On coordinating warehouse sizing, leasing and inventory policy

Organizations often fulfil their storage needs by supplementing their own warehouse with leased space, a scenario modeled here under the assumption of constant product demand. Closed-form formulae are obtained for the decision variables of interest, namely, the replenishment lot size and the warehouse size, as well as the amount of space to lease. Cost savings due to leasing are shown to have an upper bound of approximately 29% when the optimal warehouse capacity can be installed without restrictions (such as a budgetary constraint). A numerical example further indicates that leasing is significantly more beneficial when the warehouse size is tightly constrained, and that total costs are robust with respect to demand fluctuations.     

Bizarre imagery, interference, and distinctiveness.

Previous studies have shown that bizarre and common images produce equivalent levels of recall in unmixed-list designs. Using unmixed lists, we tested the view that bizarre images would be less susceptible than common images to common sources of interference. In all experiments, subjects imaged a list of either bizarre or common sentences and then performed some kind of interfering task before recalling the initial list of sentences. Experiment 1 showed that bizarre images were better accessed than common images after imaging an intervening list of common sentences. Also, components of common images tended to be better recalled than those of bizarre images after imaging an intervening list of bizarre sentences. Experiments 2a and 2b showed that interfering tasks consisting of studying lists of common concrete nouns did not differentially affect memory for bizarre and common images. In Experiment 3, labeling and imaging an interfering list of common pictures produced higher recall of bizarre images. Generally, bizarre images appeared to be less susceptible than common images to interference from certain types of common encodings. Importantly, the superior recall of bizarre images was always due to greater image (sentence) access, whereas higher recall of common images was associated with greater recovery of the image (sentence) constituents. Explanation of the precise pattern of results requires consideration of the distinctive properties of bizarre images. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Infrared target-flare discrimination using a ZISC hardware neural network

The last generation of infrared imaging aircraft seekers and trackers uses pattern recognition algorithms to find and keep a lock on an aircraft in the presence of decoy flares. These algorithms identify targets, based on the features of the various objects in the missile’s field of view. Because modern both aircrafts and missiles fly faster than sound, speed of operation of the target identifier is critical. In this article, we propose a target recognition system that respects this time constraint. It is based on an artificial neural network implemented in hardware, as a set of parallel processors on a commercially available silicon chip called a ZISC, for zero instruction set computer. This chip would be integrated in the infrared missile seeker and tracker. We describe the characteristics of the images that the image processing module of this seeker and tracker extracts from the infrared video frames and show how to construct from these translation and rotation invariant features that can be used as input to the neural network. We determine the individual discriminating power of these features by constructing their histograms, which allows us to eliminate some as not being useful for our purpose. Finally, by testing our system on real data, we show that it has a 90% success rate in aircraft-flare identification, and a processing time that during this time, the aircrafts and missiles will have traveled only a few millimeters. Most of the images on which the neural network makes its mistakes are seen to be hard to recognize even by a human expert.     

A new approach of data clustering using a flock of agents

This paper presents a new bio-inspired algorithm (FClust) that dynamically creates and visualizes groups of data. This algorithm uses the concepts of a flock of agents that move together in a complex manner with simple local rules. Each agent represents one data. The agents move together in a 2D environment with the aim of creating homogeneous groups of data. These groups are visualized in real time, and help the domain expert to understand the underlying structure of the data set, like for example a realistic number of classes, clusters of similar data, isolated data. We also present several extensions of this algorithm, which reduce its computational cost, and make use of a 3D display. This algorithm is then tested on artificial and real-world data, and a heuristic algorithm is used to evaluate the relevance of the obtained partitioning.     

