Miracle-dz/UniFAR-FTUs huggingface dataset:
On the action of viscosity in increasing the spacing ratio of a vortex street

1—von Karman, by considering two parallel rows (of indefinite extent) of isolated, equal, point-vortices existing in a non-viscous fluid, has shown that the only stable vortex arrangement is the asymmetrical staggered one; and then only provided that the geometry of the system is such that h / a = 0·281, where h = width between the rows, and a = distance between consecutive vortices in one row. Since von Karman’s investigation was published, writers on the subject have attempted to connect up the street with an obstacle producing it; and to investigate the effect of channel walls upon the stability and spacing ratio of the ideal street. At the same time efforts have been made to verify von Karman’s spacing prediction by experiment, and to check the theoretical conclusions concerning the effect of parallel walls ;§ but the results have been far from satisfactory.
Complex-valued quantitative stiffness estimation using dynamic displacement measurements and local inversion of conservation of momentum

It has been shown that elasticity can be estimated from direct displacement measurements measured using either ultrasonic or magnetic resonance (MRE) elastography methods. Most of the inversion techniques presented in the ultrasound literature are based on inverting a displacement dataset that satisfies a static equation of shear motion resulting in only relative estimates of shear modulus. The authors present a method for estimating absolute shear-wave speed and attenuation from dynamic displacement data based on local inversion of the linearized differential equation satisfied by small-amplitude displacements in a source-free region. The inversion requires knowledge of the spatial derivatives of the displacement which the authors calculate using local, least-square polynomial fits to the data. The authors apply this direct inversion technique to a two dimensional simulated and a three-dimensional measured MRE dataset. The MRE dataset was collected from a phantom composed of a marine-algae gel mixture (1.5% by weight) with an embedded cylinder and sphere composed of the same gel with a higher concentration (3%). In the simulated experiment the authors obtain good agreement with the input values of shear-wave speed while in the phantom dataset they obtain an average value of 4.2/spl plusmn/0.3 m/s wave-speed in the background gel and 9.7/spl plusmn/1.0 m/s in the cylinder and 8.8/spl plusmn/1.0 m/s in the sphere. Finally, the authors report attenuation values for the 1.5% background gel as 17/spl plusmn/12 m/sup -1/. Averaging regions inside the 3%-gel cylinder and 3%-gel sphere gives values of 21/spl plusmn/10 m/sup -1/ and 25/spl plusmn/22 m/sup -1/ respectively.
Perovskite lead zirconium titanate nanorings: Towards nanoscale ferroelectric “solenoids”?

Rings of perovskite lead zirconium titanate (PZT) with internal diameters down to ∼5nm and ring thicknesses of ∼5–10nm have been fabricated and structurally, crystallographically, and chemically characterized using an analytical transmission electron microscope. Ring fabrication involved conformal solution deposition of a thin layer of PZT on the inside of a thin film of anodized aluminum oxide nanopores, and subsequent sectioning of the coated pores perpendicular to their cylinder axes. Although the starting solution used for the solution deposition was made from morphotropic phase boundary PZT, the nanorings were found to be on the zirconium-rich side of the PZT phase diagram. Nevertheless, coatings were found to be of perovskite crystallography. The dimensions of these nanorings are such that they have the potential to demonstrate polarization vortices, as modeled by Naumov et al. [Nature (London) 432, 737 (2004)], and moreover represent the perfect morphology to allow vortex alignment and the creation of the ferroelectric “solenoid” as modeled by Gorbatsevich and Kopaev [Ferroelectrics 161, 321 (1994)]. Rings of perovskite lead zirconium titanate (PZT) with internal diameters down to ∼5nm and ring thicknesses of ∼5–10nm have been fabricated and structurally, crystallographically, and chemically characterized using an analytical transmission electron microscope. Ring fabrication involved conformal solution deposition of a thin layer of PZT on the inside of a thin film of anodized aluminum oxide nanopores, and subsequent sectioning of the coated pores perpendicular to their cylinder axes. Although the starting solution used for the solution deposition was made from morphotropic phase boundary PZT, the nanorings were found to be on the zirconium-rich side of the PZT phase diagram. Nevertheless, coatings were found to be of perovskite crystallography. The dimensions of these nanorings are such that they have the potential to demonstrate polarization vortices, as modeled by Naumov et al. [Nature (London) 432, 737 (2004)], and moreover represent the perfect morphology to allow vortex alignment and the creation.
The effect of network topology on proton trapping in amorphous SiO/sub 2/

