770 research outputs found
Functionalised nanodiamond as a platform for skeletal tissue engineering
Diamond has come of age, as a material for technology and life science applications. Despite its reputation as a gemstone, high grade single crystal diamond can be grown in the laboratory at modest cost. Other forms of diamond, such particulate nanodiamonds (typically 5nm in size) can be formed. Its superior mechanical and functionalisation properties make diamond a great candidate for skeletal tissue engineering material. In this thesis, the potential of functionalised diamond as a nanomaterial for the chondrogenic and osteogenic differentiation of Mesenchymal Stem Cells (MSCs) has been investigated. Results in chapter 4 describe the biocompatibility of human Adipose Derived Stem Cells (hADSCs) with oxygen–functionalised BBD-PPy scaffolds and oxygen–terminated nanodiamonds (NDs) and the ability of the cells to form uniform monolayers on ND substrates. Chapter 5 verifies the ability of hydrogen and oxygen terminated NDs to sustain hADSC proliferation and chondrogenic differentiation. In the same chapter, the ability of another type of mesenchymal stem cells (MSCs), chondrogenic precursor/ stem cells (CSPCs) to differentiate on H–NDs and O–NDs into three key skeletal precursors (chondrocytes, osteocytes and adipocytes) is demonstrated through staining and colorimetric quantification assays. In Chapter 6, a novel 3D scaffold made out of fibrin that incorporated H–NDs is characterised. CSPCs underwent chondrogenic and osteogenic differentiation in this novel structure. Differentiation outcomes were qualitatively demonstrated through section staining and were subsequently quantified using quantitative real time Polymerase Chain Reaction (qRT-PCR). Results indicate chondrogenic differentiation and potential endochondral ossification was promoted by increasing concentrations of H–NDs in the scaffolds, without enhancing the Young’s modulus of the constructs
Ανάλυση μοντέλου ενεργειακής διαχείρισης στόλου ηλεκτρικών οχημάτων σύμφωνα με την ελαστικότητα που προσφέρουν οι χρήστες ηλεκτρικών οχημάτων
Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Παραγωγή και Διαχείρηση Ενέργειας
Alternative Forms of Resilience. A typology of approaches for the study of Citizen Collective Responses in Hard Economic Times
A variety of theoretical and conceptual perspectives have been applied to studying collective citizen initiatives arising in response to hard economic times, such as solidarity-based exchanges and networks, cooperative structures, barter clubs, credit unions, ethical banks, time banks, alternative social currency, citizens' self-help groups, neighbourhood assemblies and social enterprises. Since the global financial crisis of 2008, scholarly attention on novel, alternative, resilient structures has increased, especially in regions that have been most affected. A comprehensive literature review is therefore needed on these initiatives which usually aim to meet basic needs such as food, shelter, health and education at the community level, or build and envision autonomous communities. This paper has four aims. First, it proposes a new, all-encompassing conceptual framework, alternative forms of resilience, to embrace all issues and groups related to such initiatives, during the new millennium and its economic and political challenges, while taking into account the impact of the 2008 crisis. Secondly, it offers a comprehensive literature review on collective citizen initiatives studied through different theoretical, methodological and conceptual understandings. Thirdly, it provides a new typology of several approaches on novel, collective and solidarity-oriented critical resilience initiatives which take into account political issues, be they policy or social-movement related. Finally, it points to future research areas which would aim to systematically address the political and non-political features of citizen-collective responses
Block CUR: Decomposing Matrices using Groups of Columns
A common problem in large-scale data analysis is to approximate a matrix
using a combination of specifically sampled rows and columns, known as CUR
decomposition. Unfortunately, in many real-world environments, the ability to
sample specific individual rows or columns of the matrix is limited by either
system constraints or cost. In this paper, we consider matrix approximation by
sampling predefined \emph{blocks} of columns (or rows) from the matrix. We
present an algorithm for sampling useful column blocks and provide novel
guarantees for the quality of the approximation. This algorithm has application
in problems as diverse as biometric data analysis to distributed computing. We
demonstrate the effectiveness of the proposed algorithms for computing the
Block CUR decomposition of large matrices in a distributed setting with
multiple nodes in a compute cluster, where such blocks correspond to columns
(or rows) of the matrix stored on the same node, which can be retrieved with
much less overhead than retrieving individual columns stored across different
nodes. In the biometric setting, the rows correspond to different users and
columns correspond to users' biometric reaction to external stimuli, {\em
e.g.,}~watching video content, at a particular time instant. There is
significant cost in acquiring each user's reaction to lengthy content so we
sample a few important scenes to approximate the biometric response. An
individual time sample in this use case cannot be queried in isolation due to
the lack of context that caused that biometric reaction. Instead, collections
of time segments ({\em i.e.,} blocks) must be presented to the user. The
practical application of these algorithms is shown via experimental results
using real-world user biometric data from a content testing environment.Comment: shorter version to appear in ECML-PKDD 201
Variant Ranker: a web-tool to rank genomic data according to functional significance
BACKGROUND: The increasing volume and complexity of high-throughput genomic data make analysis and prioritization of variants difficult for researchers with limited bioinformatics skills. Variant Ranker allows researchers to rank identified variants and determine the most confident variants for experimental validation. RESULTS: We describe Variant Ranker, a user-friendly simple web-based tool for ranking, filtering and annotation of coding and non-coding variants. Variant Ranker facilitates the identification of causal variants based on novelty, effect and annotation information. The algorithm implements and aggregates multiple prediction algorithm scores, conservation scores, allelic frequencies, clinical information and additional open-source annotations using accessible databases via ANNOVAR. The available information for a variant is transformed into user-specified weights, which are in turn encoded into the ranking algorithm. Through its different modules, users can (i) rank a list of variants (ii) perform genotype filtering for case-control samples (iii) filter large amounts of high-throughput data based on user custom filter requirements and apply different models of inheritance (iv) perform downstream functional enrichment analysis through network visualization. Using networks, users can identify clusters of genes that belong to multiple ontology categories (like pathways, gene ontology, disease categories) and therefore expedite scientific discoveries. We demonstrate the utility of Variant Ranker to identify causal genes using real and synthetic datasets. Our results indicate that Variant Ranker exhibits excellent performance by correctly identifying and ranking the candidate genes CONCLUSIONS: Variant Ranker is a freely available web server on http://paschou-lab.mbg.duth.gr/Software.html . This tool will enable users to prioritise potentially causal variants and is applicable to a wide range of sequencing data
Implementing citation management and report generation value-added services over OAI-PMH compliant repositories
The National Documentation Center (EKT) has developed HELIOS (http://helios-eie.ekt.gr) - the institutional repository of the National Hellenic Research Foundation (NHRF) aiming at collecting the scientific work of its associate researchers. DSpace has been used as the repository platform in the implementation of HELIOS. According to the repository literature (A DRIVER’s Guide to European Repositories, Amsterdam University Press, 2008), offering value-added services to researchers can be an important factor for repository take-up, able to significantly increase deposits through self-archiving. Therefore, in order to encourage the usage of HELIOS among the NHRF researchers, an application providing value-added services over the repository has been developed. In brief, this application harvests the digital repository's data and presents them outside the repository's framework, enabling citation management and configurable custom reporting, for example producing publication lists per researcher and institute, exactly in the format applied in the institute annual report. The application is in operation on top of the HELIOS DSpace-based repository; however it has been designed and implemented to depend only on information retrieved via OAI-PMH, so that it can work with any OAI-PMH compliant repository platform (DSpace, Eprints, Fedora, etc.
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