This PDF file contains the front matter associated with SPIE Proceedings Volume 6554, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

Results will be reported from efforts to develop a self-contained micromachined microfluidic detection system for the presence of specific target analytes under the US Office of Naval Research Counter IED Basic Research Program. Our efforts include improving/optimizing a dedicated micromachined sensor array with integrated photodetectors and the synthesis of chemiluminescent receptors for nitramine residues. Our strategy for developing chemiluminescent synthetic receptors is to use quenched peroxyoxalate chemiluminescence; the presence of the target analyte would then trigger chemiluminescence. Preliminary results are encouraging as we have been able to measure large photo-currents from the reaction. We have also fabricated and demonstrated the feasibility of integrating photodiodes within an array of micromachined silicon pyramidal cavities. One particular advantage of such approach over a conventional planar photodiode would be its collection efficiency without the use of external optical components. Unlike the case of a normal photodetector coupled to a focused or collimated light source, the photodetector for such a purpose must couple to an emitting source that is approximately hemispherical; hence, using the full sidewalls of the bead's confining cavity as the detector allows the entire structure to act as its own integrating sphere. At the present time, our efforts are concentrating on improving the signal-to-noise ratio by reducing the leakage current by optimizing the fabrication sequence and the design.

Airborne hyperspectral imaging has been studied since the late 1980s as a tool to detect minefields for military countermine operations and for level I clearance for humanitarian demining. Hyperspectral imaging employed on unmanned ground vehicles may also be used to augment or replace broadband imagers to detect individual mines. This paper will discuss the ability of different optical wavebands - the visible/near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) - to detect surface-laid and buried mines. The phenomenology that determines performance in the different bands is discussed. Hyperspectral imagers have usually been designed and built for general purpose remote sensing applications and often do not meet the requirements of mine detection. The DRDC mine detection research program has sponsored the development by Itres Research of VNIR, SWIR and TIR instruments specifically intended for mine detection. The requirements for such imagers are described, as well as the instruments. Some results of mine detection experiments are presented. To date, reliable day time detection of surface-laid mines in non-real-time, independent of solar angle, time of day and season has been demonstrated in the VNIR and SWIR. Real-time analysis, necessary for military applications, has been demonstrated from low speed ground vehicles and recently from airborne platforms. Reliable, repeatable detection of buried mines has yet to be demonstrated, although a recently completed TIR hyperspectral imager will soon be tested for such a capability.

We have designed and tested a portable stand-off gated-Raman system that is capable of detecting organic and inorganic bulk chemicals at stand-off distances to 100 m during day and night time. Utilizing a single 532 nm laser pulse (~25 mJ/pulse), Raman spectra of several organic and inorganic compounds have been measured with the portable Raman instrument at a distance of 10 m in a well-illuminated laboratory. Raman spectra, obtained during a very short period of time (2 micro second), from organic compounds such as acetone, benzene, cyclohexane, 2-propanol, naphthalene, and inorganic nitrates, showed all major bands required for unambiguous chemical identification. We have also measured the Raman spectra of acetone, sulfuric acid, hydrogen peroxide (50%) aqueous solution, nitro-methane containing fuel, and nitrobenzene in glass containers with a 532 nm, 20 Hz pulsed laser excitation and accumulated the spectra with 200 to 600 laser shots (10 to 30 sec integration time) at 100 m with good signal-to-background ratio. The results of these investigations show that the stand-off Raman spectra to 100 m distance can be used to identify Raman fingerprints of both inorganic and organic compounds and could be useful for Homeland security and environmental monitoring.

Surface enhanced Raman spectroscopy (SERS) and spatial characterization of quartz-bound Au nanoparticle substrates has been used to assist the improvement of analytical sensitivity and limits of detection. SERS enhancement is significantly affected not only by a substrate's surface morphology but also laser-analyte orientation as well as matrix effects caused by non-analyte and non-metal substrate compounds. The use of Au hydrosols to fabricate better performing SERS substrates to detect chemical and/or biological agents has been an area of active and widespread research, but to date, the impact of matrix effects from spectral interferers introduced during fabrication on analytical sensitivity and limits of detection is not well understood. Experiments varying the depth of collection (observation) volume with respect to R6G on the substrate show high variability in analyte signal to noise ratios (S/N) well as high variability in background due to matrix effects from varying influences of the substrate non-metal components. Of the many post-fabrication design factors affecting SERS substrate sensitivity, characterization of matrix effects caused by vertical changes in observation volume near the analyte-substrate interface will improve analytical sensitivity and limits of detection.

