Sneutrino DM in the NMSSM with inverse seesaw mechanism

In supersymmetric theories like the Next-to-Minimal Supersymmetric Standard Model (NMSSM), the lightest neutralino with bino or singlino as its dominant component is customarily taken as dark matter (DM) candidate. Since light Higgsinos favored by naturalness can strength the couplings of the DM and thus enhance the DM-nucleon scattering rate, the tension between naturalness and DM direct detection results becomes more and more acute with the improved experimental sensitivity. In this work, we extend the NMSSM by inverse seesaw mechanism to generate neutrino mass, and show that in certain parameter space the lightest sneutrino may act as a viable DM candidate, i.e. it can annihilate by multi-channels to get correct relic density and meanwhile satisfy all experimental constraints. The most striking feature of the extension is that the DM-nucleon scattering rate can be naturally below its current experimental bounds regardless of the higgsino mass, and hence it alleviates the tension between naturalness and DM experiments. Other interesting features include that the Higgs phenomenology becomes much richer than that of the original NMSSM due to the relaxed constraints from DM physics and also due to the presence of extra neutrinos, and that the signatures of sparticles at colliders are quite different from those with neutralino as DM candidate.Comment: 33 page

Explaining the DAMPE data with scalar dark matter and gauged U(1)Le−LμU(1)_{L_e-L_\mu} interaction

Inspired by the peak structure observed by recent DAMPE experiment in $e^+e^-$ cosmic-ray spectrum, we consider a scalar dark matter (DM) model with gauged $U(1)_{L_e-L_\mu}$ symmetry, which is the most economical anomaly-free theory to potentially explain the peak by DM annihilation in nearby subhalo. We utilize the process $\chi \chi \to Z^\prime Z^\prime \to l \bar{l} l^\prime \bar{l}^\prime$, where $\chi$, $Z^\prime$, $l^{(\prime)}$ denote the scalar DM, the new gauge boson and $l^{(\prime)} =e, \mu$, respectively, to generate the $e^+e^-$ spectrum. By fitting the predicted spectrum to the experimental data, we obtain the favored DM mass range $m_\chi \simeq 3060^{+80}_{-100} \, {\rm GeV}$ and $\Delta m \equiv m_\chi - m_{Z^\prime} \lesssim 14 \, {\rm GeV}$ at $68\%$ Confidence Level (C.L.). Furthermore, we determine the parameter space of the model which can explain the peak and meanwhile satisfy the constraints from DM relic abundance, DM direct detection and the collider bounds. We conclude that the model we consider can account for the peak, although there exists a tension with the constraints from the LEP-II bound on $m_{Z^\prime}$ arising from the cross section measurement of $e^+e^- \to Z^{\prime\ast} \to e^+ e^-$.Comment: 15 pages, 4 figure

Hydropower Development in China: A Leapfrog Development Secured by Technological Progress of Dam Construction

It has been over 110 years since China’s first hydropower station, Shilongba Hydropower Station, was built in 1910. With the support of advanced dam construction technology, the Chinese installed capacity keeps rising rapid growth, hitting around 356 GW nationwide by the end of 2019, and the annual electricity production exceeds 10,000 TWh. At present, China contributes to 25% of global installed hydropower capacity, ranking first in the world for 20 consecutive years since 2001 and surpassing the combined of the 4 countries ranking second to fifth. This paper reviews China’s progress in the context of global hydropower development and examines the role of technological advance in supporting China’s hydropower projects, especially dam construction technology. China is currently actively promoting the “integration of wind, solar, hydro, and coal power generation and energy storage” and building a smart grid of multi-energy complementary power generation. New technologies and new concepts are expected to continue to lead the world’s hydropower development trends

Parallel numerical simulation for a super large-scale compositional reservoir

 A compositional reservoir simulation model with ten-million grids is successfully computed using parallel processing techniques. The load balance optimization principle for parallel calculation is developed, which improves the calculation speed and accuracy, and provides a reliable basis for the design of reservoir development plan. Taking M reservoir as an example, the parallel numerical simulation study of compositional model with ten million grids is carried out. When the number of computational nodes increases, message passing processes and data exchange take much time, the proportion time of solving equation is reduced. When the CPU number increases, the creation of Jacobian matrix process has the higher acceleration ratio, and the acceleration ratio of I/O process become lower. Therefore, the I/O process is the key to improve the acceleration ratio. Finally, we study the use of GPU and CPU parallel acceleration technology to increase the calculation speed. The results show that the technology is 2.4 ∼ 5.4 times faster than CPU parallel technology. The more grids there are, the better GPU acceleration effect it has. The technology of parallel numerical simulation for compositional model with ten-million grids presented in this paper has provided the foundation for fine simulation of complex reservoirs.Cited as: Lian, P., Ji, B., Duan, T., Zhao, H., Shang, X. Parallel numerical simulation for a super large-scale compositional reservoir. Advances in Geo-Energy Research, 2019, 3(4): 381-386, doi: 10.26804/ager.2019.04.0

Enhancing Security Patch Identification by Capturing Structures in Commits

With the rapid increasing number of open source software (OSS), the majority of the software vulnerabilities in the open source components are fixed silently, which leads to the deployed software that integrated them being unable to get a timely update. Hence, it is critical to design a security patch identification system to ensure the security of the utilized software. However, most of the existing works for security patch identification just consider the changed code and the commit message of a commit as a flat sequence of tokens with simple neural networks to learn its semantics, while the structure information is ignored. To address these limitations, in this paper, we propose our well-designed approach E-SPI, which extracts the structure information hidden in a commit for effective identification. Specifically, it consists of the code change encoder to extract the syntactic of the changed code with the BiLSTM to learn the code representation and the message encoder to construct the dependency graph for the commit message with the graph neural network (GNN) to learn the message representation. We further enhance the code change encoder by embedding contextual information related to the changed code. To demonstrate the effectiveness of our approach, we conduct the extensive experiments against six state-of-the-art approaches on the existing dataset and from the real deployment environment. The experimental results confirm that our approach can significantly outperform current state-of-the-art baselines

DEC1 binding to the proximal promoter of CYP3A4 ascribes to the downregulation of CYP3A4 expression by IL-6 in primary human hepatocytes

In this study, we provided molecular evidences that interleukin-6 (IL-6) contributed to the decreased capacity of oxidative biotransformation in human liver by suppressing the expression of cytochrome P450 3A4 (CYP3A4). After human hepatocytes were treated with IL-6, differentially expressed in chondrocytes 1 (DEC1) expression rapidly increased, and subsequently, the CYP3A4 expression decreased continuously. Furthermore, the repression of CYP3A4 by IL-6 occurred after the increase of DEC1 in primary human hepatocytes. In HepG2 cells, knockdown of DEC1 increased the CYP3A4 expression and its enzymatic activity. In addition, it partially abolished the decreased CYP3A4 expression as well as its enzymatic activity induced by IL-6. Consistent with this, overexpression of DEC1 markedly reduced the CYP3A4 promoter activity and the CYP3A4 expression as well as its enzymatic activity. Using sequential truncation and site directed mutagenesis of CYP3A4 proximal promoter with DEC1 construct, we showed that DEC1 specifically bound to CCCTGC sequence in the proximal promoter of CYP3A4, which was validated by EMSA and ChIP assay. These findings suggest that the repression of CYP3A4 by IL-6 is achieved through increasing the DEC1 expression in human hepatocytes, the increased DEC1 binds to the CCCTGC sequence in the promoter of CYP3A4 to form CCCTGC–DEC1 complex, and the complex downregulates the CYP3A4 expression and its enzymatic activity