Electroanalytical Method for the Analysis of Methyldopa In Pharmaceutical Tablets Using a Crude Extract of Laccase from Pycnoporus sanguineus as Oxidizing Agent

Several colorimetric and chromatographic methods have been used for the identification and quantification of methyldopa (MA) in pharmaceutical formulations and clinical samples. However, these methods are time- and reagent-consuming, which stimulated our efforts to develop a simple, fast, and low-cost alternative method. We carried out an electroanalytical method for the determination of MA in pharmaceutical formulations using the crude enzymatic extract of laccase from Pycnoporus sanguineus as oxidizing agent. This method is based on the biochemical oxidation of MA by laccase (LAC), both in solution, followed by electrochemical reduction on glassy carbon electrode surface. This method was employed for the determination of MA in pure and pharmaceutical formulations and compared with the results obtained using the official method. A wide linear curve from 23 x 10(-5) to 1 x 10(-4) mol L(-1) was found with a detection limit calculated from 43 x 10(-6) mol L(-1).

The Compromised Researcher : Issues in Feminist Research Methodologies

This article centres on issues of vulnerability and being compromised in feminist research where the focus has frequently been on researching the same. Compromise, here used in its pejorative sense, may for instance occur in terms of one’s research topic, the methods one utilizes, or the participants chosen for a study. Drawing on a range of examples including the methodological work of Ann Oakley (1981, 2000) as well as three articles on researching men that appeared in the journal Signs in 2005, I argue that feminist researchers, possibly because they work in an identity-based discipline, may be diversely vulnerable when researching the same and/or researching the different, and can be compromised both by how they are treated by those whom they encounter in their research and by their own behaviour in that context. I suggest that these concerns are under-articulated in feminist research and conclude with a series of questions that need to be raised. 

Data based Calibration System for Radar used by Vehicle Activated Signs

The accurate measurement of a vehicle’s velocity is an essential feature in adaptive vehicle activated sign systems. Since the velocities of the vehicles are acquired from a continuous wave Doppler radar, the data collection becomes challenging. Data accuracy is sensitive to the calibration of the radar on the road. However, clear methodologies for in-field calibration have not been carefully established. The signs are often installed by subjective judgment which results in measurement errors. This paper develops a calibration method based on mining the data collected and matching individual vehicles travelling between two radars. The data was cleaned and prepared in two ways: cleaning and reconstructing. The results showed that the proposed correction factor derived from the cleaned data corresponded well with the experimental factor done on site. In addition, this proposed factor showed superior performance to the one derived from the reconstructed data.

Towards Motivation-based Plan Evaluation

AI planning systems tend to be disembodied and are not situated within the environment for which plans are generated, thus losing information concerning the interaction between the system and its environment. This paper argues that such information may potentially be valuable in constraining plan formulation, and presents both an agent- and domainindependent architecture that extends the classical AI planning framework to take into account context, or the interaction between an autonomous situated planning agent and its environment. The paper describes how context constrains the goals an agent might generate, enables those goals to be prioritised, and constrains plan selection.

Technology diffusion: analysing the diffusion of agent technologies

Despite several examples of deployed agent systems, there remain barriers to the large-scale adoption of agent technologies. In order to understand these barriers, this paper considers aspects of marketing theory which deal with diffusion of innovations and their relevance to the agents domain and the current state of diffusion of agent technologies. In particular, the paper examines the role of standards in the adoption of new technologies, describes the agent standards landscape, and compares the development and diffusion of agent technologies with that of object-oriented programming. The paper also reports on a simulation model developed in order to consider different trajectories for the adoption of agent technologies, with trajectories based on various assumptions regarding industry structure and the existence of competing technology standards. We present details of the simulation model and its assumptions, along with the results of the simulation exercises.

