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Cu-V双合金化3Mn钢的组织和力学性能

金属学报 2024年第6期60卷 817-825页

作者：许仁杰屠鑫胡斌罗海文北京科技大学冶金与生态工程学院北京100083

研究了Cu-V双合金化的3Mn钢热轧板在550~650℃温轧和临界退火等制备工艺过程中(简称温轧退火样品)的组织演变与最终力学性能,并与热轧后在同样温度范围时效处理并临界退火的样品(简称热轧时效退火样品)进行对比。结果表明,温轧退火样品... 详细信息

研究了Cu-V双合金化的3Mn钢热轧板在550~650℃温轧和临界退火等制备工艺过程中(简称温轧退火样品)的组织演变与最终力学性能,并与热轧后在同样温度范围时效处理并临界退火的样品(简称热轧时效退火样品)进行对比。结果表明,温轧退火样品的塑性显著高于热轧时效退火样品,但2者屈服强度相似,这归因于温轧阶段引入大量缺陷,促进了临界退火时奥氏体逆转变过程,提高了残余奥氏体分数,最终可实现屈服强度高达1230~1320 MPa并保有23%~29%的延伸率,这一综合性能显著优于文献中Cu/V单一合金化的中锰钢,尤其是屈服强度大幅提高。这是由于采用了Cu-V双合金化并且在热轧后采用了温轧加临界退火的两段热变形处理工艺,除了在温轧阶段引入富Cu析出相以实现强化外,在临界退火阶段析出的VC还弥补了由于退火导致的软化,实现了高屈服强度;并形成25%~30%的残余奥氏体来提供相变诱导塑性,从而保证了高塑性。

关键词：中锰钢温轧析出相奥氏体力学性能

Detecting somatisation disorder via speech:introducing the Shenzhen Somatisation Speech Corpus

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Intelligent Medicine 2024年第2期4卷 96-103页

作者： Kun Qian Ruolan huang Zhihao Bao Yang Tan Zhonghao Zhao Mengkai Sun bin hu Björn W.Schuller Yoshiharu Yamamoto Key Laboratory of Brain Health Intelligent Evaluation and Intervention Ministry of EducationBeijing Institute of TechnologyBeijing 100081China School of Medical Technology Beijing Institute of TechnologyBeijing 100081China The First School of Clinical Medicine Southern Medical UniversityGuangzhouGuangdong 510515China Department of Neurology Shenzhen University General HospitalShenzhenGuangdong 518055China Group on Language Audio&MusicImperial College LondonLondon SW72AZUK Embedded Intelligence for Health Care and Wellbeing University of AugsburgAugsburg 86159Germany Educational Physiology Laboratory Graduate School of EducationThe University of TokyoTokyo 113-0033Japan

Objective Speech recognition technology is widely used as a mature technical approach in many *** the study of depression recognition,speech signals are commonly used due to their convenience and ease of *** speech recognition is popular in the research field of depression recognition,it has been little studied in somatisation disorder *** reason for this is the lack of a publicly accessible database of relevant speech and benchmark *** this end,we introduced our somatisation disorder speech database and gave benchmark *** By collecting speech samples of somatisation disorder patients,in cooperation with the Shenzhen University General Hospital,we introduced our somatisation disorder speech database,the Shenzhen Somatisation Speech Corpus(SSSC).Moreover,a benchmark for SSSC using classic acoustic features and a machine learning model was proposed in our *** To obtain a more scientific benchmark,we compared and analysed the performance of different acoustic features,i.e.,the full ComPare feature set,or only Mel frequency cepstral coefficients(MFCCs),fundamental frequency(F0),and frequency and bandwidth of the formants(F1-F3).By comparison,the best result of our benchmark was the 76.0%unweighted average recall achieved by a support vector machine with formants F1–*** The proposal of SSSC may bridge a research gap in somatisation disorder,providing researchers with a publicly accessible speech *** addition,the results of the benchmark could show the scientific validity and feasibility of computer audition for speech recognition in somatization disorders.

关键词： Somatisation disorder Machine learning Healthcare Computer audition

Computed tomography three-dimensional reconstruction in the diagnosis of bleeding small intestinal polyps:A case report

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World Journal of Clinical Cases 2024年第16期12卷 2831-2836页

作者： Shu-hui Zhang Ming-Wei Fan Yan Chen Ying-bin hu Cheng-Xia Liu Department of Gastroenterology Binzhou Medical University HospitalBinzhou 256600Shandong ProvinceChina

