scholarly journals Analysis of heavy-flavour particles in ALICE with the O2 analysis framework

2021 ◽  
Vol 251 ◽  
pp. 03064
Author(s):  
Vít Kučera ◽  
Gian Michele Innocenti ◽  
Francesco Prino ◽  
Andrea Rossi ◽  
Jan Fiete Grosse-Oetringhaus ◽  
...  
Keyword(s):  
Processing Speed ◽  
Complex Analysis ◽  
Minimum Bias ◽  
Analysis Framework ◽  
Charm Mesons ◽  
Alice Experiment ◽  
The Core ◽  
Future Developments ◽  
Physics Program ◽  
Data Volume

Precise measurements of heavy-flavour hadrons down to very low pT represent the core of the physics program of the upgraded ALICE experiment in Run 3 [1]. These physics probes are characterised by a very small signal-to-background ratio requiring very large statistics of minimum-bias events. In Run 3, ALICE is expected to collect up to 13 nb−1 of lead–lead collisions, corresponding to about 1 × 1011 minimum-bias events. In order to analyse this unprecedented amount of data, which is about 100 times larger than the statistics collected in Run 1 and Run 2, the ALICE collaboration is developing a complex analysis framework that aims at maximising the processing speed and data volume reduction [2]. In this paper, the strategy of reconstruction, selection, skimming, and analysis of heavy-flavour events for Run 3 will be presented. Some preliminary results on the reconstruction of charm mesons and baryons will be shown and the prospects for future developments and optimisation discussed.

THE ALICE EXPERIMENT AT CERN LHC: STATUS AND FIRST RESULTS

2011 ◽  
Vol 26 (03n04) ◽  
pp. 517-522
Author(s):  
◽  
ERMANNO VERCELLIN
Keyword(s):  
Data Analysis ◽  
Cosmic Rays ◽  
Dense Matter ◽  
Heavy Ion ◽  
Short Description ◽  
Alice Experiment ◽  
Ion Collisions ◽  
Physics Program ◽  
Accelerate Proton ◽  
First Results

The ALICE experiment is aimed at studying the properties of the hot and dense matter produced in heavy-ion collisions at LHC energies. In the first years of LHC operation the ALICE physics program will be focused on Pb - Pb and p - p collisions. The latter, on top of their intrinsic interest, will provide the necessary baseline for heavy-ion data. After its installation and a long commissioning with cosmic rays, in late fall 2009 ALICE participated (very successfully) in the first LHC run, by collecting data in p - p collisions at c.m. energy 900 GeV. After a short stop during winter, LHC operations have been resumed; the machine is now able to accelerate proton beams up to 3.5 TeV and ALICE has undertaken the data taking campaign at 7 TeV c.m. energy. After an overview of the ALICE physics goals and a short description of the detector layout, the ALICE performance in p - p collisions will be presented. The main physics results achieved so far will be highlighted as well as the main aspects of the ongoing data analysis.

scholarly journals Using a Core Scientific Metadata Model in Large-Scale Facilities

2010 ◽  
Vol 5 (1) ◽  
pp. 106-118 ◽  
Author(s):  
Brian Matthews ◽  
Shoaib Sufi ◽  
Damian Flannery ◽  
Laurent Lerusse ◽  
Tom Griffin ◽  
...  
Keyword(s):  
Large Scale ◽  
Materials Science ◽  
Production Quality ◽  
Scientific Study ◽  
Quality Data ◽  
Structural Elements ◽  
Metadata Model ◽  
The Core ◽  
Future Developments ◽  
The Relationship

In this paper, we present the Core Scientific Metadata Model (CSMD), a model for the representation of scientific study metadata developed within the Science & Technology Facilities Council (STFC) to represent the data generated from scientific facilities. The model has been developed to allow management of and access to the data resources of the facilities in a uniform way, although we believe that the model has wider application, especially in areas of “structural science” such as chemistry, materials science and earth sciences. We give some motivations behind the development of the model, and an overview of its major structural elements, centred on the notion of a scientific study formed by a collection of specific investigations. We give some details of the model, with the description of each investigation associated with a particular experiment on a sample generating data, and the associated data holdings are then mapped to the investigation with the appropriate parameters. We then go on to discuss the instantiation of the metadata model within a production quality data management infrastructure, the Information CATalogue (ICAT), which has been developed within STFC for use in large-scale photon and neutron sources. Finally, we give an overview of the relationship between CSMD, and other initiatives, and give some directions for future developments.    

