Microwave-assisted digestion procedures for biological samples with diluted nitric acid: Identification of reaction products

Microwave-assisted sample preparation using diluted nitric acid solutions is an alternative procedure for digesting organic samples. The efficiency of this procedure depends on the chemical properties of the samples and in this work it was evaluated by the determination of crude protein amount. fat and original carbon. Soybeans grains, bovine blood. bovine muscle and bovine viscera were digested in a cavity-microwave oven using oxidant mixtures in different acid concentrations. The digestion efficiency was evaluated based on the determination of residual carbon content and element recoveries using inductively coupled plasma optical emission spectrometry (ICP OES). In order to determine the main residual organic compounds, the digests were characterized by nuclear magnetic resonance (1 H NMR). Subsequently, studies concerning separation of nitrobenzoic acid isomers were performed by ion pair reversed phase liquid chromatography using a C18 stationary phase, water:acetonitrile:methanol (75:20:5, v/v/v) +0.05% (v/v) TFA as mobile phase and ultraviolet detection at 254 nm. Sample preparation based on diluted acids proved to be feasible and a recommendable alternative for organic sample digestion, reducing both the reagent volumes and the variability of the residues as a result of the process of decomposition. It was shown that biological matt-ices containing amino acids, proteins and lipids in their composition produced nitrobenzoic acid isomers and other organic compounds after cleavage of chemical bonds. (C) 2009 Elsevier B.V. All rights reserved.

Pedal : identification of models for duodenal administration of levodopa

Backgound and aims: The main purpose of the PEDAL study is to identify and estimate sample individual pharmacokinetic- pharmacodynamic (PK/PD) models for duodenal infusion of levodopa/carbidopa (Duodopa®) that can be used for in numero simulation of treatment strategies. Other objectives are to study the absorption of Duodopa® and to form a basis for power calculation for a future larger study. PK/PD based on oral levodopa is problematic because of irregular gastric emptying. Preliminary work with data from [Gundert-Remy U et al. Eur J Clin Pharmacol 1983;25:69-72] suggested that levodopa infusion pharmacokinetics can be described by a two-compartment model. Background research led to a hypothesis for an effect model incorporating concentration-unrelated fluctuations, more complex than standard E-max models. Methods: PEDAL involved a few patients already on Duodopa®. A bolus dose (normal morning dose plus 50%) was given after a washout during night. Data collection continued until the clinical effect was back at baseline. The procedure was repeated on two non-consecutive days per patient. The following data were collected in 5 to 15 minutes intervals: i) Accelerometer data. ii) Three e-diary questions about ability to walk, feelings of “off” and “dyskinesia”. iii) Clinical assessment of motor function by a physician. iv) Plasma concentrations of levodopa, carbidopa and the metabolite 3-O-methyldopa. The main effect variable will be the clinical assessment. Results: At date of abstract submission, lab analyses were currently being performed. Modelling results, simulation experiments and conclusions will be presented in our poster.

Application of identification techniques to determine effect of carbon content in steels on rheological parameters during hot deformation

The objective of the present work is searching for the correlation between the carbon content in steels and the parameters of the rheological models, which are used to describe the materials behavior during hot plastic deformation. This correlation can be expected in the internal variable models, which are based on physical phenomena occurring in the material. Such a model, based on the dislocation density as the internal variable, is investigated in this work. The experiments including hot torsion tests are used for the analysis.
The procedure is composed of three parts. Plastometric tests were performed for steels with various carbon content. Optimization techniques were applied next to determine the coefficients in the internal variable rheological model for these steels. Two versions of the model are considered. One is based on the average dislocation density and the second accounts for the distribution of dislocation densities. Evaluation of correlation between carbon content and such coefficients in the models as activation energy for self diffusion, activation energy for recrystallization, grain boundary mobility, recovery coefficient etc. was the main objective of the work. In consequence, the model which may be used for simulation of hot forming processes for steels with various chemical compositions, is proposed.

Client identification and money laundering control : perspectives on the Financial Intelligence Centre Act 38 of 2001

The Financial Intelligence Centre Act 38 of 2001 (FICA) compels certain persons and institutions (defined as "accountable institutions'') to identify and verify the identity of a new client before any transaction may be concluded or any business relationship is established.1 Accountable institutions are listed in schedule ¹ to FICA and include banks, brokers, financial advisers, insurance companies, attorneys and estate agents. This duty to identify new clients came into effect on 30 June 2003. However, FICA also requires a similar procedure to be followed in respect of all current clients. Current clients are those with whom an accountable institution had business relationships on 30 June 2003.² After 30 June 2004 an institution may not conclude a transaction in the course of its business relationship with an unidentified current client, until it has established and verified that client's identity as prescribed. An institution that concludes any transaction in contravention of this prohibition, commits an offence and is liable to a fine not exceeding R10 million or to imprisonment of up to 15 years.³

The majority of accountable institutions and their clients failed to meet the June 2004 current client identification deadline.4 This failure posed serious economic and legal risks. With a few days to spare, the minister of finance granted a partial and temporary exemption in respect of these requirements. This article explores the statutory scheme for identification and re-identification of clients and some of the practical problems that were encountered. The June 2004 exemptions from these requirements are also considered and proposals for law reform are made.

