Behavioral Evidence for Chemosensory and Thermosensory Pathway Convergence in the Caenorhabditis Elegans Nervous System

The nematode, Caenorhabditis elegans, is an established model system to explore the ways simple nervous systems detect and direct organismal responses to environmental changes. C. elegans possesses specialized receptor cells for the detection of a variety of environmental stimuli. Separate cell types respond to volatile chemical and thermal stimuli and the neural pathways for these show anatomical evidence of convergence. This work reports findings from behavioral assays during simultaneous exposure of nematodes to both thermal differences and attractant volatile chemicals. Combined exposure to benzaldehyde and cold neutralized the behavioral responses to both stimuli in 24°C acclimated worms. Diacetyl and mild thermal stimulation produced the same effect with 16°C acclimated worms. Benzaldehyde appears to interfere with thermophilic circuitry while diacetyl acts similarly with cryophilic circuitry

Time-variant nonparametric extreme quantile estimation with application to US temperature data

Statistical modelling for several years of daily temperature data is somewhat challenging due to remarkable variations of negative and positive temperatures throughout the year. A scatter plot of day and daily temperature shows the high magnitude of variations among data points as dots fall only in the first and fourth quadrants. One parametric modelling approach to this data is to use quantile regression to obtain regression lines on different quantiles. However, these quantile lines cannot make reliable predictions on extreme quantiles when time-variant quantiles differ significantly. In this paper, we develop several two-step nonparametric smoothing estimators and show their superiority over quantile regression for smoothing estimation of nonparametric quantiles with a novel application to temperature data. Narrower bootstrap confidence bands, smaller Minimum Absolute Distance (MAD), smaller bias and MSE, and higher coverage from the application and simulation results show that smoothing curves obtained from these smoothing estimators outperform the quantile regression line

Multivariate control charts based on Bayesian state space models

This paper develops a new multivariate control charting method for vector autocorrelated and serially correlated processes. The main idea is to propose a Bayesian multivariate local level model, which is a generalization of the Shewhart-Deming model for autocorrelated processes, in order to provide the predictive error distribution of the process and then to apply a univariate modified EWMA control chart to the logarithm of the Bayes' factors of the predictive error density versus the target error density. The resulting chart is proposed as capable to deal with both the non-normality and the autocorrelation structure of the log Bayes' factors. The new control charting scheme is general in application and it has the advantage to control simultaneously not only the process mean vector and the dispersion covariance matrix, but also the entire target distribution of the process. Two examples of London metal exchange data and of production time series data illustrate the capabilities of the new control chart.Comment: 19 pages, 6 figure

Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting

Detection algorithm using proxy data for a bioterrorism agent release and historical data for influenza was effective

Linguistic Discrimination in Writing Assessment: How Raters React to African American “Errors,” ESL Errors, and Standard English Errors on a State-Mandated Writing Exam

Raters of Georgia\u27\u27s (USA) state-mandated college-level writing exam, which is intended to ensure a minimal university-level writing competency, are trained to grade holistically when assessing these exams. A guiding principle in holistic grading is to not focus exclusively on any one aspect of writing but rather to give equal weight to style, vocabulary, mechanics, content, and development. This study details how raters react to “errors” typical of African American English writers, of ESL writers, and of standard American English writers. Using a log-linear model to generate odds ratios for comparison of essays with these error types, results indicate linguistic discrimination against African American “errors” and a leniency for ESL errors in writing assessment

A gravity corer release mechanism : design and testing.

http://www.archive.org/details/gravitycorerrele00van

A Study of the Average Run Length Characteristics of the National Notifiable Diseases Surveillance System

This study examines the statistical properties (that is, false positive and negative signals) in detecting unusual patterns of reported cases of diseases from the Centers for Disease Control and Prevention\u27s National Notifiable Diseases Surveillance System. Control charts are applied to the residuals of one-step ahead forecasts based on Box–Jenkins models of reported cases of disease. Simulation and analytical techniques are used to study the average run length characteristics of these control charts for various types of changes in the levels of the series, including spike, trend and step changes. The average run lengths for the highly correlated disease series are much longer than for the usual independent data case. This increase in the average run lengths is strongly influenced by the type of change in the level of the series and by the type of control chart. Understanding the average run length characteristics of the control charts can lead to timely detection of changes in the levels of disease series, and subsequent timely public health actions to decrease unnecessary morbidity and mortality

EWMA and CUSUM Control Charts in the Presence of Correlation

The statistical properties of control charts are usually evaluated under the assumption that the observations from the process are independent. For many processes however, observations which are closely spaced in time will be correlated. This paper considers EWMA and CUSUM control charts for the process mean when the observations are from an AR(1) process with additional random error. This simple model may be a reasonable model for many processes encountered in practice. The ARL and steady state ARL of the EWMA and CUSUM charts are evaluated numerically using an integral equation approach and a Markov chain approach. The numerical results show that correlation can have a significant effect on the properties of these charts. Tables are given to aid in the design of these charts when the observations follow the assumed model