13 research outputs found
Strange particle production in proton-proton collisions at TeV with ALICE at the LHC
The production of mesons containing strange quarks (K, ) and both
singly and doubly strange baryons (, Anti-, and
+Anti-) are measured at central rapidity in pp collisions at
= 0.9 TeV with the ALICE experiment at the LHC. The results are
obtained from the analysis of about 250 k minimum bias events recorded in 2009.
Measurements of yields (dN/dy) and transverse momentum spectra at central
rapidities for inelastic pp collisions are presented. For mesons, we report
yields () of 0.184 0.002 stat. 0.006 syst. for K and
0.021 0.004 stat. 0.003 syst. for . For baryons, we find
= 0.048 0.001 stat. 0.004 syst. for , 0.047
0.002 stat. 0.005 syst. for Anti- and 0.0101 0.0020 stat.
0.0009 syst. for +Anti-. The results are also compared with
predictions for identified particle spectra from QCD-inspired models and
provide a baseline for comparisons with both future pp measurements at higher
energies and heavy-ion collisions.Comment: 33 pages, 21 captioned figures, 10 tables, authors from page 28,
published version, figures at
http://aliceinfo.cern.ch/ArtSubmission/node/387
Fresh Fruit and Vegetable Exportation of Turkey and its Contribution to the Economic Growth
A New Paradigm for Acceptance of Analytics in Learning Management Systems at Jordanian Universities (JLMS)
E-learning or learning management systems (LMS) are broadly used in higher education systems. They've become a necessity to help the participants (instructors, students, and administrators) in their daily use. Learning analytics presents an auspicious approach. This chapter aims to examine the acceptance of analytics and use of an LMS at Jordanian universities. It also focuses on the factors influencing acceptance of analytics in LMS at Jordanian universities. Therefore, the chapter presents a new model for acceptance of analytics in learning management systems at Jordanian universities. It calls Jordanian learning management system (JLMS). This chapter is based on the most recent and related literature explaining various scenarios where learning management systems address learning issues in the digital environment in a way that was not possible in the previous confines of print logics