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Solidification crack characteristics and sensitivity of peritectic steel

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Journal of Iron and Steel Research International 2024年第7期31卷 1668-1679页

作者： Ya-qiang li Jian-hua liu zi-ming Wang Ying-ying li Yang He Xiao-wei li Department of Automotive Engineering Hebei Vocational University of Technology and EngineeringXingtai 054000HebeiChina Hebei Special Vehicle Modification Technology Innovation Center Hebei Vocational University of Technology and EngineeringXingtai 054000HebeiChina Institute of Engineering Technology University of Science and Technology BeijingBeijing 100083China School of Petroleum and Natural Gas Engineering Changzhou UniversityChangzhou 213164JiangsuChina

The characteristics and sensitivity of solidification cracks in peritectic steels were investigated using directional solidifi-cation *** cracks were observed in both hypoperitectic steels(12CrlMoV,15CrMo)and hyper-peritectic steel(20CrMo)during solidification at growth velocities of 15,50,and 80 pm/*** the dendritic boundaries,sulphide precipitates were found,promoting crack *** on the statistical analysis of interdendritic cracks in peritectic steels,the area ratio(RA)of interdendritic cracks in a directional solidification structure was proposed to evaluate the crack sensitivity of peritectic ***,the crack sensitivities of peritectic steels(12CrlMoV,15CrMo,and 20CrMo)were tested,evaluated,and compared with the surface crack rates of three types of steels produced from a steel *** results demonstrated that RA was in good agreement with that of the steel plant,and the crack sensitivity of 12CrlMoV steel was the strongest,followed by that of 15CrMo and 20CrMo ***,RA can be used to evaluate the crack sensitivity of peritectic steel.

关键词： Peritectic steel-Directional solidification Growth velocity Dendritic structure Solidification crack Crack sensitivity

A novel fracture-cavity reservoir outcrop geological knowledge base construction method considering parameter collection and processing, mutual transformation of data-knowledge, application and update

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Petroleum Science 2024年第4期21卷 2184-2202页

作者： Qi-Qiang Ren Jin-liang gao Peng Zhu Meng-ping li Jian-Wei Feng Qiang Jin San Zhang Institute of Sedimentary Geology Chengdu University of Technology PetroChina Research Institute of Petroleum Exploration and Development School of Energy Chengdu University of Technology School of Resources and Geosciences China University of Mining and Technology School of Geosciences China University of Petroleum (East China) School of Geosciences Yangtze University

This study endeavors to formulate a comprehensive methodology for establishing a Geological Knowledge Base(GKB) tailored to fracture-cavity reservoir outcrops within the North Tarim Basin. The acquisition of quantitative geological parameters was accomplished through diverse means such as outcrop observations, thin section studies, unmanned aerial vehicle scanning, and high-resolution cameras. Subsequently, a three-dimensional digital outcrop model was generated, and the parameters were standardized. An assessment of traditional geological knowledge was conducted to delineate the knowledge framework, content, and system of the GKB. The basic parameter knowledge was extracted using multiscale fine characterization techniques, including core statistics, field observations, and microscopic thin section analysis. key mechanism knowledge was identified by integrating trace elements from filling, isotope geochemical tests, and water-rock simulation experiments. Significant representational knowledge was then extracted by employing various methods such as multiple linear regression, neural network technology, and discriminant classification. Subsequently, an analogy study was performed on the karst fracture-cavity system(KFCS) in both outcrop and underground reservoir settings. The results underscored several key findings:(1) Utilization of a diverse range of techniques,including outcrop observations, core statistics, unmanned aerial vehicle scanning, high-resolution cameras, thin section analysis, and electron scanning imaging, enabled the acquisition and standardization of data. This facilitated effective management and integration of geological parameter data from multiple sources and scales.(2) The GKB for fracture-cavity reservoir outcrops, encompassing basic parameter knowledge, key mechanism knowledge, and significant representational knowledge, provides robust data support and systematic geological insights for the intricate and in-depth examination of the genetic

关键词： Geological knowledge base Karst fracture-cavity system Mutual transformation of data-knowledge Knowledge base content and application Tarim basin

Triceps skinfold thickness trajectories and the risk of all-cause mortality:A prospective cohort study

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World Journal of Clinical Cases 2024年第15期12卷 2568-2577页

作者： Na Yang li-Yun He zi-Yi li Yu-Cheng Yang Fan ping ling-ling Xu Wei li Hua-Bing Zhang Yu-Xiu li Department of Endocrinology Key Laboratory of Endocrinology of National Health CommissionPeking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China