The FIRST, a commercial hyperspectral imager developed by Telops, features high sensitivity in a compact and robust package. This sensor provides hypercubes of spectral radiance of up to 320x256 pixels at 0.35mrad spatial resolution over the 8 - 12 &mgr;m spectral range at user selectable spectral resolutions of up to 0.25 cm^-1. The measurements are converted into "chemical maps" by the use of powerful algorithms using both spatial and spectral information. The FIRST has been used at several field tests for the standoff detection and identification of chemicals. During these tests, the sensor is usually operated at 4 cm^-1 of spectral resolution and the image size is tailored according to the dissemination. Algorithms based on a combination of clutter-matched filters and spectral angle mapper have been developed and used to process the measured data. The algorithms combine sub-band selection to minimize the correlation between the spectral signatures in the library and careful selection of the thresholds to reduce the level of false alarms. The output of the algorithms is the image of the clouds superimposed on the broadband thermal image. JHU/APL has developed a processing approach that adapts to different backgrounds, yields low probability of false alarm, and performs well in the presence of "hot" pixels. The algorithm combines background/noise suppression techniques, spectral detection techniques, such as the spectral angle mapper and the matched filter, and automatic adaptive threshold techniques. This paper will present the successful standoff detection and identification of various chemical compounds using a variety of field measurements. Images of chemical disseminations will be presented, with some of them including mixtures of 2 different chemicals.

We present a multistage anomaly detection algorithm suite and suggest its application to chemical plume detection using hyperspectral (HS) imagery. This approach is proposed to handle underlying difficulties (e.g., plume shape/scale uncertainties) facing the development of autonomous anomaly detection algorithms. The approach features four stages: (i) scene random sampling, which does not require secondary information (shape and scale) about potential effluent plumes; (ii) anomaly detection; (iii) parallel processes, which are introduced to mitigate the inclusion by chance of potential plume samples into clutter background classes; and (iv) fusion of results. The probabilities of taking plume samples by chance within the parallel processes are modeled by the binomial distribution family, which can be used to assist on tradeoff decisions. Since this approach relies on the effectiveness of its core anomaly detection technique, we present a compact test statistic for anomaly detection, which is based on an asymmetric hypothesis test. This anomaly detection technique has shown to preserve meaningful detections (genuine anomalies in the scene) while significantly reducing the number of meaningless detections (transitions of background regions). Results of a proof of principle experiment are presented using this approach to test real HS background imagery with synthetically embedded gas plumes. Initial results are encouraging.

This work was focused in the measurement of spectroscopic signatures of Chemical Warfare Agent Simulants (CWAS) and degradation products of chemical agents using vibrational spectroscopy for the generation of spectroscopic libraries. The chemicals studied were: DMMP, DIMP, 2-CEES, 2-BAET, 1,4-thioxane, thiodiglycol sulfoxide, dihexylamine, cyclohexylamine, among others. Raman microscopy experiments were performed at different excitation wavelengths that spanned from NIR at 1064 and 785 nm to the VIS at 532, 514.5 and 488 nm and even the deep ultraviolet region at 244 nm. For the compounds studied the optimum excitation lines were 488 nm and 532 nm with a laser power of 25 mW. Among the most prominent bands were at these incident wavelengths were located ca. 652 and 1444 cm-1. Fourier Transform Infrared Spectroscopy in liquid and gas phase and Fiber Optics Coupled-Grazing Angle Probe-FTIR (FOCGAP- FTIR) were used to characterize the spectroscopic signature of target threat agents. The surface experiments were performed at detection levels of about 1 &mgr;g/cm² suggest that limits of detection (LOD) achievable could be as low as nanograms/cm². Remote sensing experiments were performed using a telescope coupled with a Raman spectrophotometer as a function of power and acquisition time. Characterization of compounds by vibrational spectroscopy and the early stages of the transition from the lab based experiments to remote detection experiments will be presented.

