Design of plasma shutters for improved heavy ion acceleration by ultra-intense laser pulses

In this work, we investigate the application of the plasma shutters for heavy ion acceleration driven by a high-intensity laser pulse. We use particle-in-cell (PIC) and hydrodynamic simulations. The laser pulse, transmitted through the opaque shutter, gains a steep-rising front and its peak intensity is locally increased at the cost of losing part of its energy. These effects have a direct influence on subsequent ion acceleration from the ultrathin target behind the shutter. In our 3D simulations of silicon nitride plasma shutter and a silver target, the maximal energy of high-Z ions increases significantly when the shutter is included for both linearly and circularly polarized laser pulses. Moreover, application of the plasma shutter for linearly polarized pulse results in focusing of ions towards the laser axis in the plane perpendicular to the laser polarization. The generated high energy ion beam has significantly lower divergence compared to the broad ion cloud, generated without the shutter. The effects of prepulses are also investigated assuming a double plasma shutter. The first shutter can withstand the assumed sub-ns prepulse (treatment of ns and ps prepulses by other techniques is assumed) and the pulse shaping occursvia interaction with the second shutter. On the basis of our theoretical findings, we formulated an approach towards designing a double plasma shutter for high-intensity and high-power laser pulses and built a prototype.Comment: 30 pages 13 figure

СОСТАВ И СВОЙСТВА ПОВЕРХНОСТНЫХ СЛОЕВ, ФОРМИРУЕМЫХ ИОННО-АССИСТИРУЕМЫМ ОСАЖДЕНИЕМ КАТАЛИТИЧЕСКИХ МЕТАЛЛОВ ИЗ ПЛАЗМЫ ВАКУУМНОГО ДУГОВОГО РАЗРЯДА НА УГЛЕРОДНЫЕ ПОДЛОЖКИ

Surface layers were prepared by ion beam-assisted deposition (IBAD) of platinum and rare earth metals (Ce, Yb) on the carbon-based Toray Carbon Fiber Paper TGP-H-060 T catalyst support in effort to produce electrocatalysts for direct methanol and ethanol oxidation fuel cells (DMFC, DEFC) with polymer electrolyte membrane. The layer formation in the IBAD mode, by means of the metal deposition and the mixing of a precipitating layer with the substrate by accelerated (U = 10 kV) ions of the same metal, was carried out. In this process, a neutral fraction of metal vapor and ionized plasma of vacuum pulsed electric arc was used. The study of morphology and composition of the layers was performed by scanning electron microscopy and electron probe microanalysis, X-ray fluorescence analysis and Rutherford backscattering spectrometry. Properties of the prepared electrocatalysts were investigated by cyclic voltammetry. It was established that the prepared electrocatalysts show their activity in the processes of electrochemical methanol and ethanol oxidation. Поверхностные слои сформированы ионноассистируемым осаждением (IBAD) платины и редкоземельных металлов (Ce, Yb) на носитель Toray Carbon Fiber Paper TGP-H-060 Т с целью получения электрокатализаторов для топливных элементов прямого окисления метанола и этанола с полимерным мембранным электролитом. Формирование слоев проведено в режиме IBAD, при котором осаждение металла и перемешивание осаждаемого слоя с атомами поверхности подложки ускоренными (U = 10 кВ) ионами того же металла осуществляются соответственно из нейтральной фракции пара и плазмы вакуумного дугового разряда импульсного электродугового ионного источника. Исследование морфологии и состава слоев проведено методами сканирующей электронной микроскопии и электронно-зондового микроанализа, рентгеновского флуоресцентного анализа и спектрометрии резерфордовского обратного рассеяния. Свойства электрокатализаторов исследовались методом циклической вольтамперометрии. Получаемые электрокатализаторы проявляют активность в процессах окисления метанола и этанола.

Analysis of computational approaches for motif discovery

Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechnology, Jan. 2005). This paper contains follow-up analysis of the assessment results, and raises and discusses some important issues concerning the state of the art in motif discovery methods: 1. We categorize the objective functions used by existing tools, and design experiments to evaluate whether any of these objective functions is the right one to optimize. 2. We examine various features of the data sets that were used in the assessment, such as sequence length and motif degeneracy, and identify which features make data sets hard for current motif discovery tools. 3. We identify an important feature that has not yet been used by existing tools and propose a new objective function that incorporates this feature

