A theoretical investigation of the aerodynamics of slender wing-body combinations exhibiting leading-edge separation

Theoretical investigation of aerodynamics of slender wing-body combinations exhibiting leading edge separatio

Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

Peer reviewe

The Disunity of Consciousness

It is commonplace for both philosophers and cognitive scientists to express their allegiance to the "unity of consciousness". This is the claim that a subject’s phenomenal consciousness, at any one moment in time, is a single thing. This view has had a major influence on computational theories of consciousness. In particular, what we call single-track theories dominate the literature, theories which contend that our conscious experience is the result of a single consciousness-making process or mechanism in the brain. We argue that the orthodox view is quite wrong: phenomenal experience is not a unity, in the sense of being a single thing at each instant. It is a multiplicity, an aggregate of phenomenal elements, each of which is the product of a distinct consciousness-making mechanism in the brain. Consequently, cognitive science is in need of a multi-track theory of consciousness; a computational model that acknowledges both the manifold nature of experience, and its distributed neural basis

Characterization of a hybrid flame/arc excitation source using monodisperse aerosol introduction

A hybrid flame/arc excitation source together with a monodisperse droplet generator is used to inject solute particles into selected regions of the arc plasma. With astigmatic image transfer and a 0.5 [mu]s time constant detection system, individual solute vapor cloud emission profiles are detected in the arc tail flame. These emission profiles are always asymmetric with sharper leading edges. Emission profiles are presented for Ca at several positions in the arc tail flame. The (zinc) excitation temperature was measured at 6600 K in the region 1-2 mm above the arc conduction channel. A double aperture technique was used to estimate the arc convective velocity at about 50 m s-1. When the emission plume origin from a monodisperse droplet stream is positioned in the tail flame region, analytical line-to-background ratios typically are one-two orders of magnitude greater than when the plume origin is located below the conduction channel. Analytical curves from the tail flame region are linear over at least two-three orders of concentration, and detection limits are significantly lower than literature values for the region just under the conduction channel of an Ar-stabilized bent arc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/25428/1/0000877.pd

Gene expression in Leishmania is regulated predominantly by gene dosage

ABSTRACT Leishmania tropica, a unicellular eukaryotic parasite present in North and East Africa, the Middle East, and the Indian subcontinent, has been linked to large outbreaks of cutaneous leishmaniasis in displaced populations in Iraq, Jordan, and Syria. Here, we report the genome sequence of this pathogen and 7,863 identified protein-coding genes, and we show that the majority of clinical isolates possess high levels of allelic diversity, genetic admixture, heterozygosity, and extensive aneuploidy. By utilizing paired genome-wide high-throughput DNA sequencing (DNA-seq) with RNA-seq, we found that gene dosage, at the level of individual genes or chromosomal “somy” (a general term covering disomy, trisomy, tetrasomy, etc.), accounted for greater than 85% of total gene expression variation in genes with a 2-fold or greater change in expression. High gene copy number variation (CNV) among membrane-bound transporters, a class of proteins previously implicated in drug resistance, was found for the most highly differentially expressed genes. Our results suggest that gene dosage is an adaptive trait that confers phenotypic plasticity among natural Leishmania populations by rapid down- or upregulation of transporter proteins to limit the effects of environmental stresses, such as drug selection. IMPORTANCE Leishmania is a genus of unicellular eukaryotic parasites that is responsible for a spectrum of human diseases that range from cutaneous leishmaniasis (CL) and mucocutaneous leishmaniasis (MCL) to life-threatening visceral leishmaniasis (VL). Developmental and strain-specific gene expression is largely thought to be due to mRNA message stability or posttranscriptional regulatory networks for this species, whose genome is organized into polycistronic gene clusters in the absence of promoter-mediated regulation of transcription initiation of nuclear genes. Genetic hybridization has been demonstrated to yield dramatic structural genomic variation, but whether such changes in gene dosage impact gene expression has not been formally investigated. Here we show that the predominant mechanism determining transcript abundance differences (>85%) in Leishmania tropica is that of gene dosage at the level of individual genes or chromosomal somy

A comparison of statistical emulation methodologies for multi-wave calibration of environmental models

