Magnetic and magnetocaloric effect of Er_(20)Ho_(20)Dy_(20)Cu_(20)Ni_(20)high-entropy metallic glass

Er_(20)Ho_(20)Dy_(20)Cu_(20)Ni_(20)high-entropy metallic glass exhibited excellent magnetic refrigeration material with a wide temperature range and high refrigeration capacity(RC)was reported.Er_(20)Ho_(20)Dy_(20)Cu_(20)Ni_(20)high-entropy metallic glass was observed with typical spin glass behavior around 15.5 K.In addition,we find that the magnetic entropy change(-△S_(M))originates from the sample undergoing a ferromagnetic(FM)to paramagnetic(PM)transition around 20 K.Under a field change from 0 T to 7 T,the value of maximum magnetic entropy change(-△S_(M)^(max))reaches 12.5 J/kg·K,and the corresponding value of RC reaches 487.7 J/kg in the temperature range from 6 K to 60 K.The large RC and wide temperature range make the Er_(20)Ho_(20)Dy_(20)Cu_(20)Ni_(20)high-entropy metallic glass be a promising material for application in magnetic refrigerators.

Application of fecal immunochemical test in colorectal cancer screening:A community-based,cross-sectional study in averagerisk individuals in Hainan

BACKGROUND The incidence of colorectal cancer(CRC)in China is steadily rising,with a high proportion of advanced-stage diagnoses.This highlights the significance of early detection and prevention measures to enhance survival rates.Fecal immunochemical testing(FIT)is a globally recommended CRC screening method;however,limited research has been conducted on its application in Hainan.AIM To assess the efficacy and adherence of FIT screening among average-risk individuals in Hainan,while also examining the risk factors associated with positive FIT results.METHODS This population-based cross-sectional study implemented FIT screening for CRC in 2000 asymptomatic participants aged 40-75 years from five cities and 21 community health centers in Hainan Province.The study was conducted from August 2022 to April 2023,employing a stratified sampling method to select participants.Individuals with positive FIT results subsequently underwent colonoscopy.Positive predictive values for confirmed CRC and advanced adenoma were calculated,and the relationship between relevant variables and positive FIT results was analyzed usingχ2 tests and multivariate logistic regression.RESULTS A total of 1788 participants completed the FIT screening,with a median age of 57 years(interquartile range:40-75).Among them,503(28.1%)were males,and 1285(71.9%)were females,resulting in an 89.4%compliance rate for FIT screening.The overall positivity rate of FIT was 4.4%[79 out of 1788;95%confidence interval(CI):3%-5%].The specific positivity rates for Haikou,Sanya,Orient City,Qionghai City,and Wuzhishan City were 9.6%(45 of 468;95%CI:8%-11%),1.3%(6 of 445;95%CI:0.1%-3.1%),2.7%(8 of 293;95%CI:1.2%-4.3%),3.3%(9 of 276;95%CI:1.0%-6.3%),and 4.2%(11 of 406;95%CI:1.2%-7.3%),respectively.Significant associations were found between age,dietary habits,and positive FIT results.Out of the 79 participants with positive FIT results,55 underwent colonoscopy,demonstrating an 82.2%compliance rate.Among them,10 had a clean gastrointestinal tract,43 had polyps or adenomas,and 2 were confirmed to have CRC,yielding a positive predictive value of 3.6%(95%CI:0.9%-4.2%).Among the 43 participants with polyps or adenomas,8 were diagnosed with advanced adenomas,resulting in an advanced adenoma rate of 14.5%(95%CI:10.1%-17.7%).CONCLUSION In the Hainan region,FIT screening for CRC among asymptomatic individuals at average risk is feasible and wellreceived.

Research on the Viscoelasticity of Polyester Mooring Lines Using the Absolute Nodal Coordinate Formulation

The taut mooring system using synthetic fiber ropes has overcome the shortcomings such as the large self-weight of the mooring lines and provides better mooring performance for the floating structures.The polyester rope has attracted much attention among numerous synthetic fiber rope materials due to its lightweight,low price,corrosion resistance,and high strength.Thus,the mooring characteristics of it are worth studying.Polyester mooring lines are flexible in deep water,when a marine structure is moored by them,the geometric nonlinearity such as large displacement,large stretch,and large bending deformation,and the material nonlinearity like viscoelastic of the polyester ropes become complex integrated problems to be studied.Considering the nonlinear phenomenon,the simulation and calculation of a polyester line were carried out by the absolute nodal coordinate formulation(ANCF)in this paper since the ANCF method has advantages in dealing with the significant deformation problems of the flexible structures.In addition,a chain mooring line was also simulated for comparison,and the results show that the polyester ropes reduce the self-weight of the mooring lines and provide sufficient mooring strength at the same time,and the nonlinear phenomenon of the polyester ropes is different from that of the chain mooring lines.

