Effects of sequential decay on collective flows and nuclear stopping power in heavy-ion collisions at intermediate energies

In this study, the rapidity distribution, collective flows, and nuclear stopping power in ^(197)Au+^(197)Au collisions at intermediate energies were investigated using the ultrarelativistic quantum molecular dynamics(UrQMD) model with GEMINI++ code. The UrQMD model was adopted to simulate the dynamic evolution of heavy-ion collisions, whereas the GEMINI++ code was used to simulate the decay of primary fragments produced by UrQMD. The calculated results were compared with the INDRA and FOPI experimental data. It was found that the rapidity distribution, collective flows, and nuclear stopping power were affected to a certain extent by the decay of primary fragments, especially at lower beam energies. Furthermore, the experimental data of the collective flows and nuclear stopping power at the investigated beam energies were better reproduced when the sequential decay effect was included.

Collective flow and nuclear stopping in heavy ion collisions in Fermi energy domain

The effects of the in-medium nucleon-nucleon(NN) elastic cross section on the observables in heavy ion collisions in the Fermi energy domain are investigated within the framework of the ultrarelativistic quantum molecular dynamics model. The results simulated using medium correction factors of F=σ_(NN)^(in-medium)/σ_(NN)^(free)=0.2,0.3,0.5,and the density-and momentum-dependent factor obtained from the FU3 FP1 parametrization are compared with the FOPI and INDRA experimental data. It is found that the calculations using the correction factors F=0.2 and 0.5 reproduce the experimental data(i.e.,collective flow and nuclear stopping) at 40 and 150 MeV/nucleon, respectively. Calculations with the FU3 FP1 parametrization can best fit these experimental data. These conclusions can be confirmed in both^(197)Au+^(197)Au and^(129)Xe+^(120)Sn.

Effect of melt cooling rate on glass transition kinetics and structural relaxation of Vit1 metallic glass

The thin ribbons and the bulk cylindrical rods with diameters of 2 mm and 10 mm of the Vit1 metallic glass(MG)were prepared by the single roller melt spinning method and the copper mold injection casting method,respectively.The cooling rates of the samples during melt solidification were evaluated.The glass transition behaviors of three groups of MG samples with different solidification cooling rates were studied by differential scanning calorimetry(DSC)at different heating rates.The effects of melt cooling rate on the glass transition kinetic parameters such as apparent activation energy(E)and fragility parameter(m)of the Vit1 MG were studied using the Kissinger and the Vogel-Fulcher-Tammann(VFT)equations.Additionally,the structural relaxation enthalpy(ΔHrel)of three groups of MG samples was quantitatively analyzed by DSC through multi-step temperature rise and fall measurements.Results show that the melt cooling rate(R)has a significant effect on the glass transition kinetics and the structural relaxation of the Vit1 MG.As R decreases in the order of magnitude,the glass transition temperature(Tg),E,m,andΔHrel of the Vit1 MG gradually decreases.Furthermore,in the range of the experimental cooling rates,E,m,andΔHrel all have an approximately linear relationship with lgR.

Establishment and evaluation of a theater influenza monitoring platform

Background:Influenza is an acute respiratory infectious disease with a high incidence rate in the Chinese army,which directly disturbs military training and affects soldiers’health.Influenza surveillance systems are widely used around the world and play an important role in influenza epidemic prevention and control.Methods:As a theater centers for disease prevention and control,we established an influenza monitoring platform(IMP)in 2014 to strengthen the monitoring of influenza-like illness and influenza virus infection.In this study,we introduced the constitution,influenza virus detection,and quality control for an IMP.The monitoring effect was also evaluated by comparing the monitoring data with data from national influenza surveillance systems.The experiences and problems associated with the platform also were summarized.Results:A theater IMP was established based on 3 levels of medical units,including monitoring sites,testing laboratories and a checking laboratory.A series of measures were taken to guarantee the quality of monitoring,such as technical training,a unified process,sufficient supervision and timely communication.The platform has run smoothly for 3 monitoring years to date.In the 2014–2015 and 2016–2017 monitoring years,sample amount coincided with that obtained from the National Influenza Surveillance program.In the 2015–2016 monitoring year,due to the strict prevention and control measures,an influenza epidemic peak was avoided in monitoring units,and the monitoring data did not coincide with that of the National Influenza Surveillance program.Several problems,including insufficient attention,unreasonable administrative intervention or subordination relationships,and the necessity of detection in monitoring sites were still observed.Conclusion:A theater IMP was established rationally and played a deserved role in the prevention and control of influenza.However,several problems remain to be solved.

