Direct electroanalytical determination of fluvastatin in a pharmaceutical dosage form: batch and flow analysis

The reduction of luvastatin (FLV) at a hanging mercury-drop electrode (HMDE) was studied by square-wave adsorptive-stripping voltammetry (SWAdSV). FLV can be accumulated and reduced at the electrode, with a maximum peak current intensity at a potential of approximately 1.26V vs. AgCl=Ag, in an aqueous electrolyte solution of pH 5.25. The method shows linearity between peak current intensity and FLV concentration between 1.0 10 8 and 2.7 10 6 mol L 1. Limits of detection (LOD) and quantification (LOQ) were found to be 9.9 10 9 mol L 1 and 3.3 10 8 mol L 1, respectively. Furthermore, FLV oxidation at a glassy carbon electrode surface was used for its hydrodynamic monitoring by amperometric detection in a flow-injection system. The amperometric signal was linear with FLV concentration over the range 1.0 10 6 to 1.0 10 5 mol L 1, with an LOD of 2.4 10 7 mol L 1 and an LOQ of 8.0 10 7 mol L 1. A sample rate of 50 injections per hour was achieved. Both methods were validated and showed to be precise and accurate, being satisfactorily applied to the determination of FLV in a commercial pharmaceutical.

A type system for value-dependent information flow analysis

Information systems are widespread and used by anyone with computing devices as well as corporations and governments. It is often the case that security leaks are introduced during the development of an application. Reasons for these security bugs are multiple but among them one can easily identify that it is very hard to define and enforce relevant security policies in modern software. This is because modern applications often rely on container sharing and multi-tenancy where, for instance, data can be stored in the same physical space but is logically mapped into different security compartments or data structures. In turn, these security compartments, to which data is classified into in security policies, can also be dynamic and depend on runtime data. In this thesis we introduce and develop the novel notion of dependent information flow types, and focus on the problem of ensuring data confidentiality in data-centric software. Dependent information flow types fit within the standard framework of dependent type theory, but, unlike usual dependent types, crucially allow the security level of a type, rather than just the structural data type itself, to depend on runtime values. Our dependent function and dependent sum information flow types provide a direct, natural and elegant way to express and enforce fine grained security policies on programs. Namely programs that manipulate structured data types in which the security level of a structure field may depend on values dynamically stored in other fields The main contribution of this work is an efficient analysis that allows programmers to verify, during the development phase, whether programs have information leaks, that is, it verifies whether programs protect the confidentiality of the information they manipulate. As such, we also implemented a prototype typechecker that can be found at http://ctp.di.fct.unl.pt/DIFTprototype/.

Production Linkages Between Informal and Formal Activities Considering Domestic and Imported Inputs: an Application of the Minimal-Flow-Analysis Method to Senegal.

We apply to the Senegalese input-output matrix of 1990, disagregated into formal and informal activities, a recently designed structural analytical method (Minimal-Flow-Analysis) which permits to depict the direct and indirect production likanges existing between activities.

Flow analysis based on a pulsed flow of solution: theory, instrumentation and applications

The increased demands placed on solution propulsion by programmed flow systems, such as sequential injection analysis, lab-on-value technology, bead injection and multi-commutation, has highlighted the inability of many conventional pumps to generate a smooth, consistent flow. A number of researchers have examined ways to overcome the inadvertent, uncontrolled pulsation caused by the mechanical action of peristaltic pumps. In contrast, we have developed instruments that exploit the characteristics of a reproducible pulsed flow of solution. In this paper, we discuss our instrumental approaches and some applications that have benefited from the use of a reproducible pulsed flow rather than the traditional linear flow approach. To place our approach in the context of the continuously developing field of flow analysis, an overview of other programmed flow systems is also presented.

Determination of sodium oxalate in Bayer liquor using flow-analysis incorporating an anion exchange column and tris(2,2`-bipyridyl)ruthenium(II) chemiluminescence detection

Semi-automated flow injection instrumentation, incorporating a small anion exchange column coupled with tris(2,2′-bipyridyl)ruthenium(II) (Ru(bipy)₃²⁺) chemiluminescence detection, was configured and utilised to develop rapid methodology for the determination of sodium oxalate in Bayer liquors. The elimination of both negative and positive interferences from aluminium(III) and, as yet, unknown concomitant organic species, respectively are discussed. The robustness of the methodology was considerably enhanced by using the temporally stable form of the chemiluminescence reagent, tris(2,2′-bipyridyl)ruthenium(III) perchlorate in dry acetonitrile. Real Bayer process samples were analysed and the results obtained compared well with those performed using standard methods within industrial laboratories.

