Langevin dynamics of heavy quarks in a soft-hard factorized approach

By utilizing a soft-hard factorized model, which combines a thermal perturbative description of soft scatterings and a perturbative QCD-based calculation for hard collisions, we study the energy and temperature dependence of the heavy quark diffusion coefficients in Langevin dynamics. The adjustable parameters are fixed from the comprehensive model-data comparison. We find that a small value of the spatial diffusion coefficient at transition temperature is preferred by data $2\pi TD_{s}(T_{c}) \simeq 6$. With the parameter-optimized model, we are able to describe simultaneously the prompt $D^{0}$ $R_{\rm AA}$ and $v_{2}$ data at $p_{\rm T}\le8$ GeV in Pb--Pb collisions at $\sqrt{s_{\rm NN}}=2.76$ and $\sqrt{s_{\rm NN}}=5.02$ TeV. We also make predictions for non-prompt $D^{0}$ meson for future experimental tests down to the low momentum region.Comment: 13 pages, 10 figure

Expression of MiR-9 promotes proliferation, migration and differentiation of human neural stem cells

Purpose: To investigate the effect of miR-9 on the proliferation, differentiation and migration of human neural stem cells (NSCs).Methods: The expression of miR-9 was investigated by quantitative real-time polymerase chain reaction (RT-PCR). Cell proliferation was assessed by cell counting kit-8 (CCK8) assay, while cell migration was studied by Transwell assay. The effect of miR-9 on differentiation of NSCs was investigated by western blot analysis of key differentiation marker proteins. Protein expression was determined by western blotting.Results: Transfection and over-expression of miR-9 in NSCs significantly enhanced the proliferation of NSCs (p < 0.05) in a time-dependent manner, as was evident from CCK8 assay data. MiR-9 overexpression caused down-regulation of Nestin and SOX-2, and up-regulation of Tuj-1 and MAP-2. The migration of NSCs was 37 % in the cells transfected with empty vector, compared to 68 % in the cells transfected with miR-9. This effect of miR-9 on cell migration was accompanied by up-regulation of matrix metallopeptidase 9 (MMP-9) and matrix metallopeptidase 2 (MMP-2).Conclusion: These results show that miR-9 promotes the proliferation, differentiation and migration of NSCs, and thus may be an important drug target for the generation of NSCs.Keywords: Neural stem cells, MicroRNA, Mir-9, Migration, Differentiation, Proliferatio

The position profiles of order cancellations in an emerging stock market

Order submission and cancellation are two constituent actions of stock trading behaviors in order-driven markets. Order submission dynamics has been extensively studied for different markets, while order cancellation dynamics is less understood. There are two positions associated with a cancellation, that is, the price level in the limit-order book (LOB) and the position in the queue at each price level. We study the profiles of these two order cancellation positions through rebuilding the limit-order book using the order flow data of 23 liquid stocks traded on the Shenzhen Stock Exchange in the year 2003. We find that the profiles of relative price levels where cancellations occur obey a log-normal distribution. After normalizing the relative price level by removing the factor of order numbers stored at the price level, we find that the profiles exhibit a power-law scaling behavior on the right tails for both buy and sell orders. When focusing on the order cancellation positions in the queue at each price level, we find that the profiles increase rapidly in the front of the queue, and then fluctuate around a constant value till the end of the queue. These profiles are similar for different stocks. In addition, the profiles of cancellation positions can be fitted by an exponent function for both buy and sell orders. These two kinds of cancellation profiles seem universal for different stocks investigated and exhibit minor asymmetry between buy and sell orders. Our empirical findings shed new light on the order cancellation dynamics and pose constraints on the construction of order-driven stock market models.Comment: 17 pages, 6 figures and 6 table

A particle-based cohesive crack model for brittle fracture problems

Numerical simulations of the fracture process are challenging, and the discrete element (DE) method is an effective means to model fracture problems. The DE model comprises the DE connective model and DE contact model, where the former is used for the representation of isotropic solids before cracks initiate, while the latter is employed to represent particulate materials after cracks propagate. In this paper, a DE particle-based cohesive crack model is developed to model the mixed-mode fracture process of brittle materials, aiming to simulate the material transition from a solid phase to a particulate phase. Because of the particle characteristics of the DE connective model, the cohesive crack model is constructed at inter-particle bonds in the connective stage of the model at a microscale. A potential formulation is adopted by the cohesive zone method, and a linear softening relation is employed by the traction-separation law upon fracture initiation. This particle-based cohesive crack model bridges the microscopic gap between the connective model and the contact model and, thus, is suitable to describe the material separation process from solids to particulates. The proposed model is validated by a number of standard fracture tests, and numerical results are found to be in good agreement with the analytical solutions. A notched concrete beam subjected to an impact loading is modeled, and the impact force obtained from the numerical modeling agrees better with the experimental result than that obtained from the finite element method

Electromagnetic Radiation Control for Nonlinear Dynamics of Hopfield Neural Networks

© 2024 Author(s). Published under an exclusive license by AIP Publishing. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1063/5.0194928Electromagnetic radiation (EMR) affects the dynamical behavior of the nervous system, and appropriate EMR helps to study the dynamic mechanism of the nervous system. This paper uses a sophisticated four-dimensional Hopfield neural network (HNN) model augmented with one or more memristors to simulate the effects of EMR. We focus on the chaotic dynamics of HNN under the influence of EMR. Complex dynamical behaviors are found and transient chaotic phenomena have the same initial value sensitivity, showing how transient chaos is affected by EMR. Multiperiodic phenomena induced by quasi-periodic alternations are found in the dual EMR, as well as the suppression properties of the dual EMR for system chaos. This implies that the dynamical behavior of the HNN system can be controlled by varying the amount of EMR or the number of affected neurons in the HNN. Finally, a strong validation of our proposed model is provided by Multisim and FPGA hardware.Peer reviewe

Rapid detection of sacbrood virus (SBV) by one-step reverse transcription loop-mediated isothermal amplification assay

<p>Abstract</p> <p>Background</p> <p><it>Sacbrood virus </it>(SBV) primarily infects honeybee broods, and in order to deal with the problem cost effective detection methods are required.</p> <p>Findings</p> <p>A one-step reverse transcription loop-mediated isothermal amplification (RT-LAMP) assay was developed for the rapid identification of SBV. The data demonstrated that, in a simple water bath, SBV RNA could be detected as early as 20 min at 65°C, and a positive amplification reaction was visible to the naked eye due to a color change brought on by the addition of nucleic acid stain SYBR Green.</p> <p>Conclusions</p> <p>The current study presents a method for the rapid and simple detection of SBV by RT-LAMP with high sensitivity and analytic specificity.</p