Accuracy in the experimental calorimetric study of the crystallization kinetics and predicitve transformation diagrams: Application to a Ga-Te amorphous alloy

The uncertainties inherent to experimental differential scanning calorimetric data are evaluated. A new procedure is developed to perform the kinetic analysis of continuous heating calorimetric data when the heat capacity of the sample changes during the crystallization. The accuracy of isothermal calorimetric data is analyzed in terms of the peak-to-peak noise of the calorimetric signal and base line drift typical of differential scanning calorimetry equipment. Their influence in the evaluation of the kinetic parameters is discussed. An empirical construction of the time-temperature and temperature heating rate transformation diagrams, grounded on the kinetic parameters, is presented. The method is applied to the kinetic study of the primary crystallization of Te in an amorphous alloy of nominal composition Ga20Te80, obtained by rapid solidification.

Modeling a processive molecular motor: the conventional kinesin

We present a model that allows for the derivation of the experimentally accesible observables: spatial steps, mean velocity, stall force, useful power, efficiency and randomness, etc. as a function of the [adenosine triphosphate] concentration and an external load F. The model presents a minimum of adjustable parameters and the theoretical predictions compare well with the available experimental results.

Preisach modeling of hysteresis for a pseudoelastic Cu-Zn-Al single crystal

Stress-strain trajectories associated with pseudoelastic behavior of a Cu¿19.4 Zn¿13.1 Al (at.%) single crystal at room temperature have been determined experimentally. For a constant cross-head speed the trajectories and the associated hysteresis behavior are perfectly reproducible; the trajectories exhibit memory properties, dependent only on the values of return points, where transformation direction is reverted. An adapted version of the Preisach model for hysteresis has been implemented to predict the observed trajectories, using a set of experimental first¿order reversal curves as input data. Explicit formulas have been derived giving all trajectories in terms of this data set, with no adjustable parameters. Comparison between experimental and calculated trajectories shows a much better agreement for descending than for ascending paths, an indication of a dissymmetry between the dissipation mechanisms operative in forward and reverse directions of martensitic transformation.

Cost-effective experimental design to support modeling of concentration-response functions

Modeling concentration-response function became extremely popular in ecotoxicology during the last decade. Indeed, modeling allows determining the total response pattern of a given substance. However, reliable modeling is consuming in term of data, which is in contradiction with the current trend in ecotoxicology, which aims to reduce, for cost and ethical reasons, the number of data produced during an experiment. It is therefore crucial to determine experimental design in a cost-effective manner. In this paper, we propose to use the theory of locally D-optimal designs to determine the set of concentrations to be tested so that the parameters of the concentration-response function can be estimated with high precision. We illustrated this approach by determining the locally D-optimal designs to estimate the toxicity of the herbicide dinoseb on daphnids and algae. The results show that the number of concentrations to be tested is often equal to the number of parameters and often related to the their meaning, i.e. they are located close to the parameters. Furthermore, the results show that the locally D-optimal design often has the minimal number of support points and is not much sensitive to small changes in nominal values of the parameters. In order to reduce the experimental cost and the use of test organisms, especially in case of long-term studies, reliable nominal values may therefore be fixed based on prior knowledge and literature research instead of on preliminary experiments

Prediction of Infant Drug Exposure Through Breastfeeding: Population PK Modeling and Simulation of Fluoxetine Exposure.

The likelihood of significant exposure to drugs in infants through breast milk is poorly defined, given the difficulties of conducting pharmacokinetics (PK) studies. Using fluoxetine (FX) as an example, we conducted a proof-of-principle study applying population PK (popPK) modeling and simulation to estimate drug exposure in infants through breast milk. We simulated data for 1,000 mother-infant pairs, assuming conservatively that the FX clearance in an infant is 20% of the allometrically adjusted value in adults. The model-generated estimate of the milk-to-plasma ratio for FX (mean: 0.59) was consistent with those reported in other studies. The median infant-to-mother ratio of FX steady-state plasma concentrations predicted by the simulation was 8.5%. Although the disposition of the active metabolite, norfluoxetine, could not be modeled, popPK-informed simulation may be valid for other drugs, particularly those without active metabolites, thereby providing a practical alternative to conventional PK studies for exposure risk assessment in this population.

Modeling Forest Growth with Management Data: A Matrix Approach for the Italian Alps

Summary

Fat oxidation kinetics during exercise in obese individuals.

