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Description
This ASU Science Book Discussion Poster was presented at the STS Research Forum and Poster Session in Chicago in conjunction with ALA 2013.
Programming is an essential part of library services. Having a regular program at the library and a wide distribution list raises awareness of the library to those associated with the university and beyond. Through programming, libraries demonstrate the vital role they play in the community. The ASU Science Book Discussion began meeting in the summer of 2011.
Programming is an essential part of library services. Having a regular program at the library and a wide distribution list raises awareness of the library to those associated with the university and beyond. Through programming, libraries demonstrate the vital role they play in the community. The ASU Science Book Discussion began meeting in the summer of 2011.
ContributorsTanner, Rene (Contributor)
Created2013
Description
This presentation was given at the Montana Library Association conference in Billings, MT in 2011 and the Arizona Library Association conference in Tucson, AZ in 2011.
ContributorsTanner, Rene (Author) / Flitner, Debbie (Author)
Created2011-11-22
Description
The images capture the Seeds of Change exhibit, which was co-sponsored by the Native Seeds/SEARCH and exhibited in Noble Library from October 2012 to July 2013. The display featured information about local seed history, the current efforts to protect crop diversity, and rare botanical books about gardening and herbals from ASU's Patten Collection within ASU's Special Collection.
ContributorsTanner, Rene (Curator) / Knouff, Roger (Curator) / Pannabecker, Virginia (Curator)
Created2012-10-30
ContributorsGueci, Nika (Author)
Created2013-12-11
Description
A needs assessment based on students in recovery to build a Collegiate Recovery Program.
ContributorsGueci, Nika (Author)
Created2016-05-01
Description
Qualitative research on student employees of a Collegiate Recovery Program.
ContributorsGueci, Nika (Author)
Created2017-04-01
Description
PPT lecture and notes for Recovery 101 training.
ContributorsGueci, Nika (Author)
Created2016-08-01
Description
Glycosaminoglycans (GAGs) are a class of complex biomolecules comprised of linear, sulfated polysaccharides whose presence on cell surfaces and in the extracellular matrix involve them in many physiological phenomena as well as in interactions with pathogenic microbes. Decorin binding protein A (DBPA), a Borrelia surface lipoprotein involved in the infectivity of Lyme disease, is responsible for binding GAGs found on decorin, a small proteoglycan present in the extracellular matrix. Different DBPA strains have notable sequence heterogeneity that results in varying levels of GAG-binding affinity. In this dissertation, the structures and GAG-binding mechanisms for three strains of DBPA (B31 and N40 DBPAs from B. burgdorferi and PBr DBPA from B. garinii) are studied to determine why each strain has a different affinity for GAGs. These three strains have similar topologies consisting of five α-helices held together by a hydrophobic core as well as two long flexible segments: a linker between helices one and two and a C-terminal tail. This structural arrangement facilitates the formation of a basic pocket below the flexible linker which is the primary GAG-binding epitope. However, this GAG-binding site can be occluded by the flexible linker, which makes the linker a negative regulator of GAG-binding. ITC and NMR titrations provide KD values that show PBr DBPA binds GAGs with higher affinity than B31 and N40 DBPAs, while N40 binds with the lowest affinity of the three. Work in this thesis demonstrates that much of the discrepancies seen in GAG affinities of the three DBPAs can be explained by the amino acid composition and conformation of the linker. Mutagenesis studies show that B31 DBPA overcomes the pocket obstruction with the BXBB motif in its linker while PBr DBPA has a retracted linker that exposes the basic pocket as well as a secondary GAG-binding site. N40 DBPA, however, does not have any evolutionary modifications to its structure to enhance GAG binding which explains its lower affinity for GAGs. GMSA and ELISA assays, along with NMR PRE experiments, confirm that structural changes in the linker do affect GAG-binding and, as a result, the linker is responsible for regulating GAG affinity.
ContributorsMorgan, Ashli M (Author) / Wang, Xu (Thesis advisor) / Allen, James (Committee member) / Yarger, Jeffery (Committee member) / Arizona State University (Publisher)
Created2015
Description
Image segmentation is of great importance and value in many applications. In computer vision, image segmentation is the tool and process of locating objects and boundaries within images. The segmentation result may provide more meaningful image data. Generally, there are two fundamental image segmentation algorithms: discontinuity and similarity. The idea behind discontinuity is locating the abrupt changes in intensity of images, as are often seen in edges or boundaries. Similarity subdivides an image into regions that fit the pre-defined criteria. The algorithm utilized in this thesis is the second category.
This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.
This study addresses the problem of particle image segmentation by measuring the similarity between a sampled region and an adjacent region, based on Bhattacharyya distance and an image feature extraction technique that uses distribution of local binary patterns and pattern contrasts. A boundary smoothing process is developed to improve the accuracy of the segmentation. The novel particle image segmentation algorithm is tested using four different cases of particle image velocimetry (PIV) images. The obtained experimental results of segmentations provide partitioning of the objects within 10 percent error rate. Ground-truth segmentation data, which are manually segmented image from each case, are used to calculate the error rate of the segmentations.
ContributorsHan, Dongmin (Author) / Frakes, David (Thesis advisor) / Adrian, Ronald (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2015