Part V Separation of Powers, Ch.28 The Separation of Judicial Power

2018 ◽  
Author(s):  
Foster Michelle
Keyword(s):  
Separation Of Powers ◽  
Judicial Power ◽  
Controversial Issues ◽  
Individual Rights ◽  
High Court ◽  
The Core ◽  
Future Developments ◽  
Methods And Techniques ◽  
History Of

This chapter discusses the separation of judicial power principle in Australia. First, it considers the history of the principle and whether it was intended or assumed by the Constitution's drafters. Next, the chapter examines the evolution of the principle in the High Court's jurisprudence, as well as its underlying rationales. Hereafter, this chapter considers the practical ramifications of the principle, and the methods and techniques adopted by the High Court to respond to some of its ‘inconvenient’ consequences. Finally, the chapter considers two of the core underlying rationales in the context of controversial issues in contemporary jurisprudence. It analyses the separation of judicial power principle and the protection of individual rights, in addition to the separation of judicial power principle and federalism. The chapter concludes by briefly commenting on likely future developments.

scholarly journals Remanent battery capacity estimation for autonomous ground industrial vehicles

2019 ◽  
Vol 290 ◽  
pp. 02009
Author(s):  
Tom Savu ◽  
Bogdan Alexandru Jugravu
Keyword(s):  
Neural Network ◽  
Industrial System ◽  
Ground Vehicles ◽  
Future Developments ◽  
Capacity Loss ◽  
The Neural Network ◽  
Proposed Model ◽  
Battery Capacity ◽  
Data Volume ◽  
Remaining Capacity

When travelling in an industrial system for completing their assigned tasks, autonomous ground vehicles must estimate the remanent capacity of their batteries and decide if they are able to assume the next task and afterward travel to the charging or replacement station. The amount of energy needed for moving on a certain distance depends on a set of parameters belonging to the vehicle, to the runway and to the vehicle’s trajectory. The paper proposes a model for estimating the remaining capacity of the batteries after a certain distance would be covered by a vehicle. Parameters values were obtained by simulation, capacity loss was computed using the proposed model and then a neural network was taught to perform the estimation. The neural network was further used to simulate the situation when a vehicle is estimating the needed capacity before accepting a task to be performed. The results proved that the model and the network, even developed using low data volume and processing time, are able to provide accurate enough estimations and are able to allow future developments.

scholarly journals The Structure of an Injectisome Export Gate Demonstrates Conservation of Architecture in the Core Export Gate between Flagellar and Virulence Type III Secretion Systems

mBio ◽  
2019 ◽  
Vol 10 (3) ◽  
Author(s):  
Steven Johnson ◽  
Lucas Kuhlen ◽  
Justin C. Deme ◽  
Patrizia Abrusci ◽  
Susan M. Lea
Keyword(s):  
Type Iii Secretion ◽  
Complex Analysis ◽  
Secretion Systems ◽  
Core Complex ◽  
Type Iii ◽  
The Core ◽  
Cryo Electron Microscopy ◽  
Type Iii Secretion Systems ◽  
Equivalent Complex ◽  
Resolution Structure

ABSTRACT Export of proteins through type III secretion systems (T3SS) is critical for motility and virulence of many major bacterial pathogens. Proteins are exported through a genetically defined export gate complex consisting of three proteins. We have recently shown at 4.2 Å that the flagellar complex of these three putative membrane proteins (FliPQR in flagellar systems, SctRST in virulence systems) assembles into an extramembrane helical assembly that likely seeds correct assembly of the rod. Here we present the structure of an equivalent complex from the Shigella virulence system at 3.5 Å by cryo-electron microscopy. This higher-resolution structure yields a more precise description of the structure and confirms the prediction of structural conservation in this core complex. Analysis of particle heterogeneity also suggests how the SctS/FliQ subunits sequentially assemble in the complex. IMPORTANCE Although predicted on the basis of sequence conservation, the work presented here formally demonstrates that all classes of type III secretion systems, flagellar or virulence, share the same architecture at the level of the core structures. This absolute conservation of the unusual extramembrane structure of the core export gate complex now allows work to move to focusing on both mechanistic studies of type III but also on fundamental studies of how such a complex is assembled.

Design of Nut Machine Vision Inspection and Screening Systems Based on PC

2013 ◽  
Vol 712-715 ◽  
pp. 2733-2737
Author(s):  
Zhong An Yu ◽  
Chun Li Wang ◽  
Pei Yu Guo ◽  
Kong Kan
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Processing Speed ◽  
High Reliability ◽  
Single Chip ◽  
The Core ◽  
Vision Inspection ◽  
System Use ◽  
Fast Processing ◽  
Machine Vision Inspection

This system use PC as the core of image analysis and processing, with the single chip processor as the control core execution, combining with machine vision image processing technology, using advanced image processing algorithms, to achieve separation of the nut, and through experiments to test the correctness of the algorithm. The system has the advantage of a fast processing speed and high reliability. It not only save the manpower cost, but also improve the efficiency of the nut sorting.

scholarly journals The evolution of the ALICE O2 monitoring system

2020 ◽  
Vol 245 ◽  
pp. 01042
Author(s):  
Adam Wegrzynek ◽  
Gioacchino Vino
Keyword(s):  
Monitoring System ◽  
Fault Tolerant ◽  
Heavy Ion ◽  
Tool Selection ◽  
Alice Experiment ◽  
The Core ◽  
Computing Model ◽  
Ion Collisions ◽  
Software Sensors ◽  
Component Failures

