Scintillator-based ion beam profiler for diagnosing laser-accelerated ion beams

Next generation intense, short-pulse laser facilities require new high repetition rate diagnostics for the detection of ionizing radiation. We have designed a new scintillator-based ion beam profiler capable of measuring the ion beam transverse profile for a number of discrete energy ranges. The optical response and emission characteristics of four common plastic scintillators has been investigated for a range of proton energies and fluxes. The scintillator light output (for 1 MeV > Ep < 28 MeV) was found to have a non-linear scaling with proton energy but a linear response to incident flux. Initial measurements with a prototype diagnostic have been successful, although further calibration work is required to characterize the total system response and limitations under the high flux, short pulse duration conditions of a typical high intensity laser-plasma interaction

Learning to Fix Build Errors with Graph2Diff Neural Networks

Professional software developers spend a significant amount of time fixing builds, but this has received little attention as a problem in automatic program repair. We present a new deep learning architecture, called Graph2Diff, for automatically localizing and fixing build errors. We represent source code, build configuration files, and compiler diagnostic messages as a graph, and then use a Graph Neural Network model to predict a diff. A diff specifies how to modify the code’s abstract syntax tree, represented in the neural network as a sequence of tokens and of pointers to code locations. Our network is an instance of a more general abstraction which we call Graph2Tocopo, which is potentially useful in any development tool for predicting source code changes. We evaluate the model on a dataset of over 500k real build errors and their resolutions from professional developers. Compared to the approach of DeepDelta [23], our approach tackles the harder task of predicting a more precise diff but still achieves over double the accuracy

Learning to Fix Build Errors with Graph2Diff Neural Networks

Professional software developers spend a significant amount of time fixing builds, but this has received little attention as a problem in automatic program repair. We present a new deep learning architecture, called Graph2Diff, for automatically localizing and fixing build errors. We represent source code, build configuration files, and compiler diagnostic messages as a graph, and then use a Graph Neural Network model to predict a diff. A diff specifies how to modify the code’s abstract syntax tree, represented in the neural network as a sequence of tokens and of pointers to code locations. Our network is an instance of a more general abstraction which we call Graph2Tocopo, which is potentially useful in any development tool for predicting source code changes. We evaluate the model on a dataset of over 500k real build errors and their resolutions from professional developers. Compared to the approach of DeepDelta [23], our approach tackles the harder task of predicting a more precise diff but still achieves over double the accuracy

Environmentally friendly analysis of emerging contaminants by pressurized hot water extraction-stir bar sorptive extraction-derivatization and gas chromatography-mass spectrometry

This work describes the development, optimiza- tion, and validation of a new method for the simultaneous determination of a wide range of pharmaceuticals (beta- blockers, lipid regulators ... ) and personal care products (fragrances, UV filters, phthalates ... ) in both aqueous and solid environmental matrices. Target compounds were extracted from sediments using pressurized hot water ex- traction followed by stir bar sorptive extraction. The first stage was performed at 1,500 psi during three static extrac- tion cycles of 5 min each after optimizing the extraction temperature (50 – 150 °C) and addition of organic modifiers (% methanol) to water, the extraction solvent. Next, aqueous extracts and water samples were processed using polydime- thylsiloxane bars. Several parameters were optimized for this technique, including extraction and desorption time, ionic strength, presence of organic modifiers, and pH. Fi- nally, analytes were extracted from the bars by ultrasonic irradiation using a reduced amount of solvent (0.2 mL) prior to derivatization and gas chromatography – mass spectrome- try analysis. The optimized protocol uses minimal amounts of organic solvents (<10 mL/sample) and time ( ≈ 8 h/sam- ple) compared to previous ex isting methodologies. Low standard deviation (usually below 10 %) and limits of de- tection (sub-ppb) vouch for the applicability of the method- ology for the analysis of target compounds at trace levels. Once developed, the method was applied to determin

Stratorotational instability in MHD Taylor-Couette flows

The stability of dissipative Taylor-Couette flows with an axial stable density stratification and a prescribed azimuthal magnetic field is considered. Global nonaxisymmetric solutions of the linearized MHD equations with toroidal magnetic field, axial density stratification and differential rotation are found for both insulating and conducting cylinder walls. Flat rotation laws such as the quasi-Kepler law are unstable against the nonaxisymmetric stratorotational instability (SRI). The influence of a current-free toroidal magnetic field depends on the magnetic Prandtl number Pm: SRI is supported by Pm > 1 and it is suppressed by Pm \lsim 1. For too flat rotation laws a smooth transition exists to the instability which the toroidal magnetic field produces in combination with the differential rotation. This nonaxisymmetric azimuthal magnetorotational instability (AMRI) has been computed under the presence of an axial density gradient. If the magnetic field between the cylinders is not current-free then also the Tayler instability occurs and the transition from the hydrodynamic SRI to the magnetic Tayler instability proves to be rather complex. Most spectacular is the `ballooning' of the stability domain by the density stratification: already a rather small rotation stabilizes magnetic fields against the Tayler instability. An azimuthal component of the resulting electromotive force only exists for density-stratified flows. The related alpha-effect for magnetic SRI of Kepler rotation appears to be positive for negative d\rho/dz <0.Comment: 10 pages, 13 figures, submitted to Astron. Astrophy

Multilevel Deconstruction of the In Vivo Behavior of Looped DNA-Protein Complexes

Protein-DNA complexes with loops play a fundamental role in a wide variety of cellular processes, ranging from the regulation of DNA transcription to telomere maintenance. As ubiquitous as they are, their precise in vivo properties and their integration into the cellular function still remain largely unexplored. Here, we present a multilevel approach that efficiently connects in both directions molecular properties with cell physiology and use it to characterize the molecular properties of the looped DNA-lac repressor complex while functioning in vivo. The properties we uncover include the presence of two representative conformations of the complex, the stabilization of one conformation by DNA architectural proteins, and precise values of the underlying twisting elastic constants and bending free energies. Incorporation of all this molecular information into gene-regulation models reveals an unprecedented versatility of looped DNA-protein complexes at shaping the properties of gene expression.Comment: Open Access article available at http://www.plosone.org/article/fetchArticle.action?articleURI=info%3Adoi%2F10.1371%2Fjournal.pone.000035

Stress related epigenetic changes may explain opportunistic success in biological invasions in Antipode mussels

Different environmental factors could induce epigenetic changes, which are likely involved in the biological invasion process. Some of these factors are driven by humans as, for example, the pollution and deliberate or accidental introductions and others are due to natural conditions such as salinity. In this study, we have analysed the relationship between different stress factors: time in the new location, pollution and salinity with the methylation changes that could be involved in the invasive species tolerance to new environments. For this purpose, we have analysed two different mussels’ species, reciprocally introduced in antipode areas: the Mediterranean blue mussel Mytilus galloprovincialis and the New Zealand pygmy mussel Xenostrobus securis, widely recognized invaders outside their native distribution ranges. The demetylathion was higher in more stressed population, supporting the idea of epigenetic is involved in plasticity process. These results can open a new management protocols, using the epigenetic signals as potential pollution monitoring tool. We could use these epigenetic marks to recognise the invasive status in a population and determine potential biopollutants

Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

Методи управління екологічними ризиками в системі забезпечення економічного розвитку регіону

Метою статті є дослідження методів управління екологічними ризиками в системі забезпечення економічного розвитку регіону