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Concentration and synthesis of phosphoribosylpyrophosphate in erythrocytes from normal, hyperuricemic, and gouty subjects.
Phosphoribosylpyrophosphate (PRPP) synthetase activity and the intracellular concentration of PRPP were assayed in erythrocytes from patients with primary hyperuricemia and primary metabolic gout. Sensitivity of the enzyme to feed-back inhibition by adenosine diphosphate (ADP), guanosine diphosphate (GDP), and 2,3-diphosphoglycerate (2,3-DPG) was determined. All patients with gout and four of ten patients with hyperuricemia were taking allopurinol during the study. Mean PRPP synthetase activity in erythrocytes from hyperuricemic and gouty patients was similar to that in normal subjects, and feedback inhibition by ADP, GDP, and 2,3-DPG was intact. The concentration of PRPP in erythrocytes was higher in normal females than in normal males, higher in normal subjects than in gouty patients, and lower in hyperuricemic patients taking allopurinol than in those hyperuricemic patients not taking this drug. The difference in intracellular levels of PRPP in erythrocytes in gout versus hyperuricemic patients was not significant. The significance of these findings is discussed in relation to the regulation of PRPP synthetase and in the important regulatory role of PRPP in purine metabolism. © 1971
Checking the transverse Ward-Takahashi relation at one loop order in 4-dimensions
Some time ago Takahashi derived so called {\it transverse} relations relating
Green's functions of different orders to complement the well-known
Ward-Green-Takahashi identities of gauge theories by considering wedge rather
than inner products. These transverse relations have the potential to determine
the full fermion-boson vertex in terms of the renormalization functions of the
fermion propagator. He & Yu have given an indicative proof at one-loop level in
4-dimensions. However, their construct involves the 4th rank Levi-Civita tensor
defined only unambiguously in 4-dimensions exactly where the loop integrals
diverge. Consequently, here we explicitly check the proposed transverse
Ward-Takahashi relation holds at one loop order in -dimensions, with
.Comment: 20 pages, 3 figures This version corrects and clarifies the previous
result. This version has been submitted for publicatio
Projections, Pseudo-Stopping Times and the Immersion Property
Given two filtrations , we study under which
conditions the -optional projection and the -dual
optional projection coincide for the class of -optional processes
with integrable variation. It turns out that this property is equivalent to the
immersion property for and , that is every -local martingale is a -local martingale, which, equivalently, may
be characterised using the class of -pseudo-stopping times. We also
show that every -stopping time can be decomposed into the minimum of
two barrier hitting times
Proximity Full-Text Search with a Response Time Guarantee by Means of Additional Indexes
Full-text search engines are important tools for information retrieval. Term
proximity is an important factor in relevance score measurement. In a proximity
full-text search, we assume that a relevant document contains query terms near
each other, especially if the query terms are frequently occurring words. A
methodology for high-performance full-text query execution is discussed. We
build additional indexes to achieve better efficiency. For a word that occurs
in the text, we include in the indexes some information about nearby words.
What types of additional indexes do we use? How do we use them? These questions
are discussed in this work. We present the results of experiments showing that
the average time of search query execution is 44-45 times less than that
required when using ordinary inverted indexes.
This is a pre-print of a contribution "Veretennikov A.B. Proximity Full-Text
Search with a Response Time Guarantee by Means of Additional Indexes" published
in "Arai K., Kapoor S., Bhatia R. (eds) Intelligent Systems and Applications.
IntelliSys 2018. Advances in Intelligent Systems and Computing, vol 868"
published by Springer, Cham. The final authenticated version is available
online at: https://doi.org/10.1007/978-3-030-01054-6_66. The work was supported
by Act 211 Government of the Russian Federation, contract no 02.A03.21.0006.Comment: Alexander B. Veretennikov. Chair of Calculation Mathematics and
Computer Science, INSM. Ural Federal Universit
Nondestructive quantitative measurement for precision quality control in additive manufacturing using hyperspectral imagery and machine learning.
