Annular flow of viscoelastic fluids: Analytical and numerical solutions

This work provides analytical and numerical solutions for the linear, quadratic and exponential Phan–Thien–Tanner (PTT) viscoelastic models, for axial and helical annular fully-developed flows under no slip and slip boundary conditions, the latter given by the linear and nonlinear Navier slip laws. The rheology of the three PTT model functions is discussed together with the influence of the slip velocity upon the flow velocity and stress fields. For the linear PTT model, full analytical solutions for the inverse problem (unknown velocity) are devised for the linear Navier slip law and two different slip exponents. For the linear PTT model with other values of the slip exponent and for the quadratic PTT model, the polynomial equation for the radial location (β) of the null shear stress must be solved numerically. For both models, the solution of the direct problem is given by an iterative procedure involving three nonlinear equations, one for β, other for the pressure gradient and another for the torque per unit length. For the exponential PTT model we devise a numerical procedure that can easily compute the numerical solution of the pure axial flow problem

Implementation of integral viscoelastic constitutive models in OpenFOAM® computational library

This work reports the implementation and verification of a new so lver in OpenFOAM® open source computational library, able to cope with integral viscoelastic models based on the integral upper-convected Maxwell model. The code is verified through the comparison of its predictions with analytical solutions and numerical results obtained with the differential upper-convected Maxwell model

Structure-property relationships in polymer nanocomposites

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos

Modelling Amazonian forest eddy covariance data: a comparison of big leaf versus sun/shade models for the C-14 tower at Manaus I. Canopy photosynthesis

In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.

Abundance of two Dendrocincla woodcreepers (aves: Dendrocolaptidae) in relation to forest structure in Central Amazonia

Few studies have been conducted to verify how the structure of the forest affects the occurence and abundance of neotropical birds. Our research was undertaken between January 2002 and July 2004 at the Reserva Ducke, near Manaus (02º55',03º01'S; 59º53',59º59'W) in central Amazonia, to verify how the forest structure affects the occurrence and abundance of two bird species: the Plain-brown Woodcreeper Dendrocincla fuliginosa and the White-chinned Woodcreeper Dendrocincla merula. Bird species occurrence was recorded using lines of 20 mist-nets (one sample unit), along 51 1-km transects distributed along 9 pararel 8 km trails covering an area of 6400 ha. Along these transects, we placed 50 x 50m plots where we recorded forest structure components (tree abundance, canopy openness, leaf litter, standing dead trees, logs, proximity to streams, and altitude). We then related these variables to bird occurence and abundance using multiple logistic and multiple linear regression models, respectively. We found that D. fuliginosa frequently used plateau areas; being more abundant in areas with more trees. On the other hand, D. merula occurred more frequently and was more abundant in areas with low tree abundance. Our results suggest that although both species overlap in the reserve (both were recorded in at least 68% of the sampled sites), they differ in the way they use the forest microhabitats. Therefore, local variation in the forest structure may contribute to the coexistence of congeneric species and may help to maintain local alpha diversity.

Lithium ion rechargeable batteries: State of the art and future needs of microscopic theoretical models and simulations

This review deals with the recent developments and present status of the theoretical models for the simulation of the performance of lithium ion batteries. Preceded by a description of the main materials used for each of the components of a battery -anode, cathode and separator- and how material characteristics affect battery performance, a description of the main theoretical models describing the operation and performance of a battery are presented. The influence of the most relevant parameters of the models, such as boundary conditions, geometry and material characteristics are discussed. Finally, suggestions for future work are proposed.

