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This paper describes the development of acousto-optic tunable filter (AOTF) devices that are fabricated using in-house grown, high-quality single crystals of mercurous bromide (Hg2Br2). The Hg2Br2 crystals were grown using physical vapor transport (PVT). The quality of the Hg2Br2 single crystals are determined using high-resolution x-ray diffraction (HRXRD). The full width at half maximum (FWHM) of the (220) reflection was found to be 0.029 degrees, which is a significant improvement in the growth of Hg2Br2 bulk single crystals. The diffraction efficiencies of the fabricated AOTF device in the long wavelength infrared (LWIR) found to be 26% which is the highest reported. The device was tested for point detection and for imaging capabilities in the LWIR range. The study shows promising results using Hg2Br2 in LWIR AOTF-based technologies.

Mercury telluride colloidal quantum dots (CQD) hold potential for the fabrication of IR devices that operate in the range of near IR, through short-, mid-, and long wavelength (NIR, SWIR, MWIR, and LWIR, respectively). We synthesized a variety of colloidal HgTe QDs using the wet technique in a non-coordinating environment. Both a standard synthesis technique (mixing Hg and Te precursors and letting the nanocrystals grow and develop) and a more complex technique involving the controlled intermittent addition of precursors were applied. CQDs with sizes up to 20–30 nm were grown, although materials with sizes well above 10 nm did not show a distinct excitonic absorption peak. Our synthesized CQDs were used to fabricate photoconductive devices and measure their photoresponse. We present the synthesis techniques used in this work, photoconductive device fabrication and characterization. Devices with quantum efficiency of about 12.5% at a 4 V bias were obtained.

Single crystals of mercurous halide were grown by physical vapor transport method (PVT). The orientation and the crystalline quality of the grown crystals were determined using high resolution x-ray diffraction (HRXRD) technique. The full width at half maximum (FWHM) of the grown mercurous bromide crystals was measured to be 0.13 degrees for (004) reflection, which is the best that has been achieved so far for PVT grown mercurous halide single crystals. The extended defects of the crystals were also analyzed using high resolution x-ray diffraction topography. Preliminary studies were carried out to evaluate the performance of the crystals on acousto-optic modulator (AOM) and gamma-ray detector applications. The results indicate the grown mercurous halide crystals are excellent materials for acousto-optic modulator device fabrication. The diffraction efficiencies of the fabricated AOM device with 1152 and 1523 nm wavelength lasers polarizing parallel to the acoustic wave were found to be 35% and 28%, respectively. The results also indicate the grown crystals are a promising material for gamma-ray detector application with a very high energy resolution of 1.86% FWHM.

Mercurous halides; mercurous iodide (Hg2I2), mercurous bromide (Hg2Br2) and mercurous chloride (Hg2Cl2) are high figure of merit materials for fabricating Acousto-optic (AO) devices that operate in the visible and infrared regions. Single crystals of mercurous halides were grown by physical vapor transport (PVT) method. Thermal expansion as well as the effect of annealing on the material are discussed. Mercurous halides show positive thermal expansion along "a" axis whereas no significant thermal expansion along "c" axis. The coefficients of thermal expansion of Hg2Cl2, Hg2Br2 and Hg2I2 are 6.72 × 10-5 °C-1, 6.44× 10-5 °C-1 and 6.08 × 10-5 °C-1, respectively. The optical band gap of Hg2Cl2 was calculated using the transmission spectra as 2.9 eV.

HgTe and PbS colloidal quantum dots (CQD) with first excitonic absorption peak of about 2 μm and shorter (down to about 1 μm) have been synthesized and characterized. The synthesized CQDs were characterized using FTIR spectroscopy and TEM technique. The nanomaterials were tested for photo-electrical properties with photoconductive (PC) devices. The devices were fabricated by drop-casting a suspension of the CQDs on the fanout, followed by solid state ligand exchange (SSLE) process, and then spectral and electrical photoresponse of the device were measured. The SSLE process was evaluated thru absorption spectra of test samples. The device fabrication parameters were the number of deposited layers, the thickness of individual layers, the type of the substituting ligand, and the ligand exchange duration. For selected devices external quantum efficiency (EQE) was also determined.