Measuring the purity of the metal powder is essential to maintain the quality of additive manufacturing products. Contamination is a significant concern, leading to cracks and malfunctions in the final products. Conventional assessment methods focus more on physical integrity rather than material composition and can be time-consuming. By capturing spectral data from a wide frequency range along with the spatial information, hyperspectral imaging (HSI) can detect minor differences in terms of temperature, moisture, and chemical composition to tackle this challenge. In this article, we explore the application of HSI in conjunction with machine learning for nondestructive inspection of metal powders. By employing near-infrared and visible HSI cameras, we introduce the utilization of HSI for this purpose. We delve into the technical challenges encountered and present detailed solutions through three case studies, including the establishment of a spectral dictionary, contamination detection, and band selection analysis. Our experimental results demonstrate the immense potential of HSI and its synergy with machine learning for nondestructive testing in powder metallurgy, particularly in meeting the requirements of industrial manufacturing environments
wsrf: An R Package for Classification with Scalable Weighted Subspace Random Forests
We describe a parallel implementation in R of the weighted subspace random forest algorithm (Xu, Huang, Williams, Wang, and Ye 2012) available as the wsrf package. A novel variable weighting method is used for variable subspace selection in place of the traditional approach of random variable sampling. This new approach is particularly useful in building models for high dimensional data - often consisting of thousands of variables. Parallel computation is used to take advantage of multi-core machines and clusters of machines to build random forest models from high dimensional data in considerably shorter times. A series of experiments presented in this paper demonstrates that wsrf is faster than existing packages whilst retaining and often improving on the classification performance, particularly for high dimensional data
Outer zone electrons
Spatial and temporal behavior of high energy trapped electrons in outer zone of magnetospher
Inexpensive multi-plane particle image velocimetry based on defocusing: proof of concept on two-component measurement
This paper presents a method for simultaneous particle image velocimetry (PIV) on parallel planes offset in depth. The method places images from two planes onto a different half of a camera sensor by using image splitting optics with variable optical path lengths. A shallow depth of field is achieved to ensure only one plane is in focus on each half of the sensor. Without needing additional lasers, the method is designed as an inexpensive means to increase the number of measurement plane(s) of single/multi-plane PIV setups and can be combined with existing plane discrimination approaches such as polarization and wavelength. The method is useful for studying instantaneous flow correlations on different planes while retaining high in-plane spatial resolution of typical planar PIV measurement. The measurement uncertainty caused by crosstalk from out-of-focus images is discussed. Experimental results from a laminar flow rig test indicate that the average measurement error of each velocity component is lower than 0.1 pixels per time step, with a 20 mm plane separation in depth and a 35 × 54 mm2 field of view. As an application with varying background scatter and out-of-plane flow motions, in-cylinder flow measurements in an optically accessible internal combustion engine were performed on two swirl planes simultaneously. Characteristics of the proposed method performing stereoscopic PIV measurements will be studied in future
Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy
Automated label-free quantitative imaging of biological samples can greatly
benefit high throughput diseases diagnosis. Digital holographic microscopy
(DHM) is a powerful quantitative label-free imaging tool that retrieves
structural details of cellular samples non-invasively. In off-axis DHM, a
proper spatial filtering window in Fourier space is crucial to the quality of
reconstructed phase image. Here we describe a region-recognition approach that
combines shape recognition with an iterative thresholding to extracts the
optimal shape of frequency components. The region recognition technique offers
fully automated adaptive filtering that can operate with a variety of samples
and imaging conditions. When imaging through optically scattering biological
hydrogel matrix, the technique surpasses previous histogram thresholding
techniques without requiring any manual intervention. Finally, we automate the
extraction of the statistical difference of optical height between malaria
parasite infected and uninfected red blood cells. The method described here
pave way to greater autonomy in automated DHM imaging for imaging live cell in
thick cell cultures
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