Computational speed-up with a single qudit

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

NUMERICAL AND ANALYTICAL VERIFICATION OF A MULTISCALE COMPUTATIONAL MODEL FOR IMPACT PROBLEMS IN HETEROGENEOUS VISCOELASTIC MATERIALS WITH EVOLVING DAMAGE

Composites are engineered materials that take advantage of the particular properties of each of its two or more constituents. They are designed to be stronger, lighter and to last longer which can lead to the creation of safer protection gear, more fuel efficient transportation methods and more affordable materials, among other examples. This thesis proposes a numerical and analytical verification of an in-house developed multiscale model for predicting the mechanical behavior of composite materials with various configurations subjected to impact loading. This verification is done by comparing the results obtained with analytical and numerical solutions with the results found when using the model. The model takes into account the heterogeneity of the materials that can only be noticed at smaller length scales, based on the fundamental structural properties of each of the composite’s constituents. This model can potentially reduce or eliminate the need of costly and time consuming experiments that are necessary for material characterization since it relies strictly upon the fundamental structural properties of each of the composite’s constituents. The results from simulations using the multiscale model were compared against results from direct simulations using over-killed meshes, which considered all heterogeneities explicitly in the global scale, indicating that the model is an accurate and fast tool to model composites under impact loads. Advisor: David H. Allen

Generalizing the dynamic field theory of spatial cognition across real and developmental time scales

Within cognitive neuroscience, computational models are designed to provide insights into the organization of behavior while adhering to neural principles. These models should provide sufficient specificity to generate novel predictions while maintaining the generality needed to capture behavior across tasks and/or time scales. This paper presents one such model, the Dynamic Field Theory (DFT) of spatial cognition, showing new simulations that provide a demonstration proof that the theory generalizes across developmental changes in performance in four tasks—the Piagetian A-not-B task, a sandbox version of the A-not-B task, a canonical spatial recall task, and a position discrimination task. Model simulations demonstrate that the DFT can accomplish both specificity—generating novel, testable predictions—and generality—spanning multiple tasks across development with a relatively simple developmental hypothesis. Critically, the DFT achieves generality across tasks and time scales with no modification to its basic structure and with a strong commitment to neural principles. The only change necessary to capture development in the model was an increase in the precision of the tuning of receptive fields as well as an increase in the precision of local excitatory interactions among neurons in the model. These small quantitative changes were sufficient to move the model through a set of quantitative and qualitative behavioral changes that span the age range from 8 months to 6 years and into adulthood. We conclude by considering how the DFT is positioned in the literature, the challenges on the horizon for our framework, and how a dynamic field approach can yield new insights into development from a computational cognitive neuroscience perspective.

Gas-phase reactivity of protonated 2-oxazoline derivatives: mass spectrometry and computational studies

RATIONALE: Oxazolines have attracted the attention of researchers worldwide due to their versatility as carboxylic acid protecting groups, chiral auxiliaries, and ligands for asymmetric catalysis. Electrospray ionization tandem mass spectrometric (ESI-MS/MS) analysis of five 2-oxazoline derivatives has been conducted, in order to understand the influence of the side chain on the gas-phase dissociation of these protonated compounds under collision-induced dissociation (CID) conditions. METHODS: Mass spectrometric analyses were conducted in a quadrupole time-of-flight (Q-TOF) spectrometer fitted with electrospray ionization source. Protonation sites have been proposed on the basis of the gas-phase basicity, proton affinity, atomic charges, and a molecular electrostatic potential map obtained on the basis of the quantum chemistry calculations at the B3LYP/6-31 + G(d, p) and G2(MP2) levels. RESULTS: Analysis of the atomic charges, gas-phase basicity and proton affinities values indicates that the nitrogen atom is a possible proton acceptor site. On the basis of these results, two main fragmentation processes have been suggested: one taking place via neutral elimination of the oxazoline moiety (99 u) and another occurring by sequential elimination of neutral fragments with 72 u and 27 u. These processes should lead to formation of R+. CONCLUSIONS: The ESI-MS/MS experiments have shown that the side chain could affect the dissociation mechanism of protonated 2-oxazoline derivatives. For the compound that exhibits a hydroxyl at the lateral chain, water loss has been suggested to happen through an E2-type elimination, in an exothermic step. Copyright (C) 2012 John Wiley & Sons, Ltd.

Error Upper Bounds for a Computational Method for Nonlinear Boundary and Initial-Value Problems

This work develops a computational approach for boundary and initial-value problems by using operational matrices, in order to run an evolutive process in a Hilbert space. Besides, upper bounds for errors in the solutions and in their derivatives can be estimated providing accuracy measures.