The discussion of the FICA identification scheme necessitates the following brief overview of the international and South African money laundering control framework.

1 s 21(1) of FICA.
2 s 21(2) of FICA. See also s 82(2)(b).
3 s 46(2) of FICA read with s 68(1) of FICA.

Exploring metaphor as an alternative marketing language

Purpose: – The main aim of this paper is to stimulate more relevant and critical ideas about marketing and the wider management field by exploring the actual and potential contribution of metaphor to marketing theory and practice. The subsequent connections made can help contribute towards understanding and coping with the theory/practice gap.

Design/methodology/approach: – To date, the majority of metaphor application has tended to be literal and surface-level rather than theoretically grounded. This paper interrogates the literature surrounding metaphor in marketing and management fields, while also examining the contribution of other areas such as art. The paper constructs and debates the conceptual notion of the marketer as an artist.

Findings: – Incorporation of theoretically grounded metaphors into marketing theory can help develop a form of marketing which is capable of dealing with ambiguity, chaotic market conditions, creative thinking and practice.

Originality/value: – Adoption of a metaphorical approach to marketing research helps to instil a critical and creative ethos in the research process. Marketers are concerned with identification and exploitation of opportunities. Metaphor assists in the process by enhancing visualisation of these future directions. We live out our lives to a large degree through the making of metaphorical connections. We should therefore embrace more qualitative, creative associations in marketing theory, as well as practice.

Identification of implicit technical relationships in overlapping networks

Overlapping network techniques to expand the single sequential finish-to-start relationship between preceding and succeeding activities in scheduling construction projects have been developed for decades. The hidden logic relationships between activities and two virtual activities, Start and Finish, however limit the applications of these techniques in practice as they may lead to incorrect time parameters of some activities. In this research, a novel approach has been developed to identify those concealed relationships in a structured procedure by a two-dimensional nested diagram. An empirical study was carried out to demonstrate the network modification approach.

Spectral element model updating for damage identification using clonal selection algorithm

A spectral element model updating procedure is presented to identify damage in a structure using Guided wave propagation results. Two damage spectral elements (DSE1 and DSE2) are developed to model the local (cracks in reinforcement bar) and global (debonding between reinforcement bar and concrete) damage in one-dimensional homogeneous and composite waveguide, respectively. Transfer matrix method is adopted to assemble the stiffness matrix of multiple spectral elements. In order to solve the inverse problem, clonal selection algorithm is used for the optimization calculations. Two displacement-based functions and two frequency-based functions are used as objective functions in this study. Numerical simulations of wave propagation in a bare steel bar and in a reinforcement bar without and with various assumed damage scenarios are carried out. Numerically simulated data are then used to identify local and global damage of the steel rebar and the concrete-steel interface using the proposed method. Results show that local damage is easy to be identified by using any considered objective function with the proposed method while only using the wavelet energy-based objective function gives reliable identification of global damage. The method is then extended to identify multiple damages in a structure. To further verify the proposed method, experiments of wave propagation in a rectangular steel bar before and after damage are conducted. The proposed method is used to update the structural model for damage identification. The results demonstrate the capability of the proposed method in identifying cracks in steel bars based on measured wave propagation data.

Detecting K-complexes for sleep stage identification using nonsmooth optimisation

The process of sleep stage identification is a labour-intensive task that involves the specialized interpretation of the polysomnographic signals captured from a patient’s overnight sleep session. Automating this task has proven to be challenging for data mining algorithms because of noise, complexity and the extreme size of data. In this paper we apply nonsmooth optimization to extract key features that lead to better accuracy. We develop a specific procedure for identifying K-complexes, a special type of brain wave crucial for distinguishing sleep stages. The procedure contains two steps. We first extract “easily classified” K-complexes, and then apply nonsmooth optimization methods to extract features from the remaining data and refine the results from the first step. Numerical experiments show that this procedure is efficient for detecting K-complexes. It is also found that most classification methods perform significantly better on the extracted features.

