974 resultados para INFRARED-SPECTRA


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We have analyzed a frondelite mineral sample from the Cigana mine, located in the municipality of Conselheiro Pena, a well-known pegmatite in Brazil. In the Cigana pegmatite, secondary phosphates, namely eosphorite, fairfieldite, fluorapatite, frondelite, gormanite, hureaulite, lithiophilite, reddingite and vivianite are common minerals in miarolitic cavities and in massive blocks after triphylite. The chemical formula was determined as (Mn0.68, Fe0.32)(Fe3+)3,72(PO4)3.17(OH)4.99. The structure of the mineral was assessed using vibrational spectroscopy. Bands attributed to the stretching and bending modes of PO4 3- and HOPO3 3- units were identified. The observation of multiple bands supports the concept of symmetry reduction of the phosphate anion in the frondelite structure. Sharp Raman and infrared bands at 3581 cm−1 is assigned to the OH stretching vibration. Broad Raman bands at 3063, 3529 and 3365 cm−1 are attributed to water stretching vibrational modes.

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The mineral creedite is a fluorinated hydroxy hydrated sulphate of aluminium and calcium of formula Ca3Al2SO4(F,OH)·2H2O. The mineral has been studied by a combination of electron probe analysis to determine the molecular formula of the mineral and the structure assessed by vibrational spectroscopy. The spectroscopy of creedite may be compared with that of the alums. The Raman spectrum of creedite is characterised by an intense sharp band at 986 cm−1 assigned to the View the MathML source ν1 (Ag) symmetric stretching mode. Multiple bands of creedite in the antisymmetric stretching region support the concept of a reduction in symmetry of the sulphate anion. Multiple bands are also observed in the bending region with the three bands at 601, 629 and 663 cm−1 assigned to the View the MathML source ν4 (Ag) bending modes. The observation of multiple bands at 440, 457 and 483 cm−1 attributed to the View the MathML source ν2 (Bg) bending modes supports the concept that the symmetry of the sulphate is reduced by coordination to the water bonded to the Al3+ in the creedite structure. The splitting of the ν2, ν3 and ν4 modes is attributed to the reduction of symmetry of the SO4 and it is proposed that the sulphate coordinates to water in the hydrated aluminium in bidentate chelation.

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Abstract An assessment of the molecular structure of carletonite a rare phyllosilicate mineral with general chemical formula given as KNa4Ca4Si8O18(CO3)4(OH,F)·H2O has been undertaken using vibrational spectroscopy. Carletonite has a complex layered structure. Within one period of c, it contains a silicate layer of composition NaKSi8O18·H2O, a carbonate layer of composition NaCO3·0.5H2O and two carbonate layers of composition NaCa2CO3(F,OH)0.5. Raman bands are observed at 1066, 1075 and 1086 cm−1. Whether these bands are due to the CO32- ν1 symmetric stretching mode or to an SiO stretching vibration is open to question. Multiple bands are observed in the 300–800 cm−1 spectral region, making the attribution of these bands difficult. Multiple water stretching and bending modes are observed showing that there is much variation in hydrogen bonding between water and the silicate and carbonate surfaces.

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The mineral chalcosiderite with formula CuFe6(PO4)4(OH)8⋅4H2O has been studied by Raman spectroscopy and by infrared spectroscopy. A comparison of the chalcosiderite spectra is made with the spectra of turquoise. The spectra of the mineral samples are very similar in the 1200–900 cm−1 region but strong differences are observed in the 900–100 cm−1 region. The effect of substitution of Fe for Al in chalcosiderite shifts the bands to lower wave numbers. Factor group analysis (FGA) implies four OH stretching vibrations for both the water and hydroxyl units. Two bands ascribed to water are observed at 3276 and 3072 cm−1. Three hydroxyl stretching vibrations are observed. Calculations using a Libowitzky type formula show that the hydrogen bond distances of the water molecules are 2.745 and 2.812 Å which are considerably shorter than the values for the hydroxyl units 2.896, 2.917 and 2.978 Å. Two phosphate stretching vibrations at 1042 and 1062 cm−1 in line with the two independent phosphate units in the structure of chalcosiderite. Three bands are observed at 1102, 1159 and 1194 cm−1 assigned to the phosphate antisymmetric stretching vibrations. FGA predicts six bands but only three are observed due to accidental degeneracy. Both the ν2 and ν4 bending regions are complex. Four Raman bands observed at 536, 580, 598 and 636 cm−1 are assigned to the ν4 bending modes. Raman bands at 415, 420, 475 and 484 cm−1are assigned to the phosphate ν2 bending modes. Vibrational spectroscopy enables aspects of the molecular structure of chalcosiderite to be assessed.

