Applications of sensitivity analysis for probit stochastic network equilibrium

Network equilibrium models are widely used by traffic practitioners to aid them in making decisions concerning the operation and management of traffic networks. The common practice is to test a prescribed range of hypothetical changes or policy measures through adjustments to the input data, namely the trip demands, the arc performance (travel time) functions, and policy variables such as tolls or signal timings. Relatively little use is, however, made of the full implicit relationship between model inputs and outputs inherent in these models. By exploiting the representation of such models as an equivalent optimisation problem, classical results on the sensitivity analysis of non-linear programs may be applied, to produce linear relationships between input data perturbations and model outputs. We specifically focus on recent results relating to the probit Stochastic User Equilibrium (PSUE) model, which has the advantage of greater behavioural realism and flexibility relative to the conventional Wardrop user equilibrium and logit SUE models. The paper goes on to explore four applications of these sensitivity expressions in gaining insight into the operation of road traffic networks. These applications are namely: identification of sensitive, ‘critical’ parameters; computation of approximate, re-equilibrated solutions following a change (post-optimisation); robustness analysis of model forecasts to input data errors, in the form of confidence interval estimation; and the solution of problems of the bi-level, optimal network design variety. Finally, numerical experiments applying these methods are reported

Exact solution approaches for bilevel lot-sizing

In this paper we propose exact solution methods for a bilevel uncapacitated lot-sizing problem with backlogs. This is an extension of the classical uncapacitated lot-sizing problem with backlogs, in which two autonomous and self-interested decision makers constitute a two-echelon supply chain. The leader buys items from the follower in order to meet external demand at lowest cost. The follower also tries to minimize its costs. Both parties may backlog. We study the leader's problem, i.e., how to determine supply requests over time to minimize its costs in view of the possible actions of the follower. We develop two mixed-integer linear programming reformulations, as well as cutting planes to cut off feasible, but suboptimal solutions. We compare the reformulations on a series of benchmark instances. © 2012 Elsevier B.V. All rights reserved

A sequence-anchored genetic linkage map for the moss, Physcomitrella patens

The moss Physcomitrella patens is a model for the study of plant cell biology and, by virtue of its basal position in land plant phylogeny, for comparative analysis of the evolution of plant gene function and development. It is ideally suited for ‘reverse genetic’ analysis by virtue of its outstanding ability to undertake targeted transgene integration by homologous recombination. However, gene identification through mutagenesis and map-based cloning has hitherto not been possible, due to the lack of a genetic linkage map. Using molecular markers [amplified fragment length polymorphisms (AFLP) and simple sequence repeats (SSR)] we have generated genetic linkage maps for Physcomitrella. One hundred and seventy-nine gene-specific SSR markers were mapped in 46 linkage groups, and 1574 polymorphic AFLP markers were identified. Integrating the SSR- and AFLP-based maps generated 31 linkage groups comprising 1420 markers. Anchorage of the integrated linkage map with gene-specific SSR markers coupled with computational prediction of AFLP loci has enabled its correspondence with the newly sequenced Physcomitrella genome. The generation of a linkage map densely populated with molecular markers and anchored to the genome sequence now provides a resource for forward genetic interrogation of the organism and for the development of a pipeline for the map-based cloning of Physcomitrella genes. This will radically enhance the potential of Physcomitrella for determining how gene function has evolved for the acquisition of complex developmental strategies within the plant kingdom

A theoretical investigation into the trapping of noble gases by clathrates on Titan

In this paper, we use a statistical thermodynamic approach to quantify the efficiency with which clathrates on the surface of Titan trap noble gases. We consider different values of the Ar, Kr, Xe, CH4, C2H6 and N2 abundances in the gas phase that may be representative of Titan's early atmosphere. We discuss the effect of the various parameters that are chosen to represent the interactions between the guest species and the ice cage in our calculations. We also discuss the results of varying the size of the clathrate cages. We show that the trapping efficiency of clathrates is high enough to significantly decrease the atmospheric concentrations of Xe and, to a lesser extent, of Kr, irrespective of the initial gas phase composition, provided that these clathrates are abundant enough on the surface of Titan. In contrast, we find that Ar is poorly trapped in clathrates and, as a consequence, that the atmospheric abundance of argon should remain almost constant. We conclude that the mechanism of trapping noble gases via clathration can explain the deficiency in primordial Xe and Kr observed in Titan's atmosphere by Huygens, but that this mechanism is not sufficient to explain the deficiency in Ar.Comment: Accepted for publication in Planetary and Space Scienc

Constraining the Jurassic extent of Greater India: Tectonic evolution of the West Australian margin

