Developing a tool to support communication of parental concerns when a child is in hospital

The involvement of parents in their child’s hospital care has been strongly advocated in paediatric healthcare policy and practice. However, incorporating parental worries about their child’s condition into clinical care can be difficult for both parents and healthcare professionals. Through our “Listening To You” quality improvement project we developed and piloted an innovative approach to listening, incorporating and responding to parental concerns regarding their child’s condition when in hospital. Here we describe the phases of work undertaken to develop our “Listening To You” communications bundle, including a survey, literature review and consultation with parents and staff, before findings from the project evaluation are presented and discussed.

Why (and When) are Preferences Convex? Threshold Effects and Uncertain Quality

It is often assumed (for analytical convenience, but also in accordance with common intuition) that consumer preferences are convex. In this paper, we consider circumstances under which such preferences are (or are not) optimal. In particular, we investigate a setting in which goods possess some hidden quality with known distribution, and the consumer chooses a bundle of goods that maximizes the probability that he receives some threshold level of this quality. We show that if the threshold is small relative to consumption levels, preferences will tend to be convex; whereas the opposite holds if the threshold is large. Our theory helps explain a broad spectrum of economic behavior (including, in particular, certain common commercial advertising strategies), suggesting that sensitivity to information about thresholds is deeply rooted in human psychology.

The thermodynamics and statistical mechanics of protein folding

The physics of self-organization and complexity is manifested on a variety of biological scales, from large ecosystems to the molecular level. Protein molecules exhibit characteristics of complex systems in terms of their structure, dynamics, and function. Proteins have the extraordinary ability to fold to a specific functional three-dimensional shape, starting from a random coil, in a biologically relevant time. How they accomplish this is one of the secrets of life. In this work, theoretical research into understanding this remarkable behavior is discussed. Thermodynamic and statistical mechanical tools are used in order to investigate the protein folding dynamics and stability. Theoretical analyses of the results from computer simulation of the dynamics of a four-helix bundle show that the excluded volume entropic effects are very important in protein dynamics and crucial for protein stability. The dramatic effects of changing the size of sidechains imply that a strategic placement of amino acid residues with a particular size may be an important consideration in protein engineering. Another investigation deals with modeling protein structural transitions as a phase transition. Using finite size scaling theory, the nature of unfolding transition of a four-helix bundle protein was investigated and critical exponents for the transition were calculated for various hydrophobic strengths in the core. It is found that the order of the transition changes from first to higher order as the strength of the hydrophobic interaction in the core region is significantly increased. Finally, a detailed kinetic and thermodynamic analysis was carried out in a model two-helix bundle. The connection between the structural free-energy landscape and folding kinetics was quantified. I show how simple protein engineering, by changing the hydropathy of a small number of amino acids, can enhance protein folding by significantly changing the free energy landscape so that kinetic traps are removed. The results have general applicability in protein engineering as well as understanding the underlying physical mechanisms of protein folding. ^

Fibrations and contact structures

We prove that a closed 3-dimensional manifold is a torus bundle over the circle if and only if it carries a closed nonsingular 1-form which is linearly deformable into contact forms.

Rank and k-nullity of contact manifolds

We prove that the dimension of the 1-nullity distribution N(1) on a closed Sasakian manifold M of rankl is at least equal to 2l−1 provided that M has an isolated closed characteristic. The result is then used to provide some examples of k-contact manifolds which are not Sasakian. On a closed, 2n+1-dimensional Sasakian manifold of positive bisectional curvature, we show that either the dimension of N(1) is less than or equal to n+1 or N(1) is the entire tangent bundle TM. In the latter case, the Sasakian manifold Mis isometric to a quotient of the Euclidean sphere under a finite group of isometries. We also point out some interactions between k-nullity, Weinstein conjecture, and minimal unit vector fields.

Análise da formulação em Monte Carlo dos pacotes de energia multiespectrais aplicada a meios constituídos por vapor d'água

The Monte Carlo method is accurate and is relatively simple to implement for the solution of problems involving complex geometries and anisotropic scattering of radiation as compared with other numerical techniques. In addition, differently of what happens for most of numerical techniques, for which the associated simulations computational time tends to increase exponentially with the complexity of the problems, in the Monte Carlo the increase of the computational time tends to be linear. Nevertheless, the Monte Carlo solution is highly computer time consuming for most of the interest problems. The Multispectral Energy Bundle model allows the reduction of the computational time associated to the Monte Carlo solution. The referred model is here analyzed for applications in media constituted for nonparticipating species and water vapor, which is an important emitting species formed during the combustion of hydrocarbon fuels. Aspects related to computer time optimization are investigated the model solutions are compared with benchmark line-by-line solutions

CAUTI prevention bundles: improving best practices within Western Health for continued success