Differential reflectometry (DR) is an effective tool to supplement existing explosives detection systems thus making the combined unit more effective than one tool alone. It is an optical technique in which the investigative light beam emanates from an extended distance onto the substance under investigation, thus rendering it to be a standoff method. The applicable distance still needs to be determined but could be well within the 50 to 100 m range. Specifically, differential reflectometry (also known as Differential reflection spectroscopy) is a surface analytical technique that reveals details about the electron structure. In other words, the instrument allows the measurement of the energies that electrons absorb from photons as they are raised into higher, allowed energy states. Since each material has a specific electron structure the measurement of the characteristic energies for "electron transitions" serves as a means (i.e. a fingerprint) for identifying these substances. The DR device can be made portable, it is fast, safe for the public, does not require human involvement, is cost effective, and most of all, it is a standoff technique which does not require ingestion of a suspicious substance into an instrument.

The CH stretching overtone transitions of chemical warfare agents are of interest in the area of threat detection, including standoff threat detection, as many of these transitions occur near regions where small, efficient diode lasers operate. Further, detectors which operate in the regions where CH overtone transitions occur (i.e., in the near infrared and visible regions) are usually much more sensitive than detectors which operate in the region where fundamental CH vibrational transitions occur (i.e., in the mid infrared). However, the interpretation of experimental overtone spectra is complex, and the computational simulation of overtone spectra is challenging. Presented herein are the simulated vapour phase CH overtone stretching transitions in the nerve agent simulants trimethyl phosophate and triethyl phosophate. Spectral regions are simulated using the harmonically coupled anharmonic oscillator (HCAO) model. Data for HCAO calculations are obtained from ab initio calculations, without recourse to experimental data.

Northrop Grumman has designed, developed and demonstrated acousto-optic tunable filter (AOTF) based hyperspectral imager to cover visible to long wavelength infrared (LWIR) spectral region. We have experimentally demonstrated and report the results of crystal growth, fabrication, design, development and performance for the long wavelength infrared (LWIR) acousto-optic tunable filter (AOTF)-based hyperspectral imager based on an efficient crystal thallium arsenic selenide. The results on the growth of 40 mm diameter and 15 cm long crystals, 4.0 cm long AOTF fabrication, and system design and performance are presented. A system concept was developed with high efficiency, resolution, and throughput utilizing this TAS AOTF. The test setup consisted of an LWIR camera (microbolometer), the AOTF, and SF₆. The object was placed ~20" in front of the AOTF. The camera was aligned to the first order diffracted beam of the AOTF. The AOTF was tuned to 10.6 um wavelength by applying a 13.9 MHz RF signal on the transducer. The results on the growth of crystals, AOTF fabrication, and systems design and performance are presented.

Photoacoustic spectroscopy is a useful monitoring technique that is well suited for trace gas detection applications. A sensitive and compact differential photoacoustic method for trace gas measurements is proposed. The technique possesses favorable detection characteristics that suggest the system dimensions may scale to a micro-system design. The objective of present work is to incorporate two strengths of the Army Research Laboratory (ARL); Interband Quantum Cascade Laser (ICL) source development and Chemical and Biological Sensing; we then applied them into a monolithic micro-electromechanical systems (MEMS) photoacoustic trace gas sensor. Previous data has shown that reducing the size of the photoacoustic cell can produce a very sensitive sensor using a CO₂ laser. Recent work has shown that with further reduction in the size of the photoacoustic cell in combination with an ICL as the source, produces favorable detection limits for Dimethyl Methyl Phosphonate (DMMP) a precursor to a nerve agent. These studies involve the incorporation of an ICL source operating at ~3.45 &mgr;m. This experimentation is expected to culminate in the creation of an extremely versatile MEMS photoacoustic sensor.

