Two-fluid Hydrodynamics of a quasi-1D unitary Fermi gas

This thesis is devoted to the study of the hydrodynamic behavior of the unitary Fermi gas trapped by a highly elongated harmonic potential. Propagation of sound is one of the most exciting features exhibited by interacting many-body systems. It provides crucial information on the dynamic behavior of the system as well as on key thermodynamic quantities. The propagation of sound is particularly interesting in superfluids where two-fluid hydrodynamic theory predicts the occurrence of two different sounds: first sound, where the normal and superfluid component oscillate in phase, and second sound, where the two components oscillate with opposite phase. In the thesis, we investigate the propagation of sound waves of the unitary Fermi gas in a cylindrical geometry by solving the equations of two-fluid hydrodynamics in the `1D' scenario at finite temperature. The relevant thermodynamic functions entering the hydrodynamic equations are discussed in the superfluid and normal regimes in terms of universal scaling functions. Both the first sound and second sound solutions are calculated as a function of temperature and the role of the superfluid density is explicitly pointed out. The density fluctuations in the second sound wave are found to be large enough to be measured as a consequence of the finite thermal expansion coefficient of the gas, which is the strategy used in a recent experiment carried out at Innsbruck where second sound was detected in the unitary Fermi gas. We also provide an investigation of the temperature dependence of the collective oscillations of first sound nature exhibited by a highly elongated harmonically trapped Fermi gas at unitarity, including the region below the critical temperature for superfluidity. Differently from the lowest axial breathing mode, the hydrodynamic frequencies of the higher-nodal excitations show a temperature dependence, which is calculated starting from Landau two-fluid theory and using the available experimental knowledge of the equation of state

First and second sound in a highly elongated Fermi gas at unitarity

We consider a Fermi gas at unitarity trapped by a highly elongated harmonic potential and solve the equations of two fluid hydrodynamics at finite temperature. The propagation of sound waves as well as the discretized solutions in the presence of weak axial trapping are considered. The relevant thermodynamic functions entering the hydrodynamic equations are discussed in the superfluid and normal regimes in terms of universal scaling functions. Both first sound and second sound solutions are calculated as a function of temperature and the role of the superfluid density is explicitly pointed out. The density fluctuations in the second sound wave are found to be large enough to be measured as a consequence of the finite thermal expansion coefficient of the gas. Emphasis is given to the comparison with recent experimental data.Comment: 15 pages, 11 figure

The relationship between job performance and perceived organizational support in faculty members at Chinese universities: a questionnaire survey

BACKGROUND: Although several studies have been conducted to investigate the relationship between perceived organizational support (POS) and job performance (JP), it remains unclear whether this relationship is appropriate for faculty members at Chinese universities. The objectives of this study were to (a) examine the correlation between POS andJP; (b) identify the predictors of POS, including demographic and organizational characteristics among faculty members at a Chinese university; (c) investigate the influence of mediating factors between POS and JP; and (d) compare the findings of this study with related studies. METHODS: A cross-sectional questionnaire survey was used in this study. The questionnaire was administered to 700 faculty members who were randomly selected from all faculty members at six universities. A total of 581 questionnaires were obtained. A statistical model for JP was developed based on the literature review. RESULTS: The analysis results indicated that the relationship between POS and JP was mediated by job satisfaction (JS), positive affectivity (PA), and affective commitment (AC). In addition, procedural and distributive justice contribute to POS. CONCLUSIONS: The study concludes that the relationship between POS and JP is mediated by JS, PA, and AC and is influenced by POS. These results can provide evidence for university administrators to improve POS and increase the JP of faculty members at universities

Peptide-siRNA nanocomplexes targeting NF-κB subunit p65 suppress nascent experimental arthritis

