Workbook for estimating the climatology of regional-continental scale atmospheric dispersion and deposition over the United States /

Mode of access: Internet.

A modern, scientific, simplified, step by step, safe method for teaching safety driving in the family car; a text book for behind the wheel driver training, an educational book for better, safer, smoother, driving, a method of driving to end accidents.

Mode of access: Internet.

Preadamites; or, A demonstration of the existence of men before Adam : together with a study of their condition, antiquity, racial affinities, and progressive dispersion over the earth.

"Preadamitism in literature": p. 454-474.

Criminal offending in schizophrenia over a 25-year period marked by deinstitutionalization and increasing prevalence of comorbid substance use disorders

Objective: This study examined the pattern of criminal convictions in persons with schizophrenia over a 25-year period marked by both radical deinstitutionalization and increasing rates of substance abuse problems among persons with schizophrenia in the community. Method: The criminal records of 2,861 patients (1,689 of whom were male) who had a first admission for schizophrenia in the Australian state of Victoria in 1975, 1980, 1985, 1990, and 1995 were compared for the period from 1975 to 2000 with those of an equal number of community comparison subjects matched for age, gender, and neighborhood of residence. Results: Relative to the comparison subjects, the patients with schizophrenia accumulated a greater total number of criminal convictions (8,791 versus 1,119) and were significantly more likely to have been convicted of a criminal offense (21.6% versus 7.8%) and of an offense involving violence (8.2% versus 1.8%). The proportion of patients who had a conviction increased from 14.8% of the 1975 cohort to 25.0% of the 1995 cohort, but a proportionately similar increase from 5.1% to 9.6% occurred among the comparison subjects. Rates of known substance abuse problems among the schizophrenia patients increased from 8.3% in 1975 to 26.1% in 1995. Significantly higher rates of criminal conviction were found for patients with substances abuse problems than for those without substance abuse problems (68.1% versus 11.7%). Conclusions: A significant association was demonstrated between having schizophrenia and a higher rate of criminal convictions, particularly for violent offenses. However, the rate of increase in the frequency of convictions over the 25-year study period was similar among schizophrenia patients and comparison subjects, despite a change from predominantly institutional to community care and a dramatic escalation in the frequency of substance abuse problems among persons with schizophrenia. The results do not support theories that attempt to explain the mediation of offending behaviors in schizophrenia by single factors, such as substance abuse, active symptoms, or characteristics of systems of care, but suggest that offending reflects a range of factors that are operative before, during, and after periods of active illness.

Relative accuracy and predictive ability of direct valuation methods, price to aggregate earnings method and a hybrid approach

In this paper, we assess the relative performance of the direct valuation method and industry multiplier models using 41 435 firm-quarter Value Line observations over an 11 year (1990–2000) period. Results from both pricingerror and return-prediction analyses indicate that direct valuation yields lower percentage pricing errors and greater return prediction ability than the forward price to aggregated forecasted earnings multiplier model. However, a simple hybrid combination of these two methods leads to more accurate intrinsic value estimates, compared to either method used in isolation. It would appear that fundamental analysis could benefit from using one approach as a check on the other.

An integrated analysis of five double-blind, randomized controlled trials evaluating the safety and efficacy of a hyaluronan product for intra-articular injection in osteoarthritis of the kneel

Objective: Five double-blind, randomized, saline-controlled trials (RCTs) were included in the United States marketing application for an intra-articular hyaluronan (IA-HA) product for the treatment of osteoarthritis (OA) of the knee. We report an integrated analysis of the primary Case Report Form (CRF) data from these trials. Method. Trials were similar in design, patient population and outcome measures - all included the Lequesne Algofunctional Index (LI), a validated composite index of pain and function, evaluating treatment over 3 months. Individual patient data were pooled; a repeated measures analysis of covariance was performed in the intent-to-treat (ITT) population. Analyses utilized both fixed and random effects models. Safety data from the five RCTs were summarized. Results: A total of 1155 patients with radiologically confirmed knee OA were enrolled: 619 received three or five IA-HA injections; 536 received. placebo saline injections. In the active and control groups, mean ages were 61.8 and 61.4 years; 62.4% and 58.8% were women; baseline total Lequesne scores 11.03 and 11.30, respectively. Integrated analysis of the pooled data set found a statistically significant reduction (P < 0.001) in total Lequesne score with hyaluronan (HA) (-2.68) vs placebo (-2.00); estimated difference -0.68 (95% CI: -0.56 to -0.79), effect size 0.20. Additional modeling approaches confirmed robustness of the analyses. Conclusions: This integrated analysis demonstrates that multiple design factors influence the results of RCTs assessing efficacy of intra-articular (IA) therapies, and that integrated analyses based on primary data differ from meta-analyses using transformed data. (C) 2006 OsteoArthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Prediction of vapor-moisture equilibriums for a wood-moisture system using a modified UNIQUAC model

