bluuebunny/crossref_metadata_2025_split huggingface dataset:
The simulation study of damage assessment of a surface-to-air missile system attacked by an anti-radiation missile and the optimization of fuze-warhead coordination
Authors: Zhang Zh B , Wang Y Sh , Cao Y 
Published: July 2020

Abstract
The final damage effectiveness of warhead is the most important objective in missile system design. To obtain the damage probability of a certain anti-radiation missile warhead against a typical field surface-to-air missile system and find the optimal fuze-warhead coordination strategy, the studies of modelling, simulation and optimization are carried out. First, the vulnerability of the target is analysed and the target vulnerability model is established. Secondly, the calculation models of fragments field and over-pressure field are established to realize the calculation of encounter between warhead and target. Finally, the damage assessment model is established to calculate the damage probability of the parts and the whole system. Through Monte Carlo simulation, the single-shot damage probability of the missile is obtained when the parameters of the encounter between warhead and target are randomly selected according to a certain probability distribution. And the optimal fuze control strategies of the missile at different entrance angles are obtained through optimization calculation. If the entrance angle of the missile cannot be identified, the optimal fuze initiation strategy of the anti-radiation missile in this paper is a delay of 13ms. The results show that the research method of this paper can be applied to the missile weapon system with the function of entrance angle identification to maximize the damage efficiency.
Programming possibilities using MATLAB simulink embedded coder on the example of data analysis from ahrs module
Authors: Elert S 
Published: July 2020

Abstract
This paper shows capabilities to program Texas Instruments TMS320F2839xD DSP (Digital Signal Processor) using MATLAB Simulink Embedded Coder on the example of receiving and processing data from VN-100 AHRS module. The first part of article described specification of C2000 Delfino MCU F28379D LaunchPad development kit and AHRS module. Next part prensents physical connection VN-100 module with microcontroller and configuration method to setup MATLAB Simulink and Embedded Coder for selected microcontroller. Presented program in MATLAB Simulink shows communication between AHRS module. VN-100 and microcontroller treated as receiver. Also It shows how to generate code and described the basic functions that were used to run application. The designed system is explained as a photos from MATLAB and real tests. The last part of paper demonstrates graphic preview of microcontroller load possible during operation and advantages of programming using MATLAB Simulink Embedded Coder.
Error spectrum full range convergence technique for laser optics element
Authors: Wang Zh B , Zhang Y L , Jiao M Y , Zhang F , Zhang Zh 
Published: July 2020

Abstract
In the application of laser optics, it requires well surface roughness and profile to reduce the laser energy losing. Such as ultra-smooth processing technology is generally used for processing optical components to meet the surface quality requirements. However, traditional elevation parameters PV(Peak-Valley)/RMS(Root Mean Square) are not enough to meet the optics demand. Error Spectrum distribution is an important technical index to be concerned in the field of ultra-high power laser. Different spectral errors cause different laser energy losing. So it is necessary to explore the error full-spectral convergence processing technology. In this paper, basing on the discussion of error spectrum Evaluation methods, the full spectral range converges technology is introduced to meet the demands of high power laser.
MCSANCee generator with one-loop electroweak corrections for processes with polarized e+e- beams
Authors: Sadykov R R , Arbuzov A B , Bondarenko S G , Dydyshka Ya V , Kalinovskaya L V , Novikov I I , Yermolchyk V L , Rumyantsev L A 
Published: July 2020

Abstract
A new Monte Carlo event generator MCSANCee for simulations of processes at future e+e− colliders is presented. Complete one-loop electroweak radiative corrections and polarization of the initial beams are taken into account. The present generator includes the following processes:

e
+

e
−

→

e
+

e
−

,

μ
+

μ
−

,

τ
+

τ
−

,
Z
H

. Numerical results for the

e
+

e
−

→
Z
H

process are shown. Plans for the further extension of the MCSANCee generator are discussed.
Computer algebra with Rings library
Authors: Poslavsky Stanislav 
Published: July 2020

Abstract
Implementation of modern algorithms in computer algebra requires the use of generic and high-performance instruments. Rings is an open-source library, written in Java and Scala programming languages, which implements basic concepts and algorithms from computational commutative algebra while demonstrating quite a high performance among existing software. It rigorously uses generic programming approach, providing a well-designed generic API with a fully typed hierarchy of algebraic structures and algorithms for commutative algebra. Polynomial arithmetic, GCDs, factorization, and Gröbner bases are implemented with the use of modern asymptotically fast algorithms. The use of the Scala language brings a quite novel powerful, strongly typed functional programming model allowing to write short, expressive, and fast code for applications in high-energy physics and other research areas.
Declarative analysis in “Troitsk nu-mass” experiment
Authors: Nozik Alexander 
Published: July 2020