Background: Persons in acute care settings who have indwelling urethral catheters are at higher risk of acquiring a urinary tract infection (UTI). Other complications related to prolonged indwelling urinary catheters include decreased mobility, damage to the meatus and/or urethra, increase use of antibiotics, increased length of stay, and pain. UTIs in acute care settings account for 30 to 40% of all health care associated infections (HAIs). Of these, 80% are catheter associated UTIs (CAUTIs). Purpose: To utilized the CDC (2009) bundle approach for CAUTI prevention and create a program which supports a multimodal method to improving urinary catheter use, maintenance, and removal, including a continuing competency program where role expansion is anticipated. Methods: A comprehensive review of the literature was conducted. Physicians were consulted through a power point presentation followed by a letter explaining the project, a questionnaire, and two selections of relevant literature. Nursing staff and allied health professionals from the target units of 3A and 3B medicine attended one of two lunch and learns. They were presented the project via a power point presentation and the same questionnaire as distributed to physicians. Results: Five e-learning modules, a revised policy, and clinical pathway have been developed to support staff with best practice knowledge transfer. Conclusion: Behaviour changes need to be approached with a framework, extensive consultation, and education. Sustainability of any practice change cannot occur without having completed the background work to ensure staff have access to tools to support the change.

Opportunistic Contact Graph Routing

L'ambiente di questa tesi è quello del Delay and Disruption Tolerant Networks (DTN), un'architettura di rete di telecomunicazioni avente come obiettivo le comunicazioni tra nodi di reti dette “challenged”, le quali devono affrontare problemi come tempi di propagazione elevati, alto tasso di errore e periodi di perdita delle connessioni. Il Bunde layer, un nuovo livello inserito tra trasporto e applicazione nell’architettura ISO/OSI, ed il protocollo ad esso associato, il Bundle Protocol (BP), sono stati progettati per rendere possibili le comunicazioni in queste reti. A volte fra la ricezione e l’invio può trascorrere un lungo periodo di tempo, a causa della indisponibilità del collegamento successivo; in questo periodo il bundle resta memorizzato in un database locale. Esistono varie implementazioni dell'architettura DTN come DTN2, implementazione di riferimento, e ION (Interplanetary Overlay Network), sviluppata da NASA JPL, per utilizzo in applicazioni spaziali; in esse i contatti tra i nodi sono deterministici, a differenza delle reti terrestri nelle quali i contatti sono generalmente opportunistici (non noti a priori). Per questo motivo all’interno di ION è presente un algoritmo di routing, detto CGR (Contact Graph Routing), progettato per operare in ambienti con connettività deterministica. È in fase di ricerca un algoritmo che opera in ambienti non deterministici, OCGR (Opportunistic Contact Graph Routing), che estende CGR. L’obiettivo di questa tesi è quello di fornire una descrizione dettagliata del funzionamento di OCGR, partendo necessariamente da CGR sul quale è basato, eseguire dei test preliminari, richiesti da NASA JPL, ed analizzarne i risultati per verificare la possibilità di utilizzo e miglioramento dell’algoritmo. Sarà inoltre descritto l’ambiente DTN e i principali algoritmi di routing per ambienti opportunistici. Nella parte conclusiva sarà presentato il simulatore DTN “The ONE” e l’integrazione di CGR e OCGR al suo interno.

Estensione dell'Abstraction Layer di DTNperf alle API di IBR-DTN

Sono dette “challenged networks” quelle reti in cui lunghi ritardi, frequenti partizionamenti e interruzioni, elevati tassi di errore e di perdita non consentono l’impiego dei classici protocolli di comunicazione di Internet, in particolare il TCP/IP. Il Delay-/Disruption-Tolerant Networking (DTN) è una soluzione per il trasferimento di dati attraverso queste reti. L’architettura DTN prevede l’introduzione, sopra il livello di trasporto, del cosiddetto “bundle layer”, che si occupa di veicolare messaggi, o bundle, secondo l’approccio store-and-forward: ogni nodo DTN conserva persistentemente un bundle finché non si presenta l’opportunità di inoltrarlo al nodo successivo verso la destinazione. Il protocollo impiegato nel bundle layer è il Bundle Protocol, le cui principali implementazioni sono tre: DTN2, l’implementazione di riferimento; ION, sviluppata da NASA-JPL e più orientata alle comunicazioni spaziali; IBR-DTN, rivolta soprattutto a dispositivi embedded. Ciascuna di esse offre API che consentono la scrittura di applicazioni in grado di inviare e ricevere bundle. DTNperf è uno strumento progettato per la valutazione delle prestazioni in ambito DTN. La più recente iterazione, DTNperf_3, è compatibile sia con DTN2 che con ION nella stessa versione del programma, grazie all’introduzione di un “Abstraction Layer” che fornisce un’unica interfaccia per l’interazione con le diverse implementazioni del Bundle Protocol e che solo internamente si occupa di invocare le API specifiche dell’implementazione attiva. Obiettivo della tesi è estendere l’Abstraction Layer affinché supporti anche IBR-DTN, cosicché DTNperf_3 possa essere impiegato indifferentemente su DTN2, ION e IBR DTN. Il lavoro sarà ripartito su tre fasi: nella prima esploreremo IBR DTN e le sue API; nella seconda procederemo all’effettiva estensione dell’Abstraction Layer; nella terza verificheremo il funzionamento di DTNperf a seguito delle modifiche, sia in ambiente esclusivamente IBR-DTN, sia ibrido.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.

