Steady and dynamic magnetic phase transitions in interacting quantum dots arrays coupled with leads

We apply the Hubbard model, non-equilibrium Green's function (NEGF) theory, exact diagonalization (ED) and the hierarchical equations of motion (HEOM) method to investigate abundant magnetic phase transitions in the 1D interacting quantum dots arrays (QDA) sandwiched by non-interaction leads. The spin polarization phase transitions are firstly studied with a mean-field approximation. The many-body calculation of the ED method is then used to verify such transitions. We find with the weak device-leading couplings, the anti-ferromagnetic (AF) state only exists in the uniform odd-numbered QDA or the staggered-hopping QDA systems. With increasing the coupling strength or the bias potentials, there exists the magnetism-to non-magnetism phase transition. With the spin-resolved HEOM method we also investigate the detailed dynamic phase transition process of these lead-QDA-lead systems.Comment: 17 pages, 6 figure

Modes of Antiviral Action of Chemical Portions and Constituents from Woad Root Extract against Influenza Virus A FM1

Woad root has been used for the prevention of influenza for hundreds of years in many Asian countries. In this study, the antiviral modes of clemastanin B (CB), epigoitrin, phenylpropanoid portion (PEP), and the mixture of phenylpropanoids, alkaloids, and organic acid portions (PEP + ALK + OA) from wood root extract against influenza virus A FM1 were investigated. The results revealed that CB, epigoitrin, PEP, and PEP + ALK + OA exert their anti-influenza activity via inhibiting the virus multiplication, prophylaxis, and blocking the virus attachment. The primary mode of action of PEP and PEP + ALK + OA is the inhibition of virus replication. The inhibitory effect on virus attachment and multiplication is the main modes for epigoitrin. All the compounds or chemical portions from woad root extract tested in this study do not have direct virucidal activity. Our results provided the comprehensive analysis of the antiviral mechanism of wood root extract

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

Complete mitochondrail genome of Corydoras agassizii

We reported the complete mitochondrial genome yielded using next-generation sequencing of Corydoras agassizii in this study. The total length of the mitochondrial genome is 16,562 bp, with the base composition of 32.6% A, 25.9% T, 26.8% C, and 14.7% G, in several. It contains two rRNA genes, 22 tRNA genes, 13 protein-coding genes, and a 945 bp non-coding control region (D-loop region). The sequence of these genes is consistent with that found in the Siluriformes. The complete mitogenomes of C. agassizii and other 17 species of fish were constructed by phylogenetic analysis using Neighbour-Joining method. The topological structure indicated that species participating in the analysis belong to three groups (Siluridae, Loricariidae, and Callichthyidae) of nine genera, and the C. agassizii was clustered with other species from genus Corydoras. The external morphological characteristics of C. agassizii are consistent with the results of molecular classification, so the mitogenome can be used to identify Corydoras species in the future

A Role Based Framework for Robot Sensor Management

Sensors play an important role in the execution of robot tasks as an important component of understanding the world. In this paper, we propose a role-based sensor management framework on ROS (Robot Operating System), in which the role is a set of information needed for robot sensor development. Firstly, we develop a sensor management interface to facilitate the development of sensor applications on robot. And a subscriber module is proposed to shield the details of the sensor driver and the communication between processes, the sensor drivers on the robot are effectively managed. Robot sensors have different executive ability in different situations when robot performing tasks. For example, we know that RGB camera can collect a clear image when the light is strong, while generate a blurred image in weak light environment. Secondly, we propose an environment based sensor role dynamic evaluation mechanism to get the confidence of sensor in a certain environment. The confidence represents the executive ability of sensor when performing tasks. The confidence provides the basis for switching the task schemes. In the mechanism we can dynamically configure the environment information and confidence calculation method. In the experiment phase, we verify the effectiveness of the framework through a robot patrol task. Experiment results show that our framework can effectively manage the robot sensors with a certain environmental adaptability