Renormalization Group Study of the Minimal Majoronic Dark Radiation and Dark Matter Model

We study the 1-loop renormalization group equation running in the simplest singlet Majoron model constructed by us earlier to accommodate the dark radiation and dark matter content in the universe. A comprehensive numerical study was performed to explore the whole model parameter space. A smaller effective number of neutrinos $\triangle N_{eff}\sim 0.05$, or a Majoron decoupling temperature higher than the charm quark mass, is preferred. We found that a heavy scalar dark matter, $\rho$, of mass $1.5-4$ TeV is required by the stability of the scalar potential and an operational type-I see-saw mechanism for neutrino masses. A neutral scalar, $S$, of mass in the $10-100$ GeV range and its mixing with the standard model Higgs as large as $0.1$ is also predicted. The dominant decay modes are $S$ into $b\bar{b}$ and/or $\omega\omega$. A sensitive search will come from rare $Z$ decays via the chain $Z\rightarrow S+ f\bar{f}$, where $f$ is a Standard Model fermion, followed by $S$ into a pair of Majoron and/or b-quarks. The interesting consequences of dark matter bound state due to the sizable $S\rho \rho$-coupling are discussed as well. In particular, shower-like events with an apparent neutrino energy at $M_\rho$ could contribute to the observed effective neutrino flux in underground neutrino detectors such as IceCube.Comment: 33 pages,11 figures, published versio

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

Identification of Five Putative Yeast RNA Helicase Genes

The RNA helicase gene family encodes a group of eight homologous proteins that share regions of sequence similarity. This group of evolutionarily conserved proteins presumably all utilize ATP (or some other nucleoside triphosphate) as an energy source for unwinding double-stranded RNA. Members of this family have been implicated in a variety of physiological functions in organisms ranging from Escherichia coli to human, such as translation initiation, mitochondrial mRNA splicing, ribosomal assembly, and germinal line cell differentiation. We have applied polymerase chain reaction technology to search for additional members of the RNA helicase family in the yeast Saccharomyces cerevisiae. Using degenerate oligonucleotide primers designed to amplify DNA fragments flanked by the highly conserved motifs V L D E A D and Y I H R I G, we have detected five putative RNA helicase genes. Northern and Southern blot analyses demonstrated that these genes are single copy and expressed in yeast. Several members of the RNA helicase family share sequence identity ranging from 49.2% to 67.2%, suggesting that they are functionally related. The discovery of such a multitude of putative RNA helicase genes in yeast suggests that RNA helicase activities are involved in a variety of fundamentally important biological processes

SAR data compression: Application, requirements, and designs

The feasibility of reducing data volume and data rate is evaluated for the Earth Observing System (EOS) Synthetic Aperture Radar (SAR). All elements of data stream from the sensor downlink data stream to electronic delivery of browse data products are explored. The factors influencing design of a data compression system are analyzed, including the signal data characteristics, the image quality requirements, and the throughput requirements. The conclusion is that little or no reduction can be achieved in the raw signal data using traditional data compression techniques (e.g., vector quantization, adaptive discrete cosine transform) due to the induced phase errors in the output image. However, after image formation, a number of techniques are effective for data compression