bluuebunny/crossref_metadata_2025_split huggingface dataset:
Particle identification using semi-supervised learning in the PICO-60 dark matter detector
Authors: Matusch Brendon , Cao Gevy 
Published: July 2020

Abstract
Astrophysical observations have demonstrated the existence of dark matter over the past decades. Experimental efforts in the search for dark matter are largely focused on the well-motivated weakly interacting massive particles (WIMPs) as a dark matter candidate. Current experiments in direct detection are producing increasingly competitive limits on the cross section of WIMP-nucleon scattering. The main experimental challenge for all direct detection experiments is the presence of background signals. These backgrounds need to be either eliminated by providing sufficient shielding or discriminated from WIMP signals. In this work, semi-supervised learning techniques are developed to discriminate alpha recoils from nuclear recoils induced by WIMPs in the PICO-60 detector. The two semi-supervised learning techniques, gravitational differentiation and iterative cluster nucleation, maximize the effect of the most confidently predicted data samples on subsequent training iterations. Classifications using both techniques can reproduce the traditional acoustic parameter with accuracies over 98%. The best model yields an accuracy of 99.2% and a class-wise standard deviation value of 0.11. These techniques can reliably serve as an intermediate verification tool before the acoustic parameter is constructed in future detectors.
Accelerating dark matter search in emulsion SHiP detector by deep learning
Authors: Shirobokov S K , Ustyuzhanin A E , Golutvin A I 
Published: July 2020

Abstract
We introduce a novel approach for the reconstruction of particle properties for the SHiP detector. The SHiP experiment significantly focuses on finding effects of dark matter particle interaction. A characteristic trace of such an interaction is an electromagnetic shower. Our algorithm aims to reconstruct the energy and origin of such showers using online Target Tracker subdetectors that do not suffer from pile-up. Thus, the online observation of the excess of events with proper energy can be a signal for a dark matter. Two different approaches were applied: classical, using Gaussian Mixtures and machine learning based on a convolutional neural network. We’ve refined the output of the previous step by clusterization techniques to improve transverse coordinate estimation. The obtained results are 25% for energy resolution, 0.8 cm for position resolution in the longitudinal direction and 1 mm in the transverse direction, without any usage of the emulsion.
Reinforced sorting networks for particle physics analyses
Authors: Erdmann Martin , Fischer Benjamin , Noll Dennis 
Published: July 2020

Abstract
Deep learning architectures in particle physics are often strongly dependent on the order of their input variables. We present a two-stage deep learning architecture consisting of a network for sorting input objects and a subsequent network for data analysis. The sorting network (agent) is trained through reinforcement learning using feedback from the analysis network (environment). The optimal order depends on the environment and is learned by the agent in an unsupervised approach. Thus, the two-stage system can choose an optimal solution which is not known to the physicist in advance. We present the new approach and its application to the signal and background separation in top-quark pair associated Higgs boson production.
Vectorization techniques for probability distribution functions using VecCore
Authors: Chaparro Amaro Oscar R. , Martínez-Castro J. , Yung Jun Soon 
Published: July 2020

Abstract
Probability distribution functions (PDFs) are very used in modeling random processes and physics simulations. Improving the performance of algorithms that generate many random numbers under complex PDFs is often a very challenging task when methods as direct functions are not available. In this work we present general strategies on how to vectorize some PDFs using VecCore library. We show the results for the Exponential, Gaussian, discrete Poisson and Gamma probability distributions.
Jet Grooming through Reinforcement Learning
Authors: Carrazza Stefano , Dreyer Frédéric A. 
Published: July 2020

Abstract
We introduce a novel implementation of a reinforcement learning (RL) algorithm which is designed to find an optimal jet grooming strategy, a critical tool for collider experiments. The RL agent is trained with a reward function constructed to optimize the resulting jet properties, using both signal and background samples in a simultaneous multi-level training. We show that the grooming algorithm derived from the deep RL agent can match state-of-the-art techniques used at the Large Hadron Collider, resulting in improved mass resolution for boosted objects. Given a suitable reward function, the agent learns how to train a policy which optimally removes soft wide-angle radiation, allowing for a modular grooming technique that can be applied in a wide range of contexts. These results are accessible through the corresponding GroomRL framework.
Deep Learning based Algorithms in Astroparticle Physics
Authors: Erdmann Martin , Glombitza Jonas 
Published: July 2020

