Physics of Solar Prominences: I - Spectral Diagnostics and Non-LTE Modelling

This review paper outlines background information and covers recent advances made via the analysis of spectra and images of prominence plasma and the increased sophistication of non-LTE (ie when there is a departure from Local Thermodynamic Equilibrium) radiative transfer models. We first describe the spectral inversion techniques that have been used to infer the plasma parameters important for the general properties of the prominence plasma in both its cool core and the hotter prominence-corona transition region. We also review studies devoted to the observation of bulk motions of the prominence plasma and to the determination of prominence mass. However, a simple inversion of spectroscopic data usually fails when the lines become optically thick at certain wavelengths. Therefore, complex non-LTE models become necessary. We thus present the basics of non-LTE radiative transfer theory and the associated multi-level radiative transfer problems. The main results of one- and two-dimensional models of the prominences and their fine-structures are presented. We then discuss the energy balance in various prominence models. Finally, we outline the outstanding observational and theoretical questions, and the directions for future progress in our understanding of solar prominences.Comment: 96 pages, 37 figures, Space Science Reviews. Some figures may have a better resolution in the published version. New version reflects minor changes brought after proof editin

Survivability In Telecommunication Networks

It is proposed that traffic in a telecommunications network be secured in the event of a node or link failure by the rerouting of traffic over a reserve network. The problem consists of two related parts: the dimensioning of a reserve network, and the re-allocation, or rerouting of traffic. We formulate the problem as a linear programming problem of huge size which we solve using a cutting plane algorithm based on the concept of an analytic center. The method enables the solution of the survivability problem for networks with up to 60 nodes and 120 links, which allows a realistic modelling of France Telecom's Main Interconnection Network. Key words: Survivability in telecommunication networks, cutting plane methods, interior point methods, decomposition. FRANCE TELECOM, CNET, 38-40, Rue du General Leclerc, 92131, Issy les Moulineaux Cedex, France. y LOGILAB, HEC-Gen`eve, Universit'e de Gen`eve, 102 Bd Carl Vogt, CH-1211 Gen`eve 4, Suisse. z This work was financed by contract No 9..

Optimal Joint Synthesis of Base and Reserve Telecommunication Networks

A telecommunication network is survivable if, following an arc failure, the interrupted traffic can be redirected through the network via existing excess capacity. The standard survivability problem consists in finding the least cost investment in spare capacity to allow rerouting of a given base traffic. In this paper we consider the more involved problem of simultaneously designing the base traffic and the spare capacity investment. If the investment costs are linear, the problem can be formulated as a large scale structured linear program that we solve using different decomposition techniques, including the analytic center cutting plane method. The global analysis is performed under the assumption of local rerouting of the traffic, i.e., the interrupted traffic creates a local demand between the end points of the broken edge. More sophisticated telecommunication network management allows to break down the interrupted traffic into its individual demand components. We do not treat the..

Deriving robust counterparts of nonlinear uncertain inequalities

In this paper we provide a systematic way to construct the robust counterpart of a nonlinear uncertain inequality that is concave in the uncertain parameters. We use convex analysis (support functions, conjugate functions, Fenchel duality) and conic duality in order to convert the robust counterpart into an explicit and computationally tractable set of constraints. It turns out that to do so one has to calculate the support function of the uncertainty set and the concave conjugate of the nonlinear constraint function. Conveniently, these two computations are completely independent. This approach has several advantages. First, it provides an easy structured way to construct the robust counterpart both for linear and nonlinear inequalities. Second, it shows that for new classes of uncertainty regions and for new classes of nonlinear optimization problems tractable counterparts can be derived. We also study some cases where the inequality is nonconcave in the uncertain parameters

Deriving Robust Counterparts of Nonlinear Uncertain Inequalities

Abstract: In this paper we provide a systematic way to construct the robust counterpart of a nonlinear uncertain inequality that is concave in the uncertain parameters. We use convex analysis (support functions, conjugate functions, Fenchel duality) and conic duality in order to convert the robust counterpart into an explicit and computationally tractable set of constraints. It turns out that to do so one has to calculate the support function of the uncertainty set and the concave conjugate of the nonlinear constraint function. Conveniently, these two computations are completely independent. This approach has several advantages. First, it provides an easy structured way to construct the robust counterpart both for linear and nonlinear inequalities. Second, it shows that for new classes of uncertainty regions and for new classes of nonlinear optimization problems tractable counterparts can be derived. We also study some cases where the inequality is nonconcave in the uncertain parameters

Partner support during the prenatal testing period after assisted conception.

Pregnancy after infertility is a challenging experience. The first-trimester screening test may add stress. Partner support reduces psychological distress in pregnant women after spontaneous conception. No data are available for women who conceive via assisted reproductive technology. To assess whether there was a difference between couples who underwent assisted reproductive technology and couples who conceived spontaneously in the support they felt they provided to their partner and whether their perception of support received from their partner reduced their distress. This longitudinal prospective study included 52 women (spontaneous conception) and 53 women (assisted reproductive technology), as well as their partners. Participants completed the state scale of the State-Trait Anxiety Inventory, the Edinburgh Depression Scale, and two partner-support subscales of the Dyadic Coping Inventory: before prenatal testing (gestational age 12 weeks), immediately after receiving the results (gestational age of approximately 14 weeks), and once all the prenatal screenings had been completed (gestational age 22 weeks). Women who underwent assisted reproductive technology felt less able to help their partner cope with stress and felt their partner was less able to help them cope with stress than women with spontaneous pregnancy. This difference was not observed in men. Higher perceived partner support lowered the anxiety and depression of couples who conceived spontaneously, but did not benefit couples who followed fertility treatment. These results add to our knowledge of the emotional state of women and their partners during pregnancy after infertility. This knowledge may allow prenatal care providers to offer specialized counselling to women and their partners in the transition from infertility to parenthood

Characterization of the local hydromechanical stress through experimental and numerical analysis of hydrodynamics under dark fermentation operating conditions

International audienc

Globalized Robust Optimization for Nonlinear Uncertain Inequalities

Robust optimization is a methodology that can be applied to problems that are affected by uncertainty in the problem’s parameters. The classical robust counterpart (RC) of the problem requires the solution to be feasible for all uncertain parameter values in a so-called uncertainty set, and offers no guarantees for parameter values outside this uncertainty set. The globalized robust counterpart (GRC) extends this idea by allowing controlled constraint violations in a larger uncertainty set. The constraint violations are controlled by the distance of the parameter to the original uncertainty set. We derive tractable GRCs that extend the initial GRCs in the literature: our GRC is applicable to nonlinear constraints instead of only linear or conic constraints, and the GRC is more flexible with respect to both the uncertainty set and distance measure function, which are used to control the constraint violations. In addition, we present a GRC approach that can be used to provide an extended trade-off overview between the objective value and several robustness measures