GDP 4.0 transfer to SGP 3.0 for SCIAMACHY no2 column processing: Verification with SDOAS / GDOAS prototype algorithms and delta-validation with NDACC / UV-visible network data

Until mid 2006, SCIAMACHY data processors for the operational retrieval of nitrogen dioxide (NO2) column data were based on the historical version 2 of the GOME Data Processor (GDP). On top of known problems inherent to GDP 2, ground-based validations of SCIAMACHY NO2 data revealed issues specific to SCIAMACHY, like a large cloud-dependent offset occurring at Northern latitudes. In 2006, the GDOAS prototype algorithm of the improved GDP version 4 was transferred to the off-line SCIAMACHY Ground Processor (SGP) version 3.0. In parallel, the calibration of SCIAMACHY radiometric data was upgraded. Before operational switch-on of SGP 3.0 and public release of upgraded SCIAMACHY NO2 data, we have investigated the accuracy of the algorithm transfer: (a) by checking the consistency of SGP 3.0 with prototype algorithms; and (b) by comparing SGP 3.0 NO2 data with ground-based observations reported by the WMO/GAW NDACC network of UV-visible DOAS/SAOZ spectrometers. This delta-validation study concludes that SGP 3.0 is a significant improvement with respect to the previous processor IPF 5.04. For three particular SCIAMACHY states, the study reveals unexplained features in the slant columns and air mass factors, although the quantitative impact on SGP 3.0 vertical columns is not significant.

The influence of zero-value subtraction on the performance of two laser fluorescence devices for detecting occlusal caries in vitro

Background. The aim of this study was to evaluate the influence of zero-value subtraction on the performance of two laser fluorescence (LF) devices developed to detect occlusal caries. Methods. The authors selected 119 permanent molars. Two examiners assessed three areas (cuspal, middle and cervical) of both mesial and distal portions of the buccal surface and one occlusal site using an LF device and an LF pen. For each tooth, the authors subtracted the value measured in the cuspal, middle and cervical areas in the buccal surface from the value measured in the respective occlusal site. Results. The authors observed differences among the readings for both devices in the cuspal, middle and cervical areas in the buccal surface as well as differences for both devices with and without the zero-value subtraction in the occlusal surface. When the authors did not perform the zero-value subtraction, they found statistically significant differences for sensitivity and accuracy for the LF device. When this was done with the LF pen, specificity increased and sensitivity decreased significantly. Conclusions. For the LF device, the zero-value subtraction decreased the sensitivity. For this reason, the authors concluded that clinicians can obtain measures with the LF device effectively without using zero-value subtraction. For the LF pen, however, the absence of the zero-value subtraction changed both the sensitivity and specificity, and so the authors concluded that clinicians should not eliminate this step from the procedure. Clinical Implications. When using the LF device, clinicians might not need to perform the zero-value subtraction; however, for the LF pen, clinicians should do so.

Accuracy of impression techniques for implants. Part 1 - Influence of transfer copings surface abrasion

Purpose: This study evaluated the influence of surface abrasion of transfer copings to obtain a precise master cast for a partially edentulous restoration with different inclinations. Materials and Methods: Replicas (N = 30) of a metal matrix (control group) containing two implants at 90° and 65° in relation to the benchtop were obtained using a polyether impression material and three impression techniques: square impression copings splint with dental floss and autopolymerizing acrylic resin (TRS), square impression copings abraded with aluminum oxide (TA), and square impression copings abraded with aluminum oxide and adhesive-coated (TAA). The replicas obtained in type V stone were digitalized, and the images were exported to AutoCAD software to perform the readings of possible degree alterations in implant inclinations. The results were submitted to analysis of variance (ANOVA) and Tukey test (α < 0.05). Results: Comparing the techniques with regard to the 90° implant inclination, no statistical difference was observed between the three techniques and the control group. Analyzing the three techniques with regard to the 65° implant inclination, no significant difference was seen between technique TA and the control group. Conclusions: Technique TA presented more accurate master casts than TRS and TAA techniques. The angulated implant (65°) tended to generate more imprecise master casts than implants perpendicular to the surface. © 2008 by The American College of Prosthodontists.

Influence of storage period and effect of different brands of acrylic resin on the dimensional accuracy of the maxillary denture base

The aim of this study was to evaluate the dimensional changes of denture bases made from different resins after different storage periods. For this purpose, 25 sets of plaster models/resin bases were prepared using 4 acrylic resins submitted to two types of polymerization: 1- QC-20 submitted to polymerization by microwave energy; 2- QC-20 submitted to polymerization by water hot bath; 3- Vipi Cril submitted to polymerization by water hot bath; 4- Vipi Wave submitted to polymerization by microwave energy; and 5- Onda Cryl submitted to polymerization by microwave energy. After polymerization, the specimens were sectioned for accuracy readings using a comparison microscope. Readings were taken at 3 points: the crests of the right (A) and left (B) ridges, and the median region of the palate, in 4 different periods. The data obtained were submitted to two-way ANOVA and Tukey's test at 5% significance level. The greatest distortions were found in the posterior palatal region of the base (M), with statistically significant difference (p<0.05) for the studied resins. All acrylic resins presented dimensional changes and the storage period influenced these alterations.

A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Assessment of manipulation accuracy of digitized occlusal radiographic images--sub and over exposure.

