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Northfield, MN, United States

Agency: NSF | Branch: Standard Grant | Program: | Phase: Campus Cyberinfrastrc (CC-NIE) | Award Amount: 327.64K | Year: 2014

This project expands access at St. Olaf College to massive, complex datasets and delivers the analytic power they require. The 2-year effort upgrades the current campus network so researchers in physics, biology, economics, computer science and mathematics can accelerate their projects and expand the range of datasets they investigate. In particular, greater network capacity advances the NSF-funded Center for Interdisciplinary Research and the CSinParallel initiative. The Network for Big Data also enhances formal instruction in data science across the STEM disciplines. Looking ahead, the Network for Big Data will enable St. Olaf researchers to access massive data sets generated via remote sensing methods, including Light Detection and Ranging (LIDAR).

The Network for Big Data continues St. Olafs tradition of taking innovative, cost-effective approaches to advanced computing. All data transfer nodes and Big Data enclave devices reside in a single virtual local area network to serve St. Olafs science and mathematics data management zone. Once core and data center switches are consolidated in one enhanced switch, external connectivity, which includes Internet2, will increase to 10 Gbps. The fiber infrastructure connecting St. Olafs network border to its core and to key STEM buildings is upgraded to support 10Gbps connections, with IPv6 campus-wide deployment, and continuous performance monitoring performance and outcomes of these upgrades using a perfSONAR node.

Agency: NSF | Branch: Standard Grant | Program: | Phase: ANALYSIS PROGRAM | Award Amount: 19.39K | Year: 2015

This award provides funding to help defray the expenses of participants in the Summer Symposium in Real Analysis 39 that will be held June 8-13, 2015, on the campus of St. Olaf College. This conference is the thirty-ninth in a series that has evolved into one of the major venues internationally for the presentation of research developments in real analysis and related areas.

The scientific program for the 2015 Symposium covers a broad array of topics, ranging from regularity issues for partial differential equations to Morse-Sard-type results, from questions in geometric measure theory to topics in combinatorial and set theoretic analysis. The featured speakers are Marianna Csornyei (University of Chicago), Alexander Olevskii (University of Tel Aviv), and Miklos Laczkovich (Eotovos Lorand University). The conference program provides ample opportunity for graduate students, postdocs, and other young scientists to present their work. Proceedings of the Symposium will be made available on-line.

Conference web site: http://www.stolaf.edu/analysis/

Agency: NSF | Branch: Standard Grant | Program: | Phase: OFFICE OF MULTIDISCIPLINARY AC | Award Amount: 210.22K | Year: 2015

Topological data analysis (TDA) is a relatively new branch of statistics whose goal is to apply topology to develop tools for studying the coarse-scale, global, non-linear, geometric features of data. Persistent homology, the most widely studied tool for TDA, has been applied to many areas of science and engineering, including image processing, time series data in biological systems, and sensor networks. Persistent homology yields invariants of data, called barcodes, by associating to the data a sequence of nested topological spaces called a filtration, and then applying standard topological and algebraic constructions. However, for many data sets of interest, such as point cloud data with noise or non-uniformities in density, a single filtration is not rich enough to encode the structure of interest in the data. This motivates the consideration of multidimensional persistent homology, which associates to the data a topological space simultaneously equipped with two or more filtrations. Multi-D persistent homology yields algebraic invariants of data far more complex than in the 1-D setting. New methodology is thus required for working with these invariants in practice. The goal of this project is to introduce such methodology in the 2-D setting.

Specifically, this project is to develop algorithms and design practical software tools that extend the usual persistent homology methodology for exploratory data analysis to the 2-D setting. The proposed tools provide an interactive visualization of the barcodes of the restriction of a 2-D persistence module to affine 1-D lines. At the heart of the computational approach is a novel data structure, based on planar line arrangements, on which one can perform fast queries for these barcodes. The tools also provide a visualization of the multi-graded Betti numbers of a 2-D persistence module. It is proposed to apply the tools to the study of scientific data - especially data arising from biological systems - in much the same way that ordinary persistent homology has been applied to the study of data over the last ten to fifteen years. This project will intend to establish statistical foundations for the corresponding methodology.

