A percentile system optimization approach with and without path enumeration

In this paper we deal with the travel time reliability PUE (probabilistic user equilibrium) problem studied by Lo et al. (2006) [12] and Nie (2011) [15] and we propose an alternative model that assumes a location-scale family for the path travel times, whose means and variances are evaluated in terms of link travel times. This avoids the use of the central limit theorem and convolutions providing a flexible and simple alternative. Contrary to the most existing models that require path enumeration or an iterative method to add paths sequentially, we present a percentile system optimization in its two versions: with and without path enumeration. Two examples of applications, one of them real, are used to illustrate the power of the proposed method. The cpu times required to solve the problem seem reasonable. In addition, we answer an open question raised by Nie (2011) [15] about the permutability of percentiles and partial derivatives of route travel times with respect to route flows. A family of counterexamples is given to demonstrate that the two operations: (a) obtain percentiles and (b) partial derivation of route travel times do not commute. Finally, to reproduce the trial-and-error sequence followed by users when selecting paths, we also present an algorithm that simulates this iterative process and shows that the final long-term user behavior coincides with PUE (probabilistic user equilibrium) problem resulting from some existing models.     

SIMULATING STRUCTURAL CHANGE IN ADAPTIVE ORGANIZATIONS

This paper presents an agent-based model of an organization. The model is made of a social network—composed of the different organization workers—and a knowledge network. Workers are assigned tasks, for which they have to use information in the knowledge network. We have modeled the quality of the information by assigning each information item a probability of being wrong. Agents can interact with other agents, who can recommend to them new information items in the knowledge network for the task to be performed. Workers are assigned different information-seeking behavior (passive, active, and learning), governing the way in which they interact with each other. Moreover, indirect interaction is also possible, as a publicly accessible knowledge base contains each agent's preferred information items.

The model was implemented in SDML, and its simulation shows that agents quickly learn to discern the better information items for the given task. However, group formation (agents' collaborating by exchanging information) takes longer to stabilize. Additionally, when the quality of items is changed, agents can quickly select the better new knowledge items, and organization performance improves again to a maximum that is only randomly disturbed.     

First report on the presence of emerging Fusarium mycotoxins enniatins (A,A1, B,B1), beauvericin and fusaproliferin in rice on the Moroccan retail markets

Seventy samples of rice purchased from local markets in six cities from Morocco (Rabat, Casablanca, Kénitra, Mohammadia, Tanger and Errachidia) were analyzed for the presence of six emerging mycotoxins: four enniatins ENs (ENA, ENA₁, ENB and ENB₁), beauvericin (BEA) and fusaproliferin (FUS). Samples were extracted with a mixture of acetonitrile/water (85/15, v/v) by using an ultra-turrax homogenizer. Mycotoxins were then identified and quantified with liquid chromatography (LC) coupled to diode array detector (DAD). Positive samples were confirmed with an LC-MS/MS. Analytical results showed that BEA was present in 75.7% of total analyzed samples. BEA levels varied between 3.8 and 26.3 mg/kg. The frequencies of contamination of samples with total ENs and FUS were 50% and 4.3%, respectively. Among the ENs, ENB was the mycotoxin much more found (30% of total samples), while ENB₁, ENA and ENA₁ were found in 24.6%, 22.8% and 5.7% of total samples, respectively. The high ENs value was registered in a rice sample from kénitra (448.7 mg/kg of ENA₁). This is the first study that describes the presence of emerging Fusarium mycotoxins in rice available in Morocco.     

Sol-gel Preparation and Preliminary in vitro Evaluation of Fluorapatite／Hydroxyapatite Solid Solution Films

Fluorapatite/hydroxyapatite solid solution has better biological properties than other apatites, especially used as films or coatings. In this work, sol-gel preparation and in vitro behavior of fluorapatite/hydroxyapatite solid solution films on titanium alloy were investigated. Ca(NO3)2-4H20 and PO(OH)x(OEt)3-x were selected as precursors, and hexafluorophosphoric acid (HPFo) was used as a fluorine containing reagent. The Ca and P precursors were mixed with HPFo to keep the Ca/P molar ratio 1.67. The mixtures refluxed for 12 h were used as dipping sols for the preparation of the films. The phase of the films obtained at 600℃ was apatite. The F contents in the films increased with the concentrations of HPF6 in the dipping sols. The solid solution films were shown to have better stability than hydroxyapatite films, and a reasonably good bioactivity in the in vitro evaluation.     

Lack of power enhances visual perceptual discrimination.

Powerless individuals face much challenge and uncertainty. As a consequence, they are highly vigilant and closely scrutinize their social environments. The aim of the present research was to determine whether these qualities enhance performance in more basic cognitive tasks involving simple visual feature discrimination. To test this hypothesis, participants performed a series of perceptual matching and search tasks involving colour, texture, and size discrimination. As predicted, those primed with powerlessness generated shorter reaction times and made fewer eye movements than either powerful or control participants. The results indicate that the heightened vigilance shown by powerless individuals is associated with an advantage in performing simple types of psychophysical discrimination. These findings highlight, for the first time, an underlying competency in perceptual cognition that sets powerless individuals above their powerful counterparts, an advantage that may reflect functional adaptation to the environmental challenge and uncertainty that they face. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Analysis of laminated doubly-curved shells by a layerwise theory and radial basis functions collocation,accounting for through-the-thickness deformations

In this paper, the static and free vibration analysis of laminated shells is performed by radial basis functions (RBFs) collocation, according to a layerwise deformation theory (LW). The present LW theory accounts for through-the-thickness deformation, by considering an Mindlin-like evolution of all displacements in each layer. The equations of motion and the boundary conditions are obtained by Carrera’s unified formulation, and further interpolated by collocation with RBFs.     

Multi-objective design optimization of a new space radiator

In this work different multi-objective techniques are used to the conceptual design of a new kind of space radiator. Called VESPAR (Variable Emittance Space Radiator), the radiator has an effective variable emittance which makes it able to reduce or avoid the demand for heater power to warm up equipment during cold case operations in orbit. The multi-objective approach was aimed on obtaining a radiator that minimize its mass while at the same time minimize the need for heater power during cold case. Four multi-objective algorithms were used: Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II), Multi-Objective Genetic Algorithm (MOGA), Multi-Objective Simulating Annealing (MOSA) and Multi-Objective Generalized Extremal Optimization (M-GEO). The first three algorithms were used under the modeFrontier^® optimization software package, while M-GEO is a recently proposed multi-objective implementation of the Generalized Extremal Optimization (GEO) algorithm. The Pareto frontier showing the trade-off solutions between radiator mass and heater power consumption is obtained by the four algorithms and the results compared. An assessment of the performance of M-GEO on this problem, compared to the other well-known multi-objective algorithms is also made.