Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Cardiac motion estimation by joint alignment of tagged MRI sequences

Image registration has been proposed as an automatic method for recovering cardiac displacement fields from Tagged Magnetic Resonance Imaging (tMRI) sequences. Initially performed as a set of pairwise registrations, these techniques have evolved to the use of 3D+t deformation models, requiring metrics of joint image alignment (JA). However, only linear combinations of cost functions defined with respect to the first frame have been used. In this paper, we have applied k-Nearest Neighbors Graphs (kNNG) estimators of the -entropy (H ) to measure the joint similarity between frames, and to combine the information provided by different cardiac views in an unified metric. Experiments performed on six subjects showed a significantly higher accuracy (p < 0.05) with respect to a standard pairwise alignment (PA) approach in terms of mean positional error and variance with respect to manually placed landmarks. The developed method was used to study strains in patients with myocardial infarction, showing a consistency between strain, infarction location, and coronary occlusion. This paper also presentsan interesting clinical application of graph-based metric estimators, showing their value for solving practical problems found in medical imaging.

Active deformation fields: dense deformation field estimation for atlas-based segmentation using the active contour framework.

This paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and encompasses many of the state-of-the-art atlas-based segmentation methods. It also allows to perform the registration of atlas and target images based on only selected structures of interest. The versatility and potentiality of the proposed framework are demonstrated by presenting three diverse applications: In the first application, we show how the proposed framework can be used to simulate the growth of inconsistent structures like a tumor in an atlas. In the second application, we estimate the position of nonvisible brain structures based on the surrounding structures and validate the results by comparing with other methods. In the final application, we present the segmentation of lymph nodes in the Head and Neck CT images, and demonstrate how multiple registration forces can be used in this framework in an hierarchical manner.

Grade and Cross Slope Estimation from LIDAR-based Surface Models, 2003

Many transportation agencies maintain grade as an attribute in roadway inventory databases; however, the information is often in an aggregated format. Cross slope is rarely included in large roadway inventories. Accurate methods available to collect grade and cross slope include global positioning systems, traditional surveying, and mobile mapping systems. However, most agencies do not have the resources to utilize these methods to collect grade and cross slope on a large scale. This report discusses the use of LIDAR to extract roadway grade and cross slope for large-scale inventories. Current data collection methods and their advantages and disadvantages are discussed. A pilot study to extract grade and cross slope from a LIDAR data set, including methodology, results, and conclusions, is presented. This report describes the regression methodology used to extract and evaluate the accuracy of grade and cross slope from three dimensional surfaces created from LIDAR data. The use of LIDAR data to extract grade and cross slope on tangent highway segments was evaluated and compared against grade and cross slope collected using an automatic level for 10 test segments along Iowa Highway 1. Grade and cross slope were measured from a surface model created from LIDAR data points collected for the study area. While grade could be estimated to within 1%, study results indicate that cross slope cannot practically be estimated using a LIDAR derived surface model.

Estimation of forest canopy cover : a comparison of field measurement techniques

Abstract

Effects of computing parameters and measurement locations on the estimation of 3D NPS in non-stationary MDCT images.

The goal of this study was to investigate the impact of computing parameters and the location of volumes of interest (VOI) on the calculation of 3D noise power spectrum (NPS) in order to determine an optimal set of computing parameters and propose a robust method for evaluating the noise properties of imaging systems. Noise stationarity in noise volumes acquired with a water phantom on a 128-MDCT and a 320-MDCT scanner were analyzed in the spatial domain in order to define locally stationary VOIs. The influence of the computing parameters in the 3D NPS measurement: the sampling distances bx,y,z and the VOI lengths Lx,y,z, the number of VOIs NVOI and the structured noise were investigated to minimize measurement errors. The effect of the VOI locations on the NPS was also investigated. Results showed that the noise (standard deviation) varies more in the r-direction (phantom radius) than z-direction plane. A 25 × 25 × 40 mm(3) VOI associated with DFOV = 200 mm (Lx,y,z = 64, bx,y = 0.391 mm with 512 × 512 matrix) and a first-order detrending method to reduce structured noise led to an accurate NPS estimation. NPS estimated from off centered small VOIs had a directional dependency contrary to NPS obtained from large VOIs located in the center of the volume or from small VOIs located on a concentric circle. This showed that the VOI size and location play a major role in the determination of NPS when images are not stationary. This study emphasizes the need for consistent measurement methods to assess and compare image quality in CT.

Simultaneous determination of gross alpha, gross beta and Ra-226 in natural water by liquid scintillation counting.

The determination of gross alpha, gross beta and 226Ra activity in natural waters is useful in a wide range of environmental studies. Furthermore, gross alpha and gross beta parameters are included in international legislation on the quality of drinking water [Council Directive 98/83/EC].1 In this work, a low-background liquid scintillation counter (Wallac, Quantulus 1220) was used to simultaneously determine gross alpha, gross beta and 226Ra activity in natural water samples. Sample preparation involved evaporation to remove 222Rn and its short-lived decay daughters. The evaporation process concentrated the sample ten-fold. Afterwards, a sample aliquot of 8 mL was mixed with 12 mL of Ultima Gold AB scintillation cocktail in low-diffusion vials. In this study, a theoretical mathematical model based on secular equilibrium conditions between 226Ra and its short-lived decay daughters is presented. The proposed model makes it possible to determine 226Ra activity from two measurements. These measurements also allow determining gross alpha and gross beta simultaneously. To validate the proposed model, spiked samples with different activity levels for each parameter were analysed. Additionally, to evaluate the model's applicability in natural water, eight natural water samples from different parts of Spain were analysed. The eight natural water samples were also characterised by alpha spectrometry for the naturally occurring isotopes of uranium (234U, 235U and 238U), radium (224Ra and 226Ra), 210Po and 232Th. The results for gross alpha and 226Ra activity were compared with alpha spectrometry characterization, and an acceptable concordance was obtained.

