Dark-energy constraints and correlations with systematics from CFHTLS weak lensing, SNLS supernovae Ia and WMAP5

Aims We combine measurements of weak gravitational lensing from the CFHTLS-Wide survey, supernovae Ia from CFHT SNLS and CMB anisotropies from WMAP5 to obtain joint constraints on cosmological parameters, in particular, the dark-energy equation-of-state parameter w. We assess the influence of systematics in the data on the results and look for possible correlations with cosmological parameters. Methods We implemented an MCMC algorithm to sample the parameter space of a flat CDM model with a dark-energy component of constant w. Systematics in the data are parametrised and included in the analysis. We determine the influence of photometric calibration of SNIa data on cosmological results by calculating the response of the distance modulus to photometric zero-point variations. The weak lensing data set is tested for anomalous field-to-field variations and a systematic shape measurement bias for high-redshift galaxies. Results Ignoring photometric uncertainties for SNLS biases cosmological parameters by at most 20% of the statistical errors, using supernovae alone; the parameter uncertainties are underestimated by 10%. The weak-lensing field-to-field variance between 1 deg2-MegaCam pointings is 5-15% higher than predicted from N-body simulations. We find no bias in the lensing signal at high redshift, within the framework of a simple model, and marginalising over cosmological parameters. Assuming a systematic underestimation of the lensing signal, the normalisation increases by up to 8%. Combining all three probes we obtain -0.10 < 1 + w < 0.06 at 68% confidence ( -0.18 < 1 + w < 0.12 at 95%), including systematic errors. Our results are therefore consistent with the cosmological constant . Systematics in the data increase the error bars by up to 35%; the best-fit values change by less than 0.15.

Managing flexible work arrangements in small not-for-profit firms: The influence of organisational size, financial constraints and workforce characteristics

Small, not-for-profit organisations fulfil a need in the economy that is typically not satisfied by for-profit firms. They also operate in ways that are distinct from larger organisations. While such firms employ a substantial proportion of the workforce, research addressing human resource management (HRM) practices in these settings is limited. This article used data collected from five small not-for-profit firms in Australia to examine the way one significant HRM practice – the provision and utilisation of flexible work arrangements – operates in the sector. Drawing on research from several scholarly fields, the article firstly develops a framework comprising three tensions in not-for-profits that have implications for HRM. These tensions are: (1) contradictions between an informal approach to HRM vs. a formal regulatory system; (2) employee values that favour social justice vs. external market forces; and (3) a commitment to service vs. external financial expectations. The article then empirically examines how these tensions are managed in relation to the specific case of flexible work arrangements. The study reveals that tensions around providing and accessing flexible work arrangements are managed in three ways: discretion, leadership style and distancing. These findings more broadly inform the way HRM is operationalised in this under-examined sector.

Data distribution and task scheduling for distributed computing of all-to-all comparison problems

This research studied distributed computing of all-to-all comparison problems with big data sets. The thesis formalised the problem, and developed a high-performance and scalable computing framework with a programming model, data distribution strategies and task scheduling policies to solve the problem. The study considered storage usage, data locality and load balancing for performance improvement in solving the problem. The research outcomes can be applied in bioinformatics, biometrics and data mining and other domains in which all-to-all comparisons are a typical computing pattern.

Deriving optimal fishing effort for managing Australia's Moreton Bay multispecies trawl fishery with aggregated effort data

Deriving an estimate of optimal fishing effort or even an approximate estimate is very valuable for managing fisheries with multiple target species. The most challenging task associated with this is allocating effort to individual species when only the total effort is recorded. Spatial information on the distribution of each species within a fishery can be used to justify the allocations, but often such information is not available. To determine the long-term overall effort required to achieve maximum sustainable yield (MSY) and maximum economic yield (MEY), we consider three methods for allocating effort: (i) optimal allocation, which optimally allocates effort among target species; (ii) fixed proportions, which chooses proportions based on past catch data; and (iii) economic allocation, which splits effort based on the expected catch value of each species. Determining the overall fishing effort required to achieve these management objectives is a maximizing problem subject to constraints due to economic and social considerations. We illustrated the approaches using a case study of the Moreton Bay Prawn Trawl Fishery in Queensland (Australia). The results were consistent across the three methods. Importantly, our analysis demonstrated the optimal total effort was very sensitive to daily fishing costs—the effort ranged from 9500–11 500 to 6000–7000, 4000 and 2500 boat-days, using daily cost estimates of $0, $500, $750, and $950, respectively. The zero daily cost corresponds to the MSY, while a daily cost of $750 most closely represents the actual present fishing cost. Given the recent debate on which costs should be factored into the analyses for deriving MEY, our findings highlight the importance of including an appropriate cost function for practical management advice. The approaches developed here could be applied to other multispecies fisheries where only aggregated fishing effort data are recorded, as the literature on this type of modelling is sparse.

