A generalised formulation for computing the microbuckling load in periodic layered materials

Acknowledgments The financial support of the part of this research by The Royal Society, The Royal Academy of Engineering and The Carnegie Trust for the Universities of Scotland is gratefully acknowledged.

A generalised formulation for computing the microbuckling load in periodic layered materials

Acknowledgments The financial support of the part of this research by The Royal Society, The Royal Academy of Engineering and The Carnegie Trust for the Universities of Scotland is gratefully acknowledged.

Mise au point de micelles polymères pour la formulation d'agents anticancéreux hydrophobes

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Pre-formulation and systematic evaluation of amino acid assisted permeability of insulin across in vitro buccal cell layers

The aim of this work was to investigate alternative safe and effective permeation enhancers for buccal peptide delivery. Basic amino acids improved insulin solubility in water while 200 and 400 µg/mL lysine significantly increased insulin solubility in HBSS. Permeability data showed a significant improvement in insulin permeation especially for 10 µg/mL of lysine (p < 0.05) and 10 µg/mL histidine (p < 0.001), 100 µg/mL of glutamic acid (p < 0.05) and 200 µg/mL of glutamic acid and aspartic acid (p < 0.001) without affecting cell integrity; in contrast to sodium deoxycholate which enhanced insulin permeability but was toxic to the cells. It was hypothesized that both amino acids and insulin were ionised at buccal cavity pH and able to form stable ion pairs which penetrated the cells as one entity; while possibly triggering amino acid nutrient transporters on cell surfaces. Evidence of these transport mechanisms was seen with reduction of insulin transport at suboptimal temperatures as well as with basal-to-apical vectoral transport, and confocal imaging of transcellular insulin transport. These results obtained for insulin is the first indication of a possible amino acid mediated transport of insulin via formation of insulin-amino acid neutral complexes by the ion pairing mechanism.

The effects of formulation and processing on surface characteristics and functional properties of dairy powders

The objectives of this thesis were to (i) study the effect of increasing protein concentration in milk protein concentrate (MPC) powders on surface composition and sorption properties; (ii) examine the effect of increasing protein content on the rehydration properties of MPC; (iii) study the physicochemical properties of spraydried emulsion-containing powders having different water and oil contents; (iv) analyse the effect of protein type on water sorption and diffusivity properties in a protein/lactose dispersion, and; (v) characterise lactose crystallisation and emulsion stability of model infant formula containing intact or hydrolysed whey proteins. Surface composition of MPC powders (protein contents 35 - 86 g / 100 g) indicated that fat and protein were preferentially located on the surface of powders. Low protein powder (35 g / 100 g) exhibited lactose crystallisation, whereas powders with higher protein contents did not, due to their high protein: lactose ratio. Insolubility was evident in high protein MPCs and was primarily related to insolubility of the casein fraction. High temperature (50 °C) was required for dissolution of high protein MPCs (protein content > 60 g / 100 g). The effect of different oil types and spray-drying outlet temperature on the physicochemical properties of the resultant fat-filled powders was investigated and showed that increasing outlet temperature reduced water content, water activity and tapped bulk density, irrespective of oil type, and increased solvent-extractable free fat for all oil types and onset of glass transition (Tg) and crystallisation (Tcr) temperature. Powder dispersions of protein/lactose (0.21:1), containing either intact or hydrolysed whey protein (12 % degree of hydrolysis; DH), were spray-dried at pilot scale. Moisture sorption analysis at 25 °C showed that dispersions containing intact whey protein exhibited lactose crystallisation at a lower relative humidity (RH). Dispersions containing hydrolysed whey protein had significantly higher (P < 0.05) water diffusivity. Finally, a spray-dried model infant formula was produced containing hydrolysed or intact whey as the protein with sunflower oil as the fat source. Reconstituted, hydrolysed formula had a significantly (P < 0.05) higher fat globule size and lower emulsion stability than intact formula. Lactose crystallisation in powders occurred at higher RH for hydrolysed formula. In conclusion, this research has shown the effect of altering the protein type, protein composition, and oil type on the surface composition and physical properties of different dairy powders, and how these variations greatly affect their rehydration characteristics and storage stability.

Mise au point de micelles polymères pour la formulation d'agents anticancéreux hydrophobes

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Novel Formulation and Efficient Solution Strategy for Strategic Optimization of an Industrial Chemical Supply Chain Under Demand Uncertainty

This paper is concerned with strategic optimization of a typical industrial chemical supply chain, which involves a material purchase and transportation network, several manufacturing plants with on-site material and product inventories, a product transportation network and several regional markets. In order to address large uncertainties in customer demands at the different regional markets, a novel robust scenario formulation, which has been developed by the authors recently, is tailored and applied for the strategic optimization. Case study results show that the robust scenario formulation works well for this real industrial supply chain system, and it outperforms the deterministic formulation and the classical scenario-based stochastic programming formulation by generating better expected economic performance and solutions that are guaranteed to be feasible for all uncertainty realizations. The robust scenario problem exhibits a decomposable structure that can be taken advantage of by Benders decomposition for efficient solution, so the application of Benders decomposition to the solution of the strategic optimization is also discussed. The case study results show that Benders decomposition can reduce the solution time by almost an order of magnitude when the number of scenarios in the problem is large.

