Sequential extraction and single-step cold-acid extraction: A feasibility study for use with freshwater-canal sediments

This investigation examines metal release from freshwater sediment using sequential extraction and single-step cold-acid leaching. The concentrations of Cd, Cr, Cu, Fe, Ni, Pb and Zn released using a standard 3-step sequential extraction (Rauret et al., 1999) are compared to those released using a 0.5 M HCl; leach. The results show that the three sediments behave in very different ways when subject to the same leaching experiments: the cold-acid extraction appears to remove higher relative concentrations of metals from the iron-rich sediment than from the other two sediments. Cold-acid extraction appears to be more effective at removing metals from sediments with crystalline iron oxides than the "reducible" step of the sequential extraction. The results show that a single-step acid leach can be just as effective as sequential extractions at removing metals from sediment and are a great deal less time-consuming.

Solvent extraction and lanthanide complexation studies with new terdentate ligands containing two 1,3,5-triazine moieties

The extracting agent 2,6-bis(4,6-di-pivaloylamino-1,3,5-triazin-2-yl)-pyridine (L-5) in n-octanol was found, in synergy with 2-bromodecanoic acid, to give D-Am/D-Eu separation factors (SFs) between 2.4 and 3.7 when used to extract the metal ions from 0.02-0.12 M HNO3. Slightly higher SFs (4-6) were obtained in the absence of the synergist when the ligand was used to extract Am(III) and Eu(III) from 0.98 M HNO3. In order to investigate the possible nature of the extracted species crystal structures of L-5 and the complex formed between Yb(III) with 2,6-bis(4,6-di-amino-1,3,5-triazin-2-yl)-pyridine (L-4) were also determined. The structure of L-5 shows 3 methanol solvent molecules all of which form 2 or 3 hydrogen bonds with triazine nitrogen atoms, amide nitrogen or oxygen atoms, or pyridine nitrogen atoms. However, L-5 is relatively unstable in metal complexation reactions and loses amide groups to form the parent tetramine L-4. The crystal structure of Yb(L-4)(NO3)(3) shows ytterbium in a 9-coordinate environment being bonded to three donor atoms of the ligand and three bidentate nitrate ions. The solvent extraction properties of L-4 and L-5 are far inferior to those found for the 2,6-bis-(1,2,4-triazin-3-yl)-pyridines (L-1) which have SF values of ca. 140 and theoretical calculations have been made to compare the electronic properties of the ligands. The electronic charge distribution in L-4 and L-5 is similar to that found in other terdentate ligands such as terpyridine which have equally poor extraction properties and suggests that the unique properties of L-1 evolve from the presence of two adjacent nitrogen atoms in the triazine rings.

Extraction and coordination studies of the unexplored bifunctional ligand carbamoyl methyl sulfoxide (CMSO) with uranium(VI) and cerium(III) nitrates. Synthesis and structures of [UO2(NO3)(2)((PhSOCH2CONBu2)-Bu-i)] and [Ce(NO3)(3)(PhSOCH2CONBu2)(2)]

The bifunctional carbamoyl methyl sulfoxide ligands, PhCH2SOCH2CONHPh (L-1), PhCH2SOCH2CONHCH2Ph (L-2), (PhSOCH2CONPr2)-Pr-i (L-3), PhSOCH2CONBu2 (L-4), (PhSOCH2CONBu2)-Bu-i (L-5) and PhSOCH2CON(C8H17)(2) (L-6) have been synthesized and characterized by spectroscopic methods. The selected coordination chemistry of L-1, L-3, L-4 and L-5 with [UO2(NO3)(2)] and [Ce(NO3)(3)] has been evaluated. The structures of the compounds [UO2(NO3)(2)((PhSOCH2CONBu2)-Bu-i)] (10) and [Ce(NO3)(3)(PhSOCH2CONBu2)(2)] (12) have been determined by single crystal X-ray diffraction methods. Preliminary extraction studies of ligand L-6 with U(VI), Pu(IV) and Am(III) in tracer level showed an appreciable extraction for U(VI) and Pu(IV) in up to 10 M HNO3 but not for Am(III). Thermal studies on compounds 8 and 10 in air revealed that the ligands can be destroyed completely on incineration. The electron spray mass spectra of compounds 8 and 10 in acetone show that extensive ligand distribution reactions occur in solution to give a mixture of products with ligand to metal ratios of 1 : 1 and 2 : 1. However, 10 retains its solid state structure in CH2Cl2.

Extraction and determination of ellagic acid content in chestnut bark and fruit

Chestnuts are an important economic resource in the chestnut growing regions, not only for the fruit, but also for the wood. The content of ellagic acid (EA), a naturally occurring inhibitor of carcinogenesis, was determined in chestnut fruits and bark. EA was extracted with methanol and free ellagic acid was determined by HPLC with UV detection, both in the crude extract and after hydrolysis. The concentration of EA was generally increased after hydrolysis due to the presence of ellagitannins in the crude extract. The concentration varied between 0.71 and 21.6 ing g(-1) (d.w.) in un-hydrolyzed samples, and between 2.83 and 18.4 mg g(-1) (d.w.) ill hydrolyzed samples. In chestnut fruits, traces of EA were present in the seed, with higher concentrations in the pellicle and pericarp. However, all fruit tissues had lower concentrations of EA than had the bark. The concentration of EA in the hydrolyzed samples showed a non-linear correlation with the concentration in the unhydrolyzed extracts. (C) 2008 Elsevier Ltd. All rights reserved.

