Modeling aviation baggage screening security systems: a case study

Aviation security protects vital national interests, as well as passengers and aircraft. Key components of an aviation security system include baggage and passenger screening devices and operations. Determining how and where to assign (deploy) such devices can be quite challenging. Moreover, even after such systems are in place, it can be difficult to measure their effectiveness. This paper describes how discrete optimization models can be used to address these questions, based on three performance measures that quantify the effectiveness of airport baggage screening security device systems. These models are used to solve for optimal airport baggage screening security device deployments considering the number of passengers on a set of flights who have not been cleared using a security risk assessment system in use by the Federal Aviation Administration (i.e., passengers whose baggage is subjected to screening), the number of flights in this set, and the size of the aircraft for such flights. Several examples are provided to illustrate these results, including an example that uses data available from the Official Airline Guide.     

Cardiovascular effects produced by R-(+)-8-hydroxy-2-(di-n-propylamino) tetralin in the preoptic area of conscious rats

The effect of ancrod-induced defibrinogenation on thrombosis and bleeding time was determined in anesthetized rats. Functional plasma fibrinogen levels were reduced 42, 71, 94 and 93% by ancrod doses of 5, 10, 20 and 30 U/kg, respectively, while a 2.5 U/kg dose was without significant effect. Ancrod inhibited vena cava thrombosis induced by partial stasis of blood flow combined with mild vascular injury. Thrombus weight was decreased 85 and 93% by the 10 and 20 U/kg doses, but was unaffected at lower doses. In contrast, ancrod doses of up to 30 U/kg did not significantly decrease carotid artery thrombi formed in response to oxidative transmural vessel injury. Ancrod caused a dose-dependent increase in bleeding time measured by puncturing small mesenteric arteries with a hypodermic needle. The bleeding time increase was approximately 38% in response to the 2.5 and 5 U/kg doses, and 182% in response to the 10 U/kg dose. These studies demonstrate that ancrod-induced reductions in plasma fibrinogen more effectively inhibit venous compared to arterial thrombosis, although these activities require doses that also increase bleeding time in small arteries.     

Impact of die-to-die and within-die parameter fluctuations on themaximum clock frequency distribution for gigascale integration

A model describing the maximum clock frequency (FMAX) distribution of a microprocessor is derived and compared with wafer sort data for a recent 0.25-μm microprocessor. The model agrees closely with measured data in mean, variance, and shape. Results demonstrate that within-die fluctuations primarily impact the FMAX mean and die-to-die fluctuations determine the majority of the FMAX variance. Employing rigorously derived device and circuit models, the impact of die-to-die and within-die parameter fluctuations on future FMAX distributions is forecast for the 180, 130, 100, 70, and 50-nm technology generations. Model predictions reveal that systematic within-die fluctuations impose the largest performance degradation resulting from parameter fluctuations. Assuming a 3σ channel length deviation of 20%, projections for the 50-nm technology generation indicate that essentially a generation of performance gain can be lost due to systematic within-die fluctuations. Key insights from this work elucidate the recommendations that manufacturing process controls be targeted specifically toward sources of systematic within-die fluctuations, and the development of new circuit design methodologies be aimed at suppressing the effect of within-die parameter fluctuations     

Metallurgical failure analysis of cold cracking in a structural steel weldment: Revisiting a classic failure mechanism

Cold cracking of structural steel weldments is a well-characterized, well-documented, and well-understood failure mechanism. Extensive effort has been put forth to recognize the welding and materials selection parameters that are conducive to cold cracking; however, these engineering efforts have not fully eliminated the occurrence of such failures. This article describes cold cracking failure specifically related to the construction industry. This particular failure was successfully identified prior to final erection of the structural member, and the weld was successfully reworked. These actions potentially prevented a serious catastrophic event that could have occurred have occurred either later in the construction process or possibly during the use of the building. Individual welding parameters, such as electrode/wire selection, joint design, and pre/postheating, played a role in the failure, and a number of human factors relating to the actual fabrication practices also contributed to the failure process.     