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Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

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The microwave synthesis of MnC2O4·2H2O nanoparticles was performed through the thermal double decomposition of oxalic acid dihydrate (C2H2O4·2H2O) and Mn(OAc)2·4H2O solutions using a CATA-2R microwave reactor. Structural characterization was performed using X-ray diffraction (XRD), particle size and shape were analyzed using transmission electron microscopy (TEM). The chemical in the structures was investigated using electron paramagnetic resonance (EPR) as well as optical absorption spectra and near-infrared (NIR) spectroscopies. The nanocrystals produced with this method were pure and had a distorted rhombic octahedral structure.

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The mineral amarantite Fe23+(SO4)O∙7H2O has been studied using a combination of techniques including thermogravimetry, electron probe analyses and vibrational spectroscopy. Thermal analysis shows decomposition steps at 77.63, 192.2, 550 and 641.4°C. The Raman spectrum of amarantite is dominated by an intense band at 1017 cm-1 assigned to the SO42- ν1 symmetric stretching mode. Raman bands at 1039, 1054, 1098, 1131, 1195 and 1233 cm-1 are attributed to the SO42- ν3 antisymmetric stretching modes. Very intense Raman band is observed at 409 cm-1 with shoulder bands at 399, 451 and 491 cm-1 are assigned to the v2 bending modes. A series of low intensity Raman bands are found at 543, 602, 622 and 650 cm-1 are assigned to the v4 bending modes. A very sharp Raman band at 3529 cm-1 is assigned to the stretching vibration of OH units. A series of Raman bands observed at 3025, 3089, 3227, 3340, 3401 and 3480 cm-1 are assigned to water bands. Vibrational spectroscopy enables aspects of the molecular structure of the mineral amarantite to be ascertained.

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In Australia and increasingly worldwide, methamphetamine is one of the most commonly seized drugs analysed by forensic chemists. The current well-established GC/MS methods used to identify and quantify methamphetamine are lengthy, expensive processes, but often rapid analysis is requested by undercover police leading to an interest in developing this new analytical technique. Ninety six illicit drug seizures containing methamphetamine (0.1% - 78.6%) were analysed using Fourier Transform Infrared Spectroscopy with an Attenuated Total Reflectance attachment and Chemometrics. Two Partial Least Squares models were developed, one using the principal Infrared Spectroscopy peaks of methamphetamine and the other a Hierarchical Partial Least Squares model. Both of these models were refined to choose the variables that were most closely associated with the methamphetamine % vector. Both of the models were excellent, with the principal peaks in the Partial Least Squares model having Root Mean Square Error of Prediction 3.8, R2 0.9779 and lower limit of quantification 7% methamphetamine. The Hierarchical Partial Least Squares model had lower limit of quantification 0.3% methamphetamine, Root Mean Square Error of Prediction 5.2 and R2 0.9637. Such models offer rapid and effective methods for screening illicit drug samples to determine the percentage of methamphetamine they contain.