Защитные свойства Zr-содержащих конверсионных покрытий на цинке

The aim of the study is to develop an environmentally friendly chromium-free passivation technology for galvanized steel. Passivation of zinc coatings was carried out by deposition of conversion coatings from solutions containing ZrO(NO3)2, Na2SiF6 and oxidizer H2O2 or K2S2O8. The effect of the solution pH, the concentration of Na2SiF6 and the type of oxidizer on the protective properties of coatings was studied by the drop method and electrochemical method of linear voltammetry in 3 % NaCl using the full factor experiment 23 . The main effects and effects of the interaction of the studied factors for the darkening time of the droplet and the dissolution potential of zinc are calculated. The solution pH in the presence of the oxidizing agent K2S2O8 influences the both parameters in the most extent. Concentration of Na2SiF6 has a significant effect on the dissolution potential of zinc and the least effect on the darkening time of the droplet. An increase in the solution pH and the concentration of Na2SiF6 increases the protective properties of the coatings. Measurements of the mass loss and open circuit potential during the resource testing of conversion coatings in 3% NaCl showed an increase in the corrosion rate over time.Цель исследования − разработка экологически безопасной бесхромовой технологии пассивации гальванически оцинкованной стали. Пассивация гальванических цинковых покрытий проводилась осаждением на них конверсионных покрытий из растворов, содержащих ZrO(NO3)2, Na2SiF6 и окислитель H2O2 или K2S2O8. Изучалось влияние pH раствора, концентрации Na2SiF6 и типа окислителя на показатели защитных свойств покрытий методом капли и электрохимическим методом линейной вольтамперометрии в 3 %-ном NaCl с использованием полного факторного эксперимента 23 . Рассчитаны главные эффекты и эффекты взаимодействия исследованных факторов для времени потемнения капли и потенциала растворения цинка. Наибольшее влияние на оба показателя оказывает pH раствора в присутствии окислителя K2S2O8. Концентрация Na2SiF6 оказывает значительное влияние на потенциал растворения цинка и наименьшее влияние на время потемнения капли. Увеличение pH раствора и концентрации Na2SiF6 увеличивает показатели защитных свойств покрытий. Измерения потери массы и потенциала разомкнутой цепи в процессе ресурсных испытаний конверсионных покрытий в 3 %-ном NaCl показали возрастание скорости коррозии со временем

Коррозионная стойкость горячеоцинкованной стали в хлоридсодержащей среде

Today, corrosion and corrosion protection of metals are the most important scientific, technical, economic and environmental problems. The effect of additions of sodium molybdate, ammonium metavanadate, a mixture of sodium molybdate and ammonium metavanadate, thiourea and sodium orthophosphate on the corrosive behavior of hot-dip galvanized steel in a neutral and slightly alkaline chloride-containing medium has been studied. The experimental results obtained by weight and electrochemical methods proved sodium molybdate, ammonium metavanadate, a mixture of sodium molybdate and ammonium metavanadate, thiourea and sodium orthophosphate to be corrosion inhibitors that slow down the rate of destruction of hot-dip galvanized steel in a neutral and slightly alkaline chloride-containing medium by 1.5–11 times.Коррозия и защита металлов от коррозии по-прежнему остаются важнейшими научно-техническими, экономическими и экологическими задачами. В работе изучено влияние добавок молибдата натрия, метаванадата аммония, смеси молибдата натрия и метаванадата аммония, тиомочевины, ортофосфата натрия на коррозионное поведение горячеоцинкованной стали в нейтральной и слабощелочной хлоридсодержащей среде. Полученные весовым и электрохимическими методами экспериментальные результаты показали, что молибдат натрия, метаванадат аммония, смесь молибдата натрия и метаванадата аммония, тиомочевина, ортофосфат натрия проявляют ингибирующие свойства, уменьшая скорость коррозии горячеоцинкованной стали в нейтральной и слабощелочной хлоридсодержащей среде в 1,5–11 раз

