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Journal of Iron and Steel Research International 2024年第1期31卷 108-120页

作者： Zi-han Wang jing Guo Han-jie Guo Bin Li School of Metallurgical Engineering University of Science and Technology BeijingBeijing100083China School of Metallurgical Engineering Xi’an University of Architecture and TechnologyXi’an710055ShaanxiChina

A high-temperature reduction roasting method was used to achieve metallic iron and zinc recovery from blast furnace gas ash(BFA).the reduction processes for Zn-containing and Fe-containing oxides were analyzed in detail by using ther-modynamic equilibrium calculation and the principle of minimum free *** results showed that the main reaction in the system is the reduction of ZnFe_(2)_(4)and iron *** the full temperature range,iron oxides were more easily reduced t.an zinc *** of the amount of CO contained in the system,the reduction of ZnO to Zn was difficult to proceed below the boiling point(906℃)of *** the reduction temperature is below 906℃,the reduction process of zinc ferrate was ZnFe_(2)_(4)→ZnO;when the reduction temperature is above 906℃,its reduction process becomed ZnFe_(2)_(4)→ZnO→Zn(g).the metallization and dezincification rates of the BFA gradually increased with increasing reaction *** the C/O ratio increased,the metallization and dezincification rates first increased and then *** effect of reduction time on BFA reduction was similar to that of reaction temperature.

关键词： Blast furnace gas ash thermodynamics Zinc removal Iron reduction High-temperature reduction roasting Integrated utilization

Liquid metal biomaterials: t.anslational medicines,challenges and perspectives

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National Science Review 2024年第2期11卷 264-284页

作者： Hanchi Xu Jincheng Lu Yikuang Xi Xuelin Wang jing Liu Department of Biomedical Engineering School of Medicine Tsinghua University Beijing tsinghua Changgung Hospital School of Clinical Medicine Tsinghua University Shanghai World Foreign Language Academy Beijing Advanced Innovation Center for Biomedical Engineering School of Engineering MedicineBeihang University Beijing Key Lab of Cryo-Biomedical Engineering and Key Lab of Cryogenics Technical Institute of Physics and Chemistry Chinese Academy of Sciences

Until now, significant healthcare challenges and growing urgent clinical requirements remain incompletely addressed by presently available biomedical materials. this is due to their inadequate mechanical compatibility, suboptimal physical and chemical properties, susceptibility to immune rejection, and concerns about long-term biological safety. As an alternative, liquid metal(LM) opens up a promising class of biomaterials with unique advantages like biocompatibility, flexibility, excellent electrical conductivity,and ease of functionalization. However, despite the unique advantages and successful explorations of LM in biomedical fields, widespread clinical t.anslations and applications of LM-based medical products remain limited. this article summarizes the current status and future prospects of LM biomaterials, interprets their applications in healthcare, medical imaging, bone repair, nerve interface, and tumor therapy, *** to t.anslate LM materials into medicine and obstacles encountered in practices are *** that, we outline a blueprint for LM clinics, emphasizing their potential in making new-generation artificial organs. Last, the core challenges of LM biomaterials in clinical t.anslation, including bio-safety,material stability, and ethical concerns are also discussed. Overall, the current progress, t.anslational medicine bottlenecks, and perspectives of LM biomaterials signify their immense potential to drive future medical breakthroughs and thus open up novel avenues for upcoming clinical practices.

关键词： liquid metal biomaterials t.anslational medicine clinical device healthcare therapeutics

In-depth understanding of t.ansport behavior of sulfided nano zerovalent iron/reduced graphene oxide@guar gum slurry: Stability and mobility

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Journal of Environmental Sciences 2024年第10期144卷 1-14页

作者： Yuheng Ma Wenhui You Zijiang Yang Zhongyu Ren Qi jing Faculty of Architecture Civil and Transportation EngineeringBeijing University of TechnologyBeijing 100124China