Modelling and Administration of Contract-Based Systems

Mirroring the paper versions exchanged between businesses today, electronic contracts offer the possibility of dynamic, automatic creation and enforcement of restrictions and compulsions on agent behaviour that are designed to ensure business objectives are met. However, where there are many contracts within a particular application, it can be difficult to determine whether the system can reliably fulfil them all; computer-parsable electronic contracts may allow such verification to be automated. In this paper, we describe a conceptual framework and architecture specification in which normative business contracts can be electronically represented, verified, established, renewed, etc. In particular, we aim to allow systems containing multiple contracts to be checked for conflicts and violations of business objectives. We illustrate the framework and architecture with an aerospace example.

Norm-based behaviour modification in BDI agents

While there has been much work on developing frameworks and models of norms and normative systems, consideration of the impact of norms on the practical reasoning of agents has attracted less attention. The problem is that traditional agent architectures and their associated languages provide no mechanism to adapt an agent at runtime to norms constraining their behaviour. This is important because if BDI-type agents are to operate in open environments, they need to adapt to changes in the norms that regulate such environments. In response, in this paper we provide a technique to extend BDI agent languages, by enabling them to enact behaviour modification at runtime in response to newly accepted norms. Our solution consists of creating new plans to comply with obligations and suppressing the execution of existing plans that violate prohibitions. We demonstrate the viability of our approach through an implementation of our solution in the AgentSpeak(L) language.

Comparing value-at-risk methodologies

In this paper, we compare four different Value-at-Risk (V aR) methodologies through Monte Carlo experiments. Our results indicate that the method based on quantile regression with ARCH effect dominates other methods that require distributional assumption. In particular, we show that the non-robust methodologies have higher probability to predict V aRs with too many violations. We illustrate our findings with an empirical exercise in which we estimate V aR for returns of S˜ao Paulo stock exchange index, IBOVESPA, during periods of market turmoil. Our results indicate that the robust method based on quantile regression presents the least number of violations.

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

Using an animated pedagogical agent to interact affectively with the student

This work proposes an animated pedagogical agent that has the role of providing emotional support to the student: motivating and encouraging him, making him believe in his self-ability, and promoting a positive mood in him, which fosters learning. This careful support of the agent, its affective tactics, is expressed through emotional behaviour and encouragement messages of the lifelike character. Due to human social tendency of anthropomorphising software, we believe that a software agent can accomplish this affective role. In order to choose the adequate affective tactics, the agent should also know the student’s emotions. The proposed agent recognises the student’s emotions: joy/distress, satisfaction/disappointment, anger/gratitude, and shame, from the student’s observable behaviour, i. e. his actions in the interface of the educational system. The inference of emotions is psychologically grounded on the cognitive theory of emotions. More specifically, we use the OCC model which is based on the cognitive approach of emotion and can be computationally implemented. Due to the dynamic nature of the student’s affective information, we adopted a BDI approach to implement the affective user model and the affective diagnosis. Besides, in our work we profit from the reasoning capacity of the BDI approach in order for the agent to deduce the student’s appraisal, which allows it to infer the student’s emotions. As a case study, the proposed agent is implemented as the Mediating Agent of MACES: an educational collaborative environment modelled as a multi-agent system and pedagogically based on the sociocultural theory of Vygotsky.

Assessing interdependence among countries' fundamentals and its implications for exchange rate misalignment estimates: An empirical exercise based on GVAR

Exchange rates are important macroeconomic prices and changes in these rates a ect economic activity, prices, interest rates, and trade ows. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that the global vector autoregressions model (GVAR) proposed by Pesaran and co-authors can add relevant information to the literature on measuring exchange rate misalignment. Our empirical exercise suggests that the estimate exchange rate misalignment obtained from GVAR can be quite di erent to that using the traditional cointegrated time series techniques, which treat countries as detached entities. The di erences between the two approaches are more pronounced for small and developing countries. Our results also suggest a strong interdependence among eurozone countries, as expected

Addressing important econometric issues on how to construct theoretical based exchange rate misalignment estimates

