The Different Structures of the Two Classes of Starless Cores

We describe a model for the thermal and dynamical equilibrium of starless cores that includes the radiative transfer of the gas and dust and simple CO chemistry. The model shows that the structure and behavior of the cores is significantly different depending on whether the central density is either above or below about 10^5 cm-3. This density is significant as the critical density for gas cooling by gas-dust collisions and also as the critical density for dynamical stability, given the typical properties of the starless cores. The starless cores thus divide into two classes that we refer to as thermally super-critical and thermally sub-critical.This two-class distinction allows an improved interpretation of the different observational data of starless cores within a single model.Comment: ApJ in pres

The MAST motional Stark effect diagnostic

A motional Stark effect (MSE) diagnostic is now installed and operating routinely on the MAST spherical tokamak, with 35 radial channels, spatial resolution of ∼2.5 cm, and time resolution of ∼1 ms at angular noise levels of ∼0.5°. Conventional (albeit very narrow) interference filters isolate π or σ polarized emission. Avalanche photodiode detectors with digital phase-sensitive detection measure the harmonics of a pair of photoelastic modulators operating at 20 and 23 kHz, and thus the polarization state. The π component is observed to be significantly stronger than σ, in reasonably good agreement with atomic physics calculations, and as a result, almost all channels are now operated on π. Trials with a wide filter that admits the entire Stark pattern (relying on the net polarization of the emission) have demonstrated performance almost as good as the conventional channels. MSE-constrained equilibrium reconstructions can readily be produced between pulses.This work was funded partly by the United Kingdom Engineering and Physical Sciences Research Council under Grant No. P/G003955 and by the European Communities under the contract of association between Euratom and CCFE

Patterns of homozygosity in insular and continental goat breeds

Background: Genetic isolation of breeds may result in a significant loss of diversity and have consequences on health and performance. In this study, we examined the effect of geographic isolation on caprine genetic diversity patterns by genotyping 480 individuals from 25 European and African breeds with the Goat SNP50 BeadChip and comparing patterns of homozygosity of insular and nearby continental breeds. Results: Among the breeds analysed, number and total length of ROH varied considerably and depending on breeds, ROH could cover a substantial fraction of the genome (up to 1.6 Gb in Icelandic goats). When compared with their continental counterparts, goats from Iceland, Madagascar, La Palma and Ireland (Bilberry and Arran) displayed a significant increase in ROH coverage, ROH number and F ROH values (P value < 0.05). Goats from Mediterranean islands represent a more complex case because certain populations displayed a significantly increased level of homozygosity (e.g. Girgentana) and others did not (e.g. Corse and Sarda). Correlations of number and total length of ROH for insular goat populations with the distance between islands and the nearest continental locations revealed an effect of extremely long distances on the patterns of homozygosity. Conclusions: These results indicate that the effects of insularization on the patterns of homozygosity are variable. Goats raised in Madagascar, Iceland, Ireland (Bilberry and Arran) and La Palma, show high levels of homozygosity, whereas those bred in Mediterranean islands display patterns of homozygosity that are similar to those found in continental populations. These results indicate that the diversity of insular goat populations is modulated by multiple factors such as geographic distribution, population size, demographic history, trading and breed management

Global and local environmental changes as drivers of Buruli ulcer emergence

International audienceMany emerging infectious diseases are caused by generalist pathogens that infect and transmit via multiple host species with multiple dissemination routes, thus confounding the understanding of pathogen transmission pathways from wildlife reservoirs to humans. The emergence of these pathogens in human populations has frequently been associated with global changes, such as socio-economic, climate or biodiversity modifications, by allowing generalist pathogens to invade and persist in new ecological niches, infect new host species, and thus change the nature of transmission pathways. Using the case of Buruli ulcer disease, we review how land-use changes, climatic patterns and biodiversity alterations contribute to disease emergence in many parts of the world. Here we clearly show that Mycobacterium ulcerans is an environmental pathogen characterized by multi-host transmission dynamics and that its infectious pathways to humans rely on the local effects of global environmental changes. We show that the interplay between habitat changes (for example, deforestation and agricultural land-use changes) and climatic patterns (for example, rainfall events), applied in a local context, can lead to abiotic environmental changes and functional changes in local biodiversity that favor the pathogen’s prevalence in the environment and may explain disease emergence

The potential use of service-oriented infrastructure framework to enable transparent vertical scalability of cloud computing infrastructure