Abstract
In recent years, great progress has been made in the fields of machine translation, image classification and speech recognition by using deep neural networks and associated techniques (deep learning). Recently, the astroparticle physics community successfully adapted supervised learning algorithms for a wide range of tasks including background rejection, object reconstruction, track segmentation and the denoising of signals. Additionally, the first approaches towards fast simulations and simulation refinement indicate the huge potential of unsupervised learning for astroparticle physics. We summarize the latest results, discuss the algorithms and challenges and further illustrate the opportunities for the astrophysics community offered by deep learning based algorithms.
Making RooFit Ready for Run 3
Authors: Hageböck S , Moneta L 
Published: July 2020

Abstract
RooFit and RooStats, the toolkits for statistical modelling in ROOT, are used in most searches and measurements at the Large Hadron Collider. The data to be collected in Run 3 will enable measurements with higher precision and models with larger complexity, but also require faster data processing.
In this work, first results on modernising RooFit’s collections, restructuring data flow and vectorising likelihood fits in RooFit will be discussed. These improvements will enable the LHC experiments to process larger datasets without having to compromise with respect to model complexity, as fitting times would increase significantly with the large datasets to be expected in Run 3.
GRAAL: Gem Reconstruction And Analysis Library
Authors: Farinelli R. , Alexeev M. , Amoroso A. , Bagnasco S. , Baldini Ferroli R. , Balossino I. , Bertani M. , Bettoni D. , Bortone A. , Bianchi F. , Calcaterra A. , Cerioni S. , Chai J. , Cheng W. , Chiozzi S. , Cibinetto G. , Cossio F. , Cotta Ramusino A. , Cotto G. , Da Rocha Rolo M. , De Mori F. , Destefanis M. , Evangelisti F. , Fava L. , Felici G. , Gaido L. , Garzia I. , Gatta M. , Giraudo G. , Gramigna S. , Greco M. , Lavezzi L. , Lusso S. , Li H. , Maggiora M. , Malaguti R. , Mangoni A. , Marcello S. , Melchiorri M. , Mezzadri G. , Mignone M. , Pacetti S. , Patteri P. , Passalacqua B. , Rivetti A. , Savrié M. , Sosio S. , Spataro S. , Tskhadadze E. , Yan L. , Wheadon R. J. 
Published: July 2020

Abstract
Micro Pattern Gas Detectors (MPGD) are the new frontier in gas trackers. Among this kind of devices, the Gas Electron Multiplier (GEM) chambers are widely used. The experimental signals acquired with the detector must obviously be reconstructed and analysed. In this contribution, a new offline software to perform reconstruction, alignment and analysis on the data collected with APV-25 and TIGER ASICs will be presented. GRAAL (Gem Reconstruction And Analysis Library) is able to measure the performance of a MPGD detector with a strip segmented anode (presently). The code is divided in three parts: reconstruction, where the hits are digitized and clusterized; tracking, where a procedure fits the points from the tracking system and uses that information to align the chamber with rotations and shifts; analysis, where the performance is evaluated (e.g. efficiency, spatial resolution,etc.). The user must set the geometry of the setup and then the program returns automatically the analysis results, taking care of different conditions of gas mixture, electric field, magnetic field, geometries, strip orientation, dead strip, misalignment and many others.
A multifunctional silk coating on additively manufactured porous titanium to prevent implant-associated infection and stimulate bone regeneration
Authors: Gorgin Karaji Z , Jahanmard F , Mirzaei A H , van der Wal B , Amin Yavari S 
Published: July 2020