Abstract
The modern scientific data processing is not only a collection of powerful algorithms but also a whole infrastructure of facilities for data reading, processing, and results output. As the amount of data grows, so grows a need for automation of the process. The proper automation requires not only improvement of existing frameworks, but also a search of new ways to organize data processing in a way it could be automated and parallelized. DataForge experimental framework solves some problems by making the analysis configuration declarative instead of imperative. In this article, we present a limited demonstration of the idea applied to “Troitsk nu-mass” experiment in the search for sterile neutrino.
An innovative monitoring and maintenance model for the INFN CNAF Tier-1 data center infrastructure
Authors: Ricci P P , Donatelli M , Onofri M , Scarponi L B , Velardo A 
Published: July 2020

Abstract
During the last years we have carried out a renewal of the Building Management System (BMS) software of our data center with the aim of improving the data collection capability. Considering the complex physical distribution of the technical plants and the limits of the actual building hosting our center, a system that simply monitors and collects all the necessary information and provides alarms only in case of major failures has proven to be unsatisfactory. In 2017 we suffered a major flood due to one main water pipeline failure in the public street. After this disastrous event, clearly far beyond our control, we were however forced to reconsider completely the physical site robustness of our building in addition to the current monitoring and alarm system capabilities. It was clear that in some specific cases, alerts should be triggered hours or days before the actual main problem arises in order to allow efficient human intervention and proper escalation process. This paradigm could be easily applied to almost all the infrastructure components in our site, mainly the electric power distribution and continuity systems as well as the whole cooling devices. For this reason, in parallel to a consistent increase in the sensor widespread distribution of our BMS data collector system, a study of a predictive maintenance approach applicability to our site has been started. Predictive maintenance techniques aims at prevent unexpected infrastructure components failures or major events with the study of the whole monitoring data collection and the creation of appropriate statistical models with the help of big data analysis and machine learning techniques. An improvement in the Power Distribution Units (PDUs) monitoring in our site and the introduction of a dedicated network of water leak sensors were the first steps for increasing the data collection information at our disposal. With sufficient monitoring statistical information stored in our BMS system a preliminary and exploratory predictive data analysis proof of concept could be constructed. This could lead to the model building phase and the creation of a prototype with the aim of forecasting future infrastructure main failure events and forthcoming error conditions. The general idea is, conceivably, an approach to the predictive maintenance model where it would be possible to introduce scheduled corrective actions for the purpose of preventing potential failures in the next future and increasing the site overall reliability.
Fips: An OpenGL based FITS viewer
Authors: Kornilov Matwey , Malanchev Konstantin 
Published: July 2020

Abstract
FITS (Flexible Image Transport System) is a common format for astronomical data storage. [1]. Even though astronomical data is now processed mostly using software, visual data inspection by a human is still important during equipment or software commissioning and while observing. We present Fips [2, 3], a cross-platform FITS file viewer released as open source software1. To the best of our knowledge, it is for the first time that the image rendering algorithms are implemented mostly on GPU (graphics processing unit). We show that it is possible to implement a fully-capable FITS viewer using OpenGL [4] interface, including movie support for representing 3D data. We also emphasise the advantages of using GPUs for efficient image handling.
A Virtualized Tier-3g Facility Installation for WLCG Network of CERN
Authors: Saygın H. , Kuday S. , Alici A. , Turk Cakir I. 
Published: July 2020

Abstract
A Tier-3g Facility within the computing resources of Istanbul Aydin University has been planned and installed with the TR-ULAKBIM national Tier-2 center. The facility is intended to provide an upgraded data analysis infrastructure to CERN researchers who are the members in the recent nation-wide projects and international projects such as ATLAS and CMS experiments. The fundamental design of Tier-3g has been detailed in this work with an emphasis on technical implementations of the following parts: Virtualization of all nodes, VOMS usage for reaching fast experimental data in the WLCG network, batch cluster / multicore computing with HTCONDOR and PROOF systems, usage of grid proxies to access code libraries in AFS and CVMFS, dynamic disk space allocation and remote system mounting of EOS. We also present the interpretation of test results that was obtained by the simulation of typical analysis codes.
New ROOT graphics language
Authors: Betsou Iliana , Linev Serguei , Bellenot Bertrand , Couet Olivier 
Published: July 2020