Intense laser pulses may be used for standoff detection of energetic materials. Coherent backscattered spectroscopy offers a tremendous advantage over other spectroscopic detection techniques in that it uses stimulated or amplified spontaneous emission from the sample to produce a minimally divergent, directional beam back to the detection platform. The characteristics of the backscattered beam depend largely on the intensity and pulse width of the laser source as well as the concentration and photo-physical characteristics of the target molecule. Different target molecules will exhibit different backscattered emission signals, allowing differential detection of energetic materials in the vapor phase. Because of the highly directional nature of the coherent backscattered beam, detection limits in the vapor of less than 1 ppm at ranges up to 100 meters can be anticipated.

Traditional micro-fabricated inertial measurement devices like MEMS accelerometers, gyroscopes, and IMUs consist of two principle components: (1) a micromechanical structure that responds to inertial forces and deforms in a way that can be measured electronically by, for example, changing the height of a gap, and, thus, its capacitance; (2) an analog or digital computing device that integrates the electronically sensed acceleration to yield velocity and position, and then records this information for later use. These two components must be replicated in some fashion in a "nano" version of the same devices, specifically a nano-IMU is considered. The proposed approach combines an inertially-sensitive nanostructure or nano fluid/structure system with a micro- or nano- sized chemical reactor that functions as an analog computer. This paper will outline the feasibility of using a cantilever-based acceleration-sensing valve to feed reactants into a first order chemical reaction. The proposed approach to the development of a nano-IMU would allow the benefits of existing MEMS IMU technology to be applied to an even broader array of applications by enabling the development of a new class of geospatially-sensitive drugs and materials and has application in a variety of military, intelligence, and commercial activities.

Raman spectroscopy has been evaluated as a candidate technology for waterborne pathogen detection. Parameters have been investigated that influence the fidelity of Raman spectra of microorganisms and protein biological substances including bacterial species and strains, susceptibility to laser induced photodamage, composition of water matrix, and organism aging in water. An important operating parameter is the laser induced photodamage threshold of a variety of biological materials. The laser induced photodamage may be minimized by operating a 532 nm continuous wave laser excitation at laser power densities below 2300 W/cm² for Gram-positive Bacillus atrophaeus (BG) vegetative cells, 2800 W/cm² for BG spores, and 3500 W/cm² for Gram-negative E. coli organisms. Multivariate principal components analysis was able to discriminate six Gram-positive and Gram-negative organisms as well as five proteins between 5K and 65K mass units. B. thuringiensis, B. cereus, BG spore and vegetative preparations, and E. coli showed minimal aging effects when suspended in distilled and tap water. In general, Raman microspectroscopy of biological substances exhibited minimal spectral variability due to the age of a resting suspension, water matrix, and bacterial strain. The observed signature variability did not prevent the differentiation and characterization of bacterial genus and species and protein substances using Raman spectroscopy.

Raman spectroscopy is being evaluated as a candidate technology for waterborne pathogen detection and the fidelity of the Raman spectra of microorganisms with respect to their differentiation at the single cell level are investigated. Individual entities are investigated in the microscope field of view (FOV) by Raman chemical imaging microscopy (RCIM). The size of a substance was not found to cause spectral confusion when collating individual entities in the FOV by multivariate principal components (PCA) and RCIM methods. Polystyrene (PS) beads in 1-3 micron sizes were collectively grouped together by PCA. Distilled and recipe tap water matrices produced the proper identification of the PS beads throughout the FOV, and all PS beads in a FOV were grouped together by PCA. A mixture of Gram-positive Bacillus atrophaeus spores and Gram-negative E. coli cells were differentiated and distinguished by RCIM.