We report the results of first-principles quantum chemical calculations of the interactions of H/H/sup +/ with oxide ring structures of varying sizes. The calculations suggest that the binding and stability of protons in amorphous SiO/sub 2/ depend upon the topology of the interacting network. A neutral hydrogen atom, H/sup 0/, does not bind to bridging O atoms in the rings, but may occupy voids within larger rings.
The geometry and the radial breathing mode of carbon nanotubes: beyond the ideal behaviour

First principles calculations using density functional theory were carried out to obtain the geometrical properties and the radial breathing mode (RBM) frequency of 40 different single-walled carbon nanotubes with small diameter. Fourteen chiral nanotubes with diameters less than 0.8 nm were considered, for which the number of atoms in the unit cell is not larger than 200. From the achiral (zigzag, armchair) nanotubes all those having a diameter less than 1.6 nm were considered. The geometrical parameters deviate from the values obtained from simple wrapping of a perfect hexagonal sheet. The deviation from the ideal behaviour increases with increasing curvature. The most prominent change is the increase of the diameter with respect to its ideal value. The lattice constant along the tube axis exhibits a slight shrinking. The RBM frequency does not follow the usually assumed 1/d behaviour; there is a general softening with increasing curvature. The softening of the RBM frequency cannot be described by a simple function of the diameter; it also depends on the chiral angle and the metallicity of the tube. In addition to this, the coupling of the totally symmetric radial motion with the totally symmetric tangential motion(s) has a non-negligible effect.
Bayesian Methods for Nonlinear Classification and Regressing

Preface. Acknowledgements. Introduction. Bayesian Modelling. Curve Fitting. Surface Fitting. Classification using Generalised Nonlinear Models. Bayesian Tree Models. Partition Models. Nearest-Neighbour Models. Multiple Response Models. Appendix A: Probability Distributions. Appendix B: Inferential Processes. References Index. Author Index.
Exact quantum surface of section method

This letter presents exact surface of section reduction of quantum mechanics. The main theoretical result is a decomposition of the resolvent of the autonomous bound Hamiltonian H,(E-H)-1 in terms of the four propagators which propagate from and/or to Hilbert space over the configuration space (CS) to and/or from Hilbert space over the configurational surface of section (CSOS), which has one dimension less than CS. The exact energy quantization condition can be expressed solely in terms of the CSOS-CSOS propagator. All these newly defined energy-dependent (CS/CSOS)-(CS/CSOS) propagators are expressed in terms of the resolvent of the related scattering Hamiltonian.
METALLICITY AND ABUNDANCE RATIOS IN ELLIPTICAL GALAXIES

Using the theoretical results of Barbuy, the variation of the Mg2 index as a function of the stellar parameters ( T eff, log g, [Fe/H]), including the Mg/Fe ratio, is obtained. This allows a new calibration of the metallicity indicators Mg2 and (Fe) through synthetic indices computed for stellar populations having a metallicity spread and ages of the order of 14-16 Gyr. The models indicate that the integrated Mg2 index depends on the chemical history, since it varies not only with the metallicity but also with the average Mg/Fe ratio. The study of a sample of elliptical galaxies shows that on average, [Mg/Fe] = 0.40, comparable to the values observed in metal-poor galactic halo stars. This confirms the early suspicions that elliptical galaxies (Es) had a very high star formation rate in the past, and that the enrichment was caused by massive stars.
Spline approximation with interpolation constraints for numerical integration