An acousto-optic devices were designed and fabricated using high quality single crystals of mercurous halide (Hg2X2) that were grown by physical vapor transport method (PVT). The orientation and the crystalline quality of the grown crystals were determined using high resolution x-ray diffraction (HRXRD) technique. The full width at half maximum (FWHM) of the grown mercurous bromide (Hg2Br2) crystals was measured to be 0.13 degrees for (004) reflection, which is the best that has been achieved so far for PVT grown mercurous halide single crystals. The extended defects of the crystals were also analyzed using high resolution x-ray diffraction topography. Preliminary studies were carried out to evaluate the performance of the crystals on acousto-optic modulator (AOM) and acousto-optic tunable filter (AOTF) applications. The results indicate the grown mercurous halide crystals are excellent materials for acousto-optic modulator as well as acousto-optic tunable filter device fabrications. The diffraction efficiencies of the fabricated AOM device with 1152 and 1523nm wavelength lasers polarizing parallel to the acoustic wave were found to be 35% and 28%, respectively. The diffraction efficiencies of the fabricated AOTF device with 10600 nm wavelength laser found to be 26%.

DNA is generally associated with the storage of genetic information. However, in many ways, it is also an ideal building material. The shape of a DNA structure is determined by the sequences of the DNA strands within the structure. DNA origami [1] has recently evolved as a method for producing programmable structures at the nanoscale. In a DNA origami, a long single-stranded DNA molecule is folded and held in place with shorter DNA strands. This process can be visualized by taking a very long tube or hose and folding it into a desired shape. Smaller strands of the same material can then be used to tie the large tube into a space-filling structure. In the case of DNA origami the shorter strands are called staples. The staples crosslink and stabilize the entire structure, enabling the formation of complex and programmable 2-D and 3-D shapes. Structures with considerable complexity can be designed and produced.

This study investigated influences encouraging active music engagement beyond the high school and college years among nonmusic majors who are actively engaged in music. A web survey yielded a 50% response rate ( N = 476) from nonmajor students enrolled in performing organizations at a large Midwestern public university, whose responses addressed music activities in and out of school environments, influences on starting and continuing participation during high school and college, and whether ensemble directors promoted continued engagement. Results indicated high amounts of intrinsic motivation in both settings and active diverse curricular and noncurricular participation in music during high school. However, respondents indicated limited music activity outside of the college ensemble; indeed, a majority said they would not have sought a way to continue had it not been for the availability of a university ensemble that welcomed nonmajors. High school directors provided more encouragement to continue than college directors.

Multispectral and hyperspectral imaging in the long wave infrared (LWIR) spectral region has numerous applications in agriculture, astronomy20-22, medicine, and the sensing of dangerous chemical/biological agents23-25. One of the challenges of developing a spectral imaging system in the LWIR is the availability of spectral filters. We will report on three different design methods for realizing spectral filters in the LWIR. The first is an all-dielectric reflection filter based on the guidedmode resonance response. The second is a spatially-varying plasmonic structure that can be used to synthesize complicated spectral reflectance. The third is a Fabry-Perot design for tunable transmission. Numerical and experimental results will be presented.