FTIR, Raman spectroscopy and Surface Enhanced Raman Scattering (SERS) requires a minimum of sample allows fast identification of microorganisms. The use of this technique for characterizing the spectroscopic signatures of these agents and their stimulants has recently gained considerable attention due to the fact that these techniques can be easily adapted for standoff detection from considerable distances. The techniques also show high sensitivity and selectivity and offer near real time detection duty cycles. This research focuses in laying the grounds for the spectroscopic differentiation of Staphylococcus spp., Pseudomonas spp., Bacillus spp., Salmonella spp., Enterobacter aerogenes, Proteus mirabilis, Klebsiella pneumoniae, and E. coli, together with identification of their subspecies. In order to achieve the proponed objective, protocols to handle, cultivate and analyze the strains have been developed. Spectroscopic similarities and marked differences have been found for Spontaneous or Normal Raman spectra and for SERS using silver nanoparticles have been found. The use of principal component analysis (PCA), discriminate factor analysis (DFA) and a cluster analysis were used to evaluate the efficacy of identifying potential threat bacterial from their spectra collected on single bacteria. The DFA from the bacteria Raman spectra show a little discrimination between the diverse bacterial species however the results obtained from the SERS demonstrate to be high discrimination technique. The spectroscopic study will be extended to examine the spores produced by selected strains since these are more prone to be used as Biological Warfare Agents due to their increased mobility and possibility of airborne transport. Micro infrared spectroscopy as well as fiber coupled FTIR will also be used as possible sensors of target compounds.

Real time monitoring of biowarfare agents (BWA) for military and civilian protection remains a high priority for homeland security and battlefield readiness. Available devices have adequate sensitivity, but the detection modules have limited periods of deployment, require frequent maintenance, employ single-use disposable components, and have limited multiplexing capability. Surface Plasmon Resonance enhanced Common Path Interferometry (SPR-CPI) is a label-free, high sensitivity biomolecular interaction measurement technology that allows multiplexed real-time measurement of biowarfare agents, including small molecules, proteins, and microbes. The technology permits continuous operation in a field-deployable detection module of an integrated BWA monitoring system. SPR-CPI measures difference in phase shift of polarized light reflected from the transducer interface caused by changes in refractive index induced by biomolecular interactions. The measurement is performed on a discrete 2-dimensional area functionalized with biomolecule capture reagents in a microarray format, allowing simultaneous measurement of up to 100 separate analytes. Output consists of simultaneous voltage measurements proportional to the phase differences resulting from the refractive index changes and is automatically processed and displayed graphically or delivered to a decision making algorithm. This enables a fully automatic field-deployable detection system capable of integration into existing modular BWA detection systems. Proof-of-concept experiments on surrogate models of anticipated BWA threats have demonstrated utility. Efforts are in progress for full development and deployment of the device.

Much work has been reported on attempting to identify spores from their spectral signatures. Since spores are also complex scattering objects, with a layered internal refractive index structure, it makes sense to explore the possibility of making an identification simply from a scattering pattern or from anticipated scattering characteristics combined with a spectral signature. Models for scattering from simple geometrical coated shapes have been developed and recently Bragg spheres and onion-ring resonator-like scatterers in the Mie regime have received considerable attention driven by other applications. Also, our own group has recently advanced a method for inverting scattered field data from strongly scattering penetrable targets. We present here some very early considerations of the convergence of these possibilities and suggest some simple experiments that might advance our understanding of spore detection and identification.

Bacterial contamination of food products puts the public at risk and also generates a substantial cost for the food-processing industry. One of the greatest challenges in the response to these incidents is rapid recognition of the bacterial agents involved. Only a few currently available technologies allow testing to be performed outside of specialized microbiological laboratories. Most current systems are based on the use of expensive PCR or antibody-based techniques, and require complicated sample preparation for reliable results. Herein, we report our efforts to develop a noninvasive optical forward-scattering system for rapid, automated identification of bacterial colonies grown on solid surfaces. The presented system employs computer-vision and pattern-recognition techniques to classify scatter patterns produced by bacterial colonies irradiated with laser light. Application of Zernike and Chebyshev moments, as well as Haralick texture descriptors for image feature extraction, allows for a very high recognition rate. An SVM algorithm was used for classification of patterns. Low error rates determined by cross-validation, reproducibility of the measurements, and robustness of the system prove that the proposed technology can be implemented in automated devices for bacterial detection.

