Numerical and physical simulation of rapid microstructural evolution of gas atomised Ni superalloy powders

The rapid microstructural evolution of gas atomised Ni superalloy powder compacts over timescales of a few seconds was studied using a Gleeble 3500 thermomechanical simulator, finite element based numerical model and electron microscopy. The study found that the microstructural changes were governed by the characteristic temperatures of the alloy. At a temperature below the γ' solvus, the powders maintained dendritic structures. Above the γ' solvus temperature but in the solid-state, rapid grain spheroidisation and coarsening occurred, although the fine-scale microstructures were largely retained. Once the incipient melting temperature of the alloy was exceeded, microstructural change was rapid, and when the temperature was increased into the solid + liquid state, the powder compact partially melted and then re-solidified with no trace of the original structures, despite the fast timescales. The study reveals the relationship between short, severe thermal excursions and microstructural evolution in powder processed components, and gives guidance on the upper limit of temperature and time for powder-based processes if desirable fine-scale features of powders are to be preserved

Dynamically stabilized decoherence-free states in non-Markovian open fermionic systems

Decoherence-free subspaces (DFSs) provide a strategy for protecting the dynamics of an open system from decoherence induced by the system-environment interaction. So far, DFSs have been primarily studied in the framework of Markovian master equations. In this work, we study decoherence-free (DF) states in the general setting of a non-Markovian fermionic environment. We identify the DF states by diagonalizing the non-unitary evolution operator for a two-level fermionic system attached to an electron reservoir. By solving the exact master equation, we show that DF states can be stabilized dynamically.Comment: 11 pages, 3 figures. Any comments are welcom

Gut microbiota targeted approach in the management of chronic liver diseases

The liver is directly connected to the intestines through the portal vein, which enables the gut microbiota and gut-derived products to influence liver health. There is accumulating evidence of decreased gut flora diversity and alcohol sensitivity in patients with various chronic liver diseases, including non-alcoholic/alcoholic liver disease, chronic hepatitis virus infection, primary sclerosing cholangitis and liver cirrhosis. Increased intestinal mucosal permeability and decline in barrier function were also found in these patients. Followed by bacteria translocation and endotoxin uptake, these will lead to systemic inflammation. Specific microbiota and microbiota-derived metabolites are altered in various chronic liver diseases studies, but the complex interaction between the gut microbiota and liver is missing. This review article discussed the bidirectional relationship between the gut and the liver, and explained the mechanisms of how the gut microbiota ecosystem alteration affects the pathogenesis of chronic liver diseases. We presented gut-microbiota targeted interventions that could be the new promising method to manage chronic liver diseases

Resonances in a two-dimensional electron waveguide with a single delta-function scatterer

We study the conductance properties of a straight two-dimensional electron waveguide with an s-like scatterer modeled by a single delta-function potential with a finite number of modes. Even such a simple system exhibits interesting resonance phenomena. These resonances are explained in terms of quasi-bound states both by using a direct solution of the Schroedinger equation and by studying the Green's function of the system. Using the Green's function we calculate the survival probability as well as the power absorption and show the influence of the quasi-bound states on these two quantities.Comment: 5 pages, 6 figures, to be published in Physical Review

Flexible and Robust Privacy-Preserving Implicit Authentication

Implicit authentication consists of a server authenticating a user based on the user's usage profile, instead of/in addition to relying on something the user explicitly knows (passwords, private keys, etc.). While implicit authentication makes identity theft by third parties more difficult, it requires the server to learn and store the user's usage profile. Recently, the first privacy-preserving implicit authentication system was presented, in which the server does not learn the user's profile. It uses an ad hoc two-party computation protocol to compare the user's fresh sampled features against an encrypted stored user's profile. The protocol requires storing the usage profile and comparing against it using two different cryptosystems, one of them order-preserving; furthermore, features must be numerical. We present here a simpler protocol based on set intersection that has the advantages of: i) requiring only one cryptosystem; ii) not leaking the relative order of fresh feature samples; iii) being able to deal with any type of features (numerical or non-numerical). Keywords: Privacy-preserving implicit authentication, privacy-preserving set intersection, implicit authentication, active authentication, transparent authentication, risk mitigation, data brokers.Comment: IFIP SEC 2015-Intl. Information Security and Privacy Conference, May 26-28, 2015, IFIP AICT, Springer, to appea

How Many Cooks Spoil the Soup?

