Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Modifications of MCM-22 zeolite through sequential post-synthesis treatments. Implications on the acidic and catalytic behaviour

Desilication and a combination of alkaline followed by acid treatment were applied to MCM-22 zeolite using two different base concentrations. The samples were characterised by powder X-ray diffraction, Al-27 and Si-29 MAS-NMR spectroscopy, SEM, TEM and low temperature N-2 adsorption. The acidity of the samples was study through pyridine adsorption followed by FTIR spectroscopy and by the analyses of the hydroxyl region. The catalytic behaviour, anticipated by the effect of post-synthesis treatments on the acidity and space available inside the two internal pore systems was evaluated by using the model reaction of m-xylene transformation. The generation of mesoporosity was achieved upon alkaline treatment with 0.05 M NaOH solution and practically no additional gain was obtained when the more concentrate solution, 0.1 M, was used. Instead, Al extraction takes place along with Si, as shown by Si-29 and Al-27 MAS-NMR data, followed by Al deposition as extraframework species. Samples submitted to alkaline plus acid treatments present distinct behaviour. When the lowest NaOH solution was used no relevant effect was observed on the textural characteristics. Additionally, when the acid treatment was performed on an already fragilized MCM-22 structure, due to previous desilication with 0.1 M NaOH solution, the extraction of Al from both internal pore systems promotes their interconnection, evolving from a 2-D to a 3-D porous structure. This transformation has a marked effect in the catalytic behaviour, allowing an increase of m-xylene conversion as a consequence of an easier and faster molecular traffic in the 3-D structure. On the other hand, the continuous deposition of extraframework Al species inside the pores leads to a shape selective effect that privileges the formation of the more valuable isomer p-xylene.

Diagnostic performance of visual screening tests in the elderly

This study aimed to determine and evaluate the diagnostic accuracy of visual screening tests for detecting vision loss in elderly. This study is defined as study of diagnostic performance. The diagnostic accuracy of 5 visual tests -near convergence point, near accommodation point, stereopsis, contrast sensibility and amsler grid—was evaluated by means of the ROC method (receiver operating characteristics curves), sensitivity, specificity, positive and negative likelihood ratios (LR+/LR−). Visual acuity was used as the reference standard. A sample of 44 elderly aged 76.7 years (±9.32), who were institutionalized, was collected. The curves of contrast sensitivity and stereopsis are the most accurate (area under the curves were 0.814−p = 0.001, C.I.95%[0.653;0.975]— and 0.713−p = 0.027, C.I.95%[0,540;0,887], respectively). The scores with the best diagnostic validity for the stereopsis test were 0.605 (sensitivity 0.87, specificity 0.54; LR+ 1.89, LR−0.24) and 0.610 (sensitivity 0.81, specificity 0.54; LR+1.75, LR−0.36). The scores with higher diagnostic validity for the contrast sensibility test were 0.530 (sensitivity 0.94, specificity 0.69; LR+ 3.04, LR−0.09). The contrast sensitivity and stereopsis test's proved to be clinically useful in detecting vision loss in the elderly.

Diagnostic performance of visual screening tests in the elderly

The aging of Portuguese population is characterized by an increase of individuals aged older than 65 years. Preventable visual loss in older persons is an important public health problem. Tests used for vision screening should have a high degree of diagnostic validity confirmed by means of clinical trials. The primary aim of a screening program is the early detection of visual diseases. Between 20% and 50% of older people in the UK have undetected reduced vision and in most cases is correctable. Elderly patients do not receive a systematic eye examination unless a problem arises with their glasses or suspicion vision loss. This study aimed to determine and evaluate the diagnostic accuracy of visual screening tests for detecting vision loss in elderly. Furthermore, it pretends to define the ability to find the subjects affected with vision loss as positive and the subjects not affected with the same disease as negative. The ideal vision screening method should have high sensitivity and specificity for early detection of risk factors. It should be also low cost and easy to implement in all geographic and socioeconomic regions. Sensitivity is the ability of an examination to identify the presence of a given disease and specificity is the ability of the examination to identify the absence of a given disease. It was not an aim of this study to detect abnormalities that affect visual acuity. The aim of this study was to find out what´s the best test for the identification of any vision loss.

