Further Development of the Improved QMD Model and its Applications to Fusion Reaction near Barrier

The Improved Quantum Molecular Dynamics model is further developed by introducing new parameters in interaction potential energy functional based on Skyrme interaction of SkM$^{*}$ and SLy series. The properties of ground states of selected nuclei can be reproduced very well. The Coulomb barriers for a series of reaction systems are studied and compared with the results of the proximity potential. The fusion excitation functions for a series of fusion reactions are calculated and the results are in good agreement with experimental data.Comment: 17 pages, 10 figures, PRC accepte

Connection between the Largest Lyapunov Exponent, Density Fluctuation and Multifragmentation in Excited Nuclear Systems

Within a quantum molecular dynamics model we calculate the largest Lyapunov exponent (LLE), density fluctuation and mass distribution of fragments for a series of nuclear systems at different initial temperatures. It is found that the $LLE$ peaks at the temperature ("critical temperature") where the density fluctuation reaches a maximal value and the mass distribution of fragments is best fitted by the Fisher's power law from which the critical exponents for mass and charge distribution are obtained. The time-dependent behavior of the LLE and density fluctuation is studied. We find that the time scale of the density fluctuation is much longer than the inverse LLE, which indicates that the chaotic motion can be well developed during the process of fragment formation. The finite-size effect on "critical temperature" for nuclear systems ranging from Calcium to superheavy nuclei is also studied.Comment: 18 pages, 8 figures Submited to Phys. Rev.

Applications of Skyrme energy-density functional to fusion reactions spanning the fusion barriers

The Skyrme energy density functional has been applied to the study of heavy-ion fusion reactions. The barriers for fusion reactions are calculated by the Skyrme energy density functional with proton and neutron density distributions determined by using restricted density variational (RDV) method within the same energy density functional together with semi-classical approach known as the extended semi-classical Thomas-Fermi method. Based on the fusion barrier obtained, we propose a parametrization of the empirical barrier distribution to take into account the multi-dimensional character of real barrier and then apply it to calculate the fusion excitation functions in terms of barrier penetration concept. A large number of measured fusion excitation functions spanning the fusion barriers can be reproduced well. The competition between suppression and enhancement effects on sub-barrier fusion caused by neutron-shell-closure and excess neutron effects is studied.Comment: 28 pages, 13 figures and 2 tables. accepted by Nucl. Phys.

A review of epilepsy detection and prediction methods based on EEG signal processing and deep learning

Epilepsy is a chronic neurological disorder that poses significant challenges to patients and their families. Effective detection and prediction of epilepsy can facilitate patient recovery, reduce family burden, and streamline healthcare processes. Therefore, it is essential to propose a deep learning method for efficient detection and prediction of epileptic electroencephalography (EEG) signals. This paper reviews several key aspects of epileptic EEG signal processing, focusing on epilepsy detection and prediction. It covers publicly available epileptic EEG datasets, preprocessing techniques, feature extraction methods, and deep learning-based networks used in these tasks. The literature is categorized based on patient independence, distinguishing between patient-independent and non-patient-independent studies. Additionally, the evaluation methods are classified into general classification indicators and specific epilepsy prediction criteria, with findings organized according to the prediction cycles reported in various studies. The review reveals several important insights. Despite the availability of public datasets, they often lack diversity in epilepsy types and are collected under controlled conditions that may not reflect real-world scenarios. As a result, signal preprocessing methods tend to be limited and may not fully represent practical conditions. Feature extraction and network designs frequently emphasize fusion mechanisms, with recent advances in Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) showing promising results, suggesting that new network models warrant further exploration. Studies using patient-independent data generally produce better results than those relying on non-patient-independent data. Metrics based on general classification methods typically perform better than those using specific epilepsy prediction criteria, though future research should focus on the latter for more accurate evaluation. Epilepsy prediction cycles are typically kept under 1 h, with most studies concentrating on intervals of 30 min or less

Color-tunable emissions and multi-mode optical thermometer in Mg3Gd2Ge3O12: Tb3+, Eu3+ phosphors