Total Nasal Tip Defect:Bilateral Lateral Nasal Artery Flaps for Lining Reconstruction

Background In full-thickness nasal defects,the internal lining is perhaps the most challenging aspect of the three layers to rebuild.Nasal damage is usually more concentrated on the tip,soft triangles,alar wings,and columella,but the lateral nasal arteries are often left intact and the damage to the dorsal sidewalls are normally superficial.Methods Twelve patients who required total nasal reconstruction received a forehead flap placement as external coverage and autologous rib cartilage as structural support.Residual normal/superficial scar tissue flaps on the dorsal sidewalls with lateral nasal artery pedicles were mobilized and designed for internal lining repair without creating secondary donor site damage.The flaps were then turned 180°downward and placed between the alar medial angles and the fornix.Results No total lining flap necrosis occurred in all the patients.Partial necrosis occurred on the distal edge owing to overpressure of the nostril splint to the flaps;however,the wounds eventually healed,and the nasal structural integrity was preserved.The patients were satisfied with the aesthetic results and had no complaints of airway stenosis.Conclusions Lateral nasal artery pedicle dorsal sidewall skin flaps are appropriately thick,providing enough nostril circumferential support to improve airway stenosis.It allows sufficient blood supply and creates no extra donor site damage.Blood vessels and skin flaps are often undamaged,thereby allowing maximum application in total nasal reconstruction.

Effects of CeO_(2)pre-calcined at different temperatures on the performance of Pt/CeO_(2)-C electrocatalyst for methanol oxidation reaction

Pt/CeO_(2)-C catalysts with CeO_(2)pre-calcined at 300-600 ℃were synthesized by combining hydrothermal calcination and wet im-pregnation.The effects of the pre-calcined CeO_(2)on the performance of Pt/CeO_(2)-C catalysts in methanol oxidation were investigated.The Pt/CeO_(2)-C catalysts with pre-calcined CeO_(2)at 300-600 ℃showed an average particle size of 2.6-2.9 nm and exhibited better methanol elec-tro-oxidation catalytic activity than the commercial Pt/C catalyst.In specific,the Pt/CeO_(2)-C catalysts with pre-calcined CeO_(2)at 400 ℃dis-played the highest electrochemical surface area value of 68.14 m2·g−1 and If/Ib ratio(the ratio of the forward scanning peak current density(If)and the backward scanning peak current density(Ib))of 1.26,which are considerably larger than those(53.23 m2·g−1 and 0.79,respectively)of the commercial Pt/C catalyst,implying greatly enhanced CO tolerance.

Machine learning the nuclear mass

Background:The masses of-2500 nuclei have been measured experimentally;however,>7000 isotopes are predicted to exist in the nuclear landscape from H(Z=1)to Og(Z=118)based on various theoretical calculations.Exploring the mass of the remaining isotopes is a popular topic in nuclear physics.Machine learning has served as a powerful tool for learning complex representations of big data in many fields.Purpose:We use Light Gradient Boosting Machine(LightGBM),which is a highly efficient machine learning algorithm,to predict the masses of unknown nuclei and to explore the nuclear landscape on the neutron-rich side from learning the measured nuclear masses.Methods:Several characteristic quantities(e.g.,mass number and proton number)are fed into the LightGBM algorithm to mimic the patterns of the residual δ(Z,A)between the experimental binding energy and the theoret-ical one given by the liquid-drop model(LDM),Duflo–Zucker(DZ,also dubbed DZ28)mass model,finite-range droplet model(FRDM,also dubbed FRDM2012),as well as the Weizsacker–Skyrme(WS4)model to refine these mass models.Results:By using the experimental data of 80%of known nuclei as the training dataset,the root mean square devia-tions(RMSDs)between the predicted and the experimental binding energy of the remaining 20%are approximately 0.234±0.022,0.213±0.018,0.170±0.011,and 0.222±0.016 MeV for the LightGBM-refined LDM,DZ model,WS4 model,and FRDM,respectively.These values are approximately 90%,65%,40%,and 60%smaller than those of the corresponding origin mass models.The RMSD for 66 newly measured nuclei that appeared in AME2020 was also significantly improved.The one-neutron and two-neutron separation energies predicted by these refined models are consistent with several theoretical predictions based on various physical models.In addition,the two-neutron separation energies of several newly measured nuclei(e.g.,some isotopes of Ca,Ti,Pm,and Sm)pre-dicted with LightGBM-refined mass models are also in good agreement with the latest experimental data.Conclusions:LightGBM can be used to refine theoretical nuclear mass models and predict the binding energy of unknown nuclei.Moreover,the correlation between the input characteristic quantities and the output can be inter-preted by SHapley additive exPlanations(a popular explainable artificial intelligence tool),which may provide new insights for developing theoretical nuclear mass models.

