scholarly journals A Ranking Method for Selection of $\eta $ Mesons in High Multiplicity Events

2018 ◽  
Vol 49 (4) ◽  
pp. 727
Author(s):  
A. Bingül ◽  
U. Şaşmaz ◽  
A.J. Beddall
Author(s):  
Ilaria Palomba ◽  
Dario Richiedei ◽  
Alberto Trevisani

Resonant system design and optimization is usually supported by finite element models. Large dimensional models are often needed to achieve the desired accuracy in the representation of the vibrational behaviour at the frequency of interest. Unfortunately, large dimensional models are frequently too cumbersome to be actually useful, mainly at the optimization stage. On the other hand, the choice of the most appropriate reduction strategy and dimension for a reduced-order model is generally left to designers’ experience. Having recognized the effectiveness and spreading of the Craig Bampton reduction technique, the aim of this paper is to propose a rigorous ranking method, called Interior Mode Ranking (IMR), for the selection of the interior normal modes of the full order model to be inherited by the reduced order one. The method is aimed at finding the set of interior modes of minimum dimensions which allows achieving a desired level of accuracy of the reduced order model at a frequency of interest. The method is here applied to a resonator widely employed in industry: an ultrasonic welding bar horn, which is usually designed to operate excited in resonance. The results achieved through the application of the IMR method are compared with those yielded by other ranking techniques available in literature in order to prove its effectiveness.


2020 ◽  
Vol 69 ◽  
pp. 44-51
Author(s):  
Natarajan Ramar ◽  
S.R. Meher ◽  
Vaitheeswaran Ranganathan ◽  
Bojarajan Perumal ◽  
Prashant Kumar ◽  
...  

Author(s):  
Vijay Manikrao Athawale ◽  
Prasenjit Chatterjee ◽  
Shankar Chakraborty

2015 ◽  
Vol 14 ◽  
pp. CIN.S24388 ◽  
Author(s):  
Emily M. Mackay ◽  
Jennifer Koppel ◽  
Pooja Das ◽  
Joanna Woo ◽  
David C. Schriemer ◽  
...  

In recent years, hundreds of candidate protein biomarkers have been identified using discovery-based proteomics. Despite the large number of candidate biomarkers, few proteins advance to clinical validation. We propose a hypothesis-driven approach to identify candidate biomarkers, previously characterized in the literature, with the highest probability of clinical applicability. A ranking method, called the “hypothesis-directed biomarker ranking” (HDBR) system, was developed to score candidate biomarkers based on seven criteria deemed important in the selection of clinically useful biomarkers. To demonstrate its application, we applied the HDBR system to identify candidate biomarkers for the development of a diagnostic test for the early detection of colorectal cancer. One-hundred and fifty-one candidate biomarkers were identified from the literature and ranked based on the specified criteria. The top-ranked candidates represent a group of biomarkers whose further study and validation would be justified in order to expedite the development of biomarkers that could be used in a clinical setting.


Proceedings ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 6 ◽  
Author(s):  
Francesco Collaboration

Deconfined strongly interacting QCD matter is produced in the laboratory at the highest energy densities in heavy-ion collisions at the LHC. A selection of recent results from ALICE is presented, spanning observables from the soft sector (bulk particle production and correlations), the hard probes (charmed hadrons and jets) and signatures of possible collective effects in pp and p–Pb collisions with high multiplicity. Finally, the perspectives after the detectors upgrades, taking place in the period 2019–2020, are presented.


Author(s):  
Aleksey Bal'chugov

It is shown that the ranking method allows for a preliminary selection of factors in the study of the learning process


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