Cyclic cosmology from Lagrange-multiplier modified gravity

We investigate cyclic and singularity-free evolutions in a universe governed by Lagrange-multiplier modified gravity, either in scalar-field cosmology, as well as in $f(R)$ one. In the scalar case, cyclicity can be induced by a suitably reconstructed simple potential, and the matter content of the universe can be successfully incorporated. In the case of $f(R)$-gravity, cyclicity can be induced by a suitable reconstructed second function $f_2(R)$ of a very simple form, however the matter evolution cannot be analytically handled. Furthermore, we study the evolution of cosmological perturbations for the two scenarios. For the scalar case the system possesses no wavelike modes due to a dust-like sound speed, while for the $f(R)$ case there exist an oscillation mode of perturbations which indicates a dynamical degree of freedom. Both scenarios allow for stable parameter spaces of cosmological perturbations through the bouncing point.Comment: 8 pages, 3 figures, references added, accepted for publicatio

Testing the Lorentz and CPT Symmetry with CMB polarizations and a non-relativistic Maxwell Theory

We present a model for a system involving a photon gauge field and a scalar field at quantum criticality in the frame of a Lifthitz-type non-relativistic Maxwell theory. We will show this model gives rise to Lorentz and CPT violation which leads to a frequency-dependent rotation of polarization plane of radiations, and so leaves potential signals on the cosmic microwave background temperature and polarization anisotropies.Comment: 7 pages, 2 figures, accepted on JCAP, a few references adde

Comprehensive Characterization of the Transmitted/Founder env Genes From a Single MSM Cohort in China

Background: The men having sex with men (MSM) population has become one of the major risk groups for HIV-1 infection in China. However, the epidemiological patterns, function of the env genes, and autologous and heterologous neutralization activity in the same MSM population have not been systematically characterized. Methods: The env gene sequences were obtained by the single genome amplification. The time to the most recent common ancestor was estimated for each genotype using the Bayesian Markov Chain Monte Carlo approach. Coreceptor usage was determined in NP-2 cells. Neutralization was analyzed using Env pseudoviruses in TZM-bl cells. Results: We have obtained 547 full-length env gene sequences by single genome amplification from 30 acute/early HIV-1–infected individuals in the Beijing MSM cohort. Three genotypes (subtype B, CRF01_AE, and CRF07_BC) were identified and 20% of the individuals were infected with multiple transmitted/founder (T/F) viruses. The tight clusters of the MSM sequences regardless of geographic origins indicated nearly exclusive transmission within the MSM population and limited number of introductions. The time to the most recent common ancestor for each genotype was 10–15 years after each was first introduced in China. Disparate preferences for coreceptor usages among 3 genotypes might lead to the changes in percentage of different genotypes in the MSM population over time. The genotype-matched and genotype-mismatched neutralization activity varied among the 3 genotypes. Conclusions: The identification of unique characteristics for transmission, coreceptor usage, neutralization profile, and epidemic patterns of HIV-1 is critical for the better understanding of transmission mechanisms, development of preventive strategies, and evaluation of vaccine efficacy in the MSM population in China

Shear Resistance Prediction of post-fire reinforced concrete beams using artificial neural network

In this paper, a prediction method based on artificial neural network was developed to rapidly determine the residual shear resistance of reinforced concrete (RC) beams after fire. Firstly, the temperature distribution along the beam section was determined through finite element analysis using software ABAQUS. A residual shear strength calculation model was developed and validated using the test data. Using this model, 384 data entries were derived for training and testing. The input layer of neural network involved parameters of beam height, beam width, fire exposure time, cross-sectional area of stirrup, stirrup spacing, concrete strength, and concrete cover thickness. The output was the shear resistance of RC beams. It was found that use of BP neural network could precisely predict the post-fire shear resistance of RC beams. The predicted data were highly consistent with the target data. Thus, this is a novel method for computing post-fire shear resistance of RC beams. Using this new method, further investigation was also made on the effects of different parameters on the shear resistance of the beams

Encouraging this Particular Form of (Very Fun) Madness – Roles for Deans and Faculty Members

Our broader goal is to encourage experiential learning in the transactions curriculum. I know that all of you are here and do not need convincing. So my goal for this session is to try and provide some persuasive tools to help you convince people at your schools about both the value and the possibility of this type of teaching and learning