Art to empower: designing and implementing a contemporary visual culture art education for urban elementary institutions with implications for classroom practice

The following paper offers a comprehensive historiography of the curricular trends and approaches for the teaching of elementary visual arts within the discourse of Art Education. The exploration begins with an overview of the modernist, Discipline Based Art Education curriculum, including its origins and implementation within the U.S., public K-8 school system. In this section I offer an assessment of DBAE???s curricular strengths and weaknesses. Next, the text moves into an examination of post-modern, contemporary curricular approaches to teaching visual arts, more specifically, the visual culture theory. With this, I introduce a discussion about the current reality of arts education within the urban, public school system of Chicago, Illinois. This section offers insight into current art education trends and exposes the discrepancy of resources for visual arts education among Chicago???s elementary institutions. Finally, I offer a sample visual arts curriculum designed to empower students to take responsibility for their learning and success

Wedge Sampling for Computing Clustering Coefficients and Triangle Counts on Large Graphs

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of such graphs. Some of the most useful graph metrics are based on triangles, such as those measuring social cohesion. Algorithms to compute them can be extremely expensive, even for moderately-sized graphs with only millions of edges. Previous work has considered node and edge sampling; in contrast, we consider wedge sampling, which provides faster and more accurate approximations than competing techniques. Additionally, wedge sampling enables estimation local clustering coefficients, degree-wise clustering coefficients, uniform triangle sampling, and directed triangle counts. Our methods come with provable and practical probabilistic error estimates for all computations. We provide extensive results that show our methods are both more accurate and faster than state-of-the-art alternatives.Comment: Full version of SDM 2013 paper "Triadic Measures on Graphs: The Power of Wedge Sampling" (arxiv:1202.5230

Triadic Measures on Graphs: The Power of Wedge Sampling

Graphs are used to model interactions in a variety of contexts, and there is a growing need to quickly assess the structure of a graph. Some of the most useful graph metrics, especially those measuring social cohesion, are based on triangles. Despite the importance of these triadic measures, associated algorithms can be extremely expensive. We propose a new method based on wedge sampling. This versatile technique allows for the fast and accurate approximation of all current variants of clustering coefficients and enables rapid uniform sampling of the triangles of a graph. Our methods come with provable and practical time-approximation tradeoffs for all computations. We provide extensive results that show our methods are orders of magnitude faster than the state-of-the-art, while providing nearly the accuracy of full enumeration. Our results will enable more wide-scale adoption of triadic measures for analysis of extremely large graphs, as demonstrated on several real-world examples

A Scalable Null Model for Directed Graphs Matching All Degree Distributions: In, Out, and Reciprocal

Degree distributions are arguably the most important property of real world networks. The classic edge configuration model or Chung-Lu model can generate an undirected graph with any desired degree distribution. This serves as a good null model to compare algorithms or perform experimental studies. Furthermore, there are scalable algorithms that implement these models and they are invaluable in the study of graphs. However, networks in the real-world are often directed, and have a significant proportion of reciprocal edges. A stronger relation exists between two nodes when they each point to one another (reciprocal edge) as compared to when only one points to the other (one-way edge). Despite their importance, reciprocal edges have been disregarded by most directed graph models. We propose a null model for directed graphs inspired by the Chung-Lu model that matches the in-, out-, and reciprocal-degree distributions of the real graphs. Our algorithm is scalable and requires $O(m)$ random numbers to generate a graph with $m$ edges. We perform a series of experiments on real datasets and compare with existing graph models.Comment: Camera ready version for IEEE Workshop on Network Science; fixed some typos in tabl

Ventricular tachycardia associated with lacosamide co-medication in drug-resistant epilepsy.

We report a case of sustained ventricular tachycardia following the initiation of lacosamide as adjunctive epilepsy treatment. A 49-year-old male with intractable frontal lobe seizures experienced severe ventricular tachycardia following the addition of 400 mg lacosamide to his existing regimen of carbamazepine, lamotrigine, clonazepam, and valproate. The tachycardia occurred during a cardiac stress test; stress tests prior to initiation of lacosamide were normal. Conduction defects, including QRS prolongation, persisted during hospitalization until lacosamide was discontinued. The patient had no prior history of cardiac arrhythmia but did possess cardiac risk factors, including hypertension, hypercholesterolemia, and low heart rate variability. This case represents one part of a growing body of literature suggesting a link between arrhythmia and use of lacosamide, which enhances slow inactivation of sodium channels in both the brain and the heart. We believe further study may be necessary to assess the safety of lacosamide in epilepsy patients with cardiac risk factors