Estudo dos parâmetros dosimétricos de sementes de Iodo-125 desenvolvidas pelo IPEN-CNEN/SP utilizadas em braquiterapia por simulação computacional pelo método de Monte Carlo

As expectativas da Organização Mundial de Saúde para o ano de 2030 são que o número de mortes por câncer seja de aproximadamente 13,2 milhões, evidenciando a elevada parcela desta doença no problema de saúde mundial. Com relação ao câncer de próstata, de acordo com o Instituto Nacional do Câncer, o número de casos diagnosticados no mundo em 2012 foi de aproximadamente 1,1 milhão, enquanto que no Brasil os dados indicam a incidência de 68 mil novos casos. O tratamento deste tipo de neoplasia pode ser realizado com cirurgia (prostatectomia) ou radioterapia. Dentre a radioterapia, podemos destacar a técnica de braquiterapia, a qual consiste na introdução (implante) de pequenas fontes radioativas (sementes) no interior da próstata, onde será entregue um valor elevado de dose no volume de tratamento e baixa dose nos tecidos ao redor. No Brasil, a classe médica estima uma demanda de aproximadamente 8000 sementes/mês, sendo o custo unitário de cada semente de pelo menos U$ 26,00. A Associação Americana de Físicos na Medicina publicou alguns documentos descrevendo quais parâmetros e análises devem ser realizadas para avaliações da distribuição de dose, como por exemplo, os parâmetros Constante de taxa de dose, Função radial e Função de anisotropia. Estes parâmetros podem ser obtidos através de medidas experimentais da distribuição de dose ou por simulações computacionais. Neste trabalho foram determinados os parâmetros dosimétricos da semente OncoSeed-6711 da empresa Oncura-GEHealthcare e da semente desenvolvida pelo Grupo de Dosimetria de Fontes de Braquiterapia do Centro de Tecnologia das Radiações (CTR IPEN-CNEN/SP) por simulação computacional da distribuição de dose utilizando o código MCNP5, baseado no Método de Monte Carlo. A semente 6711 foi modelada, assim como um sistema dosimétrico constituído por um objeto simulador cúbico de 30x30x30 cm3 preenchido com água. Os valores obtidos da semente 6711 foram comparados com alguns apresentados na literatura, onde o parâmetro Constante de taxa de dose apresentou erro relativo em relação ao valor publicado no TG- 43 de 0,1%, sendo que os outros parâmetros analisados também apresentaram boa concordância com os valores publicados na literatura. Deste modo, pode-se considerar que os parâmetros utilizados nas simulações (espectro, modelagem geométrica e avaliação de resultados) estão compatíveis com outros estudos, sendo estes parâmetros também utilizados nas simulações da semente do IPEN. Considerando as análises de incerteza estatística, os valores obtidos da semente do IPEN são semelhantes aos valores da semente 6711.

