Clicks and Cliques. Exploring the Soul of the Community

In the paper we analyze 26 communities across the United States with the objective to understand what attaches people to their community and how this attachment differs among communities. How different are attached people from unattached? What attaches people to their community? How different are the communities? What are key drivers behind emotional attachment? To address these questions, graphical, supervised and unsupervised learning tools were used and information from the Census Bureau and the Knight Foundation were combined. Using the same pre-processed variables as Knight (2010) most likely will drive the results towards the same conclusions than the Knight foundation, so this paper does not use those variables

New records and geographic distribution map of Bothropoides diporus Cope, 1862 (Reptilia: Viperidae)

We provide two new records of Bothropoides diporus for Neuquén province, northern Patagonia, Argentina. Both records are the second and third for this species in this province. One of these records, from the northern slope of Auca Mahuida Mountain, extends approximately 120 km to the north the present known geographic distribution of this species in Neuquén province.Fil: Minoli, Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; ArgentinaFil: Janis Alvarez, Diego. Universidade Federal do Rio Grande do Sul; BrasilFil: Avila, Luciano Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Nacional Patagónico; Argentin

Top-antitop resonance searches beyond 1 TeV

We perform a general parton level analysis for the search of heavy resonant states in the production of top-antitop pairs at the LHC with an integrated luminosity of 30 fb^-1. We assume the existence of resonances that only couple to quarks and propose kinematic cuts in order to increase the amount of events produced through quark-annihilation. We study the interplay between different variables and their impact on the purity of the selected sample. We make focus on the longitudinal ($\beta$) and transverse ($p_T$) momentum of the top-antitop pair, and the scattering angle ($\theta$) in the center of mass reference frame. We observe that $\beta$ is replaced by $\theta$ as a suitable discriminating variable of quark-annihilation processes for invariant masses above 1 TeV. Finally, we illustrate the analysis with a gluon resonance of 1.5 TeV and show the improvement in the sensitivity of the signal when cuts on $\theta$ are imposed.Comment: 19 pages and 6 figure

Student performance predictive models using LMS data in Primary Schools

Plan Ceibal is a public policy implemented in Uruguay, it is part of the global initiative One Lap- top per Child (OLPC, 2005). The basic feature is providing every student and teacher in primary school with a laptop or tablet and internet access. Different data sets were combined, students and teachers activities registered in the Learning Management System (LMS) and student’s performance in national standardized tests. Data were used to compute student’s engagement indexes, combining motivation, creativity, velocity and performance. Statistical models were used to determine key drivers of LMS use, this is relevant to define educational policies based on evidence. Models for LMS use are fitted for several regional levels. Additionally, statistical learning methods were fitted to predict student’s performance in national standardized test us- ing as predictor variables different constructed usage indexes from the LMS platform. A major challenge was how to deal with sub-grouping data structure into machine learning algorithms, usually developed for independent observations. Initial results suggest school district is the main driver of the technology usage in the classroom.ANI

Bayesian analysis of high-dimensional count data

This thesis describes my research work in past years in the Statistic Department of Iowa State University. There are several key statistical features common to the whole thesis. In the first place, all the statistical methods are developed taking a Bayesian perspective to conduct the statistical inference. A second common feature of the two main parts is that both correspond to high-dimensional problems. In the first case, because a large amount of information for a few individuals is available, and in the second part due to model space is really large which brings computational intractability issues. Finally, the response variable in all data used here is a positive count, in the first part, it is associated with the gene expression while in the second part it represents a number of automobile crashes

k-core decomposition: a tool for the visualization of large scale networks

We use the k-core decomposition to visualize large scale complex networks in two dimensions. This decomposition, based on a recursive pruning of the least connected vertices, allows to disentangle the hierarchical structure of networks by progressively focusing on their central cores. By using this strategy we develop a general visualization algorithm that can be used to compare the structural properties of various networks and highlight their hierarchical structure. The low computational complexity of the algorithm, O(n+e), where 'n' is the size of the network, and 'e' is the number of edges, makes it suitable for the visualization of very large sparse networks. We apply the proposed visualization tool to several real and synthetic graphs, showing its utility in finding specific structural fingerprints of computer generated and real world networks