The use of FT-IR as a screening technique for organic residue analysis of archaeological samples

A range of archaeological samples have been examined using FT-IR spectroscopy. These include suspected coprolite samples from the Neolithic site of Catalhoyuk in Turkey, pottery samples from the Roman site of Silchester, UK and the Bronze Age site of Gatas, Spain and unidentified black residues on pottery sherds from the Roman sites of Springhead and Cambourne, UK. For coprolite samples the aim of FT-IR analysis is identification. Identification of coprolites in the field is based on their distinct orange colour; however, such visual identifications can often be misleading due to their similarity with deposits such as ochre and clay. For pottery the aim is to screen those samples that might contain high levels of organic residues which would be suitable for GC-MS analysis. The experiments have shown coprolites to have distinctive spectra, containing strong peaks from calcite, phosphate and quartz; the presence of phosphorus may be confirmed by SEM-EDX analysis. Pottery containing organic residues of plant and animal origin has also been shown to generally display strong phosphate peaks. FT-IR has distinguished between organic resin and non-organic compositions for the black residues, with differences also being seen between organic samples that have the same physical appearance. Further analysis by CC-MS has confirmed the identification of the coprolites through the presence of coprostanol and bile acids, and shows that the majority of organic pottery residues are either fatty acids or mono- or di-acylglycerols from foodstuffs, or triterpenoid resin compounds exposed to high temperatures. One suspected resin sample was shown to contain no organic residues. and it is seen that resin samples with similar physical appearances have different chemical compositions. FT-IR is proposed as a quick and cheap method of screening archaeological samples before subjecting them to the more expensive and time-consuming method of GC-MS. This will eliminate inorganic samples such as clays and ochre from CC-MS analysis, and will screen those samples which are most likely to have a high concentration of preserved organic residues. (C) 2008 Elsevier B.V. All rights reserved.

Evaluation of the model representation of the evolution of convective systems using satellite observations of outgoing longwave radiation

We introduce a technique for assessing the diurnal development of convective storm systems based on outgoing longwave radiation fields. Using the size distribution of the storms measured from a series of images, we generate an array in the lengthscale-time domain based on the standard score statistic. It demonstrates succinctly the size evolution of storms as well as the dissipation kinematics. It also provides evidence related to the temperature evolution of the cloud tops. We apply this approach to a test case comparing observations made by the Geostationary Earth Radiation Budget instrument to output from the Met Office Unified Model run at two resolutions. The 12km resolution model produces peak convective activity on all lengthscales significantly earlier in the day than shown by the observations and no evidence for storms growing in size. The 4km resolution model shows realistic timing and growth evolution although the dissipation mechanism still differs from the observed data.

Mapping and controlling molecular processes: The application of control theory and system identification algorithms to ASOPS and other fast pulse spectroscopies

Asynchronous Optical Sampling (ASOPS) [1,2] and frequency comb spectrometry [3] based on dual Ti:saphire resonators operated in a master/slave mode have the potential to improve signal to noise ratio in THz transient and IR sperctrometry. The multimode Brownian oscillator time-domain response function described by state-space models is a mathematically robust framework that can be used to describe the dispersive phenomena governed by Lorentzian, Debye and Drude responses. In addition, the optical properties of an arbitrary medium can be expressed as a linear combination of simple multimode Brownian oscillator functions. The suitability of a range of signal processing schemes adopted from the Systems Identification and Control Theory community for further processing the recorded THz transients in the time or frequency domain will be outlined [4,5]. Since a femtosecond duration pulse is capable of persistent excitation of the medium within which it propagates, such approach is perfectly justifiable. Several de-noising routines based on system identification will be shown. Furthermore, specifically developed apodization structures will be discussed. These are necessary because due to dispersion issues, the time-domain background and sample interferograms are non-symmetrical [6-8]. These procedures can lead to a more precise estimation of the complex insertion loss function. The algorithms are applicable to femtosecond spectroscopies across the EM spectrum. Finally, a methodology for femtosecond pulse shaping using genetic algorithms aiming to map and control molecular relaxation processes will be mentioned.

Expression of metallothionein genes I and II in bank vole clethrionomys glareolus populations chronically exposed in situ to heavy metals

The expression of two metallothionein genes (Mt-I and Mt-II) in the liver, kidney, and gonad of bank voles collected at four metal-contaminated sites (Cd, Zn, Pb, and Fe) were measured using the quantitative real-time PCR method (QPCR). Relative Mt gene expression was calculated by applying a normalization factor (NF) using the expression of two housekeeping genes, ribosomal 18S and beta-actin. Relative Mt expression in tissues of animals from contaminated sites was up to 54.8-fold higher than those from the reference site for Mt-I and up to 91.6-fold higher for Mt-II. Mt-II gene expression in the livers of bank voles from contaminated sites was higher than Mt-I gene expression. Inversely, Mt-II expression in the kidneys of voles was lower than Mt-I expression. Positive correlations between cadmium levels in the tissues and Mt-I were obtained in all studied tissues. Zinc, which undergoes homeostatic regulation, correlated positively with both Mt-I and Mt-II gene expression only in the kidney. Results showed that animals living in chronically contaminated environments intensively activate detoxifying mechanisms such as metallothionein expression. This is the first time that QPCR techniques to measure MT gene expression have been applied to assess the impact of environmental metal pollution on field collected bank voles.