Quasi-static magnetic compression of field-reversed configuration plasma:amended scalings and limits from two-dimensional MHD equilibrium

In this work,several key scaling laws of the quasi-static magnetic compression of field reversed configuration(FRC)plasma(Spencer et al 1983 Phys.Fluids 261564)are amended from a series of two-dimensional FRC MHD equilibriums numerically obtained using the Grad–Shafranov equation solver NIMEQ.Based on the new scaling for the elongation and the magnetic fields at the separatrix and the wall,the empirically stable limits for the compression ratio,the fusion gain,and the neutron yield are evaluated,which may serve as a more accurate estimate for the upper ceiling of performance from the magnetic compression of FRC plasma as a potential fusion energy as well as neutron source devices.

An application of the shortest path algorithm for the identification of weak MHD mode

The identification of magnetohydrodynamic(MHD)modes is a crucial issue in the control of magnetically confined plasmas.This paper proposes a novel method for identifying the evolution of MHD modes from a signal with a low signal-to-noise ratio.The proposed method generates a weighted directed graph from the time-frequency spectrum and calculates the evolution of the mode frequency by solving the shortest path.This method addresses the limitations posed by the lack of data channels and the disturbance of noise in the estimation of mode frequency and yields much better results compared to traditional methods.It is demonstrated that,using this method,the evolution of an unlocked tearing mode was more accurately calculated on the J-TEXT tokamak.This method remains feasible even with a low signal-to-noise ratio of 0.5,as shown by its uncertainty.Furthermore,with appropriate parameters,this method can be applied to not only signals with MHD modes,but also to general signals with continuous modes.

Selective conversion of CO_(2)to CO using earth abundant tin modified copper gas diffusion electrodes

Earth-abundant copper-tin(CuSn)electrocatalysts are potential candidates for cost-effective and sustainable production of CO from electrochemical carbon dioxide reduction(eCO_(2)R).However,the requirement of highoverpotential for obtaining reasonable current,low Faradaic efficiencies(FE)and low intrinsic catalytic activities require the optimisation of the CuSn nanoarchitecture for the further advancement in the field.In the current work,we have optimised Sn loading on Cu gas diffusion electrodes(GDEs)by electrochemical spontaneous precipitation.Samples with various Sn loadings were tested in a three-chamber GDE reactor to evaluate their CO_(2)reduction performances.The best performance of 92%CO Faradaic efficiency at a cathodic current density of 120 mA cm^(-2)was obtained from the 20 min Sn deposited Cu_(2)O sample operated at-1.13 V vs.RHE.The electrocatalyst had~13%surface coverage of Sn on Cu GDE surface,and had Sn in oxide form and copper in metallic form.The catalyst also showed stable performance and was operable for>3 h under chronoamperometric conditions.The surface of the GDE reduces from Cu2O to Cu during eCO_(2)R and goes further reconstruction during the eCO_(2)R.This study demonstrates the potential of Cu-Sn for selective CO production at high current densities.

One-step cell biomanufacturing platform:porous gelatin microcarrier beads promote human embryonic stem cell-derived midbrain dopaminergic progenitor cell differentiation in vitro and survival after transplantation in vivo

Numerous studies have shown that cell replacement therapy can replenish lost cells and rebuild neural circuitry in animal models of Parkinson’s disease.Transplantation of midbrain dopaminergic progenitor cells is a promising treatment for Parkinson’s disease.However,transplanted cells can be injured by mechanical damage during handling and by changes in the transplantation niche.Here,we developed a one-step biomanufacturing platform that uses small-aperture gelatin microcarriers to produce beads carrying midbrain dopaminergic progenitor cells.These beads allow midbrain dopaminergic progenitor cell differentiation and cryopreservation without digestion,effectively maintaining axonal integrity in vitro.Importantly,midbrain dopaminergic progenitor cell bead grafts showed increased survival and only mild immunoreactivity in vivo compared with suspended midbrain dopaminergic progenitor cell grafts.Overall,our findings show that these midbrain dopaminergic progenitor cell beads enhance the effectiveness of neuronal cell transplantation.