BACKGROUND Computed tomography(CT)small bowel three-dimensional(3D)reconstruction is a powerful tool for the diagnosis of small bowel disease and can clearly show the intestinal lumen and wall as well as the outside structure of the *** horizontal axis position can show the best adjacent intestinal tube and the lesion between the intestinal tubes,while the coronal position can show the overall view of the small *** ileal end of the localization of the display of excellent,and easy to quantitative measurement of the affected intestinal segments,the sagittal position for the rectum and the pre-sacral lesions show the best,for the discovery of fistulae is also *** view can show rectal and presacral lesions and is useful for fistula *** is suitable for the assessment of inflammatory bowel disease,such as assessment of disease severity and diagnosis and differential diagnosis of the small bowel and mesenteric space-occupying lesions as well as the judgment of small bowel obstruction *** SUMMARY Bleeding caused by small intestinal polyps is often difficult to diagnose in clinical *** study reports a 29-year-old male patient who was admitted to the hospital with black stool and abdominal pain for 3 *** the combination of CT-3D reconstruction and capsule endoscopy,the condition was diagnosed correctly,and the polyps were removed using single-balloon enteroscopyendoscopic retrograde cholangiopancreatography without postoperative *** The role of CT-3D in gastrointestinal diseases was ***-3D can assist in the diagnosis and treatment of gastrointestinal diseases in combination with capsule endoscopy and small intestinal microscopy.

关键词： Computed tomography three-dimensional reconstruction Capsule endoscopy Single-balloon enteroscopy Gastrointestinal bleeding Case report

新时代我国工程教育质量问责的体系建构与机制探构

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黑龙江高教研究 2024年第4期42卷 33-39页

作者：胡洪彬浙江财经大学浙江杭州310018

工程教育质量问责既是工程教育质量提升的重要保障,也是新时代破解我国工程教育发展难题和深化工程教育改革的应有之义。推进新时代我国工程教育质量问责实现有序展开和科学运行,必须对工程教育质量问责的介入主体、指向客体、基本情形... 详细信息

工程教育质量问责既是工程教育质量提升的重要保障,也是新时代破解我国工程教育发展难题和深化工程教育改革的应有之义。推进新时代我国工程教育质量问责实现有序展开和科学运行,必须对工程教育质量问责的介入主体、指向客体、基本情形以及运行程序与方式等基本要素作出界定。近年来,在党和政府的高度重视和积极推动下,我国工程教育无论在规模还是实力上均实现了巨大提升,但较之于国外,我国工程教育质量问责依然处在探索阶段,尤其是缺乏针对性和具体性的制度规范体系。当前,在完善工程教育治理体系的进程中,应积极立足协同介入机制、全过程嵌入机制、规范操作机制、信息公开机制以及理念引导机制等层面,对我国工程教育质量问责作出探索性建构,由此才能为加快建设世界工程教育强国提供更加坚实的内在保障与制度支撑。

关键词：工程教育工程教育质量问责机制工程教育治理

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抑郁症EEG诊断的类脑学习模型

计算机工程与应用 2024年第3期60卷 157-164页

作者：曾昊辰胡滨关治洪华中科技大学人工智能与自动化学院武汉430074 华南理工大学未来技术学院广州510641 人工智能与数字经济广东省实验室(广州) 广州510335

抑郁症是一种全球性精神疾病,传统诊断方法主要依靠量表与医生的主观评估,无法有效识别症状,甚至存在误诊的风险。基于生理信号的深度学习辅助诊断有望改善传统缺乏生理学依据的方法。然而,传统深度学习方法依赖巨大算力,且大多是端到... 详细信息

抑郁症是一种全球性精神疾病,传统诊断方法主要依靠量表与医生的主观评估,无法有效识别症状,甚至存在误诊的风险。基于生理信号的深度学习辅助诊断有望改善传统缺乏生理学依据的方法。然而,传统深度学习方法依赖巨大算力,且大多是端到端的网络学习。这些学习方法也缺乏生理可解释性,限制了辅助诊断临床应用。提出一种用于抑郁症脑电图(electroencephalogram,EEG)诊断的类脑学习模型,在功能层面,构建脉冲神经网络对抑郁症与健康个体进行分类,精度超过97.5%,相比深度卷积方法,脉冲方法降低了能耗;在结构层面,利用复杂网络建立脑连接的空间拓扑并分析其图特征,找出了抑郁症个体潜在的脑功能连接异常机制。

关键词：类脑学习脉冲神经网络复杂网络特征抑郁症脑电图

铌微合金化和淬火速率对热成形钢组织与力学性能的影响

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材料工程 2024年第2期52卷 146-154页

作者：陈华丁灿灿胡斌罗海文北京科技大学冶金与生态工程学院北京100083

基于传统22MnB5钢设计了一种新型含Nb热成形钢,研究在不同淬火速率下Nb对热成形钢显微组织与力学性能的影响。新型Nb微合金化热成形钢与广泛应用的22MnB5商业钢种均经900℃保温3 min的固溶处理后分别水淬和油淬至室温,检测两种钢在两个... 详细信息

