Artificial neural network prediction of weld distortion rectification using a travelling induction coil

An experimental investigation has been carried out to determine the applicability of an induction heating process with a travelling induction coil for the rectification of angular welding distortion. The results obtained from experimentation have been used to create artificial neural network models with the ability to predict the welding induced distortion and the distortion rectification achieved using a travelling induction coil. The experimental results have shown the ability to reduce the angular distortion for 8 mm and 10 mm thick DH36 steel plate and effectively eliminate the distortion on 6 mm thick plate. Results for 6 mm plate also show the existence of a critical induction coil travel speed at which maximum corrective bending occurs. Artificial neural networks have demonstrated the ability to predict the final distortion of the plate after both welding and induction heating. The models have also been used as a tool to determine the optimum speed to minimise the resulting distortion of steel plate after being subjected to both welding and induction heating processes

On the iterated Crank-Nicolson for hyperbolic and parabolic equations in numerical relativity

The iterated Crank-Nicolson is a predictor-corrector algorithm commonly used in numerical relativity for the solution of both hyperbolic and parabolic partial differential equations. We here extend the recent work on the stability of this scheme for hyperbolic equations by investigating the properties when the average between the predicted and corrected values is made with unequal weights and when the scheme is applied to a parabolic equation. We also propose a variant of the scheme in which the coefficients in the averages are swapped between two corrections leading to systematically larger amplification factors and to a smaller numerical dispersion.Comment: 7 pages, 3 figure

Tracking TCRß sequence clonotype expansions during antiviral therapy using high-throughput sequencing of the hypervariable region

To maintain a persistent infection viruses such as hepatitis C virus (HCV) employ a range of mechanisms that subvert protective T cell responses. The suppression of antigen-specific T cell responses by HCV hinders efforts to profile T cell responses during chronic infection and antiviral therapy. Conventional methods of detecting antigen-specific T cells utilize either antigen stimulation (e.g., ELISpot, proliferation assays, cytokine production) or antigen-loaded tetramer staining. This limits the ability to profile T cell responses during chronic infection due to suppressed effector function and the requirement for prior knowledge of antigenic viral peptide sequences. Recently, high-throughput sequencing (HTS) technologies have been developed for the analysis of T cell repertoires. In the present study, we have assessed the feasibility of HTS of the TCRβ complementarity determining region (CDR)3 to track T cell expansions in an antigen-independent manner. Using sequential blood samples from HCV-infected individuals undergoing antiviral therapy, we were able to measure the population frequencies of >35,000 TCRβ sequence clonotypes in each individual over the course of 12 weeks. TRBV/TRBJ gene segment usage varied markedly between individuals but remained relatively constant within individuals across the course of therapy. Despite this stable TRBV/TRBJ gene segment usage, a number of TCRβ sequence clonotypes showed dramatic changes in read frequency. These changes could not be linked to therapy outcomes in the present study; however, the TCRβ CDR3 sequences with the largest fold changes did include sequences with identical TRBV/TRBJ gene segment usage and high junction region homology to previously published CDR3 sequences from HCV-specific T cells targeting the HLA-B*0801-restricted 1395HSKKKCDEL1403 and HLA-A*0101-restricted 1435ATDALMTGY1443 epitopes. The pipeline developed in this proof of concept study provides a platform for the design of future experiments to accurately address the question of whether T cell responses contribute to SVR upon antiviral therapy. This pipeline represents a novel technique to analyze T cell dynamics in situations where conventional antigen-dependent methods are limited due to suppression of T cell functions and highly diverse antigenic sequences

Contact transmission of influenza virus between ferrets imposes a looser bottleneck than respiratory droplet transmission allowing propagation of antiviral resistance

Influenza viruses cause annual seasonal epidemics and occasional pandemics. It is important to elucidate the stringency of bottlenecks during transmission to shed light on mechanisms that underlie the evolution and propagation of antigenic drift, host range switching or drug resistance. The virus spreads between people by different routes, including through the air in droplets and aerosols, and by direct contact. By housing ferrets under different conditions, it is possible to mimic various routes of transmission. Here, we inoculated donor animals with a mixture of two viruses whose genomes differed by one or two reverse engineered synonymous mutations, and measured the transmission of the mixture to exposed sentinel animals. Transmission through the air imposed a tight bottleneck since most recipient animals became infected by only one virus. In contrast, a direct contact transmission chain propagated a mixture of viruses suggesting the dose transferred by this route was higher. From animals with a mixed infection of viruses that were resistant and sensitive to the antiviral drug oseltamivir, resistance was propagated through contact transmission but not by air. These data imply that transmission events with a looser bottleneck can propagate minority variants and may be an important route for influenza evolution

