Effect of microcrystalline and microfibrillated cellulose on the evolution of hydration of cement pastes by thermogravimetry

Journal of Thermal Analysis and Calorimetry - The interest in the use of cellulose fibers of increasingly smaller sizes in cementitious materials has increased in recent years. This paper brings...     

Recent results from the TCV tokamak

During the first two years of operation, the TCV tokamak has produced a large variety of plasma shapes and magnetic configurations, with 1.0B _tor1.46T,I _p800kA,k2.05, –0.71. A new shape control algorithm, based on a finite element reconstruction of the plasma current in real time, has been implemented. Vertical growth rates up to 1000s^–1 have been stabilized using the external coil system. Ohmic H-modes with Troyon factors ( _tor aB/I _p) up to two and densities up to 2.25×10²⁰m^–3, corresponding to the Greenwald limit, have been obtained in diverted discharges. Limiter H-modes with line averaged electron densities up to 1.7×10²⁰m^–3 have been obtained in elongated D-shaped plasmas with 360 kAI _P600 kA.Presented at 17^th Symposium Plasma Physics and Technology, Prague, June 13–16, 1995.This work was partly supported by the Fonds National Suisse de la Recherche Scientifique.     

Gompertz zero-inflated cure rate regression models applied to credit risk data

In the financial market, it is important to consider that there is a proportion of customers that have settled their debt in time zero, immediately recovering their ability to pay. In this context, in this paper, we propose a survival analysis methodology that allows the insertion of times equal to zero in scenarios where credit risk is observed. The proposed model addresses the survival analysis model of the zero-inflated cure rate which incorporates the heterogeneity of three subgroups (individuals having events in the initial time, and individuals not susceptible and susceptible to the event). In our proposal, all available survival data of customers are modeled considering that the number of competitive causes follows a Poisson distribution and the baseline risk function follows a Gompertz distribution. The model parameter estimation is obtained by the maximum likelihood estimation procedure and simulation studies are conducted to evaluate the estimators' performance. The studied methodology will be applied to a credit database provided by a financial institution in Brazil.     

Use of pruned computational neural networks for processing the response of oscillating chemical reactions with a view to analyzing nonlinear multicomponent mixtures

The suitability of pruned computational neural networks (CNNs) for resolving nonlinear multicomponent systems involving synergistic effects by use of oscillating chemical reaction-based methods implemented using the analyte pulse perturbation technique is demonstrated. The CNN input data used for this purpose are estimates provided by the Levenberg-Marquardt method in the form of a three-parameter Gaussian curve associated with the singular profile obtained when the oscillating system is perturbed by an analyte mixture. The performance of the proposed method was assessed by applying it to the resolution of mixtures of pyrogallol and gallic acid based on their perturbating effect on a classical oscillating chemical system, viz. the Belousov-Zhabotinskyi reaction. A straightforward network topology (3:3:2, with 18 connections after pruning) allowed the resolution of mixtures of the two analytes in concentration ratios from 1:7 to 6:2 with a standard error of prediction for the testing set of 4.01 and 8.98% for pyrogallol and gallic acid, respectively. The reduced dimensions of the selected CNN architecture allowed a mathematical transformation of the input vector into the output one that can be easily implemented via software. Finally, the suitability of response surface analysis as an alternative to CNNs was also tested. The results were poor (relative errors were high), which confirms that properly selected pruned CNNs are effective tools for solving the analytical problem addressed in this work.     

A coupling cutting stock-lot sizing problem in the paper industry

An important production programming problem arises in paper industries coupling multiple machine scheduling with cutting stocks. Concerning machine scheduling: how can the production of the quantity of large rolls of paper of different types be determined. These rolls are cut to meet demand of items. Scheduling that minimizes setups and production costs may produce rolls which may increase waste in the cutting process. On the other hand, the best number of rolls in the point of view of minimizing waste may lead to high setup costs. In this paper, coupled modeling and heuristic methods are proposed. Computational experiments are presented.     

On-chip photoactivation of heterologously expressed rhodopsin allows kinetic analysis of G-protein signaling by surface plasmon resonance spectroscopy

Surface plasmon resonance spectroscopy allows the study of protein interaction dynamics in real-time. Application of this technique to G-protein coupled receptors, the largest family of receptors involved in signal transduction, has been complicated by their low level of expression and the critical dependence of their native conformation on the hydrophobic transmembrane lipid environment. Here, we investigate and compare three different strategies to immobilize rhodopsin, a prototypical G-protein coupled receptor on a sensor chip surface using antibodies and a lectin for receptor capturing. By further probing of different experimental conditions (pH, detergent type) we identified the optimal factors to maintain rhodopsin in a functional conformation and extended this approach to recombinant rhodopsin that was heterologously expressed in COS cells. Functional operation of rhodopsin on the sensor chip surface was proven by its activation and subsequent light-stimulated G-protein coupling. The influence of these experimental parameters on the association and dissociation kinetics of G-protein receptor coupling was determined. Thereby, we found that the kinetics of G_t interaction were not changed by the strategy of immobilization or the type of detergent. Regeneration of opsin directly on a chip allowed recycling of the immobilized native and recombinant receptor. Thus, the approach provides an experimental framework for choosing the most suitable conditions for the solubilization, immobilization, and for functional tests of rhodopsin on a biosensor surface.     

Mass transport problems for the Euclidean distance obtained as limits of p-Laplacian type problems with obstacles

In this paper we analyze a mass transportation problem that consists in moving optimally (paying a transport cost given by the Euclidean distance) an amount of a commodity larger than or equal to a fixed one to fulfil a demand also larger than or equal to a fixed one, with the obligation of paying an extra cost of −_g1(x)$-g_1(x)$ for extra production of one unit at location x   and an extra cost of _g2(y)$g_2(y)$ for creating one unit of demand at y  . The extra amounts of mass (commodity/demand) are unknowns of the problem. Our approach to this problem is by taking the limit as p→∞$p\to \infty$ to a double obstacle problem (with obstacles _g1$g_1$, _g2$g_2$) for the p  -Laplacian. In fact, under a certain natural constraint on the extra costs (that is equivalent to impose that the total optimal cost is bounded) we prove that this limit gives the extra material and extra demand needed for optimality and a Kantorovich potential for the mass transport problem involved. We also show that this problem can be interpreted as an optimal mass transport problem in which one can make the transport directly (paying a cost given by the Euclidean distance) or may hire a courier that cost _g2(y)−_g1(x)$g_2(y)-g_1(x)$ to pick up a unit of mass at y and deliver it to x. For this different interpretation we provide examples and a decomposition of the optimal transport plan that shows when we have to use the courier.