Multispectral remote sensing for site-specific nitrogen fertilizer management

The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R²=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil

The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Trends in the modes of delivery and their impact on perinatal mortality rates

OBJECTIVE: To determine changes in the incidence of vaginal deliveries, cesarean sections, and forceps deliveries and their potential association with fetal, early neonatal, and perinatal mortality rates over time. METHODS: A retrospective study was carried out and the occurrence of deliveries supervised by university services between January 1991 and December 2000 was determined. Data regarding fetal, early neonatal, and perinatal deaths were assessed using obstetric and pediatric records and autopsy reports. RESULTS: Of a total of 33,360 deliveries, the incidence of vaginal deliveries, cesarean sections, and forceps deliveries was relatively steady (around 60, 30, and 10%, respectively) while, at the same time, there was a marked reduction in fetal mortality (from 33.3 to 13.0‰), early neonatal mortality (from 30.6 to 9.0‰), and perinatal mortality (from 56.4 to 19.3‰). CONCLUSIONS: The marked reduction in perinatal mortality rates seen during the study period without an increase in cesarean sections indicates that the decrease in perinatal mortality was not impacted by cesarean section rates. The plausible hypothesis seems to be that the reduction in perinatal mortality of deliveries performed under the supervision of university services was more likely to be associated with better neonatal care rather than the mode of delivery.

Household members and health care workers as supervisors of tuberculosis treatment

OBJECTIVE: To compare tuberculosis cure rates among patients supervised by household members or health care workers. METHODS: Prospective cohort study of 171 patients treated by the program in Vitoria, Southeastern Brazil, from 2004 to 2007. Each patient was followed-up for six months until the end of the treatment. Of the patients studied, a household member supervised 59 patients and healthcare workers supervised 112 patients. Patients' sociodemographic and clinic data were analyzed. Differences between groups were assessed using chi-square test or Student's t-test. Significance level was set at 5%. RESULTS: Most patients had smear positive, culture confirmed pulmonary tuberculosis. Two patients were HIV-positive. There were more illiterate patients in the healthcare-supervised group, in comparison to those supervised by their families (p=0.01). All patients supervised by a household member were cured compared to 90% of the patients supervised by health care workers (p = 0.024). CONCLUSIONS: Successful tuberculosis treatment was more frequent when supervised by household members.

Dapsone hypersensitivity syndrome in an adolescent during treatment during of leprosy

A 12 y old girl was admitted 24 days after start a WHO multidrug therapy scheme for multibacillary leprosy (dapsone, clofazimine and rifampicin) with intense jaundice, generalized lymphadenopathy, hepatoesplenomegaly, oral erosions, conjunctivitis, morbiliform rash and edema of face, ankles and hands. The main laboratory data on admission included: hemoglobin, 8.4 g/dL; WBC, 15,710 cells/mm³; platelet count, 100,000 cells/mm³; INR = 1.49; increased serum levels of aspartate and alanine aminotransferases, gamma-glutamyl transpeptidase, alkaline phosphatase, direct and indirect bilirubin. Following, the clinical conditions had deteriorated, developing exfoliative dermatitis, shock, generalized edema, acute renal and hepatic failure, pancytopenia, intestinal bleeding, pneumonia, urinary tract infection and bacteremia, needing adrenergic drugs, replacement of fluids and blood product components, and antibiotics. Ten days after admission she started to improve, and was discharged to home at day 39th, after start new supervised treatment for leprosy with clofazimine and rifampicin, without adverse effects. This presentation fulfils the criteria for the diagnosis of dapsone hypersensitivity syndrome (fever, generalized lymphadenopathy, exfoliative rash, anemia and liver involvement with mixed hepatocellular and cholestatic features). Physicians, mainly in geographical areas with high prevalence rates of leprosy, should be aware to this severe, and probably not so rare, hypersensitivity reaction to dapsone.

Aerobic Training after Myocardial Infarction: Remodeling Evaluated by Cardiac Magnetic Resonance

Abstract Background: Numerous studies show the benefits of exercise training after myocardial infarction (MI). Nevertheless, the effects on function and remodeling are still controversial. Objectives: To evaluate, in patients after (MI), the effects of aerobic exercise of moderate intensity on ventricular remodeling by cardiac magnetic resonance imaging (CMR). Methods: 26 male patients, 52.9 ± 7.9 years, after a first MI, were assigned to groups: trained group (TG), 18; and control group (CG), 8. The TG performed supervised aerobic exercise on treadmill twice a week, and unsupervised sessions on 2 additional days per week, for at least 3 months. Laboratory tests, anthropometric measurements, resting heart rate (HR), exercise test, and CMR were conducted at baseline and follow-up. Results: The TG showed a 10.8% reduction in fasting blood glucose (p = 0.01), and a 7.3-bpm reduction in resting HR in both sitting and supine positions (p < 0.0001). There was an increase in oxygen uptake only in the TG (35.4 ± 8.1 to 49.1 ± 9.6 mL/kg/min, p < 0.0001). There was a statistically significant decrease in the TG left ventricular mass (LVmass) (128.7 ± 38.9 to 117.2 ± 27.2 g, p = 0.0032). There were no statistically significant changes in the values of left ventricular end-diastolic volume (LVEDV) and ejection fraction in the groups. The LVmass/EDV ratio demonstrated a statistically significant positive remodeling in the TG (p = 0.015). Conclusions: Aerobic exercise of moderate intensity improved physical capacity and other cardiovascular variables. A positive remodeling was identified in the TG, where a left ventricular diastolic dimension increase was associated with LVmass reduction.

