Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

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.

Correlation, by multivariate statistical analysis, between the scavenging capacity against reactive oxygen species and the bioactive compounds from frozen fruit pulps

The contents of total phenolic compounds (TPC), total flavonoids (TF), and ascorbic acid (AA) of 18 frozen fruit pulps and their scavenging capacities against peroxyl radical (ROO•), hydrogen peroxide (H2O2), and hydroxyl radical (•OH) were determined. Principal Component Analysis (PCA) showed that TPC (total phenolic compounds) and AA (ascorbic acid) presented positive correlation with the scavenging capacity against ROO•, and TF (total flavonoids) showed positive correlation with the scavenging capacity against •OH and ROO• However, the scavenging capacity against H2O2 presented low correlation with TF (total flavonoids), TPC (total phenolic compounds), and AA (ascorbic acid). The Hierarchical Cluster Analysis (HCA) allowed the classification of the fruit pulps into three groups: one group was formed by the açai pulp with high TF, total flavonoids, content (134.02 mg CE/100 g pulp) and the highest scavenging capacity against ROO•, •OH and H2O2; the second group was formed by the acerola pulp with high TPC, total phenolic compounds, (658.40 mg GAE/100 g pulp) and AA , ascorbic acid, (506.27 mg/100 g pulp) contents; and the third group was formed by pineapple, cacao, caja, cashew-apple, coconut, cupuaçu, guava, orange, lemon, mango, passion fruit, watermelon, pitanga, tamarind, tangerine, and umbu pulps, which could not be separated considering only the contents of bioactive compounds and the scavenging properties.

Using different satellite imagery and classification techniques to assess the contribution of trees outside forests in the municipality of Maringá, Brazil

Forest cover of the Maringá municipality, located in northern Parana State, was mapped in this study. Mapping was carried out by using high-resolution HRC sensor imagery and medium resolution CCD sensor imagery from the CBERS satellite. Images were georeferenced and forest vegetation patches (TOFs - trees outside forests) were classified using two methods of digital classification: reflectance-based or the digital number of each pixel, and object-oriented. The areas of each polygon were calculated, which allowed each polygon to be segregated into size classes. Thematic maps were built from the resulting polygon size classes and summary statistics generated from each size class for each area. It was found that most forest fragments in Maringá were smaller than 500 m². There was also a difference of 58.44% in the amount of vegetation between the high-resolution imagery and medium resolution imagery due to the distinct spatial resolution of the sensors. It was concluded that high-resolution geotechnology is essential to provide reliable information on urban greens and forest cover under highly human-perturbed landscapes.

Comparison of methods for classification of the coefficient of variation in papaya

ABSTRACT The objective of this work was to study the distribution of values of the coefficient of variation (CV) in the experiments of papaya crop (Carica papaya L.) by proposing ranges to guide researchers in their evaluation for different characters in the field. The data used in this study were obtained by bibliographical review in Brazilian journals, dissertations and thesis. This study considered the following characters: diameter of the stalk, insertion height of the first fruit, plant height, number of fruits per plant, fruit biomass, fruit length, equatorial diameter of the fruit, pulp thickness, fruit firmness, soluble solids and internal cavity diameter, from which, value ranges were obtained for the CV values for each character, based on the methodology proposed by Garcia, Costa and by the standard classification of Pimentel-Gomes. The results obtained in this study indicated that ranges of CV values were different among various characters, presenting a large variation, which justifies the necessity of using specific evaluation range for each character. In addition, the use of classification ranges obtained from methodology of Costa is recommended.

Risk factors for basal cell carcinoma: a case-control study

A controlled trial was performed with the purpose of investigating which factors could be considered of significant risk for the development of basal cell carcinoma. A total of 259 cases of basal cell carcinoma diagnosed from July 1991 to July 1992 were compared with 518 controls matched for age and sex. All subjects in both groups were white. Protocol data were submitted to statistical analysis by the chi-square test and by multiple conditional logistic regression analysis and the following conclusions were reached: 1) light skin color (types I and II of the Fitzpatrick classification), odds ratio of 2.8; outdoor work under constant sunlight, odds ratio of 5.0; the presence of actinic lesions due to exposure to the sun, odds ratio of 4.9, are risk factors perse. 2) Type III skin in the Fitzpatrick classification only represents a risk factor when the patient reports a history of intense sunburns, but not in the absence of such a history. 3) Sunburns per se do not represent a risk factor althorig the point made in item 2 of these conclusions is valid. 4) Other suspected risk factors whose significance was not confirmed by multiple conditioned logistic regression analysis were: residence in rural areas, light eyes and blond hair color, extent of the awareness of the "sun x skin cancer" relationship, familial occurrence of skin cancer, excessive exposure to the sun, and freckles appearing in childhood.

