Effect of changing data collection parameters on statistical motor unit number estimates

The effect of number of samples and selection of data for analysis on the calculation of surface motor unit potential (SMUP) size in the statistical method of motor unit number estimates (MUNE) was determined in 10 normal subjects and 10 with amyotrophic lateral sclerosis (ALS). We recorded 500 sequential compound muscle action potentials (CMAPs) at three different stable stimulus intensities (10–50% of maximal CMAP). Estimated mean SMUP sizes were calculated using Poisson statistical assumptions from the variance of 500 sequential CMAP obtained at each stimulus intensity. The results with the 500 data points were compared with smaller subsets from the same data set. The results using a range of 50–80% of the 500 data points were compared with the full 500. The effect of restricting analysis to data between 5–20% of the CMAP and to standard deviation limits was also assessed. No differences in mean SMUP size were found with stimulus intensity or use of different ranges of data. Consistency was improved with a greater sample number. Data within 5% of CMAP size gave both increased consistency and reduced mean SMUP size in many subjects, but excluded valid responses present at that stimulus intensity. These changes were more prominent in ALS patients in whom the presence of isolated SMUP responses was a striking difference from normal subjects. Noise, spurious data, and large SMUP limited the Poisson assumptions. When these factors are considered, consistent statistical MUNE can be calculated from a continuous sequence of data points. A 2 to 2.5 SD or 10% window are reasonable methods of limiting data for analysis. Muscle Nerve 27: 320–331, 2003

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Statistical motion learning for improved transform domain Wyner-Ziv video coding

Wyner - Ziv (WZ) video coding is a particular case of distributed video coding (DVC), the recent video coding paradigm based on the Slepian - Wolf and Wyner - Ziv theorems which exploits the source temporal correlation at the decoder and not at the encoder as in predictive video coding. Although some progress has been made in the last years, WZ video coding is still far from the compression performance of predictive video coding, especially for high and complex motion contents. The WZ video codec adopted in this study is based on a transform domain WZ video coding architecture with feedback channel-driven rate control, whose modules have been improved with some recent coding tools. This study proposes a novel motion learning approach to successively improve the rate-distortion (RD) performance of the WZ video codec as the decoding proceeds, making use of the already decoded transform bands to improve the decoding process for the remaining transform bands. The results obtained reveal gains up to 2.3 dB in the RD curves against the performance for the same codec without the proposed motion learning approach for high motion sequences and long group of pictures (GOP) sizes.

Analysis of tongue shape and motion in speech production using statistical modeling

The mechanisms of speech production are complex and have been raising attention from researchers of both medical and computer vision fields. In the speech production mechanism, the articulator’s study is a complex issue, since they have a high level of freedom along this process, namely the tongue, which instigates a problem in its control and observation. In this work it is automatically characterized the tongues shape during the articulation of the oral vowels of Portuguese European by using statistical modeling on MR-images. A point distribution model is built from a set of images collected during artificially sustained articulations of Portuguese European sounds, which can extract the main characteristics of the motion of the tongue. The model built in this work allows under standing more clearly the dynamic speech events involved during sustained articulations. The tongue shape model built can also be useful for speech rehabilitation purposes, specifically to recognize the compensatory movements of the articulators during speech production.

Statistical analysis of quality control measurements in IMRT for head and neck and prostate cancer

Intensity Modulated Radiotherapy (IMRT) is a technique introduced to shape more precisely the dose distributions to the tumour, providing a higher dose escalation in the volume to irradiate and simultaneously decreasing the dose in the organs at risk which consequently reduces the treatment toxicity. This technique is widely used in prostate and head and neck (H&N) tumours. Given the complexity and the use of high doses in this technique it’s necessary to ensure as a safe and secure administration of the treatment, through the use of quality control programmes for IMRT. The purpose of this study was to evaluate statistically the quality control measurements that are made for the IMRT plans in prostate and H&N patients, before the beginning of the treatment, analysing their variations, the percentage of rejected and repeated measurements, the average, standard deviations and the proportion relations.

A few what-ifs on using statistical analysis of stochastic simulation runs to extract timeliness properties

Modern real-time systems, with a more flexible and adaptive nature, demand approaches for timeliness evaluation based on probabilistic measures of meeting deadlines. In this context, simulation can emerge as an adequate solution to understand and analyze the timing behaviour of actual systems. However, care must be taken with the obtained outputs under the penalty of obtaining results with lack of credibility. Particularly important is to consider that we are more interested in values from the tail of a probability distribution (near worst-case probabilities), instead of deriving confidence on mean values. We approach this subject by considering the random nature of simulation output data. We will start by discussing well known approaches for estimating distributions out of simulation output, and the confidence which can be applied to its mean values. This is the basis for a discussion on the applicability of such approaches to derive confidence on the tail of distributions, where the worst-case is expected to be.

