Visualization and prediction of spatial deformation using thin-plate splines in the context of scoliosis

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Visualization and prediction of spatial deformation using thin-plate splines in the context of scoliosis

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Irreducibility of Random Hilbert Schemes

We prove that a random Hilbert scheme that parametrizes the closed subschemes with a fixed Hilbert polynomial in some projective space is irreducible and nonsingular with probability greater than $0.5$. To consider the set of nonempty Hilbert schemes as a probability space, we transform this set into a disjoint union of infinite binary trees, reinterpreting Macaulay's classification of admissible Hilbert polynomials. Choosing discrete probability distributions with infinite support on the trees establishes our notion of random Hilbert schemes. To bound the probability that random Hilbert schemes are irreducible and nonsingular, we show that at least half of the vertices in the binary trees correspond to Hilbert schemes with unique Borel-fixed points.

Electric shock causes physiological stress responses in shore crabs, consistent with prediction of pain

Animal pain is defined by a series of expectations or criteria, one of which is that there should be a physiological stress response associated with noxious stimuli. While crustacean stress responses have been demonstrated they are typically preceded by escape behaviour and thus the physiological change might be attributed to the behaviour rather than a pain experience. We found higher levels of stress as measured by lactate in shore crabs exposed to brief electric shock than non-shocked controls. However, shocked crabs showed more vigorous behaviour than controls. We then matched crabs with the same level of behaviour and still found that shocked crabs had stronger stress response compared with controls. The finding of the stress response, coupled with previous findings of long-Term motivational change and avoidance learning, fulfils the criteria expected of a pain experience.

Extended Energy Vector Prediction of Ambisonically Reproduced Image Direction at Off-Centre Listening Positions

This paper presents an extension to the energy vector, well known in the Ambisonics literature, to improve its predictions of localisation at off-centre listening positions. In determining the source direction, a perceptual weight is assigned to each loudspeaker gain, taking into account the relative arrival times, levels, and directions of the loudspeaker signals. The proposed model is evaluated alongside the original energy vector and two binaural models through comparison with the results of recent perceptual studies. The extended version was found to provide results that were at least 50% more accurate than the second best predictor for two experiments involving off-centre listeners with first- and third-order Ambisonics systems.

Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks

The focus of this work is to develop the knowledge of prediction of the physical and chemical properties of processed linear low density polyethylene (LLDPE)/graphene nanoplatelets composites. Composites made from LLDPE reinforced with 1, 2, 4, 6, 8, and 10 wt% grade C graphene nanoplatelets (C-GNP) were processed in a twin screw extruder with three different screw speeds and feeder speeds (50, 100, and 150 rpm). These applied conditions are used to optimize the following properties: thermal conductivity, crystallization temperature, degradation temperature, and tensile strength while prediction of these properties was done through artificial neural network (ANN). The three first properties increased with increase in both screw speed and C-GNP content. The tensile strength reached a maximum value at 4 wt% C-GNP and a speed of 150 rpm as this represented the optimum condition for the stress transfer through the amorphous chains of the matrix to the C-GNP. ANN can be confidently used as a tool to predict the above material properties before investing in development programs and actual manufacturing, thus significantly saving money, time, and effort.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Simplified model for prediction of compressive strength of alkali-activated natural pozzolans

The assessment of pozzolanic activity is essential for estimating the reaction of a material as pozzolan. Natural pozzolans can be activated and condensed with sodium silicate in an alkaline environment to synthesize high performance cementitious construction materials with low environmental impact. In this paper, the pozzolanic activities of five natural pozzolans are studied. The correlation between type and chemical composition of natural pozzolan, which affects the formation of the geopolymer gel phase, both for the calcined and untreated natural pozzolans, have been reviewed. The improvement in pozzolanic properties was studied following heat treatment including calcinations and/or elevated curing temperature by using alkali solubility, and compressive strength tests. A model was developed to allow prediction of the alkali-activated pozzolan strength versus their chemical compositions, alkali solubility, and crystallinity.

The influence of socio-demographic, psychological and knowledge-related variables alongside perceived cooking and food skills abilities in the prediction of diet quality in adults: a nationally representative cross-sectional study

Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

Validation of stress indicators for the assessment of animal welfare and prediction of pork meat quality variation at commercial level

Les procédures appliquées avant l’abattage des animaux influencent directement la qualité de la viande en modulant l’état physiologique des porcs; ainsi, l’augmentation de la température corporelle, les taux élevés de lactate sanguin et l’épuisement des réserves de glycogène entre autres, occasionnent la majorité des baisses de qualité. L’objectif de cette thèse était de valider des outils indicateurs de stress porcin pour les fermes et les abattoirs. Ceux-ci seraient appliqués à la surveillance du bien-être animal et à la prédiction de variation de qualité de la viande porcine au niveau commercial. Premierement, les résultats de la thèse ont permis de conclure qu’un des outils développés (analyseur portatif de lactate) mesure la variation du niveau de lactate sanguin associé à l’état physiologique des porcs dans la phase péri-mortem et aide à expliquer la variation de la qualité de la viande chez le porc à l’abattoir, en particulier dans les muscles du jambon. Deuxièmement, les résultats des audits du bien-être animal appliqués de la ferme à l’abattoir ont démontré que la qualité du système d’élevage à la ferme d’origine et les compétences du chauffeur de camion sont d’importants critères affectant la réponse comportementale des porcs à la manipulation avant l’abattage. Ces résultats ont également démontré que les conditions de logement à la ferme (la faible densité et l’enrichissement dans les enclos), le comportement des porcs en période pré-abattage (glissade), ainsi que les interventions du manipulateur (utilisation du bâton électrique) dans la zone d’étourdissement de l’abattoir affectent négativement la variation de la qualité de la viande. L’application des protocoles d’audits dans la filière porcine a également démontré que le respect des critères de bien-être animal fixés par un outil de vérification est primordiale et permet de contrôler les conditions de bien-être des porcs à chaque étape de la période pré-abattage, de produire une viande de qualité supérieure et de réduire les pertes. Les audits de bien-être animal sont donc un outil qui apporte des resultats très pertinents pour aider a éviter les variations de la qualité de la viande chez le porc. Troisièmement, la thermographie infrarouge s’est avéré être une technique prometteuse permettant d’évaluer la variation de température corporelle de l’animal pendant et après un stress physique, en particulier lorsque cette mesure est prise derrière les oreilles. En conclusion, les outils validés à travers cette thèse représentent des méthodologies non invasives et potentiellement complémentaires à d’autres approches d’évaluation de l’état physiologique et du bien-être animal par rapport au stress, permettant de réduire les pertes de qualité de viande (par exemple en utilisation conjointe avec le niveau de lactate sanguin et les indicateurs de stress comportemental, entre autres).

Prediction of Sudden Cardiac Arrest for Patients with Congestive Heart Failure

Thesis (Ph.D.)--University of Washington, 2016-07

Prediction of cold shuts using an unstructured mesh finite volume code

Abstract not available

Prediction of defects in steel castings with a multi-physics numerical code

Abstract not available