A semi-automatic computerized method to measure baroreflex-mediated heart rate responses that reduces interobserver variability

Arterial baroreflex sensitivity estimated by pharmacological impulse stimuli depends on intrinsic signal variability and usually a subjective choice of blood pressure (BP) and heart rate (HR) values. We propose a semi-automatic method to estimate cardiovascular reflex sensitivity to bolus infusions of phenylephrine and nitroprusside. Beat-to-beat BP and HR time series for male Wistar rats (N = 13) were obtained from the digitized signal (sample frequency = 2 kHz) and analyzed by the proposed method (PRM) developed in Matlab language. In the PRM, time series were low-pass filtered with zero-phase distortion (3rd order Butterworth used in the forward and reverse direction) and presented graphically, and parameters were selected interactively. Differences between basal mean values and peak BP (deltaBP) and HR (deltaHR) values after drug infusions were used to calculate baroreflex sensitivity indexes, defined as the deltaHR/deltaBP ratio. The PRM was compared to the method traditionally (TDM) employed by seven independent observers using files for reflex bradycardia (N = 43) and tachycardia (N = 61). Agreement was assessed by Bland and Altman plots. Dispersion among users, measured as the standard deviation, was higher for TDM for reflex bradycardia (0.60 ± 0.46 vs 0.21 ± 0.26 bpm/mmHg for PRM, P < 0.001) and tachycardia (0.83 ± 0.62 vs 0.28 ± 0.28 bpm/mmHg for PRM, P < 0.001). The advantage of the present method is related to its objectivity, since the routine automatically calculates the desired parameters according to previous software instructions. This is an objective, robust and easy-to-use tool for cardiovascular reflex studies.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

The performance of semi-quantitative differential PCR is similar to that of real-time PCR for the detection of the MYCN gene in neuroblastomas

Amplification of the MYCN gene in neuroblastomas is a potent biological marker of highly aggressive tumors, which are invariably fatal unless sound clinical management is applied. To determine the usefulness of semi-quantitative differential PCR (SQ-PCR) for accurate quantification of MYCN gene copy number, we evaluated the analytical performance of this method by comparing the results obtained with it for 101 tumor samples of neuroblastoma to that obtained by absolute and relative real-time PCR. Similar results were obtained for 100 (99%) samples, no significant difference was detected between the median log10 MYCN copy number (1.53 by SQ-PCR versus 1.55 by absolute real-time PCR), and the results of the two assays correlated closely (r = 0.8, Pearson correlation; P < 0.001). In the comparison of SQ-PCR and relative real-time PCR, SQ-PCR versus relative real-time PCR concordant results were found in 100 (99%) samples, no significant difference was found in median log10 MYCN copy number (1.53 by SQ-PCR versus 1.27 by relative real-time PCR), and the results of the two assays correlated closely (r = 0.8, Pearson correlation; P < 0.001). These findings indicate that the performance of SQ-PCR was comparable to that of real-time PCR for the amplification and quantification of MYCN copy number. Thus, SQ-PCR can be reliably used as an alternative assay in laboratories without facilities for real-time PCR.

Brain tissue segmentation using q-entropy in multiple sclerosis magnetic resonance images

The loss of brain volume has been used as a marker of tissue destruction and can be used as an index of the progression of neurodegenerative diseases, such as multiple sclerosis. In the present study, we tested a new method for tissue segmentation based on pixel intensity threshold using generalized Tsallis entropy to determine a statistical segmentation parameter for each single class of brain tissue. We compared the performance of this method using a range of different q parameters and found a different optimal q parameter for white matter, gray matter, and cerebrospinal fluid. Our results support the conclusion that the differences in structural correlations and scale invariant similarities present in each tissue class can be accessed by generalized Tsallis entropy, obtaining the intensity limits for these tissue class separations. In order to test this method, we used it for analysis of brain magnetic resonance images of 43 patients and 10 healthy controls matched for gender and age. The values found for the entropic q index were 0.2 for cerebrospinal fluid, 0.1 for white matter and 1.5 for gray matter. With this algorithm, we could detect an annual loss of 0.98% for the patients, in agreement with literature data. Thus, we can conclude that the entropy of Tsallis adds advantages to the process of automatic target segmentation of tissue classes, which had not been demonstrated previously.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Semi-automatic measurement of visual verticality perception in humans reveals a new category of visual field dependency

Previous assessment of verticality by means of rod and rod and frame tests indicated that human subjects can be more (field dependent) or less (field independent) influenced by a frame placed around a tilted rod. In the present study we propose a new approach to these tests. The judgment of visual verticality (rod test) was evaluated in 50 young subjects (28 males, ranging in age from 20 to 27 years) by randomly projecting a luminous rod tilted between -18 and +18° (negative values indicating left tilts) onto a tangent screen. In the rod and frame test the rod was displayed within a luminous fixed frame tilted at +18 or -18°. Subjects were instructed to verbally indicate the rod’s inclination direction (forced choice). Visual dependency was estimated by means of a Visual Index calculated from rod and rod and frame test values. Based on this index, volunteers were classified as field dependent, intermediate and field independent. A fourth category was created within the field-independent subjects for whom the amount of correct guesses in the rod and frame test exceeded that of the rod test, thus indicating improved performance when a surrounding frame was present. In conclusion, the combined use of subjective visual vertical and the rod and frame test provides a specific and reliable form of evaluation of verticality in healthy subjects and might be of use to probe changes in brain function after central or peripheral lesions.

