Fourier transform infrared microspectroscopy as a tool to identify macroalgal propagules

Understanding of macroalgal dispersal has been hindered by the difficulty in identifying propagules. Different carrageenans typically occur in gametophytes and tetrasporophytes of the red algal family Gigartinaceae, and we may expect that carpospores and tetraspores also differ in composition of carrageenans. Using Fourier transform infrared (FT-IR) microspectroscopy, we tested the model that differences in carrageenans and other cellular constituents between nuclear phases should allow us to discriminate carpospores and tetraspores of Chondrus verrucosus Mikami. Spectral data suggest that carposporophytes isolated from the pericarp and female gametophytes contained κ-carrageenan, whereas tetrasporophytes contained λ-carrageenan. However, both carpospores and tetraspores exhibited absorbances in wave bands characteristic of κ-,ι-, and λ-carrageenans. Carpospores contained more proteins and may be more photosynthetically active than tetraspores, which contained more lipid reserves. We draw analogies to planktotrophic and lecithotrophic larvae. These differences in cellular chemistry allowed reliable discrimination of spores, but pretreatment of spectral data affected the accuracy of classification. The best classification of spores was achieved with extended multiplicative signal correction (EMSC) pretreatment using partial least squares discrimination analysis, with correct classification of 86% of carpospores and 83% of tetraspores. Classification may be further improved by using synchrotron FT-IR microspectroscopy because of its inherently higher signal-to-noise ratio compared with microspectroscopy using conventional sources of IR. This study demonstrates that FT-IR microspectroscopy and bioinformatics are useful tools to advance our understanding of algal dispersal ecology through discrimination of morphologically similar propagules both within and potentially between species.

Characterization of supported cylinder-planar germanium waveguide sensors with synchrotron Infrared radiation

Cylinder-planar Ge waveguides are being developed as evanescent-wave sensors for chemical microanalysis. The only non-planar surface is a cylinder section having a 300-mm radius of curvature. This confers a symmetric taper, allowing for direct coupling into and out of the waveguide's 1-mm² end faces while obtaining multiple reflections at the central <30-μm-thick sensing region. Ray-optic calculations indicate that the propagation angle at the central minimum has a strong nonlinear dependence on both angle and vertical position of the input ray. This results in rather inefficient coupling of input light into the off-axis modes that are most useful for evanescent-wave absorption spectroscopy. Mode-specific performance of the cylinder-planar waveguides has also been investigated experimentally. As compared to a blackbody source, the much greater brightness of synchrotron-generated infrared (IR) radiation allows a similar total energy throughput, but restricted to a smaller fraction of the allowed waveguide modes. However, such angle-selective excitation results in a strong oscillatory interference pattern in the transmission spectra. These spectral oscillations are the principal technical limitation on using synchrotron radiation to measure evanescent-wave absorption spectra with the thin waveguides.

Surface-Enhanced Infrared Spectra of Manganese (III) Tetraphenylporphine Chloride Physisorbed on Gold Island Films

Surface-enhanced infrared absorption (SEIRA) spectra of manganese (III) tetraphenylporphine chloride (Mn(TPP)Cl) on metal island films were measured in transmission mode. Dependences of the enhancement factor of SEIRA on both the sample quantity and the type of evaporated metal were investigated by subsequently increasing the amount of Mn(TPP)Cl on gold and silver substrates. The enhancement increases nonlinearly with the amount of sample and varies slightly with the thickness of metal islands. In particular, the SEIRA transmission method presents an anomalous spectral enhancement by a factor of 579, with substantial spectral shifts, observed only for the physisorbed Mn(TPP)Cl that remained on a 3-nm-thick gold film after immersion of the substrates into acetone. A charge-transfer (CT) interaction between the porphyrinic Mn and gold islands is therefore proposed as an additional factor in the SEIRA mechanism of the porphyrin system. The number of remaining porphyrin molecules was estimated by calibration-based fluorescence spectroscopy to be 2.36×1013 molecules (i.e., ~2.910-11 mol/cm2) for a 3-nm-thick gold film, suggesting that the physisorbed molecules distributed very loosely on the metal island surface as a result of the weak van der Waals interactions. Fluorescence microscopy revealed the formation of microcrystalline porphyrin aggregates during the consecutive increase in sample solution. However, the immersion likely redistributed the porphyrin to be directly attached on the gold surface, as evidenced by an absence of porphyrinic microcrystals and the observed SEIRA enhancement. The distinctive red shift in the UV-visible spectra and the SEIRA-enhanced peaks indicate the presence of a preferred orientation in the form of the porphyrin ring inclined with respect to the gold surface.

