Study of Balance Equations for Hot-Electron Transport in an Arbitrary Energy Band (III)

By choosing an electron gas resting instead of drifting in the laboratory coordinate system as the initial state, the first order perturbation calculation of the previous paper (Phys. Stat. Sol. (b) 198, 785(1996)) is revised and extended to include the high order field corrections in the expression for the frictional forces and the energy transfer rates. The final expressions are formally the same as those in first order in the electric field, but the distribution functions of electrons appearing in them are defined by different expressions. The problems relative to the distribution function are discussed in detail and a new closed expression for the distribution function is obtained. The nonlinear impurity-limited resistance of a strong degenerate electron gas is computed numerically. The result calculated by using the new expression for the distribution function is quite different from that using the displaced Fermi function when the electric field is sufficiently high.Comment: 15 pages with 3 PS figures, RevTeX, to be published in Physica Status Solidi (b

Numerical Simulation Research on the Characteristics of Tide and Salinity at Pearl River Estuary in China

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Determination of impact parameter in high-energy heavy-ion collisions via deep learning

In this study, Au+Au collisions with the impact parameter of $0 \leq b \leq 12.5$ fm at $\sqrt{s_{NN}} = 200$ GeV are simulated by the AMPT model to provide the preliminary final-state information. After transforming these information into appropriate input data (the energy spectra of final-state charged hadrons), we construct a deep neural network (DNN) and a convolutional neural network (CNN) to connect final-state observables with impact parameters. The results show that both the DNN and CNN can reconstruct the impact parameters with a mean absolute error about $0.4$ fm with CNN behaving slightly better. Then, we test the neural networks for different beam energies and pseudorapidity ranges in this task. It turns out that these two models work well for both low and high energies. But when making test for a larger pseudorapidity window, we observe that the CNN shows higher prediction accuracy than the DNN. With the method of Grad-CAM, we shed light on the `attention' mechanism of the CNN model

Empirical metallicity-dependent calibrations of effective temperature against colours for dwarfs and giants based on interferometric data

We present empirical metallicity-dependent calibrations of effective temperature against colours for dwarfs of luminosity classes IV and V and for giants of luminosity classes II and III, based on a collection from the literature of about two hundred nearby stars with direct effective temperature measurements of better than 2.5 per cent. The calibrations are valid for an effective temperature range 3,100 - 10,000 K for dwarfs of spectral types M5 to A0 and 3,100 - 5,700 K for giants of spectral types K5 to G5. A total of twenty-one colours for dwarfs and eighteen colours for giants of bands of four photometric systems, i.e. the Johnson ($UBVR_{\rm J}I_{\rm J}JHK$), the Cousins ($R_{\rm C}I_{\rm C}$), the Sloan Digital Sky Survey (SDSS, $gr$) and the Two Micron All Sky Survey (2MASS, $JHK_{\rm s}$), have been calibrated. Restricted by the metallicity range of the current sample, the calibrations are mainly applicable for disk stars ([Fe/H]$\,\gtrsim\,-1.0$). The normalized percentage residuals of the calibrations are typically 2.0 and 1.5 per cent for dwarfs and giants, respectively. Some systematic discrepancies at various levels are found between the current scales and those available in the literature (e.g. those based on the infrared flux method IRFM or spectroscopy). Based on the current calibrations, we have re-determined the colours of the Sun. We have also investigated the systematic errors in effective temperatures yielded by the current on-going large scale low- to intermediate-resolution stellar spectroscopic surveys. We show that the calibration of colour ($g-K_{\rm s}$) presented in the current work provides an invaluable tool for the estimation of stellar effective temperature for those on-going or upcoming surveys.Comment: 28 pages, 19 figures, 8 tables, accepted for publication in MNRA

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie

The High-Order Symplectic Finite-Difference Time-Domain Scheme

published_or_final_versio

Elevated circulating level of P2X7 receptor is related to severity of coronary artery stenosis and prognosis of acute myocardial infarction

Background: Acute myocardial infarction (AMI) is a severely life-threatening cardiovascular disease. Previous research has identified an association between the P2X7 receptor (P2X7R) and the development of atherosclerosis. However, the correlation of its expression with the clinical prognosis of patients with AMI remains unclear. The present study aimed to investigate the potential role of P2X7R in Chinese patients with AMI. Methods: Seventy-nine patients with AMI and 48 controls were consecutively enrolled in this prospective observational study. Circulating P2X7R mRNA expression levels and other clinical variables were determined upon admission to the hospital. Patients were followed up for 360 days, and the end-point was considered as the occurrence of major adverse cardiovascular events (MACE). Results: Circulating P2X7R mRNA expression level in peripheral blood mononuclear cells of patients with AMI were significantly higher than those in controls and had promising diagnostic ability of AMI with an area under the curve of 0.928. Furthermore, P2X7R was demonstrated to be correlated positively with the severity of coronary artery stenosis. Additionally, this is the first study to indicate that higher P2X7R mRNA expression is associated with a higher rate of MACE within 360 days after AMI. Conclusions: The present study showed that the circulating level of P2X7R was elevated in AMI patients and was closely associated with the severity of coronary artery stenosis and prognosis of AMI