Percepção do clima de segurança do paciente em instituições hospitalares

Quase um em cada dez pacientes é lesionado ao receber cuidados de saúde e, destes, muitos sofrem lesões incapacitantes ou morte todos os anos. Entendendo a importância e o impacto negativo das falhas na segurança do paciente em âmbito global e a influência que a cultura e o clima de segurança exercem sobre a adoção de ações e decisões mais seguras, este estudo teve por objetivo a analise da cultura de segurança do paciente em instituições hospitalares, por meio da mensuração do clima de segurança. Trata-se de pesquisa quantitativa, transversal, do tipo Survey, em que para a realização da coleta de dados foi aplicado o Questionário de Atitudes de Segurança, adaptação transcultural para o Brasil do Safety Attitudes Questionnaire (SAQ) - Short Form 2006. O estudo ocorreu em dois hospitais gerais do estado de São Paulo, localizados em diferentes regiões metropolitanas, sendo um público e o outro privado. Os profissionais Médicos, Enfermeiros, Técnicos e Auxiliares de Enfermagem, Fisioterapeutas, Farmacêuticos e Nutricionistas, que atuavam nestes hospitais há pelo menos 6 meses, com carga horária de trabalho semanal de no mínimo 20 horas, constituíram a população deste estudo. Foi realizado um estudo piloto com 25 profissionais em cada hospital e a prevalência resultante deste teste foi utilizada no cálculo do tamanho amostral com nível de significância de 5%, erro relativo de 10% e perda de 20%, resultando em um total de 235 participantes. Os profissionais escolhidos como parte da amostra foram sorteados empregando-se amostragem aleatória simples computadorizada. As variáveis de cada domínio da escala quando testadas pelo Teste Kolmogorov-Smirnov não apresentaram normalidade. Deste modo, foi aplicado o Teste Mann-Whitney para comparar os valores das pontuações entre os hospitais e entre as categorias profissionais. Com relação aos resultados houve índice de participação de 86,8% da amostra sorteada, prevalecendo os sujeitos com 5 a 20 anos de tempo na especialidade, do gênero feminino, e trabalhadores da enfermagem. Não houve diferenças significantes dentre as pontuações obtidas pelos dois hospitais. Os participantes do estudo apresentaram percepção negativa quanto ao clima de segurança do paciente, com domínios Reconhecimento do Estresse e Percepção da Gestão apresentando resultados negativos, tanto para a amostra como um todo quanto por hospital. Os domínios Clima de Trabalho em Equipe, Satisfação no Trabalho e Comportamento Seguro/Práticas Seguras resultaram em percepções positivas para todas as categorias profissionais. Já o domínio Percepção da Gestão do Hospital resultou em percepção negativa para todas estas. Os Médicos e os Técnicos e Auxiliares de Enfermagem apresentaram percepções negativas em mais domínios. Em contrapartida, os Enfermeiros foram os únicos a apresentar atitude de segurança do paciente positiva, com escore total do SAQ exibindo diferença significante quando comparado a todas as outras categorias, apresentando também percepção positiva em maior número de domínios. Concluiu-se que existe a necessidade de abordagem relacionada ao Reconhecimento do Estresse dos profissionais, além dos aspectos do Gerenciamento. As categorias profissionais diferiram entre si com relação às percepções sobre a atitude de segurança do paciente. Desta forma, o desenvolvimento da cultura de segurança deve englobar todas as categorias profissionais, uma vez que esta abrange toda a organização, destacando-se a necessidade de enfoque de ações com relação a categoria dos Médicos e dos Técnicos e Auxiliares de Enfermagem. Além disso, ficou evidente o papel de destaque e liderança dos profissionais Enfermeiros nos processos de melhoria da qualidade, e colocando-os em posição privilegiada para conduzir os esforços de melhoria contínua da qualidade nos serviços de saúde

3D models created from ROV videos and their corresponding subtransect dimensions

Underwater video transects have become a common tool for quantitative analysis of the seafloor. However a major difficulty remains in the accurate determination of the area surveyed as underwater navigation can be unreliable and image scaling does not always compensate for distortions due to perspective and topography. Depending on the camera set-up and available instruments, different methods of surface measurement are applied, which make it difficult to compare data obtained by different vehicles. 3-D modelling of the seafloor based on 2-D video data and a reference scale can be used to compute subtransect dimensions. Focussing on the length of the subtransect, the data obtained from 3-D models created with the software PhotoModeler Scanner are compared with those determined from underwater acoustic positioning (ultra short baseline, USBL) and bottom tracking (Doppler velocity log, DVL). 3-D model building and scaling was successfully conducted on all three tested set-ups and the distortion of the reference scales due to substrate roughness was identified as the main source of imprecision. Acoustic positioning was generally inaccurate and bottom tracking unreliable on rough terrain. Subtransect lengths assessed with PhotoModeler were on average 20% longer than those derived from acoustic positioning due to the higher spatial resolution and the inclusion of slope. On a high relief wall bottom tracking and 3-D modelling yielded similar results. At present, 3-D modelling is the most powerful, albeit the most time-consuming, method for accurate determination of video subtransect dimensions.

Radionuclides measured on water bottle samples

Actinium is one of the rarest naturally occurring elements on earth. We measured its longest-lived isotope 227Ac (half-life 21.77 yr) for the first time in the water column of the Southeast Pacific, the Central Arctic, the Antarctic Circumpolar Current (ACC) and the Weddell Gyre (WG). Besides the profile in the Southeast Pacific, which confirms earlier findings about the role of diapycnal mixing for 227Ac distribution, we found three other different types of vertical profiles. These profiles point to a prominent role of advection for 227Ac distribution, especially in the Southern Ocean. Depending on the type of profile found, 227Ac is proposed as a tracer for different oceanographic questions. In the Southern Ocean, up to 4.93±0.32 dpm/m**3 227Ac is found close to the sea floor, which is the highest concentration ever observed in the ocean. Close to the sea surface in the WG, 0.46±0.05 dpm/m**3 227Acex (227Ac in excess of its progenitor 231Pa) is detected. We use 227Acex there to determine the upwelling velocity in the Eastern WG to be about 55 m/yr. In the ACC, Upper and Lower Circumpolar Deep Water (UCDW and LCDW) are found to differ clearly in their 227Acex activity. High 227Acex activities are therefore a promising tracer for recent inputs of LCDW to the sea surface, which may help to understand the role of deep upwelling for iron inputs into Antarctic surface waters. The expected release of 227Ac is compared with 228Ra to make sure that the large near-surface excess in the water column of the Southern Ocean is not due to lateral inputs by isopycnal mixing. Data from the Central Arctic and from a transect across the ACC confirm that 228Ra and 227Acex differ strongly in their sources. The first measurements of 227Ac on suspended matter (less than 1.7% of total 227Ac close to the sea floor) indicate that the particle reactivity of 227Ac is negligible in the open ocean, in agreement with earlier findings [Y. Nozaki, Nature 310 (1984) 486-488]. Despite the extremely low concentrations of 227Ac, new measurement techniques [W.S. Moore, R. Arnold, J. Geophys. Res. 101 (1996) 1321-1329] point to a comfortable and comparably simple determination of 227Ac in the future. Finally, 227Acex may become a widely used deep-sea specific tracer.

