Algorithm for the treatment of type 2 diabetes: a position statement of Brazilian Diabetes Society

The Brazilian Diabetes Society is starting an innovative project of quantitative assessment of medical arguments of and implementing a new way of elaborating SBD Position Statements. The final aim of this particular project is to propose a new Brazilian algorithm for the treatment of type 2 diabetes, based on the opinions of endocrinologists surveyed from a poll conducted on the Brazilian Diabetes Society website regarding the latest algorithm proposed by American Diabetes Association /European Association for the Study of Diabetes, published in January 2009.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

Parallel Layout Construction Algorithm for Irregular Shape Packing Problems

Cutting and packing problems arise in a variety of industries, including garment, wood and shipbuilding. Irregular shape packing is a special case which admits irregular items and is much more complex due to the geometry of items. In order to ensure that items do not overlap and no item from the layout protrudes from the container, the collision free region concept was adopted. It represents all possible translations for a new item to be inserted into a container with already placed items. To construct a feasible layout, collision free region for each item is determined through a sequence of Boolean operations over polygons. In order to improve the speed of the algorithm, a parallel version of the layout construction was proposed and it was applied to a simulated annealing algorithm used to solve bin packing problems. Tests were performed in order to determine the speed improvement of the parallel version over the serial algorithm

Multi-objective evolutionary algorithm for single and multiple fault service restoration in large-scale distribution systems

Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.

Programmable logic design of a compact Genetic Algorithm for phasor estimation in real-time

The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

Test and Evaluation of the FastSLAM Algorithm in a Mobile Robot

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Computational analyses on the structure-function relation in ion channels

Ion channels are protein molecules, embedded in the lipid bilayer of the cell membranes. They act as powerful sensing elements switching chemicalphysical stimuli into ion-fluxes. At a glance, ion channels are water-filled pores, which can open and close in response to different stimuli (gating), and one once open select the permeating ion species (selectivity). They play a crucial role in several physiological functions, like nerve transmission, muscular contraction, and secretion. Besides, ion channels can be used in technological applications for different purpose (sensing of organic molecules, DNA sequencing). As a result, there is remarkable interest in understanding the molecular determinants of the channel functioning. Nowadays, both the functional and the structural characteristics of ion channels can be experimentally solved. The purpose of this thesis was to investigate the structure-function relation in ion channels, by computational techniques. Most of the analyses focused on the mechanisms of ion conduction, and the numerical methodologies to compute the channel conductance. The standard techniques for atomistic simulation of complex molecular systems (Molecular Dynamics) cannot be routinely used to calculate ion fluxes in membrane channels, because of the high computational resources needed. The main step forward of the PhD research activity was the development of a computational algorithm for the calculation of ion fluxes in protein channels. The algorithm - based on the electrodiffusion theory - is computational inexpensive, and was used for an extensive analysis on the molecular determinants of the channel conductance. The first record of ion-fluxes through a single protein channel dates back to 1976, and since then measuring the single channel conductance has become a standard experimental procedure. Chapter 1 introduces ion channels, and the experimental techniques used to measure the channel currents. The abundance of functional data (channel currents) does not match with an equal abundance of structural data. The bacterial potassium channel KcsA was the first selective ion channels to be experimentally solved (1998), and after KcsA the structures of four different potassium channels were revealed. These experimental data inspired a new era in ion channel modeling. Once the atomic structures of channels are known, it is possible to define mathematical models based on physical descriptions of the molecular systems. These physically based models can provide an atomic description of ion channel functioning, and predict the effect of structural changes. Chapter 2 introduces the computation methods used throughout the thesis to model ion channels functioning at the atomic level. In Chapter 3 and Chapter 4 the ion conduction through potassium channels is analyzed, by an approach based on the Poisson-Nernst-Planck electrodiffusion theory. In the electrodiffusion theory ion conduction is modeled by the drift-diffusion equations, thus describing the ion distributions by continuum functions. The numerical solver of the Poisson- Nernst-Planck equations was tested in the KcsA potassium channel (Chapter 3), and then used to analyze how the atomic structure of the intracellular vestibule of potassium channels affects the conductance (Chapter 4). As a major result, a correlation between the channel conductance and the potassium concentration in the intracellular vestibule emerged. The atomic structure of the channel modulates the potassium concentration in the vestibule, thus its conductance. This mechanism explains the phenotype of the BK potassium channels, a sub-family of potassium channels with high single channel conductance. The functional role of the intracellular vestibule is also the subject of Chapter 5, where the affinity of the potassium channels hEag1 (involved in tumour-cell proliferation) and hErg (important in the cardiac cycle) for several pharmaceutical drugs was compared. Both experimental measurements and molecular modeling were used in order to identify differences in the blocking mechanism of the two channels, which could be exploited in the synthesis of selective blockers. The experimental data pointed out the different role of residue mutations in the blockage of hEag1 and hErg, and the molecular modeling provided a possible explanation based on different binding sites in the intracellular vestibule. Modeling ion channels at the molecular levels relates the functioning of a channel to its atomic structure (Chapters 3-5), and can also be useful to predict the structure of ion channels (Chapter 6-7). In Chapter 6 the structure of the KcsA potassium channel depleted from potassium ions is analyzed by molecular dynamics simulations. Recently, a surprisingly high osmotic permeability of the KcsA channel was experimentally measured. All the available crystallographic structure of KcsA refers to a channel occupied by potassium ions. To conduct water molecules potassium ions must be expelled from KcsA. The structure of the potassium-depleted KcsA channel and the mechanism of water permeation are still unknown, and have been investigated by numerical simulations. Molecular dynamics of KcsA identified a possible atomic structure of the potassium-depleted KcsA channel, and a mechanism for water permeation. The depletion from potassium ions is an extreme situation for potassium channels, unlikely in physiological conditions. However, the simulation of such an extreme condition could help to identify the structural conformations, so the functional states, accessible to potassium ion channels. The last chapter of the thesis deals with the atomic structure of the !- Hemolysin channel. !-Hemolysin is the major determinant of the Staphylococcus Aureus toxicity, and is also the prototype channel for a possible usage in technological applications. The atomic structure of !- Hemolysin was revealed by X-Ray crystallography, but several experimental evidences suggest the presence of an alternative atomic structure. This alternative structure was predicted, combining experimental measurements of single channel currents and numerical simulations. This thesis is organized in two parts, in the first part an overview on ion channels and on the numerical methods adopted throughout the thesis is provided, while the second part describes the research projects tackled in the course of the PhD programme. The aim of the research activity was to relate the functional characteristics of ion channels to their atomic structure. In presenting the different research projects, the role of numerical simulations to analyze the structure-function relation in ion channels is highlighted.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Performance evaluation of a parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes

[EN]A new parallel algorithm for simultaneous untangling and smoothing of tetrahedral meshes is proposed in this paper. We provide a detailed analysis of its performance on shared-memory many-core computer architectures. This performance analysis includes the evaluation of execution time, parallel scalability, load balancing, and parallelism bottlenecks. Additionally, we compare the impact of three previously published graph coloring procedures on the performance of our parallel algorithm. We use six benchmark meshes with a wide range of sizes. Using these experimental data sets, we describe the behavior of the parallel algorithm for different data sizes. We demonstrate that this algorithm is highly scalable when it runs on two different high-performance many-core computers with up to 128 processors...

T-spline parameterization of 2D geometries based on the meccano method with a new T-mesh optimization algorithm

[EN]We present a new method, based on the idea of the meccano method and a novel T-mesh optimization procedure, to construct a T-spline parameterization of 2D geometries for the application of isogeometric analysis. The proposed method only demands a boundary representation of the geometry as input data. The algorithm obtains, as a result, high quality parametric transformation between 2D objects and the parametric domain, the unit square. First, we define a parametric mapping between the input boundary of the object and the boundary of the parametric domain. Then, we build a T-mesh adapted to the geometric singularities of the domain in order to preserve the features of the object boundary with a desired tolerance…

Processi di deposizione di blocking layers di TiO2 per Dye - Sensitized Solar Cells (DSSC)

