Haut PDF Clustering and the Three-Point Function

Clustering and the Three-Point Function

Clustering and the Three-Point Function

jiangyf2008@gmail.com, skomatsu@perimeterinstitute.ca, ivan.kostov & didina.serban@cea.fr Abstract We develop analytical methods for computing the structure constant for three heavy operators, starting from the recently proposed hexagon approach. Such a structure constant is a semiclassical object, with the scale set by the inverse length of the operators playing the role of the Planck constant. We reformulate the hexagon expansion in terms of multiple contour integrals and recast it as a sum over clusters generated by the residues of the measure of integration. We test the method on two examples. First, we compute the asymptotic three-point function of heavy fields at any coupling and show the result in the semiclassical limit matches both the string theory computation at strong coupling and the tree-level results obtained before. Second, in the case of one non-BPS and two BPS operators at strong coupling we sum up all wrapping corrections associated with the opposite bridge to the non-trivial operator, or the “bottom” mirror channel. We also give an alternative interpretation of the results in terms of a gas of fermions and show that they can be expressed compactly as an operator- valued super-determinant.
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Nutrient patterns, cognitive function, and decline in older persons: results from the Three-City and NuAge studies

Nutrient patterns, cognitive function, and decline in older persons: results from the Three-City and NuAge studies

Received: 15 July 2019; Accepted: 23 July 2019; Published: 5 August 2019    Abstract: Dietary patterns, or the combination of foods and beverages intake, have been associated with better cognitive function in older persons. To date, no study has investigated the link between a posteriori nutrient patterns based on food intake, and cognitive decline in longitudinal analyses. The aim of this study was to evaluate the relationship between nutrient patterns and cognitive function and decline in two longitudinal cohorts of older persons from France and Canada. The study sample was composed of participants from the Three-City study (3C, France) and the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge, Quebec, Canada). Both studies estimated nutritional intakes at baseline, and carried out repeated measures of global cognitive function for 1,388 and 1,439 individuals, respectively. Nutrient patterns were determined using principal component analysis methodology in the two samples, and their relation with cognitive function and decline was estimated using linear mixed models. In 3C, a healthy nutrient pattern, characterized by higher intakes of plant-based foods, was associated with a higher global cognitive function at baseline, as opposed to a Western nutrient pattern, which was associated with lower cognitive performance. In NuAge, we also found a healthy nutrient pattern and a Western pattern, although no association was observed with either of these patterns in the Canadian cohort. No association between any of the nutrient patterns and cognitive decline was observed in either cohort. There is a need for longitudinal cohorts focusing on nutrient patterns with substantial follow-up, in order to evaluate more accurately associations between nutrition and cognition in older persons.
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Inappropriate drug use and mortality in community-dwelling elderly with impaired kidney function--the Three-City population-based study.: Inappropriate drug use in the elderly with impaired kidney function

Inappropriate drug use and mortality in community-dwelling elderly with impaired kidney function--the Three-City population-based study.: Inappropriate drug use in the elderly with impaired kidney function

Although adverse outcomes related to inappropriate drug use according to Beer s criteria is well documented, 14 16 this study is the ’ [ – ] first to point out that using drugs requiring dose adjustment is associated with excess mortality among community-dwelling elderly with impaired kidney function, regardless of age, gender, and several potential confounders. The hazard ratio for contraindicated drugs was of the same order of magnitude, but not statistically significant, possibly because of the small sample size for this subgroup. These findings are consistent with those from Hug et al, 8 showing that adverse drug events were common among hospitalized adult patients with [ ]
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Fixing the quantum three-point function

Fixing the quantum three-point function

Each of these results covers a particular case of three- (or higher-) point functions, and we do not yet have a comprehensive understanding of the generic structure of correlation functions, as we do for the spectrum. In particular, we do not yet have a method which provides an acceptable recipe for obtaining a particular three-point function. Nevertheless, a coherent picture starts to emerge, and an important step forward is the very recent calculation of su(2) correlation functions by Kazama and Komatsu at strong coupling [21]. In this work, we revisit the computation of quantum three-point functions in [16–18], with the purpose 1) to get reliable expressions in the semi-classical limit, which can be compared to the strong coupling results and 2) to set up a systematic formalism for proceeding to higher loop orders. In order to extend the results from tree-level to loops, we need to have a good description of the wave functions and scalar products of long-range interacting spin chains.
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The effect of ageing process on three-point bending strength and permeability of 3D printed sand molds