Computational tools for comparing asymmetric GARCH models via Bayes factors

In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare GARCH models from a Bayesian perspective. We allow for possibly heavy tailed and asymmetric distributions in the error term. We use a general method proposed in the literature to introduce skewness into a continuous unimodal and symmetric distribution. For each model we compute an approximation to the marginal likelihood, based on the MCMC output. From these approximations we compute Bayes factors and posterior model probabilities. (C) 2012 IMACS. Published by Elsevier B.V. All rights reserved.

Analysis of energy dissipation in stirred suspension polymerisation reactors using computational fluid dynamics

This work evaluates the spatial distribution of normalised rates of droplet breakage and droplet coalescence in liquidliquid dispersions maintained in agitated tanks at operation conditions normally used to perform suspension polymerisation reactions. Particularly, simulations are performed with multiphase computational fluid dynamics (CFD) models to represent the flow field in liquidliquid styrene suspension polymerisation reactors for the first time. CFD tools are used first to compute the spatial distribution of the turbulent energy dissipation rates (e) inside the reaction vessel; afterwards, normalised rates of droplet breakage and particle coalescence are computed as functions of e. Surprisingly, multiphase simulations showed that the rates of energy dissipation can be very high near the free vortex surfaces, which has been completely neglected in previous works. The obtained results indicate the existence of extremely large energy dissipation gradients inside the vessel, so that particle breakage occurs primarily in very small regions that surround the impeller and the free vortex surface, while particle coalescence takes place in the liquid bulk. As a consequence, particle breakage should be regarded as an independent source term or a boundary phenomenon. Based on the obtained results, it can be very difficult to justify the use of isotropic assumptions to formulate particle population balances in similar systems, even when multiple compartment models are used to describe the fluid dynamic behaviour of the agitated vessel. (C) 2011 Canadian Society for Chemical Engineering

Computational and experimental characterization of a low-cost piezoelectric valveless diaphragm pump

Flow pumps act as important devices in areas such as Bioengineering, Medicine, and Pharmacy, among other areas of Engineering, mainly for delivering liquids or gases at small-scale and precision flow rate quantities. Principles for pumping fluids based on piezoelectric actuators have been widely studied, since they allow the construction of pump systems for displacement of small fluid volumes with low power consumption. This work studies valveless piezoelectric diaphragm pumps for flow generation, which uses a piezoelectric ceramic (PZT) as actuator to move a membrane (diaphragm) up and down as a piston. The direction of the flow is guaranteed by valveless configuration based on a nozzle-diffuser system that privileges the flow in just one pumping direction. Most research efforts on development of valveless flow pump deal either with computational simulations based on simplified models or with simplified physical approaches based on analytical models. The main objective of this work is the study of a methodology to develop a low-cost valveless piezoelectric diaphragm flow pump using computational simulations, parametric study, prototype manufacturing, and experimental characterization. The parametric study has shown that the eccentricity of PZT layer and metal layer plays a key role in the performance of the pump.

The nature of Ru-NO bonds in ruthenium tetraazamacrocycle nitrosyl complexes-a computational study

Ruthenium complexes including nitrosyl or nitrite complexes are particularly interesting because they can not only scavenge but also release nitric oxide in a controlled manner, regulating the NO-level in vivo. The judicious choice of ligands attached to the [RuNO] core has been shown to be a suitable strategy to modulate NO reactivity in these complexes. In order to understand the influence of different equatorial ligands on the electronic structure of the Ru-NO chemical bonding, and thus on the reactivity of the coordinated NO, we propose an investigation of the nature of the Ru-NO chemical bond by means of energy decomposition analysis (EDA), considering tetraamine and tetraazamacrocycles as equatorial ligands, prior to and after the reduction of the {RuNO}(6) moiety by one electron. This investigation provides a deep insight into the Ru-NO bonding situation, which is fundamental in designing new ruthenium nitrosyl complexes with potential biological applications.

