Gendering Experiences of Anti-Semitism: A Quantitative Analysis of Discrimination in Europe

Little is known about the gendered dimension of anti-Semitism. Emerging from a literature review on social identity theory, anti-Semitism, sexism, and Jewish feminism, I demonstrate the urgency of examining the link between gender and experiences of anti-Semitism, using the FRA’s 2018 dataset “Experiences and Perceptions of Antisemitism: Second Survey on Discrimination and Hate Crime against Jews in the EU,” a large-scale survey of Jews in thirteen countries across Europe. The independent variable is gender identity. Five dependent variables relate to experiences of sex/gender discrimination, physical attacks, offensive/threatening comments, offensive gestures/staring, and online harassment. Using five control variables—being identifiable as a Jew in public, country, Jewish identity, education level, and Jewish population in one’s neighborhood—I engage with descriptive statistics and binary logistic regression analysis to analyze my variables. The findings show that while women are more likely to experience gender discrimination, men are significantly more likely to experience anti-Semitism

Structure of the clean Ta(100) surface

The clean Ta(100) surface and some aspects of hydrogen adsorption have been studied by LEED and AES. The thorough examination of LEED patterns did not provide any evidence for an atomic reconstruction of the clean surface over the entire temperature range investigated, 150–600 K. The r-factor analysis used for comparison between measured and calculated I–V spectra yields a contraction of the topmost layer spacing of about 11% and an expansion of the second layer spacing of about 1% compared to the bulk value. The hydrogen adsorption does not induce any superstructures, but small hydrogen exposures lass then 1 L influence I–V spectra substantially

Logarithmic interaction under periodic boundary conditions: Closed form formulas for energy and forces

A method is given to obtain closed form formulas for the energy and forces for an aggregate of charges interacting via a logarithmic interaction under periodic boundary conditions. The work done here is a generalization of Glasser's results [M. L. Glasser, J. Math. Phys. 15, 188 (1974)] and is obtained with a different and simpler method than that by Stremler [M. A. Stremler, J. Math. Phys. 45, 3584 (2004)]. The simplicity of the formulas derived here makes them extremely convenient in a computer simulation

Global Ultrasound Elastography Using Convolutional Neural Network

Displacement estimation is very important in ultrasound elastography and failing to estimate displacement correctly results in failure in generating strain images. As conventional ultrasound elastography techniques suffer from decorrelation noise, they are prone to fail in estimating displacement between echo signals obtained during tissue distortions. This study proposes a novel elastography technique which addresses the decorrelation in estimating displacement field. We call our method GLUENet (GLobal Ultrasound Elastography Network) which uses deep Convolutional Neural Network (CNN) to get a coarse time-delay estimation between two ultrasound images. This displacement is later used for formulating a nonlinear cost function which incorporates similarity of RF data intensity and prior information of estimated displacement. By optimizing this cost function, we calculate the finer displacement by exploiting all the information of all the samples of RF data simultaneously. The Contrast to Noise Ratio (CNR) and Signal to Noise Ratio (SNR) of the strain images from our technique is very much close to that of strain images from GLUE. While most elastography algorithms are sensitive to parameter tuning, our robust algorithm is substantially less sensitive to parameter tuning.Comment: 4 pages, 4 figures; added acknowledgment section, submission type late

Confluent Orthogonal Drawings of Syntax Diagrams

We provide a pipeline for generating syntax diagrams (also called railroad diagrams) from context free grammars. Syntax diagrams are a graphical representation of a context free language, which we formalize abstractly as a set of mutually recursive nondeterministic finite automata and draw by combining elements from the confluent drawing, layered drawing, and smooth orthogonal drawing styles. Within our pipeline we introduce several heuristics that modify the grammar but preserve the language, improving the aesthetics of the final drawing.Comment: GD 201