Introduction An impaired ability to oxidize fat may be a factor in the obesity's aetiology (3). Moreover, the exercise intensity (Fatmax) eliciting the maximal fat oxidation rate (MFO) was lower in obese (O) compared with lean (L) individuals (4). However, difference in fat oxidation rate (FOR) during exercise between O and L remains equivocal and little is known about FORs during high intensities (>60% ) in O compared with L. This study aimed to characterize fat oxidation kinetics over a large range of intensities in L and O. Methods 12 healthy L [body mass index (BMI): 22.8±0.4] and 16 healthy O men (BMI: 38.9±1.4) performed submaximal incremental test (Incr) to determine whole-body fat oxidation kinetics using indirect calorimetry. After a 15-min resting period (Rest) and 10-min warm-up at 20% of maximal power output (MPO, determined by a maximal incremental test), the power output was increased by 7.5% MPO every 6-min until respiratory exchange ratio reached 1.0. Venous lactate and glucose and plasma concentration of epinephrine (E), norepinephrine (NE), insulin and non-esterified fatty acid (NEFA) were assessed at each step. A mathematical model (SIN) (1), including three variables (dilatation, symmetry, translation), was used to characterize fat oxidation (normalized by fat-free mass) kinetics and to determine Fatmax and MFO. Results FOR at Rest and MFO were not significantly different between groups (p≥0.1). FORs were similar from 20-60% (p≥0.1) and significantly lower from 65-85% in O than in L (p≤0.04). Fatmax was significantly lower in O than in L (46.5±2.5 vs 56.7±1.9 % respectively; p=0.005). Fat oxidation kinetics was characterized by similar translation (p=0.2), significantly lower dilatation (p=0.001) and tended to a left-shift symmetry in O compared with L (p=0.09). Plasma E, insulin and NEFA were significantly higher in L compared to O (p≤0.04). There were no significant differences in glucose, lactate and plasma NE between groups (p≥0.2). Conclusion The study showed that O presented a lower Fatmax and a lower reliance on fat oxidation at high, but not at moderate, intensities. This may be linked to a: i) higher levels of insulin and lower E concentrations in O, which may induce blunted lipolysis; ii) higher percentage of type II and a lower percentage of type I fibres (5), and iii) decreased mitochondrial content (2), which may reduce FORs at high intensities and Fatmax. These findings may have implications for an appropriate exercise intensity prescription for optimize fat oxidation in O. References 1. Cheneviere et al. Med Sci Sports Exerc. 2009 2. Holloway et al. Am J Clin Nutr. 2009 3. Kelley et al. Am J Physiol. 1999 4. Perez-Martin et al. Diabetes Metab. 2001 5. Tanner et al. Am J Physiol Endocrinol Metab. 2002

Kinetics of dexamethasone-induced alterations of glucose metabolism in healthy humans.

Six healthy human subjects were studied during three 75-g oral, [13C]glucose tolerance tests to assess the kinetics of dexamethasone-induced impairment of glucose tolerance. On one occasion, they received dexamethasone (4 x 0.5 mg/day) during the previous 2 days. On another occasion, they received a single dose (0. 5 mg) of dexamethasone 150 min before ingestion of the glucose load. On the third occasion, they received a placebo. Postload plasma glucose was significantly increased after both 2 days dexamethasone and single dose dexamethasone compared with control (P < 0.05). This corresponded to a 20-23% decrease in the metabolic clearance rate of glucose, whereas total glucose turnover ([6,6-2H]glucose), total (indirect calorimetry) and exogenous glucose oxidation (13CO2 production), and suppression of endogenous glucose production were unaffected by dexamethasone. Plasma insulin concentrations were increased after 2 days of dexamethasone but not after a single dose of dexamethasone. In a second set of experiments, the effect of a single dose of dexamethasone on insulin sensitivity was assessed in six healthy humans during a 2-h euglycemic hyperinsulinemic clamp. Dexamethasone did not significantly alter insulin sensitivity. It is concluded that acute administration of dexamethasone impairs oral glucose tolerance without significantly decreasing insulin sensitivity.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

Animal manure phosphorus characterization by sequential chemical fractionation, release kinetics and 31P-NMR analysis

Phosphate release kinetics from manures are of global interest because sustainable plant nutrition with phosphate will be a major concern in the future. Although information on the bioavailability and chemical composition of P present in manure used as fertilizer are important to understand its dynamics in the soil, such studies are still scarce. Therefore, P extraction was evaluated in this study by sequential chemical fractionation, desorption with anion-cation exchange resin and 31P nuclear magnetic resonance (31P-NMR) spectroscopy to assess the P forms in three different dry manure types (i.e. poultry, cattle and swine manure). All three methods showed that the P forms in poultry, cattle and swine dry manures are mostly inorganic and highly bioavailable. The estimated P pools showed that organic and recalcitrant P forms were negligible and highly dependent on the Ca:P ratio in manures. The results obtained here showed that the extraction of P with these three different methods allows a better understanding and complete characterization of the P pools present in the manures.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.