The effect of ageing process on three-point bending strength and permeability of 3D printed sand molds

Fig.1 Schematic representation of, (a) particle binder bonding and resin bridge in 3D printed sand molds, (b) tighly packed particles The interstices between the grains of sand in the 3D printed parts permit the evacuation of air during the filling of the mold as well as the flow of the gases generated during filling and solidification of the alloy. These gases are evacuated more or less rapidly depending on the permeability of the sand [12, 13]. Researchers have studied the gas emissions from mold and core sand binders, where the thermal degradation of binders was measured by collecting off gasses in specially designed ventilation hood at a constant flow rate [13]. Also a numerical model was developed to estimate the potential out-gassing of the furan bonded silica molds and cores [12]. In this respect, liquid binder blocks gas flow through the sand, resulting in slow filling of the mold cavity and more gas being trapped during pouring of the alloy. Therefore, the permeability of the mold must be high enough to accelerate filling and minimize casting defects. However, excessively high permeability values obtained by using coarse grains of sand may also lead to metal penetration defects due to large inter-sand grain spacing, so a compromise between both effects should be found.
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The VIMOS Public Extragalactic Redshift Survey (VIPERS). Exploring the dependence of the three-point correlation function on stellar mass and luminosity at $0.5 < z < 1.1$

The VIMOS Public Extragalactic Redshift Survey (VIPERS). Exploring the dependence of the three-point correlation function on stellar mass and luminosity at $0.5 < z < 1.1$

Matarrese et al. 1997 ; Verde et al. 1998 , 2000 ; Scoccimarro 2000 ; Scoccimarro et al. 2001 ; Sefusatti & Scoccimarro 2005 ; Sefusatti & Komatsu 2007 ). The aim of this paper is to push these investigations to higher redshifts. For this purpose, we analyse the VIPERS Public Data Release 1 (PDR-1) ( Guzzo et al. 2014 ; Garilli et al. 2014 ), con- straining the dependence of the 3PCF on stellar mass and lumi- nosity. A similar analysis of the same dataset has been performed by Marulli et al. ( 2013 ) (hereafter M13), but for the 2PCF. This paper is intended as an extension of the analysis done in M13, exploiting the additional constraints that can be obtained from higher-order correlation functions. In particular, we focus our analysis on the non-linear or mildly non-linear evolution regime, since the size of the survey does not allow us to probe those scales sensitive to possible primordial non-Gaussianities.
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Angular Clustering of X-ray Point-Like Sources in the XMM Large Scale Structure Survey

Angular Clustering of X-ray Point-Like Sources in the XMM Large Scale Structure Survey

1 ANGULAR CLUSTERING OF X-RAY POINT-LIKE SOURCES IN THE XMM LARGE SCALE STRUCTURE SURVEY O. Garcet 1 , P. Gandhi 2 , E. Gosset 1 , A. Gueguen 3 , F. Pacaud 3 , M. Pierre 3 , and J. Surdej 1 1 Institut d’Astrophysique et de G´eophysique, Universit´e de Li`ege, Belgium

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Automatic Clustering Of Celtic Coins Based On 3d Point Cloud Pattern Analysis

Automatic Clustering Of Celtic Coins Based On 3d Point Cloud Pattern Analysis

4.4 Metric learning evaluation We have seen in the previous section that the decision whether two coins have the same die is a problem of binary classifica- tion. To correctly evaluate this part, we have aligned by hand the patterns, then we perform an ICP to refine and then, we can test if two patterns are similar or not. As it said in previous section, the dataset is composed of 2145 comparisons so 2145 histograms. In our dataset, we have 1436 negative labels and 709 positive labels. We divide our dataset randomly in a train- ing set and a test set: half of our dataset is used for training, the other half is used for testing. We can simply compute the accur- acy on the test set to see if our method is correct or not. When the patterns are correctly registered using ICP, the accuracy is 98% on the test set. But if we registrate the patterns by hand the accuracy drop to 72% on the test set. It shows that ICP allows a better repeatability in decision. We can see that the method is very effective when the patterns are well aligned. When pat- terns are the same, the histograms of distances are good features to see if the patterns are similar or not. But it will fail when the coins are not well aligned. We have also shown that the metric learning part doesn’t need a huge dataset to learn an appropriate metric.
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POINT-SPREAD FUNCTION MODEL FOR FLUORESCENCE MACROSCOPY IMAGING

