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.

Predictive value of the ankle-brachial index in the evaluation of intermittent claudication

The purpose of this study was to determine whether the ankle-brachial index (ABI) could be used to predict the prognosis for a patient with intermittent claudication (IC). We studied 611 patients prospectively during 28 months of follow-up. We analyzed the predictive power of using various levels of ABI - 0.30 to 0.70 at 0.05 increments - in terms of the measure's specificity (association with a favorable outcome after exercise rehabilitation therapy) and sensitivity (association with a poor outcome after exercise rehabilitation therapy). We found that using an ABI of 0.30 as a cut-off value produced the lowest margin of error overall, but the predictive power was still low with respect to identifying the patients with a poor prognosis after non-aggressive therapeutic treatment. Further study is needed to perhaps identify a second factor that could increase the sensitivity of the test.

Terms of international classification for Nursing Practice in motor and physical rehabilitation

OBJECTIVE To validate terms of nursing language especially for physical-motor rehabilitation and map them to the terms of ICNP® 2.0. METHOD A methodology research based on document analysis, with collection and analysis of terms from 1,425 records. RESULTS 825 terms were obtained after the methodological procedure, of which 226 had still not been included in the ICNP® 2.0. These terms were distributed as follows: 47 on the Focus axis; 15 on the Judgment axis; 31 on the Action axis; 25 on the Location axis; 102 on the Means axis; three on the Time axis; and three on the Client axis. All non-constant terms in ICNP® have been validated by experts, having reached an agreement index ≥0.80. CONCLUSION The ICNP® is applicable and used in nursing care for physical-motor rehabilitation.

Assessment of the teaching-learning process in students of the health area: cardiopulmonary resuscitation maneuvers

OBJECTIVETo evaluate the skills and knowledge of undergraduate students in the health area on cardiopulmonary resuscitation maneuvers with the use of an automatic external defibrillator.METHODThe evaluation was performed in three different stages of the teaching-learning process. A theoretical and practical course was taught and the theoretical classes included demonstration. The evaluation was performed in three different stages of the teaching-learning process. Two instruments were applied to evaluate the skills (30-items checklist) and knowledge (40-questions written test). The sample comprised 84 students.RESULTSAfter the theoretical and practical course, an increase was observed in the number of correct answers in the 30-items checklist and 40-questions written test.CONCLUSIONAfter the theoretical class (including demonstration), only one of the 30-items checklist for skills achieved an index ≥ 90% of correct answers. On the other hand, an index of correct answers greater than 90% was achieved in 26 (86.7%) of the 30 items after a practical training simulation, evidencing the importance of this training in the defibrillation procedure.

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt and clay fractions, pH in water and organic carbon at six depths according to the specifications of the consortium of digital soil mapping at the global level (GlobalSoilMap). Continuous covariates and categorical predictors were used and their contributions to the model assessed. Only the environmental covariates elevation, aspect, stream power index (SPI), soil wetness index (SWI), normalized difference vegetation index (NDVI), and b3/b2 band ratio were significantly correlated with soil properties. The predictive models had a mean coefficient of determination of 0.21. Best results were obtained with the geostatistical predictive models, where the highest coefficient of determination 0.43 was associated with sand properties between 60 to 100 cm deep. The use of a sparse data set of soil properties for digital mapping can explain only part of the spatial variation of these properties. The results may be related to the sampling density and the quantity and quality of the environmental covariates and predictive models used.

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar¹

Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

Construction of an index of information from clinical practice in Radiology and Imaging Diagnosis based on text mining and thesaurus

Objective To construct a Portuguese language index of information on the practice of diagnostic radiology in order to improve the standardization of the medical language and terminology. Materials and Methods A total of 61,461 definitive reports were collected from the database of the Radiology Information System at Hospital das Clínicas – Faculdade de Medicina de Ribeirão Preto (RIS/HCFMRP) as follows: 30,000 chest x-ray reports; 27,000 mammography reports; and 4,461 thyroid ultrasonography reports. The text mining technique was applied for the selection of terms, and the ANSI/NISO Z39.19-2005 standard was utilized to construct the index based on a thesaurus structure. The system was created in *html. Results The text mining resulted in a set of 358,236 (n = 100%) words. Out of this total, 76,347 (n = 21%) terms were selected to form the index. Such terms refer to anatomical pathology description, imaging techniques, equipment, type of study and some other composite terms. The index system was developed with 78,538 *html web pages. Conclusion The utilization of text mining on a radiological reports database has allowed the construction of a lexical system in Portuguese language consistent with the clinical practice in Radiology.