A modified UNIQUAC model has been extended to describe and predict the equilibrium relative humidity and moisture content for wood. The method is validated over a range of moisture content from oven-dried state to fiber saturation point, and over a temperature range of 20-70 degrees C. Adjustable parameters and binary interaction parameters of the UNIQUAC model were estimated from experimental data for Caribbean pine and Hoop pine as well as data available in the literature. The two group-interaction parameters for the wood-moisture system were consistent with using function group contributions for H2O, -OH and -CHO. The result reconfirms that the main contributors to water adsorption in cell walls are the hydroxyl groups of the carbohydrates in cellulose and hemicelluloses. This provides some physical insight into the intermolecular force and energy between bound water and the wood material. (c) 2006 Elsevier Ltd. All rights reserved.

Safety behaviors and dysfunctional beliefs about sleep: Testing a cognitive model of the maintenance of insomnia

Objective: Our aim was to determine if insomnia severity, dysfunctional beliefs about sleep, and depression predicted sleep-related safety behaviors. Method: Standard sleep-related measures (such as the Insomnia Severity Index; the Dysfunctional Beliefs About Sleep scale; the Depression, Anxiety, and Stress Scale; and the Sleep-Related Behaviors Questionnaire) were administered. Additionally, 14 days of sleep diary (Pittsburg Sleep Diary) data and actual use of sleep-related behaviors were collected. Results: Regression analysis revealed that dysfunctional beliefs about sleep predicted sleep-related safety behaviors. Insomnia severity did not predict sleep-related safety behaviors. Depression accounted for the greatest amount of unique variance in the prediction of safety behaviors, followed by dysfunctional beliefs. Exploratory analysis revealed that participants with higher levels of depression used more sleep-related behaviors and reported greater dysfunctional beliefs about their sleep. Conclusion: The findings underlie the significant influence that dysfunctional beliefs have on individuals' behaviors. Moreover, the results suggest that depression may need to be considered as an explicit component of cognitive-behavioral models of insomnia. (c) 2006 Elsevier Inc. All rights reserved.

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.

Two Bayesian treatments of the n-tuple recognition method

Two probabilistic interpretations of the n-tuple recognition method are put forward in order to allow this technique to be analysed with the same Bayesian methods used in connection with other neural network models. Elementary demonstrations are then given of the use of maximum likelihood and maximum entropy methods for tuning the model parameters and assisting their interpretation. One of the models can be used to illustrate the significance of overlapping n-tuple samples with respect to correlations in the patterns.

Bayesian regression filter and the issue of priors

We propose a Bayesian framework for regression problems, which covers areas which are usually dealt with by function approximation. An online learning algorithm is derived which solves regression problems with a Kalman filter. Its solution always improves with increasing model complexity, without the risk of over-fitting. In the infinite dimension limit it approaches the true Bayesian posterior. The issues of prior selection and over-fitting are also discussed, showing that some of the commonly held beliefs are misleading. The practical implementation is summarised. Simulations using 13 popular publicly available data sets are used to demonstrate the method and highlight important issues concerning the choice of priors.

Prediction of paroxysmal atrial fibrillation

We present a novel method for prediction of the onset of a spontaneous (paroxysmal) atrial fibrilation episode by representing the electrocardiograph (ECG) output as two time series corresponding to the interbeat intervals and the lengths of the atrial component of the ECG. We will then show how different entropy measures can be calulated from both of these series and then combined in a neural network trained using the Bayesian evidence procedure to form and effective predictive classifier.