Application of auto regressive models of wavelet sub-bands for classifying Terahertz pulse measurements

This paper presents an approach for automatic classification of pulsed Terahertz (THz), or T-ray, signals highlighting their potential in biomedical, pharmaceutical and security applications. T-ray classification systems supply a wealth of information about test samples and make possible the discrimination of heterogeneous layers within an object. In this paper, a novel technique involving the use of Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) models on the wavelet transforms of measured T-ray pulse data is presented. Two example applications are examined - the classi. cation of normal human bone (NHB) osteoblasts against human osteosarcoma (HOS) cells and the identification of six different powder samples. A variety of model types and orders are used to generate descriptive features for subsequent classification. Wavelet-based de-noising with soft threshold shrinkage is applied to the measured T-ray signals prior to modeling. For classi. cation, a simple Mahalanobis distance classi. er is used. After feature extraction, classi. cation accuracy for cancerous and normal cell types is 93%, whereas for powders, it is 98%.

Collaterally cued labelling framework underpinning semantic-level visual content descriptor

In this paper, we introduce a novel high-level visual content descriptor devised for performing semantic-based image classification and retrieval. The work can be treated as an attempt for bridging the so called "semantic gap". The proposed image feature vector model is fundamentally underpinned by an automatic image labelling framework, called Collaterally Cued Labelling (CCL), which incorporates the collateral knowledge extracted from the collateral texts accompanying the images with the state-of-the-art low-level visual feature extraction techniques for automatically assigning textual keywords to image regions. A subset of the Corel image collection was used for evaluating the proposed method. The experimental results indicate that our semantic-level visual content descriptors outperform both conventional visual and textual image feature models.

Spatial and temporal modeling of community non-timber forest extraction

This paper examines the interaction of spatial and dynamic aspects of resource extraction from forests by local people. Highly cyclical and varied across space and time, the patterns of resource extraction resulting from the spatial–temporal model bear little resemblance to the patterns drawn from focusing either on spatial or temporal aspects of extraction alone. Ignoring this variability inaccurately depicts villagers’ dependence on different parts of the forest and could result in inappropriate policies. Similarly, the spatial links in extraction decisions imply that policies imposed in one area can have unintended consequences in other areas. Combining the spatial–temporal model with a measure of success in community forest management—the ability to avoid open-access resource degradation—characterizes the impact of incomplete property rights on patterns of resource extraction and stocks.

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

Classification in e-procurement

Three coupled knowledge transfer partnerships used pattern recognition techniques to produce an e-procurement system which, the National Audit Office reports, could save the National Health Service £500 m per annum. An extension to the system, GreenInsight, allows the environmental impact of procurements to be assessed and savings made. Both systems require suitable products to be discovered and equivalent products recognised, for which classification is a key component. This paper describes the innovative work done for product classification, feature selection and reducing the impact of mislabelled data.

Aqueous enzyme assisted oil extraction from oilseeds and emulsion de-emulsifying methods: a review

Regulatory, safety, and environmental issues have prompted the development of aqueousenzymatic extraction (AEE) for extracting components from oil-bearing materials. The emulsion resulting from AEE requires de-emulsification to separate the oil; when enzymes are used for this purpose, the method is known as aqueous enzymatic emulsion de-emulsification (AEED). In general, enzyme assisted oil extraction is known to yield oil having highly favourable characteristics. This review covers technological aspects of enzyme assisted oil extraction, and explores the quality characteristics of the oils obtained,focusing particularly on recent efforts undertaken to improve process economics by recovering and reusing enzymes.

Differences in phosphorus retention and release in soils amended with animal manures and sewage sludge

Excessive levels of P in agricultural soils pose a threat to local water quality. This study evaluated (i) time-dependent changes in soil P sorption (expressed as a phosphorus sorption index, PSI) and P availability (as resin P) during incubation (100 d) with poultry litter, cattle slurry, sewage sludge, or KH2PO4, added on a P-equivalent basis (100 mg P kg(-1)), and (ii) the subsequent kinetics of P release, measured by repeated extractions with a mixed cation-anion exchange resin. Soil exchangeable Ca and ammonium oxalate-extractable Fe and Al were also determined at 100 d of incubation. The small decrease in P sorption in the litter and sludge treatments (25%), compared with that in the slurry and KH2PO4 treatments (52%) between 20 and 100 d of incubation was attributed partly to the formation of new adsorption sites for P. Subsequent P release was described by a power equation: Resin P = a(extraction number)(b), where the constants a and b represent resin P obtained with a single extraction and the rate of P release per resin extraction, respectively. On average, the rate of P release decreased in the order: KH2PO4 and slurry > litter > sludge, and was inversely related to exchangeable Ca content of the incubated soils (R-2 = 0.57). The slower rates of P release in the litter and sludge treatments (P < 0.001) are attributed to the large values for exchangeable Ca (1050-2640 and 1070-2710 mg kg(-1), respectively) in these amended soils. Future research concerned with short-term declines in environmentally harmful levels of P in recently amended soils should consider the differential effects of the amendments on soil P dynamics.

