Turbulence Measurements in Submerged Water Jets by Electromagnetic Induction Anemometry

This paper describes the measurement and data analysis of the turbulence in a two-dimensional water jet discharging from a thin slot into a large body of stationary water having the same width as the slot. Tap water without additives was used as the flow medium. The electromagnetic induction method (commonly known as magnetohydrodynamics, or the MHD method) was used to sense the fluctuation velocities in the diffusion zone of the jet. A DC magnet was placed outside the flow field with the magnetic flux density of 885 Gauss perpendicular to the plane of homogeneity of the two-dimensional flow field. A small probe in the flow field sensed voltage changes due to the turbulent velocities. The induced voltages picked up at the electrodes were fed into a high input 12 impedance (about 10 ohms) differential amplifier. The output from the amplifier was recorded on tape which was later read into a hybrid computer for analyzing the variances, autocorrelation and spectrum of the turbulence signal. Turbulent velocities induce fluctuating electric potentials everywhere in the flow field whenever a magnetic flux is present, and hence set up fluctuating currents between any two points of different potentials. These currents have an equalizing effect on the induced voltage, thus causing the differential fluctuating voltage sensed by the electrodes in a turbulent flow to be less than the true value. The voltage reduction effect was experimentally determined to be a constant value by comparing the measured variance of turbulence in a water jet by the MHD method with the variance in an air jet using hot-wire anemometry. The constant reduction factor should have no effect on the normalized autocorrelation and spectrum results of the water jet

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models.

Knowing the catalytic turnover numbers of enzymes is essential for understanding the growth rate, proteome composition, and physiology of organisms, but experimental data on enzyme turnover numbers is sparse and noisy. Here, we demonstrate that machine learning can successfully predict catalytic turnover numbers in Escherichia coli based on integrated data on enzyme biochemistry, protein structure, and network context. We identify a diverse set of features that are consistently predictive for both in vivo and in vitro enzyme turnover rates, revealing novel protein structural correlates of catalytic turnover. We use our predictions to parameterize two mechanistic genome-scale modelling frameworks for proteome-limited metabolism, leading to significantly higher accuracy in the prediction of quantitative proteome data than previous approaches. The presented machine learning models thus provide a valuable tool for understanding metabolism and the proteome at the genome scale, and elucidate structural, biochemical, and network properties that underlie enzyme kinetics

The NASA/IPAC Infrared Science Archive (IRSA): The Demo

This paper describes the services available at the NASA/IPAC Infrared Science Archive (IRSA). Currently there are nearly 250,000 data requests a month, taking advantage of IRSA's data repository which includes 660 million sources (60 catalogs), 10 million images (22 image sets; 10.4 TB) and over 30,000 spectra (7 spectroscopic datasets). These data are the science products of: The Two Micron All Sky Survey (2MASS), The Infrared Astronomical Satellite (IRAS), The Midcourse Space Experiment (MSX), The Submillimeter Wave Astronomy Satellite (SWAS), The Infrared Space Observatory (ISO), The Infrared Telescope in Space (IRTS), The Spitzer First Look Survey (FLS), Spitzer Legacy & Ancillary data, Spitzer Reserved Observations (ROC) and the Spitzer Space Telescope data. IRSA is also seamlessly interoperable with ten remote archives and services: GOODS, ISO, MAST, VizieR, DSS, NVSS, FIRST, HEASARC, NED and JPL, which help expand the available dataset wavelength range from X-ray to radio. The majority of IRSA's image collections are Simple Image Access (SIA) compliant and are available through the Virtual Observatory (VO) data mining tools. The IRSA demo includes IRSA's ¯ve main services: inventory service RADAR, catalog query service Gator, data fusion service OASIS, general search service for complex data collections Atlas, and IRSA's 2MASS Image data access services. IRSA's website is http://irsa.ipac.caltech.edu

New trajectories of the Hungarian regional development: balanced and rush growth of territorial capital

The basic assumption of the paper is that numerous similarities exist between the patterns of economic growth and territorial capital growth. The rush economic growth and rush growth of territorial capital are compared empirically at Hungarian micro-regional level from 2004 until 2010. After normalizing the dataset, a very novel spatial econometric method is applied, called a penalty for bottleneck. The results show that the constant rush growth of territorial capital is as harmful as economic recession. On the other hand, the decrease of infrastructural and social capital caused the rush growth of territorial capital in this period. Moreover, the key findings of two case studies suggest that the balanced growth of territorial capital will be created by the falling social inequalities and increasing infrastructural capita

Oldest Known Eucalyptus Macrofossils Are from South America

The evolutionary history of Eucalyptus and the eucalypts, the larger clade of seven genera including Eucalyptus that today have a natural distribution almost exclusively in Australasia, is poorly documented from the fossil record. Little physical evidence exists bearing on the ancient geographical distributions or morphologies of plants within the clade. Herein, we introduce fossil material of Eucalyptus from the early Eocene (ca. 51.9 Ma) Laguna del Hunco paleoflora of Chubut Province, Argentina; specimens include multiple leaves, infructescences, and dispersed capsules, several flower buds, and a single flower. Morphological similarities that relate the fossils to extant eucalypts include leaf shape, venation, and epidermal oil glands; infructescence structure; valvate capsulate fruits; and operculate flower buds. The presence of a staminophore scar on the fruits links them to Eucalyptus, and the presence of a transverse scar on the flower buds indicates a relationship to Eucalyptus subgenus Symphyomyrtus. Phylogenetic analyses of morphological data alone and combined with aligned sequence data from a prior study including 16 extant eucalypts, one outgroup, and a terminal representing the fossils indicate that the fossils are nested within Eucalyptus. These are the only illustrated Eucalyptus fossils that are definitively Eocene in age, and the only conclusively identified extant or fossil eucalypts naturally occurring outside of Australasia and adjacent Mindanao. Thus, these fossils indicate that the evolution of the eucalypt group is not constrained to a single region. Moreover, they strengthen the taxonomic connections between the Laguna del Hunco paleoflora and extant subtropical and tropical Australasia, one of the three major ecologic-geographic elements of the Laguna del Hunco paleoflora. The age and affinities of the fossils also indicate that Eucalyptus subgenus Symphyomyrtus is older than previously supposed. Paleoecological data indicate that the Patagonian Eucalyptus dominated volcanically disturbed areas adjacent to standing rainforest surrounding an Eocene caldera lake