Abstract
Despite tremendous progress in the design and manufacturing of metallic implants, they do not outlive the patient. To illustrate, more than half of hip replacements will fail, mainly due to implant infection and loosening. Surface engineering approaches and, in particular, coatings can facilitate implant bio-functionality via the recruitment of more host cells for new bone formation and inhibition of bacterial colonization. Here, we used electrophoretic deposition to apply a silk fibroin solution consisting of tricalcium phosphate (TCP) and vancomycin as a coating on the surface of additively-manufactured porous titanium. Furthermore, the surface properties of the coatings developed and the release kinetics of the vancomycin were studied to evaluate the applied coating. The in vitro antibacterial behavior of the multifunctional coating, as well as the cell viability and osteogenic differentiation of the MC3T3-E1 cell line were extensively studied. The biomaterials developed exhibited an antibacterial behavior with a reduction of up to four orders of magnitude in both planktonic and adherent bacteria for 6 h and 1 d. A live-dead assay, the Alamar Blue activity, the DNA content, and cytoskeleton staining demonstrated a significant increase in the cell density of the coated groups versus the as-manufactured ones. The significantly enhanced calcium deposition and the increase in mineralization for the groups with TCP after 21 and 28 d, respectively, demonstrate upregulation of the MC3T3 cells’ osteogenic differentiation. Our results collectively show that the multifunctional coating studied here can be potentially used to develop a new generation of orthopedic implants.
Study on the Optimal Travel Route Selection Based on Ant Colony Algorithm Model
Authors: Sang Senyao 
Published: July 2020

Abstract
Based on the perspective of travel agencies, this paper focuses on the optimization of tourist traffic routes, and divides the optimization of tourist traffic routes into “one day tour”, the optimization of tourist traffic routes and the optimization of “multi day tour” tourist traffic routes. The objective function of tourism traffic route optimization is improved by using principal component analysis. Finally, the ant colony algorithm is used to model, which completes the research based on the ant colony algorithm model to select the best tourism route, so that the travel agency get the most benefits and the tourists enjoy the most humane experience.
Research on the Monitoring and Response Mechanism of Earthquake Public Opinion
Authors: Gao Shuang , Li Xiaojun , Bo Tao 
Published: July 2020

Abstract
Earthquake public opinion along with the development of online media platforms has become an important part of earthquake public opinion monitoring. In order to strengthen the monitoring of public opinion on the seismic network, scientifically respond to the public opinion on the seismic network, and effectively disseminate seismic information, we analyze the content of the public opinion on the seismic network, the characteristics of the public opinion, the monitoring of the public opinion, and the response mechanism of the public opinion on the earthquake.
Air Quality Analysis of Wuhan from the Perspective of Functional Data
Authors: Chen Guici , Zhang Zuo , Zuo Qian 
Published: July 2020

Abstract
In recent years, with the continuous advancement of Wuhan’s industry, manufacturing and engineering construction, the consumption of energy is also increasing, and the air quality problems caused by it have also received attention from all walks of life. In order to explore the characteristics of air pollution in Wuhan, this paper uses functional data analysis methods to study air quality (AQI) from the perspective of space and time. The results show that 13 prefecture-level cities in Wuhan can be divided into 4 levels according to the quality of air quality. In general, Xinzhou District, Huang pi District, Jiangxia District and Hannan District have the best air quality, while Qingshan District and Dongxihu District have the worst air quality; all have significant seasonal characteristics in the time dimension, that is, winter is a high-frequency band with serious air pollution.
Screening of rhizosphere growth promoting bacteria and their growth promoting ability of sunflower in cold black soil area
Authors: Zou Danzhi , Zheng Hongjuan , Zhang Yaosheng , Gu Ye , Cao Yajie , Song Yujun , Li Lan 
Published: July 2020