From simulation to statistical analysis: timeliness assessment of ethernet/IP-based distributed systems

A number of characteristics are boosting the eagerness of extending Ethernet to also cover factory-floor distributed real-time applications. Full-duplex links, non-blocking and priority-based switching, bandwidth availability, just to mention a few, are characteristics upon which that eagerness is building up. But, will Ethernet technologies really manage to replace traditional Fieldbus networks? Ethernet technology, by itself, does not include features above the lower layers of the OSI communication model. In the past few years, it is particularly significant the considerable amount of work that has been devoted to the timing analysis of Ethernet-based technologies. It happens, however, that the majority of those works are restricted to the analysis of sub-sets of the overall computing and communication system, thus without addressing timeliness at a holistic level. To this end, we are addressing a few inter-linked research topics with the purpose of setting a framework for the development of tools suitable to extract temporal properties of Commercial-Off-The-Shelf (COTS) Ethernet-based factory-floor distributed systems. This framework is being applied to a specific COTS technology, Ethernet/IP. In this paper, we reason about the modelling and simulation of Ethernet/IP-based systems, and on the use of statistical analysis techniques to provide usable results. Discrete event simulation models of a distributed system can be a powerful tool for the timeliness evaluation of the overall system, but particular care must be taken with the results provided by traditional statistical analysis techniques.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Assessment of climate change statistical downscaling methods: Application and comparison of two statistical methods to a single site in Lisbon

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Saúde mental, qualidade de vida e acesso aos cuidados de saúde na comunidade brasileira de Lisboa