BACKGROUND The measurement of triceps skinfold(TSF)thickness serves as a noninvasive metric for evaluating subcutaneous fat *** its clinical utility,the TSF thickness trajectories and their correlation with overall mortality have not been thoroughly *** To explore TSF thickness trajectories of Chinese adults and to examine their associations with all-cause *** This study encompassed a cohort of 14747 adults sourced from the China Health and Nutrition *** class trajectory modeling was employed to identify distinct trajectories of TSF *** were classified into subgroups reflective of their respective TSF thickness *** utilized multivariate Cox regression analyses and mediation examinations to explore the link between TSF thickness trajectory and overall mortality,including contributory *** Upon adjustment for multiple confounding factors,we discerned that males in the‘Class 2:Thin-stable’and‘Class 3:Thin-moderate’TSF thickness trajectories exhibited a markedly reduced risk of mortality from all causes in comparison to the‘Class 1:Extremely thin’*** the mediation analyses,the Geriatric Nutritional Risk Index was found to be a partial intermediary in the relationship between TSF thickness trajectories and *** females,a lower TSF thickness pattern was significantly predictive of elevated all-cause mortality risk exclusively within the non-elderly *** In males and non-elderly females,lower TSF thickness trajectories are significantly predictive of heightened mortality risk,independent of single-point TSF thickness,body mass index,and waist circumference.

关键词： Triceps skinfold thickness Trajectory All-cause mortality Body mass index Geriatric Nutritional Risk Index

Multiscale feature learning and attention mechanism for infrared and visible image fusion

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Science China(Technological Sciences) 2024年第2期67卷 408-422页

作者： gao li LUO Delin WANG Song School of Aerospace Engineering Xiamen UniversityXiamen 361102China Electric Power Research Institute China Southern Power GridGuangzhou 510063China

Current fusion methods for infrared and visible images tend to extract features at a single scale,which results in insufficient detail and incomplete feature *** address these issues,we propose an infrared and visible image fusion network based on a multiscale feature learning and attention mechanism(MsAFusion).A multiscale dilation convolution framework is employed to capture image features across various scales and broaden the perceptual ***,an attention network is introduced to enhance the focus on salient targets in infrared images and detailed textures in visible *** compensate for information loss during convolution,jump connections are utilized during the image reconstruction *** fusion process utilizes a combined loss function consisting of pixel loss and gradient loss for unsupervised fusion of infrared and visible *** experiments on the dataset of electricity facilities demonstrate that our proposed method outperforms nine state-of-theart methods in terms of visual perception and four objective evaluation metrics.

关键词： infrared and visible images image fusion attention mechanism CNN feature extraction

Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence:A population-based study

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World Journal of Gastrointestinal Oncology 2024年第6期16卷 2404-2418页

作者： Jie Song Xiang-Xiu Yan Fang-liang Zhang Yong-Yi Lei zi-Yin ke Fang li Kai Zhang Yu-Qi He Wei li Chao li Yuan-Ming Pan Department of Gastroenterology Dongying People’s HospitalDongying Hospital of Shandong Provincial Hospital GroupDongying 257000Shandong ProvinceChina Gastrointestinal Surgery Department Suining Central HospitalSuining 629000Sichuan ProvinceChina Obstetrical Department Suining Central HospitalSuining 629000Sichuan ProvinceChina School of Medicine Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107Guangdong ProvinceChina Department of Pathology Aerospace Center HospitalPeking University Aerospace School of Clinical MedicineBeijing 100049China General Department Beijing Chest HospitalCapital Medical University/Beijing Tuberculosis and Thoracic Tumor Research InstituteBeijing 101149China Department of Gastroenterology Beijing Chest HospitalCapital Medical University/Beijing Tuberculosis and Thoracic Tumor Research InstituteBeijing 101149China Department of Thoracic Surgery Sichuan Academy of Medical Sciences and Sichuan Provincial People’s HospitalUniversity of Electronic Science and Technology of ChinaChengdu 610072Sichuan ProvinceChina Department of Gastroenterology Aerospace Center HospitalPeking University Aerospace School of Clinical MedicineBeijing 100049China Cancer Research Center Beijing Chest HospitalCapital Medical University/Beijing Tuberculosis and Thoracic Tumor Research InstituteBeijing 101149China