Exchange rate misalignment assessment is becoming more relevant in recent period particularly after the nancial crisis of 2008. There are di erent methodologies to address real exchange rate misalignment. The real exchange misalignment is de ned as the di erence between actual real e ective exchange rate and some equilibrium norm. Di erent norms are available in the literature. Our paper aims to contribute to the literature by showing that Behavioral Equilibrium Exchange Rate approach (BEER) adopted by Clark & MacDonald (1999), Ubide et al. (1999), Faruqee (1994), Aguirre & Calderón (2005) and Kubota (2009) among others can be improved in two following manners. The rst one consists of jointly modeling real e ective exchange rate, trade balance and net foreign asset position. The second one has to do with the possibility of explicitly testing over identifying restrictions implied by economic theory and allowing the analyst to show that these restrictions are not falsi ed by the empirical evidence. If the economic based identifying restrictions are not rejected it is also possible to decompose exchange rate misalignment in two pieces, one related to long run fundamentals of exchange rate and the other related to external account imbalances. We also discuss some necessary conditions that should be satis ed for disrcarding trade balance information without compromising exchange rate misalignment assessment. A statistical (but not a theoretical) identifying strategy for calculating exchange rate misalignment is also discussed. We illustrate the advantages of our approach by analyzing the Brazilian case. We show that the traditional approach disregard important information of external accounts equilibrium for this economy.

Development of a novel microextraction by packed sorbent-based approach followed by ultrahigh pressure liquid chromatography as a powerful technique for quantification phenolic constituents of biological interest in wines

A novel analytical approach, based on a miniaturized extraction technique, the microextraction by packed sorbent (MEPS), followed by ultrahigh pressure liquid chromatography (UHPLC) separation combined with a photodiode array (PDA) detection, has been developed and validated for the quantitative determination of sixteen biologically active phenolic constituents of wine. In addition to performing routine experiments to establish the validity of the assay to internationally accepted criteria (linearity, sensitivity, selectivity, precision, accuracy), experiments are included to assess the effect of the important experimental parameters on the MEPS performance such as the type of sorbent material (C2, C8, C18, SIL, and M1), number of extraction cycles (extract-discard), elution volume, sample volume, and ethanol content, were studied. The optimal conditions of MEPS extraction were obtained using C8 sorbent and small sample volumes (250 μL) in five extraction cycle and in a short time period (about 5 min for the entire sample preparation step). The wine bioactive phenolics were eluted by 250 μL of the mixture containing 95% methanol and 5% water, and the separation was carried out on a HSS T3 analytical column (100 mm × 2.1 mm, 1.8 μm particle size) using a binary mobile phase composed of aqueous 0.1% formic acid (eluent A) and methanol (eluent B) in the gradient elution mode (10 min of total analysis). The method gave satisfactory results in terms of linearity with r2-values > 0.9986 within the established concentration range. The LOD varied from 85 ng mL−1 (ferulic acid) to 0.32 μg mL−1 ((+)-catechin), whereas the LOQ values from 0.028 μg mL−1 (ferulic acid) to 1.08 μg mL−1 ((+)-catechin). Typical recoveries ranged between 81.1 and 99.6% for red wines and between 77.1 and 99.3% for white wines, with relative standard deviations (RSD) no larger than 10%. The extraction yields of the MEPSC8/UHPLC–PDA methodology were found between 78.1 (syringic acid) and 99.6% (o-coumaric acid) for red wines and between 76.2 and 99.1% for white wines. The inter-day precision, expressed as the relative standard deviation (RSD%), varied between 0.2% (p-coumaric and o-coumaric acids) and 7.5% (gentisic acid) while the intra-day precision between 0.2% (o-coumaric and cinnamic acids) and 4.7% (gallic acid and (−)-epicatechin). On the basis of analytical validation, it is shown that the MEPSC8/UHPLC–PDA methodology proves to be an improved, reliable, and ultra-fast approach for wine bioactive phenolics analysis, because of its capability for determining simultaneously in a single chromatographic run several bioactive metabolites with high sensitivity, selectivity and resolving power within only 10 min. Preliminary studies have been carried out on 34 real whole wine samples, in order to assess the performance of the described procedure. The new approach offers decreased sample preparation and analysis time, and moreover is cheaper, more environmentally friendly and easier to perform as compared to traditional methodologies.