Scientific Advances and Weather Services of the China Meteorological Administration’s National Forecasting Systems during the Beijing 2022 Winter Olympics

Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.

Analysis of the Influence of Geometrical Parameters on the Performance of a Proton Exchange Membrane Fuel Cell

A suitable channel structure can lead to efficient gas distribution and significantly improve the power density of fuel cells.In this study,the influence of two channel design parameters is investigated,namely,the ratio of the channel width to the bipolar plate ridge width(i.e.,the channel ridge ratio)and the channel depth.The impact of these parameters is evaluated with respect to the flow pattern,the gas composition distribution,the temperature field and the fuel cell output capability.The results show that a decrease in the channel ridge ratio and an increase in the channel depth can effectively make the distributions of velocity,temperature and concentration more uniform in each channel and improve the output capability of the fuel cell.An increase in the channel ridge ratio and depth obviously reduces the flow resistance and improves the flow characteristics.

数字孪生灌区建设中空间信息数据运用安全的保障措施与实施路径

随着数字孪生流域、数字孪生水利工程、数字孪生水网等智慧水利技术不断应用和发展,空间地理信息数据及服务的运用的重要性逐渐凸显。文章从数字孪生灌区建设中关于空间地理信息数据的运用进行了安全分析,从建设必要性、建设原则、建设依据、实施方案及实施路径出发,探讨数据运用安全融入数字孪生灌区建设及运行中的设计思路,从而保障数据静态安全及动态安全,使其符合国家相关法律法规要求。

Influence of Diesel Engine Intake Throttle and Late Post Injection Process on the Rise of Temperature in the Diesel Oxidation Catalyst

In order to effectively implement DPF(Diesel Particulate Filters)regeneration control,thermal management of exhaust products before and inside Diesel Oxidation Catalyst(DOC)is necessary.In the present study,the Influence of the intake throttle valve and late post injection process on temperature rise inside DOC is analyzed through engine bench tests.The steady experiment results show that adjustment of the intake throttle valve can effectively increase exhaust temperature before DOC;in particular,with intake throttle valve opening at 20%,temperature before DOC can be increased by about 170℃ with respect to the full opening.An increase in the late post injection quantity can produce a significant rise of the temperature inside DOC,however its impact on the exhaust temperature before DOC is relatively limited.As the late post injection quantity increases,Hydrocarbon(HC)emissions also grow;in the present work it is shown that with a proper injection quantity,a considerable temperature increase inside the DOC can be obtained with relatively low HC emission.More specifically,with the intake throttle valve at 30%and DOC reaching ignition temperature as the late post injection quantity is increased,the exhaust temperature after DOC can be made larger than 550℃,adequate for DPF active regeneration.

Analysis of Bubble Behavior in a Horizontal Rectangular Channel under Subcooled Flow Boiling Conditions

Experiments on subcooled flow boiling have been conducted using water in a rectangular flow channel.Similar to the coolant channel in internal combustion engines(IC engines),the flow channel in this experiment was asymmetrically heated.Bubble images were captured using a high speed camera from the side view of the channel.The experimental conditions in terms of bulk temperature,bulk velocity,pressure and heat flux ranged from 65°C–75°C,0.25 m/s–0.75 m/s,1–1.7 bar and 490 kW/m2–700 kW/m2,respectively.On the basis of these tests,a statistical analysis of the bubble size has been conducted considering a population of 1400 samples.It has been found that the mean Sauter bubble diameter increases with the decrease of subcooling,bulk velocity,pressure and increased heat flux.A modified correlation has been finally proposed to predict the mean Sauter bubble diameter under subcooled flow boiling conditions upstream of the onset of significant void,which shows good accuracy with the experimental results.

Substance abuse rehabilitation needs to be guided by well-developed practice model(s)

Although occupational therapy for substance abuse,as a field in psychiatric rehabilitation,has been implemented for over half a century,it still seems underdeveloped.This area of rehabilitation aims to enhance the quality of life of substance abuse rehabilitants and prevent them from relapse.1 It can be achieved by enabling them to identify their meaningful occupations and occupational roles,and supporting them to re-engage in the occupations that they value,which would help empower them to overcome abuse.12 The interventions around the world include brief intervention,motivational strategy,cognitive behavioural therapy.

