An Iterative Beam Search Algorithm for Degenerate Primer Selection

Single Nucleotide Polymorphism (SNP) Genotyping is an important molecular genetics process in the early stages of producing results that will be useful in the medical field. Due to inherent complexities in DNA manipulation and analysis, many different methods have been proposed for a standard assay. One of the proposed techniques for performing SNP Genotyping requires amplifying regions of DNA surrounding a large number of SNP loci. In order to automate a portion of this particular method, it is necessary to select a set of primers for the experiment. Selecting these primers can be formulated as the Multiple Degenerate Primer Design (MDPD) problem. In this thesis, we describe an iterative beam-search algorithm, Multiple, It-erative Primer Selector (MIPS), for MDPD. Theoretical and experimental analyses show that this algorithm performs well compared to the limits of degenerate primer design. Furthermore, MIPS outperforms an existing algorithm which was designed for a related degenerate primer selection problem. Further analysis shows that, due to the composition of the human genome, the results from MIPS may not be realized in practice. Consequently, we address the challenges involved in selecting a suitable set of degenerate primers and possible future improvements to the algorithm

NATURE VERSUS NURTURE: CAMPUS INVOLVEMENT’S EFFECT ON STUDENT LEADERSHIP DEVELOPMENT

The purpose of this research was to find if leadership skills are developed from co-curricular involvement. Research would determine whether natural-born leaders were drawn to student involvement opportunities, or whether involvement develops the average students’ leadership skills. To arrive at a conclusion, research asked the question “Does involvement on a college campus develop leadership skills?” Research was answered by quantitative research. Fifty undergraduate students from a private Midwestern university were surveyed. Each participant was given two assessments. One was a leadership self-assessment and another was a campus involvement assessment. The campus involvement assessment was created for the purpose of this research. The Leadership Practice Inventory’s self-assessment was used for the leadership assessment. Researcher hypothesized that over seventy percent of involved students were natural born leaders. Overall, data neither supported nor denied the hypothesis. However, research did confirm that leadership is developed for co-curricular involvement

Manifold Learning for Natural Image Sets, Doctoral Dissertation August 2006

The field of manifold learning provides powerful tools for parameterizing high-dimensional data points with a small number of parameters when this data lies on or near some manifold. Images can be thought of as points in some high-dimensional image space where each coordinate represents the intensity value of a single pixel. These manifold learning techniques have been successfully applied to simple image sets, such as handwriting data and a statue in a tightly controlled environment. However, they fail in the case of natural image sets, even those that only vary due to a single degree of freedom, such as a person walking or a heart beating. Parameterizing data sets such as these will allow for additional constraints on traditional computer vision problems such as segmentation and tracking. This dissertation explores the reasons why classical manifold learning algorithms fail on natural image sets and proposes new algorithms for parameterizing this type of data

Mechanisms of Erythropoietin-induced Neuroprotection in: in-vivo and in-vitro Models of hypoxia Ischema

Hypoxic ischemic brain injury (HIBI) is a common cause of neonatal mortality and morbidity. Approximately 60 % of preterm babies and 2% of full term infants suffer from asphyxia. Asphyxia related death accounts for approximately 23% of neonatal mortality annually. Many therapeutic interventions show promise in the laboratory but fail in clinics. A thorough understanding of mechanisms by which promising therapeutic intervention confers its neuroprotection is necessary to promote smoother transitions from bench to the bedside. Erythropoietin (EPO), a hematopoietic growth factor that increases oxygen availability during hypoxia/ischemia is associated with cell survival and neuroprotection in: in vivo and in vitro models of hypoxia ischemia. However these studies hold limited clinical translations because the underlying mechanism remains unclear and the key molecules involved in EPO-induced neuroprotection are still to be determined. Thus the central aim of this proposal is: to determine the key mediators of EPO-induced neuroprotection and the mechanisms by which this occurs in: in vitro and in vivo models of hypoxia ischemia. Two alternate pathways of EPO-induced neuroprotection were elucidated in vitro using oxygen and glucose deprivation to mimic hypoxia ischemia. Our findings showed that EPO treatment resulted in an upregulation of tissues inhibitor of matrix metalloproteinase (TIMP)-1 and inhibition of hypoxia inducible factor (HIF-1α) both of which subsequently decreased in matrix metalloproteinase (MMP)-9 and promoted neuroprotection. MMP-9 inhibition was associated with neuroprotection in both pathways thus, inferring that inhibition of MMP-9 is one of the primary mechanisms of EPO-induced neuroprotection. We also observed that EPO-induced neuroprotection was reversed by inhibition of TIMP-1 or prolyl hydroxylase (PHD)-2. This lends to the conclusion that TIMP-1 and PHD-2 are the key mediators of EPO-induced neuroprotection in: in vivo and in vitro models of hypoxia ischemia

Link projections and flypes

Let \Pi be a link projection in S^2. John Conway and later Francis Bonahon and Larry Siebenmann undertook to split $\Pi$ into canonical pieces. These pieces received different names: basic or polyhedral diagrams on one hand, rational, algebraic, bretzel, arborescent diagrams on the other hand. This paper proposes a thorough presentation of the theory, known to happy fews. We apply the existence and uniqueness theorem for the canonical decomposition to the classification of Haseman circles and to the localisation of the flypes

Entrance to U.S. Cemetery, Corinth, Miss.

https://egrove.olemiss.edu/ms_pcards/1056/thumbnail.jp

Hotels-50K: A Global Hotel Recognition Dataset

Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have been trafficked, and where their traffickers might move them or others in the future. Recognizing the hotel from images is challenging because of low image quality, uncommon camera perspectives, large occlusions (often the victim), and the similarity of objects (e.g., furniture, art, bedding) across different hotel rooms. To support efforts towards this hotel recognition task, we have curated a dataset of over 1 million annotated hotel room images from 50,000 hotels. These images include professionally captured photographs from travel websites and crowd-sourced images from a mobile application, which are more similar to the types of images analyzed in real-world investigations. We present a baseline approach based on a standard network architecture and a collection of data-augmentation approaches tuned to this problem domain