Detection of pyrrolizidine alkaloids using flow analysis with both acidic potassium permanganate and tris(2,2’-bipyridyl)ruthenium(II) chemiluminescence

For the first time, analytically useful chemiluminescence was elicited from the reactions of the pyrrolizidine alkaloids. Heliotrine, retronecine, supinine, monocrotaline and echinatine N-oxide yielded chemiluminescence upon reaction with tris(2,2′-bipyridyl)ruthenium(II) whilst lasiocarpine, its N-oxide and supinine elicited light upon reaction with acidic potassium permanganate. Detection limits for heliotrine were 1.25 × 10⁻⁷ M and 9 × 10⁻⁹ M for tris(2,2′-bipyridyl)ruthenium(III) perchlorate with flow injection analysis (FIA) and the silica-immobilised reagent (4-[4-(dichloromethylsilanyl)-butyl]-4′-methyl-2,2′-bipyridine)bis(2,2′-bipyridyl)ruthenium(II) with sequential injection analysis (SIA), respectively. Lasiocarpine was detectable at 1.4 × 10⁻⁷ M using acidic potassium permanganate with FIA. Additionally, the silica-immobilised reagent was optimised with respect to the oxidant (ammonium ceric nitrate) concentration and the aspiration times which afforded a detection limit for codeine of 5 × 10⁻¹⁰ M using SIA.

Plant bioactive determinations using flow analysis, chromatography with chemiluminescence detection

The development of rapid analytical methodologies for the determination of plant bioactives including antioxidants, amino acids and opium alkaloids was investigated using novel flow analysis and liquid chromatographic techniques. These methodologies were applied to the wine, food and pharmaceutical industries.

Determination of sodium oxalate in Bayer process liquors using flow analysis with tris(2,2'-bipyridyl)ruthenium(II) chemiluminescence detection

The research was a detailed investigation into a challenging analytical chemistry problem for the alumina industry. The successful outcomes were derived through innovative reagent chemistry and novel instrumental development. The resultant methodology and instrumentation deployed on this most demanding sample matrix is more robust, reliable and less expensive than anything currently used in this industry worldwide.

An extended multivariate autoregressive framework for EEG-based information flow analysis of a brain network

Recently effective connectivity studies have gained significant attention among the neuroscience community as Electroencephalography (EEG) data with a high time resolution can give us a wider understanding of the information flow within the brain. Among other tools used in effective connectivity analysis Granger Causality (GC) has found a prominent place. The GC analysis, based on strictly causal multivariate autoregressive (MVAR) models does not account for the instantaneous interactions among the sources. If instantaneous interactions are present, GC based on strictly causal MVAR will lead to erroneous conclusions on the underlying information flow. Thus, the work presented in this paper applies an extended MVAR (eMVAR) model that accounts for the zero lag interactions. We propose a constrained adaptive Kalman filter (CAKF) approach for the eMVAR model identification and demonstrate that this approach performs better than the short time windowing-based adaptive estimation when applied to information flow analysis.

The relationship between labour market conditions and welfare receipt in Australia: A stock-flow analysis

Understanding the determinants of changes in welfare caseloads is an important, but little studied, topic in Australia. This paper evaluates the role of labour market conditions in explaining the changes in the Australian welfare caseload since the late 1990s. The paper employs a stock-flow approach to better control for persistence in welfare receipt and includes different specifications to deal with measurement error in labour market data. The results suggest that the labour market is an important determinant of movements on and off welfare, accounting for the majority of the caseload decline during 1997-2005. The results also highlight the importance of robustness checks when data are measured with error.

Application of extended multivariate modeling for information flow analysis of event related responses

Event related potential (ERP) analysis is one of the most widely used methods in cognitive neuroscience research to study the physiological correlates of sensory, perceptual and cognitive activity associated with processing information. To this end information flow or dynamic effective connectivity analysis is a vital technique to understand the higher cognitive processing under different events. In this paper we present a Granger causality (GC)-based connectivity estimation applied to ERP data analysis. In contrast to the generally used strictly causal multivariate autoregressive model, we use an extended multivariate autoregressive model (eMVAR) which also accounts for any instantaneous interaction among variables under consideration. The experimental data used in the paper is based on a single subject data set for erroneous button press response from a two-back with feedback continuous performance task (CPT). In order to demonstrate the feasibility of application of eMVAR models in source space connectivity studies, we use cortical source time series data estimated using blind source separation or independent component analysis (ICA) for this data set.

Multivariate autoregressive-based neuronal network flow analysis for in-vitro recorded bursts

Neuroscientific studies of in vitro neuron cell cultures has attracted paramount attention to investigate the behaviour of neuronal networks in response to different environmental conditions and external stimuli such as drugs, optical and electrical stimulations. Microelec trodearray (MEA) technology has been widely adopted as a tool for this investigation. In this work, we present a new approach to estimate interconnectivity of neural spikes using multivariate autoregressive (MVAR) analysis and Partial Directed Coherence (PDC). The proposed approach has the potential to discover hidden intra-burst causal connectivity patterns and to help understand the spatiotemporal communication patterns within bursts, pre and post stimulations.

A Time-domain Harmonic Power-Flow Analysis in Electrical Energy Distribution Networks, Using Norton Models for Non-linear Loading

The purpose of this paper is to present the application of a three-phase harmonic propagation analysis time-domain tool, using the Norton model to approach the modeling of non-linear loads, making the harmonics currents flow more appropriate to the operation analysis and to the influence of mitigation elements analysis. This software makes it possible to obtain results closer to the real distribution network, considering voltages unbalances, currents imbalances and the application of mitigation elements for harmonic distortions. In this scenario, a real case study with network data and equipments connected to the network will be presented, as well as the modeling of non-linear loads based on real data obtained from some PCCs (Points of Common Coupling) of interests for a distribution company.