Supercritical CO2 extraction of secondary metabolites from Agaricus blazei: experiments and modelling

The mycelium and young fruiting bodies of Agaricus blazei were submitted to supercritical CO2 extraction, in a modified commercial flow apparatus, at temperatures from 40 to 80 ºC, pressures up to 600 bar and CO2 flow-rates from 2.0 to 9.0 g.min-1. The best extraction conditions of secondary metabolites, whereby the degree of solubilization (g extract/100 g of fungi) is the highest, was obtained with pure CO2 at 400 bar, 70 ºC and a CO2 flow rate of 5.7g.min-1. The extract in that conditions were analysed by GC-Ms. In order to increase the extraction yield of secondary metabolites, which are mostly present in glycolipid fractions, a polar compound (ethanol) was used as co-solvent in the proportions of 5 and 10 % (mol/mol). The presence of ethanol increased the yield when compared with the extraction with pure CO2. Moreover, a simple model was applied to the supercritical CO2 extraction of secondary metabolites from Agaricus blazei.

Herbicidal activity of volatiles from coriander, winter savory, cotton lavender, and thyme isolated by hydrodistillation and supercritical fluid extraction

The volatiles from Coriandrum sativum L., Satureja montana L., Santolina chamaecyparissus L., and Thymus vulgaris L. were isolated by hydrodistillation (essential oil) and supercritical fluid extraction (volatile oil). Their effect on seed germination and root and shoot growth of the surviving seedlings of four crops (Zea mays L., Triticum durum L., Pisum sativum L., and Lactuca sativa L.) and two weeds (Portulaca oleracea L. and Vicia sativa L.) was investigated and compared with those of two synthetic herbicides, Agrocide and Prowl. The volatile oils of thyme and cotton lavender seemed to be promising alternatives to the synthetic herbicides because they were the least injurious to the crop species. The essential oil of winter savory, on the other hand, affected both crop and weeds and can be appropriate for uncultivated fields.

Composition and antioxidant activity of thymus vulgaris volatiles: comparison between supercritical fluid extraction and hydrodistillation

Supercritical fluid extraction (SEE) of the volatile oil from Thymus vulgaris L. aerial flowering parts was performed under different conditions of pressure, temperature, mean particle size and CO2 flow rate and the correspondent yield and composition were compared with those of the essential oil isolated by hydrodistillation (HD). Both the oils were analyzed by GC and GC-MS and 52 components were identified. The main volatile components obtained were p-cymene (10.0-42.6% for SFE and 28.9-34.8% for HD), gamma-terpinene (0.8-6.9% for SFE and 5.1-7.0% for HD), linalool (2.3-5.3% for SFE and 2.8-3.1% for HD), thymol (19.5-40.8% for SFE and 35.4-41.6% for HD), and carvacrol (1.4-3.1% for SFE and 2.6-3.1% for HD). The main difference was found to be the relative percentage of thymoquinone (not found in the essential oil) and carvacryl methyl ether (1.0-1.2% for HD versus t-0.4 for SFE) which can explain the higher antioxidant activity, assessed by Rancimat test, of the SFE volatiles when compared with HD. Thymoquinone is considered a strong antioxidant compound.

Mathematical modelling of supercritical CO2 extraction of volatile oils from aromatic plants

The modelling of the experimental data of the extraction of the volatile oil from six aromatic plants (coriander, fennel, savoury, winter savoury, cotton lavender and thyme) was performed using five mathematical models, based on differential mass balances. In all cases the extraction was internal diffusion controlled and the internal mass transfer coefficienty (k(s)) have been found to change with pressure, temperature and particle size. For fennel, savoury and cotton lavender, the external mass transfer and the equilibrium phase also influenced the second extraction period, since k(s) changed with the tested flow rates. In general, the axial dispersion coefficient could be neglected for the conditions studied, since Peclet numbers were high. On the other hand, the solute-matrix interaction had to be considered in order to ensure a satisfactory description of the experimental data.