Complement components of nerve regeneration conditioned fluid influence the microenvironment of nerve regeneration

Nerve regeneration conditioned fluid is secreted by nerve stumps inside a nerve regeneration chamber.A better understanding of the proteinogram of nerve regeneration conditioned fluid can provide evidence for studying the role of the microenvironment in peripheral nerve regeneration.In this study,we used cylindrical silicone tubes as the nerve regeneration chamber model for the repair of injured rat sciatic nerve.Isobaric tags for relative and absolute quantitation proteomics technology and western blot analysis confirmed that there were more than 10 complement components（complement factor I,C1q-A,C1q-B,C2,C3,C4,C5,C7,C8β and complement factor D） in the nerve regeneration conditioned fluid and each varied at different time points.These findings suggest that all these complement components have a functional role in nerve regeneration.

Correction to:Machine learning the nuclear mass

Following publication of the original article,Formula(2)is missing and Fig.11,Fig.9 are identical.The original article has been corrected and the Publisher apologized to the authors and the readers for the inconve-nience caused by this error.

Neutralizing antibodies against SARS-CoV-2 virus after vaccination in patients with neurofibromatosis type 1

Dear Editor,The severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)has triggered a COVID-19 pandemic that has caused high morbidity and mortality worldwide.1 COVID-19 vaccines are urgently needed to protect all susceptible populations from SARS-CoV-2 infection.Neurofibromatosis type 1(NF1)is a hereditary dominant disease that affects approximately one in every 3000 newborns.

Progress of quantum molecular dynamics model and its applications in heavy ion collisions

In this review article,we first briefty introduce the transport theory and quantum molecular dynamics model applied in the study of the heavy ion collisions from low to intermediate energies.The developments of improved quantum molecular dynamics model(ImQMD)and ultra-relativistic quantum molecular dynamics model(UrQMD),are reviewed.The reaction mechanism and phenomena related to the fusion,multinucleon transrer,fragmentation,collective flow and particle production are reviewed and discussed within the framework of the two models.The constraints on the isospin asymmetric muclear equation of state and in-medium nucleon nucleon cross sections by comparing the heavy ion collision data with transport models calculations in last decades are also discussed,and the uncertainties of these constraints are analyzed as well.Finally,we discuss the future direction of the development of the transport models for improving the understanding of the reaction mechanism,the descriptions of various observables,the constraint on the nuclear equation of state,as well as for the constraint on in-medium nucleon-nucleon cross sections.

Application of microscopic transport model in the study of nuclear equation of state from heavy ion collisions at intermediate energies

The equation of state(EOS)of nuclear matter,i.e.,the thermodynamic relationship between the binding energy per nucleon,temperature,density,as well as the isospin asymmetry,has been a hot topic in nuclear physics and astrophysics for a long time.The knowledge of the nuclear EOS is essential for studying the propertics of muclei,the structure of neutron stars,the dynamics of heavy ion collision(HIC),as well as neutron star mergers.HIC offers a unique way to create muclear matter with high density and isospin asymmetry in terrestrial laboratory,but the formed dense nuclear matter exists only for a very short period,one cannot measure the nuclear EOS directly in experiments.Practically,transport models which often incorporate phenomenological potentials as an input are utilized to deduce the EOS from the comparison with the observables mcasured in laboratory.The ultrarelativistic quantum molecular dynamics(UrQMD)model has been widely employed for investigating HIC from the Fermi energy(40 MeV per nucleon)up to the CERN Large Hadron Collider energies(TeV).With further improvement in the nmuclear mean-field potential term,the collision term,and the cluster recognition term of the UrQMD model,the newly measured collective flow and nuclear stopping data of light charged particles by the FOPI Collaboration can be reproduced.In this article we highlight our recent results on the studies of the muclear EOS and the muclear symmetry energy with the UrQMD model.New opportunities and challenges in the extraction of the nuclear EOS from transport models and HIC experiments are discussed.

