A Simple Technique for Predicting High-Redshift Galaxy Evolution

We show that the ratio of galaxies' specific star formation rates (SSFRs) to their host halos' specific mass accretion rates (SMARs) strongly constrains how the galaxies' stellar masses, specific star formation rates, and host halo masses evolve over cosmic time. This evolutionary constraint provides a simple way to probe z>8 galaxy populations without direct observations. Tests of the method with galaxy properties at z=4 successfully reproduce the known evolution of the stellar mass--halo mass (SMHM) relation, galaxy SSFRs, and the cosmic star formation rate (CSFR) for 5<z<8. We then predict the continued evolution of these properties for 8<z<15. In contrast to the non-evolution in the SMHM relation at z<4, the median galaxy mass at fixed halo mass increases strongly at z>4. We show that this result is closely linked to the flattening in galaxy SSFRs at z>2 compared to halo specific mass accretion rates; we expect that average galaxy SSFRs at fixed stellar mass will continue their mild evolution to z~15. The expected CSFR shows no breaks or features at z>8.5; this constrains both reionization and the possibility of a steep falloff in the CSFR at z=9-10. Finally, we make predictions for stellar mass and luminosity functions for the James Webb Space Telescope (JWST), which should be able to observe one galaxy with M* > ~10^8 Msun per 10^3 Mpc^3 at z=9.6 and one such galaxy per 10^4 Mpc^3 at z=15.Comment: Revised to include JWST luminosity functions, matching accepted versio

Classification of Epileptic EEG Signals by Wavelet based CFC

Electroencephalogram, an influential equipment for analyzing humans activities and recognition of seizure attacks can play a crucial role in designing accurate systems which can distinguish ictal seizures from regular brain alertness, since it is the first step towards accomplishing a high accuracy computer aided diagnosis system (CAD). In this article a novel approach for classification of ictal signals with wavelet based cross frequency coupling (CFC) is suggested. After extracting features by wavelet based CFC, optimal features have been selected by t-test and quadratic discriminant analysis (QDA) have completed the Classification.Comment: Electroencephalogram; Wavelet Decomposition; Cross Frequency Coupling;Quadratic Discriminant Analysis; T-test Feature Selectio

The Rockstar Phase-Space Temporal Halo Finder and the Velocity Offsets of Cluster Cores

We present a new algorithm for identifying dark matter halos, substructure, and tidal features. The approach is based on adaptive hierarchical refinement of friends-of-friends groups in six phase-space dimensions and one time dimension, which allows for robust (grid-independent, shape-independent, and noise-resilient) tracking of substructure; as such, it is named Rockstar (Robust Overdensity Calculation using K-Space Topologically Adaptive Refinement). Our method is massively parallel (up to 10^5 CPUs) and runs on the largest current simulations (>10^10 particles) with high efficiency (10 CPU hours and 60 gigabytes of memory required per billion particles analyzed). A previous paper (Knebe et al 2011) has shown Rockstar to have class-leading recovery of halo properties; we expand on these comparisons with more tests and higher-resolution simulations. We show a significant improvement in substructure recovery as compared to several other halo finders and discuss the theoretical and practical limits of simulations in this regard. Finally, we present results which demonstrate conclusively that dark matter halo cores are not at rest relative to the halo bulk or satellite average velocities and have coherent velocity offsets across a wide range of halo masses and redshifts. For massive clusters, these offsets can be up to 350 km/s at z=0 and even higher at high redshifts. Our implementation is publicly available at http://code.google.com/p/rockstar .Comment: 20 pages, 14 figures. Minor revisions to match accepted versio

The Role of Technical and Vocational Training for Entrepreneurship Development and Business Skills in the Boushehr Province Technical and Vocational Training IRAN Aspect.

This study was to identify the role of technical and vocational training in entrepreneurship development and business skills in the main office of B. province technical and vocational training. The corelational study was conducted. The population consisted of 1500 apprentices among which 420 persons were randomly selected according to Cochran formula based on a systematic sampling method. Data is gathered via a researcher-structured questionnaire containing 35 items based on Likert scale. Content validity and Cronbach\u27S Alpha (α=/94) are used. The data was analysed using SPSS software. The descriptive and inferential statistics are also used to examined the hypotheses. The result showed that there was a significant relationship between technical and vocational training and dimensions of entrepreneurship in the apprentices that includes: technical and vocational training, knowledge and technical ability, success seeking