Split flow humidity generator equilibration and stability study.

Generation and control of humidity in a testing environment is crucial when evaluating a chemical vapor sensor as water vapor in the air can not only interfere with the sensor itself, but also react with a chemical analyte changing its composition. Upon constructing a split-flow humidity generator for chemical vapor sensor development, numerous issues were observed due to instability of the generated relative humidity level and drift of the humidity over time. By first fixing the initial relative humidity output of the system at 50%, we studied the effects of flowrate on stabilization time along with long term stability for extended testing events.

Independent Vector Analysis for SSVEP Signal Enhancement, Detection, and Topographical Mapping.

Steady state visual evoked potentials (SSVEPs) have been identified as an effective solution for brain computer interface (BCI) systems as well as for neurocognitive investigations. SSVEPs can be observed in the scalp-based recordings of electroencephalogram signals, and are one component buried amongst the normal brain signals and complex noise. We present a novel method for enhancing and improving detection of SSVEPs by leveraging the rich joint blind source separation framework using independent vector analysis (IVA).

Bioaerosol analysis with Raman chemical imaging microspectroscopy.

Raman chemical imaging microspectroscopy is evaluated as a technology for waterborne pathogen and bioaerosol detection. Raman imaging produces a three-dimensional data cube consisting of a Raman spectrum at every pixel in a microscope field of view. Binary and ternary mixtures including combinations of polystyrene beads, gram-positive Bacillus anthracis, B.

Classification of select category A and B bacteria by Fourier transform infrared spectroscopy.

Fourier transform infrared (FT-IR) spectroscopy historically is a powerful tool for the taxonomic classification of bacteria by genus, species, and strain when they are grown under carefully controlled conditions. Relatively few reports have investigated the determination and classification of pathogens such as the National Institute of Allergy and Infectious Diseases (NIAID) Category A Bacillus anthracis spores and cells (BA), Yersinia species, Francisella tularensis (FT), and Category B Brucella species from FT-IR spectra. We investigated the multivariate statistics classification ability of the FT-IR spectra of viable pathogenic and non-pathogenic NIAID Category A and B bacteria.