A Bayesian Search for Transcriptional Motifs

Identifying transcription factor (TF) binding sites (TFBSs) is an important step towards understanding transcriptional regulation. A common approach is to use gaplessly aligned, experimentally supported TFBSs for a particular TF, and algorithmically search for more occurrences of the same TFBSs. The largest publicly available databases of TF binding specificities contain models which are represented as position weight matrices (PWM). There are other methods using more sophisticated representations, but these have more limited databases, or aren't publicly available. Therefore, this paper focuses on methods that search using one PWM per TF. An algorithm, MATCHTM, for identifying TFBSs corresponding to a particular PWM is available, but is not based on a rigorous statistical model of TF binding, making it difficult to interpret or adjust the parameters and output of the algorithm. Furthermore, there is no public description of the algorithm sufficient to exactly reproduce it. Another algorithm, MAST, computes a p-value for the presence of a TFBS using true probabilities of finding each base at each offset from that position. We developed a statistical model, BaSeTraM, for the binding of TFs to TFBSs, taking into account random variation in the base present at each position within a TFBS. Treating the counts in the matrices and the sequences of sites as random variables, we combine this TFBS composition model with a background model to obtain a Bayesian classifier. We implemented our classifier in a package (SBaSeTraM). We tested SBaSeTraM against a MATCHTM implementation by searching all probes used in an experimental Saccharomyces cerevisiae TF binding dataset, and comparing our predictions to the data. We found no statistically significant differences in sensitivity between the algorithms (at fixed selectivity), indicating that SBaSeTraM's performance is at least comparable to the leading currently available algorithm. Our software is freely available at: http://wiki.github.com/A1kmm/sbasetram/building-the-tools

Statistical Modeling of Transcription Factor Binding Affinities Predicts Regulatory Interactions

Recent experimental and theoretical efforts have highlighted the fact that binding of transcription factors to DNA can be more accurately described by continuous measures of their binding affinities, rather than a discrete description in terms of binding sites. While the binding affinities can be predicted from a physical model, it is often desirable to know the distribution of binding affinities for specific sequence backgrounds. In this paper, we present a statistical approach to derive the exact distribution for sequence models with fixed GC content. We demonstrate that the affinity distribution of almost all known transcription factors can be effectively parametrized by a class of generalized extreme value distributions. Moreover, this parameterization also describes the affinity distribution for sequence backgrounds with variable GC content, such as human promoter sequences. Our approach is applicable to arbitrary sequences and all transcription factors with known binding preferences that can be described in terms of a motif matrix. The statistical treatment also provides a proper framework to directly compare transcription factors with very different affinity distributions. This is illustrated by our analysis of human promoters with known binding sites, for many of which we could identify the known regulators as those with the highest affinity. The combination of physical model and statistical normalization provides a quantitative measure which ranks transcription factors for a given sequence, and which can be compared directly with large-scale binding data. Its successful application to human promoter sequences serves as an encouraging example of how the method can be applied to other sequences

Transcriptional Autoregulatory Loops Are Highly Conserved in Vertebrate Evolution

BACKGROUND: Feedback loops are the simplest building blocks of transcriptional regulatory networks and therefore their behavior in the course of evolution is of prime interest. METHODOLOGY: We address the question of enrichment of the number of autoregulatory feedback loops in higher organisms. First, based on predicted autoregulatory binding sites we count the number of autoregulatory loops. We compare it to estimates obtained either by assuming that each (conserved) gene has the same chance to be a target of a given factor or by assuming that each conserved sequence position has an equal chance to be a binding site of the factor. CONCLUSIONS: We demonstrate that the numbers of putative autoregulatory loops conserved between human and fugu, danio or chicken are significantly higher than expected. Moreover we show, that conserved autoregulatory binding sites cluster close to the factors' starts of transcription. We conclude, that transcriptional autoregulatory feedback loops constitute a core transcriptional network motif and their conservation has been maintained in higher vertebrate organism evolution

A ChIP-Seq Benchmark Shows That Sequence Conservation Mainly Improves Detection of Strong Transcription Factor Binding Sites

Transcription factors are important controllers of gene expression and mapping transcription factor binding sites (TFBS) is key to inferring transcription factor regulatory networks. Several methods for predicting TFBS exist, but there are no standard genome-wide datasets on which to assess the performance of these prediction methods. Also, it is believed that information about sequence conservation across different genomes can generally improve accuracy of motif-based predictors, but it is not clear under what circumstances use of conservation is most beneficial.Here we use published ChIP-seq data and an improved peak detection method to create comprehensive benchmark datasets for prediction methods which use known descriptors or binding motifs to detect TFBS in genomic sequences. We use this benchmark to assess the performance of five different prediction methods and find that the methods that use information about sequence conservation generally perform better than simpler motif-scanning methods. The difference is greater on high-affinity peaks and when using short and information-poor motifs. However, if the motifs are specific and information-rich, we find that simple motif-scanning methods can perform better than conservation-based methods.Our benchmark provides a comprehensive test that can be used to rank the relative performance of transcription factor binding site prediction methods. Moreover, our results show that, contrary to previous reports, sequence conservation is better suited for predicting strong than weak transcription factor binding sites