Estimation method for serial dilution experiments.

Titration of microorganisms in infectious or environmental samples is a corner stone of quantitative microbiology. A simple method is presented to estimate the microbial counts obtained with the serial dilution technique for microorganisms that can grow on bacteriological media and develop into a colony. The number (concentration) of viable microbial organisms is estimated from a single dilution plate (assay) without a need for replicate plates.

Probability theory for 3-layer remote sensing in ideal gas law environment.

We extend the probability model for 3-layer radiative transfer [Opt. Express 20, 10004 (2012)] to ideal gas conditions where a correlation exists between transmission and temperature of each of the 3 layers. The effect on the probability density function for the at-sensor radiances is surprisingly small, and thus the added complexity of addressing the correlation can be avoided.

Regression model for estimating inactivation of microbial aerosols by solar radiation.

The inactivation of pathogenic aerosols by solar radiation is relevant to public health and biodefense. We investigated whether a relatively simple method to calculate solar diffuse and total irradiances could be developed and used in environmental photobiology estimations instead of complex atmospheric radiative transfer computer programs. The second-order regression model that we developed reproduced 13 radiation quantities calculated for equinoxes and solstices at 35(°) latitude with a computer-intensive and rather complex atmospheric radiative transfer program (MODTRAN) with a mean error <6% (2% for most radiation quantities).

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model.

A model for inactivation of microbes suspended in the atmosphere by solar ultraviolet radiation.

Solar ultraviolet (UV) light within 280-320 nm (UVB) is the primary cause for virus inactivation in the atmosphere. Only the effect of the direct component has been previously evaluated. We developed a simple regression model to estimate the inactivation of a virus due to direct (unscattered), diffuse (scattered) and total (direct + diffuse) components of solar UV (daily integrated irradiances).

Radiative transfer model for aerosols at infrared wavelengths for passive remote sensing applications: revisited.

We introduced a two-dimensional radiative transfer model for aerosols in the thermal infrared [Appl. Opt.45, 6860-6875 (2006)APOPAI0003-693510.

Impact of atmospheric boundary layer turbulent temperature fluctuations on remote detection of vapors by passive infrared spectroscopy.

A computational model to simulate the effects of boundary layer isotropic atmospheric turbulence on the radiative transfer process is presented. We perform a large number of simulations with stochastic ambient conditions to estimate the statistics necessary to predict the detection limit of a given trace gas. We find that the radiance and transmittance variability are primarily determined by the optical depth of the emitting atmosphere, and that the relative variability of the transmittance is an order of magnitude smaller than that of the radiance.

Simultaneous estimation of aerosol cloud concentration and spectral backscatter from multiple-wavelength lidar data.

We present a sequential algorithm for estimating both concentration dependence on range and time and backscatter coefficient spectral dependence of optically thin localized atmospheric aerosols using data from rapidly tuned lidar. The range dependence of the aerosol is modeled as an expansion of the concentration in an orthonormal basis set whose coefficients carry the time dependence. Two estimators are run in parallel: a Kalman filter for the concentration range and time dependence and a maximum-likelihood estimator for the aerosol backscatter wavelength and time dependence.

Lidar detection algorithm for time and range anomalies.

A new detection algorithm for lidar applications has been developed. The detection is based on hyperspectral anomaly detection that is implemented for time anomaly where the question "is a target (aerosol cloud) present at range R within time t(1) to t(2)" is addressed, and for range anomaly where the question "is a target present at time t within ranges R(1) and R(2)" is addressed. A detection score significantly different in magnitude from the detection scores for background measurements suggests that an anomaly (interpreted as the presence of a target signal in space/time) exists.

Radiative transfer model for aerosols in infrared wavelengths for passive remote sensing applications.