Green-Ampt approximations

The solution to the Green and Ampt infiltration equation is expressible in terms of the Lambert W-1 function. Approximations for Green and Ampt infiltration are thus derivable from approximations for the W-1 function and vice versa. An infinite family of asymptotic expansions to W-1 is presented. Although these expansions do not converge near the branch point of the W function (corresponds to Green-Ampt infiltration with immediate ponding), a method is presented for approximating W-1 that is exact at the branch point and asymptotically, with interpolation between these limits. Some existing and several new simple and compact yet robust approximations applicable to Green-Ampt infiltration and flux are presented, the most accurate of which has a maximum relative error of 5 x 10(-5)%. This error is orders of magnitude lower than any existing analytical approximations. (c) 2005 Elsevier Ltd. All rights reserved.

Continuous phase synchronised drives (for a rod-making machine)

Traditional high speed machinery actuators are powered and coordinated by mechanical linkages driven from a central drive, but these linkages may be replaced by independently synchronised electric drives. Problems associated with utilising such electric drives for this form of machinery were investigated. The research concentrated on a high speed rod-making machine, which required control of high inertias (0.01-0.5kgm2), at continuous high speed (2500 r/min), with low relative phase errors between two drives (0.0025 radians). Traditional minimum energy drive selection techniques for incremental motions were not applicable to continuous applications which require negligible energy dissipation. New selection techniques were developed. A brushless configuration constant enabled the comparison between seven different servo systems; the rate earth brushless drives had the best power rates which is a performance measure. Simulation was used to review control strategies, such that a microprocessor controller with a proportional velocity loop within a proportional position loop with velocity feedforward was designed. Local control schemes were investigated as means of reducing relative errors between drives: the slave of a master/slave scheme compensates for the master's errors: the matched scheme has drives with similar absolute errors so the relative error is minimised, and the feedforward scheme minimises error by adding compensation from previous knowledge. Simulation gave an approximate velocity loop bandwidth and position loop gain required to meet the specification. Theoretical limits for these parameters were defined in terms of digital sampling delays, quantisation, and system phase shifts. Performance degradation due to mechanical backlash was evaluated. Thus any drive could be checked to ensure that the performance specification could be realised. A two drive demonstrator was commissioned with 0.01kgm2 loads. By use of simulation the performance of one drive was improved by increasing the velocity loop bandwidth fourfold. With the master/slave scheme relative errors were within 0.0024 radians at a constant 2500 r/min for two 0.01 kgm^2 loads.

Mathematical modelling and control of agitated extraction columns

Liquid-liquid extraction has long been known as a unit operation that plays an important role in industry. This process is well known for its complexity and sensitivity to operation conditions. This thesis presents an attempt to explore the dynamics and control of this process using a systematic approach and state of the art control system design techniques. The process was studied first experimentally under carefully selected. operation conditions, which resembles the ranges employed practically under stable and efficient conditions. Data were collected at steady state conditions using adequate sampling techniques for the dispersed and continuous phases as well as during the transients of the column with the aid of a computer-based online data logging system and online concentration analysis. A stagewise single stage backflow model was improved to mimic the dynamic operation of the column. The developed model accounts for the variation in hydrodynamics, mass transfer, and physical properties throughout the length of the column. End effects were treated by addition of stages at the column entrances. Two parameters were incorporated in the model namely; mass transfer weight factor to correct for the assumption of no mass transfer in the. settling zones at each stage and the backmixing coefficients to handle the axial dispersion phenomena encountered in the course of column operation. The parameters were estimated by minimizing the differences between the experimental and the model predicted concentration profiles at steady state conditions using non-linear optimisation technique. The estimated values were then correlated as functions of operating parameters and were incorporated in·the model equations. The model equations comprise a stiff differential~algebraic system. This system was solved using the GEAR ODE solver. The calculated concentration profiles were compared to those experimentally measured. A very good agreement of the two profiles was achieved within a percent relative error of ±2.S%. The developed rigorous dynamic model of the extraction column was used to derive linear time-invariant reduced-order models that relate the input variables (agitator speed, solvent feed flowrate and concentration, feed concentration and flowrate) to the output variables (raffinate concentration and extract concentration) using the asymptotic method of system identification. The reduced-order models were shown to be accurate in capturing the dynamic behaviour of the process with a maximum modelling prediction error of I %. The simplicity and accuracy of the derived reduced-order models allow for control system design and analysis of such complicated processes. The extraction column is a typical multivariable process with agitator speed and solvent feed flowrate considered as manipulative variables; raffinate concentration and extract concentration as controlled variables and the feeds concentration and feed flowrate as disturbance variables. The control system design of the extraction process was tackled as multi-loop decentralised SISO (Single Input Single Output) as well as centralised MIMO (Multi-Input Multi-Output) system using both conventional and model-based control techniques such as IMC (Internal Model Control) and MPC (Model Predictive Control). Control performance of each control scheme was. studied in terms of stability, speed of response, sensitivity to modelling errors (robustness), setpoint tracking capabilities and load rejection. For decentralised control, multiple loops were assigned to pair.each manipulated variable with each controlled variable according to the interaction analysis and other pairing criteria such as relative gain array (RGA), singular value analysis (SVD). Loops namely Rotor speed-Raffinate concentration and Solvent flowrate Extract concentration showed weak interaction. Multivariable MPC has shown more effective performance compared to other conventional techniques since it accounts for loops interaction, time delays, and input-output variables constraints.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Discriminative training of the hidden vector state model for semantic parsing