Nanoscale zero-valent iron(NZVI),which has the advantages of small particle size,large specific surface area,and high reactivity,is often injected into contaminated aquifers in the form of ***,the prone to passivation and agglomeration as well as poor stability andmobility of NZVI limit the further application of this technology in ***,sulfided NZVI loaded on reduced graphene oxide(S-NZVI/rGO)and guar gum(GG)with shearthinning properties as stabilizers were used to synthesize S-NZVI/rGO@GG ***,tEM,and Ft-IR confirmed that the dispersion and anti-passivation of NZVI were optimized in the coupled *** stability and mobility of the slurry were improved by increasing the GG concentration,enhancing the pH,and decreasing the ionic strength and the presence of Ca^(2+)ions,respectively.A modified advection-dispersion equation(ADE)was used to simulate the t.ansport experiments considering the strain and physicochemical deposition/***,colloidal filtration theory(CFt)demonstrated that Brownian motion plays a dominant role in themigration of S-NZVI/rGO@GG slurry,and the maximummigration distance can be increased by appropriately increasing the injection ***-Derjaguin-Landau-Verwey-Overbeek(XDLVO)theory showed that the excellent stability and migration of S-NZVI/rGO@GG slurry mainly came from the GG spatial *** study has important implications for the field injection of S-NZVI/rGO@GG *** to the injection parameters,the injection range of S-NZVI/rGO@GG slurry is effectively controlled,which lays the foundation for the promotion of application in actual fields.

关键词： S-NZVI rGO Guar gum t.ansport Stability

An Initial Perturbation Method for the Multiscale Singular Vector in Global Ensemble Prediction

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Advances in Atmospheric Sciences 2024年第3期41卷 545-563页

作者： Xin LIU jing CHEN Yongzhu LIU Zhenhua HUO Zhizhen XU Fajing CHEN jing WANG Yanan MA Yumeng HAN School of Atmospheric Sciences Nanjing University of Information Science&TechnologyNanjing 210044China Chinese Academy of Meteorological Sciences Beijing 100081China CMA Earth System Modeling and Prediction Centre(CEMC) Beijing 100081China Key Laboratory of Earth System Modeling and Prediction of China Meteorological Administration Beijing 100081China t.anjin Meteorological Observatory Tianjin 300074China China Meteorological Administration Xiong’an Atmospheric Boundary Layer Key Laboratory Hebei 071799China

Ensemble prediction is widely used to represent the uncertainty of single deterministic Numerical Weather Prediction(NWP) caused by errors in initial conditions(ICs). the traditional Singular Vector(SV) initial perturbation method tends only to capture synoptic scale initial uncertainty rather t.an mesoscale uncertainty in global ensemble prediction. to address this issue, a multiscale SV initial perturbation method based on the China Meteorological Administration Global Ensemble Prediction System(CMA-GEPS) is proposed to quantify multiscale initial uncertainty. the multiscale SV initial perturbation approach entails calculating multiscale SVs at different resolutions with multiple linearized physical processes to capture fast-growing perturbations from mesoscale to synoptic scale in target areas and combining these SVs by using a Gaussian sampling method with amplitude coefficients to generate initial perturbations. Following that, the energy norm,energy spectrum, and structure of multiscale SVs and their impact on GEPS are analyzed based on a batch experiment in different seasons. the results show that the multiscale SV initial perturbations can possess more energy and capture more mesoscale uncertainties t.an the traditional single-SV method. Meanwhile, multiscale SV initial perturbations can reflect the strongest dynamical instability in target areas. their performances in global ensemble prediction when compared to single-scale SVs are shown to(i) improve the relationship between the ensemble spread and the root-mean-square error and(ii) provide a better probability forecast skill for atmospheric circulation during the late forecast period and for short-to medium-range precipitation. this study provides scientific evidence and application foundations for the design and development of a multiscale SV initial perturbation method for the GEPS.

