Benoit Morel

Statistical distributions for air pollution applied to the study of the particulate problem in Santiago

Abstract An expression relating the distribution of concentrations of air pollutants to the emission levels is derived and applied to the study of the air pollution problem of Santiago de Chile. Features specific to the area, like the geography and meteorology are included in a stochastic framework. The resulting distribution is simple. It has two parameters which can be easily estimated from the data. It fits well the data from Santiago and is a powerful tool to analyze pollution data and design a mitigation strategy. The methodology developed here can be applied to any city.

Lagrangian chaos, Eulerian chaos, and mixing enhancement in converging–diverging channel flows

A study of Lagrangian chaos, Eulerian chaos, and mixing enhancement in converging–diverging channel flows, using spectral element direct numerical simulations, is presented. The time‐dependent, incompressible Navier–Stokes and continuity equations are solved for laminar, transitional, and chaotic flow regimes for 100≤Re≤850. Classical fluid dynamics representations and dynamical system techniques characterize Eulerian flows, whereas Lagrangian trajectories and finite‐time Lagrangian Lyapunov exponents identify Lagrangian chaotic flow regimes and quantify mixing enhancement. Classical representations demonstrate that the flow evolution to an aperiodic chaotic regime occurs through a sequence of instabilities, leading to three successive supercritical Hopf bifurcations. Poincare sections and Eulerian Lyapunov exponent evaluations verify the first Hopf bifurcation at 125<Re<150 and the onset of Eulerian chaos at Re≊550. Lagrangian trajectories and finite‐time Lagrangian Lyapunov exponents reveal the onset of...

Real option theory from finance to batch distillation

Batch distillation processes have gained renewed interest because of the recent development in small-scale industries producing high-value-added, low-volume specialty chemicals. The flexibility and unsteady state nature of batch distillation constitute a challenge for the designer. A particularly difficult problem is the optimal control problem involving open loop solution for the reflux ratio profile. This is because of the complexity of the formulation and the large computational effort associated to its solution. The mathematical and numerical complexities of the optimal control problem get worse when uncertainty is present in the formulation. In this work, by applying the optimality conditions from the real option theory based on the Ito’s Lemma [Investment under uncertainity (1994); Memoirs Am. Math. Soc. 4 (1951) 1; Appl. Math. Opt. 4 (1974) 374], the mathematical tools needed to solve optimal control problems in batch distillation columns when uncertainties in the state variables are present have been developed. Furthermore, the coupled maximum principle and NLP approach developed by Diwekar [Am. Inst. Chem. Eng. J. 38 (1992) 1551] has been extended for solving the optimal control problem in the uncertain case. This new algorithm has been implemented in the MultiBatchDS batch distillation process simulator. Finally, a numerical case-study is presented to show the scope and application of the proposed approach. # 2003 Elsevier Ltd. All rights reserved.

New insights into mathematical modeling of the immune system

In order to understand the integrated behavior of the immune system, there is no alternative to mathematical modeling. In addition, the advent of experimental tools such as gene arrays and proteomics poses new challenges to immunologists who are now faced with more information than can be readily incorporated into existing paradigms of immunity. We review here our ongoing efforts to develop mathematical models of immune responses to infectious disease, highlight a new modeling approach that is more accessible to immunologists, and describe new ways to analyze microarray data. These are collaborative studies between experimental immunologists, mathematicians, and computer scientists.

Artificial intelligence and the future of cybersecurity

A position paper toward an important and urgent discussion on how best use the potential of Artificial Intelligence in the context of cybersecurity. AI is often mentioned in papers on cybersecurity. But what is meant is using pre-existing AI techniques in cybersecurity. AI techniques are developed around applications. Cybersecurity has never been an area of concentration in AI. In this paper we argue that cybersecurity calls for new and specific AI techniques developed with that kind of application in mind. In practice, this paper is based on a broad overview of different approaches, which have the potential to be game changers in cybersecurity. This paper focuses on web application security and advocates the use of Knowledge Based Systems, probabilistic reasoning and Bayesian updating to control the probability of false positives and false negatives.