Low-cost and portable gas chromatography-ion mobility spectrometry (GC-IMS) has been used to identify chemicals. To accomplish this, two parameters are used. The first parameter relates to the GC retention time (RT), which is the residence time of an analyte as it passes through the column. Different chemicals have different RTs. The second parameter is the drift time of ionized species derived for a specific chemical in the IMS. Due to molecular cross section, mass, and chemical properties, different chemicals produce ionized species with different drift times. Combining these two parameters, GC-IMS has been shown to distinguish between different chemicals. Chemical detection and identification are not that easy in practice. First, the concentration of chemicals may be very low, and it may be difficult to determine the chromatographic RT and IMS drift time for chemicals under these conditions. Second, the specific ionized species produced in the IMS are concentration dependent and the IMS spectra obtained at different analyte concentrations are not easily predictable. For example, at low concentrations, chemicals seldom form dimers following atmospheric pressure ionization. The possible presence of either monomers or dimers in the IMS drift tube may confuse the chemical classification process. Third, it is important to estimate the concentration of chemicals, as this information will provide toxicity, and the linear dynamic range of typical IMS systems is relatively low In this study, an image processing approach to enhancing the GC-IMS signal quality is introduced. The key idea in this approach is to treat GC-IMS data as an image and then apply an anomaly detector to detect and enhance abnormal regions in the image. The results of a study that compares a conventional approach to chemical detection and the introduced image enhancement approach are presented. Receiver operating characteristics curves were used to compare the detection performances of the two approaches.

The three most important desirable features in the search for room temperature semiconductor detector (RTSD) candidate as an alternative material to current commercially off-the-shelf (COTS) material for gamma and/or thermal neutron detection are: low cost, high performance and long term stability. This is especially important for pager form application in homeland security. Despite years of research, no RTSD candidate so far can satisfy the above 3 features simultaneously. In this work, we show that mercurous halide materials Hg2X2 (X= I, Cl, Br) is a new class of innovative compound semiconductors that is capable of delivering breakthrough advances to COTS radiation detector materials. These materials are much easier to grow thicker and larger volume crystals. They can detect gamma and potentially neutron radiation making it possible to detect two types of radiation with just one crystal material. The materials have wider bandgaps (compared to COTS) meaning higher resistivity and lower leakage current, making this new technology more compatible with available microelectronics. The materials also have higher atomic number and density leading to higher stopping power and better detector sensitivity/efficiency. They are not hazardous so there are no environmental and health concerns during manufacturing and are more stable making them more practical for commercial deployment. Focus will be on Hg2I2. Material characterization and detector performance will be presented and discussed. Initial results show that an energy resolution better than 2% @ 59.6 keV gamma from Am-241 and near 1% @ 662 keV from Cs-137 source can be achieved at room temperature.

Due to recent advances in hyperspectral imaging sensors many subtle unknown signal sources that cannot be resolved by multispectral sensors can be now uncovered for target detection, discrimination, and identification. Because the information about such sources is generally not available, automatic target recognition (ATR) presents a great challenge to hyperspectral image analysts. Many approaches developed for ATR are based on second-order statistics in the past years. This paper investigates ATR techniques using high order statistics. For ATR in hyperspectral imagery, most interesting targets usually occur with low probabilities and small population and they generally cannot be described by second-order statistics. Under such circumstances, using high-order statistics to perform target detection have been shown by experiments in this paper to be more effective than using second order statistics. In order to further address a challenging issue in determining the number of signal sources needed to be detected, a recently developed concept of virtual dimensionality (VD) is used to estimate this number. The experiments demonstrate that using high-order statistics-based techniques in conjunction with the VD to perform ATR are indeed very effective

The normal mode frequencies and corresponding vibrational assignments of hexachloro-cyclopentadiene (HCP) in C 2v symmetry are examined theoretically using the Gaussian 98 set of quantum chemistry codes. All normal modes were successfully assigned to one of five types of motion (CC stretch, CC stretch, CCl stretch, CCl bend, and CCC bend) predicted by a group theoretical analysis. By comparing the calculated vibrational frequencies with IR and Raman spectra available in the literature, a set of correction factors is derived. Theoretical IR and Raman intensities are reported. Molecular orbitals and bonding are examined.