Expensive computer codes, particularly those used simulating environmental or geological processes such as climate models, require calibration (sometimes called tuning). When calibrating expensive simulators using uncertainty quantification methods, it is usually necessary to use a statistical model called an emulator in place of the computer code when running the calibration algorithm. Though emulators based on Gaussian processes are typically many orders of magnitude faster to evaluate than the simulator they mimic, many applications have sought to speed up the computations by using regression-only emulators within the calculations instead, arguing that the extra sophistication brought using the Gaussian process is not worth the extra computational power. This was the case for the analysis that produced the UK climate projections in 2009. In this paper we compare the effectiveness of both emulation approaches upon a multi-wave calibration framework that is becoming popular in the climate modelling community called \history matching". We find that Gaussian processes offer significant benefits to the reduction of parametric uncertainty over regression-only approaches. We find that in a multi-wave experiment, a combination of regression-only emulators initially, followed by Gaussian process emulators for refocussing experiments can be nearly as effective as using Gaussian processes throughout for a fraction of the computational cost. We also discover a number of design and emulator-dependent features of the multi-wave history matching approach that can cause apparent, yet premature, convergence of our estimates of parametric uncertainty. We compare these approaches to calibration in idealised examples and apply it to a well-known geological reservoir mode

EU support for biofuels and bioenergy, environmental sustainability criteria, and trade policy

This paper presents physics-based surrogate modeling algorithms for systems governed by parameterized partial differential equations (PDEs) commonly encountered in design optimization and uncertainty analysis. We first outline unsupervised learning approaches that leverage advances in the machine learning literature for a meshfree solution of PDEs. Subsequently, we propose continuum and discrete formulations for systems governed by parameterized steady-state PDEs. We consider the case of both deterministically and randomly parameterized systems. The basic idea is to embody the design variables or uncertain parameters in additional dimensions of the governing PDEs along with the spatial coordinates. We show that the undetermined parameters of the surrogate model can be estimated by minimizing a physics-based objective function derived using a multidimensional least-squares collocation or the Bubnov-Galerkin scheme. This potentially allows us to construct surrogate models without using data from computer experiments on a deterministic analysis code. Finally, we also outline an extension of the present approach to directly approximate the density function of random algebraic equations

The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs

With the development of new highly efficacious direct acting antiviral treatments (DAAs) for hepatitis C (HCV), the concept of treatment as prevention is gaining credence. To date the majority of mathematical models assume perfect mixing with injectors having equal contact with all other injectors. This paper explores how using a networks based approach to treat people who inject drugs (PWID) with DAAs affects HCV prevalence. Method: Using observational data we parameterized an Exponential Random Graph Model containing 524 nodes. We simulated transmission of HCV through this network using a discrete time, stochastic transmission model. The effect of five treatment strategies on the prevalence of HCV was investigated; two of these strategies were 1) treat randomly selected nodes and 2) “treat your friends” where an individual is chosen at random for treatment and all their infected neighbours are treated. Results: As treatment coverage increases, HCV prevalence at 10 years reduces for both the high efficacy and low efficacy treatment. Within each set of parameters, the “treat your friends” strategy performed better than the random strategy being most marked for higher efficacy treatment. For example over 10 years of treating 25 per 1000 PWID, the prevalence drops from 50% to 40% for the random strategy, and to 33% for the “treat your friends” strategy (6.5% difference, 95% CI 5.1 – 8.1%). Discussion: “Treat your friends” is a feasible means of utilising network strategies to improve treatment efficiency. In an era of highly efficacious and highly tolerable treatment such an approach will benefit not just the individual but the community more broadly by reducing the prevalence of HCV amongst PWID

Skin, Thermal and Umbilical Cord Care Practices for Neonates in Southern, Rural Zambia: A Qualitative Study

Background: In Choma District, southern Zambia, the neonatal mortality rate is approximately 40 per 1000 live births and, although the rate is decreasing, many deliveries take place outside of formal facilities. Understanding local practices during the postnatal period is essential for optimizing newborn care programs. Methods: We conducted 36 in-depth interviews, five focus groups and eight observational sessions with recently-delivered women, traditional birth attendants, and clinic and hospital staff from three sites, focusing on skin, thermal and cord care practices for newborns in the home. Results: Newborns were generally kept warm by application of hats and layers of clothing. While thermal protection is provided for preterm and small newborns, the practice of nighttime bathing with cold water was common. The vernix was considered important for the preterm newborn but dangerous for HIV-exposed infants. Mothers applied various substances to the skin and umbilical cord, with special practices for preterm infants. Applied substances included petroleum jelly, commercial baby lotion, cooking oil and breastmilk. The most common substances applied to the umbilical cord were powders made of roots, burnt gourds or ash. To ward off malevolent spirits, similar powders were reportedly placed directly into dermal incisions, especially in ill children. Conclusions: Thermal care for newborns is commonly practiced but co-exists with harmful practices. Locally appropriate behavior change interventions should aim to promote chlorhexidine in place of commonly-reported application of harmful substances to the skin and umbilical cord, reduce bathing of newborns at night, and address the immediate bathing of HIV-infected newborns