Abstract
In the context of ROOT7, the graphics system is completely redefined. Based on client server architecture and with the use of modern C++ and JavaScript, ROOT7 provides a new web based graphics system. The new concepts of ROOT7 can be displayed directly in the browsers using the new classes for opening a new web window, communicate with the server and exchange data between front and back end and JavaScript ROOT (JSROOT).
JupyterLab at the Saint Petersburg State University
Authors: Erokhin Andrey , Zarochentsev Andrey 
Published: July 2020

Abstract
This paper describes our experience using and extending JupyterLab. We started with a copy of CERN SWAN environment, but now our project evolves independently. A major difference is that we switched from classic Jupyter Notebook to JupyterLab, because our users are more insterested in text editor plus terminal workflow rather than in Notebook workflow. However, like in SWAN, we are still using CVMFS to load Jupyter kernels and other software packages, and EOS to store user home directories.
Overall quality optimization for DQM stage in High Energy Physics experiments
Authors: Benekos N , Parra-Royon M , Benitez J M 
Published: July 2020

Abstract
Data Acquisition (DAQ) and Data Quality Monitoring (DQM) are key parts in the HEP data chain, where the data are processed and analyzed to obtain accurate monitoring quality indicators. Such stages are complex, including an intense processing work-flow and requiring a high degree of interoperability between software and hardware facilities. Data recorded by DAQ sensors and devices are sampled to perform live (and offline) DQM of the status of the detector during data collection providing to the system and scientists the ability to identify problems with extremely low latency, minimizing the amount of data that would otherwise be unsuitable for physical analysis. DQM stage performs a large set of operations (Fast Fourier Transform (FFT), clustering, classification algorithms, Region of Interest, particles tracking, etc.) involving the use of computing resources and time, depending on the number of events of the experiment, sampling data, complexity of the tasks or the quality performance. The objective of our work is to show a proposal with aim of developing a general optimization of the DQM stage considering all these elements. Techniques based on computational intelligence like EA can help improve the performance and therefore achieve an optimization of task scheduling in DQM.
The DQM system for the SND detector
Authors: Pugachev K. V. , Kardapoltsev L. V. , Korol A. A. 
Published: July 2020

Abstract
The SND detector has been operating at the VEPP-2000 collider (BINP, Russia) for several years. We present its new DQM system.
The system deals with multiple parameters being numbers, histograms or user opinions to form a data quality decision (good, bad, etc). It calculates SND subsystem and overall statuses and produces summaries available via web-interface. The system supports multiple parameter sets for different usages like daily checks, precise subsystem control, preparing data for processing, etc. The parameter values are analyzed using special ROOT macros yielding quality checks that could be supplemented or corrected by users.
The system is a part of a new SND information system implemented as a web application using Node.js and MySQL. The ROOT macros are written by SND subsystems experts using a simple framework. Histograms are displayed using JSROOT.
The system is put into production. It is consistent, however there are some improvements to implement.
Next Generation of HEP CPU benchmarks
Authors: Giordano Domenico , Santorinaiou Evangelia 
Published: July 2020

Abstract
HEPSPEC-06(HS06) is a decade old suite used to benchmark CPU resources for WLCG. Its adoption spans from hardware vendors, to site managers, funding agencies and software experts. Although it is stable, reproducible and accurate, it is reaching the end of its life. Initial hints of lack of correlations with HEP applications have been collected. Looking for suitable alternatives the HEPiX Benchmarking Working Group has evaluated SPEC CPU 2017 with a number of fast benchmarks. The studies that have been done so far do not show any major advantage in adopting SPEC CPU 2017 with respect to HS06.
A suite based on workloads that HEP experiments run can be an alternative to industrial standard benchmarks. The adoption by LHC experiments of modern software development techniques simplifies the ability to package, distribute and maintain a field-specific benchmark suite. The HEPiX Benchmarking Working Group is actively working to make this possible.
This report summarises the progress of the HEPiX Benchmarking Working Group in building a benchmarking suite based on HEP workloads. Comparisons of results with SPEC CPU 2017 and HS06 will be discussed.
Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures with the CMS Detector
Authors: Cerati G , Elmer P , Gravelle B , Kortelainen M , Krutelyov V , Lantz S , Masciovecchio M , McDermott K , Norris B , Reinsvold Hall A , Riley D , Tadel M , Wittich P , Würthwein F , Yagil A 
Published: July 2020