The structure, bonding, electron distribution, normal mode frequencies and the corresponding vibrational assignments of tetrarsenic tetrasulfide (As4S4) in D2d symmetry are examined theoretically using the gaussian 98 set of quantum chemistry codes at the HF, MP2 and B3LYP(DFT) levels of theory using the standard 6-311G* basis. By comparison to experimental normal mode frequencies deduced by Chapman [Spectrochim. Acta 24A(1968)1687] correction factors for predominant vibrational motions are determined and compared. Normal modes were decomposed into four nonredundant motions {As– As stretch, As– S stretch, As–S–As bend, and As–S–As wagging modes}.

Dendrimers are highly branched, tree-like polymers that possess precise size and shape, as well as surface groups. Among them, polyamidoamine dendrimers are the most widely studied, water-soluble/biocompatable dendritic macromolecules. Such dendrimers have exploited for interesting applications in immunodiagnostics, magnetic resonance imaging, gene therapy, and drug delivery. In this paper, a new signal amplification strategy using dendrimers will be introduced. While only one fluorescein group can be linked onto an antibody molecule, a large number of fluorophores can be attached to an antibody through a dendrimer linker molecule, thus forming a water-soluble fluorescein-dendrimer-antibody bioconjugate. Upon addition of the antigen, enhanced fluorescence signals are obtained when compared with the corresponding fluorescein-antibody analogs.

Developing methods for alternative testing is increasingly important due to dwindling funding resources and increasing costs associated with animal testing and legislation. We propose to test the feasibility of a new and novel method for detecting DNA mutagenesis using millimeter wave spectroscopy. Although millimeter wave spectroscopy has been known since the 1950s, the cost was prohibitive and studies did not extend to large biological proteins such as DNA. Recent advances have made this technology feasible for developing laboratory and field equipment. We present preliminary findings for lesion-induced vibrational modes in DNA observed from 80 to 1000 gigahertz (GHz). These findings suggest that there are vibrational modes that can be used as identification resonances. These modes are associated with localized defects of the DNA polymers. They are unique for each defect/lesion, and should be easy to detect. We described a field-detecting detector based on the local modes.

We attempt to interpret the fluorescence of dipicolinic acid(2,6-pyridinedicarboxylic acid) and its ion by performing 6 in 6 complete active space MCSCF computations with the gaussian 92 program package using a 6-31G basis set. We report optimized geometries, charge densities, energies and vibrational frequencies for the ground state and first excited singlet state of dipicolinic acid and its ion. The theoretical results are used to predict and interpret the fluorescence of the acid and ion. It is argued that the results are relevant to the study of bacterial spores.

This article examines the responsibilities and roles of higher education in fostering musically engaged adults by exploring three primary contexts: (a) the adult population within the university; (b) the adult population in the community in which the university resides; and (c) the interactive university-community adult population. Adults whose lives are enriched through musical engagement are more likely to have the passion and the power to advocate for, and facilitate musical engagement for others.

Raman chemical imaging microspectroscopy (RCIM) is being evaluated as a technology for waterborne pathogen detection. Binary and ternary mixtures including combinations of polystyrene beads, Grampositive Bacillus anthracis and B. atrophaeus spores, B. cereus vegetative cells, and Gram-negative E. coli cells were investigated by RCIM for differentiation and characterization purposes. We have demonstrated the ability of RCIM, in combination with Pearson's cross correlation and multivariate principal components analysis data reduction techniques, to differentiate these components in the same field of view (FOV). Conventional applications of RCIM consist of differentiating relatively broad areas in a FOV. Here, RCIM is expanded in its capabilities to differentiate and distinguish between different micron size species in single particles and clusters of mixed species.