A series of Mg3Gd2Ge3O12 phosphors co-doped with Tb3+ and Eu3+ was produced using a solid-state method. The phosphors doped solely with Tb3+ have blue emission (383 nm) and green emission (544 nm), and the addition of Eu3+ can produce red emission (610 nm). The transformation of green-orange could be achieved by adjusting the doping amount of Eu3+ because of the energy transfer (ET) from Tb3+ to Eu3+. The ET process was attributed to dipole-dipole interaction. In addition, the emission intensities of three levels and the lifetimes of 5D3 decrease with increasing temperature, and the color changes are produced. According to these interesting phenomena, a optical thermometer with different modes was designed utilizing the fluorescence intensity ratio (FIR) and the fluorescence lifetime (FL) model. The maximum values of relative sensitivity (Sr) were found to be 1.24% K-1 at 494 K (FIR = I383/I610), 0.43% K-1 at 423 K (FIR =I544/I610) and 1.38% ms∙K-1 at 465 K (FL). The great repeatability of samples can be got by cyclic testing. The above results demonstrate that Mg3Gd2Ge3O12: Tb3+, Eu3+ samples are potential materials for visual optical temperature measurement

Profiles of Mathematics Anxiety Among 15-Year-Old Students: A Cross-Cultural Study Using Multi-Group Latent Profile Analysis

Using PISA 2012 data, the present study explored profiles of mathematics anxiety (MA) among 15-year old students from Finland, Korea, and the United States to determine the similarities and differences of MA across the three national samples by applying a multi-group latent profile analysis (LPA). The major findings were that (a) three MA profiles were found in all three national samples, i.e., Low MA, Mid MA, and High MA profile, and (b) the percentages of students classified into each of the three MA profiles differed across the Finnish, Korean, and American samples, with United States having the highest prevalence of High MA, and Finland the lowest. Multi-group LPA also provided clear and useful latent profile separation. The High MA profile demonstrated significant poorer mathematics performance and lower mathematics interest, self-efficacy, and self-concept than the Mid and Low MA profiles. Same differences appeared between the Mid and Low MA profiles. The implications of the findings seem clear: (1) it is possible that there is some relative level of universality in MA among 15-year old students which is independent of cultural context; and (2) multi-group LPA could be a useful analytic tool for research on the study of classification and cultural differences of MA

Effect of Process Mineralogical Properties on Floatability of a Copper-cobalt Ore in Zambia

This is an article in the field of mining engineering. The process mineralogy is the prerequisite for flotation. The influence of ore fineness and the degree of dissociation of the target mineral monomer on ore floatability can be used to guide the selection of suitable flotation conditions. A systematic study of the process mineralogy of a copper-cobalt ore was carried out using the methods of X-ray fluorescence analysis, X-ray powder diffraction analysis, scanning electron microscopy, and electron polarizing microscopy. Based on the process mineralogy studies, the flotation tests were carried out, at the condition of grinding fineness of -0.074 mm 70%, with a process of one roughing-two scavenging-two cleaning closed-circuit flowsheet. The sulfide concentrate with the grade of Cu 21.04%, Co 9.83% and the recovery of Cu 92.88%, Co 92.84% was achieved

Bioactivity-based HPLC tandem Q/TOF for alpha-glucosidase inhibitors : Screening, identification, and quantification from actinomycetes

This study was performed to screen α-glucosidase inhibitors from the actinomycete metabolites library by high throughput screening. Twelve strains of actinomycete were considered to be α-glucosidase inhibitors producing strains; then effective inhibitory strain PW409 was fermented and separated by bioactivity based HPLC, two fractions showing remarkable inhibitory activities; the two compounds were identified as 1-deoxynojirimycin (DNJ) and miglitol by mass spectrometry, comparing with authentic standards, and relevant literature. The quantification analysis of DNJ and miglitol by HPLC-MS/MS showed that the average concentrations of DNJ and miglitol in broth of strain PW409 were 11.2 and 95.8 mg/L, respectively. This is the first report about Streptomyces sp. products α-glucosidase inhibitor miglitol. The strain PW409 has potential application in biosynthesis and biotransformation of antidiabetes drug miglitol. The method can be utilized for new α-glucosidase inhibitors discovering and development from other inhibitory activity strains.Colegio de Farmacéuticos de la Provincia de Buenos Aire