The aim of this study was to evaluate whether digitized images obtained from occlusal radiographs taken with low or over dose of radiation could be improved with the aid of computer software for digital treatment. Thirteen occlusal radiographs of a dry skull were taken employing 13 different exposure times. The radiographs were digitized and then manipulated with the program for image editing. 143 evaluations were performed by specialists in dental radiology who classified radiographs as appropriate or not appropriate for interpretation. Test Z was used for statistical analysis of the data and the results showed that it is possible to manipulate digitized radiographic images taken with 75% of the ideal exposure time and to make them suitable for interpretation and diagnosis. Conversely, it was concluded that the over exposed images, 57.50% above the standard exposure time, were inadequate.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

Improving the accuracy of the optimum-path forest supervised classifier for large datasets

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the training set. Identification of outliers is based on a penalty computed for each sample in the training set from the corresponding number of imputable false positive and false negative classification of samples. This approach enhances the accuracy of OPF while still gaining in classification time, at the expense of a slight increase in training time. © 2010 Springer-Verlag.

Spatial load forecasting using a demand propagation approach

A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance. © 2011 IEEE.

Improving accuracy and speed of optimum-path forest classifier using combination of disjoint training subsets

The Optimum-Path Forest (OPF) classifier is a recent and promising method for pattern recognition, with a fast training algorithm and good accuracy results. Therefore, the investigation of a combining method for this kind of classifier can be important for many applications. In this paper we report a fast method to combine OPF-based classifiers trained with disjoint training subsets. Given a fixed number of subsets, the algorithm chooses random samples, without replacement, from the original training set. Each subset accuracy is improved by a learning procedure. The final decision is given by majority vote. Experiments with simulated and real data sets showed that the proposed combining method is more efficient and effective than naive approach provided some conditions. It was also showed that OPF training step runs faster for a series of small subsets than for the whole training set. The combining scheme was also designed to support parallel or distributed processing, speeding up the procedure even more. © 2011 Springer-Verlag.

Preprocessing data for short-term load forecasting with a general regression neural network and a moving average filter

This paper proposes a filter based on a general regression neural network and a moving average filter, for preprocessing half-hourly load data for short-term multinodal load forecasting, discussed in another paper. Tests made with half-hourly load data from nine New Zealand electrical substations demonstrate that this filter is able to handle noise, missing data and abnormal data. © 2011 IEEE.

Short-term multinodal load forecasting in distribution systems using general regression neural networks

Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, trustable and has a short-time processing. This paper proposes two methodologies based on general regression neural networks for short-term multinodal load forecasting. The first individually forecast the local loads and the second forecast the global load and individually forecast the load participation factors to estimate the local loads. To design the forecasters it wasn't necessary the previous study of the local loads. Tests were made using a New Zealand distribution subsystem and the results obtained are compatible with the ones founded in the specialized literature. © 2011 IEEE.

The accuracy potential of Galileo E5/E1 pseudoranges for surveying and mapping

In the paper we discuss the potential of the new Galileo signals for pseudorange based surveying and mapping in open areas under optimal reception conditions (open sky scenarios) and suboptimal ones (multipath created by moderate to thick tree coverage). The paper reviews the main features of the Galileo E5 AltBOC and E1 CBOC signals; describes the simulation strategy, models and algorithms to generate realistic E5 and E1 pseudoranges with and without multipath sources; describes the ionosphere modeling strategy, models and algorithms and discusses and presents the expected positioning accuracy and precision results. According to the simulations performed, pseudoranges can be extracted from the Galileo E5 AltBOC signals with tracking errors (1-σ level) ranging from 0.02 m (open sky scenarios) to 0.08 m (tree covered scenarios) whereas for the Galileo E1 CBOC signals the tracking errors range between 0.25 m to 2.00 m respectively. With these tracking errors and with the explicit estimation of the ionosphere parameters, simulations indicate real-time open sky cm-level horizontal positioning precisions and dm-level vertical ones and dm-level accuracies for both the horizontal and vertical position components.

Avaliação dos dados decendiais de precipitação e temperatura máxima e mínima do ar simulados pelo modelo ECMWF para o estado de São Paulo

The weather and climate has a direct influence in agriculture, it affects all stages of farming, since soil preparation to harvest. Meteorological data derived from automatic or conventional weather stations are used to monitor these effects. These meteorological data has problems like difficulty of data access and low density of meteorological stations in Brazil. Meteorological data from atmospheric models, such as ECMWF (European Center for Medium-Range Weather Forecast) can be an alternative. Thus, the aim of this study was to compare 10-day period precipitation, maximum and minimum air temperature data from the ECMWF model with interpolated maps from 33 weather stations in Sao Paulo state between 2005 and 2010 and generate statistical maps pixel by pixel. Statistical index showed spatially satisfactory (most of the results with R 2 > 0.60, d > 0.7, RMSE < 5°C and < 50 mm; Es < 5°C and < 24 mm) in period and ECMWF model can be recommended for use in the Sao Paulo state.

Tooth embedding medium influences the accuracy of electronic apex locator

This study evaluated the influence of tooth embedding media on the accuracy ofan electronic apex locator. The root canal length of 20 human mandibular canines was measured by inserting a 15 K-file into the root canal up to the apical foramen. The distance was measured with a digital caliper. The embedding media evaluated were alginate, saline, floral foam or gauze soaked in saline. Electronic root canal length measurement was performed with Root ZX II. Data were analysed using ANOVA for repeated measurements and Tukey test, at a significance level of 5%. There was no difference between the actual root canal length measurement and the electronic reading recorded with alginate medium. The readings obtained with the other media differed from the actual root canal length measurements. Alginate provided greater accuracy in electronic root canal length determination by Root ZX II than saline, floral foam and gauze.