POINT-SPREAD FUNCTION MODEL FOR FLUORESCENCE MACROSCOPY IMAGING

Fig. 2. The vignetting of an oblique light beam in a lens. Reproduced from [ 6 ] treme oblique rays, the light is extinguished altogether. Vignetting, as this phenomenon is known in photography, is the denotation of the gradual fading of the intensity of an image from the centre to- wards the edge. As a result, an unintended darkening of the image corners might appear in a photographic image. While natural and optical vignetting might be inherent to the optical lens system de- sign, mechanical vignetting is usually caused by due to protrusions that partially occlude the FOV [ 7 ]. The difference between them is that while natural and optical vignetting leads to a gradual transition from a brighter image center to darker corners, for mechanical vi- gnetting, the fall-off is usually abrupt. In this paper, we will only discuss optical vignetting as this is the primary field aberration in a MACROscope. An important remark is that the optical vignetting should not be confused with the Petzval field curvature, an optical aberration, caused due to the inability of the lens to focus a flat ob- ject normal to the optical axis to a flat image plane.
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A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications

A Dynamic Clustering Algorithm for Multi-Point Transmissions in Mission-Critical Communications

A. Related Work Dynamic clustering in cooperative transmissions has been well investigated in the literature, but mostly for unicast best effort traffic with the goal of maximizing functions of the user data rates under static traffic models. The different approaches can be classified into network-centric and user- centric clustering. In the former, a set of BSs forms a cluster, and all the users attached to them are served by the cluster. In the latter, each user may have its own cluster of coordinated BSs and thus clusters for different transmissions may overlap. Greedy algorithms based approaches have been widely used in network-centric clustering algorithms, e.g. [8]–[12]. They are based on the idea of sequentially adding the best BSs to the cluster up to a certain maximum cluster size. A greedy algorithm based on sum-rate maximization is developed in [8], one of the first reference on BS clustering. Yoon et al. focus in [9] on cell-edge users performance and propose a greedy clustering algorithm to maximize the cooperation gain, along with an interference weight calculation algorithm to reduce complexity. Improving the spectral efficiency is the main goal of [10], which relies on dynamic but non-overlapping clusters formed based on a greedy approach. In [11], a dynamic BS clustering algorithm has been proposed based on maximizing the weighted sum rate, using a greedy iterative algorithm. This clustering is combined with a scheduling algorithm and eval- uated with dynamic traffic models in [12]. However, greedy search method based clustering algorithms may not provide the optimal cluster for group communications, since the cluster must be designed based on all group users performance. We note that, for computational complexity reasons, only non- overlapping clusters are considered in these studies, which may be sub-optimal for some users.
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Nonconvex optimization for 3D point source localization using a rotating point spread function

Nonconvex optimization for 3D point source localization using a rotating point spread function

spread function ∗ Chao Wang † , Raymond Chan † , Mila Nikolova ‡ , Robert Plemmons § , and Sudhakar Prasad ¶ Abstract. We consider the high-resolution imaging problem of 3D point source image recovery from 2D data using a method based on point spread function (PSF) engineering. The method involves a new technique, recently proposed by S. Prasad, based on the use of a rotating PSF with a single lobe to obtain depth from defocus. The amount of rotation of the PSF encodes the depth position of the point source. Applications include high-resolution single molecule localization microscopy as well as the problem addressed in this paper on localization of space debris using a space-based telescope. The localization problem is discretized on a cubical lattice where the coordinates of nonzero entries represent the 3D locations and the values of these entries the fluxes of the point sources. Finding the locations and fluxes of the point sources is a large-scale sparse 3D inverse problem. A new nonconvex regularization method with a data-fitting term based on Kullback-Leibler (KL) divergence is proposed for 3D localization for the Poisson noise model. In addition, we propose a new scheme of estimation of the source fluxes from the KL data-fitting term. Numerical experiments illustrate the efficiency and stability of the algorithms that are trained on a random subset of image data before being applied to other images. Our 3D localization algorithms can be readily applied to other kinds of depth-encoding PSFs as well.
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Space non-invariant point-spread function and its estimation in fluorescence microscopy