A compact chamber was developed for the dissemination of biological aerosols. The chamber, measuring 110 cm in length, was designed according to short-range LIDAR principles, and will be used to simulate open-air releases of aerosols. Measurements, carried out by light-induced fluorescence (LIF) techniques, will be correlated with spectroscopic data obtained with a long-range lidar system owned by Defence Research and Development Canada (DRDC). The chamber allows complete control over environmental factors, such as humidity, pressure and temperature, thus facilitating the creation of a trustworthy signature database for the standoff detection of bio-aerosols. Studies will also include the influence of growth stage, stress and growth media on the fluorescence spectra of various biological aerosols.

We report on the advances made in the basic research to label specific chemical or biological aerosols on-the-fly using an electrospray technique. Fluorescent biomarkers that have been created for specific targets, and that produce a detectable change in emission characteristics only upon binding, will be used to coat all aerosols in an air stream. Aerosols with appropriate receptors will be labeled in this manner, allowing them to be identified in near real-time using a simple laser-induced fluorescence technique. In effect, an immunoassay is quickly performed on the surface of single chemical or biological particles as they flow in an air stream, labeling specific ones for rapid, single-particle interrogation and identification among a diverse and dynamic background. This method permits the use of solutions containing mixtures of different biomarkers to simultaneously identify multiple types of chemical or biological aerosols. Some issues that are currently being investigated include the kinetics of biomarker surface binding to an aerosol in flight and the control of charged aerosols for efficient single particle interrogation.

Aerosol backscatter and extinction cross-sections are required to model and evaluate the performance of both active and passive detection systems. A method has been developed by which begins with laboratory measurements of thin films and suspensions of biological material to obtain the complex index refraction of the film from the UV to the LWIR. Using that result with particle size distribution and shape information as inputs to T-matrix calculations yields the extinction cross-section and backscatter cross section as a function of wavelength. These are important inputs to the lidar equation. In a continuing effort to provide validated optical cross-sections, measurements have been made on a number of high purity biological species in the laboratory as well as measurements of material released at recent field tests. The resulting observed differences aid in distinguishing between intrinsic and extrinsic effects, which can affect the characteristic signatures of important biological aerosols. A variety of biological aerosols are examined.

A bioaerosol sensor based on dual wavelength fluorescence excitation and multiple wavelength elastic scattering has been developed and characterized for classifying micron-sized particles on the fly. The UVLIF instrument successfully completed a field trial in which we detected and correctly identified over 90% of the simulant releases over the 2 week testing period.

The primary goal of this paper is to develop Hyperspectral algorithms for early detection of a readout system used in conjunction with plants designed to de-green or discolor after detection of explosives, harmful chemicals, and environmental pollutants. Work in progress is aimed to develop a new class of biosensors or Plant Sentinels that can serve as inexpensive plant-based biological early-warning systems capable of detecting substances that are harmful to human or the environment [LoHe03]. The de-greening circuits in the laboratory plant, Arabidopsis, have been shown to induce rapid chlorophyll loss, thereby change color under the influence of synthetic estrogens. However, as of now, the bio de-greening phenomenon is detectable by human eyes or with a system (chlorophyll fluorescence) that works best in laboratory conditions. In order to make the plant sentinel system practically viable, we have developed automated monitoring scheme for early detection of the de-greening phenomenon. The automated detection capability would lead to practical applicability and wider usage. This paper presents novel and effective HSI-based algorithms for early detection of de-greening of plants and vegetation due to explosives or chemical agents. The image processing based automated degreening detector, presented in this paper will be capable of 24/7 monitoring of the plant sentinels and to detect minutest possible discoloration of the plant-sensors to serve as an early-warning system. We also present preliminary results on estimating the length of time that the explosive or chemical agent has been present.

The spectrally resolved absolute fluorescence cross sections of Bacillus globigii (BG) and Bacillus thuringiensis (BT) were measured with a 266nm Nd:YAG laser source. The aerosol samples were prepared in dilute aqueous suspensions for measurement and the absolute cross section was found by use of the Raman scattering line from water. Integrated cross sections for BT and BG were found to be 1.1864 × 10^-12 cm²(spore sr) and 3.251 × 10^-13 cm²/ (spore sr) respectively.