Flocculation behavior of some cationic polyelectrolytes

The settling rates and adsorption isotherms produced by a variety of suites of cationic polyelectrolytes in 3% kaolin suspensions were measured. Settling rates increased with molar mass even for low-mass, high-charge polymers. The very high settling rates produced by cationic copolymers of acrylamide decreased as the charge density of the polymer used increased. Hydrolysis of unbuffered polymers occurred over time and produced large changes in the effectiveness of the polymers. This is attributed to conformational changes. © 1994 John Wiley & Sons, Inc.     

Constraints on benthic algal response to nutrient addition in oligotrophic mountain rivers

Nutrient availability has long been considered one of the most important factors regulating production of benthic algae in oligotrophic rivers; yet, empirical relationships do not have as wide an application as similar models derived for lentic systems. The aim of this research was to derive empirical relationships between nutrient concentrations and benthic algal abundance and to identify commonalities with other studies to improve our understanding of constraints on algae in oligotrophic rivers. Surveys of physical, chemical and biological attributes of oligotrophic mountain rivers in spring, summer and autumn for 2 years confirmed that small amounts of anthropogenic phosphorus (0.1–5.6 µg/L total phosphorus (TP)) resulted in 4‐ to 30‐fold increases in abundance of benthic algae and benthic macroinvertebrates (BMIs). Algal accrual along a gradient in nutrient availability was not masked by grazing pressure but was positively correlated with abundance of scrapers. Epilithic abundance was highest downstream of anthropogenic nutrient sources in autumn. We concluded that benthic algal abundance in these mountain rivers was weakly correlated with phosphorus availability if light was not limiting but ultimately controlled by temperature and river discharge. Therefore, we recommend more direct measures of nutrient limitation be used to predict changes in ecological integrity at the lower end of the resource gradient. Copyright © 2007 John Wiley & Sons, Ltd.     

Analysing neurobiological models using communicating automata

Two important issues in computational modelling in cognitive neuroscience are: first, how to formally describe neuronal networks (i.e. biologically plausible models of the central nervous system), and second, how to analyse complex models, in particular, their dynamics and capacity to learn. We make progress towards these goals by presenting a communicating automata perspective on neuronal networks. Specifically, we describe neuronal networks and their biological mechanisms using Data-rich Communicating Automata, which extend classic automata theory with rich data types and communication. We use two case studies to illustrate our approach. In the first case study, we model a number of learning frameworks, which vary in respect of their biological detail, for instance the Backpropagation (BP) and the Generalized Recirculation (GeneRec) learning algorithms. We then used the SPIN model checker to investigate a number of behavioral properties of the neural learning algorithms. SPIN is a well-known model checker for reactive distributed systems, which has been successfully applied to many non-trivial problems. The verification results show that the biologically plausible GeneRec learning is less stable than BP learning. In the second case study, we presented a large scale (cognitive-level) neuronal network, which models an attentional spotlight mechanism in the visual system. A set of properties of this model was verified using Uppaal, a popular real-time model checker. The results show that the asynchronous processing supported by concurrency theory is not only a more biologically plausible way to model neural systems, but also provides a better performance in cognitive modelling of the brain than conventional artificial neural networks that use synchronous updates. Finally, we compared our approach with several other related theories that apply formal methods to cognitive modelling. In addition, the practical implications of the approach are discussed in the context of neuronal network based controllers.     

Development of a comprehensive free radical photopolymerization model incorporating heat and mass transfer effects in thick films

A comprehensive kinetic model describing photopolymerization is developed which allows variation of temperature, species concentrations, and light intensity through the thickness of a photopolymerized film. Heat and mass transfer effects are included, as is the generation of heat by both reaction and light absorption. In addition to initiation, propagation, and termination mechanisms, both primary radical termination and inhibition are incorporated into the model. The possible presence and diffusion of an inert solvent are also accounted for. Thus, the model is useful for examining complex polymerization kinetics and behavior in industrially and commercially important thick film photopolymerizations, such as the curing of contact lenses, dental restorative materials, photolithographic resists, and optoelectronic coatings. The comprehensive model is used to predict polymerization rate, temperature, and conversion profiles in a variety of systems. The effects of heat generation and the thermal boundary conditions are explored, with the result that heat generation in thick samples leads to greatly increased conversions approaching 100 percent. Increased temperature in these samples also may lead to the appearance of two rate maxima, with the first due to the temperature increase and the second caused by the autoacceleration process. The magnitude of the temperature increase, along with the resultant effects, is more pronounced in insulated systems.