Thermal analysis of nanofluids in microfluidics using an infrared camera

We present the thermal analysis of liquid containing Al2O3 nanoparticles in a microfluidic platform using an infrared camera. The small dimensions of the microchannel along with the low flow rates (less than 120 μl min−1) provide very low Reynolds numbers of less than 17.5, reflecting practical parameters for a microfluidic cooling platform. The heat analysis of nanofluids has never been investigated in such a regime, due to the deficiencies of conventional thermal measurement systems. The infrared camera allows non-contact, three dimensional and high resolution capability for temperature profiling. The system was studied at different w/w concentrations of thermally conductive Al2O3 nanoparticles and the experiments were in excellent agreement with the computational fluid dynamics (CFD) simulations.

Quantitative determination of fatty acid compositions in micro-encapsulated fish-oil supplements using Fourier transform infrared (FTIR) spectroscopy

The research describes a rapid method for the determination of fatty acid (FA) contents in a micro-encapsulated fish-oil (μEFO) supplement by using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis. Using the ATR-FTIR technique, the μEFO powder samples can be directly analysed without any pre-treatment required, and our developed PLSR strategic approach based on the acquired spectral data led to production of a good linear calibration with R^₂ = 0.99. In addition, the subsequent predictions acquired from an independent validation set for the target FA compositions (i.e., total oil, total omega-3 fatty acids, EPA and DHA) were highly accurate when compared to the actual values obtained from standard GC-based technique, with plots between predicted versus actual values resulting in excellent linear fitting (R² ⩾ 0.96) in all cases. The study therefore demonstrated not only the substantial advantage of the ATR-FTIR technique in terms of rapidness and cost effectiveness, but also its potential application as a rapid, potentially automated, online monitoring technique for the routine analysis of FA composition in industrial processes when used together with the multivariate.

Illumination-invariant face recognition from a single image across extreme pose using a dual dimension AAM ensemble in the thermal infrared spectrum

Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in practice. While inherently insensitive to visible spectrum illumination changes, IR data introduces specific challenges of its own, most notably sensitivity to factors which affect facial heat emission patterns, e.g. emotional state, ambient temperature, and alcohol intake. In addition, facial expression and pose changes are more difficult to correct in IR images because they are less rich in high frequency detail which is an important cue for fitting any deformable model. In this paper we describe a novel method which addresses these major challenges. Specifically, when comparing two thermal IR images of faces, we mutually normalize their poses and facial expressions by using an active appearance model (AAM) to generate synthetic images of the two faces with a neutral facial expression and in the same view (the average of the two input views). This is achieved by piecewise affine warping which follows AAM fitting. A major contribution of our work is the use of an AAM ensemble in which each AAM is specialized to a particular range of poses and a particular region of the thermal IR face space. Combined with the contributions from our previous work which addressed the problem of reliable AAM fitting in the thermal IR spectrum, and the development of a person-specific representation robust to transient changes in the pattern of facial temperature emissions, the proposed ensemble framework accurately matches faces across the full range of yaw from frontal to profile, even in the presence of scale variation (e.g. due to the varying distance of a subject from the camera). The effectiveness of the proposed approach is demonstrated on the largest public database of thermal IR images of faces and a newly acquired data set of thermal IR motion videos. Our approach achieved perfect recognition performance on both data sets, significantly outperforming the current state of the art methods even when they are trained with multiple images spanning a range of head views.

Infrared face recognition: a literature review

Automatic face recognition (AFR) is an area with immense practical potential which includes a wide range of commercial and law enforcement applications, and it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in AFR continues to improve, benefiting from advances in a range of different fields including image processing, pattern recognition, computer graphics and physiology. However, systems based on visible spectrum images continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease their accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject.