Neutrino Masses in a 5D SU(3)WSU(3)_W TeV Unification Model

We study the generation of neutrino masses in the $SU(3)_W$ electroweak unified theory in $M_4\times S_1/(Z_2\times Z'_2)$ spacetime. By appropriate orbifolding, the bulk symmetry $SU(3)_W$ is broken into $SU(2)_L \times U(1)_Y$ at one of the fixed points, where the quarks reside. The leptons form $SU(3)_W$ triplets, localized at the other symmetric fixed point. The fermion masses arise from the bulk Higgs sector containing a triplet and an anti-sextet. We construct neutrino Majorana masses via 1-loop quantum corrections by adding a parity odd bulk triplet scalar. No right-handed neutrino is needed. The neutrino mass matrix is of the inverted hierarchy type. We show that the model can easily accommodate the bi-large mixing angle solution favored by the recent neutrino experiments without much fine tuning of parameters. The constraints from \mu\ra 3e transition and neutrinoless double beta decays are discussed.Comment: 14 pages, 4 figure

Cloud Storage and Bioinformatics in a private cloud deployment: Lessons for Data Intensive research

This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) are performed and results confirm backup automation is completed swiftly and is reliable for data-intensive research. The data recovery result confirms that execution time is in proportion to quantity of recovered data, but the failure rate increases in an exponential manner. The data migration result confirms execution time is in proportion to disk volume of migrated data, but again the failure rate increases in an exponential manner. In addition, benefits of CCAF are illustrated using several bioinformatics examples such as tumour modelling, brain imaging, insulin molecules and simulations for medical training. Our Cloud Storage solution described here offers cost reduction, time-saving and user friendliness