A feasibility study of the destruction of chemical weapons by photocatalytic oxidation

The destruction of existing arsenals or deposits of chemical weapons is an important obstacle on the way to the successful implementation of the Chemical Weapons Convention which was opened for signature in 1993. Many approaches have been proposed and none can be seen as a panacea. Each has its merits and shortcomings. In this paper we review the different technologies and propose a new one, photocatalytic oxidation, which has the potential to fill an important gap: a cheap, small, mobile facility for chemical warfare agents which are difficult to transport or are deposited in a remote area. We report some relevant experimental results with this technology for the destruction of chemical weapons.

Limits of space-based remote sensing for methane source characterization

This analysis examines the ability of a space-based instrument to identify and quantify methane sources in the presence of temperature, humidity, and albedo uncertainty. Thus, the objective is to quantify in the context of the NASA Earth Observing System (EOS) the synergistic benefit of simultaneous observation of the Earths surface with atmospheric attributes. The analysis is illustrative of the type of examination that should inform remote sensing policy and system configuration decisions. The retrieval technique considered is linear inversion of near-IR spectral signals. The anticipated range of methane mixing ratio enhancement due to sources at the Earths surface is compared to the detection limit of the space-based instrument. >

Space nuclear power plants—I

Abstract Space nuclear power plants can be configured in a number of different ways depending on the choice of primary loop transport, conversion techniques and heat addition and rejection systems. The large number of the possible configurations mandates a modular approach. A global approach to analyzing the various configurations has been developed. A generalized software, SNAPS (Space Nuclear Auxiliary Power analysis System), has emerged from the studies thus far. The first part of this project which we are presenting in this paper is this computer program SNAPS designed to simulate space nuclear power plants with different energy conversion techniques, to find optimal characteristics constrained in feasibility limitations, and to design the plant for maximum reliability and flexibility. This program is based on the flowsheeting approach in chemical engineering.

Mathematical Modeling of Th1-Th2 Dynamics

One of the main functions of the immune system is the recognition and removal of foreign antigens. The first specific recognition of invading antigens is carried out by antigen-specific T lymphocytes. T cells are activated following the recognition of antigenic peptides that are bound in a cleft on molecules of the major histocompatibility complex (MHC) (Zinkernagel and Doherty, 1974; Fathman and Frelinger, 1983; Davis and Bjorkman,1988). MHC molecules are highly polymorphic cell surface glycoproteins that occur in two distinct forms: class I MHC molecules (H-2K,D,L in mice and HLA-A,B,C in humans) and class II MHC molecules (H2-I in mice and HLA-D in humans) (Hood et al,1983). Class I MHC molecules are expressed on almost all cells of the body, bind peptides derived from endogenous proteins and are recognized by T cells bearing the CD8 marker; these T cells are in general cytotoxic T cells (CTLs). Class II MHC molecules are primarily expressed on macrophages, dendritic cells, B cells and thymic epithelium, bind peptides derived from exogenous antigens and are recognized by T cells bearing the CD4 marker; these T cells are in general helper T cells (Th) (Swain, 1983). Activation of Th cells results in morphologic changes (blastogenesis) at about 12 hours, cell division by 24–48 hours and differentiation as up to 70 genes are sequentially activated for several days (Crabtree,1989). During this process a wide variety of lymphokines are secreted. These include the T cell growth factors IL-2, IL-4 and IL-7, the macrophage activator IFN-γ, and the B cell activators IL-4, IL-5 and IL-6 (Kurt- Jones et al, 1987; Mosmann et al, 1987). These lymphokines, and many others are responsible for the activation and differentiation of cells important in the immune response.

How Could Carbon Credits for Reducing Deforestation Compete with Returns from Palm Oil: A Proposal for a More Flexible REDD Valuation Tool

In order for carbon credits awarded for reducing emissions from deforestation and degradation of forests (REDD) to be effective, they need to be competitive with alternative land uses. In the case of Southeast Asia, oil palm cultivation is one of the most lucrative possible land uses. Existing mechanisms for awarding certified emission reductions (CERs) might not be adequately flexible to changing commodity prices or to meet the needs of landowners who heavily discount future returns from their land. Real options could be a useful valuation tool for negotiating an annual contract that guarantees a minimum payment or “strike price” to the landowner depending on the potential returns from cultivation of their land. The real option based algorithm computes a competitive payment dependent on the relevant commodity prices contributing to land cover change. This article proposes a method whereby the risk is shared between the seller and buyer, providing a per hectare payment that favors the conservation of forests containing higher biomass per hectare.