Activity of glucose oxidase functionalized onto magnetic nanoparticles

BACKGROUND: Magnetic nanoparticles have been significantly used for coupling with biomolecules, due to their unique properties. METHODS: Magnetic nanoparticles were synthesized by thermal co-precipitation of ferric and ferrous chloride using two different base solutions. Glucose oxidase was bound to the particles by direct attachment via carbodiimide activation or by thiophene acetylation of magnetic nanoparticles. Transmission electron microscopy was used to characterize the size and structure of the particles while the binding of glucose oxidase to the particles was confirmed using Fourier transform infrared spectroscopy. RESULTS: The direct binding of glucose oxidase via carbodiimide activity was found to be more effective, resulting in bound enzyme efficiencies between 94–100% while thiophene acetylation was 66–72% efficient. Kinetic and stability studies showed that the enzyme activity was more preserved upon binding onto the nanoparticles when subjected to thermal and various pH conditions. The overall activity of glucose oxidase was improved when bound to magnetic nanoparticles CONCLUSION: Binding of enzyme onto magnetic nanoparticles via carbodiimide activation is a very efficient method for developing bioconjugates for biological application

Job Turnover, Unemployment and Labor Market Institutions

This paper studies the role of labor market institutions on unemployment and on the cyclical properties of job flows. We construct an intertemporal general equilibrium model with search unemployment and endogenous job turnover, and examine the consequences of introducing an unemployment benefit, a firing cost and a downward wage rigidity. The simulations suggest that downward wage rigidities, rather than unemployment benefit or firing cost, may well play a dominant role in explaining both the high unemployment rate and the job flows dynamics of such an economy.Unemployment, Job flows dynamics, Institutions

Mean Likelihood Estimation And Time Series Analysis

In this thesis, I develop mean likelihood estimation (MeLE) and maximum likelihood estimation (MLE) for the parameters of a fractionally differenced autoregressive moving average (FARMA) model and its integrated form (IFARMA).;In chapter 1, I study the sampling distribution theory of MeLE by embedding the estimation problem into a Bayesian model.;In chapter 2, I apply MeLE and MLE to the estimation of the moving average parameter of a MA(1) model. The main result is that the MeLE has a smaller mean square error than the MLE when the moving average parameter is sufficiently inside the parameter space. I also demonstrate that the concentrated likelihood function of a time series with a MA(1) component has a local maximum or minimum at the boundary {dollar}\pm{dollar}1.;In chapter 3, I give the theory and methods needed to simulate FARMA series and to estimate the parameters of the FARMA model by MeLE and MLE. I explain how to calculate the exact value of the likelihood function for the parameters of a FARMA model. I show how to integrate functions over the stationary and invertible region of an ARMA process. Finally, I conduct simulation studies that compare the MLE and MeLE in combination with various algorithms to calculate them.;In the last chapter, I solve the problem of defining a likelihood function that unifies both the stationary FARMA and non-stationary IFARMA models, and I show how to select an appropriate model for a given time series by using a minimum information criteria strategy

Critères d’attribution des allocations chômage et performances du marché du travail

Dans cet article, nous étudions les effets des critères d’attribution des allocations chômage dans un modèle de chômage d’équilibre où les efforts de recherche et les salaires sont endogènes. La prise en compte d’une durée d’emploi minimale exigée pour bénéficier des prestations d’assurance permet ainsi de nuancer, à taux de taxe donné, le rôle des salaires dans la détermination du profil optimal des allocations. Les simulations du modèle suggèrent que la baisse des salaires des employés non-éligibles contribue à la plus grande efficacité, en termes d’emploi et de bien-être aggrégé, d’un profil dégressif des allocationschômage. Nous montrons aussi qu’un durcissement des conditions d’éligibilité peut être favorable à l’emploi et au bien-être de tous les travailleurs lorsque les salaires sont endogènes. Enfin, à taux de chômage donné, la détermination du profil optimal de l’indemnisation implique que la flexibilité salariale doit être associée à la poursuite d’une objectif utilitariste. L’application du critère de bien-être rawlsien plaide cependant en faveur d’une forte rigidité des salaires.Unemployment benefits, matching models, unemployment, welfare

Design of Optimum Torsionally Flexible PropRotors for Tilt-Body MAVs

This paper presents a methodology to design the optimum proprotor for tilt-body microair-vehicles (TB-MAV) with efficient global propulsion system and long flight endurance in both cruise and hover modes. The TB-MAV developed at ISAE, which is called MAVion, was used as a baseline in the design process. To acquire maximum performance of TB-MAV’s global propulsion system, an efficient optimization process of the proprotor propulsion system was carried out. The optimization process consists of two-step inverse design methods. The first step determines the optimal operating conditions in terms of power and rotational speed of proprotor and the second step designs the optimal blade geometry in terms of twist angle distribution. The optimal blade twist distribution along the blade was computed using the Glauert’s strip theory for minimum energy loss condition. Meanwhile, the optimal operating conditions were determined by the motor outputs corresponding to high motor efficiency. A comparison of performance in terms of total efficiency and flight endurance between the optimized flexible proprotor, the optimized rigid proprotor, optimized propeller and optimized rotor is presented