Optical and infrared spectrophotometry of 18 Markarian galaxies

Slit spectra, spectrophotometric scans and infrared broad band observations are presented. Eight of the program galaxies can be classified as Seyfert galaxies. Arguments are given that thermal, nonthermal and stellar radiation components were present. One group of Seyfert galaxies was characterized both by the presence of a high density region of gas and by a continuum dominated by nonthermal radiation. The continua of the remaining program Seyferts, which did not have a high density region of gas, were dominated by thermal radiation from dust and a stellar continuum. Ten of the galaxies, which are not Seyfert galaxies, are shown to be examples of extragalactic H 2 regions

Star counts in NGC 6397

I-band CCD images of a large area of the nearby globular cluster NGC~6397 have been used to construct a surface density profile and two luminosity and mass functions. The surface density profile extends out to 14\arcm from the cluster center and shows no sign of a tidal cutoff. The inner profile is a power-law with slope -0.8 steepening to -1.7 outside of 1\arcm. The mass functions are for fields at 4\arcm\ and 11\arcm from the cluster center and confirm the upturn in the mass function for stars less massive than about 0.4 M\solar. There appears to be an excess of low-mass stars over higher-mass stars in the outer field with respect to the inner, in qualitative agreement with expectations for mass segregation.Comment: 16 pages + 7 pages of tables, LaTeX using AASTeX macros, 11 figures available by request, IoA preprin

The age of data-driven proteomics : how machine learning enables novel workflows

A lot of energy in the field of proteomics is dedicated to the application of challenging experimental workflows, which include metaproteomics, proteogenomics, data independent acquisition (DIA), non-specific proteolysis, immunopeptidomics, and open modification searches. These workflows are all challenging because of ambiguity in the identification stage; they either expand the search space and thus increase the ambiguity of identifications, or, in the case of DIA, they generate data that is inherently more ambiguous. In this context, machine learning-based predictive models are now generating considerable excitement in the field of proteomics because these predictive models hold great potential to drastically reduce the ambiguity in the identification process of the above-mentioned workflows. Indeed, the field has already produced classical machine learning and deep learning models to predict almost every aspect of a liquid chromatography-mass spectrometry (LC-MS) experiment. Yet despite all the excitement, thorough integration of predictive models in these challenging LC-MS workflows is still limited, and further improvements to the modeling and validation procedures can still be made. In this viewpoint we therefore point out highly promising recent machine learning developments in proteomics, alongside some of the remaining challenges

Estimation Of Fluid Loading On Offshore Structures

This paper is a working guide to methods and associated data for estimating loading on offshore structures due to waves and currents. Its primary concern is with existing practice in which the formula known as Morison' s equation is extensively used but some attention is given to diffraction theory methods now quite widely adopted for large monolithic types of structure and a section on the influence of marine roughness on loading is included. Regarding Morison's equation, a comprehensive review of published data on the relevant coefficients is presented, stressing the considerable uncertainties which still exist in some areas but offering advice on the best values to be used in the light of current knowledge, systematically documented by references to the corresponding data sources. Other important questions discussed include selection of appropriate wave theories and associated particle kinematics, the effects on fluid loading of proximity and inclination of structural members and the special problems of estimating impact or 'slamming' forces. The section on diffraction theory analysis discusses the interpretation of the results for both fixed and moving bodies and problems of practical application. It also reviews published information on both analytical and numerical solutions including comments on reliability and experimental validation and tabular summaries of the capabilities of an extensive range of methods and computer programs already available. In discussing marine roughness recent published data indicating the substantial effects which it can have on drag coefficients in both waves and currents are reviewed and advice is given on how these should be estimated. A general conclusion of the paper is that although data on fluid loading available in the literature is very plentiful there are still many serious uncertainties and gaps in knowledge. It is therefore important that research should continue with emphasis on the need for more reliable data from large scale structures in the real environment

Atomic Beams

Contains research objectives and reports on five research projects.Lincoln Laboratory, Purchase Order DDL-B222Department of the ArmyDepartment of the NavyDepartment of the Air Force under Contract AF19(122)-45

Comparison of data on Mutation Frequencies of Mice Caused by Radiation - Low Dose Model -

We propose LD(Low Dose) model, the extension of LDM model which was proposed in the previous paper [Y. Manabe et al.: J. Phys. Soc. Jpn. 81 (2012) 104004] to estimate biological damage caused by irradiation. LD model takes account of all the considerable effects including cell death effect as well as proliferation, apoptosis, repair. As a typical example of estimation, we apply LD model to the experiment of mutation frequency on the responses induced by the exposure to low levels of ionizing radiation. The most famous and extensive experiments are those summarized by Russell and Kelly [Russell, W. L. & Kelly, E. M: Proc. Natl Acad. Sci. USA 79 (1982) 539-541], which are known as 'Mega-mouse project'. This provides us with important information of the frequencies of transmitted specific-locus mutations induced in mouse spermatogonia stem-cells. It is found that the numerical results of the mutation frequency of mice are in reasonable agreement with the experimental data: the LD model reproduces the total dose and dose rate dependence of data reasonably. In order to see such dose-rate dependence more explicitly, we introduce the dose-rate effectiveness factor (DREF). This represents a sort of preventable effects such as repair, apoptosis and death of broken cells, which are to be competitive with proliferation effect of broken cells induced by irradiation.Comment: subimitting to J. Phys. Soc. Jpn, 32 pages, 8 figure

Report on an all-sky LIGO search for periodic gravitational waves in the S4 data

We report on an all-sky search with the LIGO detectors for periodic gravitational waves in the frequency range 50-1000 Hz and having a negative frequency time derivative with magnitude between zero and $10^{-8}$ Hz/s. Data from the fourth LIGO science run have been used in this search. Three different semi-coherent methods of summing strain power were applied. Observing no evidence for periodic gravitational radiation, we report upper limits on strain amplitude and interpret these limits to constrain radiation from rotating neutron stars.Comment: 5 pages, 1 figure, presented at Amaldi7, Sydney (July 2007