Implicit and explicit knowledge bases in artificial grammar learning

Two experiments examined the claim for distinct implicit and explicit learning modes in the artificial grammar-learning task (Reber, 1967, 1989). Subjects initially attempted to memorize strings of letters generated by a finite-state grammar and then classified new grammatical and nongrammatical strings. Experiment 1 showed that subjects' assessment of isolated parts of strings was sufficient to account for their classification performance but that the rules elicited in free report were not sufficient. Experiment 2 showed that performing a concurrent random number generation task under different priorities interfered with free report and classification performance equally. Furthermore, giving different groups of subjects incidental or intentional learning instructions did not affect classification or free report.

Combinatorial peptide ligand libraries and plant proteomics: a winning strategy at a price

The mechanism of action and properties of a solid-phase ligand library made of hexapeptides (combinatorial peptide ligand libraries or CPLL), for capturing the "hidden proteome", i.e. the low- and very low-abundance proteins constituting the vast majority of species in any proteome, as applied to plant tissues, are reviewed here. Plant tissues are notoriously recalcitrant to protein extraction and to proteome analysis. Firstly, rigid plant cell walls need to be mechanically disrupted to release the cell content and, in addition to their poor protein yield, plant tissues are rich in proteases and oxidative enzymes, contain phenolic compounds, starches, oils, pigments and secondary metabolites that massively contaminate protein extracts. In addition, complex matrices of polysaccharides, including large amount of anionic pectins, are present. All these species compete with the binding of proteins to the CPLL beads, impeding proper capture and identification / detection of low-abundance species. When properly pre-treated, plant tissue extracts are amenable to capture by the CPLL beads revealing thus many new species among them low-abundance proteins. Examples are given on the treatment of leaf proteins, of corn seed extracts and of exudate proteins (latex from Hevea brasiliensis). In all cases, the detection of unique gene products via CPLL capture is at least twice that of control, untreated sample.

Monatin and its stereoisomers: chemoenzymatic synthesis and taste properties

The sweet natural compound monatin 1 has two stereogenic centres and the (2S,4S) absolute configuration has been attributed to the natural isomer. We obtained all four stereoisomers as pure compounds by a six-step synthetic sequence. The stereogenic centre at C-4 was introduced stereoselectively by a regio- and enantiospecific enzymatic hydrolysis of the racemic ethyl dicarboxylate 4 using a protease from Aspergillus oryzae. The absolute configuration of the intermediate products was assigned by X-ray diffraction of chiral derivatives. The stereogenic centre at C-2 was introduced non-specifically, and the resulting diastereomeric mixtures were separated by RP-HPLC. The absolute configurations of the final products were established by comparing retention times on a chiral HPLC column with those of known samples. The four stereoisomers were submitted to tasting trials and three of them, particularly the (2R,4R) isomer, were found to be intensely sweet. A sample of natural monatin analysed under the same conditions is shown to contain all the four stereoisomers. The relative stereoisomeric content in the plant, as well as the possible isomerisation of the chiral centres during extraction and manipulation of monatin samples, are important points that need to be clarified by extensive analysis of the natural extracts. ((c) Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005).

Combinatorial peptide ligand libraries and plant proteomics: a winning strategy at a price

The mechanism of action and properties of a solid-phase ligand library made of hexapeptides (combinatorial peptide ligand libraries or CPLL, for capturing the "hidden proteome", i.e. the low- and very low-abundance proteins Constituting the vast majority of species in any proteome. as applied to plant tissues, are reviewed here. Plant tissues are notoriously recalcitrant to protein extraction and to proteome analysis, Firstly, rigid plant cell walls need to be mechanically disrupted to release the cell content and, in addition to their poor protein yield, plant tissues are rich in proteases and oxidative enzymes, contain phenolic Compounds, starches, oils, pigments and secondary metabolites that massively contaminate protein extracts. In addition, complex matrices of polysaccharides, including large amount of anionic pectins, are present. All these species compete with the binding of proteins to the CPLL beads, impeding proper capture and identification I detection of low-abundance species. When properly pre-treated, plant tissue extracts are amenable to capture by the CPLL beads revealing thus many new species among them low-abundance proteins. Examples are given on the treatment of leaf proteins, of corn seed extracts and of exudate proteins (latex from Hevea brasiliensis). In all cases, the detection of unique gene products via CPLL Capture is at least twice that of control, untreated sample. (c) 2008 Elsevier B.V. All rights reserved.

