gebhart/patrepeval huggingface dataset:
Angular Confinement of Field Electron and Ion Emission (1969)

Three methods of confining the angular dispersion of a field electron beam from 〈100〉 oriented tungsten emitters are investigated; they are (1) thermal-field buildup, (2) selective work function reduction by zirconium adsorption, and (3) high-temperature field evaporation. All three methods confine the emission to a beam half-angle of less than 9° in the dc current range 0.1 to 100 μA. Method (1) results in a ∼50% reduction in beam voltage. Provided that the vacuum level is good (∼10−10 Torr), long and short term current instabilities are negligible for dc current levels below 10 μA at 300°K for each of the emitter end forms investigated. The angular dispersion and beam voltage of a field ion beam can also be reduced by method (1) as described briefly in this paper.
Uncertainties in altimetry‐based velocity estimates (2002)

Three methods to estimate ocean geostrophic surface currents from satellite altimetry measurements are evaluated for several single‐ and multiple‐satellite configurations, with specific emphasis on resulting uncertainties. Altimetric sea surface height measurements are simulated by sampling along satellite ground tracks the surface pressure output from the 1/10° North Atlantic run of the Los Alamos Parallel Ocean Program model and by subsequently adding realistic instrument and orbit errors. The effects of both sampling and data errors on the velocity estimates are discussed. The satellite orbit configurations considered represent current missions or candidates for future coordinated tandem missions. Data error budgets are based on those of existing missions and on estimates for new altimetric technology currently under development. In midlatitude regions characterized by strong variability, such as the Gulf Stream region, velocities estimated at crossovers of interleaved tracks, and along a virtual ground track between two parallel tracks with a 0.75° zonal offset, are found to be comparable in accuracy and more accurate than velocities estimated from optimally interpolated sea surface height maps. Error variances as low as 15–25% of the local signal variance can be obtained from all three methods near the Gulf Stream core. Larger relative errors are found almost everywhere else with the exact details of the error in the two velocity components depending on data error, orbit configuration, latitude, estimation method, and smoothing. Several scientific applications of the configurations and methods are discussed, including the estimation of Reynolds stresses, momentum fluxes, velocity spectra, and covariance functions. Accuracy and applicability suggest that the newly proposed parallel track configuration is a viable option for future tandem missions.
Eddy current imager based on bobbin-type hall sensor arrays for nondestructive evaluation in small-bore piping system (2013)

A bobbin coil with bobbin-type solid-state Hall sensor arrays was proposed for eddy current testing. A 32×32 matrix of InSb Hall sensors was set on a cylinder 15 mm in diameter and 25 mm long. The distorted alternating magnetic fields around inner diameter (ID) and outer-diameter stress corrosion cracks (ODSCCs)were imaged at 1 fps. The effectiveness of the proposed techniquewas verified with a standard copper alloy specimen with hole-type circumferential ID-and ODSCCs.
Impedance spectroscopy failure diagnosis of a DFIG-based wind turbine (2012)

Wind turbines proliferation in industrial and residential applications is facing the problem of maintenance and fault diagnosis. Periodic maintenances are necessary to ensure an acceptable life span. The aim of this work is to develop theoretical tools to diagnose the failure or the malfunction of the doubly-fed induction generator (DFIG). The diagnosis method is based on the impedance spectroscopy which is used for the diagnosis of batteries, fuel cells, and electrochemical systems. This first attempt for using this method to the diagnosis of the DFIG provides good results for the detection of the grounding connection, short circuit and stator resistance variation.
Hydrogenation of Lignin over Raney Nickel<sup>2</sup> (1946)

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTHydrogenation of Lignin over Raney Nickel2J. F. Saeman and E. E. HarrisCite this: J. Am. Chem. Soc. 1946, 68, 12, 2507–2509Publication Date (Print):December 1, 1946Publication History Published online1 May 2002Published inissue 1 December 1946https://doi.org/10.1021/ja01216a023Request reuse permissionsArticle Views184Altmetric-Citations7LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (372 KB) Get e-Alertsclose Get e-Alerts
Time-dependent quantum transport: A practical scheme using density functional theory (2005)

