Thermal and nonthermal emission from a peculiar long-duration GRB 211211A

Long-duration GRB 211211A that lacks a supernova emission even down to very stringent limits at such a low redshift $z=0.076$ and is associated with kilonova emission, suggests that its physical origin is from a binary compact star merger. By reanalyzing its data observed with the Gamma-Ray Burst Monitor on board the Fermi mission, we find that both time-integrated and time-resolved spectra can be fitted well by using a 2SBPL plus blackbody (2SBPL+BB) model in the prompt emission. The bulk Lorentz factors ($\Gamma_{\rm ph}$) of the outflow can be inferred by invoking the observed thermal emission at the photosphere radius within a pure fireball model, and we find out that the temporal evolution of $\Gamma_{\rm ph}$ seems to be tracking with the light curve. The derived values of $\Gamma_{\rm ph}$ are also consistent with the $\Gamma_{\rm ph}$-$L_{\gamma, \rm iso}$/$E_{\gamma, \rm iso}$ correlations that had been found in other bursts. Moreover, we also calculate the magnetization factor $\sigma_{0}$ in the central engine and $\sigma_{\rm ph}$ at the photosphere radius within the framework of a hybrid jet model, and find that the values of both $1+\sigma_{\rm 0}$ and $1+\sigma_{\rm ph}$ are larger than 1 for different time slices. It suggests that at least the Poynting-flux component is indeed existent in the outflow. If this is the case, one possible physical interpretation of thermal and nonthermal emissions in GRB 211211A is from the contributions of both $\nu\bar{\nu}$ annihilation and the Blandford-Znajek mechanisms in the relativistic jet when a stellar mass black hole resides in the central engine.Comment: 12 pages, 6 figures, and 4 tables. ApJ in press, and matched with the published veriso

The research on intelligent extraction of furnace mouth flame characteristics based on DNN

Deep neural networks are a focus of artificial intelligence and big data analysis in recent years. The monitor of the converter mouth is essential to the quality of the steel material production while the requirement of the steel material production is increasingly higher in China. The end-point control of converter blowing is the ultimate regulation of the carbon content and temperature. The severity of carbon-oxygen reaction and the temperature of molten steel can be reflected by the converter mouth flame. Operators judge the end of the steel by watching the converter mouth flame, the converter mouth spark and the time of oxygen supply. So, it is very important to offer a quantitative analysis to converter mouth flame characteristics. We quote the deep neural network into the intelligent extraction of the flame characteristics of the furnace mouth and construct a flame color recognition algorithm based on the deepness letter neural network. This paper belongs to the data science problem in the intelligent research of steel production. By observing the converter flame during the steel flame changes, this paper records the data of light intensity and end-point carbon content of each steel making furnace. When this paper then uses the temperature of flame emission spectrum to deduce and the absorption of the molten steel to judge the contents of the carbon during the converter steel blew process, it is more feasible and accurate than watching by operators. At the same time, by using deep learning algorithm, this paper makes the control process get automatic learning ability and achieve intelligent production so that we can provide a basis for solving the problem of predicting the end-point carbon content in molten steel during the blowing process

Above 400 K Robust Perpendicular Ferromagnetic Phase in a Topological Insulator

The quantum anomalous Hall effect (QAHE) that emerges under broken time-reversal symmetry in topological insulators (TI) exhibits many fascinating physical properties for potential applications in nano-electronics and spintronics. However, in transition-metal doped TI, the only experimentally demonstrated QAHE system to date, the effect is lost at practically relevant temperatures. This constraint is imposed by the relatively low Curie temperature (Tc) and inherent spin disorder associated with the random magnetic dopants. Here we demonstrate drastically enhanced Tc by exchange coupling TI to Tm3Fe5O12, a high-Tc magnetic insulator with perpendicular magnetic anisotropy. Signatures that the TI surface states acquire robust ferromagnetism are revealed by distinct squared anomalous Hall hysteresis loops at 400 K. Point-contact Andreev reflection spectroscopy confirms that the TI surface is indeed spin-polarized. The greatly enhanced Tc, absence of spin disorder, and perpendicular anisotropy are all essential to the occurrence of the QAHE at high temperatures

L-band GHz femtosecond passively harmonic mode-locked Er-doped fiber laser based on nonlinear polarization rotation

Via using an L-band optimized in-fiber polarizing grating device, a GHz L-band femtosecond passively harmonic mode-locked (PHML) Er-doped fiber laser based on nonlinear polarization rotation (NPR) is firstly demonstrated. 4.22 GHz pulses with the duration of 810 fs and super-mode suppression ratio (SMSR) of 32 dB are obtained under the pump power of 712 mW corresponding to 215th harmonic order. The central wavelength of 4.22 GHz pulses is 1581.7 nm with 10.1 nm 3-dB bandwidth. Furthermore, under this fixed pump power, higher harmonic orders can also be attained by rotating the polarization controllers (PCs) properly. The highest repetition rate we obtained is 7.41 GHz with the SMSR of 20.7 dB

Connexin 43 recruits E-cadherin expression and inhibits the malignant behaviour of lung cancer cells.

The interaction of connexin 43 and E-cadherin may play an important role in carcinogenesis and malignant behaviour of tumours. In this study, we examined the relationship between connexin 43 and E-cadherin in human non-small cell lung cancers (NSCLC). Expression levels of connexin 43 and E-cadherin were examined in 107 NSCLC specimens by immunohistochemistry. The connexin 43 gene was transfected into lung cancer LH7 cells. The protein localizations and levels of connexin 43 and E-cadherin were detected using immunofluorescence staining and western blot. Cell cycle and proliferation of lung cancer cells were examined using flow cytometry and MTT. We found that reduced expression of both connexin 43 and E-cadherin significantly correlated to poor differentiation, advanced TNM stage, and lymph note metastasis of NSCLCs. Connexin 43 and E-cadherin expression significantly correlated with each other. Over-expression of connexin 43 significantly induced E-cadherin expression. Moreover, connexin 43-transfected LH7 cells showed significantly decreased cell proliferation. The percentage of cells in G1 phase increased, while the number of cells in S and G2 phases significantly decreased. We concluded that concurrent reduction of connexin 43 and E-cadherin may contribute to the development of lung cancer. Connexin 43 may induce E-cadherin expression and inhibit cell proliferation and progression of lung cancer