Human identification from ECG signals via sparse representation of local segments

This work proposes a novel framework to extract compact and discriminative features from Electrocardiogram (ECG) signals for human identification based on sparse representation of local segments. Specifically, local segments extracted from an ECG signal are projected to a small number of basic elements in a dictionary, which is learned from training data. A final representation is extracted by performing a max pooling procedure over all the sparse coefficient vectors in the ECG signal. Unlike most of existing methods for human identification from ECG signals which require segmentation of individual heartbeats or extraction of fiducial points, the proposed method does not need to segment individual heartbeats or detect any fiducial points. The method achieves an 99.48% accuracy on a 100 subjects dataset constructed from a publicly available database, which demonstrates that both local and global structural information are well captured to characterize the ECG signals.

Vibration based damage identification of a scale-model steel frame structure subjected to bolt connection failures

Large-span steel frame structures prove to be an ideal choice for their speed of construction, relatively low cost, strength, durability and structural design flexibility. For this type of structure, the beam-column connections are critical for its structural integrity and overall stability. This is because a steel frame generally fails first at its connectors, due to the change in stress redistribution with adjacent members and material related failures, caused by various factors such as fire, seismic activity or material deterioration. Since particular attention is required at a steel frame’s connection points, this study explores the applicability of a comprehensive structural health monitoring (SHM) method to identify early damage and prolong the lifespan of connection points of steel frames. An impact hammer test was performed on a scale-model steel frame structure, recording its dynamic response to the hammer strike via an accelerometer. The testing procedure included an intact scenario and two damage scenarios by unfastening four bolt connections in an accumulating order. Based entirely on time-domain experimental data for its calibration, an Auto Regressive Average Exogenous (ARMAX) model is used to create a simple and accurate model for vibration simulation. The calibrated ARMAX model is then used to identify various bolt-connection related damage scenarios via R² value. The findings in this study suggest that the proposed time-domain approach is capable of identifying structural damage in a parsimonious manner and can be used as a quick or initial solution.

The Integrating Theory, Evidence and Action (ITEA) method: a procedure for helping practitioners translate theory and research into action

Introduction: The aim of this article is to describe and explain a new method for integrating theory and evidence that enables practitioners to translate evidence into action applied in their practice. Method: A new multiple methods procedure called the Integrating Theory, Evidence and Action method is described. It is a mixed method that progresses through seven distinct steps: clinical question, framework, identification, deconstruction, analysis, reconstruction, and transfer/utilization. An example of using this method to review evidence around occupational therapy with people recovering from alcohol misuse and/or abuse is provided. Findings: This method highlights the importance of theory, tests the empirical strength of theories, includes diverse forms of evidence, and encourages the integration of knowledge within clinical practice. Conclusion: The Integrating Theory, Evidence and Action method is accessible and useful to practitioners and will support their efforts to make their practice evidence based. Current methods of evidence-based practice focus mostly on research evidence (particularly quantitative evidence); however, research is only one of the ways of knowing that practitioners draw upon to guide their practice. This method enables occupational therapists to integrate theory, evidence, and practice in a coherent and translatable way.

Identification and estimation of interventions using changes in inequality measures

This paper presents semiparametric estimators of changes in inequality measures of a dependent variable distribution taking into account the possible changes on the distributions of covariates. When we do not impose parametric assumptions on the conditional distribution of the dependent variable given covariates, this problem becomes equivalent to estimation of distributional impacts of interventions (treatment) when selection to the program is based on observable characteristics. The distributional impacts of a treatment will be calculated as differences in inequality measures of the potential outcomes of receiving and not receiving the treatment. These differences are called here Inequality Treatment Effects (ITE). The estimation procedure involves a first non-parametric step in which the probability of receiving treatment given covariates, the propensity-score, is estimated. Using the inverse probability weighting method to estimate parameters of the marginal distribution of potential outcomes, in the second step weighted sample versions of inequality measures are computed. Root-N consistency, asymptotic normality and semiparametric efficiency are shown for the semiparametric estimators proposed. A Monte Carlo exercise is performed to investigate the behavior in finite samples of the estimator derived in the paper. We also apply our method to the evaluation of a job training program.