Abstract
High efficient growth promoting bacteria were screened from the rhizosphere soil of sunflower in the cold black soil area, and their growth promoting ability was tested to obtain the strains with comprehensive growth promoting ability. The phosphate solubilizing bacteria were screened out by inorganic phosphate bacteria culture medium, the phosphate solubilizing ability of the strain was determined by mo sb anti chromogenic method, the indoleacetic acid producing ability of the strain was determined by salkowski method, the iron carrier producing ability of the strain was determined by CAS method, and the growth promoting ability of the strain was evaluated comprehensively. Eleven strains of phosphate solubilizing bacteria were isolated and screened from soil samples. Among them, strain WP2 had the strongest phosphate solubilizing ability, and the concentration of phosphate radical was 12.75 μg/mL; strain WP1 had the strongest indoleacetic acid producing ability, and the concentration of indoleacetic acid was 25.37μg/mL; strain WP1 had the strongest iron producing ability, with Su = 72.76%, and the strength was 4+. It was found that WP1, WP2 and WP10 had strong ability of promoting growth and had strong potential of development and utilization. The above results can provide excellent strains for the development and promotion of special bio fertilizer suitable for the cold black soil.
Test and Analysis of Vibration Mode of Distribution Transformer Tank Structure
Authors: Wang Guangzhou , Yao Degui , Ma Yuchao , Zhang Songyang , Wang Guangke , Xu Lianhuan , Wang Leilei 
Published: July 2020

Abstract
Along with the social and economic development and continuous increasing of electrical load, power distribution network has its scale continuously expanded, and more and more distribution transformers go deep into the urban residential areas, leading to increasingly serious vibration and noise problems. Relying on a typical 35 kV distribution transformer, a vibration mode test was done on the tank structure of the distribution transformer, and PolyLSCF fitting method was adopted to obtain the first 10-order modal shape in this paper. Meanwhile, finite element model was built for distribution transformer tank, and contrastive analysis were done in combination with the measured data to obtain the rules of influence on vibration mode of distribution transformer by tank wall thickness. The vibration characteristics acquired by measured mode of distribution transformer are consistent with those obtained by numerical simulation, and the central vibration amplitude of the tank is the maximum. Along with the increase of wall thickness, the low-order mode of the tank structure shows insignificant change, and high-order mode frequency reduces, thus providing measured data reference for optimizing the tank structure of distribution transformer.
Study on Support Optimization of mining roadway in deep steeply dipping coal seam
Authors: Sang Fengyu , Huang jing , Zhao Baoxiang 
Published: July 2020

Abstract
In order to solve the problem of the failure phenomenon of roof fall and the inward extrusion of two roadsides in main roadway of 31205 working face of Zhubai coal mine, the theoretical analysis, field measurement and numerical simulation were adopted to study the rock breakage and instability of roadway’s and put forward the differential anchor cable and bolt targeted support solution. Industrial tests and the roadway pressure observation were carried out in 31205 main roadway. The field application results showed that the deformation and break of roadway surrounding rock is effectively controlled, the supporting cost was reduced and the supporting effect was remarkable.
A New Method for Predicting Water Breakthrough Time in the Edge Water Condensate Gas Reservoir
Authors: Huang Quanhua , Lin Xingyu , Xu Qinglong , He Yunjun 
Published: July 2020

Abstract
The influence of condensate oil is often ignored when people predict the water breakthrough time of condensate gas reservoirs, leading to a certain difference between the prediction and the actual results. In order to efficiently and scientifically develop the edge water condensate gas reservoir, it is necessary to consider the influence of the precipitated condensate oil when making reasonable predictions on the water breakthrough time. Based on the basic law of gas-water two-phase percolation, this paper simplified the water inlet process as the migration of water particles to the well bottom, with the influence of condensate oil precipitation taken into consideration. In this meantime, this paper derived a new model for predicting the breakthrough time of the edge water condensate gas reservoir based on the idea that the change of condensate saturation varies with time and the distance from well bottom. Case studies show that the lower the permeability, the greater the influence of condensate oil precipitation on water breakthrough time; the farther the well bottom is from the initial gas-water boundary, the longer the water breakthrough time; the effect of condensate oil cannot be ignored during the prediction of the water breakthrough time in the edge water condensate gas reservoir. The new model considers the dual effects of time and location on the condensate saturation, which is more in line with the actual situation of the change of condensate saturation in the formation.
GSM-R wireless field strength coverage prediction algorithm based on GA-BP algorithm
Authors: Jin Xiang , Zheng Yunshui 
Published: July 2020

