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A cylindrically symmetric (azimuthal mode number m=0) resonant inductive (MO/RITM) radio frequency (rf) helicon wave high density plasma source is described. The source consists of an antenna and bell jar generator immersed in a diverging magnetic field. Plasma is generated in this upstream region and then is transported along the field lines into the low-field downstream processing chamber. A propagating wave is observed in the plasma with rf spatial distribution and propagation characteristics that obey the theoretical m=0 helicon wave dispersion relation. By varying the divergence of the source magnetic field, the wafer etch rate and etch uniformity can be controlled. Spatially resolved optical emission spectroscopy shows that molecular gases are almost completely dissociated near the plasma center and have a uniform radial distribution. Highly uniform plasma and neutral distributions are then produced at the wafer location, and have been used in a variety of etch applications.

Motivation Nucleotides modification status can be decoded from the Oxford Nanopore Technologies (ONT) nanopore sequencing ionic current signals. Although various algorithms have been developed for nanopore sequencing-based modification analysis, more detailed characterizations, such as modification numbers, corresponding signal levels and proportions are still lacking. Results We present a framework for the unsupervised determination of the number of nucleotide modifications from nanopore sequencing readouts. We demonstrate the approach can effectively recapitulate the number of modifications, the corresponding ionic current signal levels, as well as mixing proportions under both DNA and RNA contexts. We further show, by integrating information from multiple detected modification regions, that the modification status of DNA and RNA molecules can be inferred. This method forms a key step of de novo characterization of nucleotide modifications, shedding light on the interpretation of various biological questions. Availability Modified nanopolish: https://github.com/adbailey4/nanopolish/tree/cigar_output. All other codes used to reproduce the results: https://github.com/hd2326/ModificationNumber. Supplementary information Supplementary data are available at Bioinformatics online.

Effective electric field in dc magnetization measurements: Comparing magnetization to transport critical currents

This paper presents a maximum entropy framework for the aggregation of expert opinions where the expert opinions concern the prediction of the outcome of an uncertain event. The event to be predicted and individual predictions rendered are assumed to be discrete random variables. A measure of expert competence is defined using a distance metric between the actual outcome of the event and each expert's predicted outcome. Following Levy and Delic (Levy, W. B., H. Delic. 1994. Maximum entropy aggregation of individual opinions. IEEE Trans. Sys. Man & Cybernetics 24 606--613.), we use Shannon's information measure (Shannon [Shannon, C. E. 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27 379--423.], Jaynes [Jaynes, E. T. 1957. Information theory and statistical mechanics. Phys. Rev. 106 Part I: 620--630, 108 Part II: 171--190.]) to derive aggregation rules for combining two or more expert predictions into a single aggregated prediction that appropriately calibrates different degrees of expert competence and reflects any dependence that may exist among the expert predictions. The resulting maximum entropy aggregated prediction is least prejudiced in the sense that it utilizes all information available but remains maximally non committal with regard to information not available. Numerical examples to illuminate the implications of maximum entropy aggregation are also presented.consensus, expert opinion, maximum entropy, aggregation, information theory, decision aids