Calibrated embeddings in the special Lagrangian and coassociative cases

Every closed, oriented, real analytic Riemannian 3-manifold can be isometrically embedded as a special Lagrangian submanifold of a Calabi-Yau 3-fold, even as the real locus of an antiholomorphic, isometric involution. Every closed, oriented, real analytic Riemannian 4-manifold whose bundle of self-dual 2-forms is trivial can be isometrically embedded as a coassociative submanifold in a G_2-manifold, even as the fixed locus of an anti-G_2 involution. These results, when coupled with McLean's analysis of the moduli spaces of such calibrated submanifolds, yield a plentiful supply of examples of compact calibrated submanifolds with nontrivial deformation spaces.

Consumer Behavior and Firm Competition

Understanding consumer behavior is critical for firms' decision making. How consumers make decisions about what they want and buy directly affect the profits of firms. Therefore, it is important to consider consumer behaviors and incorporate them into the model when studying the optimal strategy of firms and competition between firms. In this dissertation, I study rich and interesting consumer behaviors and their impact on firms' strategy in two essays. The first essay considers consumers' shopping cost which leads to their preference for one-stop shopping. I examine how store visit costs and consumer knowledge about a product affect the strategic store choice of consumers and, in turn, the pricing, customer service and advertising decisions of competing retailers. My analysis offers insights on how specialty stores can compete with big-box retailers. In the second essay, I focus on a well-established psychology phenomenon, cognitive dissonance. I incorporate the idea of cognitive dissonance into a model of spatial competition and examine its implications for selling strategy. I provide new insight on the profitability of advance selling and spot selling as well as the pricing of bundle and its components. Collectively, two essays in this dissertation introduce novel ways to model consumer behaviors and help to understand the impact of consumer behaviors on firm profitability and strategy.

Analytic Torsion, the Eta Invariant, and Closed Differential Forms on Spaces of Metrics

The central idea of this dissertation is to interpret certain invariants constructed from Laplace spectral data on a compact Riemannian manifold as regularized integrals of closed differential forms on the space of Riemannian metrics, or more generally on a space of metrics on a vector bundle. We apply this idea to both the Ray-Singer analytic torsion

and the eta invariant, explaining their dependence on the metric used to define them with a Stokes' theorem argument. We also introduce analytic multi-torsion, a generalization of analytic torsion, in the context of certain manifolds with local product structure; we prove that it is metric independent in a suitable sense.

Experimental and Theoretical Models to Probe Mechanisms of Biological Charge Flow

Nature is challenged to move charge efficiently over many length scales. From sub-nm to μm distances, electron-transfer proteins orchestrate energy conversion, storage, and release both inside and outside the cell. Uncovering the detailed mechanisms of biological electron-transfer reactions, which are often coupled to bond-breaking and bond-making events, is essential to designing durable, artificial energy conversion systems that mimic the specificity and efficiency of their natural counterparts. Here, we use theoretical modeling of long-distance charge hopping (Chapter 3), synthetic donor-bridge-acceptor molecules (Chapters 4, 5, and 6), and de novo protein design (Chapters 5 and 6) to investigate general principles that govern light-driven and electrochemically driven electron-transfer reactions in biology. We show that fast, μm-distance charge hopping along bacterial nanowires requires closely packed charge carriers with low reorganization energies (Chapter 3); singlet excited-state electronic polarization of supermolecular electron donors can attenuate intersystem crossing yields to lower-energy, oppositely polarized, donor triplet states (Chapter 4); the effective static dielectric constant of a small (~100 residue) de novo designed 4-helical protein bundle can change upon phototriggering an electron transfer event in the protein interior, providing a means to slow the charge-recombination reaction (Chapter 5); and a tightly-packed de novo designed 4-helix protein bundle can drastically alter charge-transfer driving forces of photo-induced amino acid radical formation in the bundle interior, effectively turning off a light-driven oxidation reaction that occurs in organic solvent (Chapter 6). This work leverages unique insights gleaned from proteins designed from scratch that bind synthetic donor-bridge-acceptor molecules that can also be studied in organic solvents, opening new avenues of exploration into the factors critical for protein control of charge flow in biology.

Geometry of Dirac Operators

Let $M$ be a compact, oriented, even dimensional Riemannian manifold and let $S$ be a Clifford bundle over $M$ with Dirac operator $D$. Then \[ \textsc{Atiyah Singer: } \quad \text{Ind } \mathsf{D}= \int_M \hat{\mathcal{A}}(TM)\wedge \text{ch}(\mathcal{V}) \] where $\mathcal{V} =\text{Hom}_{\mathbb{C}l(TM)}(\slashed{\mathsf{S}},S)$. We prove the above statement with the means of the heat kernel of the heat semigroup $e^{-tD^2}$. The first outstanding result is the McKean-Singer theorem that describes the index in terms of the supertrace of the heat kernel. The trace of heat kernel is obtained from local geometric information. Moreover, if we use the asymptotic expansion of the kernel we will see that in the computation of the index only one term matters. The Berezin formula tells us that the supertrace is nothing but the coefficient of the Clifford top part, and at the end, Getzler calculus enables us to find the integral of these top parts in terms of characteristic classes.