Abstract
In the High–Luminosity Large Hadron Collider (HL–LHC), one of the most challenging computational problems is expected to be finding and fitting charged-particle tracks during event reconstruction. The methods currently in use at the LHC are based on the Kalman filter. Such methods have shown to be robust and to provide good physics performance, both in the trigger and offline. In order to improve computational performance, we explored Kalman-filter-based methods for track finding and fitting, adapted for many-core SIMD (single instruction, multiple data) and SIMT (single instruction, multiple thread) architectures. Our adapted Kalman-filter-based software has obtained significant parallel speedups using such processors, e.g., Intel Xeon Phi, Intel Xeon SP (Scalable Processors) and (to a limited degree) NVIDIA GPUs. Recently, an effort has started towards the integration of our software into the CMS software framework, in view of its exploitation for the Run III of the LHC. Prior reports have shown that our software allows in fact for some significant improvements over the existing framework in terms of computational performance with comparable physics performance, even when applied to realistic detector configurations and event complexity. Here, we demonstrate that in such conditions physics performance can be further improved with respect to our prior reports, while retaining the improvements in computational performance, by making use of the knowledge of the detector and its geometry.
Selective background Monte Carlo simulation at Belle II
Authors: Kahn James , Kuhr Thomas , Ritter Martin 
Published: July 2020

Abstract
The Belle II experiment, beginning data taking with the full detector in early 2019, is expected to produce a volume of data ffty times that of its predecessor. This dramatic increase in data comes the opportunity for studies of rare previously inaccessible processes. The investigation of such rare processes in a high data-volume environment requires a correspondingly high volume of Monte Carlo simulations to prepare analyses and gain a deep understanding of the contributing physics processes to each individual study. This presents a signifcant challenge in terms of computing resource requirements and calls for more intelligent methods of simulation, in particular background processes with very high rejection rates. This work presents a method of predicting in the early stages of the simulation process the likelihood of relevancy of an individual event to the target study using convolutional neural networks. The results show a robust training that is integrated natively into the existing Belle II analysis software framework.
A 3D track finder for the Belle II CDC L1 trigger
Authors: Skambraks Sebastian , Bähr Steffen , Becker Jürgen , Kiesling Christian , McCarney Sara , Meggendorfer Felix , Tonder Raynette van , Lukas Unger Kai 
Published: July 2020

Abstract
Machine learning methods are integrated into the pipelined first level (L1) track trigger of the upgraded flavor physics experiment Belle II at KEK in Tsukuba, Japan. The novel triggering techniques cope with the severe background from events outside the small collision region provided by the new SuperKEKB asymmetric-energy electron-positron collider. Using the precise drift-time information of the central drift chamber which provides axial and stereo wire layers, a neural network L1 trigger estimates the 3D track parameters of tracks, based on input from the axial wire planes provided by a 2D track finder. An extension of this 2D Hough track finder to a 3D finder is proposed, where the single hit representations in the Hough plane are trained using Monte Carlo. This 3D finder improves the track finding efficiency by including the stereo sense wires as input. The estimated polar track angle allows a specialization of the subsequent neural networks to sectors in the polar angle.
Physics inspired feature engineering with Lorentz Boost Networks
Authors: Erdmann M , Geiser E , Rath Y , Rieger M 
Published: July 2020

Abstract
We present a neural network architecture designed to autonomously create characteristic features of high energy physics collision events from basic four-vector information. It consists of two stages, the first of which we call the Lorentz Boost Network (LBN). The LBN creates composite particles and rest frames from the combination of final state particles, and then boosts said particles into their corresponding rest frames. From these boosted particles, characteristic features are created and used by the second network stage to solve a given physics problem. We apply our model to the task of separating top-quark pair associated Higgs boson events from a

t

t
¯

background, and observe improved performance compared to using domain unspecific deep neural networks. We also investigate the learned combinations and boosts to gain insights into what the network is learning.
Fabrication and characterization of ultrathin spin-coated poly(L-lactic acid) films suitable for cell attachment and curcumin loading
Authors: Kulikouskaya Viktoryia , Chyshankou Ihnat , Pinchuk Sergei , Vasilevich Irina , Volotovski Igor , Agabekov Vladimir 
Published: July 2020

Abstract
In the present study, ultrathin poly(L-lactic acid) (PLLA) films were fabricated using the spin-coating technique. Physicochemical properties of the formed materials, including their morphology, thickness, transparency, and contact angle, have been studied. We determined that the morphology of PLLA films could be regulated by changing the polymer concentration and humidity. By altering the humidity, microporous and flat PLLA films can be fabricated. The obtained samples were subsequently used for culturing mesenchymal stem cells and fibroblasts. It has been determined that cells effectively adhered to prepared films and formed on them a monolayer culture with high viability. It has been shown that PLLA films are suitable for the entrapment of curcumin (up to 12.1 μm cm−2) and provide its sustained release in solutions isotonic to blood plasma. The obtained PLLA films appear to be prospective materials for potential application in regenerative medicine as part of cell-containing tissue engineered dressings for chronic wound treatment.