Introdução: A utilização de serviços de saúde tem implicações importantes para o estado de saúde das populações. As políticas de imigração adoptadas nos países de destino têm influência no estado de saúde das comunidades imigrantes. Políticas que limitam o acesso de imigrantes aos cuidados de saúde aumentarão a vulnerabilidade e os riscos na saúde. Apesar da imigração promover uma série de rupturas na vida do sujeito, migrar, por si só, não pode ser considerado como factor de risco no âmbito da saúde e da saúde mental. O peso dos determinantes socioeconómicos tem ganho relevância no estudo das migrações, estado de saúde geral e mental. Isto porque, em geral, os imigrantes estão em situação mais precária do que a população autóctone. O estatuto socioeconómico baixo, as condições precárias de habitação e de trabalho, a falta de suporte social e a irregularidade jurídica são indicadores de risco acrescido para a saúde mental. Neste sentido é um desafio de monta os governos estabelecerem medidas sustentadas e, simultaneamente, integradoras dos imigrantes. Em Portugal, considera-se que há escassez de estudos relacionados com a área das migrações e da saúde.Metodologia: Estudo exploratório, descritivo e transversal. A finalidade foi a de identificar o estado de saúde, saúde mental e qualidade de vida da comunidade brasileira residente em Lisboa e o seu acesso aos serviços de saúde. Este estudo teve como principais objectivos a caracterização sociodemográfica, a identificação de variáveis inerentes ao processo migratório, a identificação da auto-apreciação do estado de saúde, a caracterização do acesso aos cuidados de saúde, a identificação do grupo em provável sofrimento psicológico, a comparação entre os resultados dos imigrantes juridicamente regulares e irregulares e a comparação entre a população imigrante e a população portuguesa. Inicialmente, foi prevista a utilização da técnica de amostragem de propagação geométrica ou snowball, pois a amostra tornar-se-ia maior à medida que os próprios inquiridos identificam outros potenciais respondentes. Ao longo do estudo, a metodologia inicial mostrou-se insuficiente para estabelecer uma amostra mais representativa dos imigrantes juridicamente irregulares. Para este feito, foi utilizada a metodologia de amostragem por conveniência e o local escolhido para a recolha da amostra foi o Consulado do Brasil em Lisboa. O instrumento de recolha de dados empregue baseou-se no questionário utilizado no 4º Inquérito Nacional de Saúde. O MHI-5 (Mental Health Index 5) é um instrumento de saúde mental e é parte integrante do inquérito, sendo recomendado pela Organização Mundial de Saúde. Consta de cinco itens relativos à saúde mental e os resultados são classificados através de um indicador que mede a existência de provável sofrimento psicológico. Foram incluídos no estudo 213 brasileiros. De seguida, procedeu-se ao tratamento estatístico dos dados. Resultados: A população inquirida é jovem, a maior parte tem entre 18 e 44 anos. As mulheres representam mais de metade da amostra. A taxa de actividade é elevada e a taxa de desemprego é similar à nacional. A inserção laboral prioritária é nos segmentos pouco qualificados ou de semi-qualificação. Aproximadamente um terço dos inquiridos afirmou ser beneficiário do Sistema Nacional de Saúde. A autoapreciação do estado de saúde é classificada como bastante positiva, assim como a qualidade de vida. O provável sofrimento psicológico, definido no MHI-5 pelo ponto de corte no score 52, atinge 23,3% dos participantes. Os homens apresentam melhores resultados do que as mulheres. Além disso, para os valores mais baixos no MHI-5 foram encontradas relações com as longas jornadas de trabalho e o diagnóstico de doença crónica.Discussão: O presente estudo apresenta limitações em relação à dimensão da amostra e à provável existência de enviesamento pela ausência de aleatorização. Apesar da legislação portuguesa garantir o acesso aos serviços de saúde e garantir a equidade no caso dos imigrantes que fazem descontos para a Segurança Social, apenas um terço referiu ser beneficiário do Sistema Nacional de Saúde. Este dado pode ser justificado por factores como o cumprimento da lei por alguns serviços e, também, pela falta de conhecimento da legislação e da forma de funcionamento do Serviço Nacional de Saúde por parte dos imigrantes. O facto das mulheres representarem o maior grupo em provável sofrimento psicológico é consistente com a literatura. As hipóteses levantadas para explicar este resultado podem ser agrupadas em: artefactos metodológicos, causalidade biológica e determinação social. Em relação ao instrumento, é possível que o MHI-5 se comporte de forma diferente no que diz respeito ao género.-------------------------------------------Introduction: The utilization of health services has important implications for the health state of the populations. The immigration policies adopted in the destiny countries are going to influence the health state of immigrant communities. Policies that limit the access of immigrants to health care are going to increase the vulnerability and the risk factor in health. Although immigration promotes several disruptive actions in ones life, migrating, on its own, cannot be considered as a risk factor for health and mental health. The preponderance of the socioeconomic factors has gained relevance in the study of migrations and also in the study of general health state and mental health. This happens because, in general, immigrants are in a more unfavorable situation compared with the destiny country population. The low socioeconomic status, the poor working and housing conditions, the lack of social support and the juridical irregularity are indicators of the incremented risk to mental health. Therefore, it is a major challenge for governments to find sustainable, and simultaneously, integrative measures for the immigrants. The studies related with the migrations and health in Portugal were considered to be few.Methods: It is an exploratory, descriptive and transversal study. The purpose is to identify the health state, mental health, quality of life and the access to health care of the Brazilian community resident in Lisbon. In addition, this study has as main goals the sociodemographic characterization, the variables identification inherent to the migrating process, the identification of the self-appreciation of health state, the characterization of the access to health care, the identification of the group in probable psychological suffer, the comparison between the results of regular and irregular immigrants and the comparison between the immigrant population and the Portuguese population. Initially it was predicted the utilization of the geometric propagation or “snowball”, as sampling technique, because the sample becomes larger as one answerer identify other potential answering persons. Along with the study, the methodology has shown insufficient to establish a more representative sample of the irregular immigrants. For this latter case, it was used a convenient sample methodology and the place chosen for the sample gathering was the “Consulate of Brazil in Lisbon”. The instrument was based in the questionnaire used in the “4th National Health Inquiry”. The MHI-5 (Mental Health Index 5) is a mental health instrument which is part of the enquiry and it is recommended by the World Health Organization. There are five items related to mental health and the results are classified through an indicator which measures the existence of a probable psychological suffer. It were included 213 Brazilian in the study. After, the statistical treatment of the data took place.Results: The answering population is young and the majority is between the 18 and 44 years of age. The women represent more than one half of the sample. The activity rate is high and the unemployment rate is similar to the national one. The priority labor insertion is in the few qualified or of semi-qualification segments. Approximately, one third of the answering people has stated to be beneficiary of the National Health System. The self-appreciation of the health state as well as the quality of life are classified as fairly positive ones. The probable psychological suffer, as defined in the MHI-5 through the cut point in the score below or equal to 52, reaches 23,3% of the sample population. Men show the better results than women. Further, for the lower values of MHI-5 it was found a relation with the long work periods and chronic disease diagnostic. Discussion: The present study evidences limitations in relation to the sample dimension and in relation to the existence of biases due to the lack of randomness. Although the Portuguese legislation guarantees the access to health services and the equality in the cases of the immigrants that do their Social Security discounts, only one third has mentioned to be beneficiary of the National Health System. This can be justified by several facts such as the non-fulfillment of law by some national services or the lack of knowledge of the legislation or the functioning process of the National Health System. Women representing the bigger group in probable psychological suffer has been coherent with the literature review. The hypothesis set to explain this result might be grouped in: methodological artifacts, biologic cause and social determination. In relation to the instrument used, it may be that MHI-5 behaves in a different way in respect to gender.