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The mineral kovdorskite Mg2PO4(OH)�3H2O was studied by electron microscopy, thermal analysis and vibrational spectroscopy. A comparison of the vibrational spectroscopy of kovdorskite is made with other magnesium bearing phosphate minerals and compounds. Electron probe analysis proves the mineral is very pure. The Raman spectrum is characterized by a band at 965 cm�1 attributed to the PO3� 4 m1 symmetric stretching mode. Raman bands at 1057 and 1089 cm�1 are attributed to the PO3�4 m3 antisymmetric stretching modes. Raman bands at 412, 454 and 485 cm�1 are assigned to the PO3�4 m2 bending modes. Raman bands at 536, 546 and 574 cm�1 are assigned to the PO3�4 m4 bending modes. The Raman spectrum in the OH stretching region is dominated by a very sharp intense band at 3681 cm�1 assigned to the stretching vibration of OH units. Infrared bands observed at 2762, 2977, 3204, 3275 and 3394 cm�1 are attributed to water stretching bands. Vibrational spectroscopy shows that no carbonate bands are observed in the spectra; thus confirming the formula of the mineral as Mg2PO4(OH)�3H2O.

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We have studied the mineral senagalite, a hydrated hydroxy phosphate of aluminium with formula Al2(PO4)(OH)3⋅3H2O using a combination of electron microscopy and vibrational spectroscopy. Senegalite crystal aggregates shows tabular to prismatic habitus and orthorhombic form. The Raman spectrum is dominated by an intense band at 1029 cm−1 assigned to the PO43- ν1 symmetric stretching mode. Intense Raman bands are found at 1071 and 1154 cm−1 with bands of lesser intensity at 1110, 1179 and 1206 cm−1 and are attributed to the PO43- ν3 antisymmetric stretching vibrations. The infrared spectrum shows complexity with a series overlapping bands. A comparison is made with spectra of other aluminium containing phosphate minerals such as augelite and turquoise. Multiple bands are observed for the phosphate bending modes giving support for the reduction of symmetry of the phosphate anion. Vibrational spectroscopy offers a means for the assessment of the structure of senagalite.

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Robust hashing is an emerging field that can be used to hash certain data types in applications unsuitable for traditional cryptographic hashing methods. Traditional hashing functions have been used extensively for data/message integrity, data/message authentication, efficient file identification and password verification. These applications are possible because the hashing process is compressive, allowing for efficient comparisons in the hash domain but non-invertible meaning hashes can be used without revealing the original data. These techniques were developed with deterministic (non-changing) inputs such as files and passwords. For such data types a 1-bit or one character change can be significant, as a result the hashing process is sensitive to any change in the input. Unfortunately, there are certain applications where input data are not perfectly deterministic and minor changes cannot be avoided. Digital images and biometric features are two types of data where such changes exist but do not alter the meaning or appearance of the input. For such data types cryptographic hash functions cannot be usefully applied. In light of this, robust hashing has been developed as an alternative to cryptographic hashing and is designed to be robust to minor changes in the input. Although similar in name, robust hashing is fundamentally different from cryptographic hashing. Current robust hashing techniques are not based on cryptographic methods, but instead on pattern recognition techniques. Modern robust hashing algorithms consist of feature extraction followed by a randomization stage that introduces non-invertibility and compression, followed by quantization and binary encoding to produce a binary hash output. In order to preserve robustness of the extracted features, most randomization methods are linear and this is detrimental to the security aspects required of hash functions. Furthermore, the quantization and encoding stages used to binarize real-valued features requires the learning of appropriate quantization thresholds. How these thresholds are learnt has an important effect on hashing accuracy and the mere presence of such thresholds are a source of information leakage that can reduce hashing security. This dissertation outlines a systematic investigation of the quantization and encoding stages of robust hash functions. While existing literature has focused on the importance of quantization scheme, this research is the first to emphasise the importance of the quantizer training on both hashing accuracy and hashing security. The quantizer training process is presented in a statistical framework which allows a theoretical analysis of the effects of quantizer training on hashing performance. This is experimentally verified using a number of baseline robust image hashing algorithms over a large database of real world images. This dissertation also proposes a new randomization method for robust image hashing based on Higher Order Spectra (HOS) and Radon projections. The method is non-linear and this is an essential requirement for non-invertibility. The method is also designed to produce features more suited for quantization and encoding. The system can operate without the need for quantizer training, is more easily encoded and displays improved hashing performance when compared to existing robust image hashing algorithms. The dissertation also shows how the HOS method can be adapted to work with biometric features obtained from 2D and 3D face images.