Metallothionein I and II gene expression as a response to metal contamination in bank vole Clethrionomys glareolus

The expression of two metallothionein genes (Mt-I and Mt-II) in the liver, kidney, and gonad of bank voles collected at four metal-contaminated sites (Cd, Zn, Pb, and Fe) were measured using the quantitative real-time PCR method (QPCR). Relative Mt gene expression was calculated by applying a normalization factor (NF) using the expression of two housekeeping genes, ribosomal 18S and beta-actin. Relative Mt expression in tissues of animals from contaminated sites was up to 54.8-fold higher than those from the reference site for Mt-I and up to 91.6-fold higher for Mt-II. Mt-II gene expression in the livers of bank voles from contaminated sites was higher than Mt-I gene expression. Inversely, Mt-II expression in the kidneys of voles was lower than Mt-I expression. Positive correlations between cadmium levels in the tissues and Mt-I were obtained in all studied tissues. Zinc, which undergoes homeostatic regulation, correlated positively with both Mt-I and Mt-II gene expression only in the kidney. Results showed that animals living in chronically contaminated environments intensively activate detoxifying mechanisms such as metallothionein expression. This is the first time that QPCR techniques to measure MT gene expression have been applied to assess the impact of environmental metal pollution on field collected bank voles.

Pulse shaping using state space algorithms

We discuss the use of pulse shaping for optimal excitation of samples in time-domain THz spectroscopy. Pulse shaping can be performed in a 4f optical system to specifications from state space models of the system's dynamics. Subspace algorithms may be used for the identification of the state space models.

State-space model identification of a wireless THz network

We model the large scale fading of wireless THz communications links deployed in a metropolitan area taking into account reception through direct line of sight, ground or wall reflection and diffraction. The movement of the receiver in the three dimensions is modelled by an autonomous dynamic linear system in state-space whereas the geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a Wiener model from time-domain measurements of the field intensity.

Classification of lactose and mandelic acid THz spectra using subspace and wavelet-packet algorithms

This work compares classification results of lactose, mandelic acid and dl-mandelic acid, obtained on the basis of their respective THz transients. The performance of three different pre-processing algorithms applied to the time-domain signatures obtained using a THz-transient spectrometer are contrasted by evaluating the classifier performance. A range of amplitudes of zero-mean white Gaussian noise are used to artificially degrade the signal-to-noise ratio of the time-domain signatures to generate the data sets that are presented to the classifier for both learning and validation purposes. This gradual degradation of interferograms by increasing the noise level is equivalent to performing measurements assuming a reduced integration time. Three signal processing algorithms were adopted for the evaluation of the complex insertion loss function of the samples under study; a) standard evaluation by ratioing the sample with the background spectra, b) a subspace identification algorithm and c) a novel wavelet-packet identification procedure. Within class and between class dispersion metrics are adopted for the three data sets. A discrimination metric evaluates how well the three classes can be distinguished within the frequency range 0. 1 - 1.0 THz using the above algorithms.

Comparison of extrasystolic ECG signal classifiers using discrete wavelet transforms

This work compares and contrasts results of classifying time-domain ECG signals with pathological conditions taken from the MITBIH arrhythmia database. Linear discriminant analysis and a multi-layer perceptron were used as classifiers. The neural network was trained by two different methods, namely back-propagation and a genetic algorithm. Converting the time-domain signal into the wavelet domain reduced the dimensionality of the problem at least 10-fold. This was achieved using wavelets from the db6 family as well as using adaptive wavelets generated using two different strategies. The wavelet transforms used in this study were limited to two decomposition levels. A neural network with evolved weights proved to be the best classifier with a maximum of 99.6% accuracy when optimised wavelet-transform ECG data wits presented to its input and 95.9% accuracy when the signals presented to its input were decomposed using db6 wavelets. The linear discriminant analysis achieved a maximum classification accuracy of 95.7% when presented with optimised and 95.5% with db6 wavelet coefficients. It is shown that the much simpler signal representation of a few wavelet coefficients obtained through an optimised discrete wavelet transform facilitates the classification of non-stationary time-variant signals task considerably. In addition, the results indicate that wavelet optimisation may improve the classification ability of a neural network. (c) 2005 Elsevier B.V. All rights reserved.