Alternative reconstructions of the Jurassic northern extent of Greater India differ by up to several thousand kilometers. We present a new model that is constrained by revised seafloor spreading anomalies, fracture zones and crustal ages based on drillsites/dredges from all the abyssal plains along the West Australian margin and the Wharton Basin, where an unexpected sliver of Jurassic seafloor (153 Ma) has been found embedded in Cretaceous (95 My old) seafloor. Based on fracture zone trajectories, this NeoTethyan sliver must have originally formed along a western extension of the spreading center that formed the Argo Abyssal Plain, separating a western extension of West Argoland/West Burma from Greater India as a ribbon terrane. The NeoTethyan sliver, Zenith and Wallaby plateaus moved as part of Greater India until westward ridge jumps isolated them. Following another spreading reorganization, the Jurassic crust resumed migrating with Greater India until it was re-attached to the Australian plate ∼95 Ma. The new Wharton Basin data and kinematic model place strong constraints on the disputed northern Jurassic extent of Greater India. Late Jurassic seafloor spreading must have reached south to the Cuvier Abyssal Plain on the West Australian margin, connected to a spreading ridge wrapping around northern Greater India, but this Jurassic crust is no longer preserved there, having been entirely transferred to the conjugate plate by ridge propagations. This discovery constrains the major portion of Greater India to have been located south of the large-offset Wallaby-Zenith Fracture Zone, excluding much larger previously proposed shapes of Greater India

Fear and loathing of electric vehicles: the reactionary rhetoric of range anxiety

“Range anxiety,” defined as the psychological anxiety a consumer experiences in response to the limited range of an electric vehicle, continues to be labelled and presented as one of the most pressing barriers to their mainstream diffusion. As a result, academia, policymakers and even industry have focused on addressing the range anxiety barrier in order to accelerate adoption. Much literature recognizes that range anxiety is increasingly psychological, rather than technical, in its nature. However, we argue in this paper that even psychological and technical explanations are incomplete. We examine range anxiety through Hirschman’s Rhetoric of Reaction, which supposes that conservative forces may oppose change by propagating theses related to jeopardy, perversity, and futility. To do so, we use three qualitative methods to understand the role of range anxiety triangulated via a variety of perspectives: 227 semi-structured interviews with experts at 201 institutions, a survey with nearly 5,000 respondents, and 8 focus groups, all across 17 cities in the five Nordic countries. We find evidence where consumers and experts use and perpetuate the rhetoric of reaction, particularly the jeopardy thesis. We conclude with a reexamination of the policies geared to assuage range-based barriers, which a construction of range anxiety as a rhetorical excuse would render as ineffective or inefficient, as well as future implications for diffusion theory

Lung cancer prediction by Deep Learning to identify benign lung nodules

INTRODUCTION: Deep Learning has been proposed as promising tool to classify malignant nodules. Our aim was to retrospectively validate our Lung Cancer Prediction Convolutional Neural Network (LCP-CNN), which was trained on US screening data, on an independent dataset of indeterminate nodules in an European multicentre trial, to rule out benign nodules maintaining a high lung cancer sensitivity. METHODS: The LCP-CNN has been trained to generate a malignancy score for each nodule using CT data from the U.S. National Lung Screening Trial (NLST), and validated on CT scans containing 2106 nodules (205 lung cancers) detected in patients from from the Early Lung Cancer Diagnosis Using Artificial Intelligence and Big Data (LUCINDA) study, recruited from three tertiary referral centers in the UK, Germany and Netherlands. We pre-defined a benign nodule rule-out test, to identify benign nodules whilst maintaining a high sensitivity, by calculating thresholds on the malignancy score that achieve at least 99 % sensitivity on the NLST data. Overall performance per validation site was evaluated using Area-Under-the-ROC-Curve analysis (AUC). RESULTS: The overall AUC across the European centers was 94.5 % (95 %CI 92.6-96.1). With a high sensitivity of 99.0 %, malignancy could be ruled out in 22.1 % of the nodules, enabling 18.5 % of the patients to avoid follow-up scans. The two false-negative results both represented small typical carcinoids. CONCLUSION: The LCP-CNN, trained on participants with lung nodules from the US NLST dataset, showed excellent performance on identification of benign lung nodules in a multi-center external dataset, ruling out malignancy with high accuracy in about one fifth of the patients with 5-15 mm nodules

Identifying the connection between Roman Conceptions of ‘Pure Air’ and Physical and Mental Health in Pompeian Gardens (c. 150 BC-AD 79): A Multi-Sensory Approach to Ancient Medicine

Different genres of Roman literature commented on the relationship between the condition of the environment and physical and mental health. They often refer to clear, pure, or good air as a beneficial aspect of the environment. Yet, unlike fetid air, they provide few descriptions of what constituted healthy air quality. Moreover, aside from pointing out the association between the environment and bodily condition, the writers also did not explain precisely how the link between the two was made. This paper utilizes a comparative study of ancient literature and the archaeological remains of Roman gardens in Pompeii: archaeobotanical samples, fresco paintings, location, and surviving features. Three questions are addressed in this study: First, how did the Romans identify and define pure? Second, how did air connect to the body? Third, what were the qualities of pure air and how did they benefit the body? Not only was inhalation a means of linking air to the body, but the two were also related through sensory perception. I argue that sight, sound, and olfaction were used to identify the qualities of pure air. Through the sensory process of identification, the beneficial properties of pure air were, in accordance with ancient perceptions of sensory function, taken into the body and affected health. Thus, sensory perception acted as the bridge between the environment and health