The NF-κB signaling pathway is implicated in various inflammatory diseases, including rheumatoid arthritis (RA); therefore, inhibition of this pathway has the potential to ameliorate an array of inflammatory diseases. Given that NF-κB signaling is critical for many immune cell functions, systemic blockade of this pathway may lead to detrimental side effects. siRNAs coupled with a safe and effective delivery nanoplatform may afford the specificity lacking in systemic administration of small-molecule inhibitors. Here we demonstrated that a melittin-derived cationic amphipathic peptide combined with siRNA targeting the p65 subunit of NF-κB (p5RHH-p65) noncovalently self-assemble into stable nanocomplexes that home to the inflamed joints in a murine model of RA. Specifically, administration of p5RHH-p65 siRNA nanocomplexes abrogated inflammatory cytokine expression and cellular influx into the joints, protected against bone erosions, and preserved cartilage integrity. The p5RHH-p65 siRNA nanocomplexes potently suppressed early inflammatory arthritis without affecting p65 expression in off-target organs or eliciting a humoral response after serial injections. These data suggest that this self-assembling, largely nontoxic platform may have broad utility for the specific delivery of siRNA to target and limit inflammatory processes for the treatment of a variety of diseases

The LAMOST Survey of Background Quasars in the Vicinity of the Andromeda and Triangulum Galaxies -- II. Results from the Commissioning Observations and the Pilot Surveys

We present new quasars discovered in the vicinity of the Andromeda and Triangulum galaxies with the LAMOST during the 2010 and 2011 observational seasons. Quasar candidates are selected based on the available SDSS, KPNO 4 m telescope, XSTPS optical, and WISE near infrared photometric data. We present 509 new quasars discovered in a stripe of ~135 sq. deg from M31 to M33 along the Giant Stellar Stream in the 2011 pilot survey datasets, and also 17 new quasars discovered in an area of ~100 sq. deg that covers the central region and the southeastern halo of M31 in the 2010 commissioning datasets. These 526 new quasars have i magnitudes ranging from 15.5 to 20.0, redshifts from 0.1 to 3.2. They represent a significant increase of the number of identified quasars in the vicinity of M31 and M33. There are now 26, 62 and 139 known quasars in this region of the sky with i magnitudes brighter than 17.0, 17.5 and 18.0 respectively, of which 5, 20 and 75 are newly-discovered. These bright quasars provide an invaluable collection with which to probe the kinematics and chemistry of the ISM/IGM in the Local Group of galaxies. A total of 93 quasars are now known with locations within 2.5 deg of M31, of which 73 are newly discovered. Tens of quasars are now known to be located behind the Giant Stellar Stream, and hundreds behind the extended halo and its associated substructures of M31. The much enlarged sample of known quasars in the vicinity of M31 and M33 can potentially be utilized to construct a perfect astrometric reference frame to measure the minute PMs of M31 and M33, along with the PMs of substructures associated with the Local Group of galaxies. Those PMs are some of the most fundamental properties of the Local Group.Comment: 26 pages, 6 figures, AJ accepte

Storage Fit Learning with Feature Evolvable Streams

Feature evolvable learning has been widely studied in recent years where old features will vanish and new features will emerge when learning with streams. Conventional methods usually assume that a label will be revealed after prediction at each time step. However, in practice, this assumption may not hold whereas no label will be given at most time steps. A good solution is to leverage the technique of manifold regularization to utilize the previous similar data to assist the refinement of the online model. Nevertheless, this approach needs to store all previous data which is impossible in learning with streams that arrive sequentially in large volume. Thus we need a buffer to store part of them. Considering that different devices may have different storage budgets, the learning approaches should be flexible subject to the storage budget limit. In this paper, we propose a new setting: Storage-Fit Feature-Evolvable streaming Learning (SF$^2$EL) which incorporates the issue of rarely-provided labels into feature evolution. Our framework is able to fit its behavior to different storage budgets when learning with feature evolvable streams with unlabeled data. Besides, both theoretical and empirical results validate that our approach can preserve the merit of the original feature evolvable learning i.e., can always track the best baseline and thus perform well at any time step