Détermination du facteur de multiplication M pour un fonctionnement optimal des photodétecteurs à avalanche

The purpose of this paper is relative to the determination of the multiplication factor Mfor an optimum behaviour of the avalanche photodetector. Two types of avalanche photodetector s are compared: a silicon structure n ⁺ πpπp ⁺ Read diode and a GaAlAs heterostructure. Calculating the Noise Equivalent Power (nep)of the whole system, the law S_i(f) =2q I_phoM_x is used, where the parameter x is determined experimentally in both avalanche photodetectors. The exponent x (between 2 and 4) dominates in the nep expression and the ideal nep for the avalanche photodetector system is obtained when x equals 2.     

Reg-1α, a New Substrate of Calpain-2 Depending on Its Glycosylation Status

Reg-1α/lithostathine, a protein mainly associated with the digestive system, was previously shown to be overexpressed in the pre-clinical stages of Alzheimer’s disease. In vitro, the glycosylated protein was reported to form fibrils at physiological pH following the proteolytic action of trypsin. However, the nature of the protease able to act in the central nervous system is unknown. In the present study, we showed that Reg-1α can be cleaved in vitro by calpain-2, the calcium activated neutral protease, overexpressed in neurodegenerative diseases. Using chemical crosslinking experiments, we found that the two proteins can interact with each other. Identification of the cleavage site using mass spectrometry, between Gln⁴ and Thr⁵, was found in agreement with the in silico prediction of the calpain cleavage site, in a position different from the one reported for trypsin, i.e., Arg¹¹-Ile¹² peptide bond. We showed that the cleavage was impeded by the presence of the neighboring glycosylation of Thr⁵. Moreover, in vitro studies using electron microscopy showed that calpain-cleaved protein does not form fibrils as observed after trypsin cleavage. Collectively, our results show that calpain-2 cleaves Reg-1α in vitro, and that this action is not associated with fibril formation.     

Assessing the effect of nutrient mitigation measures in the watersheds of the Southern Bight of the North Sea

The Seine, Somme, and Scheldt Rivers (France, Belgium, and Netherlands) are the major delivering rivers flowing into the continental coastal zone of the Southern Bight of the North Sea, an area regularly affected by eutrophication problems. In the present work, the Seneque-Riverstrahler model was implemented in a multi-regional case study in order to test several planned mitigation measures aimed at limiting stream nutrient contamination and restoring balanced nutrient ratios at the coastal zone.This modeling approach, which is spatially distributed at the basin scale, allows assessing the impact of any change in human activities, which widely differ over the three basins. Here, we define realistic scenarios based on currently proposed measures to reduce point and non-point sources, such as the upgrading of wastewater treatment, the introduction of catch crops, and the development of extensive farming. An analysis of the current situation showed that a 47-72% reduction in P point-source emissions within the three basins could be reached if the intended P treatment was generalized to the largest treatment plants. However, only an overall 14-23% reduction in N could be achieved at the outlet of the three basins, by combining improved wastewater treatment and land use with management measures aimed at regulating agricultural practices. Nonetheless, in spite of these efforts, N will still be exported in large excess with respect to the equilibrium defined by the Redfield ratios, even in the most optimistic hypothesis describing the long-term response of groundwater nitrate concentrations.A comprehensive assessment of these mitigation measures supports the need for additional reductions of nutrient losses from agriculture to control harmful algae development. It also stresses the relevance of this mechanistic approach, in which nutrient transfers from land to sea can be calculated, as an integrated strategy to test policy recommendations.     

Nanohybrid Materials with Tunable Birefringence via Cation Exchange in Polymer Films

In this work, a nanohybrid material based on a freestanding polymeric liquid crystal network capable of postmodification via cation exchange to tune birefringence is proposed. The smectic liquid crystal films can be infiltrated with a variety of cations, thereby changing the refractive indices (n_e and n_o) and the effective birefringence (Δn) of the nanohybrid material, with reversible cation infiltration occurring within minutes. Birefringence could be tuned between values of 0.06 and 0.19, depending on the cation infiltrated into the network. Upon infiltration, a decrease in the smectic layer spacing is found with layer contraction independent of the induced change in birefringence. Potential applications are in the field of specialty optical devices, such as flexible, retunable reflective filters.