Can neuroimaging be used as a support to diagnosis of borderline personality disorder? An approach based on computational neuroanatomy and machine learning

Several recent studies in literature have identified brain morphological alterations associated to Borderline Personality Disorder (BPD) patients. These findings are reported by studies based on voxel-based-morphometry analysis of structural MRI data, comparing mean gray-matter concentration between groups of BPD patients and healthy controls. On the other hand, mean differences between groups are not informative about the discriminative value of neuroimaging data to predict the group of individual subjects. In this paper, we go beyond mean differences analyses, and explore to what extent individual BPD patients can be differentiated from controls (25 subjects in each group), using a combination of automated-morphometric tools for regional cortical thickness/volumetric estimation and Support Vector Machine classifier. The approach included a feature selection step in order to identify the regions containing most discriminative information. The accuracy of this classifier was evaluated using the leave-one-subject-out procedure. The brain regions indicated as containing relevant information to discriminate groups were the orbitofrontal, rostral anterior cingulate, posterior cingulate, middle temporal cortices, among others. These areas, which are distinctively involved in emotional and affect regulation of BPD patients, were the most informative regions to achieve both sensitivity and specificity values of 80% in SVM classification. The findings suggest that this new methodology can add clinical and potential diagnostic value to neuroimaging of psychiatric disorders. (C) 2012 Elsevier Ltd. All rights reserved.

Cyclic Voltammetry and Computational Chemistry Studies on the Evaluation of the Redox Behavior of Parabens and other Analogues

Parabens are antimicrobial preservatives widely used in pharmaceutical, cosmetic and food industries. The alkyl chain connected to the ester group defines some important physicochemical characteristics of these compounds, including the partition coefficient and redox properties. The voltammetric and computational analyses were carried out in order to evaluate the redox behavior of these compounds and other phenolic analogues. A strong correlation between chemical substituents inductive effects of parabens with redox potentials was observed. Using cyclic voltammetry and glassy carbon working electrode, only one irreversible anodic peak was observed around 0.8 V for methylparaben (MP), ethylparaben (EP), propylparaben (PP), butylparaben (BP), benzylparaben (BzP) and p-substituted phenolic analogues. The electrodonating inductive effect of alkyl groups was demonstrated by the anodic oxidation potential shift to lower values as the carbon number increases and, therefore the parabens (and other phenolic analogues) oxidation processes to the quinonoidic forms showed great dependence on the substituent pattern.

Expanding the horizontal capabilities of CRT monitors using artificial inter-pixel steps for neuroscience experiments

This article describes the development of a visual stimulus generator to be used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of a fixed image that is displaced horizontally according to the stimulus data. The system is capable of displaying 640 x 480 pixels with 256 intensity levels at 200 frames per second (FPS) on conventional raster monitors. To double the possible horizontal positioning possibilities from 640 to 1280, a novel technique is presented introducing artificial inter-pixel steps. The implementation consists in using two video frame buffers containing each a distinct view of the desired image pattern. This implementation generates a visual effect capable of doubling the horizontal positioning capabilities of the visual stimulus generator allowing more precise and movements more contiguous. (C) 2011 Elsevier Inc. All rights reserved.

IDM - A New Parallel Methodology to Calculate the Determinant of Matrices of the Order n, with Computational Complexity O(n)

This paper presents a new parallel methodology for calculating the determinant of matrices of the order n, with computational complexity O(n), using the Gauss-Jordan Elimination Method and Chio's Rule as references. We intend to present our step-by-step methodology using clear mathematical language, where we will demonstrate how to calculate the determinant of a matrix of the order n in an analytical format. We will also present a computational model with one sequential algorithm and one parallel algorithm using a pseudo-code.

Gas-phase reactivity of 2-hydroxy-1,4-naphthoquinones: a computational and mass spectrometry study of lapachol congeners

In order to understand the influence of alkyl side chains on the gas-phase reactivity of 1,4-naphthoquinone derivatives, some 2-hydroxy-1,4-naphthoquinone derivatives have been prepared and studied by electrospray ionization tandem mass spectrometry in combination with computational quantum chemistry calculations. Protonation and deprotonation sites were suggested on the basis of gas-phase basicity, proton affinity, gas-phase acidity (?Gacid), atomic charges and frontier orbital analyses. The nature of the intramolecular interaction as well as of the hydrogen bond in the systems was investigated by the atoms-in-molecules theory and the natural bond orbital analysis. The results were compared with data published for lapachol (2-hydroxy-3-(3-methyl-2-butenyl)-1,4-naphthoquinone). For the protonated molecules, water elimination was verified to occur at lower proportion when compared with side chain elimination, as evidenced in earlier studies on lapachol. The side chain at position C(3) was found to play important roles in the fragmentation mechanisms of these compounds. Copyright (c) 2012 John Wiley & Sons, Ltd.

Towards a precise test for malaria diagnosis in the Brazilian Amazon: comparison among field microscopy, a rapid diagnostic test, nested PCR, and a computational expert system based on artificial neural networks

Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.