By using a Walsh-type theorem, we impose a finite number of interpolation constraints to a polynomial spline approximation operator. These constrained approximating splines reproduce polynomials and give orders of convergence identical to those of the unconstrained ones. We give an application in numerical integration by using the constrained splines for evaluation of Cauchy principal value integrals.
Grouping Optimization Based Hybrid Beamforming for Multiuser MmWave Massive MIMO Systems

In millimeter-wave massive multiple input multiple output multiuser systems, inter-user interference becomes a major factor limiting system capacity. The premise of increasing system capacity is to minimize inter-user interference on the basis of ensuring large receiving power. In response to this situation, this paper proposes a low complexity grouping optimization based hybrid beamforming (HBF) algorithm. Specifically, we group users according to user channel correlation and a correlation threshold. Users with strong correlation are grouped into a group. Then, with the goal of maximizing capacity, the low-dimensional exhaustive algorithm is used in each group to select the base station beamforming vector. Moreover, a greedy algorithm is adopted, i.e., the influence of the beamforming vectors of the previous groups is considered. Simulation results show that the system sum rate of the grouping optimization HBF algorithm is higher than that of the existing HBF algorithms.
Parametrization of instantaneous global horizontal irradiance: clear‐sky component

Based on an accurate atmospheric radiative transfer scheme, a parametrization of instantaneous global horizontal irradiance (GHI) at the Earth's surface has been developed. The scheme is named SUNFLUX and this article describes the development of the scheme for clear‐sky conditions. The work dealing with clouds has been published in a separate article. Unlike traditional methods, this study applies the band model idea used in radiative transfer theory to the development of the surface radiation scheme and, importantly, includes absorption and scattering in the parametrization. Thus the scheme is more accurate compared with those using simple empirical approaches and may be applied to any site without being tuned for local conditions. The parametrization of aerosol transmittance and albedo developed by Kokhanovsky et al. is adopted to account for the effects of aerosols. All variables used in the scheme are available in climate models or from satellite observations. Therefore, the parametrization can be used to determine the GHI at the surface under clear‐sky conditions
Stability conditions for a bivariate arch system which is cointegrated in mean

This note gives necessary and sufficient conditions for covariance stationarity in a bivariate system of individually first-order integrated (i.e. difference-stationary) processes. The two processes are linked by a cointegrating relation and by a special ARCH model that describes their time-changing volatility. The problem of deriving necessary conditions for strict stationarity in this system is demonstrated using Monte Carlo simulation. The conditions of the theorem are highlighted using empirical examples.
Classification of image data in conjugate representation spaces

Over the past few years, automatic multivariate statistical classification techniques have successfully been used for analyzing large and noisy electron-microscopic data sets. After the raw data are compressed with eigenvector–eigenvalue procedures, classes of images are formed, using unsupervised clustering procedures. The classes elucidate even subtle differences existing within the data set. Here we extend these methods to find classes of pixels or features in the images (or other n-dimensional signals) that exhibit a homogeneous statistical behavior throughout the data set. This feature extraction—itself a form of data compression—is mathematically entirely symmetric to the determination of the image classes and also serves the purpose of revealing the information present in the set of input images. The properties of simultaneous representations of the image-space and feature-space data onto the same two-dimensional map are discussed in relation to the metrics used in both spaces. Model data are used to illustrate the basic ideas.
Mesh‐based geometry

A systematic approach to building a complete geometric and topologic representation of a model given only the finite element (FE) description is proposed. The objective of the proposed system is to provide a geometry foundation for existing finite element based models so that standard mesh generation tools can be used without requiring CAD‐based modelling systems such as ACIS or other proprietary commercial tools. To accomplish this, a method for extracting topology from the FE model is proposed. Topology entities including volumes, surfaces, curves and vertices are built based on user‐defined boundary conditions and surface features. Curve and surface geometry is described by either linear triangular facets or G1 continuous 4th‐order Bezier patches. Integration of the proposed mesh‐based geometry (MBG) system into an existing mesh generation toolkit is described. Sample applications and examples of MBG are presented. Published in 2003 by John Wiley & Sons, Ltd.
Eigensolutions for matrices of special structures