Development of a dynamic headspace solid-phase microextraction procedure coupled to GC–qMSD for evaluation the chemical profile in alcoholic beverages

In the present study, a simple and sensitive methodology based on dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography with quadrupole mass detection (GC–qMSD), was developed and optimized for the determination of volatile (VOCs) and semi-volatile (SVOCs) compounds from different alcoholic beverages: wine, beer and whisky. Key experimental factors influencing the equilibrium of the VOCs and SVOCs between the sample and the SPME fibre, as the type of fibre coating, extraction time and temperature, sample stirring and ionic strength, were optimized. The performance of five commercially available SPME fibres was evaluated and compared, namely polydimethylsiloxane (PDMS, 100 μm); polyacrylate (PA, 85 μm); polydimethylsiloxane/divinylbenzene (PDMS/DVB, 65 μm); carboxen™/polydimethylsiloxane (CAR/PDMS, 75 μm) and the divinylbenzene/carboxen on polydimethylsiloxane (DVB/CAR/PDMS, 50/30 μm) (StableFlex). An objective comparison among different alcoholic beverages has been established in terms of qualitative and semi-quantitative differences on volatile and semi-volatile compounds. These compounds belong to several chemical families, including higher alcohols, ethyl esters, fatty acids, higher alcohol acetates, isoamyl esters, carbonyl compounds, furanic compounds, terpenoids, C13-norisoprenoids and volatile phenols. The optimized extraction conditions and GC–qMSD, lead to the successful identification of 44 compounds in white wines, 64 in beers and 104 in whiskys. Some of these compounds were found in all of the examined beverage samples. The main components of the HS-SPME found in white wines were ethyl octanoate (46.9%), ethyl decanoate (30.3%), ethyl 9-decenoate (10.7%), ethyl hexanoate (3.1%), and isoamyl octanoate (2.7%). As for beers, the major compounds were isoamyl alcohol (11.5%), ethyl octanoate (9.1%), isoamyl acetate (8.2%), 2-ethyl-1-hexanol (5.9%), and octanoic acid (5.5%). Ethyl decanoate (58.0%), ethyl octanoate (15.1%), ethyl dodecanoate (13.9%) followed by 3-methyl-1-butanol (1.8%) and isoamyl acetate (1.4%) were found to be the major VOCs in whisky samples.

Effectiveness of different solid-phase microextraction fibres for differentiation of selected Madeira island fruits based on their volatile metabolite profile: identification of novel compounds

A headspace solid-phase microextraction (HS-SPME) procedure based on five commercialised fibres (85 μm polyacrylate – PA, 100 μm polydimethylsiloxane – PDMS, 65 μm polydimethylsiloxane/divinylbenzene – PDMS/DVB, 70 μm carbowax/divinylbenzene – CW/DVB and 85 μm carboxen/polydimethylsiloxane – CAR/PDMS) is presented for the characterization of the volatile metabolite profile of four selected Madeira island fruit species, lemon (Citrus limon), kiwi (Actinidia deliciosa), papaya (Carica papaya L.) and Chickasaw plum (Prunus angustifolia). The isolation of metabolites was followed by thermal desorption gas chromatography–quadrupole mass spectrometry (GC–qMS) methodology. The performance of the target fibres was evaluated and compared. The SPME fibre coated with CW/DVB afforded the highest extraction efficiency in kiwi and papaya pulps, while in lemon and plum the same was achieved with PMDS/DVB fibre. This procedure allowed for the identification of 80 compounds, 41 in kiwi, 24 in plums, 23 in papaya and 20 in lemon. Considering the best extraction conditions, the most abundant volatiles identified in kiwi were the intense aldehydes and ethyl esters such as (E)-2-hexenal and ethyl butyrate, while in Chicasaw plum predominate 2-hexenal, 2-methyl-4-pentenal, hexanal, (Z)-3-hexenol and cyclohexylene oxide. The major compounds identified in the papaya pulp were benzyl isothiocyanate, linalool oxide, furfural, hydroxypropanone, linalool and acetic acid. Finally, lemon was shown to be the most divergent of the four fruits, being its aroma profile composed almost exclusively by terpens, namely limonene, γ-terpinene, o-cymene and α-terpinolene. Thirty two volatiles were identified for the first time in the fruit or close related species analysed and 14 volatiles are reported as novel volatile metabolites in fruits. This includes 5 new compounds in kiwi (2-cyclohexene-1,4-dione, furyl hydroxymethyl ketone, 4-hydroxydihydro-2(3H)-furanone, 5-acetoxymethyl-2-furaldehyde and ethanedioic acid), 4 in plum (4-hydroxydihydro-2(3H)-furanone, 5-methyl-2-pyrazinylmethanol, cyclohexylene oxide and 1-methylcyclohexene), 4 in papaya (octaethyleneglycol, 1,2-cyclopentanedione, 3-methyl-1,2-cyclopentanedione and 2-furyl methyl ketone) and 2 in lemon (geranyl farnesate and safranal). It is noteworthy that among the 15 volatile metabolites identified in papaya, 3-methyl-1,2-cyclopentanedione was previously described as a novel PPARγ (peroxisome proliferator-activated receptor γ) agonist, having a potential to minimize inflammation.

Identification of Mechanical Systems through Kautz Filter

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