial breast cancer. Features of hereditary breast cancer include an early age-of-onset and over-representation of the 'triple-negative' phenotype (negative for estrogen-receptor, progesterone-receptor and HER2). The decision to offer genetic testing to a breast cancer patient is usually based on her family history, but in the absence of a family history of cancer, some women may qualify for testing based on the age-of-onset and/or the pathologic features of the breast cancer.</p> <p>Methods</p> <p>We studied 54 women who were diagnosed with high-grade, triple-negative invasive breast cancer at or before age 40. These women were selected for study because they had little or no family history of breast or ovarian cancer and they did not qualify for genetic testing using conventional family history criteria. BRCA1 screening was performed using a combination of fluorescent multiplexed-PCR analysis, BRCA1 exon-13 6 kb duplication screening, the protein truncation test (PTT) and fluorescent multiplexed denaturing gradient gel electrophoresis (DGGE). All coding exons of BRCA1 were screened. The two large exons of BRCA2 were also screened using PTT. All mutations were confirmed with direct sequencing.</p> <p>Results</p> <p>Five deleterious BRCA1 mutations and one deleterious BRCA2 mutation were identified in the 54 patients with early-onset, triple-negative breast cancer (11%).</p> <p>Conclusion</p> <p>Women with early-onset triple-negative breast cancer are candidates for genetic testing for BRCA1, even in the absence of a family history of breast or ovarian cancer.</p

Statistical analysis of inequality with decompositions: the Canadian experience

This study carries out a decomposition of Theil-entropy measures into a between-group component, based on factors such as education, age, gender, and marital status, and a component representing inequality within each group. We apply a bootstrapping technique to measures of inequality to enable statistical inference. Trends in household income inequality in Canada are investigated using data from 1991 to 1997 drawn from Survey of Consumer Finance. We find an evident trend toward increasing inequality of household incomes between the years 1991–1997, during which the economy was recovering from a steep recession. Although most of the increase in measured inequality is attributed to the `within-group' component, we find the change in `between-group' inequality to be significant for education, age, and marital status. Copyright Springer-Verlag Berlin Heidelberg 2003Key words: Inequality, Decomposition, Bootstrapping, Canada,