In this article, a simple and efficient method is developed for calculating the eigenvalues and eigen vectors of matrices having special structures. This is achieved by decomposing the matrices into specific forms. The application is extended to the eigensolution of the Laplacian matrices of symmetric graphs. Copyright © 2003 John Wiley & Sons, Ltd.
Progress toward Accelogic compression in ROOT

For the last 7 years, Accelogic pioneered and perfected a radically new theory of numerical computing codenamed “Compressive Computing”, which has an extremely profound impact on real-world computer science [1]. At the core of this new theory is the discovery of one of its fundamental theorems which states that, under very general conditions, the vast majority (typically between 70% and 80%) of the bits used in modern large-scale numerical computations are absolutely irrelevant for the accuracy of the end result. This theory of Compressive Computing provides mechanisms able to identify (with high intelligence and surgical accuracy) the number of bits (i.e., the precision) that can be used to represent numbers without affecting the substance of the end results, as they are computed and vary in real time. The bottom-line outcome will be to provide state-of-the-art compression algorithms --and accompanying software libraries-- able to surpass the performance of the compression engines currently available in the ROOT [7] framework. The resulting technology has the capability to enable substantial economic and operational gains (including speedup) for High Energy and Nuclear Physics data storage/analysis. In our initial studies, a factor of nearly x4 (3.9) compression was achieved with RHIC/STAR data where ROOT compression managed only x1.4 [6]. As a collaboration of experimental scientists, private industry, and the ROOT Team, our aim is to capitalize on the substantial success delivered by the initial effort and produce a robust technology properly packaged as an open-source tool that could be used by virtually every experiment around the world as means for improving data management and accessibility. In this contribution, we will present our efforts integrating our concepts of “functionally lossless compression” within the ROOT framework implementation, with the purpose of producing a basic solution readily integrated into HENP applications. We will also present our progress applying this compression through realistic examples of analysis from both the STAR and CMS experiments.
Photochromic liquid-core fibers with nonlinear input-output characteristics

Photochromic liquid-core fibers were fabricated by using benzene or 2-propanol solution of spirobenzopyran. The fiber element consisting of a benzene-solution core and a silica-glass cladding exhibited variable transmittance that was controlled by ultraviolet irradiation. When a visible laser beam (532-nm wavelength) was used as input signal, output signal power increased nonlinearly with input power due to reversed photochromism. This nonlinear input-output characteristic was observed without ultraviolet light, when a fiber was constructed with 2-propanol solution and a polymer-coated glass tube. These experimental results agreed with the theoretical prediction that was based on a simple photochromic fiber model.
Particle Swarm Optimization for Short-Term Scheduling of Thermal-Hydro-Solar Power Generation Systems

Thermal-hydro-solar scheduling is the most difficult power system optimization issue in the modern day. The core mean of the arrangement of thermal-hydro-solar is to decide the most favorable power from thermal, hydro, and solar sources while meeting the various constraints of thermal, hydro, solar, and network. This paper describes the optimum hourly generation schedule plan in a thermal-hydro-solar power network utilizing particle swarm optimization (PSO) approach to attain the best or optimum solutions for scenarios involving three thermal power plants, four hydro power plants and ten solar photovoltaic (PV) plants. The conclusion of the simulation shows that the suggested PSO method seems to be able to minimize fuel costs, and emissions and has improved outcomes performance and strong integration than other approaches.
Anomaly detection of I/O behaviours in HEP computing cluster based on unsupervised machine learning

