Power spectrum with k6k^6 growth for primordial black holes

The decrease of both the rolling speed of the inflaton and the sound speed of the curvature perturbations can amplify the curvature perturbations during inflation so as to generate a sizable amount of primordial black holes. In the ultraslow-roll inflation scenario, it has been found that the power spectrum of curvature perturbations has a $k^4$ growth. In this paper, we find that when the speed of sound decreases suddenly, the curvature perturbations becomes scale dependent in the infrared limit and the power spectrum of the curvature perturbation only has a $k^2$ growth. Furthermore, by studying the evolution of the power spectrum in the inflation model, in which both the sound speed of the curvature perturbations and the rolling speed of the inflaton are reduced, we find that the power spectrum is nearly scale invariant at the large scales to satisfy the constraint from the cosmic microwave background radiation observations, and at the same time can be enhanced at the small scales to result in an abundant formation of primordial black holes. In the cases of the simultaneous changes of the sound speed and the slow-roll parameter $\eta$ and the change of the sound speed preceding that of the slow-roll parameter $\eta$, the power spectrum can possess a $k^6$ growth under certain conditions, which is the steepest growth of the power spectrum reported so far.Comment: 29 pages, 14 figures, to appear in PR

Growth of power spectrum due to decrease of sound speed during inflation

We study the amplification of the curvature perturbations due to a small sound speed and find that its origin is different completely from that due to the ultraslow-roll inflation. This is because when the sound speed is very small the enhancement of the power spectrum comes from the fact that the curvature perturbations at the scales smaller than the cosmic microwave background (CMB) scale becomes scale-variant, rather than growing that leads to the amplification of the curvature perturbations during the ultraslow-roll inflation. At large scales the power spectrum of the curvature perturbations remains to be scale invariant, which is consistent with the CMB observations, and then it will have a transient $k^2$ growth and finally approach a $k^4$ growth as the scale becomes smaller and smaller. Thus the power spectrum can be enhanced to generate a sizable amount of primordial black holes. Furthermore, when the high order correction in the dispersion relation of the curvature perturbations is considered the growth of the power spectrum of the curvature perturbations has the same origin as that in the case without this correction.Comment: 11 pages, 1 figure. three references adde

The Analysis on Chinese Traditional Ideology’s Impacts on Aged People’s Motivation to Continue Working

This paper examines Chinese employees' acceptance and considerations towards bridge employment. Bridge employment provides retirees opportunities to continue working after retirement. It seems that bridge employment has become broadly accepted by individuals in some developed countries. However, Chinese older workers show much resistance towards it. This research is based on 157 quantitative data collected through questionnaires. Through analyzing cross-tables, this survey shows that the traditional ideology regarding inter-generational connection still exists and plays an influential factor in the decision-making process of bridge employment acceptance. Besides, other individual factors and organisational factors are also examined

Phase Fluctuation Analysis in Functional Brain Networks of Scaling EEG for Driver Fatigue Detection

The characterization of complex patterns arising from electroencephalogram (EEG) is an important problem with significant applications in identifying different mental states. Based on the operational EEG of drivers, a method is proposed to characterize and distinguish different EEG patterns. The EEG measurements from seven professional taxi drivers were collected under different states. The phase characterization method was used to calculate the instantaneous phase from the EEG measurements. Then, the optimization of drivers’ EEG was realized through performing common spatial pattern analysis. The structures and scaling components of the brain networks from optimized EEG measurements are sensitive to the EEG patterns. The effectiveness of the method is demonstrated, and its applicability is articulated.</p

Nitrogen-doped carbon nanotubes with encapsulated Fe nanoparticles as efficient oxygen reduction catalyst for alkaline membrane direct ethanol fuel cells

Exploring low-cost and highly efficient non-precious metal electrocatalysts toward oxygen reduction reaction is crucial for the development of fuel cells. Herein, we report the synthesis of bamboo-like N-doped carbon nanotubes with encapsulated Fe-nanoparticles through high-temperature pyrolysis of multiple nitrogen complex consisting of benzoguanamine, cyanuric acid, and melamine. As-prepared catalyst exhibits high catalytic activity for oxygen reduction with onset potential of 1.10 V and half-wave potential of 0.93 V, as well as low H2O2 yield (<1%) in alkaline medium. The mass activity of the catalyst at 1.0 V (0.58 A g−1) can reach 43% of state-of-the-art commercial Pt/C. This catalyst also exhibits high durability and ethanol tolerance. When it was applied in alkaline membrane direct ethanol fuel cell, the peak power density could reach to 64 mW cm−2, indicating its attractive application prospect in fuel cells

Experiments of Image Retrieval Using Weak Attributes

Searching images based on descriptions of image attributes is an intuitive process that can be easily understood by humans and recently made feasible by a few promising works in both the computer vision and multimedia communities. In this report, we describe some experiments of image retrieval methods that utilize weak attributes