Extraction behavior of nickel(II) using some of the BTBP-class ligands

Recently the BTBP-family of solvating ligands have been studied for their ability to separate trivalent actinides from lanthanides. Five of the BTBPs were evaluated for their ability to extract nickel(II) from aqueous nitrate media into cyclohexanone. It was shown by both solvent extraction and X-ray diffraction experiments that the BTBPs are capable of forming both 1: 1 and 1:2 complexes with nickel(II). When the BTBP concentration is low the nickel distribution ratio is governed by the formation of the nickel/BTBP complex while at higher BTBP concentrations the partitioning of the nickel complex between the two phases dictates the nickel distribution ratio.

6,6 '-bis (5,5,8,8-tetramethyl-5,6,7,8-tetrahydro-benzo[1,2,4]triazin-3-yl) [2,2 ']bipyridine, an effective extracting agent for the separation of americium(III) and curium(III) from the lanthanides

The extraction of americium(III), curium(III), and the lanthanides(III) from nitric acid by 6,6'- bis (5,5,8,8-tetramethyl-5,6,7,8-tetrahydro-benzo[1,2,4]triazin-3-yl)-[2,2'] bipyridine (CyMe4-BTBP) has been studied. Since the extraction kinetics were slow, N,N'-dimethyl-N,N'-dioctyl-2-(2-hexyloxy-ethyl)malonamide (DMDOHEMA) was added as a phase transfer reagent. With a mixture of 0.01 M CyMe4-BTBP + 0.25 M DMDOHEMA in n -octanol, extraction equilibrium was reached within 5 min of mixing. At a nitric acid concentration of 1 M, an americium(III) distribution ratio of approx. 10 was achieved. Americium(III)/lanthanide(III) separation factors between 50 (dysprosium) and 1500 (lanthanum) were obtained. Whereas americium(III) and curium(III) were extracted as disolvates, the stoichiometries of the lanthanide(III) complexes were not identified unambiguously, owing to the presence of DMDOHEMA. In the absence of DMDOHEMA, both americium(III) and europium(III) were extracted as disolvates. Back-extraction with 0.1 M nitric acid was thermodynamically possible but rather slow. Using a buffered glycolate solution of pH=4, an americium(III) distribution ratio of 0.01 was obtained within 5 min of mixing. There was no evidence of degradation of the extractant, for example, the extraction performance of CyMe4-BTBP during hydrolylsis with 1 M nitric acid did not change over a two month contact.

Studies on the parallel synthesis and evaluation of new heterocyclic extractants for the partitioning of minor actinides

Multiple parallel synthesis and evaluation have been combined in order to identify new nitrogen heterocycles for the partitioning of minor actinides(III) such as americium(III) from lanthanides such as europium(Ill). An array of triazine-containing molecules was made using multiple parallel syntheses from diketones and amide hydrazides. An excess of each of the resulting purified reagents was dissolved in 1,1,2,2-tetrachloroethane containing 2-bromodecanoic acid, and equilibrated with an aqueous solution containing the radiotracers Eu-152 and Am-241 in nitric acid ([Eu] + [Am] < 400 nanomol dm(-3)). Gamma counting of the organic and aqueous phases led to the identification of several new reagents for the selective extraction of americium(III). In particular, 6-(2-pyridyl)-2-(5,6-dialkyl-1,2,4-triazaphenyl)pyridines were found to be effective reagents for the separation of americium(III) from europium(III), (SFAm/Eu was ca. 30 in [HNO3] = 0.013 mol/L).

Use of thermography and fibre optics microscopy for the evaluation of railway structures in the Athens Metro in Greece (Invited Paper)

Rolling Contact Fatigue (RCF) is one of the main issues that concern, at least initially, the head of the railway; progressively they can be of very high importance as they can propagate inside the material with the risk of damaging the railway. In this work, two different non-destructive techniques, infrared thermography (IRT) and fibre optics microscopy (FOM), were used in the inspection of railways for the tracing of defects and deterioration signs. In the first instance, two different approaches (dynamic and pulsed thermography) were used, whilst in the case of FOM, microscopic characterisation of the railway heads and classification of the deterioration -- damage on the railways according to the UIC (International Union of Railways) code, took place. Results from both techniques are presented and discussed.