Acoustic tweets and blogs: Using social media in an undergraduate acoustics course

Each fall, the author teaches an undergraduate architectural acoustics course to around 40 third-year architectural engineering students at the University of Nebraska. Beginning in 2011, a social media component was introduced to explore the use of this technology and how it may supplement the students\u27 learning experience. Students were given an opportunity to receive extra credit by using Twitter and/or blogging about course material using a set hashtag (#AE3300) or through the course website. Results were positive, and the author will discuss pros and cons that she has experienced in adding this social media component. Suggestions for future implementations and examples of student participation will be presented

Acoustic tweets and blogs: Using social media in an undergraduate acoustics course

Each fall, the author teaches an undergraduate architectural acoustics course to around 40 third-year architectural engineering students at the University of Nebraska. Beginning in 2011, a social media component was introduced to explore the use of this technology and how it may supplement the students\u27 learning experience. Students were given an opportunity to receive extra credit by using Twitter and/or blogging about course material using a set hashtag (#AE3300) or through the course website. Results were positive, and the author will discuss pros and cons that she has experienced in adding this social media component. Suggestions for future implementations and examples of student participation will be presented

Calibration, error analysis, and ongoing measurement process monitoring for mass spectrometry

We consider problems of quantifying and monitoring accuracy and precision of measurement in mass spectrometry, particularly in contexts where there is unavoidable day-to-day/period-to-period changes in instrument sensitivity. First we consider the issue of estimating instrument sensitivity based on data from a typical calibration study. Simple method-of-moments methods, likelihood-based methods, and Bayes methods based on the one-way random effects model are illustrated. Then we consider subsequently assessing the precision of an estimate of a mole fraction of a gas of interest in an unknown. Finally, we turn to the problem of ongoing measurement process monitoring and illustrate appropriate set-up of Shewhart control charts in this application. --

Detection and Estimation of an Optical Image by Photon-Counting Techniques

Statistical description of a photoelectric detector is given. The photosensitive surface of the detector is divided into many small areas, and the moment generating function of the photo-counting statistic is derived for large time-bandwidth product. The detection of a specified optical image in the presence of the background light by using the hypothesis test is discussed. The ideal detector based on the likelihood ratio from a set of numbers of photoelectrons ejected from many small areas of the photosensitive surface is studied and compared with the threshold detector and a simple detector which is based on the likelihood ratio by counting the total number of photoelectrons from a finite area of the surface. The intensity of the image is assumed to be Gaussian distributed spatially against the uniformly distributed background light. The numerical approximation by the method of steepest descent is used, and the calculations of the reliabilities for the detectors are carried out by a digital computer

Association Signals Unveiled by a Comprehensive Gene Set Enrichment Analysis of Dental Caries Genome-Wide Association Studies

Gene set-based analysis of genome-wide association study (GWAS) data has recently emerged as a useful approach to examine the joint effects of multiple risk loci in complex human diseases or phenotypes. Dental caries is a common, chronic, and complex disease leading to a decrease in quality of life worldwide. In this study, we applied the approaches of gene set enrichment analysis to a major dental caries GWAS dataset, which consists of 537 cases and 605 controls. Using four complementary gene set analysis methods, we analyzed 1331 Gene Ontology (GO) terms collected from the Molecular Signatures Database (MSigDB). Setting false discovery rate (FDR) threshold as 0.05, we identified 13 significantly associated GO terms. Additionally, 17 terms were further included as marginally associated because they were top ranked by each method, although their FDR is higher than 0.05. In total, we identified 30 promising GO terms, including 'Sphingoid metabolic process,' 'Ubiquitin protein ligase activity,' 'Regulation of cytokine secretion,' and 'Ceramide metabolic process.' These GO terms encompass broad functions that potentially interact and contribute to the oral immune response related to caries development, which have not been reported in the standard single marker based analysis. Collectively, our gene set enrichment analysis provided complementary insights into the molecular mechanisms and polygenic interactions in dental caries, revealing promising association signals that could not be detected through single marker analysis of GWAS data. © 2013 Wang et al

Development of a Model to Predict the Likelihood of Complaints due to Assorted Tone-in-Noise Combinations

This paper develops a model to predict if listeners would be likely to complain due to annoyance when exposed to a certain noise signal with a prominent tone, such as those commonly produced by heating, ventilation, and air-conditioning systems. Twenty participants completed digit span tasks while exposed in a controlled lab to noise signals with differing levels of tones, ranging from 125 to 1000 Hz, and overall loudness. After completing the digit span tasks under each noise signal, from which task accuracy and speed of completion were captured, subjects were asked to rate level of annoyance and indicate the likelihood of complaining about the noise. Results show that greater tonality in noise has statistically significant effects on task performance by increasing the time it takes for participants to complete the digit span task; no statistically significant effects were found on task accuracy. A logistic regression model was developed to relate the subjective annoyance responses to two noise metrics, the stationary Loudness and Tonal Audibility, selected for the model due to high correlations with annoyance responses. The percentage of complaints model showed better performance and reliability over the percentage of highly annoyed or annoyed