We present a computationally tractable scheme of time-dependent transport phenomena within open-boundary time-dependent density functional theory. Within this approach all the response properties of a system are determined from the time propagation of the set of ``occupied'' Kohn-Sham orbitals under the influence of the external bias. This central idea is combined with an open-boundary description of the geometry of the system that is divided into three regions: left∕right leads and the device region (``real simulation region''). We have derived a general scheme to extract the set of initial states in the device region that will be propagated in time with proper transparent boundary-condition at the device∕lead interface. This is possible due to a new modified Crank-Nicholson algorithm that allows an efficient time-propagation of open quantum systems. We illustrate the method in one-dimensional model systems as a first step towards a full first-principles implementation. In particular we show how a stationary current develops in the system independent of the transient-current history upon application of the bias. The present work is ideally suited to study ac transport and photon-induced charge-injection. Although the implementation has been done assuming clamped ions, we discuss how it can be extended to include dissipation due to electron-phonon coupling through the combined simulation of the electron-ion dynamics as well as electron-electron correlations.
Identifying spatio-temporal patterns of transboundary disease spread: examples using avian influenza H5N1 outbreaks (2009)

Characterizing spatio-temporal patterns among epidemics in which the mechanism of spread is uncertain is important for generating disease spread hypotheses, which may in turn inform disease control and prevention strategies. Using a dataset representing three phases of highly pathogenic avian influenza H5N1 outbreaks in village poultry in Romania, 2005-2006, spatiotemporal patterns were characterized. We first fit a set of hierarchical Bayesian models that quantified changes in the spatio-temporal relative risk for each of the 23 affected counties. We then modeled spatial synchrony in each of the three epidemic phases using non-parametric covariance functions and Thin Plate Spline regression models. We found clear differences in the spatio-temporal patterns among the epidemic phases (local versus regional correlated processes), which may indicate differing spread mechanisms (for example wild bird versus human-mediated). Elucidating these patterns allowed us to postulate that a shift in the primary mechanism of disease spread may have taken place between the second and third phases of this epidemic. Information generated by such analyses could assist affected countries in determining the most appropriate control programs to implement, and to allocate appropriate resources to preventing contact between domestic poultry and wild birds versus enforcing bans on poultry movements and quarantine. The methods used in this study could be applied in many different situations to analyze transboundary disease data in which only location and time of occurrence data are reported.
The presurgical episode: an untapped opportunity to improve value. (2019)

Expansion of episode of care measurement models to include presurgical care is an added opportunity to improve quality, value, and efficiency in healthcare delivery.
Text-guided Attention Model for Image Captioning (2016)

Visual attention plays an important role to understand images and demonstrates its effectiveness in generating natural language descriptions of images. On the other hand, recent studies show that language associated with an image can steer visual attention in the scene during our cognitive process. Inspired by this, we introduce a text-guided attention model for image captioning, which learns to drive visual attention using associated captions. For this model, we propose an exemplar-based learning approach that retrieves from training data associated captions with each image, and use them to learn attention on visual features. Our attention model enables to describe a detailed state of scenes by distinguishing small or confusable objects effectively. We validate our model on MS-COCO Captioning benchmark and achieve the state-of-the-art performance in standard metrics.
Oncogenes and Tumor Suppressors Regulate Glutamine Metabolism in Cancer Cells (2013)

Several hallmarks of cancer cells are their display of metabolic changes and enhanced proliferation. Highly proliferating cells utilize glutamine as a source of nitrogen, and therefore, one of the commonly seen metabolic changes is increased glutaminolysis, or glutamine catabolism. In addition, glutamine is an important anaplerotic source by which cells support the pools of TCA cycle intermediates in Myc-expressing cancer cells. Glutamine is converted to aspartate, which forms oxaloacetate, malate, and pyruvate. These conversions increase the NADPH/NADP(+) ratio and maintain redox balance, which supports proliferation in K-ras-expressing cells. Therefore, glutamine is important for cancer cell proliferation and survival. On the other hand, glutamine stimulates the activation of the tumor suppressor p53, which induces apoptosis and tumor regression. The tumor suppressor SIRT4 inhibits glutamate dehydrogenase, which converts glutamic acid to α-ketoglutarate, an intermediate in the TCA cycle. Overall, the expression levels of oncogenes and tumor suppressors are critical to determine whether glutamine supports or suppresses proliferation and survival of cancer cells.
FINE TUNING OF THE SPECIFICITY OF THE PERIPLASMIC PHOSPHATE TRANSPORT RECEPTOR: SITE-DIRECTED MUTAGENESIS, LIGAND BINDING, AND CRYSTALLOGRAPHIC STUDIES (1994)