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

Exploring female mice interstrain differences relevant for models of depression

Depression is an extremely heterogeneous disorder. Diverse molecular mechanisms have been suggested to underlie its etiology. To understand the molecular mechanisms responsible for this complex disorder, researchers have been using animal models extensively, namely mice from various genetic backgrounds and harboring distinct genetic modifications. The use of numerous mouse models has contributed to enrich our knowledge on depression. However, accumulating data also revealed that the intrinsic characteristics of each mouse strain might influence the experimental outcomes, which may justify some conflicting evidence reported in the literature. To further understand the impact of the genetic background, we performed a multimodal comparative study encompassing the most relevant parameters commonly addressed in depression, in three of the most widely used mouse strains: Balb/c, C57BL/6, and CD-1. Moreover, female mice were selected for this study taken into account the higher prevalence of depression in women and the fewer animal studies using this gender. Our results show that Balb/c mice have a more pronounced anxious-like behavior than CD-1 and C57BL/6 mice, whereas C57BL/6 animals present the strongest depressive-like trait. Furthermore, C57BL/6 mice display the highest rate of proliferating cells and brain-derived neurotrophic factor (Bdnf) expression levels in the hippocampus, while hippocampal dentate granular neurons of Balb/c mice show smaller dendritic lengths and fewer ramifications. Of notice, the expression levels of inducible nitric oxide synthase (iNos) predict 39.5% of the depressive-like behavior index, which suggests a key role of hippocampal iNOS in depression. Overall, this study reveals important interstrain differences in several behavioral dimensions and molecular and cellular parameters that should be considered when preparing and analyzing experiments addressing depression using mouse models. It further contributes to the literature by revealing the predictive value of hippocampal iNos expression levels in depressive-like behavior, irrespectively of the mouse strain.

Cylindrically symmetric models of gravitational collapse to black holes: a short review

We survey results about exact cylindrically symmetric models of gravitational collapse in General Relativity. We focus on models which result from the matching of two spacetimes having collapsing interiors which develop trapped surfaces and vacuum exteriors containing gravitational waves. We collect some theorems from the literature which help to decide a priori about eventual spacetime matchings. We revise, in more detail, some toy models which include some of the main mathematical and physical issues that arise in this context, and compute the gravitational energy flux through the matching boundary of a particular collapsing region. Along the way, we point out several interesting open problems.

Specification and testing of multiplicative time-varying GARCH models with applications

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns.

Exploring the role of O-Mannosylation in the modulation of E-Cadherin function in Gastric Cancer cell line models

Dissertação de mestrado em Bioquímica Aplicada – Biomedicina

Evaluating biomaterial-and microfluidic-based 3D tumor models

Cancer is a major cause of morbidity and mortality worldwide, with a disease burden estimated to increase in the coming decades. Disease heterogeneity and limited information on cancer biology and disease mechanisms are aspects that 2D cell cultures fail to address. We review the current "state-of-the-art" in 3D Tissue Engineering (TE) models developed for and used in cancer research. Scaffold-based TE models and microfluidics, are assessed for their potential to fill the gap between 2D models and clinical application. Recent advances in combining the principles of 3D TE models and microfluidics are discussed, with a special focus on biomaterials and the most promising chip-based 3D models.

Single line for assembly just-in-sequence multiple models

Programa Doutoral em Líderes para as Indústrias Tecnológicas

Metabolic engineering with multi-objective optimization of kinetic models

Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.

A survey of distributed data aggregation algorithms

Distributed data aggregation is an important task, allowing the de- centralized determination of meaningful global properties, that can then be used to direct the execution of other applications. The resulting val- ues result from the distributed computation of functions like count, sum and average. Some application examples can found to determine the network size, total storage capacity, average load, majorities and many others. In the last decade, many di erent approaches have been pro- posed, with di erent trade-o s in terms of accuracy, reliability, message and time complexity. Due to the considerable amount and variety of ag- gregation algorithms, it can be di cult and time consuming to determine which techniques will be more appropriate to use in speci c settings, jus- tifying the existence of a survey to aid in this task. This work reviews the state of the art on distributed data aggregation algorithms, providing three main contributions. First, it formally de nes the concept of aggrega- tion, characterizing the di erent types of aggregation functions. Second, it succinctly describes the main aggregation techniques, organizing them in a taxonomy. Finally, it provides some guidelines toward the selection and use of the most relevant techniques, summarizing their principal characteristics.