Terapia de aceptación y compromiso en un caso de tras¬torno mixto de ansiedad y depresión en una paciente con cáncer

This paper introduces the case of a woman with breast cancer who had developed a mixed depressive-anxiety disorder with avoidance behaviors. The patient presented depressive symptoms like listlessness, insomnia, weeping, food disorders and hopelessness though. Also, she exhibited physiological arousal and restlessness feelings. Additionally, the patient had an avoidance patron behavior in relation with all stimulus she believed could hurt her. Based on the Acceptance and Commitment Therapy (ACT) the intervention planted the following objectives: the patient will learn to accept her illness and the emotional distress that she was experiencing, also, the patient will recover the other areas of her life that she had abandoned. The treatment was developed in 14 sessions. The therapist used these techniques: creative hopelessness, disabling verbal functions, values clarification and loss of control over private events. In the results, it was observed a positive change in the behavior of the patient as well as a decrease in emotional distress that was his reason for initial consultation

Effect of the Electrolyte Formulation on the Performances of Edlc and Li-Ion Batteries

One of the most important components in electrochemical storage devices (batteries and supercapacitors) is undoubtedly the electrolyte. The basic function of any electrolyte in these systems is the transport of ions between the positive and negative electrodes. In addition, electrochemical reactions occurring at each electrode/electrolyte interface are the origin of the current generated by storage devices. In other words, performances (capacity, power, efficiency and energy) of electrochemical storage devices are strongly related to the electrolyte properties, as well as, to the affinity for the electrolyte to selected electrode materials. Indeed, the formulation of electrolyte presenting good properties, such as high ionic conductivity and low viscosity, is then required to enhance the charge transfer reaction at electrode/electrolyte interface (e.g. charge accumulation in the case of Electrochemical Double Layer Capacitor, EDLC). For practical and safety considerations, the formulation of novel electrolytes presenting a low vapor pressure, a large liquid range temperature, a good thermal and chemical stabilities is also required.

This lecture will be focused on the effect of the electrolyte formulation on the performances of electrochemical storage devices (Li-ion batteries and supercapacitors). During which, a summary of the physical, thermal and electrochemical data obtained by our group, recently, on the formulation of novel electrolyte-based on the mixture of an ionic liquid (such as EmimNTf2 and Pyr14NTf2) and carbonate or dinitrile solvents will be presented and commented. The impact of the electrolyte formulation on the storage performances of EDLC and Li-ion batteries will be also discussed to further understand the relationship between electrolyte formulation and electrochemical performances. This talk will also be an opportunity to further discuss around the effects of additives (SEI builder: fluoroethylene carbonate and vinylene carbonate), ionic liquids, structure and nature of lithium salt (LiTFSI vs LiPF6) on the cyclability of negative electrode to then enhance the electrolyte formulation. For that, our recent results on TiSnSb and graphite negative electrodes will be presented and discussed, for example 1,2.

1-C. Marino, A. Darwiche1, N. Dupré, H.A. Wilhelm, B. Lestriez, H. Martinez, R. Dedryvère, W. Zhang, F. Ghamouss, D. Lemordant, L. Monconduit “ Study of the Electrode/Electrolyte Interface on Cycling of a Conversion Type Electrode Material in Li Batteries” J. Phys.chem. C, 2013, 117, 19302-19313

2- Mouad Dahbi, Fouad Ghamouss, Mérièm Anouti, Daniel Lemordant, François Tran-Van “Electrochemical lithiation and compatibility of graphite anode using glutaronitrile/dimethyl carbonate mixtures containing LiTFSI as electrolyte” 2013, 43, 4, 375-385.

Face recognition using a unified 3D morphable model

We address the problem of 3D-assisted 2D face recognition in scenarios when the input image is subject to degradations or exhibits intra-personal variations not captured by the 3D model. The proposed solution involves a novel approach to learn a subspace spanned by perturbations caused by the missing modes of variation and image degradations, using 3D face data reconstructed from 2D images rather than 3D capture. This is accomplished by modelling the difference in the texture map of the 3D aligned input and reference images. A training set of these texture maps then defines a perturbation space which can be represented using PCA bases. Assuming that the image perturbation subspace is orthogonal to the 3D face model space, then these additive components can be recovered from an unseen input image, resulting in an improved fit of the 3D face model. The linearity of the model leads to efficient fitting. Experiments show that our method achieves very competitive face recognition performance on Multi-PIE and AR databases. We also present baseline face recognition results on a new data set exhibiting combined pose and illumination variations as well as occlusion.

Unified: The Musical by Guy Le Jeune

A large-scale community play based on interviews with former workers at the Unifi textile plant in Letterkenny, Co. Donegal

Automated Equation Formulation for Causal Loop Diagrams

The annotation of Business Dynamics models with parameters and equations, to simulate the system under study and further evaluate its simulation output, typically involves a lot of manual work. In this paper we present an approach for automated equation formulation of a given Causal Loop Diagram (CLD) and a set of associated time series with the help of neural network evolution (NEvo). NEvo enables the automated retrieval of surrogate equations for each quantity in the given CLD, hence it produces a fully annotated CLD that can be used for later simulations to predict future KPI development. In the end of the paper, we provide a detailed evaluation of NEvo on a business use-case to demonstrate its single step prediction capabilities.