Patients with physical debility undergoing subacute physical rehabilitation following an acute hospital admission demonstrated improvement in cognitive functional task independence

Background: Hospitalised older adults often experience a decline in physical functioning and mobility in the lead up to (or during) an acute hospital admission. During acute illness and hospitalisation, older adults may also experience a decline or fluctuation in their cognitive functioning. Previous studies have demonstrated that patients with or without reduced cognitive functioning on admission to subacute inpatient rehabilitation have considerable potential to improve their physical functioning and quality of life.

Archaean crustal evolution in eastern Finland : New geochronological and geochemical constraints from the Kuhmo terrain and the Nurmes belt

This thesis summarises the results of four original papers concerning U-Pb geochronology and geochemical evolution of Archaean rocks from the Kuhmo terrain and the Nurmes belt, eastern Finland. The study area belongs to a typical Archaean granite-greenstone terrain, composed of metavolcanic and metasedimentary rocks in generally N-S trending greenstone belts as well as a granitoid-gneiss complex with intervening gneissic and migmatised supracrustal and plutonic rocks. U-Pb data on migmatite mesosomes indicate that the crust surrounding the Tipasjärvi-Kuhmo-Suomussalmi greenstone belt is of varying age. The oldest protolith detected for a migmatite mesosome from the granitoid-gneiss complex is 2.94 Ga, whereas the other dated migmatites protoliths have ages of 2.84 2.79 Ga. The latter protoliths are syngenetic with the majority of volcanic rocks in the adjacent Tipasjärvi-Kuhmo-Suomussalmi greenstone belt. This suggests that the genesis of some of the volcanic rocks within the greenstone belt and surrounding migmatite protoliths could be linked. Metamorphic zircon overgrowths with ages of 2.84 2.81 Ga were also obtained. The non-migmatised plutonic rocks in the Kuhmo terrain and in the Nurmes belt record secular geochemical evolution, typical of Archaean cratons. The studied tonalitic rocks have ages of 2.83 2.75 Ga and they have geochemical characteristics similar to low-Al and high-Al TTD (tonalite-trondhjemite-dacite). The granodiorites, diorites, and gabbros with high Mg/Fe and LILE-enriched characteristics were mostly emplaced between 2.74 2.70 Ga and they exhibit geochemical characteristics typical of Archaean sanukitoid suites. The latest identified plutonic episode took place at 2.70 2.68 Ga, when compositionally heterogeneous leucocratic granitoid rocks, with a variable crustal component, were emplaced. U-Pb data on migmatite leucosomes suggest that leucosome generation may have been coeval with this latest plutonic event. On the basis of available U-Pb and Sm-Nd isotopic data it appears that the plutonic rocks of the Kuhmo terrain and the Nurmes belt do not contain any significant input from Palaeoarchaean sources. A characteristic feature of the Nurmes belt is the presence of migmatised paragneisses, locally preserving primary edimentary structures, with sporadic amphibolite intercalations. U-Pb studies on zircons indicate that the precursors of the Nurmes paragneisses were graywackes that were deposited between 2.71 Ga and 2.69 Ga and that they had a prominent 2.75 2.70 Ga source. Nd isotopic and whole-rock geochemical data for the intercalated amphibolites imply MORB sources. U-Pb data on zircons from the plutonic rocks and paragneisses reveal that metamorphic zircon growth took place at 2.72 2.63 Ga. This was the last tectonothermal event related to cratonisation of the Archaean crust of eastern Finland.