Systematic evaluation and trial sequential analysis of warming acupuncture combined with joint mobilization in the treatment of scapulohumeral periarthritis

Objective:To evaluate the clinical efficacy of warming acupuncture combined with joint mobilization for the treatment of scapulohumeral periarthritis.Methods:A search for published randomized controlled trials(RCT)investigating warming acupuncture combined with joint mobilization for the treatment of scapulohumeral periarthritis was performed using the Cochrane Library,PubMed,Embase,and Web of Science databases.According to requirements of the Cochrane systematic review,all evaluations of RCT investigating warming acupuncture with joint mobilization in the treatment of scapulohumeral periarthritis were performed via method quality assessment,data extraction,and data analysis.Revman 5.3 and Stata 12.0 statistical software were used for the meta-analysis,and the trial sequential analysis(TSA)software estimated the required information size for each outcome.Results:A total of 14 articles were retrieved for meta-analysis,which included 551 cases in the treatment group and 539 cases in the control group.Meta-analysis showed that:(1)warming acupuncture combined with joint mobilization improved total efficiency[OR=6.16,95%CI(3.79,10.00),Z=7.34;P<0.001),TSA results confirmed the results of the meta-analysis;(2)warming acupuncture combined with joint mobilization improved the cure rate[OR=2.84,95%CI(2.19,3.70),P<0.001],TSA results revealed that no further tests were needed to verify;(3)warming acupuncture combined with joint mobilization reduced the number of treatments required for healing[MD=-7.49,95%CI(-9.75,-5.23),P<0.001],TSA results confirmed the results of the meta-analysis;(4)in comparing visual analog scale scores before and after treatment,meta-analysis result showed that:SMD=-2.01,95%CI(-2.37,-1.65),P<0.001,the difference was statistically significant,TSA results confirmed the results of the meta-analysis.Conclusion:Warming acupuncture combined with joint mobilization had a significant effect on the treatment of scapulohumeral periarthritis.

Machine learning application to predict the electron temperature on the J-TEXT tokamak

The reliability of diagnostic systems in tokamak plasma is of great significance for physics researches or fusion reactor.When some diagnostics fail to detect information about the plasma status,such as electron temperature,they can also be obtained by another method:fitted by other diagnostic signals through machine learning.The paper herein is based on a machine learning method to predict electron temperature,in case the diagnostic systems fail to detect plasma temperature.The fully-connected neural network,utilizing back propagation with two hidden layers,is utilized to estimate plasma electron temperature approximately on the J-TEXT.The input parameters consist of soft x-ray emission intensity,electron density,plasma current,loop voltage,and toroidal magnetic field,while the targets are signals of electron temperature from electron cyclotron emission and x-ray imaging crystal spectrometer.Therefore,the temperature profile is reconstructed by other diagnostic signals,and the average errors are within 5%.In addition,generalized regression neural network can also achieve this function to estimate the temperature profile with similar accuracy.Predicting electron temperature by neural network reveals that machine learning can be used as backup means for plasma information so as to enhance the reliability of diagnostics.

Magnetic diagnostics for magnetohydrodynamic instability research and the detection of locked modes in J-TEXT

Magnetohydrodynamic(MHD)instabilities are widely observed during tokamak plasma operation.Magnetic diagnostics provide important information which supports the understanding and control of MHD instabilities.This paper presents the current status of the magnetic diagnostics dedicated to measuring MHD instabilities at the J-TEXT tokamak;the diagnostics consist of five Mirnov probe arrays for measuring high-frequency magnetic perturbations and two saddle-loop arrays for low-frequency magnetic perturbations,such as the locked mode.In recent years,several changes have been made to these arrays.The structure of the probes in the poloidal Mirnov arrays has been optimized to improve their mechanical strength,and the number of in-vessel saddle loops has also been improved to support better spatial resolution.Due to the installation of high-field-side(HFS)divertor targets in early 2019,some of the probes were removed,but an HFS Mirnov array was designed and installed behind the targets.Owing to its excellent toroidal symmetry,the HFS Mirnov array has,for the first time at J-TEXT,provided valuable new information about the locked mode and the quasi-static mode(QSM)in the HFS.Besides,various groups of magnetic diagnostics at different poloidal locations have been systematically used to measure the QSM,which confirmed the poloidal mode number m and the helical structure of the QSM.By including the HFS information,the 2/1 resonant magnetic perturbation(RMP)-induced locked mode was measured to have a poloidal mode number m of~2.