Abstract
With the opening of multiple railway lines, newly-built routes are adjacent to, close to, and overcoming existing routes. If you do not consider the network coverage of adjacent lines in future planning in the early construction of the lines, you need to adjust the original The reconstruction of the line network coverage has increased the difficulty of construction and investment costs. In this paper, based on the genetic algorithm and BP artificial neural network, a GSM-R wireless network communication field strength prediction model is established. Combined with the field strength measured data of the base station, the GA-BP neural network model is compared with the traditional HATA model and BP neural network model. The comparison and verification show that the model has greatly improved the accuracy of prediction compared with the HATA model and the BP neural network model. It provides a feasible theoretical basis for the subsequent construction of railway parallel GSM-R wireless network coverage design.
Structure Design of Multi-joint Bionic Robot Based on Solidworks
Authors: Xu KaiJie , Wang Rihe , Lu Yaping 
Published: July 2020

Abstract
The body structure of the multi joint bionic robot is designed and analyzed. According to the movement form of snake and caterpillar, a multi joint bionic robot is designed and manufactured based on the principle of bionics. Using SolidWorks software to establish the model, there are three parts: head joint, body joint and tail joint. The bionic robot uses 3D technology to be printed and make a physical prototype, and experiment with the prototype. It can imitate the movement of snakes and caterpillars, and realize snake movement, insect movement, turning, curling, lurking and other movements. Through the structural design, processing and manufacturing of the multi joint bionic robot, the movement shape is analyzed and adjusted to make its movement attitude completely similar to the biological shape.
Safety Evaluation of Dry-fasten Stone Curtain Wall Structure of Existing Building
Authors: Liu Zhong 
Published: July 2020

Abstract
Stone curtain walls are more and more widely used due to their good decorative effect and hard texture. However, with the increase of their service life, many safety issues have gradually appeared and caused widespread concern from all walks of life. The dry-fasten stone curtain wall of an office building has been used for more than 12 years. Through on-site inspection and testing of the verticality of the stone curtain wall, the connection node between the stone curtain wall and the main structure, the stone curtain wall framework system, the curtain wall stone panel and weather resisting silicone sealant, some suggestions for transformation are proposed for the existed problems.
Research on Cold Chain Transport of Vaccines in Major Outbreaks
Authors: Li Gang , Wang Gangyi , Ma Yuanbo , Yue Lulu , Zhao Wenting 
Published: July 2020

Abstract
In the face of the sudden outbreak of new type of coronavirus, the virus is spreading at a faster rate than expected, which seriously threatens people’s life and health and national security. According to the World Organization, infectious diseases have been at a high incidence in the last two decades. How to transport kits and vaccines safely and efficiently to suspected cases and patients in a short period of time is related to the speed of national control of the epidemic. This paper first analyzes the scale of the pharmaceutical cold chain market in China, analyzes the policy of the pharmaceutical cold chain industry issued by the state, and analyzes the problems existing in the pharmaceutical cold chain industry; then it analyzes the influence of epidemic situation on cold chain transportation, and finally puts forward the safe and efficient transportation scheme of vaccine under epidemic situation.
Rsearch on Load Adaptability of Existing Hollow Slab Bridge of Ji-Qing Highway
Authors: Hao Long , Liu Guiru , Wang Shan , Fang Hua 
Published: July 2020

Abstract
Throughout the reconstruction and expansion process of the Jinan and Qingdao Expressway, there is a need for the existing Bridge to be demolished first and then reinforced for a better utilization. In order to better evaluate the load capability of the Level 1 lane, the load ability of the Seven-Ministry loads adaptability model and the current Ji-Qing traffic model, this paper examines three models of the load adaptability of existing small span Bridges. The load adaptability of the three load models on the old bridge of Jiqing existing line is analysed by comparing the bearing capacity level of the three load models in the three spans of 5m, 8m, and 13m of the hollow slab bridge.
EEG Neuro - processing for the development of neurointerfaces
Authors: Chervyakov N I , Lyakhov P A , Kiladze M R , Kovalets A A , Lyakhova U A 
Published: July 2020

Abstract
Fast and accurate processing of electroencephalogram (EEG) signals is necessary for correct realization of neurointerfaces. Neural network is one of the ways of its processing. In this article the method of EEG processing with the help of multilayer perceptron trained by the algorithm of error backpropagation is considered. The results of modeling during training of the neural network showed the minimum value of the Mean Squared error.