Le Dye – Sensitized Solar Cells (DSSC) sono attualmente considerate tra le alternative più promettenti al fotovoltaico tradizionale. I ridotti costi di produzione e l’elevata versatilità di utilizzo rappresentano i punti di forza di questi dispositivi innovativi. Ad oggi la ricerca è concentrata prevalentemente sull’incremento delle prestazioni delle DSSC, ottenibile solamente attraverso un miglioramento delle funzioni dei singoli componenti e dell’interazione sinergica tra questi. Tra i componenti, ha recentemente assunto particolare interesse il blocking layer (BL), costituito generalmente da un film sottile di TiO2 depositato sulla superficie dell’anodo (FTO) e in grado di ottimizzare i fenomeni all’interfaccia FTO/TiO2/elettrolita. Nel corso di questo lavoro di tesi si è rivolta l’attenzione prevalentemente sulle caratteristiche del BLs (ad esempio proprietà morfologico – strutturali) cercando di mettere in correlazione il processo di deposizione con le caratteristiche finali del film ottenuto. A questo scopo è stato ottimizzato un processo di deposizione dei film via spin coating, a partire da soluzioni acquosa o alcolica di precursore (TiCl4). I film ottenuti sono stati confrontati con quelli depositati tramite un processo di dip coating riportato in letteratura. I BLs sono stati quindi caratterizzati tramite microscopia (SEM – AFM), spettrofotometria (UV.- Vis) e misure elettrochimiche (CV – EIS). I risultati ottenuti hanno messo in evidenza come i rivestimenti ottenuti da soluzione acquosa di precursore, indipendentemente dalla tecnica di deposizione utilizzata (spin coating o dip coating) diano origine a film disomogenei e scarsamente riproducibili, pertanto non idonei per l’applicazione nelle DSSC. Viceversa, i BLs ottenuti via spin coating dalla soluzione alcolica di TiCl4 sono risultati riproducibili, omogenei, e uniformemente distribuiti sulla superficie di FTO. Infine, l’analisi EIS ha in particolare evidenziato un effettivo aumento della resistenza al trasferimento di carica tra elettrodo FTO ed elettrolita in presenza di questi BLs, fenomeno generalmente associato ad un efficace blocking effect.

Preliminary studies for the establishment of a tsunami early detection algorithm to be used in the frame of a Tsunami Warning System

This thesis presents and discusses TEDA, an algorithm for the automatic detection in real-time of tsunamis and large amplitude waves on sea level records. TEDA has been developed in the frame of the Tsunami Research Team of the University of Bologna for coastal tide gauges and it has been calibrated and tested for the tide gauge station of Adak Island, in Alaska. A preliminary study to apply TEDA to offshore buoys in the Pacific Ocean is also presented.

An alternative blocking layer for titanium dioxide (TiO 2) solar cell applications

In hybrid organic solar cells a blocking layer between transparent electrode and nanocrystalline titania particles is essential to prevent short-circuiting and current loss through recombination at the electrode interface. Here the preparation of a uniform hybrid blocking layer which is composed of conducting titania nanoparticles embedded in an insulating polymer derived ceramic is presented. This blocking layer is prepared by sol-gel chemistry where an amphiphilic block copolymer is used as a templating agent. A novel poly(dimethylsiloxane) containing amphiphilic block copolymer poly(ethyleneglycol)methylethermethacrylate-block-poly(dimethylsiloxane)-block-poly(ethyleneglycol)methylethermethacrylate has been synthesized to act as the templating agent. Plasma treatment uncovered titania surface from any polymer. Annealing at 450°C under nitrogen resulted in anatase titania with polymer derived silicon oxycarbide ceramic. Electrical characterization by conductive scanning probe microscopy experiments revealed a percolating titania network separated by an insulating ceramic matrix. Scanning Kelvin probe force microscopy showed predominant presence of titania particles on the surface creating a large surface area for dye absorption. The uniformity of the percolating structures was proven by microbeam grazing incidence small angle x-ray scattering. First applications in hybrid organic solar cells in comparison with conventional titanium dioxide blocking layer containing devices revealed 15 fold increases in corresponding efficiencies. Poly(dimethylsiloxane)-block-poly(ethyleneglycol)methylethermethacrylate and poly(ethyleneoxide)-poly(dimethylsiloxane)methylmethacrylate diblock copolymers were also synthesized. Their titania nanocomposite films were compared with the integrated blocking layer. Liner poly(ethyleneoxide) containing diblock copolymer resulted in highly ordered foam like structures. The effect of heating temperature rise to 600°C and 1000°C on titania morphology was investigated by scanning electron and force microscopy and x-ray scattering. Sol-gel contents, hydrochloric acid, titania precursor and amphiphilic triblock copolymer were altered to see their effect on titania morphology. Increase in block copolymer content resulted in titania particles of diameter 15-20 nm.