Clinical and epidemiological profiles of individuals with drug-resistant tuberculosis

Drug-resistant tuberculosis (TB) is a growing global threat. Approximately 450,000 people developed multidrug-resistant TB worldwide in 2012 and an estimated 170,000 people died from the disease. This paper describes the sociodemographic, clinical-epidemiological and bacteriological aspects of TB and correlates these features with the distribution of anti-TB drug resistance. Mycobacterium tuberculosis (MT) cultures and drug susceptibility testing were performed according to the BACTEC MGIT 960 method. The results demonstrated that MT strains from individuals who received treatment for TB and people who were infected with human immunodeficiency virus were more resistant to TB drugs compared to other individuals (p < 0.05). Approximately half of the individuals received supervised treatment, but most drug-resistant cases were positive for pulmonary TB and exhibited positive acid-fast bacilli smears, which are complicating factors for TB control programs. Primary healthcare is the ideal level for early disease detection, but tertiary healthcare is the most common entry point for patients into the system. These factors require special attention from healthcare managers and professionals to effectively control and monitor the spread of TB drug-resistant cases.

The dynamics of Brazilian protozoology over the past century

Brazilian scientists have been contributing to the protozoology field for more than 100 years with important discoveries of new species such asTrypanosoma cruzi and Leishmania spp. In this work, we used a Brazilian thesis database (Coordination for the Improvement of Higher Education Personnel) covering the period from 1987-2011 to identify researchers who contributed substantially to protozoology. We selected 248 advisors by filtering to obtain researchers who supervised at least 10 theses. Based on a computational analysis of the thesis databases, we found students who were supervised by these scientists. A computational procedure was developed to determine the advisors’ scientific ancestors using the Lattes Platform. These analyses provided a list of 1,997 researchers who were inspected through Lattes CV examination and allowed the identification of the pioneers of Brazilian protozoology. Moreover, we investigated the areas in which researchers who earned PhDs in protozoology are now working. We found that 68.4% of them are still in protozoology, while 16.7% have migrated to other fields. We observed that support for protozoology by national or international agencies is clearly correlated with the increase of scientists in the field. Finally, we described the academic genealogy of Brazilian protozoology by formalising the “forest” of Brazilian scientists involved in the study of protozoa and their vectors over the past century.

Pedagogical reflective practice of nursing undergraduates: the portfolio as an instrument

Objective Analyzing the narratives related to the pedagogical practice experienced during the Supervised Curricular Internship reported in the portfolios of Nursing undergraduate students, regarding the levels of reflection. Method This is a documentary descriptive exploratory study that examined two of the activities proposed for the portfolio preparation. Results Among the 28 analyzed portfolios, all showed the three levels of reflection (technical, critical and metacritical). Conclusion The students had the opportunity to experience the pedagogical practice and presented reflections at metacritical level, reflecting on their performance, the construction of their teaching identity, and about the importance of reflecting on the practice with the objective of transforming it and transforming themselves.

Nursing care in the anesthetic procedure: an integrative review

Abstract OBJECTIVE To search for the scientific evidence available on nursing professional actions during the anesthetic procedure. METHOD An integrative review of articles in Portuguese, English and Spanish, indexed in MEDLINE/PubMed, CINAHL, LILACS, National Cochrane, SciELO databases and the VHL portal. RESULTS Seven studies were analyzed, showing nurse anesthetists' work in countries such as the United States and parts of Europe, with the formulation of a plan for anesthesia and patient care regarding the verification of materials and intraoperative controls. The barriers to their performance involved working in conjunction with or supervised by anesthesiologists, the lack of government guidelines and policies for the legal exercise of the profession, and the conflict between nursing and the health system for maintenance of the performance in places with legislation and defined protocols for the specialty. Conclusion Despite the methodological weaknesses found, the studies indicated a wide diversity of nursing work. Furthermore, in countries absent of the specialty, like Brazil, the need to develop guidelines for care during the anesthetic procedure was observed.

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.

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.

Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).

Estimating soybean crop areas using spectral-temporal surfaces derived from MODIS images in Mato Grosso, Brazil

The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.