On-line desorption of dried blood spots coupled to hydrophilic interaction/reversed-phase LC/MS/MS system for the simultaneous analysis of drugs and their polar metabolites.

An assay for the simultaneous analysis of pharmaceutical compounds and their metabolites from micro-whole blood samples (i.e. 5 microL) was developed using an on-line dried blood spot (on-line DBS) device coupled with hydrophilic interaction/reversed-phase (HILIC/RP) LC/MS/MS. Filter paper is directly integrated to the LC device using a homemade inox desorption cell. Without any sample pretreatment, analytes are desorbed from the paper towards an automated system of valves linking a zwitterionic-HILIC column to an RP C18 column. In the same run, the polar fraction is separated by the zwitterionic-HILIC column while the non-polar fraction is eluted on the RP C18. Both fractions are detected by IT-MS operating in full scan mode for the survey scan and in product ion mode for the dependant scan using an ESI source. The procedure was evaluated by the simultaneous qualitative analysis of four probes and their relative phase I and II metabolites spiked in whole blood. In addition, the method was successfully applied to the in vivo monitoring of buprenorphine metabolism after the administration of an intraperitoneal injection of 30 mg/kg on adult female Wistar rat.

Simultaneous determination of human plasma levels of citalopram, paroxetine, sertraline, and their metabolites by gas chromatography-mass spectrometry.

A gas chromatography-mass spectrometry method is presented which allows the simultaneous determination of the plasma concentrations of the selective serotonin reuptake inhibitors citalopram, paroxetine, sertraline, and their pharmacologically active N-demethylated metabolites (desmethylcitalopram, didesmethylcitalopram, and desmethylsertraline) after derivatization with the reagent N-methyl-bis(trifluoroacetamide). No interferences from endogenous compounds are observed following the extraction of plasma samples from six different human subjects. The standard curves are linear over a working range of 10-500 ng/mL for citalopram, 10-300 ng/mL for desmethylcitalopram, 5-60 ng/mL for didesmethylcitalopram, 20-400 ng/mL for sertraline and desmethylsertraline, and 10-200 ng/mL for paroxetine. Recoveries measured at three concentrations range from 81 to 118% for the tertiary amines (citalopram and the internal standard methylmaprotiline), 73 to 95% for the secondary amines (desmethylcitalopram, paroxetine and sertraline), and 39 to 66% for the primary amines (didesmethylcitalopram and desmethylsertraline). Intra- and interday coefficients of variation determined at three concentrations range from 3 to 11% for citalopram and its metabolites, 4 to 15% for paroxetine, and 5 to 13% for sertraline and desmethylsertraline. The limits of quantitation of the method are 2 ng/mL for citalopram and paroxetine, 1 ng/mL for sertraline, and 0.5 ng/mL for desmethylcitalopram, didesmethylcitalopram, and desmethylsertraline. No interferences are noted from 20 other psychotropic drugs. This sensitive and specific method can be used for single-dose pharmacokinetics. It is also useful for therapeutic drug monitoring of these three drugs and could possibly be adapted for the quantitation of the two other selective serotonin reuptake inhibitors on the market, namely fluoxetine and fluvoxamine.

Equilibrium of the simultaneous etherification ofisobutene and isoamylenes with ethanol inliquid-phase

The simultaneous etherification of isobutene and isoamylenes with ethanol has been studied using macroreticu-lar acid ion-exchange resins as catalyst. Most of the experiments were carried out over Amberlyst-35. In addition,Amberlyst-15 and Purolite CT-275 were also tested. Chemical equilibrium of four chemical reactions was studied:ethyl tert-butyl ether formation, tert-amyl ethyl ether formation from isoamylenes (2-methyl-1-butene and 2-methyl-2-butene) and isomerization reaction between both isoamylenes. Equilibrium data were obtained in a batchwisestirred tank reactor operated at 2.0 MPa and within the temperature range from 323 to 353 K. Experimental molarstandard enthalpy and entropy changes of reaction were determined for each reaction. From these data, the molarenthalpy change of formation of ethyl tert-butyl ether and tert-amyl ethyl ether were estimated. Besides, the chemical equilibrium between both diisobutene dimers, 2,4,4-trimethyl-1-pentene and 2,4,4-trimethyl-2-pentene, wasevaluated. A good agreement between thermodynamic results for the simultaneous etherification carried out in thiswork and those obtained for the isolated ethyl tert-butyl ether and tert-amyl ethyl ether systems was obtained.

Soybean crop area estimation by Modis/Evi data

The objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatística. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics.

Stratified estimation of forest inventory variables using spatially summarized stratifications

Abstract