Comparative evaluation of underlying causes of death processed by the Automated Classification of Medical Entities and the Underlying Cause of Death Selection Systems

INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

Comorbidity adjustment index for the international classification of diseases, 10

OBJECTIVE: To develop a Charlson-like comorbidity index based on clinical conditions and weights of the original Charlson comorbidity index. METHODS: Clinical conditions and weights were adapted from the International Classification of Diseases, 10th revision and applied to a single hospital admission diagnosis. The study included 3,733 patients over 18 years of age who were admitted to a public general hospital in the city of Rio de Janeiro, southeast Brazil, between Jan 2001 and Jan 2003. The index distribution was analyzed by gender, type of admission, blood transfusion, intensive care unit admission, age and length of hospital stay. Two logistic regression models were developed to predict in-hospital mortality including: a) the aforementioned variables and the risk-adjustment index (full model); and b) the risk-adjustment index and patient's age (reduced model). RESULTS: Of all patients analyzed, 22.3% had risk scores >1, and their mortality rate was 4.5% (66.0% of them had scores >1). Except for gender and type of admission, all variables were retained in the logistic regression. The models including the developed risk index had an area under the receiver operating characteristic curve of 0.86 (full model), and 0.76 (reduced model). Each unit increase in the risk score was associated with nearly 50% increase in the odds of in-hospital death. CONCLUSIONS: The risk index developed was able to effectively discriminate the odds of in-hospital death which can be useful when limited information is available from hospital databases.

Legal and health variations in drug litigation injunctions granted in Minas Gerais

OBJECTIVE To investigate the factors related to the granting of preliminary court orders [injunctions] in drug litigations. METHODS A retrospective descriptive study of drug lawsuits in the State of Minas Gerais, Southeastern Brazil, was conducted from October 1999 to 2009. The database consists of 6,112 lawsuits, out of which 6,044 had motions for injunctions and 5,167 included the requisition of drugs. Those with more than one beneficiary were excluded, which totaled 5,072 examined suits. The variables for complete, partial, and suppressed motions were treated as dependent and assessed in relation to those that were independent – lawsuits (year, type, legal representation, defendant, court in which it was filed, adjudication time), drugs (level five of the anatomical therapeutic chemical classification), and diseases (chapter of the International Classification of Diseases). Statistical analyses were performed using the Chi-square test. RESULTS Out of the 5,072 lawsuits with injunctions, 4,184 (82.5%) had the injunctions granted. Granting varied from 95.8% of the total lawsuits in 2004 to 76.9% in 2008. Where there was legal representation, granting exceeded 80.0% and in lawsuits without representation, it did not exceed 66.9%. In public civil actions (89.1%), granting was higher relative to ordinary lawsuits (82.8%) and injunctions (80.1%). Federal courts granted only 68.6% of the injunctions, while the state courts granted 84.8%. Diseases of the digestive system and neoplasms received up to 87.0% in granting, while diseases of the nervous system, mental and behavioral disorders, and diseases of the skin and subcutaneous tissue received granting below 78.6% and showed a high proportion of suspended injunctions (10.9%). Injunctions involving paroxetine, somatropin, and ferrous sulfate drugs were all granted, while less than 54.0% of those involving escitalopram, sodium diclofenac, and nortriptyline were granted. CONCLUSIONS There are significant differences in the granting of injunctions, depending on the procedural and clinical variances. Important trends in the pattern of judicial action were observed, particularly, in the reduced granting [of injunctions] over the period.

Thermostability of heterophile antibodies from human sera infected with Schistosoma mansoni and geo-helminths: an immuno-metric statistical analysis

Antibody in human sera that induces lysis of sheep erythrocytes in hemolytic assay was investigated. The present study showed that the presence in serum of the thermostable cytolytic anti-sheep red blood cells antibodies is dependent on the Schistosoma mansoni infection, and this is more frequent in adults than in children. The thermostable characteristic of hemolysins in normal sera was not dependent on the presence of Ascaris lumbricoides, Trichuris trichiura or hookworm geo-helminths. Further, thermostable complement-activating heterophile antibodies were noticed in children in association with massive number of S. mansoni eggs. The results were obtained by using the z- and the chi-square tests. The z-test allows us to formulate a one-sided alternative, i.e., a tendency of one of the attributes. On the other hand, the chi-square test analyzes the independence between attributes by using a contingency table. Besides the obtained results being interesting in the field of schistosomiasis mansoni, they can provide a new insight into the use of statistics in medical science.

Classification of varieties of pasteurella pestis strains isolated in the interior of the state of Pernambuco-Brazil

Studies were made on the biochemical behavior of 100 strains of P.pestis isolated in Northeastern Brazil with regard to production of nitrous acid, reduction of nitrates to nitrltes, and aciáification of glycerol. Results showed that 98 strains can be classified as "orientalis variety", while the remaining two could not be included in any of the existing "varieties".

Retrospective histopathological classification of 1,108 skin biopsies from patients clinically suspected of having leprosy from Bahia, Northeast Brazil

We report a retrospective histopathological classification carried out under laboratory conditions by the method of Ridley & Jopling of 1,108 skin biopsies from patients clinically suspected of having leprosy from Bahia, Northeast Brazil.