The ALICE Experiment was designed to study the physics of strongly interacting matter with heavy-ion collisions at the CERN LHC. A major upgrade of the detector and computing model (O2, Offline-Online) is currently ongoing. The ALICE O2 farm will consist of almost 1000 nodes enabled to read out and process on-the-fly about 27 Tb/s of raw data. To efficiently operate the experiment and the O2 facility a new monitoring system was developed. It will provide a complete overview of the overall health, detect performance degradation and component failures by collecting, processing, storing and visualising data from hardware and software sensors and probes. The core of the system is based on Apache Kafka ensuring high throughput, fault-tolerant and metric aggregation, processing with the help of Kafka Streams. In addition, Telegraf provides operating system sensors, InfluxDB is used as a time-series database, Grafana as a visualisation tool. The above tool selection evolved from the initial version where collectD was used instead of Telegraf, and Apache Flume together with Apache Spark instead of Apache Kafka.

scholarly journals A weighted network analysis framework for the hourglass effect—And its application in the C. elegans connectome

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0249846
Author(s):  
Ishaan Batta ◽  
Qihang Yao ◽  
Kaeser M. Sabrin ◽  
Constantine Dovrolis
Keyword(s):  
Network Analysis ◽  
Analysis Framework ◽  
Weighted Network ◽  
Motor Pathways ◽  
Major Aspect ◽  
C Elegans ◽  
The Core ◽  
Network Patterns ◽  
Weighted Network Analysis ◽  
New Framework

Understanding hierarchy and modularity in natural as well as technological networks is of utmost importance. A major aspect of such analysis involves identifying the nodes that are crucial to the overall processing structure of the network. More recently, the approach of hourglass analysis has been developed for the purpose of quantitatively analyzing whether only a few intermediate nodes mediate the information processing between a large number of inputs and outputs of a network. We develop a new framework for hourglass analysis that takes network weights into account while identifying the core nodes and the extent of hourglass effect in a given weighted network. We use this framework to study the structural connectome of the C. elegans and identify intermediate neurons that form the core of sensori-motor pathways in the organism. Our results show that the neurons forming the core of the connectome show significant differences across the male and hermaphrodite sexes, with most core nodes in the male concentrated in sex-organs while they are located in the head for the hermaphrodite. Our work demonstrates that taking weights into account for network analysis framework leads to emergence of different network patterns in terms of identification of core nodes and hourglass structure in the network, which otherwise would be missed by unweighted approaches.

scholarly journals Analysis of Financial Statement and Prewarning of Audit Risks Based on Artificial Neural Network

2021 ◽  
Vol 15 ◽  
pp. 1015-1024
Author(s):  
Yanxia Zhang
Keyword(s):  
Neural Network ◽  
Evaluation Index System ◽  
Financial Statement ◽  
Analysis Framework ◽  
Scientific Evaluation ◽  
Audit Risk ◽  
The Core ◽  
Income Statement ◽  
Proposed Model ◽  
Key Steps

The marketization of social capital has resulted in frequent audit failures, and financial statement frauds. One of the key steps of auditing is the identification of material misstatement risk of financial statement. However, there is no unified analysis framework or quantitative method for identifying this risk. Therefore, this paper aims to analyze financial statement and prewarn audit risks in an accurate manner. Firstly, the items of financial statement were analyzed in three aspects of the target enterprise: balance statement, income statement, and cash flow statement. Next, the authors probed deep into the core indices of the post audit risk verification and evaluation of the business process, constructed a scientific evaluation index system for audit risks of financial statement, and quantified the 89 tertiary indices, 21 secondary indices, and 3 primary indices. After that, an audit risk prediction model for financial statement was established based on neural network. Experimental results show the effectiveness of the proposed model for audit risk prewarning, and applicable to other tasks of financial auditing.

scholarly journals Current understandings about cognition and the neurobiological correlates in schizophrenia

2016 ◽  
Vol 07 (03) ◽  
pp. 412-418 ◽  
Author(s):  
Sujita Kumar Kar ◽  
Meha Jain
Keyword(s):  
Conceptual Understanding ◽  
Cognitive Deficits ◽  
Processing Speed ◽  
Verbal Fluency ◽  
Clinical Implications ◽  
Severe Mental Disorder ◽  
The Core ◽  
Visuospatial Skills ◽  
Multiple Domains ◽  
Core Features

ABSTRACTSchizophrenia is a severe mental disorder. Cognitive deficits are one of the core features of schizophrenia. Multiple domains of cognition (executive function, attention/vigilance, working memory, verbal fluency, visuospatial skills, processing speed, and social cognition) are affected in patients with schizophrenia. Deficits in cognition led to impairment in the real world functioning. Identifying the cognitive deficits and early intervention is required for better functional outcome. This review focuses on conceptual understanding of cognition with its neurobiological correlates in schizophrenia and its different clinical implications.

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