关键词： multiscale uncertainty singular vector initial perturbation global ensemble prediction system

A deep learning model based on contrast-enhanced computed tomography for differential diagnosis of gallbladder carcinoma

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Hepatobiliary & Pancreatic Diseases International 2024年第4期23卷 376-384页

作者： Fei Xiang Qing-tao Meng jing-jing Deng Jie Wang Xiao-Yuan Liang Xing-Yu Liu Sheng Yan Department of Hepatobiliary Pancreatic Surgery Second Affiliated HospitalZhejiang University School of MedicineHangzhou 310003China Department of Radiology Affiliated Chuzhou First People’s HospitalAnhui Medical UniversityChuzhou 239000China

Background:Gallbladder carcinoma(GBC)is highly malignant.and its early diagnosis remains *** study aimed to develop a deep learning model based on contrast-enhanced computed tomography(Ct)images to assist radiologists in identifying ***:We retrospectively enrolled 278 patients with gallbladder lesions(>10 mm)who underwent contrast-enhanced Ct.and cholecystectomy and divided them into the training(n=194)and validation(n=84)*** deep learning model was developed based on ResNet50 *** and clinical models were built based on support vector machine(SVM)*** comprehensively compared the performance of deep learning,radiomics,clinical models,and three ***:three radiomics features including LoG_3.0 gray-level size zone matrix zone variance,HHL firstorder kurtosis,and LHL gray-level co-occurrence matrix dependence variance were significantly different between benign gallbladder lesions and GBC,and were selected for developing radiomics *** regression analysis revealed that age≥65 years[odds ratios(OR)=4.4,95%confidence interval(CI):2.1-9.1,P37 U/mL(OR=4.0,95%CI:1.6-10.0,P=0.003)were significant clinical risk factors of *** deep learning model achieved the area under the receiver operating characteristic curve(AUC)values of 0.864(95%CI:0.814-0.915)and 0.857(95%CI:0.773-0.942)in the training and validation datasets,which were comparable with radiomics,clinical models and three *** sensitivity of deep learning model was the highest both in the training[90%(95%CI:82%-96%)]and validation[85%(95%CI:68%-95%)]***:the deep learning model may be a useful tool for radiologists to distinguish between GBC and benign gallbladder lesions.

关键词： Gallbladder carcinoma Computed tomography Deep learning Radiomics

An active learning workflow for predicting hydrogen atom adsorption energies on binary oxides based on local electronic t.ansfer features

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Green Energy & Environment 2024年第10期9卷 1489-1496页

作者： Wenhao jing Zihao Jiao Mengmeng Song Ya Liu Liejin Guo International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow in Power Engineering Xi'an Jiaotong University Department of Energy and Power Engineering Shandong University of Technology

Machine learning combined with density functional theory（DFt） enables rapid exploration of catalyst descriptors space such as adsorption energy, facilitating rapid and effective catalyst screening. However, there is still a lack of models for predicting adsorption energies on oxides,due to the complexity of elemental species and the ambiguous coordination environment. this work proposes an active learning workflow（Le NN） founded on local electronic t.ansfer features（e） and the principle of coordinate rotation invariance. By accurately characterizing the electron t.ansfer to adsorption site atoms and their surrounding geometric structures, Le NN mitigates abrupt feature changes due to different element types and clarifies coordination environments. As a result, it enables the prediction of *H adsorption energy on binary oxide surfaces with a mean absolute error（MAE） below 0.18 e V. Moreover, we incorporate local coverage（θl） and leverage neutral network ensemble to establish an active learning workflow, attaining a prediction MAE below 0.2 e V for 5419 multi-*H adsorption structures. these findings validate the universality and capability of the proposed features in predicting *H adsorption energy on binary oxide surfaces.