In this work, we study the following basic question: "How much parallelism does a distributed task permit?" Our definition of parallelism (or symmetry) here is not in terms of speed, but in terms of identical roles that processes have at the same time in the execution. We initiate this study in population protocols, a very simple model that not only allows for a straightforward definition of what a role is, but also encloses the challenge of isolating the properties that are due to the protocol from those that are due to the adversary scheduler, who controls the interactions between the processes. We (i) give a partial characterization of the set of predicates on input assignments that can be stably computed with maximum symmetry, i.e., $\Theta(N_{min})$, where $N_{min}$ is the minimum multiplicity of a state in the initial configuration, and (ii) we turn our attention to the remaining predicates and prove a strong impossibility result for the parity predicate: the inherent symmetry of any protocol that stably computes it is upper bounded by a constant that depends on the size of the protocol.Comment: 19 page

On Iterated Twisted Tensor Products of Algebras

We introduce and study the definition, main properties and applications of iterated twisted tensor products of algebras, motivated by the problem of defining a suitable representative for the product of spaces in noncommutative geometry. We find conditions for constructing an iterated product of three factors, and prove that they are enough for building an iterated product of any number of factors. As an example of the geometrical aspects of our construction, we show how to construct differential forms and involutions on iterated products starting from the corresponding structures on the factors, and give some examples of algebras that can be described within our theory. We prove a certain result (called ``invariance under twisting'') for a twisted tensor product of two algebras, stating that the twisted tensor product does not change when we apply certain kind of deformation. Under certain conditions, this invariance can be iterated, containing as particular cases a number of independent and previously unrelated results from Hopf algebra theory.Comment: 44 pages, 21 figures. More minor typos corrections, one more example and some references adde

Aberrant phenotype in human endothelial cells of diabetic origin: Implications for saphenous vein graft failure?

Type 2 diabetes (T2DM) confers increased risk of endothelial dysfunction, coronary heart disease, and vulnerability to vein graft failure after bypass grafting, despite glycaemic control. This study explored the concept that endothelial cells (EC) cultured from T2DM and nondiabetic (ND) patients are phenotypically and functionally distinct. Cultured human saphenous vein-(SV-) EC were compared between T2DM and ND patients in parallel. Proliferation, migration, and in vitro angiogenesis assays were performed; western blotting was used to quantify phosphorylation of Akt, ERK, and eNOS. The ability of diabetic stimuli (hyperglycaemia, TNF-α, and palmitate) to modulate angiogenic potential of ND-EC was also explored. T2DM-EC displayed reduced migration (30%) and angiogenesis (40%) compared with ND-EC and a modest, nonsignificant trend to reduced proliferation. Significant inhibition of Akt and eNOS, but not ERK phosphorylation, was observed in T2DM cells. Hyperglycaemia did not modify ND-EC function, but TNF-α and palmitate significantly reduced angiogenic capacity (by 27% and 43%, resp.), effects mimicked by Akt inhibition. Aberrancies of EC function may help to explain the increased risk of SV graft failure in T2DM patients. This study highlights the importance of other potentially contributing factors in addition to hyperglycaemia that may inflict injury and long-term dysfunction to the homeostatic capacity of the endothelium

Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm

We live in an era of abundant data. This has necessitated the development of new and innovative statistical algorithms to get the most from experimental data. For example, faster algorithms make practical the analysis of larger genomic data sets, allowing us to extend the utility of cutting-edge statistical methods. We present a randomised algorithm that accelerates the clustering of time series data using the Bayesian Hierarchical Clustering (BHC) statistical method. BHC is a general method for clustering any discretely sampled time series data. In this paper we focus on a particular application to microarray gene expression data. We define and analyse the randomised algorithm, before presenting results on both synthetic and real biological data sets. We show that the randomised algorithm leads to substantial gains in speed with minimal loss in clustering quality. The randomised time series BHC algorithm is available as part of the R package BHC, which is available for download from Bioconductor (version 2.10 and above) via http://bioconductor.org/packages/2.10/bioc/html/BHC.html. We have also made available a set of R scripts which can be used to reproduce the analyses carried out in this paper. These are available from the following URL. https://sites.google.com/site/randomisedbhc/

Improved harmonic approximation and the 2D Ising model at T≠TcT\neq T_{c} and h≠0h\neq0

We propose a new method to determine the unknown parameter associated to a self-consistent harmonic approximation. We check the validity of our technique in the context of the sine-Gordon model. As a non trivial application we consider the scaling regime of the 2D Ising model away from the critical point and in the presence of a magnetic field $h$. We derive an expression that relates the approximate correlation length $\xi$, $T-T_c$ and $h$.Comment: 11 pages, Latex, 3 figures. Accepted for publication in Journal of Physics