Learning on human resources management in the radiology residency program

Objective To investigate the process of learning on human resource management in the radiology residency program at Escola Paulista de Medicina – Universidade Federal de São Paulo, aiming at improving radiologists' education. Materials and Methods Exploratory study with a quantitative and qualitative approach developed with the faculty staff, preceptors and residents of the program, utilizing a Likert questionnaire (46), taped interviews (18), and categorization based on thematic analysis. Results According to 71% of the participants, residents have clarity about their role in the development of their activities, and 48% said that residents have no opportunity to learn how to manage their work in a multidisciplinary team. Conclusion Isolation at medical records room, little interactivity between sectors with diversified and fixed activities, absence of a previous culture and lack of a training program on human resources management may interfere in the development of skills for the residents' practice. There is a need to review objectives of the medical residency in the field of radiology, incorporating, whenever possible, the commitment to the training of skills related to human resources management thus widening the scope of abilities of the future radiologists.

Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach

AbstractObjective:The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients' body mass index.Materials and Methods:The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality.Results:An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes.Conclusion:The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient.

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

Clinical assessment of the effect of digital filtering on the detection of ventricular late potentials

Ventricular late potentials are low-amplitude signals originating from damaged myocardium and detected on the body surface by ECG filtering and averaging. Digital filters present in commercial equipment may interfere with the ability of arrhythmia stratification. We compared 40-Hz BiSpec (BI) and classical 40- to 250-Hz band-pass Butterworth bidirectional (BD) filters in terms of impact on time domain variables and diagnostic properties. In a transverse retrospective age-adjusted case-control study, 221 subjects with sinus rhythm without bundle branch block were divided into three groups after signal-averaged ECG acquisition: GI (N = 40), clinically normal controls, GII (N = 158), subjects with coronary heart disease without sustained monomorphic ventricular tachycardia (SMVT), and GIII (N = 23), subjects with heart disease and documented SMVT. Conventional variables analyzed from vector magnitude data after averaging to 0.3 µV final noise were obtained by application of each filter to the averaged signal, and evaluated in pairs by numerical comparison and by diagnostic agreement assessment, using conventional and optimized thresholds of normality. Significant differences were found between BI and BD variables in all groups, with diagnostic results showing significant disagreement between both filters [kappa value of 0.61 (P<0.05) for GII and 0.31 for GIII (P = NS)]. Sensitivity for SMVT was lower with BI than with BD (65.2 vs 91.3%, respectively, P<0.05). Filters provided significantly different numerical and diagnostic results and the BI filter showed only limited clinical application to risk stratification of ventricular arrhythmia.

Effects of isoflavone on the learning and memory of women in menopause: a double-blind placebo-controlled study

Hormone decline is common to all women during aging and, associated with other factors, leads to cognitive impairment. Its replacement enhances cognitive performance, but not all women present a clinical and family or personal history that justifies its use, mainly women with a history of cancer. The aim of this study was to determine whether a daily oral dose of 80 mg of isoflavone extract for 4 months can produce benefits in women with low hormone levels, contributing to improvement in cognitive aspects. The sample comprised 50- to 65-year-old women whose menstruation had ceased at least 1 year before and who had not undergone hormone replacement. The volunteers were allocated to two groups of 19 individuals each, i.e., isoflavone and placebo. There was a weak correlation between menopause duration and low performance in the capacity to manipulate information (central executive). We observed an increase in the capacity to integrate information in the group treated with isoflavone, but no improvement in the capacity to form new memories. We did not observe differences between groups in terms of signs and symptoms suggestive of depression according to the Geriatric Depression Scale. Our results point to a possible beneficial effect of isoflavone on some abilities of the central executive. These effects could also contribute to minimizing the impact of memory impairment. Further research based on controlled clinical trials is necessary to reach consistent conclusions.

Role of p53 codon 72 polymorphism in chromosomal aberrations and mitotic index in patients with chronic hepatitis B

Polymorphisms of the p53 gene, which participates in DNA repair, can affect the functioning of the p53 protein. The Arg and Pro variants in p53 codon 72 were shown to have different regulation properties of p53-dependent DNA repair target genes that can affect various levels of cytogenetic aberrations in chronic hepatitis B patients. The present study aimed to examine the frequency of chromosomal aberrations and the mitotic index in patients with chronic hepatitis B and their possible association with p53 gene exon 4 codon 72 Arg72Pro (Ex4+119 G>C; rs1042522) polymorphism. Fifty-eight patients with chronic hepatitis B and 30 healthy individuals were genotyped in terms of the p53 gene codon 72 Arg72Pro polymorphism by PCR-RFLP. A 72-h cell culture was performed on the same individuals and evaluated in terms of chromosomal aberrations and mitotic index. A high frequency of chromosomal aberrations and low mitotic index were detected in the patient group compared to the control group. A higher frequency of chromosomal aberrations was detected in both the patient and the control groups with a homozygous proline genotype (13 patients, 3 control subjects) compared to patients and controls with other genotypes [Arg/Pro (38 patients, 20 control subjects) and Arg/Arg (7 patients, 7 control subjects)]. We observed an increased frequency of cytogenetic aberrations in patients with chronic hepatitis B. In addition, a higher frequency of cytogenetic aberrations was observed in p53 variants having the homozygous proline genotype compared to variants having other genotypes both in patients and healthy individuals.