654 research outputs found
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Quality Electric Motor Repair: A Guidebook for Electric Utilities
This guidebook provides utilities with a resource for better understanding and developing their roles in relation to electric motor repair shops and the industrial and commercial utility customers that use them. The guidebook includes information and tools that utilities can use to raise the quality of electric motor repair practices in their service territories
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Industrial motor repair in the United States
This report characterizes the motor repair industry in the United States; summarizes current motor repair and testing practice; and identifies barriers to energy motor repair practice and recommends strategies for overcoming those barriers
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Status of the AGS Polarized H- Source
Development of a polarized H/sup -/ source for the AGS polarized proton project, initially begun at Argonne National Laboratory in 1979, has been continuing at Brookhaven National Laboratory since early 1982. A description of the source is given and the status of the project is reviewed
Efficiency of silicon thin-film photovoltaic modules with a front coloured glass
Photovoltaic electricity has already proven its ability to compete with other well established technologies for energy production. The abundant and non-toxic raw materials, the yearly increasing efficiency as well as the production cost of silicon thin-film solar cells getting lower and lower make this technology always more interesting for a wide spread use. Beside the functional features, the size, colour and glass texture of a PV module determine its appearance and aesthetics. In order to be more compliant with the built environment, photovoltaic installations have to be improved in terms of visual rendering, matching of colour of the existing roof-tops and parasitic reflections. The crystalline technology already offers various types of systems with a large choice of shapes, textures and colours as well as âsemi-transparentâ modules more easily integrated in the roof-tops or facade. By changing the anti-reflective coating (ARC) of a crystalline solar cell, it is possible to modify their colour [1]. However, for thin-film silicon technology the challenge is completely different, and up to now, the only way to modify the module colour is to reduce the thickness of the active layer and consequently its efficiency. Therefore new ways to enhance the visual rendering of the thin-film modules have to be explored. A study led in the frame of the ArchinSolar project [2] has shown that architects are ready to integrate PV modules with enhanced aesthetic aspect, even though there was a 10 % loss in efficiency. The present study shows how new coloured filters can be used to enhance PV modulesâ appearance while minimizing power loss, to achieve a better integration in the traditional urban or rural environment
Measurement of the CKM Matrix Element from at Belle
We present a new measurement of the CKM matrix element from decays, reconstructed with the full Belle data set
of integrated luminosity. Two form factor
parameterizations, originally conceived by the Caprini-Lellouch-Neubert (CLN)
and the Boyd, Grinstein and Lebed (BGL) groups, are used to extract the product
and the decay form factors, where
is the normalization factor and is a small
electroweak correction. In the CLN parameterization we find
, , , . For the BGL parameterization we
obtain , which is consistent with the World Average when correcting for
. The branching fraction of is measured to be . We also present a new
test of lepton flavor universality violation in semileptonic decays,
. The errors correspond to the statistical and
systematic uncertainties respectively. This is the most precise measurement of
and form factors to date and the first
experimental study of the BGL form factor parameterization in an experimental
measurement
Rapid generation of long synthetic tandem repeats and its application for analysis in human artificial chromosome formation
Human artificial chromosomes (HACs) provide a unique opportunity to study kinetochore formation and to develop a new generation of vectors with potential in gene therapy. An investigation into the structural and the functional relationship in centromeric tandem repeats in HACs requires the ability to manipulate repeat substructure efficiently. We describe here a new method to rapidly amplify human alphoid tandem repeats of a few hundred base pairs into long DNA arrays up to 120 kb. The method includes rolling-circle amplification (RCA) of repeats in vitro and assembly of the RCA products by in vivo recombination in yeast. The synthetic arrays are competent in HAC formation when transformed into human cells. As short multimers can be easily modified before amplification, this new technique can identify repeat monomer regions critical for kinetochore seeding. The method may have more general application in elucidating the role of other tandem repeats in chromosome organization and dynamics
Main assumptions for energy pathways
© The Author(s) 2019. The aim of this chapter is to make the scenario calculations fully transparent and comprehensible to the scientific community. It provides the scenario narratives for the reference case (5.0 °C) as well as for the 2.0 °C and 1.5 °C on a global and regional basis. Cost projections for all fossil fuels and renewable energy technologies until 2050 are provided. Explanations are given for all relevant base year data for the modelling and the main input parameters such as GDP, population, renewable energy potentials and technology parameters
A mathematical and computational review of Hartree-Fock SCF methods in Quantum Chemistry
We present here a review of the fundamental topics of Hartree-Fock theory in
Quantum Chemistry. From the molecular Hamiltonian, using and discussing the
Born-Oppenheimer approximation, we arrive to the Hartree and Hartree-Fock
equations for the electronic problem. Special emphasis is placed in the most
relevant mathematical aspects of the theoretical derivation of the final
equations, as well as in the results regarding the existence and uniqueness of
their solutions. All Hartree-Fock versions with different spin restrictions are
systematically extracted from the general case, thus providing a unifying
framework. Then, the discretization of the one-electron orbitals space is
reviewed and the Roothaan-Hall formalism introduced. This leads to a exposition
of the basic underlying concepts related to the construction and selection of
Gaussian basis sets, focusing in algorithmic efficiency issues. Finally, we
close the review with a section in which the most relevant modern developments
(specially those related to the design of linear-scaling methods) are commented
and linked to the issues discussed. The whole work is intentionally
introductory and rather self-contained, so that it may be useful for non
experts that aim to use quantum chemical methods in interdisciplinary
applications. Moreover, much material that is found scattered in the literature
has been put together here to facilitate comprehension and to serve as a handy
reference.Comment: 64 pages, 3 figures, tMPH2e.cls style file, doublesp, mathbbol and
subeqn package
PepDist: A New Framework for Protein-Peptide Binding Prediction based on Learning Peptide Distance Functions
BACKGROUND: Many different aspects of cellular signalling, trafficking and targeting mechanisms are mediated by interactions between proteins and peptides. Representative examples are MHC-peptide complexes in the immune system. Developing computational methods for protein-peptide binding prediction is therefore an important task with applications to vaccine and drug design. METHODS: Previous learning approaches address the binding prediction problem using traditional margin based binary classifiers. In this paper we propose PepDist: a novel approach for predicting binding affinity. Our approach is based on learning peptide-peptide distance functions. Moreover, we suggest to learn a single peptide-peptide distance function over an entire family of proteins (e.g. MHC class I). This distance function can be used to compute the affinity of a novel peptide to any of the proteins in the given family. In order to learn these peptide-peptide distance functions, we formalize the problem as a semi-supervised learning problem with partial information in the form of equivalence constraints. Specifically, we propose to use DistBoost [1,2], which is a semi-supervised distance learning algorithm. RESULTS: We compare our method to various state-of-the-art binding prediction algorithms on MHC class I and MHC class II datasets. In almost all cases, our method outperforms all of its competitors. One of the major advantages of our novel approach is that it can also learn an affinity function over proteins for which only small amounts of labeled peptides exist. In these cases, our method's performance gain, when compared to other computational methods, is even more pronounced. We have recently uploaded the PepDist webserver which provides binding prediction of peptides to 35 different MHC class I alleles. The webserver which can be found at is powered by a prediction engine which was trained using the framework presented in this paper. CONCLUSION: The results obtained suggest that learning a single distance function over an entire family of proteins achieves higher prediction accuracy than learning a set of binary classifiers for each of the proteins separately. We also show the importance of obtaining information on experimentally determined non-binders. Learning with real non-binders generalizes better than learning with randomly generated peptides that are assumed to be non-binders. This suggests that information about non-binding peptides should also be published and made publicly available
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