Cloud computing technology has become familiar to most Internet users. Subsequently, there has been an increased growth in the use of cloud computing, including Infrastructure as a Service (IaaS). To ensure that IaaS can easily meet the growing demand, IaaS providers usually increase the capacity of their facilities in a vertical IaaS increase capability and the capacity for local IaaS amenities such as increasing the number of servers, storage and network bandwidth. However, at the same time, horizontal scalability is sometimes not enough and requires additional strategies to ensure that the large number of IaaS service requests can be met. Therefore, strategies requiring horizontal scalability are more complex than the vertical scalability strategies because they involve the interaction of more than one facility at different service centers. To reduce the complexity of the implementation of the horizontal scalability of the IaaS infrastructures, the use of a technology service oriented infrastructure is recommended to ensure that the interaction between two or more different service centers can be done more simply and easily even though it is likely to involve a wide range of communication technologies and different cloud computing management. This is because the service oriented infrastructure acts as a middle man that translates and processes interactions and protocols of different cloud computing infrastructures without the modification of the complex to ensure horizontal scalability can be run easily and smoothly. This paper presents the potential of using a service-oriented infrastructure framework to enable transparent vertical scalability of cloud computing infrastructures by adapting three projects in this research: SLA@SOI consortium, Open Cloud Computing Interface (OCCI), and OpenStack

Experimental Quantum Hamiltonian Learning

Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quantum technologies and for our continued understanding of foundational physics. Machine-learning enhanced by quantum simulators has been proposed as a route to improve the computational cost of performing these studies. Here we interface two different quantum systems through a classical channel - a silicon-photonics quantum simulator and an electron spin in a diamond nitrogen-vacancy centre - and use the former to learn the latter's Hamiltonian via Bayesian inference. We learn the salient Hamiltonian parameter with an uncertainty of approximately $10^{-5}$. Furthermore, an observed saturation in the learning algorithm suggests deficiencies in the underlying Hamiltonian model, which we exploit to further improve the model itself. We go on to implement an interactive version of the protocol and experimentally show its ability to characterise the operation of the quantum photonic device. This work demonstrates powerful new quantum-enhanced techniques for investigating foundational physical models and characterising quantum technologies

On the experimental verification of quantum complexity in linear optics

The first quantum technologies to solve computational problems that are beyond the capabilities of classical computers are likely to be devices that exploit characteristics inherent to a particular physical system, to tackle a bespoke problem suited to those characteristics. Evidence implies that the detection of ensembles of photons, which have propagated through a linear optical circuit, is equivalent to sampling from a probability distribution that is intractable to classical simulation. However, it is probable that the complexity of this type of sampling problem means that its solution is classically unverifiable within a feasible number of trials, and the task of establishing correct operation becomes one of gathering sufficiently convincing circumstantial evidence. Here, we develop scalable methods to experimentally establish correct operation for this class of sampling algorithm, which we implement with two different types of optical circuits for 3, 4, and 5 photons, on Hilbert spaces of up to 50,000 dimensions. With only a small number of trials, we establish a confidence >99% that we are not sampling from a uniform distribution or a classical distribution, and we demonstrate a unitary specific witness that functions robustly for small amounts of data. Like the algorithmic operations they endorse, our methods exploit the characteristics native to the quantum system in question. Here we observe and make an application of a "bosonic clouding" phenomenon, interesting in its own right, where photons are found in local groups of modes superposed across two locations. Our broad approach is likely to be practical for all architectures for quantum technologies where formal verification methods for quantum algorithms are either intractable or unknown.Comment: Comments welcom

Aerodynamic investigations of ventilated brake discs.

The heat dissipation and performance of a ventilated brake disc strongly depends on the aerodynamic characteristics of the flow through the rotor passages. The aim of this investigation was to provide an improved understanding of ventilated brake rotor flow phenomena, with a view to improving heat dissipation, as well as providing a measurement data set for validation of computational fluid dynamics methods. The flow fields at the exit of four different brake rotor geometries, rotated in free air, were measured using a five-hole pressure probe and a hot-wire anemometry system. The principal measurements were taken using two-component hot-wire techniques and were used to determine mean and unsteady flow characteristics at the exit of the brake rotors. Using phase-locked data processing, it was possible to reveal the spatial and temporal flow variation within individual rotor passages. The effects of disc geometry and rotational speed on the mean flow, passage turbulence intensity, and mass flow were determined. The rotor exit jet and wake flow were clearly observed as characterized by the passage geometry as well as definite regions of high and low turbulence. The aerodynamic flow characteristics were found to be reasonably independent of rotational speed but highly dependent upon rotor geometry