Analysis of Magnetic Refrigerators With External Regeneration

The central idea of the magnetic refrigeration systems analyzed in this paper is that of a MR having a regenerator composed of an integral number of separate stages but having only a single magnetic stage. In principle, each stage is thermally isolated from the others, but the stages are accessed by a manifold and valve system which allows gas to flow between the MM and the individual stages. The concept therefore is distinctly unlike that of the unusual continuous regenerator of gas refrigerators. Although a small amount of gas in the manifold is responsible for the actual transfer of heat between elements of the REGMR, it is clear from the cycle description in the caption of Fig. 1 that the fixed mass of the MM is analogous to a fixed mass of a working fluid in a gas refrigerator or engine. Both, in effect, are carried thermally through all parts of their respective systems

Monitoring SO2 emission at the Soufriere Hills Volcano: implications for changes in erruptive conditions

FLWINinfo:eu-repo/semantics/publishe

Feasibility of detecting single atoms using photonic bandgap cavities

We propose an atom-cavity chip that combines laser cooling and trapping of neutral atoms with magnetic microtraps and waveguides to deliver a cold atom to the mode of a fiber taper coupled photonic bandgap (PBG) cavity. The feasibility of this device for detecting single atoms is analyzed using both a semi-classical treatment and an unconditional master equation approach. Single-atom detection seems achievable in an initial experiment involving the non-deterministic delivery of weakly trapped atoms into the mode of the PBG cavity.Comment: 11 pages, 5 figure

Kepler Presearch Data Conditioning II - A Bayesian Approach to Systematic Error Correction

With the unprecedented photometric precision of the Kepler Spacecraft, significant systematic and stochastic errors on transit signal levels are observable in the Kepler photometric data. These errors, which include discontinuities, outliers, systematic trends and other instrumental signatures, obscure astrophysical signals. The Presearch Data Conditioning (PDC) module of the Kepler data analysis pipeline tries to remove these errors while preserving planet transits and other astrophysically interesting signals. The completely new noise and stellar variability regime observed in Kepler data poses a significant problem to standard cotrending methods such as SYSREM and TFA. Variable stars are often of particular astrophysical interest so the preservation of their signals is of significant importance to the astrophysical community. We present a Bayesian Maximum A Posteriori (MAP) approach where a subset of highly correlated and quiet stars is used to generate a cotrending basis vector set which is in turn used to establish a range of "reasonable" robust fit parameters. These robust fit parameters are then used to generate a Bayesian Prior and a Bayesian Posterior Probability Distribution Function (PDF) which when maximized finds the best fit that simultaneously removes systematic effects while reducing the signal distortion and noise injection which commonly afflicts simple least-squares (LS) fitting. A numerical and empirical approach is taken where the Bayesian Prior PDFs are generated from fits to the light curve distributions themselves.Comment: 43 pages, 21 figures, Submitted for publication in PASP. Also see companion paper "Kepler Presearch Data Conditioning I - Architecture and Algorithms for Error Correction in Kepler Light Curves" by Martin C. Stumpe, et a

Mammalian ANP32A and ANP32B proteins drive differential polymerase adaptations in avian influenza virus

ANP32 proteins, which act as influenza polymerase cofactors, vary between birds and mammals. In mammals, ANP32A and ANP32B have been reported to serve essential but redundant roles to support influenza polymerase activity. The well-known mammalian adaptation PB2-E627K enables influenza polymerase to use mammalian ANP32 proteins. However, some mammalian-adapted influenza viruses do not harbor this substitution. Here, we show that alternative PB2 adaptations, Q591R and D701N, also allow influenza polymerase to use mammalian ANP32 proteins, whereas other PB2 mutations, G158E, T271A, and D740N, increase polymerase activity in the presence of avian ANP32 proteins as well. Furthermore, PB2-E627K strongly favors use of mammalian ANP32B proteins, whereas D701N shows no such bias. Accordingly, PB2-E627K adaptation emerges in species with strong pro-viral ANP32B proteins, such as humans and mice, while D701N is more commonly seen in isolates from swine, dogs, and horses, where ANP32A proteins are the preferred cofactor. Using an experimental evolution approach, we show that the passage of viruses containing avian polymerases in human cells drove acquisition of PB2-E627K, but not in the absence of ANP32B. Finally, we show that the strong pro-viral support of ANP32B for PB2-E627K maps to the low-complexity acidic region (LCAR) tail of ANP32B. IMPORTANCE Influenza viruses naturally reside in wild aquatic birds. However, the high mutation rate of influenza viruses allows them to rapidly and frequently adapt to new hosts, including mammals. Viruses that succeed in these zoonotic jumps pose a pandemic threat whereby the virus adapts sufficiently to efficiently transmit human-to-human. The influenza virus polymerase is central to viral replication and restriction of polymerase activity is a major barrier to species jumps. ANP32 proteins are essential for influenza polymerase activity. In this study, we describe how avian influenza viruses can adapt in several different ways to use mammalian ANP32 proteins. We further show that differences between mammalian ANP32 proteins can select different adaptive changes and are responsible for some of the typical mutations that arise in mammalian-adapted influenza polymerases. These different adaptive mutations may determine the relative zoonotic potential of influenza viruses and thus help assess their pandemic risk