Improving the efficiency of magnetic coupling energy transfer byetching fractal patterns in the shielding metals

Thin metal sheets are often located in the coupling paths of magnetic coupling energy transfer(MCET) systems. Eddy currents in the metals reduce the energy transfer efficiency and can even present safety risks. This paper describes the use of etched fractal patterns in the metals to suppress the eddy currents and improve the efficiency. Simulation and experimental results show that this approach is very effective. The fractal patterns should satisfy three features, namely, breaking the metal edge, etching in the high-intensity magnetic field region, and etching through the metal in the thickness direction. Different fractal patterns lead to different results. By altering the eddy current distribution, the fractal pattern slots reduce the eddy current losses when the metals show resistance effects and suppress the induced magnetic field in the metals when the metals show inductance effects. Fractal pattern slots in multilayer high conductivity metals(e.g., Cu) reduce the induced magnetic field intensity significantly. Furthermore, transfer power, transfer efficiency, receiving efficiency, and eddy current losses all increase with the increase of the number of etched layers. These results can benefit MCET by efficient energy transfer and safe use in metal shielded equipment.

Drug resistance and pathogenic spectrum of patients coinfected with nontuberculous mycobacteria and human-immunodeficiency virus in Chengdu, China

Background:Human-immunodeficiency virus (HIV) infection is increasing worldwide and nontuberculous mycobacteria (NTM) is an established microbiologic cause of pulmonary disease,lymphadenitis,and disseminated disease in cases of advanced immune suppression.Data on patients coinfected with HIV and NTM are limited.Thus,this study aimed to analyze the clinical characteristics,drug resistance,and pathogen spectrum of patients coinfected with both HIV and NTM in the Chengdu area of China.Methods:Data of 59 patients coinfected with both HIV and NTM collected from the Public Health Clinical Center of Chengdu,between January 2014 and December 2018,were analyzed.NTM drug sensitivity testing was performed using the microporous plate ratio method.Data were analyzed using SPSS 19.0,and the change in drug resistance rate was analyzed using the chi-square (x2) test.Results:Seven species/complex of NTM were identified from patients coinfected with HIV and NTM in this study,with Mycobacterium avium-intracellulare complex (52.5%) and M.kansasii (27.1%) as the predominant species.Male patients were more affected 50/59 (84.7%);the mean age of the 59 cases was 45 years.The clinical characteristics mainly included anemia (86.4%),cough and expectoration (79.7%).The baseline CD4 count was <50 cells/μL (84.7%).Patients were mainly in advanced acquired immunodeficiency syndrome (AIDS) stage.Chest imaging mainly showed patchy shadows (42.4%) and nodules (32.2%),with various degrees of AIDS-defining diseases.The drug resistance of NTM was severe,and the rate of isoniazid resistance (100.0%) was the highest,followed by rifampicin (94.9%),streptomycin (94.9%),ofloxacin (93.2%),and others.Ethambutol (52.5%) and clarithromycin (33.9%) were relatively low.No significant difference was found in the drug resistance rate of NTM strain against nine antituberculosis drugs in 5 years (P > 0.05).Condusions:The immune level of patients coinfected with HIV and NTM is low in advanced AIDS stage;more male are affected in patients who are mainly infected with MAC and M.kansasii and with serious drug resistance,The drug resistance rate of ethambutol and clarithromycin is relatively low.

DG-CNN:Introducing Margin Information into Convolutional Neural Networks for Breast Cancer Diagnosis in Ultrasound Images

Although using convolutional neural networks(CNNs)for computer-aided diagnosis(CAD)has made tremendous progress in the last few years,the small medical datasets remain to be the major bottleneck in this area.To address this problem,researchers start looking for information out of the medical datasets.Previous efforts mainly leverage information from natural images via transfer learning.More recent research work focuses on integrating knowledge from medical practitioners,either letting networks resemble how practitioners are trained,how they view images,or using extra annotations.In this paper,we propose a scheme named Domain Guided-CNN(DG-CNN)to incorporate the margin information,a feature described in the consensus for radiologists to diagnose cancer in breast ultrasound(BUS)images.In DG-CNN,attention maps that highlight margin areas of tumors are first generated,and then incorporated via different approaches into the networks.We have tested the performance of DG-CNN on our own dataset(including 1485 ultrasound images)and on a public dataset.The results show that DG-CNN can be applied to different network structures like VGG and ResNet to improve their performance.For example,experimental results on our dataset show that with a certain integrating mode,the improvement of using DG-CNN over a baseline network structure ResNet 18 is 2.17%in accuracy,1.69%in sensitivity,2.64%in specificity and 2.57%in AUC(Area Under Curve).To the best of our knowledge,this is the first time that the margin information is utilized to improve the performance of deep neural networks in diagnosing breast cancer in BUS images.