Specifying Reuse Interfaces for Task-Oriented Framework Specialization

Reuse of existing carefully designed and tested software improves the quality of new software systems and reduces their development costs. Object-oriented frameworks provide an established means for software reuse on the levels of both architectural design and concrete implementation. Unfortunately, due to frame-works complexity that typically results from their flexibility and overall abstract nature, there are severe problems in using frameworks. Patterns are generally accepted as a convenient way of documenting frameworks and their reuse interfaces. In this thesis it is argued, however, that mere static documentation is not enough to solve the problems related to framework usage. Instead, proper interactive assistance tools are needed in order to enable system-atic framework-based software production. This thesis shows how patterns that document a framework s reuse interface can be represented as dependency graphs, and how dynamic lists of programming tasks can be generated from those graphs to assist the process of using a framework to build an application. This approach to framework specialization combines the ideas of framework cookbooks and task-oriented user interfaces. Tasks provide assistance in (1) cre-ating new code that complies with the framework reuse interface specification, (2) assuring the consistency between existing code and the specification, and (3) adjusting existing code to meet the terms of the specification. Besides illustrating how task-orientation can be applied in the context of using frameworks, this thesis describes a systematic methodology for modeling any framework reuse interface in terms of software patterns based on dependency graphs. The methodology shows how framework-specific reuse interface specifi-cations can be derived from a library of existing reusable pattern hierarchies. Since the methodology focuses on reusing patterns, it also alleviates the recog-nized problem of framework reuse interface specification becoming complicated and unmanageable for frameworks of realistic size. The ideas and methods proposed in this thesis have been tested through imple-menting a framework specialization tool called JavaFrames. JavaFrames uses role-based patterns that specify a reuse interface of a framework to guide frame-work specialization in a task-oriented manner. This thesis reports the results of cases studies in which JavaFrames and the hierarchical framework reuse inter-face modeling methodology were applied to the Struts web application frame-work and the JHotDraw drawing editor framework.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Institutional constraints on altruism in the formation of a venture idea

This thesis is about the social orientation of new venture ideas and how the degree of social orientation is influenced by the entrepreneur's level of altruism, by industry norms, and by nonprofit work experience. Potential entrepreneurs were asked to generate new venture ideas based on 3D-printing and their ideas were rated for degree of social orientation. It was found that while greater altruism leads to more socially-oriented venture ideas, the influence of altruism on the venture idea is constrained by the profit-maximization norm that is prevalent in most industries.

Symmetries and constraints in generalized Hamiltonian dynamics

A general analysis of symmetries and constraints for singular Lagrangian systems is given. It is shown that symmetry transformations can be expressed as canonical transformations in phase space, even for such systems. The relation of symmetries to generators, constraints, commutators, and Dirac brackets is clarified.

Determination of optimal trajectory under design constraints for a satellite launch vehicle

An optimal pitch steering programme of a solid-fuel satellite launch vehicle to maximize either (1) the injection velocity at a given altitude, or (2) the size of circular orbit, for a given payload is presented. The two-dimensional model includes the rotation of atmosphere with the Earth, the vehicle's lift and drag, variation of thrust with time and altitude, inverse-square gravitational field, and the specified initial vertical take-off. The inequality constraints on the aerodynamic load, control force, and turning rates are also imposed. Using the properties of the central force motion the terminal constraint conditions at coast apogee are transferred to the penultimate stage burnout. Such a transformation converts a time-free problem into a time-fixed one, reduces the number of terminal constraints, improves accuracy, besides demanding less computer memory and time. The adjoint equations are developed in a compact matrix form. The problem is solved on an IBM 360/44 computer using a steepest ascent algorithm. An illustrative analysis of a typical launch vehicle establishes the speed of convergence, and accuracy and applicability of the algorithm.

An assessment of m-health in developing countries using task technology fit model

Health challenges present arguably the most significant barrier to sustainable global development. The introduction of ICT in healthcare, especially the application of mobile communications, has created the potential to transform healthcare delivery by making it more accessible, affordable and effective across the developing world. However, current research into the assessment of mHealth from the perspective of developing countries particularly with community Health workers (CHWs) as primary users continues to be limited. The aim of this study is to analyze the contribution of mHealth in enhancing the performance of the health workers and its alignment with existing workflows to guide its utilization. The proposed research takes into account this consideration and aims to examine the task-technology alignment of mHealth for CHWs drawing upon the task technology fit as the theoretical foundation.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent d evelopments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.