关键词： Machine learning Adsorption energy Binary oxide Electron t.ansfer Active learning

Resource utilization of drinking water treatment aluminum sludge in green cementing materials: Hydration characteristics and hydration kinetics

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Journal of Environmental Sciences 2024年第10期144卷 236-248页

作者： jing Yang Cheng Chen Shuoyu Chen Yujie Ren Jinsuo Lu School of Environmental and Municipal Engineering Xi’an University of Architecture and TechnologyXi’an 710055China

As a byproduct of water treatment,drinking water treatment aluminum sludge(DWtAS)has challenges related to imperfect treatment.and disposal,which has caused potential harm to human health and the *** this paper,heat treatment DWtAS as a supplement cementitious material was used to prepare a green cementing *** results show that the 800℃ is considered as the optimum heat treatment temperature for ***-800℃ is fully activated after thermal decomposition to form incompletely crystallized highly activeγ-Al2O3 and active SiO_(2).the addition of DWtAS promoted the formation of ettringite and C-(A)-S-H gel,which could make up for the low early compressive strength of cementing materials to a certain *** cured for 90 days,the compressive strength of the mortar with 30% DWtAS-800℃ reached 44.86 *** dynamic process was well simulated by Krstulovi′c-Dabi′c hydration kinetics *** study provided a methodology for the fabrication of environmentally friendly and cost-effective compound cementitiousmaterials and proposed a“waste-to-resource”strategy for the sustainable management of typical solid wastes.

关键词： Drinking water treatment aluminum sludge Green cementing material Hydration characteristics Hydration kinetics

Analysis of rail-bridge interaction of a high-speed railway suspension bridge under near-fault pulse-type earthquakes

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t.ansportation Safety and Environment 2024年第3期6卷 71-84页

作者： Xiangdong Yu Bangzheng Jiang Haiquan jing School of Civil Engineering Central South UniversityChangsha 410075HunanChina

Due to the limitations of railway route selection,some high-speed railways are inevitably built near or across fault *** study the distribution of rail-bridge interaction under different load history states of suspension bridges under three types of near-fault pulse-type earthquakes,this paper takes China’s longest high-speed railway suspension bridge—Wufengshan Yangtze River Bridge-as the background and establishes a spatial model of the rail-bridge interaction of a suspension *** results show that:under the constant load state,the distribution of additional force under three types of pulse-type earthquakes is generally consistent.and pulse-type earthquakes produce more significant responses t.an non-pulse-type earthquakes;with fling-step pulse being the largest,it is advised to specifically consider the influence of the fling-step pulse in the *** the initial condition of the main beam temperature loading history,all rail-bridge additional forces increase significantly,particularly affecting the steel rail *** value of the rail-bridge interaction additional force under the near-fault earthquake in the initial state of the suspension bridge when the train deflection load is loaded from the tower to the mid-span is more significant.and particularly *** initial effect of the braking load will weaken the effect of the deflection load loading *** results of the study indicate that the effect of the initial state of suspension bridges is an important factor influencing the rail-bridge interaction under near-fault pulse-type earthquakes,which needs to be considered in future seismic design.

关键词： rail-bridge interaction high-speed railway suspension bridge near-fault pulse-type earthquakes loading history initial state

GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

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Computers, Materials & Continua 2024年第7期80卷 487-506页

作者： Haiyue Li jing Xie jing Ke Ye Yuan Xiaoyong Pan Hongyi Xin Hongbin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai200240China Department of Pathology Ruijin HospitalShanghai Jiao Tong UniversitySchool of MedicineShanghai200025China Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Global Institute of Future technology Shanghai Jiao Tong UniversityShanghai200240China

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of *** neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image ***,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s *** argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator *** this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image *** begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific ***,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise ***,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and technology database(MNISt),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s *** results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

关键词： Histological images registration deformable registration generative adversarial network cushing’s disease machine learning computer vision

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

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Energy Engineering 2024年第2期121卷 523-540页

作者： Lifeng Wang jing Yu Wenlu Ji Nanjing Power Supply Company Nanjing210019China State Grid Jiangsu Electric Power Co. Ltd.Nanjing211103China

Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid *** this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the ***,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side ***,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective ***,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.

关键词： Demand response fixed time-of-use electricity price mechanism dynamic price incentives mechanism bi-level model flexible load