Space non-invariant point-spread function and its estimation in fluorescence microscopy

dominan e of a single intensity value. Hen e, the ba kground is almost uniform and for our model we an assume it to be a onstant. What we an also infer from the gures is that there is a uniformity in the illumination and no alignment problems. The mean value of the ba kground signal from this estimation pro edure was found to be about 3.13 intensity level units (IU). Fig. 4(a) shows the histogram al ulated for the sli e in Fig. 3(b). In the

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Estimating the galaxy two-point correlation function using a split random catalog

Estimating the galaxy two-point correlation function using a split random catalog

The two-point correlation function of the galaxy distribution is a key cosmological observable that allows us to constrain the dynamical and geometrical state of our Universe. To measure the correlation function we need to know both the galaxy positions and the expected galaxy density field. The expected field is commonly specified using a Monte-Carlo sampling of the volume covered by the survey and, to minimize additional sampling errors, this random catalog has to be much larger than the data catalog. Correlation function estimators compare data–data pair counts to data–random and random–random pair counts, where random–random pairs usually dominate the computational cost. Future redshift surveys will deliver spectroscopic catalogs of tens of millions of galaxies. Given the large number of random objects required to guarantee sub-percent accuracy, it is of paramount importance to improve the e fficiency of the algorithm without degrading its precision. We show both analytically and numerically that splitting the random catalog into a number of subcatalogs of the same size as the data catalog when calculating random–random pairs and excluding pairs across different subcatalogs provides the optimal error at fixed computational cost. For a random catalog fifty times larger than the data catalog, this reduces the computation time by a factor of more than ten without affecting estimator variance or bias.
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The distance-dependent two-point function of quadrangulations: a new derivation by direct recursion

The distance-dependent two-point function of quadrangulations: a new derivation by direct recursion

In a recent paper [11], we revisited the distance-dependent two-point function of planar triangulations (maps whose all faces have degree 3) and showed how to obtain its expres- sion from the solution of some direct recursion relation on the associated slice generating functions. The solution of the recursion made a crucial use of some old results by Tutte in his seminal paper [15] on triangulations. In this paper, we extend the analysis of [11] to the case of planar quadrangulations (maps which all faces of degree 4) by showing that a similar recursion may be written and solved by the same treatment as for triangulations.
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The Structural Dynamics of Engineered beta-Lactamases Vary Broadly on Three Timescales yet Sustain Native Function

The Structural Dynamics of Engineered beta-Lactamases Vary Broadly on Three Timescales yet Sustain Native Function

ard deviation suggests motions occurring on a slower timescale. Those slower motions were confirmed and char- acterized (Figs S1 and S2). S 2 in those regions generally could not be characterized by NMR due to overlapping/ broad peaks, further demonstrating the value of the simulations. Dynamics on the intermediate (ns- µs) timescale. To investigate the intermediate timescale of motions, we extracted the Cα root mean square fluctuation (RMSF) from the molecular dynamics simulations (Fig. S2 and Table S6). As observed for fast motions, the core of each β-lactamase was rigid, while the surface loops were more flexible (Fig.  3 ). TEM-1 and the chimeras showed significantly more ns-µs dynamic residues than PSE-4, in agreement with the higher sequence similarity of the chimeras to TEM-1. The substitution of up to 19 amino acids in TEM-1 did not markedly alter ns-µs dynamics.
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Spectrally resolved point-spread-function engineering using a complex medium

Spectrally resolved point-spread-function engineering using a complex medium

Here, we exploit the MSTM in conjunction with a single SLM to perform arbitrary spatio- spectral PSF engineering. It consists of (i) measuring the MSTM to characterize light scattering induced by the medium and (ii) numerically filtering a virtual pupil function with a spectrally- dependent mask prior to (iii) focusing. Importantly, nearly any arbitrary mask (phase and/or amplitude) can be applied onto the pupil function. This versatility is experimentally shown through the generation of two different spatio-spectral PSFs that both aim at decoupling axial confinement from lateral extent, with multiphoton microscopy applications envisioned. First, we revisit traditional temporal focusing (TF) and show that our approach is not restricted to disperse the pulse along only one spatial dimension as offered by diffraction gratings. Secondly, we report on another TF-like PSF that benefits from the high transverse resolution of a bessel beam but with a better axial confinement. Corresponding spatio-temporal profiles are characterized with a 2-photon fluorescence process.
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Structure function relationships in three lipids A from the Ralstonia genus rising in obese patients