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The work described in this technical report is part of an ongoing project at QUT to build practical tools for the manipulation, analysis and visualisation of recordings of the natural environment. This report describes the algorithm we use to cluster the spectra in a spectrogram. The report begins with a brief description of the signal processing that prepares the spectrograms.

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The application of different EMS current thresholds on muscle activates not only the muscle but also peripheral sensory axons that send proprioceptive and pain signals to the cerebral cortex. A 32-channel time-domain fNIRS instrument was employed to map regional cortical activities under varied EMS current intensities applied on the right wrist extensor muscle. Eight healthy volunteers underwent four EMS at different current thresholds based on their individual maximal tolerated intensity (MTI), i.e., 10 % < 50 % < 100 % < over 100 % MTI. Time courses of the absolute oxygenated and deoxygenated hemoglobin concentrations primarily over the bilateral sensorimotor cortical (SMC) regions were extrapolated, and cortical activation maps were determined by general linear model using the NIRS-SPM software. The stimulation-induced wrist extension paradigm significantly increased activation of the contralateral SMC region according to the EMS intensities, while the ipsilateral SMC region showed no significant changes. This could be due in part to a nociceptive response to the higher EMS current intensities and result also from increased sensorimotor integration in these cortical regions.

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The objective of this work is to determine the thermal stability and vibrational spectra of datolite CaBSiO4(OH) and relate these properties to the structure of the mineral. The thermal analysis of datolite shows a mass loss of 5.83% over a 700–775 °C temperature range. This mass loss corresponds to 1 water (H2O) molecules pfu. A quantitative chemical analysis using electron probe was undertaken. The Raman spectrum of datolite is characterized by bands at 917 and 1077 cm−1 assigned to the symmetric stretching modes of BO and SiO tetrahedra. A very intense Raman band is observed at 3498 cm−1 assigned to the stretching vibration of the OH units in the structure of datolite. BOH out-of-plane vibrations are characterized by the infrared band at 782 cm−1. The vibrational spectra are based upon the structure of datolite based on sheets of four- and eight-membered rings of alternating SiO4 and BO3(OH) tetrahedra with the sheets bonded together by calcium atoms.

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We have studied the mineral goyazite using Raman and infrared spectroscopy. Goyazite is a member of the crandallite subgroup of the alunite supergroup. The crystal structure is of the alunite-type and consists of sheets of corner-sharing AlO6 octahedra parallel to (0001). The octahedrally coordinated Sr2+ cations occupy cavities between pairs of octahedral sheets and are surrounded by six oxygen atoms from the (Al3+)O6 octahedra. The very intense sharp band at 983 cm-1 is assigned to the ν1 PO43- symmetric stretching mode. The observation of a single band supports the concept that all the phosphate units are equivalent in the structure of goyazite. Raman bands observed at 1029 cm-1 and 1037 cm-1 are assigned to the to the ν3 PO43- antisymmetric stretching vibrations. Two Raman bands at 895 and 927 cm-1 are attributed to the stretching vibrations of H2PO4; thus indicating some hydrogen phosphate units in the structure of goyazite. Raman bands at 556, 581, 596 and 612 cm-1 are assigned to the ν4 PO43- bending modes, suggesting a reduction of symmetry of phosphate units. Two sharp Raman bands at 3609 and 3631 cm-1 are attributed to OH stretching vibrations from the goyazite hydroxyl units. Broad Raman bands at 2924, 3043, 3210, 3429 and 3511 cm-1 are assigned to water stretching vibrations. Vibrational spectroscopy enables subtle details of the molecular structure of goyazite to be determined.