Scenario reduction for stochastic programs with Conditional Value-at-Risk

In this paper we discuss scenario reduction methods for risk-averse stochastic optimization problems. Scenario reduction techniques have received some attention in the literature and are used by practitioners, as such methods allow for an approximation of the random variables in the problem with a moderate number of scenarios, which in turn make the optimization problem easier to solve. The majority of works for scenario reduction are designed for classical risk-neutral stochastic optimization problems; however, it is intuitive that in the risk-averse case one is more concerned with scenarios that correspond to high cost. By building upon the notion of effective scenarios recently introduced in the literature, we formalize that intuitive idea and propose a scenario reduction technique for stochastic optimization problems where the objective function is a Conditional Value-at-Risk. Numerical results presented with problems from the literature illustrate the performance of the method and indicate the cases where we expect it to perform well.     

A constructive approach to cubic Hermite Fractal Interpolation Function and its constrained aspects

The theory of splines is a well studied topic, but the kinship of splines with fractals is novel. We introduce a simple explicit construction for a -cubic Hermite Fractal Interpolation Function (FIF). Under some suitable hypotheses on the original function, we establish a priori estimates (with respect to the L _p -norm, 1≤p≤∞) for the interpolation error of the -cubic Hermite FIF and its first derivative. Treating the first derivatives at the knots as free parameters, we derive suitable values for these parameters so that the resulting cubic FIF enjoys global smoothness. Consequently, our method offers an alternative to the standard moment construction of -cubic spline FIFs. Furthermore, we identify appropriate values for the scaling factors in each subinterval and the derivatives at the knots so that the graph of the resulting -cubic FIF lies within a prescribed rectangle. These parameters include, in particular, conditions for the positivity of the cubic FIF. Thus, in the current article, we initiate the study of the shape preserving aspects of fractal interpolation polynomials. We also provide numerical examples to corroborate our results.     

Impact of demand uncertainty on coordinating supply chain inventories through common replenishment epochs

Prior studies have shown that inventories in a one vendor, multi-buyer supply chain with deterministic demands can be coordinated effectively through the use of common replenishment epochs (CRE). In this paper, we study the impact of demand uncertainty on the effectiveness of coordinating such a supply chain. We develop a model to analyse the coordination mechanism using CRE in a one-vendor, multi-buyer supply chain, when the demand faced by the buyers is stochastic. Our numerical study based on the model found that coordination through CRE may not always be beneficial when the demand variance is high. We also investigate a strategy of advance order processing by the vendor to improve the effectiveness of coordination through CRE.     

2 Higgs or not 2 Higgs

Motivated by recent results from the LHC experiments, we analyze Higgs couplings in two Higgs doublet models with an approximate PQ   symmetry. Models of this kind can naturally accommodate sizable modifications to Higgs decay patterns while leaving production at hadron colliders untouched. Near the decoupling limit, we integrate out the heavy doublet to obtain the effective couplings of the SM-like Higgs and express these couplings in a physically transparent way, keeping all orders in (_mh/_mH)$(m_h/m_H)$ for small PQ breaking. Considering supersymmetric models, we show that the effects on the Higgs couplings are considerably constrained.     

Quantitative comparison between crowd models for evacuation planning and evaluation

Crowd simulation is rapidly becoming a standard tool for evacuation planning and evaluation. However, the many crowd models in the literature are structurally different, and few have been rigorously calibrated against real-world egress data, especially in emergency situations. In this paper we describe a procedure to quantitatively compare different crowd models or between models and real-world data. We simulated three models: (1) the lattice gas model, (2) the social force model, and (3) the RVO2 model, and obtained the distributions of six observables: (1) evacuation time, (2) zoned evacuation time, (3) passage density, (4) total distance traveled, (5) inconvenience, and (6) flow rate. We then used the DISTATIS procedure to compute the compromise matrix of statistical distances between the three models. Projecting the three models onto the first two principal components of the compromise matrix, we find the lattice gas and RVO2 models are similar in terms of the evacuation time, passage density, and flow rates, whereas the social force and RVO2 models are similar in terms of the total distance traveled. Most importantly, we find that the zoned evacuation times of the three models to be very different from each other. Thus we propose to use this variable, if it can be measured, as the key test between different models, and also between models and the real world. Finally, we compared the model flow rates against the flow rate of an emergency evacuation during the May 2008 Sichuan earthquake, and found the social force model agrees best with this real data.     

Reduction of CO2 by nickel (II) macrocycle catalyst at HMDE

With the aim of finding a suitable electrocatalyst for the efficient reduction of carbon dioxide, the electrochemistry of nickel (II) complex of 1,3,6,9,11,14-hexaazatricyclo [12·2·1·1] octadecane was studied using cyclic voltammetry (CV) and controlled-potential electrolysis (CPE) techniques in the presence and absence of CO₂ in 100% H₂O, CH₃CN-H₂O mixtures (20–100%) and DMF-H₂O (70–100%) mixtures. The efficiency of this process is determined using the coulometry technique. CO is the major product in the gaseous phase and HCOOH the sole product formed in the solution phase.     

The structure of strong shock waves using the Fokker-Planck model

The structure of strong shock waves in monatomic gases is studied using the Fokker-Planck model to represent the particle collisions and the Mott-Smith distribution to describe the distribution function within the shock front. The differential equation governing the variation of the density within the shock is derived by using the variational principle. The thickness of the shock front is evaluated numerically for various monatomic gases for Mach numbers varying from 2 to 20, and besides, the variation of the shock thickness with viscosity is also studied for different gases. Several parameters of physical interest within the shock, such as density, temperature and mean velocity of flow are evaluated numerically and detailed curves showing their variation within the shock are presented for different Mach numbers. It is found that the temperature rises very steeply, reaches a maximum within a distance less than half the thickness of the shock and then diminishes slowly to attain its asymptotic downstream values. The variation of the mean velocity is slow for weak shocks, but for higher Mach numbers, the mean velocity diminishes steeply and reaches the downstream values within half the thickness of the shock.     

Superconductivity and phase stability of selenium at high pressures

Hexagonal Se shows no indication of a transformation to a metallic, superconducting phase up to 160 kbar. Amorphous Se transforms at about 130 kbar to an unstable metallic, superconducting state which anneals slowly at room temperature toward a non-metallic, non-superconducting phase. Monoclinic Se behaves much like amorphous Se. X-ray diffraction indicates that all samples are in the hexagonal phase after release of pressure.