Imaging studies of peripheral nerve regeneration induced by porous collagen biomaterials

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references.There is urgent need to develop treatments for inducing regeneration in injured organs. Porous collagen-based scaffolds have been utilized clinically to induce regeneration in skin and peripheral nerves, however still there is no complete explanation about the underlying mechanism. This thesis utilizes advanced microscopy to study the expression of contractile cell phenotypes during wound healing, a phenotype believed to affect significantly the final outcome. The first part develops an efficient pipeline for processing challenging spectral fluorescence microscopy images. Images are segmented into regions of objects by refining the outcome of a pixel-wide model selection classifier by an efficient Markov Random Field model. The methods of this part are utilized by the following parts. The second part extends the image informatics methodology in studying signal transduction networks in cells interacting with 3D matrices. The methodology is applied in a pilot study of TGFP signal transduction by the SMAD pathway in fibroblasts seeded in porous collagen scaffolds. Preliminary analysis suggests that the differential effect of TGFP1 and TGFP3 to cells could be attributed to the "non-canonical" SMADI and SMAD5. The third part is an ex vivo imaging study of peripheral nerve regeneration, which focuses on the formation of a capsule of contractile cells around transected rat sciatic nerves grafted with collagen scaffolds, 1 or 2 weeks post-injury. It follows a recent study that highlights an inverse relationship between the quality of the newly formed nerve tissue and the size of the contractile cell capsule 9 weeks post-injury. Results suggest that "active" biomaterials result in significantly thinner capsule already 1 week post-injury. The fourth part describes a novel method for quantifying the surface chemistry of 3D matrices. The method is an in situ binding assay that utilizes fluorescently labeled recombinant proteins that emulate the receptor of , and is applied to quantify the density of ligands for integrins a113, a2p1 on the surface of porous collagen scaffolds. Results provide estimates for the density of ligands on "active" and "inactive" scaffolds and demonstrate that chemical crosslinking can affect the surface chemistry of biomaterials, therefore can affect the way cells sense and respond to the material.by Dimitrios S. Tzeranis.Ph. D

Mining human mobility patterns from pervasive spatial and temporal data

Recent advances in communication, sensors and processors have made pervasive systems more computationally powerful and increasingly popular. These systems are deployed everywhere all the time while remaining transparent. Take smartphones as an example; they have become an integral part of human life and people carry them wherever they go. Coupled with the popularity of pervasive systems and user tracking, this has opened up excellent opportunities to analyse human mobility. This can be applied to a broad range of location-based services such as smart navigation and recommendation systems. Data from pervasive systems has temporal, spatial and spatio-temporal aspects that can be leveraged for mining human mobility patterns. Temporal data such as time series from embedded sensors on smartphones does not usually have any information about locations, while time stamps are discarded in spatial data. The list of significant locations visited by the user is an example of spatial data. The third group of data is spatio-temporal data that has both temporal and spatial aspects such as users' trajectories. In this dissertation, we analyse human mobility by mining these three kinds of data. In each chapter, we look at a specific aspect to infer key information about users’ mobility including transition time detection, movement graph summarisation, and trajectory prediction. We analyse temporal information from time series data to extract transition times in daily activities. The transition times denote when user activities change such as when the user goes to work or when the user goes shopping. In addition to applications in location-based services, extracting the transition times helps us to understand human mobility patterns across the whole day. We tackle scalability to enable processing to take place on resource-constrained devices. We introduce Shrink as a new summarisation method to compress large scale graphs. Trajectories and movements of the user can be transformed into a graph in which each node represents stay points and each edge represents distance. Since this graph is very large, Shrink is used to reduce the size of the movement graph while preserving distances between nodes. The property that is preserved in the compressed graph, also known as the coarse graph, is the distance between the nodes. Shrink is a query friendly compression, which means the compressed graph can be queried without decompression. As the complexity of distance-based queries such as shortest path queries is highly dependent on the size of the graph, Shrink improves performance in terms of time and storage. We also investigate the effect of compression on the human mobility mining algorithms and show that the summarisation provides a trade-off between efficiency and granularity. We also analyse spatial-temporal data by predicting user trajectory based on historical data. Specifically, given the historical data and the user’s trajectory in the first part of the current day (e.g. trajectory in the morning), we predict how users will complete their trajectory in that particular day (e.g. predicting the trajectory for the rest of the day or the afternoon). The granularity of the predicted trajectory is the same as the granularity of the given trajectories. We emphasize that the predicted trajectory includes the sequence of future locations, the stay times, and the departure times. This enhances the user experience because by having the detailed trajectory in advance, location-based services can notify users about the consequence of the movement. In summary, this thesis contains efficient algorithms that can be applied to diverse aspects of pervasive signals for mining human mobility. The new algorithms are aimed at problems in transition time detection, summarisation, and prediction. The solutions address the scalability issues and can work in big pervasive temporal and spatial data effectively and accurately

Bibliography of Lewis Research Center Technical Publications announced in 1991

This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific engineering work performed and managed by the Lewis Research Center in 1991. All the publications were announced in the 1991 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses

Monitoring transient repolarization segment morphology deviations in mouse ECG

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 273-276).This thesis details the design, implementation and validation of a system that facilitates partial automation for detection of anomalous repolarization segment morphologies in the ECG of mice. The technology consists of hardware for signal conditioning of the electrocardiogram (ECG); software for the collection, archiving and real-time & retrospective Internet visualization of data; and an algorithm for morphology analysis of the repolarization segment in murine ECG. The system was validated using genetically engineered mouse subjects with elevated VLDL, analogous to LDL or "bad cholesterol" in humans, and elevated but modified HDL, or "good cholesterol." These subjects, so-called "double-knockout" or dKO mice, exhibit repolarization segment morphologies that are manifestations of severe cardiovascular pathophysiology. This thesis describes the technology in detail and its application to elucidating long-term trends in repolarization morphology deviations in dKO mice. The paper concludes with future work that will utilize the technology and potential clinical applications.by Matthew Blake OefingerPh.D

Research reports: 1994 NASA/ASEE Summer Faculty Fellowship Program

For the 30th consecutive year, a NASA/ASEE Summer Faculty Fellowship Program was conducted at the Marshall Space Flight Center (MSFC). The basic objectives of the programs, which are in the 31st year of operation nationally, are (1) to further the professional knowledge of qualified engineering and science faculty members; (2) to stimulate an exchange of ideas between participants and NASA; (3) to enrich and refresh the research and teaching activities of participants' institutions; and (4) to contribute to the research objectives of the NASA centers. The Faculty Fellows spent 10 weeks at MSFC engaged in a research project compatible with their interests and background and worked in collaboration with a NASA/MSFC colleague. This document is a compilation of Fellows' reports on their research during the summer of 1994

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Fifth Conference on Artificial Intelligence for Space Applications

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration