Magnetothermoelectric DC conductivities from holography models with hyperscaling factor in Lifshitz spacetime

We investigate an Einstein-Maxwell-Dilaton-Axion holographic model and obtain two branches of a charged black hole solution with a dynamic exponent and a hyperscaling violation factor when a magnetic field presents. The magnetothermoelectric DC conductivities are then calculated in terms of horizon data by means of holographic principle. We find that linear temperature dependence resistivity and quadratic temperature dependence inverse Hall angle can be achieved in our model. The well-known anomalous temperature scaling of the Nernst signal and the Seebeck coefficient of cuprate strange metals are also discussed.Comment: 1+23 pages, 4 figures, references adde

Three-dimensional potential energy surface for fission of 236^{236}U within covariant density functional theory

We have calculated the three-dimensional potential energy surface (PES) for the fission of compound nucleus $^{236}$U using the covariant density functional theory with constraints on the axial quadrupole and octupole deformations $(\beta_2, \beta_3)$ as well as the nucleon number in the neck $q_N$. By considering the additonal degree of freedom $q_N$, coexistence of the elongated and compact fission modes is predicted for $0.9\lesssim \beta_3 \lesssim 1.3$. Remarkably, the PES becomes very shallow across a large range of quadrupole and octupole deformations for small $q_N$, and consequently, the scission line in $(\beta_2, \beta_3)$ plane will extend to a shallow band, which leads to a fluctuation for the estimated total kinetic energies by several to ten MeV and for the fragment masses by several to about ten nucleons

Anomaly Detection Framework of System Call Trace Based on Sequence and Frequency Patterns

The existing system call-based anomaly intrusion detection methods can’t accurately describe the behavior of the process by a single trace pattern.In this paper,the process behavior is modeled based on the sequence and frequency patterns of system call trace,and a data-driven anomaly detection framework is designed.The framework could detect both sequential and quantitative anomalies of the system call trace simultaneously.With the help of combinational window mechanism,the framework could realize offline fine-grained learning and online anomaly real-time detection by meeting different requirements of offline trai-ning and online detection for extracting trace information.Performance comparison experiments of unknown anomalies detection are conducted on the ADFA-LD intrusion detection standard dataset.The results show that,compared with the four traditional machine learning methods and four deep learning methods,the comprehensive detection performance of the framework improves by about 10%

M3PS: End-to-End Multi-Grained Multi-Modal Attribute-Aware Product Summarization in E-commerce

Given the long textual product information and the product image, Multi-Modal Product Summarization (MMPS) aims to attract customers' interest and increase their desire to purchase by highlighting product characteristics with a short textual summary. Existing MMPS methods have achieved promising performance. Nevertheless, there still exist several problems: 1) lack end-to-end product summarization, 2) lack multi-grained multi-modal modeling, and 3) lack multi-modal attribute modeling. To address these issues, we propose an end-to-end multi-grained multi-modal attribute-aware product summarization method (M3PS) for generating high-quality product summaries in e-commerce. M3PS jointly models product attributes and generates product summaries. Meanwhile, we design several multi-grained multi-modal tasks to better guide the multi-modal learning of M3PS. Furthermore, we model product attributes based on both text and image modalities so that multi-modal product characteristics can be manifested in the generated summaries. Extensive experiments on a real large-scale Chinese e-commence dataset demonstrate that our model outperforms state-of-the-art product summarization methods w.r.t. several summarization metrics

Age Differences of Salivary Alpha-Amylase Levels of Basal and Acute Responses to Citric Acid Stimulation Between Chinese Children and Adults

It remains unclear how salivary alpha-amylase (sAA) levels respond to mechanical stimuli in different age groups. In addition, the role played by the sAA gene (AMY1) copy number and protein expression (glycosylated and non-glycosylated) in sAA activity has also been rarely reported. In this study, we analyzed saliva samples collected before and after citric acid stimulation from 47 child and 47 adult Chinese subjects. We observed that adults had higher sAA activity and sAA glycosylated levels (glycosylated sAA amount/total sAA amount) in basal and stimulated saliva when compared with children, while no differences were found in total or glycosylated sAA amount between them. Interestingly, adults showed attenuated sAA activity levels increase over those of children after stimulation. Correlation analysis showed that total sAA amount, glycosylated sAA amount, and AMY1 copy number×total sAA amount were all positively correlated with sAA activity before and after stimulation in both groups. Interestingly, correlation r between sAA levels (glycosylated sAA amount and total sAA amount) and sAA activity decreased after stimulation in children, while adults showed an increase in correlation r. In addition, the correlation r between AMY1 copy number×total sAA amount and sAA activity was higher than that between AMY1 copy number, total sAA amount and sAA activity, respectively. Taken together, our results suggest that total sAA amount, glycosylated sAA amount, and the positive interaction between AMY1 copy number and total sAA amount are crucial in influencing sAA activity before and after stimulation in children and adults