A surface-enhanced infrared absorption spectroscopic (SEIRAS) study of the oscillatory electro-oxidation of methanol on platinum

The oscillatory electro-oxidation of methanol was studied by means of in situ infrared (IR) spectroscopy in the attenuated total reflection (ATR) configuration using a platinum film on a Si prism as working electrode. The surface-enhanced infrared absorption (SEIRA) effect considerably improves the spectroscopic resolution, allowing at following the coverage of some adsorbing species during the galvanostatic oscillations. Carbon monoxide was the main adsorbed specie observed in the induction period and within the oscillatory regime. The system was investigated at two distinct time-scales and its dynamics characterized accordingly. During the induction period the main transformation observed as the system move through the phase space towards the oscillatory region was the decrease of the coverage of adsorbed carbon, coupled to the increase of the electrode potential. Similar transition characterizes the evolution within the oscillatory region, but at a considerably slower rate. Experiments with higher time resolution revealed that the electrode potential oscillates in-phase with the frequency of the linearly adsorbed CO vibration and that the amount of adsorbed CO oscillates with small amplitude. Adsorbed formate was found to play, if any, a very small role. Results are discussed and compared with other systems. (C) 2010 Elsevier B.V. All rights reserved.

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.

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.

Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that 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 face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition 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. Our key contributions are (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition; (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies; (iii) a description of the main databases of infrared facial images available to the researcher; and lastly (iv) a discussion of the most promising avenues for future research. © 2014 Elsevier Ltd.

Local structure and near-infrared emission features of neodymium-based amine functionalized organic/inorganic hybrids

Nd3+-based organic/inorganic hybrids have potential application in the field of integrated optics. Attractive sol-gel derived di-urea and di-urethane cross-linked poly (oxyethylene) (POE)/siloxane hybrids (di-ureasils and di-urethanesils, respectively) doped with neodymium triflate (Nd(CF3SO3)(3)) were examined by Fourier transform mid-infrared (FT-IR), Raman (FT-Raman), Si-29 magic-angle spinning (MAS) nuclear magnetic resonance (NMR) and photoluminescence spectroscopies, and small-angle X-ray scattering (SAXS). The goals of this work were to determine which cation coordinating site of the host matrix (ether oxygen atoms or carbonyl oxygen atoms) is active in each of the materials analyzed, its influence on the nanostructure of the samples and its relation with the photoluminescence properties. The main conclusion derived from this study is that the hydrogen-bonded associations formed throughout the materials play a major role in the hybrids nanostructure and photoluminescence properties.

Er3+-doped germanate glasses for active waveguides prepared by Ag+/K+ <-> Na+ ion-exchange

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Active planar waveguides based on sol-gel Er3+-doped SiO2-ZrO2 for photonic applications: Morphological, structural and optical properties

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Isolation and characterization of sodium 2-fluoroacetate from Mascagnia rigida using chromatography and infrared spectroscopy

Sodium monofluoroacetate was first identified in Dichapetalum cymosum, a South African plant that can cause livestock poisoning and death. After, several other plants also showed to contain this toxin, which leads to the "sudden death". Mascagnia rigida, a well identified poisonous plant, commonly found in northeast of Brazil also cause sudden death in cattle, which shows clinical signs similar to those produced by the ingestion of plants that contain monofluoroacetate. Our aim was to identify the toxic compound present in the aqueous extract of M. rigida. For this purpose, the dried and milled plant was extracted; the extract was lyophilized and submitted to successive chromatographic process, until the desired purity of the active compound was achieved. The study of this material by planar chromatography and by infrared spectrometry indicated that the toxin can be a mixture of mono, di and trifluoroacetate. (C) 2012 Elsevier Ltd. All rights reserved.

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Global scale investigation of cirrus clouds properties using active and passive sensors

A year of satellite-borne lidar CALIOP data is analyzed and statistics on occurrence and distribution of bulk properties of cirri are provided. The relationship between environmental and cloud physical parameters and the shape of the backscatter profile (BSP) is investigated. It is found that CALIOP BSP is mainly affected by cloud geometrical thickness while only minor impacts can be attributed to other quantities such as optical depth or temperature. To fit mean BSPs as functions of geometrical thickness and position within the cloud layer, polynomial functions are provided. It is demonstrated that, under realistic hypotheses, the mean BSP is linearly proportional to the IWC profile. The IWC parameterization is included into the RT-RET retrieval algorithm, that is exploited to analyze infrared radiance measurements in presence of cirrus clouds during the ECOWAR field campaign. Retrieved microphysical and optical properties of the observed cloud are used as input parameters in a forward RT simulation run over the 100-1100 cm-1 spectral interval and compared with interferometric data to test the ability of the current single scattering properties database of ice crystal to reproduce realistic optical features. Finally a global scale investigation of cirrus clouds is performed by developing a collocation algorithm that exploits satellite data from multiple sensors (AIRS, CALIOP, MODIS). The resulting data set is utilized to test a new infrared hyperspectral retrieval algorithm. Retrieval products are compared to data and in particular the cloud top height (CTH) product is considered for this purpose. A better agreement of the retrieval with the CALIOP CTH than MODIS is found, even if some cases of underestimation and overestimation are observed.

White-Nose Syndrome-Affected Litttle Brown Myotis (Myotis Lucifugus) Increase Grooming and Other Active Behaviors During Arousals from Hibernation

White-nose syndrome (WNS) is an emerging infectious disease of hibernating bats linked to the death of an estimated 5.7 million or more bats in the northeastern United States and Canada. White-nose syndrome is caused by the cold-loving fungus Pseudogymnoascus destructans (Pd), which invades the skin of the muzzles, ears, and wings of hibernating bats. Previous work has shown that WNS-affected bats arouse to euthermic or near euthermic temperatures during hibernation significantly more frequently than normal and that these too-frequent arousals are tied to severity of infection and death date. We quantified the behavior of bats during these arousal bouts to understand better the causes and consequences of these arousals. We hypothesized that WNS-affected bats would display increased levels of activity (especially grooming) during their arousal bouts from hibernation compared to WNS-unaffected bats. Behavior of both affected and unaffected hibernating bats in captivity was monitored from December 2010 to March 2011 using temperature-sensitive dataloggers attached to the backs of bats and infrared motion-sensitive cameras. The WNS-affected bats exhibited significantly higher rates of grooming, relative to unaffected bats, at the expense of time that would otherwise be spent inactive. Increased self-grooming may be related to the presence of the fungus. Elevated activity levels in affected bats likely increase energetic stress, whereas the loss of rest (inactive periods when aroused from torpor) may jeopardize the ability of a bat to reestablish homeostasis in a number of physiologic systems.

Active water in protein-protein communication within the membrane: the case of SRII-HtrII signal relay.

We detect internal water molecules in a membrane-embedded receptor-transducer complex and demonstrate water structure changes during formation of the signaling state. Time-resolved FTIR spectroscopy reveals stimulus-induced repositioning of one or more structurally active water molecules to a significantly more hydrophobic environment in the signaling state of the sensory rhodopsin II (SRII)-transducer (HtrII) complex. These waters, distinct from bound water molecules within the SRII receptor, appear to be in the middle of the transmembrane interface region near the Tyr199(SRII)-Asn74(HtrII) hydrogen bond. We conclude that water potentially plays an important role in the SRII --> HtrII signal transfer mechanism in the membrane's hydrophobic core.