Open Knowledge Report (2017-2018)

IUPUI University Library's Open Knowledge Report (2017-2018).This report includes all Wikimedia-related activities from January 1st, 2017 to December 31, 2018. It covers events hosted at IUPUI University Library and the Ruth Lilly Medical Library, and projects focused on making our archival collections, library-hosted publications, and the scholarly output of our faculty members more accessible. In addition, it includes a list of relevant publications as well as presentations given at various conferences as a way of sharing ongoing efforts and increasing awareness of Open Knowledge projects

Necessary Reconstruction: The Child Welfare System

This research has been composed of both primary and secondary research aimed to shine light on the most pressing issues within the child welfare system. It not only demonstrates the detrimental tolls the system has had on the children but also the tolls it has had on the public servants working within the system. This research is a gateway to awareness of the realities and necessary changes the system so desperately needs

Taller de matemáticas emocionales para alumnos de la preparatoria de la Universidad Lasalle

El Taller de Matemáticas Emocionales (ME) se diseñó para proporcionar recursos adicionales a los alumnos de la Preparatoria de la Universidad Lasalle. Es un proyecto interdisciplinario de intervención; de apoyo psicopedagógico y disciplinario, lo cual dio sustento a la utilización de los conceptos del dominio afectivo de las matemáticas: Actitudes, Emociones y Creencias. El trabajo en el taller incluye estrategias de autoconocimiento y meta cognitivas, concatenadas con ejercicios algebraicos que refuerzan sus conocimientos. Las estrategias de autoconocimiento dirigidas a mejorar la autorregulación del alumno y los elementos del dominio afectivo hacia las matemáticas, son sustentadas por la teoría constructivista que propone un estudiante más activo y responsable de su aprendizaje. Los estudiantes lograron mejorar en su curso curricular de matemáticas

Inferring phylogenetic networks with maximum pseudolikelihood under incomplete lineage sorting

Phylogenetic networks are necessary to represent the tree of life expanded by edges to represent events such as horizontal gene transfers, hybridizations or gene flow. Not all species follow the paradigm of vertical inheritance of their genetic material. While a great deal of research has flourished into the inference of phylogenetic trees, statistical methods to infer phylogenetic networks are still limited and under development. The main disadvantage of existing methods is a lack of scalability. Here, we present a statistical method to infer phylogenetic networks from multi-locus genetic data in a pseudolikelihood framework. Our model accounts for incomplete lineage sorting through the coalescent model, and for horizontal inheritance of genes through reticulation nodes in the network. Computation of the pseudolikelihood is fast and simple, and it avoids the burdensome calculation of the full likelihood which can be intractable with many species. Moreover, estimation at the quartet-level has the added computational benefit that it is easily parallelizable. Simulation studies comparing our method to a full likelihood approach show that our pseudolikelihood approach is much faster without compromising accuracy. We applied our method to reconstruct the evolutionary relationships among swordtails and platyfishes ($Xiphophorus$: Poeciliidae), which is characterized by widespread hybridizations