BACKGROUND Research on gastrointestinal mucosal adenocarcinoma(GMA)is limited and controversial,and there is no reference tool for predicting postoperative *** To investigate the prognosis of GMA and develop predictive *** From the Surveillance,Epidemiology,and End Results database,we collected clinical information on patients with *** random sampling,the patients were divided into the discovery(70%of the total,for model training),validation(20%,for model evaluation),and completely blind test cohorts(10%,for further model evaluation).The main assessment metric was the area under the receiver operating characteristic curve(AUC).All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA’s *** This model had an AUC of 0.7433[95% confidence intervals(95%CI):0.7424-0.7442]in the discovery cohort,0.7244(GMA:0.7234-0.7254)in the validation cohort,and 0.7388(95%CI:0.7378-0.7398)in the test *** packaged it into Windows software for doctors’use and uploaded *** gastric adenocarcinoma had the worst prognosis,and these were protective factors of GMA:Regional nodes examined[hazard ratio(HR):0.98,95%CI:0.97-0.98,P<0.001]and chemotherapy(HR:0.62,95%CI:0.58-0.66,P<0.001).CONCLUSION The deep learning-based tool developed can accurately predict the overall survival of patients with GMA *** surgery,chemotherapy,and adequate lymph node dissection during surgery can improve patient outcomes.

关键词： Deep learning Gastrointestinal mucous adenocarcinoma Overall survival Surgery Clinical tool

Correlation between cerebral neurotransmitters levels by proton magnetic resonance spectroscopy and HbA1c in patients with type 2 diabetes

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World Journal of Diabetes 2024年第6期15卷 1263-1271页

作者： Xiang-Yu gao Chen-Xia Zhou Hong-Mei li Min Cheng Da Chen zi-Yi li Bo Feng Jun Song Department of Endocrinology East HospitalTongji University School of MedicineShanghai 200120China Department of Endocrinology Qilu Hospital(Qingdao)Cheeloo College of MedicineShandong UniversityQingdao 266000Shandong ProvinceChina Department of Immunization Program Huangdao District Center for Disease Prevention and ControlQingdao 266400Shandong ProvinceChina

BACKGROUND Cognitive dysfunction is the main manifestation of central *** cognitive impairments tend to be overlooked in patients with diabetes mellitus(DM),there is a growing body of evidence linking DM to cognitive *** is closely related to neurological abnormalities,while often disregarded in clinical *** in cerebral neurotransmitter levels are associated with a variety of neurological abnormalities and may be closely related to blood glucose control in patients with type 2 DM(T2DM).AIM To evaluate the concentrations of cerebral neurotransmitters in T2DM patients exhibiting different hemoglobin A1c(HbA1c)*** A total of 130 T2DM patients were enrolled at the Department of Endocrinology of Shanghai East *** participants were divided into four groups according to their HbA1c levels using the interquartile method,namely Q1(linical data were collected and measured,including age,height,weight,neck/waist/hip circumferences,blood pressure,comorbidities,duration of DM,and biochemical ***,neurotransmitters in the left hippocampus and left brainstem area were detected by proton magnetic resonance *** The HbA1c level was significantly associated with urinary microalbumin(mALB),triglyceride,low-density lipoprotein cholesterol(LDL-C),homeostasis model assessment of insulin resistance(HOMA-IR),and beta cell function(HOMA-β),N-acetylaspartate/creatine(NAA/Cr),and NAA/choline(NAA/Cho).Spearman correlation analysis showed that mALB,LDL-C,HOMA-IR and NAA/Cr in the left brainstem area were positively correlated with the level of HbA1c(P<0.05),whereas HOMA-βwas negatively correlated with the HbA1c level(P<0.05).Ordered multiple logistic regression analysis showed that NAA/Cho[Odds ratio(OR):1.608,95%confidence interval(95%CI):1.004-2.578,P<0.05],LDL-C(OR:1.627,95%CI:1.119-2.370,P<0.05),and HOMA-IR(OR:1.107,95%CI:1.031-

关键词： Type 2 diabetes mellitus Hemoglobin A1c Proton magnetic resonance spectroscopy Neurotransmitters Central neuropathy

SnO_(2)/metal organic complex composite derived from low-temperature activated metal organic complex for advanced lithium storage

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Rare Metals 2024年第7期43卷 3032-3043页

作者： Gui-Long liu zi-Han Zhao Jin-ke Shen zi-Bo Zhao Nai-Teng Wu Dong-Lei Guo Wei-Wei Yuan Yong liu Ye-Hua Su Xian-Ming liu Luoyang key Laboratory of Green Energy Materials College of Chemistry and Chemical EngineeringLuoyang Normal UniversityLuoyang 471934China School of Materials Science and Engineering Henan University of Science and TechnologyLuoyang 471023China Inner Mongolia Shijie Chemical Co. Ltd.Alxa League 737300