Phosphorous, primarily in the form of phosphate, is a critical nutrient for the life of a cell. We have previously determined the 1.7-A resolution structure of the phosphate-binding protein, an initial receptor for the high-affinity phosphate active transport system or permease in Escherichia coli (Luecke, H., and Quiocho, F.A. (1990) Nature 347, 402-406). This structure is the first to reveal the key role of hydrogen bonding interactions in conferring the high specificity of the permease, a specificity also shared by other phosphate transport systems. Both monobasic and dibasic phosphates are recognized by the phosphate-binding protein with Asp56 playing a key role. Here we report site-directed mutagenesis, ligand binding, and crystallographic studies of the binding protein which show that introduction of one additional Asp by mutagenesis of the Thr141 in the ligand-binding site restricts binding to only the monobasic phosphate.
Acute prenatal androgen treatment increases birth weights and growth rates in lambs. (1995)

One hundred seventy-four Border Leicester x Merino ewes were mated to Romney Marsh rams. The ewes were randomly allocated to either an untreated control group or to one of four treatment groups. The treated groups were defined by the time (days postcoitus) of acute prenatal androgen treatment (APAT). The selected treatment times were 30, 40, 50, and 60 d postcoitus. Acute prenatal androgen treatment involved a single 2-mL i.m. injection of 100 mg/mL testosterone propionate. The statistical analysis of all measured parameters was performed using an analysis of variance via a general linear model. Postnatal plasma testosterone concentrations were not affected by treatment (P > .05). The time of treatment affected the observed responses to APAT (P < .05). Acute prenatal androgen treatment increased birth weight, ADG, and live weight and altered wool growth, plasma insulin levels, and ano-genital distance (P < .05).
Helios mission support (1977)

Deep Space Network support of Helios mission operations is discussed. Included is information on the Helios 1, 7th aphelion, Helios 2, 5th aphelion, science experiments, 22-bit error polynomial code (EPC) testing, and other mission-related activities. Mission operations and status are summarized and specific correction commands are described. Special activities and experiments include Faraday rotation data collection and a solar wind tracks experiment.
Example-based complexity-syntax and semantics as the production of ad-hoc arrangements of examples (2000)

Computational linguists have traditionally sought to model language by finding underlying parameters which govern numerous examples. I describe a different approach which argues that numerous examples themselves, by virtue of their many possible arrangements, provide the only way to specify a sufficiently rich set of "parameters".
Principle and Potential of Nuclear Magnetic Resonance Applied to the Study of Fluids in Porous Media (1992)

Nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) have been used in recent years in many fields, including the chemical and petroleum industries, and medicine. Following a review of the basic principles of these two techniques, their applications concerning the study of fluids in porous media are presented. The use of NMR in petrophysics is limited to the study of porosity, permeability, wettability, and the determination of the pore size distribution and saturation in a sample. MRI is an extremely useful technique, not only as a tomographic approach but, above all, because, it helps today to identify certain properties, such as velocity images. This article also presents the results obtained at Institut Français du Pétrole (IFP) concerning the study of wettability by NMR and the use of a high magnetic field to visualize fluids in porous media. In the future, a major potential use of NMR for the study of fluids in porous media resides in the extrapolation of the results obtained by spectroscopy to wireline logs, and to imaging.
Target classification and recognition based on micro-Doppler radar signatures (2017)

The mechanical dynamics in addition to its bulk translation of the target or any structure on the target is called micro-motion, which yields new features in the target's signature that are distinct from its signature in the absence of micro-motion. Micro-motion evokes a frequency modulation in radar echo known as micro-Doppler (m-D) effect which may help to detect specific intrinsic structures of the target, leading a potential method to perform target discrimination and identification by extracting micro-Doppler features. At present, it has drawn a lot of attention to extract the micro-motion target's m-D information for target classification and identification. The various m-D classification approaches require first the extraction of salient features from the radar signal. The micro-Doppler usually manifests curves characteristic in the time-frequency (T-F) domain. Thus the features are calculated from the joint T-F domain. Most of these techniques treat the spectrogram in T-F domain as an image, and obtain features through some image processing techniques. In this paper, we investigated statistical classification and recognition methods for target classification using their micro-Doppler signatures. In our work, micro-Doppler signatures for targets represented by point scattering model with four different micro-motions (Vibration, Coning, Spinning, and Precession) are studied. We propose use of principle component analysis (PCA) and 2-D PCA as the data driven feature extraction approaches that captures vital statistics of the input at a reduced dimension. Simulation analysis by using the simulated data is performed to confirm the effectiveness of the proposal. Experiment results show that with the proposed methods, perfect classification of four different motions can be attained when training and testing set has data from different targets.
Efficient implementation of bit-rate matching for LTE-A with sub-matrix transpose technique (2013)