A comprehensive analytical radiative transfer model for isothermal aerosols and vapors for passive infrared remote sensing applications (ground-based and airborne sensors) has been developed. The theoretical model illustrates the qualitative difference between an aerosol cloud and a chemical vapor cloud. The model is based on two and two/four stream approximations and includes thermal emission-absorption by the aerosols; scattering of diffused sky radiances incident from all sides on the aerosols (downwelling, upwelling, left, and right); and scattering of aerosol thermal emission.

Improving the linearity of infrared diffuse reflection spectroscopy data for quantitative analysis: an application in quantifying organophosphorus contamination in soil.

Diffuse reflection data are presented for ethyl methylphosphonate in a fine Utah dirt sample as a model system for organophosphate-contaminated soil. The data revealed a chemometric artifact when the spectra were represented in Kubelka-Munk units that manifests as a linear dependence of spectral peak height on variations in the observed baseline position (i.e.

Measurements of atmospheric brightness temperature fluctuations and their implications on passive remote sensing.

Passive remote sensing of airborne chemicals at infrared wavelengths may be limited by temporal fluctuations in atmospheric brightness temperatures deltaT(t). Brightness temperatures in two infrared spectral bands were simultaneously measured on clear and cloudy days along three lines of sights. For time windows t < 3-5 s, deltaT(t) remained constant at the sensor noise level and rapidly increased as t increased.

Comparison between orthogonal subspace projection and background subtraction techniques applied to remote-sensing data.

The basic measurement equation r = B + alphad + n is solved for alpha (the weight or abundance of the spectral target vector d) by two methods: (a) by subtracting the stochastic spectral background vector B from the spectral measurement's vector r (subtraction solution) and (b) by orthogonal subspace projection (OSP) of the measurements to a subspace orthogonal to B (the OSP solution). The different geometry of the two solutions and in particular the geometry of the noise vector n is explored. The angular distribution of the noise angle between B and n is the key factor for determining and predicting which solution is better.

Noise assessment of a Fourier transform infrared spectroradiometer subject to the stability of a conventional laboratory blackbody source.

A method is described for the measurement of the noise-equivalent spectral radiance (NESR) of Fourier transform infrared (FTIR) spectroradiometers at all wave numbers of a selected range. The method requires minimal detailed knowledge of the sensor and no support equipment beyond a blackbody source. The NESRs of the FTIR spectroradiometer are determined at every wave-number increment in the 700-1300 cm(-1) range, for six resolutions, with a conventional blackbody source and ensembles of differential spectra.

Detection, identification, and estimation of biological aerosols and vapors with a Fourier-transform infrared spectrometer.

Two experiments were conducted with a Fourier-transform infrared (FTIR) spectrometer. The purpose of the first experiment was to detect and identify Bacillus subtilis subsp. niger (BG) bioaerosol spores and kaolin dust in an open-air release for which the thermal contrast between the aerosol temperature and background brightness temperature is small.

Remote detection of biological aerosols at a distance of 3 km with a passive Fourier transform infrared (FTIR) sensor.

Bio-aerosols containing Bacillus subtilis var. niger (BG) were detected at a distance of 3 km with a passive Fourier Transform InfraRed (FTIR) spectrometer in an open-air environment where the thermal contrast was low (~ 1 K). The measurements were analyzed with a new hyperspectral detection, identification and estimation algorithm based on radiative transfer theory and advanced signal processing techniques that statistically subtract the undesired background spectra.

Optimized differential absorption radiometer for remote sensing of chemical effluents.

A differential absorption radiometer sensor that was optimized for near-perfect (to approximately 2%) correction of the absorption by ambient atmospheric species (e.g., water) is described.

Computation of a spectrum from a single-beam fourier-transform infrared interferogram.

A new high-accuracy method has been developed to transform asymmetric single-sided interferograms into spectra. We used a fraction (short, double-sided) of the recorded interferogram and applied an iterative correction to the complete recorded interferogram for the linear part of the phase induced by the various optical elements. Iterative phase correction enhanced the symmetry in the recorded interferogram.