Tax simulation in the SHP

This paper describes a simulation package designed to estimate the annual income taxes paid by respondents of the Swiss Household Panel (SHP). In Switzerland, the 26 cantons have their own tax system. Additionally, tax levels vary between the over 2000 municipalities and over time. The simulation package takes account of this complexity by building on existing tables on tax levels which are provided by the Swiss Federal Tax Administration Office. Because these are limited to a few types of households and only 812 municipalities, they have to be extended to cover all households and municipalities. A further drawback of these tables is that they neglect several deductions. The tax simulation package fills this gap by taking additionally account of deductions for children, double-earner couples, third pillar and support for dependent persons according to cantonal legislation. The resulting variable on direct taxes not only serves to calculate household income net of taxes, but can also be a variable for analysis by its own account.

A data-dependent skeleton estimate and a scale-sensitive dimension for classification

The classical binary classification problem is investigatedwhen it is known in advance that the posterior probability function(or regression function) belongs to some class of functions. We introduceand analyze a method which effectively exploits this knowledge. The methodis based on minimizing the empirical risk over a carefully selected``skeleton'' of the class of regression functions. The skeleton is acovering of the class based on a data--dependent metric, especiallyfitted for classification. A new scale--sensitive dimension isintroduced which is more useful for the studied classification problemthan other, previously defined, dimension measures. This fact isdemonstrated by performance bounds for the skeleton estimate in termsof the new dimension.

Random measurement error and regression dilution bias.

Summary points: - The bias introduced by random measurement error will be different depending on whether the error is in an exposure variable (risk factor) or outcome variable (disease) - Random measurement error in an exposure variable will bias the estimates of regression slope coefficients towards the null - Random measurement error in an outcome variable will instead increase the standard error of the estimates and widen the corresponding confidence intervals, making results less likely to be statistically significant - Increasing sample size will help minimise the impact of measurement error in an outcome variable but will only make estimates more precisely wrong when the error is in an exposure variable

Application of real-time PCR for total airborne bacterial assessment : comparison with epifluorescence microscopy and culture-dependent methods

Traditional culture-dependent methods to quantify and identify airborne microorganisms are limited by factors such as short-duration sampling times and inability to count nonculturableor non-viable bacteria. Consequently, the quantitative assessment of bioaerosols is often underestimated. Use of the real-time quantitative polymerase chain reaction (Q-PCR) to quantify bacteria in environmental samples presents an alternative method, which should overcome this problem. The aim of this study was to evaluate the performance of a real-time Q-PCR assay as a simple and reliable way to quantify the airborne bacterial load within poultry houses and sewage treatment plants, in comparison with epifluorescencemicroscopy and culture-dependent methods. The estimates of bacterial load that we obtained from real-time PCR and epifluorescence methods, are comparable, however, our analysis of sewage treatment plants indicate these methods give values 270-290 fold greater than those obtained by the ''impaction on nutrient agar'' method. The culture-dependent method of air impaction on nutrient agar was also inadequate in poultry houses, as was the impinger-culture method, which gave a bacterial load estimate 32-fold lower than obtained by Q-PCR. Real-time quantitative PCR thus proves to be a reliable, discerning, and simple method that could be used to estimate airborne bacterial load in a broad variety of other environments expected to carry high numbers of airborne bacteria. [Authors]

Limited heterogeneity of autoantigens and T cells in autoimmune diseases?

For many induced and spontaneous autoimmune diseases, a predominant role for T cells in the organ-specific destruction process has been shown. In one of the induced models of autoimmunity, experimental allergic encephalomyelitis (EAE), a very small heterogeneity of T-cell receptor (TcR) molecules is expressed by the pathogenic T cells in both rats and mice. Contrary to induced autoimmune diseases, little is known about the autoantigens recognized by these autoimmune T cells and the heterogeneity of their TcR in spontaneous autoimmune diseases. The aim of this work was to establish a system which allows characterization of relevant autoantigens in spontaneous insulin-dependent diabetes mellitus (IDDM) in non-obese diabetic (NOD) mice. A completely different approach was taken to characterize the gene products of the minor lymphocyte stimulatory (Mls) loci. These gene products are responsible for the clonal elimination or the clonal stimulation of T cells expressing particular TcR V beta genes and therefore could be implicated in induction of autoimmune diseases by oligoclonal T-cell populations. The finding that Mls antigens are encoded by retroviral sequences leads to the hypothesis that viruses could be the inducing agents of autoimmune diseases.

What is the influence of vaccination's routes on the regression of tumors located at mucosal sites?

Tumor-regressions following tumor-associated-antigen vaccination in animal models contrast with the limited clinical outcomes in cancer patients. Most animal studies however used subcutaneous-tumor-models and questions arise as whether these are relevant for tumors growing in mucosae; whether specific mucosal-homing instructions are required; and how this may be influenced by the tumor.

Bystander-Activated Memory CD8 T Cells Control Early Pathogen Load in an Innate-like, NKG2D-Dependent Manner.

During an infection the antigen-nonspecific memory CD8 T cell compartment is not simply an inert pool of cells, but becomes activated and cytotoxic. It is unknown how these cells contribute to the clearance of an infection. We measured the strength of T cell receptor (TCR) signals that bystander-activated, cytotoxic CD8 T cells (BA-CTLs) receive in vivo and found evidence of limited TCR signaling. Given this marginal contribution of the TCR, we asked how BA-CTLs identify infected target cells. We show that target cells express NKG2D ligands following bacterial infection and demonstrate that BA-CTLs directly eliminate these target cells in an innate-like, NKG2D-dependent manner. Selective inhibition of BA-CTL-mediated killing led to a significant defect in pathogen clearance. Together, these data suggest an innate role for memory CD8 T cells in the early immune response before the onset of a de novo generated, antigen-specific CD8 T cell response.

Quantification of permanent and variable charges in reference soils of the State of Pernambuco, Brazil

The electrical charges in soil particles are divided into structural or permanent charges and variable charges. Permanent charges develop on the soil particle surface by isomorphic substitution. Variable charges arise from dissociation and association of protons (H+), protonation or deprotonation, and specific adsorption of cations and anions. The aim of this study was to quantify the permanent charges and variable charges of Reference Soils of the State of Pernambuco, Brazil. To do so, 24 subsurface profiles from different regions (nine in the Zona da Mata, eight in the Agreste, and seven in the Sertão) were sampled, representing approximately 80 % of the total area of the state. Measurements were performed using cesium chloride solution. Determination was made of the permanent charges and the charges in regard to the hydroxyl functional groups through selective ion exchange of Cs+ by Li+ and Cs+ by NH4+, respectively. All the soils analyzed exhibited variable cation exchange capacity, with proportions from 0.16 to 0.60 and an average of 0.40 when related to total cation exchange capacity.

Multitask learning of environmental spatial data

The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

Water-Stable Aggregates and Associated Carbon in a Subtropical Rice Soil Under Variable Tillage

ABSTRACT Tillage systems can influence C sequestration by changing aggregate formation and C distribution within the aggregate. This study was undertaken to explore the impact of no-tillage without straw (NT-S) and with straw (NT+S), and moldboard plow without straw (MP-S) and with straw (MP+S), on soil aggregation and aggregate-associated C after six years of double rice planting in a Hydragric Anthrosol in Guangxi, southwest of China. Soil samples of 0.00-0.05, 0.05-0.20 and 0.20-0.30 m layers were wet-sieved and divided into four aggregate-size classes, >2 mm, 2.00-0.25 mm, 0.25-0.053 and <0.053 mm, respectively, for measuring aggregate associated C and humic and fulvic acids. Results showed that the soil organic carbon (SOC) stock in bulk soil was 40.2-51.1 % higher in the 0.00-0.05 m layer and 11.3-17.0 % lower in the 0.05-0.20 m layer in NT system (NT+S and NT-S) compared to the MP system (MP+S and MP-S), respectively. However, no statistical difference was found across the whole 0.00-0.30 m layer. The NT system increased the proportion of >2 mm aggregate fraction and reduced the proportion of <0.053 mm aggregates in both 0.00-0.05 and 0.05-0.20 m layers. The SOC concentration, SOC stock and humic and fulvic acids within the >0.25 mm macroaggregate fraction also significantly increased in the 0.00-0.5 m layer in NT system. However, those within the 2.00-0.25 mm aggregate fraction were significantly reduced in the 0.05-0.200 m layer under NT system. Straw incorporation increased not only the SOC stock in bulk soil, but also the proportion of macroaggregate, aggregate associated with SOC and humic and fulvic acids concentration within the aggregate. The effect of straw on C sequestration might be dependent on the location of straw incorporation. In conclusion, the NT system increased the total SOC accumulation and humic and fulvic acids within macroaggregates, thus contributing to C sequestration in the 0.00-0.05 m layer.

Quality of life depends on the drinking pattern in alcohol-dependent patients.

AIMS: In patients with alcohol dependence, health-related quality of life (QOL) is reduced compared with that of a normal healthy population. The objective of the current analysis was to describe the evolution of health-related QOL in adults with alcohol dependence during a 24-month period after initial assessment for alcohol-related treatment in a routine practice setting, and its relation to drinking pattern which was evaluated across clusters based on the predominant pattern of alcohol use, set against the influence of baseline variables METHODS: The Medical Outcomes Study 36-Item Short-Form Survey (MOS-SF-36) was used to measure QOL at baseline and quarterly for 2 years among participants in CONTROL, a prospective observational study of patients initiating treatment for alcohol dependence. The sample consisted of 160 adults with alcohol dependence (65.6% males) with a mean (SD) age of 45.6 (12.0) years. Alcohol use data were collected using TimeLine Follow-Back. Based on the participant's reported alcohol use, three clusters were identified: 52 (32.5%) mostly abstainers, 64 (40.0%) mostly moderate drinkers and 44 (27.5%) mostly heavy drinkers. Mixed-effect linear regression analysis was used to identify factors that were potentially associated with the mental and physical summary MOS-SF-36 scores at each time point. RESULTS: The mean (SD) MOS-SF-36 mental component summary score (range 0-100, norm 50) was 35.7 (13.6) at baseline [mostly abstainers: 40.4 (14.6); mostly moderate drinkers 35.6 (12.4); mostly heavy drinkers 30.1 (12.1)]. The score improved to 43.1 (13.4) at 3 months [mostly abstainers: 47.4 (12.3); mostly moderate drinkers 44.2 (12.7); mostly heavy drinkers 35.1 (12.9)], to 47.3 (11.4) at 12 months [mostly abstainers: 51.7 (9.7); mostly moderate drinkers 44.8 (11.9); mostly heavy drinkers 44.1 (11.3)], and to 46.6 (11.1) at 24 months [mostly abstainers: 49.2 (11.6); mostly moderate drinkers 45.7 (11.9); mostly heavy drinkers 43.7 (8.8)]. Mixed-effect linear regression multivariate analyses indicated that there was a significant association between a lower 2-year follow-up MOS-SF-36 mental score and being a mostly heavy drinker (-6.97, P < 0.001) or mostly moderate drinker (-3.34 points, P = 0.018) [compared to mostly abstainers], being female (-3.73, P = 0.004), and having a Beck Inventory scale score ≥8 (-6.54, P < 0.001), at baseline. The mean (SD) MOS-SF-36 physical component summary score was 48.8 (10.6) at baseline, remained stable over the follow-up and did not differ across the three clusters. Mixed-effect linear regression univariate analyses found that the average 2-year follow-up MOS-SF-36 physical score was increased (compared with mostly abstainers) in mostly heavy drinkers (+4.44, P = 0.007); no other variables tested influenced the MOS-SF-36 physical score. CONCLUSION: Among individuals with alcohol dependence, a rapid improvement was seen in the mental dimension of QOL following treatment initiation, which was maintained during 24 months. Improvement was associated with the pattern of alcohol use, becoming close to the general population norm in patients classified as mostly abstainers, improving substantially in mostly moderate drinkers and improving only slightly in mostly heavy drinkers. The physical dimension of QOL was generally in the normal range but was not associated with drinking patterns.

Drinking Patterns and Their Predictive Factors in CONTROL: a 12-Month Prospective Study in a Sample of Alcohol-Dependent Patients Initiating Treatment.

Aims: To describe the drinking patterns and their baseline predictive factors during a 12-month period after an initial evaluation for alcohol treatment. Methods CONTROL is a single-center, prospective, observational study evaluating consecutive alcohol-dependent patients. Using a curve clustering methodology based on a polynomial regression mixture model, we identified three clusters of patients with dominant alcohol use patterns described as mostly abstainers, mostly moderate drinkers and mostly heavy drinkers. Multinomial logistic regression analysis was used to identify baseline factors (socio-demographic, alcohol dependence consequences and related factors) predictive of belonging to each drinking cluster. ResultsThe sample included 143 alcohol-dependent adults (63.6% males), mean age 44.6 ± 11.8 years. The clustering method identified 47 (32.9%) mostly abstainers, 56 (39.2%) mostly moderate drinkers and 40 (28.0%) mostly heavy drinkers. Multivariate analyses indicated that mild or severe depression at baseline predicted belonging to the mostly moderate drinkers cluster during follow-up (relative risk ratio (RRR) 2.42, CI [1.02-5.73, P = 0.045] P = 0.045), while living alone (RRR 2.78, CI [1.03-7.50], P = 0.044) and reporting more alcohol-related consequences (RRR 1.03, CI [1.01-1.05], P = 0.004) predicted belonging to the mostly heavy drinkers cluster during follow-up. Conclusion In this sample, the drinking patterns of alcohol-dependent patients were predicted by baseline factors, i.e. depression, living alone or alcohol-related consequences and findings that may inform clinicians about the likely drinking patterns of their alcohol-dependent patient over the year following the initial evaluation for alcohol treatment.

Methods for Determining Frequency- and Region-Dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

The relationship between electrophysiological and functional magnetic resonance imaging (fMRI) signals remains poorly understood. To date, studies have required invasive methods and have been limited to single functional regions and thus cannot account for possible variations across brain regions. Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0-256 Hz) throughout the entire brain volume. This method was applied in a study where human subjects completed separate fMRI and EEG sessions while performing a passive visual task. Intracranial LFPs were estimated from the scalp-recorded data using the ELECTRA source model. We compared statistical images from BOLD signals with statistical images of each frequency of the eLFPs. In agreement with previous studies in animals, we found a significant correspondence between LFP and BOLD statistical images in the gamma band (44-78 Hz) within primary visual cortices. In addition, significant correspondence was observed at low frequencies (<14 Hz) and also at very high frequencies (>100 Hz). Effects within extrastriate visual areas showed a different correspondence that not only included those frequency ranges observed in primary cortices but also additional frequencies. Results therefore suggest that the relationship between electrophysiological and hemodynamic signals thus might vary both as a function of frequency and anatomical region.

Estimating Design-Flood Discharges for Streams in Iowa Using Drainage-Basin and Channel-Geometry Characteristics, HR-322, 1993

Drainage-basin and channel-geometry multiple-regression equations are presented for estimating design-flood discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at stream sites on rural, unregulated streams in Iowa. Design-flood discharge estimates determined by Pearson Type-III analyses using data collected through the 1990 water year are reported for the 188 streamflow-gaging stations used in either the drainage-basin or channel-geometry regression analyses. Ordinary least-squares multiple-regression techniques were used to identify selected drainage-basin and channel-geometry regions. Weighted least-squares multiple-regression techniques, which account for differences in the variance of flows at different gaging stations and for variable lengths in station records, were used to estimate the regression parameters. Statewide drainage-basin equations were developed from analyses of 164 streamflow-gaging stations. Drainage-basin characteristics were quantified using a geographic-information-system (GIS) procedure to process topographic maps and digital cartographic data. The significant characteristics identified for the drainage-basin equations included contributing drainage area, relative relief, drainage frequency, and 2-year, 24-hour precipitation intensity. The average standard errors of prediction for the drainage-basin equations ranged from 38.6% to 50.2%. The GIS procedure expanded the capability to quantitatively relate drainage-basin characteristics to the magnitude and frequency of floods for stream sites in Iowa and provides a flood-estimation method that is independent of hydrologic regionalization. Statewide and regional channel-geometry regression equations were developed from analyses of 157 streamflow-gaging stations. Channel-geometry characteristics were measured on site and on topographic maps. Statewide and regional channel-geometry regression equations that are dependent on whether a stream has been channelized were developed on the basis of bankfull and active-channel characteristics. The significant channel-geometry characteristics identified for the statewide and regional regression equations included bankfull width and bankfull depth for natural channels unaffected by channelization, and active-channel width for stabilized channels affected by channelization. The average standard errors of prediction ranged from 41.0% to 68.4% for the statewide channel-geometry equations and from 30.3% to 70.0% for the regional channel-geometry equations. Procedures provided for applying the drainage-basin and channel-geometry regression equations depend on whether the design-flood discharge estimate is for a site on an ungaged stream, an ungaged site on a gaged stream, or a gaged site. When both a drainage-basin and a channel-geometry regression-equation estimate are available for a stream site, a procedure is presented for determining a weighted average of the two flood estimates.

Surgical safety and hospital volume across a wide range of interventions

OBJECTIVES:: For certain major operations, inpatient mortality risk is lower in high-volume hospitals than those in low-volume hospitals. Extending the analysis to a broader range of interventions and outcomes is necessary before adopting policies based on minimum volume thresholds. METHODS:: Using the United States 2004 Nationwide Inpatient Sample, we assessed the effect of intervention-specific and overall hospital volume on surgical complications, potentially avoidable reoperations, and deaths across 1.4 million interventions in 353 hospitals. Outcome variations across hospitals were analyzed through a 3-level hierarchical logistic regression model (patients, surgical interventions, and hospitals), which took into account interventions on multiple organs, 144 intervention categories, and structural hospital characteristics. Discriminative performance and calibration were good. RESULTS:: Hospitals with more experience in a given intervention had similar reoperation rates but lower mortality and complication rates: odds ratio per volume deciles 0.93 and 0.97. However, the benefit was limited to heart surgery and a small number of other operations. Risks were higher for hospitals that performed more interventions overall: odds ratio per 1000 for each event was approximately 1.02. Even after adjustment for specific volume, mortality varied substantially across both high- and low-volume hospitals. CONCLUSION:: Although the link between specific volume and certain inpatient outcomes suggests that specialization might help improve surgical safety, the variable magnitude of this link and the heterogeneity of hospital effect do not support the systematic use of volume-based referrals. It may be more efficient to monitor risk-adjusted postoperative outcomes and to investigate facilities with worse than expected outcomes.