Structure function relationships in three lipids A from the Ralstonia genus rising in obese patients

40. Vreugdenhil, A. C., C. H. Rousseau, T. Hartung, J. W. Greve, C. van 't Veer and W. A. Buurman. 2003. "Lipopolysaccharide (LPS)-binding protein mediates LPS detoxification by chylomicrons." J Immunol 170: 1399-1405. 41. Atarashi, K., T. Tanoue, M. Ando, N. Kamada, Y. Nagano, S. Narushima, W. Suda, A. Imaoka, H. Setoyama, T. Nagamori, E. Ishikawa, T. Shima, T. Hara, S. Kado, T. Jinnohara, H. Ohno, T. Kondo, K. Toyooka, E. Watanabe, S.-I. Yokoyama, S. Tokoro, H. Mori, Y. Noguchi, H. Morita, I. I. Ivanov, T. Sugiyama, G. Nuñez, J. G. Camp, M. Hattori, Y. Umesaki, and K. Honda. 2015. Th17 Cell Induction by Adhesion of Microbes to Intestinal Epithelial Cells. Cell. 163: 367– 380.
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Blind Deconvolution of Medical Ultrasound Images Using a Parametric Model for the Point Spread Function

Blind Deconvolution of Medical Ultrasound Images Using a Parametric Model for the Point Spread Function

1. INTRODUCTION Medical ultrasound (US) imaging is widely used for clinical diagnosis such as cardiovascular medicine, urology and ob- stetrics. Compared to other medical imaging modalities, e.g., X-ray computed tomography (CT) and magnetic resonance imaging (MRI), US imaging has many advantages, including its harmless, cost-effective, portable and noninvasive proper- ties. However, US images suffer from a relatively low con- trast, reduced spatial resolution at a given frequency and low signal-to-noise ratio (SNR). Even though advances in ultra- sonic device-based solutions have improved the resolution of
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Adaptive estimating function inference for non-stationary determinantal point processes

Adaptive estimating function inference for non-stationary determinantal point processes

The performance of second order estimating functions depends strongly on a tuning parameter that controls which pairs of points are used in the estimation. Our adaptive choice of this tuning parameter is intuitively appealing, easy to implement and performs well in the simulation studies considered. It moreover seamlessly integrates with the asymptotic results where the use of the adaptive method poses no extra theoretical difficulties. Though we focus in this paper on determinantal point processes, the adaptive method is applicable for any spatial point process with known pair correlation function. As an example we provide in Section 3 of the supplementary material a simulation study in case of a cluster process.
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Rapid clustering from colorized 3D point cloud data for reconstructing building interiors

Rapid clustering from colorized 3D point cloud data for reconstructing building interiors

roberto.canas@nrc.gc.ca Abstract - Range scanning of building interiors generates very large, partially spurious and unstructured point cloud data. Accurate information extraction from such data sets is a complex task due to the presence of multiple objects, diversity of their shapes, large disparity in the feature sizes, and the spatial uncertainty due to occluded regions. A fast segmentation of such data is necessary for quick understanding of the scanned scene. Unfortunately, traditional range segmentation methodologies are computationally expensive because they rely almost exclusively on shape parameters (normal, curvature) and are highly sensitive to small geometric distortions in the captured data. This paper introduces a quick and effective segmentation technique for large volumes of colorized range scans from unknown building interiors and labelling clusters of points that represent distinct surfaces and objects in the scene. Rather than computing geometric parameters, the proposed technique uses a robust Hue, Saturation and Value (HSV) color model as an effective means of identifying rough clusters (objects) that are further refined by eliminating spurious and outlier points through region growth and a fixed distance neighbors (FDNs) analysis. The results demonstrate that the proposed method is effective in identifying continuous clusters and can extract meaningful object clusters, even from geometrically similar regions.
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