Raman spectroscopy is being evaluated as a candidate technology for waterborne pathogen detection. We have investigated the impact of key experimental and background interference parameters on the bacterial species level identification performance of Raman detection. These parameters include laser-induced photodamage threshold, composition of water matrix, and organism aging in water. 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 (formerly Bacillus globigii, BG) vegetative cells, 2800 W/cm2 for BG spores, and 3500 W/cm2 for Gram-negative E. coli (EC) organisms. In general, Bacillus spore microorganism preparations may be irradiated with higher laser power densities than the equivalent Bacillus vegetative preparations. In order to evaluate the impact of background interference and organism aging, we selected a biomaterials set comprising Gram-positive (anthrax simulants) organisms, Gram-negative (plague simulant) organisms, and proteins (toxin simulants) and constructed a Raman signature classifier that identifies at the species level. Subsequently, we evaluated the impact of tap water and storage time in water (aging) on the classifier performance when characterizing B. thuringiensis spores, BG spores, and EC cell preparations. In general, the measured Raman signatures of biological organisms exhibited minimal spectral variability with respect to the age of a resting suspension and water matrix composition. The observed signature variability did not substantially degrade discrimination performance at the genus and species levels. In addition, Raman chemical imaging spectroscopy was used to distinguish a mixture of BG spores and EC cells at the single cell level.

For the first time, we have identified eighteen new absorption peaks from Malathion which is used as a simulant for VX nerve agent in a spectral range from 15 to 6000 wave numbers.

Raman chemical imaging microscopy was used to visualize and discriminate between biological substances with Raman spectral database identification. Water suspensions were investigated for mixtures of different concentrations of E. coli and Bacillus subtilis spores.

Raman microspectroscopy is investigated for spectral information from bacteria and protein biological substances in distilled and tap water matrices. Laser energy flux, multivariate dataspace biological differentiation, and substance aging in water matrices were investigated.

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 investigat ed 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 t ogether 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 togeth er by PCA. A mixture of Gram-positive Bacillus atrophaeus spores and Gram-negative E. coli cells were differentiated and distinguished by RCIM. Index Headings: Raman chemical imag ing microspectroscopy; Bacillus atrophaeus ; E. coli ; Principal components analysis; Water matrix; Biological discrimination; Bacteria; Recipe tap water.

Under the U.S. Army sponsored Joint Service Agent Water Monitor (JSAWM) program, developing hand-held assays using tickets for chemical/biological agent detection has been of major interest. One of keys to success is to develop detection algorithms that not only can effectively detect the presence of various agents, but also can quantify the detected agents. This paper presents a recent development of detection software that can perform 3-dimensional (3D) receiver operating characteristics (ROC) analysis which is based on quantified agent concentration. The ROC curves have been widely used in communications, signal processing and medical communities to evaluate the effectiveness of a detection technique. It generally formulates a signal detection problem as a binary composite hypothesis testing problem with the null hypothesis and the alternative hypothesis represents the case of no signal and the case of signal presence respectively. The ROC curve is then plotted based on the detection probability (power) P D versus the false alarm probability, P F . Unfortunately, such a two-dimensional (2D) (P D ,P F )-based ROC curve does not factor in the concentration detected in an agent signal which is a crucial parameter in chemical/biological agent detection. The proposed 3D ROC analysis is developed from such a need. It includes an additional parameter, referred to as threshold t, which is used to threshold the detected agent signal concentration. Consequently, a different value of t results in a different 2D ROC curve. In order to take into account the thresholding factor t, a 3D ROC curve is derived and plotted based on three parameters, (P D ,P F ,t). As a result of the 3D ROC curve, three 2D ROC curves can be also derived. One is the conventional 2D (P D ,P F )-ROC curve. Another is a 2D (P D ,t)-ROC curve which describes the relationship between P D and the threshold value t. A third one is a 2D (P F ,t)-ROC curve which shows the effect of the threshold value t on P F . The utility of the proposed 3D ROC analysis will be demonstrated by the detection software developed by the UMBC for the tickets used in HHA for water monitoring.

The US Army Joint Service Agent Water Monitor (JSAWM) program is currently interested in an approach that can implement a hardware- designed device in ticket-based hand-held assay (currently being developed) used for chemical/biological agent detection. This paper presents a preliminary investigation of the proof of concept. Three components are envisioned to accomplish the task. One is the ticket development which has been undertaken by the ANP, Inc. Another component is the software development which has been carried out by the Remote Sensing Signal and Image Processing Laboratory (RSSIPL) at the University of Maryland, Baltimore County (UMBC). A third component is an embedded system development which can be used to drive the UMBC-developed software to analyze the ANP-developed HHA tickets on a small pocket-size device like a PDA. The main focus of this paper is to investigate the third component that is viable and is yet to be explored. In order to facilitate to prove the concept, a flatbed scanner is used to replace a ticket reader to serve as an input device. The Stargate processor board is used as the embedded System with Embedded Linux installed. It is connected to an input device such as scanner as well as output devices such as LCD display or laptop etc. It executes the C-Coded processing program developed for this embedded system and outputs its findings on a display device. The embedded system to be developed and investigated in this paper is the core of a future hardware device. Several issues arising in such an embedded system will be addressed. Finally, the proof-of-concept pilot embedded system will be demonstrated.

Hyperspectral image compression can be performed by either 3-D compression or spectral/spatial compression. It has been demonstrated that due to high spectral resolution hyperspectral image compression can be more effective if compression is carried out spectrally and spatially in two separate stages. One commonly used spectral/spatial compression implements principal components analysis (PCA) or wavelet for spectral compression followed by a 2-D/3D compression technique for spatial compression. This paper presents another type of spectral/spatial compression technique, which uses Hyvarinen and Oja's Fast independent component analysis (FastICA) to perform spectral compression, while JPEG2000 is used for 2-D/3-D spatial compression. In order to determine how many independent components are required, a newly developed concept, virtual dimensionality (VD) is used. Since the VD is determined by the false alarm probability rather than the commonly used signal-to-noise ratio or mean squared error (MSE), our proposed FastICA-based spectral/spatial compression is more effective than PCA-based or wavelet-based spectral/spatial compression in data exploitation.

Linear spectral mixture analysis (LSMA) is a widely used technique for subpxiel detection and mixed pixel classification. Due to mathematical tractability it is generally implemented without constraints. However, it has been shown that the constrained LSMA can improve the unconstrained LSMA, specifically in quantification when accurate estimates of abundance fractions are required. When the constrained LSMA is considered, two constraints are generally imposed on abundance fractions, abundance sum-to-one constraint (ASC) and abundance nonnegativity constraint (ANC), referred to as abundance-constrained LSMA (AC-LSMA). A general and common approach to solving the AC-LSMA is to estimate abundance fractions in the sense of least-squares error (LSE) subject to the imposed constraints. Since the LSE is not weighted in accordance with significance of bands, the effect caused by the LSE is assumed to be uniform over all the bands, which is generally not necessarily true. This paper extends the commonly used LSE-based AC-LSMA to weighted LSE-based AC-LSMA with the weighting matrix that is derived from various approaches such as parameter estimation, pattern classification and orthogonal subspace projection (OSP). As demonstrated by experiments, the weighted LSE-based AC-LSMA generally performs better than the commonly used LSE-based AC-LSMA where the latter can be considered a special case of the former with the weighting matrix reduced to the identity matrix.

There is an immediate need for the ability to detect, identify and quantify chemical and biological agents in water supplies during water point selection, production, storage, and distribution to consumers. Through a U.S. Army sponsored Joint Service Agent Water Monitor (JSAWM) program, based on hand-held assays that exist in a ticket format, we are developing new algorithms for automatic processing of tickets. In previous work, detection of control dots in the tickets was carried out by traditional image segmentation approaches such as Otsu's method and other entropy-based thresholding techniques. In experiments, it was found that the approaches above were sensitive to illumination effects in the camera reader. As a result, more robust, object-oriented approaches to detect the control dots are required. Mathematical morphology is a powerful technique for image analysis that focuses on the size and shape of the objects in the scene. In this work, we describe a novel application of morphological operations in identification of control dots in hand held assay ticket imagery. Such images were pre-processed by a light compensation algorithm prior to morphological analysis. The performance of the proposed approach is evaluated using Receiving Operating Characteristics (ROC) analysis.