This work proposes an efficient software implementation of circular buffer rate matching algorithm in Long Term Evolution Advanced (LTE-A). Rate matching algorithm in LTE-A performs bit re-positioning to randomize the data bits. Due to data format mismatch, such algorithm is inefficient in commodity word-based microprocessors. This work implements the transposed matrix with one or a few square sub-matrices, and each sub-matrix is performed with perfect shuffling operations. Performance of the algorithm is evaluated on the Texas Instruments C6416 with CCS-5.0. According to the results, order of magnitude performance enhancement can be achieved.
Hardware Implementation of the Huffman Encoder for Data Compression Using Altera DE2 Board (2012)

This work will aim to describe hardware implementations of static and dynamic Huffman encoders written in VHDL.The flexibility of the design allows for hardware-based implementations using FPGAs. The proposed method will have the following properties: (1) high compression for test responses is expected because Huffman coding is well-known as a minimum block coding, (2) zero-aliasing compression can be achieved.(3) It would also reduce transmission time, storage space, translation table space and encoding times
Growth of single crystalline GaN from chlorine‐free gas phase (2008)

Abstract This work is focused on the development of GaN bulk growth to overcome some limits of the established HVPE method. Evaporated Ga is transported by a carrier gas to the substrate where it reacts with atomic nitrogen from the ammonia decomposition to form GaN at temperatures of 1000–1200°C and pressures of 200–800 hPa. To prove the methods potential, 1 mm thick polycrystalline layers were deposited on the substrate holder with rates up to 50 µmh ‐1 . Numerical simulations of temperature‐, flow‐ and concentration field of the gas species were used to optimize crucible geometry and growth regime. It was experimentally found that in addition to temperature, total pressure and ammonia flow other parameters like source composition; crucible material and flow conditions near the substrate may affect seeding, growth rate and layer quality. First epitaxial layers up to 280 µm thickness were successfully grown on different bulk and template substrates. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Fully Automatic Roadside Camera Calibration for Traffic Surveillance (2014)

This paper deals with automatic calibration of roadside surveillance cameras. We focus on parameters necessary for measurements in traffic-surveillance applications. Contrary to the existing solutions, our approach requires no a priori knowledge, and it works with a very wide variety of road settings (number of lanes, occlusion, quality of ground marking), as well as with practically unlimited viewing angles. The main contribution is that our solution works fully automatically-without any percamera or per-video manual settings or input whatsoever-and it is computationally inexpensive. Our approach uses tracking of local feature points and analyzes the trajectories in a manner based on cascaded Hough transform and parallel coordinates. An important assumption for the vehicle movement is that at least a part of the vehicle motion is approximately straight-we discuss the impact of this assumption on the applicability of our approach and show experimentally that this assumption does not limit the usability of our approach severely. We efficiently and robustly detect vanishing points, which define the ground plane and vehicle movement, except for the scene scale. Our algorithm also computes parameters for radial distortion compensation. Experiments show that the obtained camera parameters allow for measurements of relative lengths (and potentially speed) with ~2% mean accuracy. The processing is performed easily in real time, and typically, a 2-min-long video is sufficient for stable calibration.
A Novel M-Estimator for Robust PCA (2011)

We study the basic problem of robust subspace recovery. That is, we assume a data set that some of its points are sampled around a fixed subspace and the rest of them are spread in the whole ambient space, and we aim to recover the fixed underlying subspace. We first estimate "robust inverse sample covariance" by solving a convex minimization procedure; we then recover the subspace by the bottom eigenvectors of this matrix (their number correspond to the number of eigenvalues close to 0). We guarantee exact subspace recovery under some conditions on the underlying data. Furthermore, we propose a fast iterative algorithm, which linearly converges to the matrix minimizing the convex problem. We also quantify the effect of noise and regularization and discuss many other practical and theoretical issues for improving the subspace recovery in various settings. When replacing the sum of terms in the convex energy function (that we minimize) with the sum of squares of terms, we obtain that the new minimizer is a scaled version of the inverse sample covariance (when exists). We thus interpret our minimizer and its subspace (spanned by its bottom eigenvectors) as robust versions of the empirical inverse covariance and the PCA subspace respectively. We compare our method with many other algorithms for robust PCA on synthetic and real data sets and demonstrate state-of-the-art speed and accuracy.