A gene-signature progression approach to identifying candidate small-molecule cancer therapeutics with connectivity mapping

Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research in connectivity mapping mainly focused on two of the key components in the framework, namely, the reference gene expression profiles and the connectivity mapping algorithms. The other key component in this framework, the query gene signature, has been left to users to construct without much consensus on how this should be done, albeit it has been an issue most relevant to end users. As a key input to the connectivity mapping process, gene signature is crucially important in returning biologically meaningful and relevant results. This paper intends to formulate a standardized procedure for constructing high quality gene signatures from a user’s perspective.

Introduction: Mapping Gwen John: Lives, Lines and Images

Nomadic Narratives, Visual Forces explores issues, questions, and problems emerging in the analysis of epistolary and visual narratives. This book focuses in particular on Gwen John's letters and paintings. It offers an innovative theoretical approach to narrative analysis by drawing on Foucault's theory of power, Deleuze and Guattari's analytics of desire, and Cavarero's concept of the narratable self. Furthermore, it examines the use of letters as documents of life in narrative research and highlights the dynamics of spatiality in the constitution of the female self in art. This study brings together theoretical insights that emerge from the analysis of life documents - some of them previously unpublished - combining innovative research with specific methodological suggestions on doing narrative analysis.

Cognitive robotics: a new approach to simultaneous localisation and mapping

Most simultaneous localisation and mapping (SLAM) solutions were developed for navigation of non-cognitive robots. By using a variety of sensors, the distances to walls and other objects are determined, which are then used to generate a map of the environment and to update the robot’s position. When developing a cognitive robot, such a solution is not appropriate since it requires accurate sensors and precise odometry, also lacking fundamental features of cognition such as time and memory. In this paper we present a SLAM solution in which such features are taken into account and integrated. Moreover, this method does not require precise odometry nor accurate ranging sensors.

Mapping und Erweiterung der Ontologie des Forschungsinformationssystems VIVO

Die Bachelorarbeit beschäftigt sich mit der Ontologie des Forschungsinformationssystems VIVO. In der Arbeit wird der Versuch unternommen, die Ontologie an die Besonderheiten des deutschen Wissenschaftsbetriebs anzupassen, mit dem Ziel, die Einführung des Systems für eine deutsche Einrichtung zu erleichtern. Das Mapping und die Erweiterung sind auf die Bereiche „Positionsbezeichnungen“ und „Organisationseinheiten“ beschränkt. Der theoretische Teil behandelt das Thema der Forschungsinformationen und deren Implementierung in ein Forschungsinformationssystem. Unter anderem werden auch die Tendenzen der Standardisierung in dem Bereich beleuchtet. Bei der Darstellung von VIVO als eine Semantic-Web-Anwendung steht die Ontologie, als Grundlage für die Funktionalitäten des Systems im Vordergrund.

From "Spaces of Fear" to "Fearscapes": Mapping for Reframing Theories About the Spatialization of Fear in Urban Space

The article engages with theory about the processes of spatialization of fear in contemporary Western urban space (fortification, privatization, exclusion/seclusion, fragmentation, polarization) and their relation to fear of crime and violence. A threefold taxonomy is outlined (Enclosure, Post-Public Space, Barrier), and “spaces of fear” in the city of Palermo are mapped with the aim of exploring the cumulative large-scale effects of the spatialization of fear on a concrete urban territory. Building on empirical evidence, the author suggests that mainstream theories be reframed as part of a less hegemonic and more discursive approach and that theories mainly based on the analyses of global cities be deprovincialized. The author argues for the deconstruction of the concept of “spaces of fear” in favor of the more discursive concept of “fearscapes” to describe the growing landscapes of fear in contemporary Western cities.

The influence of water column variability and seafloor topography on multibeam bathymetric mapping

Senior thesis written for Oceanography 445

Wind resource mapping using landscape roughness and spatial interpolation methods

Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

Mapping multi-species habitat use for marine conservation planning

Tese de Doutoramento, Ciências do Mar (Biologia Marinha)

Mapping non-suicidal self-injury in adolescence: Development and confirmatory factor analysis of the impulse, self-harm and sucidal ideation questionnaire for adolescents (ISSIQ-A)

Non-suicidal self-injury (NSSI) is the deliberate, self-inflicted destruction of body tissue without suicidal intent and an important clinical phenomenon. Rates of NSSI appear to be disproportionately high in adolescents and young adults, and is a risk factor for suicidal ideation and behavior. The present study reports the psychometric properties of the Impulse, Self-harm and Suicide Ideation Questionnaire for Adolescents (ISSIQ-A), a measure designed to comprehensively assess the impulsivity, NSSI behaviors and suicide ideation. An additional module of this questionnaire assesses the functions of NSSI. Results of Confirmatory Factor Analysis (CFA) of the scale on 1722 youths showed items' suitability and confirmed a model of four different dimensions (Impulse, Self-harm, Risk-behavior and Suicide ideation) with good fit and validity. Further analysis showed that youth׳s engagement in self-harm may exert two different functions: to create or alleviate emotional states, and to influence social relationships. Our findings contribute to research and assessment on non-suicidal self-injury, suggesting that the ISSIQ-A is a valid and reliable measure to assess impulse, self-harm and suicidal thoughts, in adolescence.

Is multidimensional scaling suitable for mapping the input respiratory impedance in subjects and patients?

This paper presents the application of multidimensional scaling (MDS) analysis to data emerging from noninvasive lung function tests, namely the input respiratory impedance. The aim is to obtain a geometrical mapping of the diseases in a 3D space representation, allowing analysis of (dis)similarities between subjects within the same pathology groups, as well as between the various groups. The adult patient groups investigated were healthy, diagnosed chronic obstructive pulmonary disease (COPD) and diagnosed kyphoscoliosis, respectively. The children patient groups were healthy, asthma and cystic fibrosis. The results suggest that MDS can be successfully employed for mapping purposes of restrictive (kyphoscoliosis) and obstructive (COPD) pathologies. Hence, MDS tools can be further examined to define clear limits between pools of patients for clinical classification, and used as a training aid for medical traineeship.

Energy-aware task mapping onto heterogeneous platforms using DVFS and sleep states

Heterogeneous multicore platforms are becoming an interesting alternative for embedded computing systems with limited power supply as they can execute specific tasks in an efficient manner. Nonetheless, one of the main challenges of such platforms consists of optimising the energy consumption in the presence of temporal constraints. This paper addresses the problem of task-to-core allocation onto heterogeneous multicore platforms such that the overall energy consumption of the system is minimised. To this end, we propose a two-phase approach that considers both dynamic and leakage energy consumption: (i) the first phase allocates tasks to the cores such that the dynamic energy consumption is reduced; (ii) the second phase refines the allocation performed in the first phase in order to achieve better sleep states by trading off the dynamic energy consumption with the reduction in leakage energy consumption. This hybrid approach considers core frequency set-points, tasks energy consumption and sleep states of the cores to reduce the energy consumption of the system. Major value has been placed on a realistic power model which increases the practical relevance of the proposed approach. Finally, extensive simulations have been carried out to demonstrate the effectiveness of the proposed algorithm. In the best-case, savings up to 18% of energy are reached over the first fit algorithm, which has shown, in previous works, to perform better than other bin-packing heuristics for the target heterogeneous multicore platform.