Toxicokinetics of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA) in the European corn borer,Ostrinia nubilalis (Hübner)

2,4-Dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), the major hydroxamic acid present in corn, and its tritiated derivative, were prepared synthetically for use in the determination of the toxicokinetics of this insect deterrent in the European corn borer (ECB),Ostrinia nubilalis. In growth studies with DIMBOA (0, 0.05, 0.2, and 0.5 mg/g diet), the mean time to pupation and adult emergence were significantly lengthened by an increase in concentration. Pupal and adult weights, for both female and male, decreased with an increase in concentration. Increased larval and pupal mortality occurred at the highest concentration of DIMBOA. DIMBOA, at concentrations of 0.2 and 0.5 mg/g diet, resulted in a decrease in the number of egg masses produced per female, and at 0.5 mg/g diet, in a decrease in the number of eggs per egg mass. Larvae fed from the neonate stage on a diet containing 0.2 mg [³H]- + [¹H]DIMBOA/g diet showed an increase in the content of label from fourth to fifth instar, but levels declined at pupation and emergence. A large amount of the labeled compounds was excreted by the insect in the pupal case. In dose-related studies, both uptake and excretion increased with an increase in concentration of DIMBOA (0.05, 0.2, 0.4 mg/g diet), while a body burden (concentration in the tissues/concentration in the frass) of approximately 0.25 was maintained for all concentrations. At the highest dose of DIMBOA (0.4 mg/g), the ECB increased consumption, possibly to compensate for the toxic effects of the compound. In topical application studies, elimination of the labeled compound in the frass was rapid, reaching 65% by 4 hr and 88% by 48 hr. Accumulation of label in tissues other than hemolymph was low. The results show that the ECB does possess adaptive mechanisms to deal with the effects of this host-derived compound.     

Relationship between microstructure and mechanical properties of polyether block amide foams

The mechanical behaviors of five polyether block amide foams, obtained by mold-opening foam injection process, were investigated with regard to their microstructures. The materials vary in mass ratios of hard versus soft segments, and/or in process packing time. The resulting microstructures have been characterized in terms of cavity size and shape ratios, by analyzing scanning electron microscope images after careful sample preparation. The foam mechanical responses have been characterized in compression at small and large strain. At small strain, the initial linear part of the stress–strain curve is enhanced firstly by the hard segment mass ratio and secondly by the fineness of the microstructure. Similar results have been obtained at large strain. The foam viscoelasticity at large strain has been characterized by stress relaxation and strain recovery tests, relevant for foam applications. Reduced packing time and pressure have been shown to lead to the presence of undesired large cavities. The morphological defects appear to have a negligible impact on the macroscopic mechanical behavior of the foams at infinitesimal strain, but lead to critical inconsistency at large strain. Furthermore, the mechanical behavior of the tested polyether block amide foams is controlled first by hard versus soft segments ratio, and second by the microstructure fineness.     

NH_3 Plasma Surface Treatments of Engineering Fluoropolymers: A Way to Enhance Adhesion of Ni or Cu Thin Films Deposited by Electroless Plating

FLUOROPOLYMERS(FPs)are thermoplasticmaterials which exhibit a number of unique chemicaland physical characteristics that no other man-madeplastic product gets together.For example,FPs showvery good resistance to almost all chemicals,excellentwater vapor barrier properties,high thermal stability,outstanding electrical insulation properties(lowdielectric constant and dissipation factors),extremelylow frictional coefficient giving them high auto-lubrication properties,high resistance to rad…     

Dynamic Model Adaptation for Multiscale Simulation of Hyperbolic Systems with Relaxation

In numerous industrial CFD applications, it is usual to use two (or more) different codes to solve a physical phenomenon: where the flow is a priori assumed to have a simple behavior, a code based on a coarse model is applied, while a code based on a fine model is used elsewhere. This leads to a complex coupling problem with fixed interfaces. The aim of the present work is to provide a numerical indicator to optimize to position of these coupling interfaces. In other words, thanks to this numerical indicator, one could verify if the use of the coarser model and of the resulting coupling does not introduce spurious effects. In order to validate this indicator, we use it in a dynamical multiscale method with moving coupling interfaces. The principle of this method is to use as much as possible a coarse model instead of the fine model in the computational domain, in order to obtain an accuracy which is comparable with the one provided by the fine model. We focus here on general hyperbolic systems with stiff relaxation source terms together with the corresponding hyperbolic equilibrium systems. Using a numerical Chapman–Enskog expansion and the distance to the equilibrium manifold, we construct the numerical indicator. Based on several works on the coupling of different hyperbolic models, an original numerical method of dynamic model adaptation is proposed. We prove that this multiscale method preserves invariant domains and that the entropy of the numerical solution decreases with respect to time. The reliability of the adaptation procedure is assessed on various 1D and 2D test cases coming from two-phase flow modeling.     