Agency: NSF | Branch: Standard Grant | Program: | Phase: S-STEM:SCHLR SCI TECH ENG&MATH | Award Amount: 231.71K | Year: 2012

The shift to parallel computing, including multi-core processors, cloud computing, and heterogeneous systems, has induced a workforce development crisis for computer science (CS) education. This project addresses how crowded CS curricula, traditionally structured around sequential (non-parallel) computing, can be changed to effectively incorporate the rapidly-evolving body of parallelism knowledge.

Saint Olaf College, Calvin College and Macalester College are demonstrating how colleges and universities can insert short (one- to three-day) teaching modules on parallel computing into their courses through self-contained units that present conceptual principles and reinforce them by hands-on experience and follow-up exercises. New modules that incorporate emerging curricular recommendations, relevant applications to other fields, and parallel design patterns are under development. Parallelism is infused incrementally throughout the CS curriculum. Having developed this modular strategy in a predecessor CCLI Type I grant, this project demonstrates the scalability of this approach to other universities and colleges by targeting two geographical regions with workshops and follow-up adopter support.

Other project activities reward participants for creating new modules, promote the national dissemination of this modular approach through conference workshops and presentations, and expand existing synergistic partnerships between CSinParallel.org and related efforts in industry, academia, and professional organizations.

Agency: NSF | Branch: Standard Grant | Program: | Phase: Cellular Dynamics and Function | Award Amount: 412.53K | Year: 2015

Tetrahymena thermophile, a single-celled, freshwater protozoan endemic to the eastern USA, is a genius at performing universal cellular activities in exaggerated ways. During sexual reproduction, Tetrahymena manufacture thousands of miniature chromosomes that must be capped at each end to preserve their integrity. This made Tetrahymena the ideal model organism for uncovering the mechanism of telomere capping leading to the 2009 Nobel Prize. Paradoxically, while Tetrahymena perform almost universal acts of cell biology, they are poised equidistant from plant and animal kingdoms, and often display novel approaches to solving fundamental biological problems. This evolutionary distance allows researchers to gain broad perspective into how life solves many of its functional dilemmas. The investigators in this research project will take advantage of this organisms unique place in the tree of life and its hugely accessible biology, to explore cellular mechanisms that resemble events triggered in higher organisms when sperm meets egg: how do cells communicate with one another to trigger changes that permit cell-cell fusion; how do cells attach to one another during mating and; how do cells protect one set of nuclei while simultaneously destroying another set of nuclei within a common cytoplasm. The results from this work will inform the understanding of cell biology associated with these processes in higher organisms. The accessibility of Tetrahymena makes this a model system for training undergraduates in the art of molecular and cellular biology and the practice of good science. Students in the investigators laboratory will learn to culture live cells, isolate cellular organelles and their constituent proteins, identify these proteins by Mass Spectrometry, take the resultant data to clone genes of interest, and perform sophisticated microscopy and electron tomography experiments to examine localization of cellular components (proteins, cytoskeleton) during mating associated events. As students are trained, they will be encouraged to cross-train, picking up multiple types of research expertise in both classroom and laboratory settings, while experiencing a truly collaborative and interdisciplinary research environment.

The formal questions that constitute the Intellectual Merit of this research are: 1) Can cell-adhesion proteins that mediate pair-formation in Tetrahymena be identified and are they related to products of the Mating Type Locus? 2) Do Tetrahymena cells engaging in pre-mating encounters exhibit elevated levels of intracellular Ca++ reminiscent of those accompanying the fertilization reaction in metazoan gametes? 3) How could physical association of post-meiotic nuclei with membrane systems of the mating junction shield those nuclei from signals that trigger macro-autophagy, and 4) What membrane trafficking pathways lead to production and shedding of micro-vesicles into the extracellular space between mating cells, and do these shed micro-vesicles perform a signaling function? This study ultimately explores inter-cellular signaling via surface proteins and possibly shed micro-vesicles and the programmed cellular responses triggered by those signals. The work in this project will be performed by undergraduates engaged in formal scientific training.

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