Kalman filter has been widely used in statistical signal processing for parameter estimation. Although a Kalman filter approach has been recently developed for spectral unmixing, referred to as Kalman filter-based linear unmixing (KFLU), its applicability to spectral characterization within a single pixel vector has not been explored. This paper presents a new application of Kalman filtering in spectral estimation and quantification. It develops a Kalman filter-based spectral signature esimator (KFSSE) which is different from the KFLU in the sense that the former performs a Kalman filter wavelength by wavelength across a spectral signature as opposed to the latter which implements a Kalman filter pixel vector by pixel vector in an image cube. The idea of the KFSSE is to implement the state equation to characterize the true spectral signature, while the measurement equation is being used to describe the spectral signature to be processed. Additionally, since a Kalman filter can accurately estimate spectral abundance fraction of a signature, our proposed KFSSE can further used for spectral quantification for subpixel targets and mixed pixel vectors, called Kalman filter-based spectral quantifier (KFSQ). Such spectral quantification is particularly important for chemical/biological defense which requires quantification of detected agents for damage control assessment. Several different types of hyperspectral data are used for experiments to demonstrate the ability of the KFSSE in estimation of spectral signature and the utility of the KFSQ in spectral quantification.

Fisher's linear discriminant analysis (FLDA) has been widely used in pattern classification due to its criterion, called Fisher's ratio, based on the ratio of between-class variance to within-class variance. Recently, a linear constrained discriminant analysis (LCDA) was developed for huperspectral image classification where Fisher's ratio was replaced with the ratio of inter-distance to intra-distance and the target signatures were constrained to orthogonal directions. This paper directly extends the FLDA to constrained Fisher's linear discriminant analysiss (CFLDA), which uses Fisher's ratio as a classification criterion. Since CFLDA is supervised which requires a set of training samples, this paper further extends the CFLDA to an unsupervised CFLDA (UCFLDA) by including a new unsupervised training sample generation algorithm to automatically produce a sample pool of training data to be used for CFLDA. In order to determine the number of classes, p, to be classified, a newly developed concept, called virtual dimensionality (VD) is used to estimate the p where a Neyman-Pearson-based eigen-analysis approach developed by Harsanyi, Farrand and Chang, called noise-whitened HFC (NWHFC)'s method, is implemented to find the VD. The experimental results have shown that the proposed UCFLDA perform effectively for HYDICE data and provides a promising unsupervised classification technique for hyperspectral imagery.

Unsupervised image classification for remotely sensed imagery is very challenging due to the fact that the unknown image background generally varies with a wide range of spectral deviations. Additionally, spectral similarity among subtle small calsses also causes tremendous difficulty in classification. This paper investigates three major issues, (1) image background removal, (2) generation of training sample data, (3) determination of the number of classes to be classified, p which are encountered in unsupervised image classification. The study on these three issues is conducted via a well-known Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) image scene, Indiana Pine test site available online at Purdue University's website. Since image background varies with different applications, it is generally difficult to perform background removal without prior knowledge. In order for unsupervised classification to be effective, a good set of training data is also necessary. These training samples must be generated directly from the image data in an unsupervised manner. This paper develops an unsupervised training sample generation algorithm (UTSGA) that can generate a good sample pool of training data for supervised classification. In determining p, a newly developed concept, called virtual dimensionality (VD) is used to estimate the p where a Neyman-Pearson-based eigen-analysis approach developed by Harsanyi, Farrand and Chang, called noise-whitened HFC (NWHFC)'s method, is implemented to find the VD to be used for the p. Finally, an unsupervised image classification algorithm can be derived by implementing a supervised classifier in conjunction with teh UTSGA algorithm and NWHFC's method.