Effect of resonant magnetic perturbation on boundary plasma turbulence and transport on J-TEXT tokamak

The effect of resonant magnetic perturbation(RMP) on boundary turbulence and transport in J-TEXT plasma is experimentally investigated.Edge plasma fluctuations in discharges with and without the(m/n=3/1) RMP currents are diagnosed by using Langmuir probe arrays.It was found that fluctuations in the edge and scrape-off layer(SOL) regions decrease with the application of a 6 kA RMP.The broadband turbulence at the radial location of ρ~0.9 which has a characteristic frequency of 40-150 kHz was strongly suppressed when applying RMP,as was the radial turbulent particle flux and blob transport in the near-SOL region.These experimental findings make RMP a promising method of suppressing and controlling turbulence and particle transport in a plasma boundary.

Effect of inhibiting miR-155 expression on proliferation and migration of airway smooth muscle cell in patients with COPD

Objective:To investigate the effect of inhibiting miR-155 expression on the proliferation and migration of airway smooth muscle cells(ASMCs)in patients with chronic obstructive pulmonary disease(COPD).Methods:ASMCs were isolated and cultured from 8 patients with COPD(observation group)and 3 patients with benign lung cancer without COPD(control group).The ASMCs were transfected with miR-155 suppression expression plasmid(to detect the expression of miR-155;flow cytometry was used to detect the cell cycler of cell clones;Transwell was used to detect cell migration and invasion;Enzyme-linked immunosorbent aanti-miR-155)and the negative contre;clone formation experiment was used to detect the numbol plasmid(anti-miR-NC),and blank control group was set.Real-time quantitative PCR(RT-qPCR)was usedssay(ELISA)method was used to detect tumor necrosis factor-α(TNF-α),interleukin-6(IL-6)level.Results:The expression level of miR-155 in ASMCs of observation group was significantly higher than that in the control group(P<0.05).The miR-155 expression level in inhibited miR-155 expression group was significantly lower,compared with the negative control group and the blank group(P<0.05).In the inhibited miR-155 expression group,the proportion of G0-G1 phase cells was increased,the proportion of S phase cells was decreased,the number of cell clones,migration,and the number of invasive cells were decreased,and the levels of TNF-αand IL-6 were increased(P<0.05).Conclusions:Inhibiting the expression of miR-155 can inhibit the proliferation and migration of airway smooth muscle cells in COPD patients,and inhibit the release of proinflammatory factors.

基于机器学习的面心立方高熵合金弹性性能预测

提出预测面心立方高熵合金弹性性能的机器学习模型。数据集来源于第一性原理计算得到的186组样本。测试集体积模量(B)和剪切模量(G)预测值的拟合优度(R2)分别达到0.81和0.84。根据机器学习结果,Co Ni CuMoW在等主元高熵合金(G/B≤0.57)中具有最高的B、G和弹性模量(Y)和良好的塑性。第一性原理计算结果表明,当W含量增加时,(CoNiCuMo)1-xWx合金的弹性各向异性提高,且塑性下降。差分电荷密度分析结果表明,W—W和W—Mo键存在明显的电荷聚集,表明W原子与邻近原子间存在共价键作用。

Investigation of the J-TEXT plasma events by k-means clustering algorithm

Various types of plasma events emerge in specific parameter ranges and exhibit similar characteristics in diagnostic signals,which can be applied to identify these events.A semisupervised machine learning algorithm,the k-means clustering algorithm,is utilized to investigate and identify plasma events in the J-TEXT plasma.This method can cluster diverse plasma events with homogeneous features,and then these events can be identified if given few manually labeled examples based on physical understanding.A survey of clustered events reveals that the k-means algorithm can make plasma events(rotating tearing mode,sawtooth oscillations,and locked mode)gathering in Euclidean space composed of multi-dimensional diagnostic data,like soft x-ray emission intensity,edge toroidal rotation velocity,the Mirnov signal amplitude and so on.Based on the cluster analysis results,an approximate analytical model is proposed to rapidly identify plasma events in the J-TEXT plasma.The cluster analysis method is conducive to data markers of massive diagnostic data.