Sn-based metal organic complexes with coordination bonds,multi-active sites,and high theoretical capacity have attracted much attention as promising anodes for lithium ion ***,the low electrical conductivity and huge volume changes restricted their electrochemical stability and practical ***,Snbased anode with superior electrochemical performance,including a high reversible capacity of 1050.1 mAh·g^(-1)at 2 A·g^(-1)and a stable capacity of 1105.5 mAh·g^(-1)after 500 cycles at 1 A·g^(-1),was fabricated via a low-temperature calcination strategy from Sn metal organic *** low-temperature calcination process regulates Sn-O bond and prevents the agglomeration of SnO_(2),generating highly dispersed SnO_(2) decorated metal organic complexes and providing sufficient active sites for ion *** situ characterizations expound that the undecomposed Sn-based metal organic complexes could be transformed into SnO_(2) during lithiation and delithiation,which enhances the electrical conductivity and induces a strong pseudo-capacitive behavior,accelerating the electrochemical kinetics;the multiple solid electrolyte interface with inflexible liF and flexible ROCO_(2)li buffers the volume variation of the electrode,resulting in its high electrochemical *** work provides a simple strategy for preparing excellent Sn-based anodes from metal organic complexes and reveals the lithium storage mechanism of the prepared Snbased anode.

关键词： Metal organic complex lithium ion battery Electrochemical activation Low-temperature activation Partial decomposition

Particle effects on the hydrodynamics in slurry bubble column reactors:A review from multiscale mechanisms Author links open overlay panel

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Particuology 2024年第8期91卷 176-189页

作者： Min An Jingqi gao Tiankuo Wang Xiangnan li National Supercomputing Center in Zhengzhou Zhengzhou UniversityZhengzhou450001China School of Chemical Engineering and New Energy Xiamen University MalaysiaSepangSelangor43900Malaysia School of Chemistry and Chemical Engineering Henan Normal UniversityXinxiang453007China

Particles can appear as catalyst,reactant or product in various gas-liquid-solid three-phase production *** bubble column reactors(SBCRs),as a kind of three-phase reactors,are preferred for phase contacting and ***,literature studies concerning the effects of particles on the hydrodynamics of SBCRs are manifold and inconsistent in ***,the multiscale interactions between particles,turbulent eddies and bubbles determine the reactor *** review focuses on revealing the particle effects in SBCRs from the perspective of multiscale *** hydrodynamic changes due to particle effects in literature are *** parameters,including the Stokes number,the solid-to-liquid density ratio,the ratio of particle and liquid characteristic lengths,the contact angle and the particle volume fraction are adopted to evaluate the characteristics of gas-liquid-solid *** relationships between particle influencing mechanisms and these parameters are analyzed and *** experimental results are explained by different ranges of these dimensionless ***,particle effects at the mesoscale and microscale,such as the influence on the bubble dynamics and the pivoting effect on the turbulence energy spectrum,are ***,progress in modeling the SBCRs with consideration of particles effects using the Euler method are *** review aims to improve the overall understanding of the complex hydrodynamics in the SBCRs.

关键词： Slurry bubble column reactors Particle effects Turbulence characteristics Bubble dynamics CFD

Deep unfolding based channel estimation for wideband terahertz near-field massive MIMO systems

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Frontiers of Information Technology & Electronic Engineering 2024年第8期25卷 1162-1172页

作者： Jiabao gao Xiaoming CHEN Geoffrey Ye li College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China Department of Electrical and Electronic Engineering Imperial College LondonLondon SW 2BUUK

The combination of terahertz and massive multiple-input multiple-output(MIMO)is promising for meeting the increasing data rate demand of future wireless communication systems thanks to the significant band-width and spatial degrees of ***,unique channel features,such as the near-field beam split effect,make channel estimation particularly challenging in terahertz massive MIMO *** one hand,adopting the conventional angular domain transformation dictionary designed for low-frequency far-feld channels will result in degraded channel sparsity and destroyed sparsity structure in the transformed *** the other hand,most existing compressive sensing based channel estimation algorithms cannot achieve high performance and low complexity *** alleviate these issues,in this study,we first adopt frequency-dependent near-field dictionaries to maintain good channel sparsity and sparsity structure in the transformed domain under the near-field beam split ***,a deep unfolding based wideband terahertz massive MIMO channel estimation algorithm is *** each iteration of the approximate message passing-sparse Bayesian learning algorithm,the optimal update rule is learned by a deep neural network(DNN),whose architecture is customized to effectively exploit the inherent channel ***,a mixed training method based on novel designs of the DNN architecture and the loss function is developed to effectively train data from different system *** results validate the superiority of the proposed algorithm in terms of performance,complexity,and robustness.

关键词： Terahertz Massive MIMO Channel estimation Deep learning