Facial feature extraction and selection by Gabor wavelets and boosting

In this paper, we present a feature selection approach based on Gabor wavelet feature and boosting for face verification. By convolution with a group of Gabor wavelets, the original images are transformed into vectors of Gabor wavelet features. Then for individual person, a small set of significant features are selected by the boosting algorithm from a large set of Gabor wavelet features. The experiment results have shown that the approach successfully selects meaningful and explainable features for face verification. The experiments also suggest that for the common characteristics such as eyes, noses, mouths may not be as important as some unique characteristic when training set is small. When training set is large, the unique characteristics and the common characteristics are both important.

A neurofuzzy network knowledge extraction and extended gram-Schmidt algorithm for model subspace decomposition

This paper introduces a new neurofuzzy model construction and parameter estimation algorithm from observed finite data sets, based on a Takagi and Sugeno (T-S) inference mechanism and a new extended Gram-Schmidt orthogonal decomposition algorithm, for the modeling of a priori unknown dynamical systems in the form of a set of fuzzy rules. The first contribution of the paper is the introduction of a one to one mapping between a fuzzy rule-base and a model matrix feature subspace using the T-S inference mechanism. This link enables the numerical properties associated with a rule-based matrix subspace, the relationships amongst these matrix subspaces, and the correlation between the output vector and a rule-base matrix subspace, to be investigated and extracted as rule-based knowledge to enhance model transparency. The matrix subspace spanned by a fuzzy rule is initially derived as the input regression matrix multiplied by a weighting matrix that consists of the corresponding fuzzy membership functions over the training data set. Model transparency is explored by the derivation of an equivalence between an A-optimality experimental design criterion of the weighting matrix and the average model output sensitivity to the fuzzy rule, so that rule-bases can be effectively measured by their identifiability via the A-optimality experimental design criterion. The A-optimality experimental design criterion of the weighting matrices of fuzzy rules is used to construct an initial model rule-base. An extended Gram-Schmidt algorithm is then developed to estimate the parameter vector for each rule. This new algorithm decomposes the model rule-bases via an orthogonal subspace decomposition approach, so as to enhance model transparency with the capability of interpreting the derived rule-base energy level. This new approach is computationally simpler than the conventional Gram-Schmidt algorithm for resolving high dimensional regression problems, whereby it is computationally desirable to decompose complex models into a few submodels rather than a single model with large number of input variables and the associated curse of dimensionality problem. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Robust neurofuzzy rule base knowledge extraction and estimation using subspace decomposition combined with regularization and D-optimality

A new robust neurofuzzy model construction algorithm has been introduced for the modeling of a priori unknown dynamical systems from observed finite data sets in the form of a set of fuzzy rules. Based on a Takagi-Sugeno (T-S) inference mechanism a one to one mapping between a fuzzy rule base and a model matrix feature subspace is established. This link enables rule based knowledge to be extracted from matrix subspace to enhance model transparency. In order to achieve maximized model robustness and sparsity, a new robust extended Gram-Schmidt (G-S) method has been introduced via two effective and complementary approaches of regularization and D-optimality experimental design. Model rule bases are decomposed into orthogonal subspaces, so as to enhance model transparency with the capability of interpreting the derived rule base energy level. A locally regularized orthogonal least squares algorithm, combined with a D-optimality used for subspace based rule selection, has been extended for fuzzy rule regularization and subspace based information extraction. By using a weighting for the D-optimality cost function, the entire model construction procedure becomes automatic. Numerical examples are included to demonstrate the effectiveness of the proposed new algorithm.

Video activity extraction and reporting with incremental unsupervised learning

The present work presents a new method for activity extraction and reporting from video based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to discover the points of entry and exit of mobiles appearing in the scene. In a second step, proximity relations between resulting clusters of detected mobiles and contextual elements from the scene are modeled employing fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows building the structure of the scene and characterises the ongoing different activities of the scene. Discovered activity zones can be reported as activity maps with different granularities thanks to the analysis of the transitive closure matrix. Taking advantage of the soft relation properties, activity zones and related activities can be labeled in a more human-like language. We present results obtained on real videos corresponding to apron monitoring in the Toulouse airport in France.

Perturbation, extraction and refinement of invariant pairs for matrix polynomials

Generalizing the notion of an eigenvector, invariant subspaces are frequently used in the context of linear eigenvalue problems, leading to conceptually elegant and numerically stable formulations in applications that require the computation of several eigenvalues and/or eigenvectors. Similar benefits can be expected for polynomial eigenvalue problems, for which the concept of an invariant subspace needs to be replaced by the concept of an invariant pair. Little has been known so far about numerical aspects of such invariant pairs. The aim of this paper is to fill this gap. The behavior of invariant pairs under perturbations of the matrix polynomial is studied and a first-order perturbation expansion is given. From a computational point of view, we investigate how to best extract invariant pairs from a linearization of the matrix polynomial. Moreover, we describe efficient refinement procedures directly based on the polynomial formulation. Numerical experiments with matrix polynomials from a number of applications demonstrate the effectiveness of our extraction and refinement procedures.