Problematic I/O pattern is the major cause of low efficient HEP jobs. In a cluster with tens of thousands of job slots, locating the source of an anomalous workload is a nontrivial task. Automatic anomaly detection can largely shorten the recovery time of these situations and reduce manpower for problem diagnoses. This paper provides a data-driven approach to solve this problem. We design and implement an anomaly detection system based on Isolation Forest, a very efficient and scalable machine learning algorithm for spatial anomaly detection in high dimension space. Historical monitoring I/O patterns collected from the Lustre file system provides a sufficient statistical basis for model training and updating. Routine model updates and job tagging ensures adaptability and promptness. Web-based visualization and sorting tools facilitate the validation of model prediction. With the detection system, time spent on tracing the source of a problematic workload can be reduced from hours to minutes.
The effective placing of Shear Wall for Seismic Resistance of G+5 Story building on sloping Ground

The buildings located on the sloped ground are irregular. Therefore, Prone to hard destruction when acted by earthquake forces. These types of buildings have different stiffness and mass in the horizontal and vertical directions. As result, the centre of rigidity and centre of mass does not coincide on a different floor and cause to suffer high damage due to irregularity during an earthquake. Because it is considered that, the seismic performance of the building in a sloped area is much more different from the plain area. Present study deal with the Earthquake manner of the G+5 story building with a shear wall in a hilly area. The fundamental aims are to; investigate the performance of G+5 story building on the sloped area for different positioning of the shear wall, and to understand the impressiveness of SW on a sloped area. In this paper, G+5 story buildings with and without shear walls resting on the sloped ground are observed. Modelling and analysis are done by considering the response spectrum with the assistance of STAAD Pro and different configurations of a shear wall compared with considering story displacement, maximum bending moment, base shear, and axial forces.
An algorithm for no-reference image quality assessment based on log-derivative statistics of natural scenes

In this paper, we propose a new method for blind/no-reference image quality assessment based on the log- derivative statistics of natural scenes. The new method, called DErivative Statistics-based Image QUality Eval- uator (DESIQUE), extracts image quality-related statistical features at two image scales in both the spatial and frequency domains, upon which a two-stage framework is employed to evaluate image quality. In the spatial domain, normalized luminance values of an image are modeled in two ways: point-wise based statistics for sin- gle pixel values and pairwise-based log-derivative statistics for the relationship of pixel pairs. In the frequency domain, log-Gabor filters are used to extract the high frequency component of an image, which is also modeled by the log-derivative statistics. All of these statistics are characterized by a generalized Gaussian distribution model, the parameters of which form the underlying features of the proposed method. Experiment results show that DESIQUE not only leads to considerable performance improvements, but also maintains high computational efficiency.
Evaluation and Implementation of Various Persistent Storage Options for CMSWEB Services in Kubernetes Infrastructure at CERN

This paper summarizes the various storage options that we implemented for the CMSWEB cluster in Kubernetes infrastructure. All CMSWEB services require storage for logs, while some services also require storage for data. We also provide a feasibility analysis of various storage options and describe the pros/cons of each technique from the perspective of the CMSWEB cluster and its users. In the end, we also propose recommendations according to the service needs. The first option is the CephFS which can be mounted multiple times across various clusters and VMs and works very well with k8s. We use it both for data and the logs. The second option is the Cinder volume. It is the block storage that runs the filesystem on top of it. It can only be attached to one instance at a time. We use this option only for the data. The third option is S3 storage. It is object storage that offers a scalable storage service that can be used by applications compatible with the Amazon S3 protocol. It is used for the logs. For S3, we explored two mechanisms. For the first scenario, we consider fluentd that runs as a sidecar container in the service pods and sends logs to S3 bucket. For the second scenario, we considered filebeat that runs as a sidecar container in the service pod and scaps those logs to fluentd which runs as a daemonset in each node and sends those logs to S3 in the end. The fourth option is EOS. We configured EOS inside the pods of the CMSWEB services. The fifth option that we explored is to use dedicated VMs that have Ceph volume attached to them. In EOS and VM, the logs from the service pods are sent to EOS/VM using the rsync approach. The last option is to send service logs to Elasticsearch. It has been implemented using fluentd that runs as a daemonset in each node. In parallel to the sending logs to S3 fluentd also sends those logs to the Elasticsearch infrastructure at CERN.