A systematic study of magnetic field in Relativistic Heavy-ion Collisions in the RHIC and LHC energy regions

The features of magnetic field in relativistic heavy-ion collisions are systematically studied by using a modified magnetic field model in this paper. The features of magnetic field distributions in the central point are studied in the RHIC and LHC energy regions. We also predict the feature of magnetic fields at LHC $\sqrt{s_{NN}}$= 900, 2760 and 7000 GeV based on the detailed study at RHIC $\sqrt{s_{NN}}$ = 62.4, 130 and 200 GeV. The dependencies of the features of magnetic fields on the collision energies, centralities and collision time are systematically investigated, respectively.Comment: 8 pages, 7 figure

Multifractal and Network Analysis of Phase Transition

Many models and real complex systems possess critical thresholds at which the systems shift from one sate to another. The discovery of the early warnings of the systems in the vicinity of critical point are of great importance to estimate how far a system is from a critical threshold. Multifractal Detrended Fluctuation analysis (MF-DFA) and visibility graph method have been employed to investigate the fluctuation and geometrical structures of magnetization time series of two-dimensional Ising model around critical point. The Hurst exponent has been confirmed to be a good indicator of phase transition. Increase of the multifractality of the time series have been observed from generalized Hurst exponents and singularity spectrum. Both Long-term correlation and broad probability density function are identified to be the sources of multifractality of time series near critical regime. Heterogeneous nature of the networks constructed from magnetization time series have validated the fractal properties of magnetization time series from complex network perspective. Evolution of the topology quantities such as clustering coefficient, average degree, average shortest path length, density, assortativity and heterogeneity serve as early warnings of phase transition. Those methods and results can provide new insights about analysis of phase transition problems and can be used as early warnings for various complex systems.Comment: 23 pages, 11 figure

Study of phase transition of Potts model with DANN

A transfer learning method, domain adversarial neural network (DANN), is introduced to study the phase transition of two-dimensional q-state Potts model. With the DANN, we only need to choose a few labeled configurations automatically as input data, then the critical points can be obtained after training the algorithm. By an additional iterative process, the critical points can be captured to comparable accuracy to Monte Carlo simulations as we demonstrate it for q = 3, 5, 7 and 10. The type of phase transition (first or second-order) is also determined at the same time. Meanwhile, for the second-order phase transition at q = 3, we can calculate the critical exponent $\nu$ by data collapse. Furthermore, compared with the traditional supervised learning, the DANN is of higher accuracy with lower cost.Comment: 25 pages, 23 figure

Spatial and temporal variations of drought in Sichuan Province from 2001 to 2020 based on modified temperature vegetation dryness index (TVDI)

Drought indicators based on remote sensing include the temperature vegetation dryness index (TVDI) and the crop water stress index (CWSI). The data was processed using TVDI, which was calculated by parameterizing the MODIS EVI and LST data connection. For drought monitoring, we compared the efficiency of TVDI with that of CWSI, which is obtained from the MOD16A2 products. The study's findings revealed that drought conditions measured by TVDI and CWSI had a number of differences and similarities, which indicated that both CWSI and TVDI can be used for drought monitoring, although they had some discrepancies in the spatiotemporal characteristics of drought intensity in this region. High TVDI values were mainly concentrated on the northwestern Sichuan Plateau and mountainous areas of southwestern Sichuan, corresponding to extreme drought. The Panzhihua and the mountainous area of southwestern Sichuan had relatively high CWSI values. Spring had the highest TVDI values, followed by autumn and winter. TVDI and CWSI have different patterns, showing moderate and severe drought conditions in different areas. Overall, CWSI values showed a significant decreasing trend (P < 0.05) from 2001 to 2020. The overall trend change of TVDI was insignificant, mainly based on an insignificant increase and an insignificant decrease. An extremely significant decreasing trend, mainly concentrated in the eastern Sichuan basin plain, accounted for 15.54% of the entire province. Spring, summer, autumn, and winter account for 74.33%, 59.15%, 68.28%, and 64.87% of Sichuan Province, respectively, in total area change. The eastern Sichuan basin plain showed a significant increasing trend, accounting for 1.69% of the province in winter. TVDI correlates positively with Yearly maximum value of daily minimum temperature (TNx), Yearly maximum value of daily maximum temperature (TXx), and Yearly maximum consecutive one-day precipitation (PX1), and negatively with Yearly minimum value of daily maximum temperature (TXn), Yearly minimum value of daily minimum temperature (TNn), and Yearly mean temperature (YMT)

Surface characterization of maize-straw-derived biochar and their sorption mechanism for Pb2+ and methylene blue.

Biochar derived from straw is a potential low-cost adsorbent for metal ions and organic pollutants, but its practical application is still limited by the adsorption capacity. In this study, the correlation between the biochar's properties and pyrolysis temperature was explored. The adsorption mechanism was studied by monitoring the changes of biochar properties before and after adsorption using BET, SEM, XPS and FT-IR spectroscopy. The adsorption mechanism was revealed following the adsorption kinetics and the changes in biochar's properties before and after adsorption. The methylene blue (MB) and Pb2+ adsorption removal efficiency reached 95% at the initial concentration of 125 and 500 mg/L, respectively. Physisorption, chemisorption, and pore filling mechanisms determined the adsorption process of MB and Pb2+ on biochar. The Pb2+ adsorption process was highly affected by chemical co-precipitation at higher pyrolysis temperatures. The appearance of tar particles increased the adsorption rate of Pb2+. The biochar obtained at the pyrolysis temperature at 500, 800 and 900°C proved to be applicable for Pb2+ removal. Chemisorption and porosity dominated the MB adsorption, and biochars produced at pyrolysis temperatures of 200, 800 and 900°C are potential materials for MB removal. This study provides optimal pyrolysis conditions for transforming maize straw into valuable, low-cost materials for the removal of different pollutants

Alumina Extraction from Coal Fly Ash via Low-Temperature Potassium Bisulfate Calcination

Owing to the depletion of bauxite and increasing demand for alumina, calcination methods for extracting alumina from coal fly ash (CFA) were developed. However, these methods have disadvantages such as the need for high temperatures and the emission of toxic gases. Hence, in this study, Al2O3 was extracted from CFA via low-temperature potassium bisulfate calcination technology. Effects of the potassium bisulfate amount, calcination temperature, and calcination time on the alumina extraction efficiency were investigated using X-ray diffraction, thermal gravimetry, scanning electron microscopy, differential scanning calorimetry, and energy-dispersive spectroscopy. It was found that this technique could recover alumina efficiently, and potassium bisulfate significantly contributed to the degradation of mullite and corundum phases. Al2O3 in CFA was converted into soluble K3Al(SO4)(3). With a KHSO4/Al2O3 molar ratio of 7:1, calcining temperature of 230 degrees C, and calcining time of 3 h, the alumina extraction efficiency reached a maximum of 92.8%. The Avrami-Erofeev equation showed the best fit with the kinetic data for the low-temperature calcination of CFA with KHSO4. The activation energy was 28.36 kJ/mol

The complete mitochondrial genome and phylogenetic analysis of the ocellated angelshark: Squatina tergocellatoides Chen, 1963

The ocellated angelshark (Squatina tergocellatoides Chen, 1963) is a threatened shark within the family Squatinidae. In the present study, we reported the mitochondrial genome sequence of the ocellated angelshark. The complete mitochondrial genome is 16,683 bp in length and contains 37 mitochondrial genes and a control region as similar to most fishes. In addition, we constructed a maximum-likelihood phylogenetic tree of S. tergocellatoides and its relative species. This work will provide molecular data for further studies on S. tergocellatoides