Pyrolysis-Gas Chromatography-Ion Mobility Spectrometry (Py-GC-IMS) has been used to detect chemical resident in water by obtaining the characteristic information on the structure and molecular weight. It is a great challenge to analyze this 2-dimensional signal because the noise is not stationary. In this paper, one approach has been designed to remove noise baseline and suppress noise power. The provided data is used for analyze the improvement under controlled experiment. Receiver Operating Characteristic (ROC) curve is also used to analyze the performance and it shows the proposed method improves the detection results.

The normal mode frequencies and corresponding vibrational assignments of trimethylarsine oxide are examined theoretically using the Gaussian 98 set of quantum chemistry codes. All normal modes were successfully assigned to one of eight types of motion (As-C stretch, As=O stretch, C-H stretch, C-As-C bend, As=O bend, H-C-H bend, CH3 wag, and CH3 twist) utilizing the C3v symmetry of the molecule. Calculations were performed at the Hartree-Fock, DFT(B3LYP), and MP2 levels of theory using the standard 6-311G** basis. Calculated infrared intensities and Raman activities are reported.

A detailed investigation of phonon modes in DNA macromolecules is presented. This work presents experimental evidence to confirm the presence of multiple dielectric resonances in the submillimeter-wave spectra (i.e., \ensuremath{\sim}0.01\char21{}10 THz) obtained from DNA samples. These long-wave (i.e., \ensuremath{\sim}1\char21{}30 ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}1}$) absorption features are shown to be intrinsic properties of the particular DNA sequence under study. Most importantly, a direct comparison of spectra between different DNA samples reveals a large number of modes and a reasonable level of sequence-specific uniqueness. This work establishes the initial foundation for the future use of submillimeter-wave spectroscopy in the identification and characterization of DNA macromolecules.

Antibodies, peptides, and enzymes are often used as molecular recognition elements in chemical and biological sensors. However, their lack of stability and signal transduction mechanisms limits their use as sensing devices. Recent advances in the field of molecularly imprinted polymers (MIPs) have created synthetic materials that can mimic the function of biological receptors but with less stability constraints. These polymers can provide high sensitivity and selectivity while maintaining excellent thermal and mechanical stability. To further enhance the advantages of the traditional imprinted polymer approach, an additional fluorescent component has been introduced into these polymers. Such a component provides enhanced chemical affinity as well as a method for signal transduction. In this type of imprinted polymer, binding of the target analyte invokes a specific spectral signature from the reporter molecule. Previous work has provided molecularly imprinted polymers that are selective for the hydrolysis products of organophosphorus species such as the nerve agents sarin and soman. (A. L. Jenkins, O. M. Uy and G. M. Murray, Anal. Chem., 1999, 71, 373). In this paper the direct imprinting of non-hydrolyzed organophosphates including pesticides and insecticides is described. Detection limits for these newly developed MIP sensors are less than 10 parts per trillion (ppt) with long linear dynamic ranges (ppt to ppm) and response times of less than 15 min.

Dwindling research and development funds coupled with increasing customer demands and rapidly developing technologies present a difficult dilemma to systems developers. A current area of innovation is the integration of the abundant but diverse computer resources (both hardware and software) into practical and powerful computing environments to support the product development processes in the industrial and defense sectors. Edgewood has leveraged a number of existing resources to create a `virtual prototyping' environment based on the principles of Concurrent Multi-Level Simulation. We named our environment the `Computational Prototyping Network'.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

This report computes the vibrational frequencies of seven amines. Experimental data are available for four of these molecules: trimethylamine, diethylmethylamine, bis(2-chloroethyl)methylamine, and triethylamine. The ratios are determined between the experimental and the computed frequencies of these molecules. The ratios are then used to derive a set of effective correction factors for the various vibrational modes. The vibrational frequencies are computed for three other tertiary amines: tris(chloromethyl) amine, tris(2- chloroethyl)amine (HN3), and bis(2-chloroethyl) ethylamine (HN1). The computed frequencies, the corresponding intensities, and the corrected frequencies are reported here. The authors emphasize that the correction factors are valid only for 3-21G computations.