Symbol detection in online handwritten graphics using Faster R-CNN

Symbol detection techniques in online handwritten graphics (e.g. diagrams and mathematical expressions) consist of methods specifically designed for a single graphic type. In this work, we evaluate the Faster R-CNN object detection algorithm as a general method for detection of symbols in handwritten graphics. We evaluate different configurations of the Faster R-CNN method, and point out issues relative to the handwritten nature of the data. Considering the online recognition context, we evaluate efficiency and accuracy trade-offs of using Deep Neural Networks of different complexities as feature extractors. We evaluate the method on publicly available flowchart and mathematical expression (CROHME-2016) datasets. Results show that Faster R-CNN can be effectively used on both datasets, enabling the possibility of developing general methods for symbol detection, and furthermore, general graphic understanding methods that could be built on top of the algorithm.Comment: Submitted to DAS-201

Critical Point in Self-Organized Tissue Growth

We present a theory of pattern formation in growing domains inspired by biological examples of tissue development. Gradients of signaling molecules regulate growth, while growth changes these graded chemical patterns by dilution and advection. We identify a critical point of this feedback dynamics, which is characterized by spatially homogeneous growth and proportional scaling of patterns with tissue length. We apply this theory to the biological model system of the developing wing of the fruit fly \textit{Drosophila melanogaster} and quantitatively identify signatures of the critical point.Comment: 5 pages, 3 figure

The impact of GSAs, school size, and geographic location on school climate in South Texas

While gay-straight alliances (GSAs) play a role in improving the well-being and sense of safety for LGBTQ students, additional factors such as school size, geographical location, and the community climate at large may have more controlling implications for school diversity and acceptance. This survey research type, quantitative study, investigates the retrospective responses of subjects from two Hispanic-Serving Institutions to examine the impact of GSAs, school size, and geographic location on school climates in rural South Texas high schools. Results suggest that the effect of GSAs on school diversity and acceptance may be diminished in a conservative, rural setting. Other factors (school size, geographic location, and community climate at large) may play a greater role in establishing school diversity and acceptance. Further research is warranted to uncover the mechanisms that drive school diversity and acceptance in conservative, rural geographical locations like South Texas