Tuning Iris Recognition for Noisy Images

The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

Extraction of hemoglobin with calixarenes and biocatalysis in organic media of the complex with pseudoactivity of peroxidase

The present work involves the use of p-tert-butylcalix[4,6,8]arene carboxylic acid derivatives ((t)Butyl[4,6,8]CH2COOH) for selective extraction of hemoglobin. All three calixarenes extracted hemoglobin into the organic phase, exhibiting extraction parameters higher than 0.90. Evaluation of the solvent accessible positively charged amino acid side chains of hemoglobin (PDB entry 1XZ2) revealed that there are 8 arginine, 44 lysine and 30 histidine residues on the protein surface which may be involved in the interactions with the calixarene molecules. The hemoglobin-(t)Butyl[6]CH2COOH complex had pseudoperoxidase activity which catalysed the oxidation of syringaldazine in the presence of hydrogen peroxide in organic medium containing chloroform. The effect of pH, protein and substrate concentrations on biocatalysis was investigated using the hemoglobin-(t)Butyl[6]CH2COOH complex. This complex exhibited the highest specific activity of 9.92 x 10(-2) U mg protein(-1) at an initial pH of 7.5 in organic medium. Apparent kinetic parameters (V'(max), K'(m), k'(cat) and k'(cat)/K'(m)) for the pseudoperoxidase activity were determined in organic media for different pH values from a Michaelis-Menten plot. Furthermore, the stability of the protein-calixarene complex was investigated for different initial pH values and half-life (t(1/2)) values were obtained in the range of 1.96 and 2.64 days. Hemoglobin-calixarene complex present in organic medium was recovered in fresh aqueous solutions at alkaline pH, with a recovery of pseudoperoxidase activity of over 100%. These results strongly suggest that the use of calixarene derivatives is an alternative technique for protein extraction and solubilisation in organic media for biocatalysis.

Supercritical carbon dioxide extraction of bioactive compounds from microalgae and volatile oils from aromatic plants

A discussion of the most interesting results obtained in our laboratories, during the supercritical CO(2) extraction of bioactive compounds from microalgae and volatile oils from aromatic plants, was carried out. Concerning the microalgae, the studies on Botryococcus braunii and Chlorella vulgaris were selected. Hydrocarbons from the first microalgae, which are mainly linear alkadienes (C(23)-C(31)) with an odd number of carbon atoms, were selectively extracted at 313 K increasing the pressure up to 30.0 MPa. These hydrocarbons are easily extracted at this pressure, since they are located outside the cellular walls. The extraction of carotenoids, mainly canthaxanthin and astaxanthin, from C. vulgaris is more difficult. The extraction yield of these components at 313 K and 35.0 MPa increased with the degree of crushing of the microalga, since they are not extracellular. On the other hand, for the extraction of volatile oils from aromatic plants, studies on Mentha pulegium and Satureja montana L were chosen. For the first aromatic plant, the composition of the volatile and essential oils was similar, the main components being the pulegone and menthone. However, this volatile oil contained small amounts of waxes, which content decreased with decreasing particle size of the plant matrix. For S. montana L it was also observed that both oils have a similar composition, the main components being carvacrol and thymol. The main difference is the relative amount of thymoquinone, which content can be 15 times higher in volatile oil. This oxygenated monoterpene has important biological activities. Moreover, experimental studies on anticholinesterase activity of supercritical extracts of S. montana were also carried out. The supercritical nonvolatile fraction, which presented the highest content of the protocatechuic, vanilic, chlorogenic and (+)-catechin acids, is the most promising inhibitor of the enzyme butyrylcholinesterase. In contrast, the Soxhlet acetone extract did not affect the activity of this enzyme at the concentrations tested. (C) 2011 Elsevier B.V. All rights reserved.

Classification and staging of chronic liver disease from multimodal data

Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

Validação de um método de cromatografia líquida de alta resolução (HPLC) para doseamento da vitamina D em géneros alimentícios: aplicação do método em diferentes matrizes alimentares

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Ensaios em pontes

Dissertação para a obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas