ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r(2), intercept and slope. Second, the two models' assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS- and RIVPACS-type models, if not to replace them.

Longitudinal Follow-Up of Bipolar Disorder in Women With Premenstrual Exacerbation: Findings From STEP-BD

Objective: The impact of hormonal fluctuation during the menstrual cycle on the course of bipolar disorder is poorly understood. The authors determined the course of illness and time to relapse of bipolar disorder in prospectively followed women with premenstrual exacerbation. Method: Participants were 293 premenopause-age women with bipolar disorder who were followed prospectively for 1 year as part of the Systematic Treatment Enhancement Program for Bipolar Disorder. Frequency of mood episodes was compared between 191 women with premenstrual exacerbation (65.2%) and 102 women without. Among 129 women who were in recovered status at baseline, time to relapse was compared between 66 women with premenstrual exacerbation (51.2%) and 63 without. Results: During follow-up, the group with premenstrual exacerbation had more episodes (primarily depressive) than did the group without, but they were not more likely to meet criteria for rapid cycling during this period. In contrast, they were more likely to report rapid cycling retrospectively. Women with premenstrual exacerbation had a shorter time to relapse and were at greater risk for relapse, but this association was not significant after adjustment for retrospectively reported rapid cycling. Women with premenstrual exacerbation had more depressive and mood elevation symptoms overall. Conclusions: Women with bipolar disorder and premenstrual exacerbation have a worse course of illness, a shorter time to relapse, and greater symptom severity, but they are not more likely to meet criteria for rapid cycling. Premenstrual exacerbation may be a clinical marker predicting a more symptomatic and relapse-prone phenotype in reproductive-age women with bipolar disorder.

A method for better positioning bipolar electrodes for lower limb EMG recordings during dynamic contractions

To obtain a high quality EMG acquisition, the signal must be recorded as far away as possible from muscle innervations and tendon zones, which are known to shift during dynamic contractions. This study describes a methodology, using commercial bipolar electrodes, to identify better electrode positions for superficial EMG of lower limb muscles during dynamic contractions. Eight female volunteers participated in this study. Myoelectric signals of the vastus lateralis, gastrocnemius medialis, peroneus longus and tibialis anterior muscles were acquired during maximum isometric contractions using bipolar electrodes. The electrode positions of each muscle were selected assessing SENIAM and then, other positions were located along the length of muscle up and down the SENIAM site. The raw signal (density), the linear envelopes, the RMS value, the motor point site, the position of the IZ and its shift during dynamic contractions were taken into account to select and compare electrode positions. For vastus lateralis and peroneus longus, the best sites were 66% and 25% of muscle length, respectively (similar to SENIAM location). The position of the tibialis anterior electrodes presented the best signal at 47.5% of its length (different from SENIAM location). The position of the gastrocnemius medialis electrodes was at 38% of its length and SENIAM does not specify a precise location for signal acquisition. The proposed method should be considered as another methodological step in every EMG study to guarantee the quality of the signal and subsequent human movement interpretations. (C) 2009 Elsevier B.V. All rights reserved.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Validation of ACB in vitro and in vivo as a biomagnetic method for measuring stomach contraction

Background The aim of this study was to validate a biomagnetic method (alternate current biosusceptometry, ACB) for monitoring gastric wall contractions in rats. Methods In vitro data were obtained to establish the relationship between ACB and the strain-gauge (SG) signal amplitude. In vivo experiments were performed in pentobarbital-anesthetized rats with SG and magnetic markers previously implanted under the gastric serosa or after ingestion of magnetic material. Gastric motility was quantified from the tracing amplitudes and frequency profiles obtained by Fast Fourier Transform. Key Results The correlation between in vitro signal amplitudes was strong (R = 0.989). The temporal cross-correlation coefficient between the ACB and SG signal amplitude was higher (P < 0.0001) in the postprandial (88.3 +/- 9.1 V) than in the fasting state (31.0 +/- 16.9 V). Irregular signal profiles, low contraction amplitudes, and smaller signal-to-noise ratios explained the poor correlation between techniques for fasting-state recordings. When a magnetic material was ingested, there was also strong correlation in the frequency and signal amplitude and a small phase-difference between the techniques. The contraction frequencies using ACB were 0.068 +/- 0.007 Hz (postprandial) and 0.058 +/- 0.007 Hz (fasting) (P < 0.002) and those using SG were 0.066 +/- 0.006 Hz (postprandial) and 0.059 +/- 0.008 Hz (fasting) (P < 0.005). Conclusions & Inferences In summary, ACB is reliable for monitoring gastric wall contractions using both implanted and ingested magnetic materials, and may serve as an accurate and sensitive technique for gastrointestinal motility studies.

The composite Euler method for stiff stochastic differential equations

In this paper we present the composite Euler method for the strong solution of stochastic differential equations driven by d-dimensional Wiener processes. This method is a combination of the semi-implicit Euler method and the implicit Euler method. At each step either the semi-implicit Euler method or the implicit Euler method is used in order to obtain better stability properties. We give criteria for selecting the semi-implicit Euler method or the implicit Euler method. For the linear test equation, the convergence properties of the composite Euler method depend on the criteria for selecting the methods. Numerical results suggest that the convergence properties of the composite Euler method applied to nonlinear SDEs is the same as those applied to linear equations. The stability properties of the composite Euler method are shown to be far superior to those of the Euler methods, and numerical results show that the composite Euler method is a very promising method. (C) 2001 Elsevier Science B.V. All rights reserved.

Patient based method of assessing adverse events in clinical trials in rheumatology: the revised Stanford Toxicity Index

We describe the progress towards developing a patient rated toxicity index that meets all of the patient-important attributes defined by the OMERACT Drug Safety Working Party, These attributes are frequency, severity. importance to patient, importance to the clinician, impact on economics, impact on activities, and integration of adverse effects with benefits. The Stanford Toxicity Index (STI) has been revised to collect all attributes with the exception of impact on activities. However, since the STI is a part of the Health Assessment Questionnaire (HAQ). impact on activities is collected by the HAQ. In particular, a new question asks patients to rate overall satisfaction, taking into consideration both benefits and adverse effects. The nest step in the development of this tool is to ensure that the STI meets the OMERACT filter of truth, discrimination, and feasibility. Although truth and feasibility have been confirmed by comparisons within the ARAMIS database, discrimination needs to be assessed in clinical trials.

The reliability of immunohistochemistry as a prescreening method for the diagnosis of hereditary nonpolyposis colorectal cancer (HNPCC) - Results of an international collaborative study

Hereditary nonpolyposis colorectal cancer syndrome (HNPCC) is an autosomal dominant condition accounting for 2–5% of all colorectal carcinomas as well as a small subset of endometrial, upper urinary tract and other gastrointestinal cancers. An assay to detect the underlying defect in HNPCC, inactivation of a DNA mismatch repair enzyme, would be useful in identifying HNPCC probands. Monoclonal antibodies against hMLH1 and hMSH2, two DNA mismatch repair proteins which account for most HNPCC cancers, are commercially available. This study sought to investigate the potential utility of these antibodies in determining the expression status of these proteins in paraffin-embedded formalin-fixed tissue and to identify key technical protocol components associated with successful staining. A set of 20 colorectal carcinoma cases of known hMLH1 and hMSH2 mutation and expression status underwent immunoperoxidase staining at multiple institutions, each of which used their own technical protocol. Staining for hMSH2 was successful in most laboratories while staining for hMLH1 proved problematic in multiple labs. However, a significant minority of laboratories demonstrated excellent results including high discriminatory power with both monoclonal antibodies. These laboratories appropriately identified hMLH1 or hMSH2 inactivation with high sensitivity and specificity. The key protocol point associated with successful staining was an antigen retrieval step involving heat treatment and either EDTA or citrate buffer. This study demonstrates the potential utility of immunohistochemistry in detecting HNPCC probands and identifies key technical components for successful staining.

A four-stage index 2 Diagonally Implicit Runge-Kutta method

High index Differential Algebraic Equations (DAEs) force standard numerical methods to lower order. Implicit Runge-Kutta methods such as RADAU5 handle high index problems but their fully implicit structure creates significant overhead costs for large problems. Singly Diagonally Implicit Runge-Kutta (SDIRK) methods offer lower costs for integration. This paper derives a four-stage, index 2 Explicit Singly Diagonally Implicit Runge-Kutta (ESDIRK) method. By introducing an explicit first stage, the method achieves second order stage calculations. After deriving and solving appropriate order conditions., numerical examples are used to test the proposed method using fixed and variable step size implementations. (C) 2001 IMACS. Published by Elsevier Science B.V. All rights reserved.

Adsorption in slit-like pores of activated carbons: Improvement of the Horvath and Kawazoe method

Anew thermodynamic approach has been developed in this paper to analyze adsorption in slitlike pores. The equilibrium is described by two thermodynamic conditions: the Helmholtz free energy must be minimal, and the grand potential functional at that minimum must be negative. This approach has led to local isotherms that describe adsorption in the form of a single layer or two layers near the pore walls. In narrow pores local isotherms have one step that could be either very sharp but continuous or discontinuous benchlike for a definite range of pore width. The latter reflects a so-called 0 --> 1 monolayer transition. In relatively wide pores, local isotherms have two steps, of which the first step corresponds to the appearance of two layers near the pore walls, while the second step corresponds to the filling of the space between these layers. All features of local isotherms are in agreement with the results obtained from the density functional theory and Monte Carlo simulations. The approach is used for determining pore size distributions of carbon materials. We illustrate this with the benzene adsorption data on activated carbon at 20, 50, and 80 degreesC, argon adsorption on activated carbon Norit ROX at 87.3 K, and nitrogen adsorption on activated carbon Norit R1 at 77.3 K.

An advanced method for eliminating impacts from frequency deviations in power system signal processing

Frequency deviation is a common problem for power system signal processing. Many power system measurements are carried out in a fixed sampling rate assuming the system operates in its nominal frequency (50 or 60 Hz). However, the actual frequency may deviate from the normal value from time to time due to various reasons such as disturbances and subsequent system transients. Measurement of signals based on a fixed sampling rate may introduce errors under such situations. In order to achieve high precision signal measurement appropriate algorithms need to be employed to reduce the impact from frequency deviation in the power system data acquisition process. This paper proposes an advanced algorithm to enhance Fourier transform for power system signal processing. The algorithm is able to effectively correct frequency deviation under fixed sampling rate. Accurate measurement of power system signals is essential for the secure and reliable operation of power systems. The algorithm is readily applicable to such occasions where signal processing is affected by frequency deviation. Both mathematical proof and numerical simulation are given in this paper to illustrate robustness and effectiveness of the proposed algorithm. Crown Copyright (C) 2003 Published by Elsevier Science B.V. All rights reserved.

Sustainable Tourism and Eradication of Poverty (Step): impact assessment of a tourism development program in Brazil

This paper aims to evaluate the social impacts of the Tourism Development Program (Prodetur) in the northeastern town of Porto Seguro, Bahia, Brazil. The method used is based on the difference in difference technique applied to the 1991 and 2000 Census microdata. The results suggest social advances following from poverty relief based on income - where the benefits are distributed, generally, in a relatively equal manner between the native and migrant population. There is a relative deterioration in the sanitary situation, which consists of a very serious problem in the mid- and long-term, whose costs are mostly borne by the native population. Therefore, maintaining the natural capital is the main aspect that distances Porto Seguro’s tourism supply from the concept of sustainability. The article also relies on difference in difference estimators to assess the impacts of local public policies related to the sector.

A DC-DC Step-Up mu-Power Converter for Energy Harvesting Applications, Using Maximum Power PointTracking, Based on Fractional Open Circuit Voltage

A DC-DC step-up micro power converter for solar energy harvesting applications is presented. The circuit is based on a switched-capacitorvoltage tripler architecture with MOSFET capacitors, which results in an, area approximately eight times smaller than using MiM capacitors for the 0.131mu m CMOS technology. In order to compensate for the loss of efficiency, due to the larger parasitic capacitances, a charge reutilization scheme is employed. The circuit is self-clocked, using a phase controller designed specifically to work with an amorphous silicon solar cell, in order to obtain themaximum available power from the cell. This will be done by tracking its maximum power point (MPPT) using the fractional open circuit voltage method. Electrical simulations of the circuit, together with an equivalent electrical model of an amorphous silicon solar cell, show that the circuit can deliver apower of 1132 mu W to the load, corresponding to a maximum efficiency of 66.81%.

The development and optimization of a modified single-drop microextraction method for organochlorine pesticides determination by gas chromatography-tandem mass spectrometry

We have developed a new method for single-drop microextraction (SDME) for the preconcentration of organochlorine pesticides (OCP) from complex matrices. It is based on the use of a silicone ring at the tip of the syringe. A 5 μL drop of n-hexane is applied to an aqueous extract containing the OCP and found to be adequate to preconcentrate the OCPs prior to analysis by GC in combination with tandem mass spectrometry. Fourteen OCP were determined using this technique in combination with programmable temperature vaporization. It is shown to have many advantages over traditional split/splitless injection. The effects of kind of organic solvent, exposure time, agitation and organic drop volume were optimized. Relative recoveries range from 59 to 117 %, with repeatabilities of <15 % (coefficient of variation) were achieved. The limits of detection range from 0.002 to 0.150 μg kg−1. The method was applied to the preconcentration of OCPs in fresh strawberry, strawberry jam, and soil.

FMRI 3D registration based on Fourier space subsets using neural networks

In this work, we present a neural network (NN) based method designed for 3D rigid-body registration of FMRI time series, which relies on a limited number of Fourier coefficients of the images to be aligned. These coefficients, which are comprised in a small cubic neighborhood located at the first octant of a 3D Fourier space (including the DC component), are then fed into six NN during the learning stage. Each NN yields the estimates of a registration parameter. The proposed method was assessed for 3D rigid-body transformations, using DC neighborhoods of different sizes. The mean absolute registration errors are of approximately 0.030 mm in translations and 0.030 deg in rotations, for the typical motion amplitudes encountered in FMRI studies. The construction of the training set and the learning stage are fast requiring, respectively, 90 s and 1 to 12 s, depending on the number of input and hidden units of the NN. We believe that NN-based approaches to the problem of FMRI registration can be of great interest in the future. For instance, NN relying on limited K-space data (possibly in navigation echoes) can be a valid solution to the problem of prospective (in frame) FMRI registration.