Subspace system identification framework for the analysis of multimoded propagation of THz-transient signals

We provide a system identification framework for the analysis of THz-transient data. The subspace identification algorithm for both deterministic and stochastic systems is used to model the time-domain responses of structures under broadband excitation. Structures with additional time delays can be modelled within the state-space framework using additional state variables. We compare the numerical stability of the commonly used least-squares ARX models to that of the subspace N4SID algorithm by using examples of fourth-order and eighth-order systems under pulse and chirp excitation conditions. These models correspond to structures having two and four modes simultaneously propagating respectively. We show that chirp excitation combined with the subspace identification algorithm can provide a better identification of the underlying mode dynamics than the ARX model does as the complexity of the system increases. The use of an identified state-space model for mode demixing, upon transformation to a decoupled realization form is illustrated. Applications of state-space models and the N4SID algorithm to THz transient spectroscopy as well as to optical systems are highlighted.

Wiener-System subspace identification for mobile wireless mm-wave networks

We discuss the feasibility of wireless terahertz communications links deployed in a metropolitan area and model the large-scale fading of such channels. The model takes into account reception through direct line of sight, ground and wall reflection, as well as diffraction around a corner. The movement of the receiver is modeled by an autonomous dynamic linear system in state space, whereas the geometric relations involved in the attenuation and multipath propagation of the electric field are described by a static nonlinear mapping. A subspace algorithm in conjunction with polynomial regression is used to identify a single-output Wiener model from time-domain measurements of the field intensity when the receiver motion is simulated using a constant angular speed and an exponentially decaying radius. The identification procedure is validated by using the model to perform q-step ahead predictions. The sensitivity of the algorithm to small-scale fading, detector noise, and atmospheric changes are discussed. The performance of the algorithm is tested in the diffraction zone assuming a range of emitter frequencies (2, 38, 60, 100, 140, and 400 GHz). Extensions of the simulation results to situations where a more complicated trajectory describes the motion of the receiver are also implemented, providing information on the performance of the algorithm under a worst case scenario. Finally, a sensitivity analysis to model parameters for the identified Wiener system is proposed.

Optimization of apodization functions in terahertz transient spectrometry

A quadratic programming optimization procedure for designing asymmetric apodization windows tailored to the shape of time-domain sample waveforms recorded using a terahertz transient spectrometer is proposed. By artificially degrading the waveforms, the performance of the designed window in both the time and the frequency domains is compared with that of conventional rectangular, triangular (Mertz), and Hamming windows. Examples of window optimization assuming Gaussian functions as the building elements of the apodization window are provided. The formulation is sufficiently general to accommodate other basis functions. (C) 2007 Optical Society of America

MIMO Wiener model identification for large scale fading of wireless mobile communications links

The large scale fading of wireless mobile communications links is modelled assuming the mobile receiver motion is described by a dynamic linear system in state-space. The geometric relations involved in the attenuation and multi-path propagation of the electric field are described by a static non-linear mapping. A Wiener system subspace identification algorithm in conjunction with polynomial regression is used to identify a model from time-domain estimates of the field intensity assuming a multitude of emitters and an antenna array at the receiver end.

Comparison of subspace and ARX models of a waveguide's terahertz transient response after optimal wavelet filtering

A quasi-optical deembedding technique for characterizing waveguides is demonstrated using wide-band time-resolved terahertz spectroscopy. A transfer function representation is adopted for the description of the signal in the input and output port of the waveguides. The time-domain responses were discretized and the waveguide transfer function was obtained through a parametric approach in the z-domain after describing the system with an AutoRegressive with eXogenous input (ARX), as well as with a state-space model. Prior to the identification procedure, filtering was performed in the wavelet domain to minimize both signal distortion, as well as the noise propagating in the ARX and subspace models. The optimal filtering procedure used in the wavelet domain for the recorded time-domain signatures is described in detail. The effect of filtering prior to the identification procedures is elucidated with the aid of pole-zero diagrams. Models derived from measurements of terahertz transients in a precision WR-8 waveguide adjustable short are presented.

Measurement of propagation constant in waveguides with wideband coherent terahertz spectroscopy

A quasi-optical technique for characterizing micromachined waveguides is demonstrated with wideband time-resolved terahertz spectroscopy. A transfer-function representation is adopted for the description of the relation between the signals in the input and output port of the waveguides. The time-domain responses were discretized, and the waveguide transfer function was obtained through a parametric approach in the z domain after describing the system with an autoregressive with exogenous input model. The a priori assumption of the number of modes propagating in the structure was inferred from comparisons of the theoretical with the measured characteristic impedance as well as with parsimony arguments. Measurements for a precision WR-8 waveguide-adjustable short as well as for G-band reduced-height micromachined waveguides are presented. (C) 2003 Optical Society of America.