Optimisation of the extraction and processing conditions of chamomile (Matricaria chamomilla L.) for incorporation into a beverage

The total phenols, apigenin 7-glucoside, turbidity and colour of extracts from dried chamomile flowers were studied with a view to develop chamomile extracts with potential anti-inflammatory properties for incorporation into beverages. The extraction of all constituents followed pseudo first-order kinetics. In general, the rate constant (k) increased as the temperature increased from 57 to 100 °C. The turbidity only increased significantly between 90 and 100 °C. Therefore, aqueous chamomile extracts had maximum total phenol concentration and minimum turbidity when extracted at 90 °C for 20 min. The effect of drying conditions on chamomile extracted using these conditions was determined. A significant reduction in phenol concentration, from 19.7 ± 0.5 mg/g GAE in fresh chamomile to 13 ± 1 mg/g GAE, was found only in the plant material oven-dried at 80 °C (p ⩽ 0.05). The biggest colour change was between fresh chamomile and that oven-dried at 80 °C, followed by samples air-dried. There was no significant difference in colour of material freeze-dried and oven-dried at 40 °C.

Towards pain-free diagnosis of skin diseases through multiplexed microneedles: biomarker extraction and detection using a highly sensitive blotting method

Immunodiagnostic microneedles provide a novel way to extract protein biomarkers from the skin in a minimally invasive manner for analysis in vitro. The technology could overcome challenges in biomarker analysis specifically in solid tissue, which currently often involves invasive biopsies. This study describes the development of a multiplex immunodiagnostic device incorporating mechanisms to detect multiple antigens simultaneously, as well as internal assay controls for result validation. A novel detection method is also proposed. It enables signal detection specifically at microneedle tips and therefore may aid the construction of depth profiles of skin biomarkers. The detection method can be coupled with computerised densitometry for signal quantitation. The antigen specificity, sensitivity and functional stability of the device were assessed against a number of model biomarkers. Detection and analysis of endogenous antigens (interleukins 1α and 6) from the skin using the device was demonstrated. The results were verified using conventional enzyme-linked immunosorbent assays. The detection limit of the microneedle device, at ≤10 pg/mL, was at least comparable to conventional plate-based solid-phase enzyme immunoassays.

Extraction behavior of the synergistic system 2,6-bis-(benzoxazolyl)-4-dodecyloxylpyridine and 2-bromodecanoic acid using Am and Eu as radioactive tracers

In this study, the extraction properties of a synergistic system consisting of 2,6-bis-(benzoxazolyl)-4-dodecyloxylpyridine (BODO) and 2-bromodecanoic acid (HA) in tert-butyl benzene (TBB) have been investigated as a function of ionic strength by varying the nitrate ion and perchlorate ion concentrations. The influence of the hydrogen ion concentration has also been investigated. Distribution ratios between 0.03-12 and 0.003-0.8 have been found for Am(III) and Eu(HI), respectively, but there were no attempts to maximize these values. It has been shown that the distribution ratios decrease with increasing amounts of ClO4-, NO3-, and H+. The mechanisms, however, by which the decrease occurs, are different. In the case of increasing perchlorate ion concentration, the decrease in extraction is linear in a log-log plot of the distribution ratio vs. the ionic strength, while in the nitrate case the complexation between nitrate and Am or Eu increases at high nitrate ion concentrations and thereby decreases the distribution ratio in a non-linearway. The decrease in extraction could be caused by changes in activity coefficients that can be explained with specific ion interaction theory (SIT); shielding of the metal ions, and by nitrate complexation with Am and Eu as competing mechanism at high ionic strengths. The separation factor between Am and Eu reaches a maximum at similar to1 M nitrate ion concentration. Thereafter the values decrease with increasing nitrate ion concentrations.

An investigation into the extraction of americium(III), lanthanides and D-block metals by 6,6 '-bis-(5,6-dipentyl-[1,2,4]triazin-3-yl)-[2,2 ']bipyridinyl(C-5-BTBP)

The tetradentate ligand (C-5-BTBP) was able to extract americium(III) selectively from nitric acid. In octanol/kerosene the distribution ratios suggest that stripping will be possible. C-5-BTBP has unusual properties and potentially offers a means of separating metals, which otherwise are difficult to separate. For example C-5-BTBP has the potential to separate paliadium(II) from a mixture containing rhodium(III) and ruthenium(H) nitrosyl. In addition, C-5-BTBP has the potential to remove traces of cadmium from effluent or from solutions of other metals contaminated with cadmium. C-5-BTBP has potential as a reagent for the separation of americium(III) from solutions contaminated with iron(III) and nickel(II), hence offering a means of concentrating americium(III) for analytical purposes from nitric acid solutions containing high concentrations of iron(III) or nickel(II).

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

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.