A memetic algorithm to solve an unrelated parallel machine scheduling problem with auxiliary resources in semiconductor manufacturing

In this paper, we propose a metaheuristic for solving an original scheduling problem with auxiliary resources in a photolithography workshop of a semiconductor plant. The photolithography workshop is often a bottleneck, and improving scheduling decisions in this workshop can help to improve indicators of the whole plant. Two optimization criteria are separately considered: the weighted flow time (to minimize) and the number of products that are processed (to maximize). After stating the problem and giving some properties on the solution space, we show how these properties help us to efficiently solve the problem with the proposed memetic algorithm, which has been implemented and tested on large generated instances. Numerical experiments show that good solutions are obtained within a reasonable computational time.     

Binarised regression tasks: methods and evaluation metrics

Some supervised tasks are presented with a numerical output but decisions have to be made in a discrete, binarised, way, according to a particular cutoff. This binarised regression task is a very common situation that requires its own analysis, different from regression and classification—and ordinal regression. We first investigate the application cases in terms of the information about the distribution and range of the cutoffs and distinguish six possible scenarios, some of which are more common than others. Next, we study two basic approaches: the retraining approach, which discretises the training set whenever the cutoff is available and learns a new classifier from it, and the reframing approach, which learns a regression model and sets the cutoff when this is available during deployment. In order to assess the binarised regression task, we introduce context plots featuring error against cutoff. Two special cases are of interest, the \( UCE \) and \( OCE \) curves, showing that the area under the former is the mean absolute error and the latter is a new metric that is in between a ranking measure and a residual-based measure. A comprehensive evaluation of the retraining and reframing approaches is performed using a repository of binarised regression problems created on purpose, concluding that no method is clearly better than the other, except when the size of the training data is small.     

The Cost of Environmental Constraints in Traffic Networks: Assessing the Loss of Optimality

Increasing numbers of hard environmental constraints are being imposed in urban traffic networks by authorities in an attempt to mitigate pollution caused by traffic. However, it is not trivial for authorities to assess the cost of imposing such hard environmental constraints. This leads to difficulties when setting the constraining values as well as implementing effective control measures. For that reason, quantifying the cost of imposing hard environmental constraints for a certain network becomes crucial. This paper first indicates that for a given network, such cost is not only related to the attribution of environmental constraints but also related to the considered control measures. Next, we present an assessment criterion that quantifies the loss of optimality under the control measures considered by introducing the environmental constraints. The criterion can be acquired by solving a bi-level programming problem with/without environmental constraints. A simple case study shows its practicability as well as the differences between this framework and other frameworks integrating the environmental aspects. This proposed framework is widely applicable when assessing the interaction of traffic and its environmental aspects.     

Second-order shape derivatives along normal trajectories,governed by Hamilton-Jacobi equations

In this paper we introduce a new variant of shape differentiation which is adapted to the deformation of shapes along their normal direction. This is typically the case in the level-set method for shape optimization where the shape evolves with a normal velocity. As all other variants of the original Hadamard method of shape differentiation, our approach yields the same first order derivative. However, the Hessian or second-order derivative is different and somehow simpler since only normal movements are allowed. The applications of this new Hessian formula are twofold. First, it leads to a novel extension method for the normal velocity, used in the Hamilton-Jacobi equation of front propagation. Second, as could be expected, it is at the basis of a Newton optimization algorithm which is conceptually simpler since no tangential displacements have to be considered. Numerical examples are given to illustrate the potentiality of these two applications. The key technical tool for our approach is the method of bicharacteristics for solving Hamilton-Jacobi equations. Our new idea is to differentiate the shape along these bicharacteristics (a system of two ordinary differential equations).     

Viscosity measurements of liquids under pressure by using the quartz crystal resonators

A quartz crystal viscometer has been developed for measuring viscosity in liquids under pressure. It employs an AT-cut quartz crystal resonator of fundamental frequency 3 MHz inserted in a variable-volume vessel designed for working up to 80 MPa. Viscosity is determined by two methods from resonance frequency and bandwidth measurements along up to eight different overtones. The resonance frequency allows an absolute measurement of the viscosity but leads to an accuracy limited to 5% whereas the bandwidth technique which works in a relative way provides an accuracy of 2%. The techniques were tested by carrying out measurements in two pure compounds: heptane and toluene. Measurement results demonstrate the feasibility of the technique in this viscosity range. The apparatus was also used to determine the viscosity of n-decane with dissolved methane. The results obtained with these mixtures reveal the applicability of the apparatus for reservoir fluids study.