In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

A novel framework of training hidden Markov support vector machines from lightly-annotated data

Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

The accuracy of parameter estimation from noisy data, with application to resonance peak estimation in distributed Brillouin sensing

Distributed Brillouin sensing of strain and temperature works by making spatially resolved measurements of the position of the measurand-dependent extremum of the resonance curve associated with the scattering process in the weakly nonlinear regime. Typically, measurements of backscattered Stokes intensity (the dependent variable) are made at a number of predetermined fixed frequencies covering the design measurand range of the apparatus and combined to yield an estimate of the position of the extremum. The measurand can then be found because its relationship to the position of the extremum is assumed known. We present analytical expressions relating the relative error in the extremum position to experimental errors in the dependent variable. This is done for two cases: (i) a simple non-parametric estimate of the mean based on moments and (ii) the case in which a least squares technique is used to fit a Lorentzian to the data. The question of statistical bias in the estimates is discussed and in the second case we go further and present for the first time a general method by which the probability density function (PDF) of errors in the fitted parameters can be obtained in closed form in terms of the PDFs of the errors in the noisy data.

Semi-supervised learning of statistical models for natural language understanding

Natural language understanding is to specify a computational model that maps sentences to their semantic mean representation. In this paper, we propose a novel framework to train the statistical models without using expensive fully annotated data. In particular, the input of our framework is a set of sentences labeled with abstract semantic annotations. These annotations encode the underlying embedded semantic structural relations without explicit word/semantic tag alignment. The proposed framework can automatically induce derivation rules that map sentences to their semantic meaning representations. The learning framework is applied on two statistical models, the conditional random fields (CRFs) and the hidden Markov support vector machines (HM-SVMs). Our experimental results on the DARPA communicator data show that both CRFs and HM-SVMs outperform the baseline approach, previously proposed hidden vector state (HVS) model which is also trained on abstract semantic annotations. In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.

Optimization of Rational Approximations by Continued Fractions

The paper has been presented at the 12th International Conference on Applications of Computer Algebra, Varna, Bulgaria, June, 2006.

Laser-induced breakdown spectroscopy quantitative analysis method via adaptive analytical line selection and relevance vector machine regression model

Abstract A new LIBS quantitative analysis method based on analytical line adaptive selection and Relevance Vector Machine (RVM) regression model is proposed. First, a scheme of adaptively selecting analytical line is put forward in order to overcome the drawback of high dependency on a priori knowledge. The candidate analytical lines are automatically selected based on the built-in characteristics of spectral lines, such as spectral intensity, wavelength and width at half height. The analytical lines which will be used as input variables of regression model are determined adaptively according to the samples for both training and testing. Second, an LIBS quantitative analysis method based on RVM is presented. The intensities of analytical lines and the elemental concentrations of certified standard samples are used to train the RVM regression model. The predicted elemental concentration analysis results will be given with a form of confidence interval of probabilistic distribution, which is helpful for evaluating the uncertainness contained in the measured spectra. Chromium concentration analysis experiments of 23 certified standard high-alloy steel samples have been carried out. The multiple correlation coefficient of the prediction was up to 98.85%, and the average relative error of the prediction was 4.01%. The experiment results showed that the proposed LIBS quantitative analysis method achieved better prediction accuracy and better modeling robustness compared with the methods based on partial least squares regression, artificial neural network and standard support vector machine.

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^