MODELAGEM E SIMULAÇÃO DA DESTERPENAÇÃO DO ÓLEO DA CASCA DE LARANJA COM CO2 SUPERCRÍTICO EM MODO SEMI-CONTÍNUO

A desterpenação do óleo da casca de laranja com CO2 supercrítico foi investigada através da modelagem e simulação da separação de uma mistura sintética de limoneno (90 % em peso) e linalol (10 %), em um extrator operando em modo semi-contínuo. A modelagem matemática da extração supercrítica foi realizada por analogia com a destilação de uma mistura binária, em batelada, expressando-se a composição das fases em equilíbrio numa base molar livre de CO2. O cálculo das variáveis do processo foi feito por integração numérica da equação de Rayleigh empregando-se o método de Runge-Kutta de quarta ordem. Para a determinação da relação de equilíbrio entre as fases, adotou-se a equação de Peng-Robinson modificada, com os parâmetros de interação obtidos de dados de ELV dos sistemas binários CO2+limoneno e CO2+linalol e do ternário CO2+limoneno+linalol.

Efeito do cloreto de sódio na produção de proteínas (Saccharomyces cerevisiae) em fermentação semi-sólida

Estudou-se o efeito do cloreto de sódio sobre a produção de biomassa e proteínas extracelulares totais, durante o cultivo de Saccharomyces cerevisiae. A levedura foi desenvonvida em fermentador de leito fluidizado, com vazão de ar de 70L/min, temperatura de 33° C, e umidade relativa de 99-100%. Foi utilizado substrato semi-sólido de batatas, previamente hidrolizado, acrescido de cloreto de sódio 0,6M. O crescimento celular foi monitorado por densidade óptica à 595 nm. Observou-se, como resultado, que a adição de cloreto de sódio 0,6M induziu um aumento de 36,86% na produção de proteínas extracelulares totais, mas inibiu o crescimento celular em 27,62% quando os meios com e sem cloreto de sódio foram testados. A produção máxima de biomassa, tanto para os experimentos com adição de cloreto de sódio quanto para o sem adição, ocorreu no período de 7 a 9 horas de fermentacão, enquanto que a produção de proteínas extracelulares totais, independentemente da adição do sal, ocorreu durante o período de 9 a 12 horas de fermentação. As velocidades específicas máximas de crescimento foram de 0,350/h para os experimentos com sal, e de 0,339/h para aqueles sem a adição do sal. A combinação de alta vazão de ar e a presença de cloreto de sódio 0,6M na fermentação parece não ter tido efeito sobre a duração da fase lag na curva de crescimento celular de Saccharomyces cerevisiae.

Development and characterization of edible films based on gluten from semi-hard and soft Brazilian wheat flours (development of films based on gluten from wheat flours)

Edible films based on gluten from four types of Brazilian wheat gluten (2 "semi-hard" and 2 "soft") were prepared and mechanical and barrier properties were compared with those of wheat gluten films with vital gluten. Water vapor, oxygen permeability, tensile strength and percent elongation at break, solubility in water and surface morphology were measured. The films from "semi-hard" wheat flours showed similar water vapor permeability and solubility in water to films from vital gluten and better tensile strength than the films from "soft" and vital gluten. The films from vital gluten had higher elongation at break and oxygen permeability and also lower solubility in water than the films from the Brazilian wheat "soft" flours. In spite of the vital gluten showed greater mechanical resistance, desirable for the bakery products, for the purpose of developing gluten films Brazilian "semi-hard" wheat flours can be used instead of vital gluten, since they showed similar barrier and mechanical properties.

Efeito do teor de amido danificado na produção de biscoitos tipo semi-duros

O trabalho objetivou estudar a danificação do amido de farinha de trigo por moagem e o seu efeito na produção de biscoitos tipo semi-duros. Amostras de trigo dos cultivares BR 23, BRS Angico e Rubi, com características diferentes quanto à dureza foram moídas em moinho de rolos através de uma passagem pelo conjunto de quebra; quebra mais três reduções na umidade 16% e quebra mais três reduções na umidade 12%. Neste tratamento, a moagem foi complementada pelo emprego de moinho de bolas. Nas farinhas, foram realizadas análises físicas, químicas, reológicas e funcionais, utilizando delineamento casualizado em planejamento fatorial completo 3 x 3, totalizando nove tratamentos. Os resultados foram analisados estatisticamente e, nos modelos significativos, as médias comparadas entre si pelo teste de Tukey a 5% de probabilidade de erro. Os resultados rendimento de quebra, proteína bruta, amido danificado, força geral do glúten (W x 10-4J) e relação tenacidade/extensibilidade (P/L) indicam que a farinha do cultivar BRS Angico apresentou melhores características para a produção de biscoitos seguido de BR 23 e Rubi. O teor de amido danificado produzido durante a moagem dos trigos influencia nas propriedades funcionais dos biscoitos apresentando melhor resultado aqueles obtidos a partir de uma passagem pelo conjunto de quebra.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.