This paper presents an overview of recent work by ECBC in algorithm development for parameter estimation, detection, and classification of localized aerosols in the atmosphere using information provided by multiple-wavelength rangeresolved lidar. The motivation for this work is the need to detect, locate, and identify potentially toxic atmospheric aerosols at safe standoff ranges using time-series data collected at a discrete set of CO₂ laser wavelengths. The goals of the processing are to use the digitized transmitted and received backscatter array data to (1) decide if significant aerosol is present, (2) provide estimates of the range and size of the aerosol cloud, (3) produce estimates of the backscatter spectral dependence, and (4) use the backscatter signatures as feature vectors for training and implementation of a support vector machine aerosol classifier. The paper describes examples this processing derived from an extensive set of data collected by ECBC during JBSDS field-testing at Dugway Proving Ground.

Although a great deal of research effort has been focused on the forward prediction of the dispersion of contaminants (e.g., chemical and biological warfare agents) released into the turbulent atmosphere, much less work has been directed toward the inverse prediction of agent source location and strength from the measured concentration, even though the importance of this problem for a number of practical applications is obvious. In general, the inverse problem of source reconstruction is ill-posed and unsolvable without additional information. It is demonstrated that a Bayesian probabilistic inferential framework provides a natural and logically consistent method for source reconstruction from a limited number of noisy concentration data. In particular, the Bayesian approach permits one to incorporate prior knowledge about the source as well as additional information regarding both model and data errors. The latter enables a rigorous determination of the uncertainty in the inference of the source parameters (e.g., spatial location, emission rate, release time, etc.), hence extending the potential of the methodology as a tool for quantitative source reconstruction. A model (or, source-receptor relationship) that relates the source distribution to the concentration data measured by a number of sensors is formulated, and Bayesian probability theory is used to derive the posterior probability density function of the source parameters. A computationally efficient methodology for determination of the likelihood function for the problem, based on an adjoint representation of the source-receptor relationship, is described. Furthermore, we describe the application of efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) for sampling from the posterior distribution of the source parameters, the latter of which is required to undertake the Bayesian computation. The Bayesian inferential methodology for source reconstruction is validated against real dispersion data for two cases involving contaminant dispersion in highly disturbed flows over urban and complex environments where the idealizations of horizontal homogeneity and/or temporal stationarity in the flow cannot be applied to simplify the problem. Furthermore, the methodology is applied to the case of reconstruction of multiple sources.

A fundamental understanding of the factors which influence binding performance is critical to any technology or methodology relying on molecular recognition of a specific target species. For the Army, there is a growing need for a basic understanding of these interactions with traditional recognition elements (e.g., antibodies) in non-traditional environmental conditions, such as with new and emerging threats. There is a similar need for building a base of knowledge on non-traditional affinity ligands that are biomimetic or biosynthetic in nature. In this paper, specific research at the Army Research Laboratory towards the development, evaluation and use of synthetic affinity ligands for sensing applications is discussed. This includes the results of our investigations of aptamer-based affinity ligands targeting Campylobacter jejuni. Using capillary electrophoretic techniques, the relative binding affinities of the aptamer ligands towards the target pathogen as well as the degree of cross-reactivity with other food borne-pathogens (i.e., Escherichia coli O157:H7 and Salmonella typhimurium) were evaluated. Current progress towards the development of synthetic affinity ligands for sensing applications will also be discussed.

In this paper we describe BioLert II, an ultraviolet laser induced fluorescence (LIF) biological agent monitor for detecting low concentrations of pathogens amid the ambient aerosol. BioLert II measures the fluorescence intensity and size of individual particles, and computes the Degree of Threat (DoT), an indicator of the likelihood that a particular threat material has appeared amid the recently sampled aerosol background. Performance is quantified using Receiver Operating Characteristic (ROC) curves, which plot the relationship among threat concentration, probability of detection, and false alert rate. We present BioLert II ROC curves for the detection of several simulated biological agents in an environment of interest.