基于传统22MnB5钢设计了一种新型含Nb热成形钢,研究在不同淬火速率下Nb对热成形钢显微组织与力学性能的影响。新型Nb微合金化热成形钢与广泛应用的22MnB5商业钢种均经900℃保温3 min的固溶处理后分别水淬和油淬至室温,检测两种钢在两个淬火条件下的力学性能,并通过扫描电镜、背散射电子衍射仪、X射线衍射仪和透射电镜等分析合金组织。结果表明:油淬时Nb微合金化热成形钢与22MnB5钢能发生较明显的自回火,但前者的屈服强度高于后者约130 MPa,且伸长率也略有改善,对强化机制的定量计算表明这是由于含Nb钢晶粒细化形成的细晶强化以及位错强化和沉淀强化的共同作用;而在水淬条件下,两种钢的屈服强度与伸长率均相似,推测是由于冷却速率高抑制了自回火,使得马氏体相变产生的残余应力成为影响屈服强度的主导因素,而当水淬样品在170℃回火减轻内应力后,此时含Nb钢屈服强度再次高于22MnB5钢。

关键词： Nb微合金化热成形钢力学性能残余应力

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声表面波-自旋波耦合及磁声非互易性器件

物理学报 2024年第15期73卷 30-48页

作者：黄铭贤胡文彬白飞明电子科技大学电子科学与工程学院成都610054 电子科技大学电子薄膜与集成器件全国重点实验室成都611731

声表面波是激发和控制自旋波的一种新兴手段,不仅激励效率高,而且传输长度可以达到毫米量级,通过引入磁声耦合还可以打破时空反演对称性,实现声表面波的非互易传播.本文对不同类型的磁声耦合的物理机制进行了梳理,对比了磁弹性耦合、自... 详细信息

声表面波是激发和控制自旋波的一种新兴手段,不仅激励效率高,而且传输长度可以达到毫米量级,通过引入磁声耦合还可以打破时空反演对称性,实现声表面波的非互易传播.本文对不同类型的磁声耦合的物理机制进行了梳理,对比了磁弹性耦合、自旋-涡度耦合(包括非磁性层注入交变自旋流和磁性材料自身的Barnett效应),以及磁-旋转耦合在不同模式的声表面波激发下的等效驱动磁场,讨论了这些等效驱动场的角度依赖性,以及相应功率吸收的频率依赖性.这为在实际应用中区分和利用各种磁声耦合机制提供了理论支持.此外,本文还介绍了利用磁声耦合实现声表面波非互易性传输的两种主流手段,包括利用手性失配效应和引入具有非互易性自旋波色散关系的磁结构,对比并讨论了它们各自的物理机制和优劣势,希望为设计和发展基于磁声耦合的固态声学隔离器、环形器提供参考.

关键词：磁声耦合自旋波声表面波声子-磁振子耦合非互易性器件

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Study on the treatment of dysphagia after stroke with electromyographic biofeedback intensive training

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World Journal of Clinical Cases 2024年第19期12卷 3725-3733页

作者： Qing-Nan Meng Yue Zhu Si-Wen Liu bin hu De-Jun Chai Chun-Xue Dong Department of Rehabilitation Medicine The Second Affiliated Hospital of Qiqihar Medical CollegeQiqihar 161000Heilongjiang ProvinceChina

BACKGROUND Dysphagia,or swallowing disorder,is a common complication following stroke,significantly impacting patients'quality of *** biofeedback(EMGBF)therapy has emerged as a potential rehabilitation technique to improve swallowing function,but its efficacy in comparison with conventional treatments remains to be further *** To investigate the effects of different treatment intensities of EMGBF on swallowing function and motor speed after *** The participants were divided into three groups,all of which received routine neurological drug therapy and motor function rehabilitation *** the basis of routine swallowing disorder training,the EMGBF group received additional EMGBF training,while the enhanced EMGBF group received two additional training *** weeks before and after treatment,the degree of swallowing disorder was evaluated using the degree of swallowing disorder score(VGF)and the Rosenbek penetration-aspiration scale(PAS).RESULTS Initially,there was no significant difference in VGF and PAS scores among the groups(P>0.05).After four weeks,all groups showed significant improvement in both VGF scores and PAS ***,the standardized swallowing assessment and videofluoroscopic dysphagia scale scores also improved significantly post-treatment,indicating enhanced swallowing function and motor function of the hyoid-bone laryngeal complex,particularly in the intensive EMGBF *** EMGBF training is more effective than traditional swallowing training in improving swallowing function and the movement rate of the hyoid laryngeal complex in patients with post-stroke dysphagia.

关键词： Stroke Swallowing disorder Electromyographic biofeedback therapy Rosenbek penetration-aspiration scale score Swallowing disorder score

Prediction of ultimate tensile strength of Al-Si alloys based on multimodal fusion learning

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Materials Genome Engineering Advances 2024年第1期2卷 104-119页

作者： Longfei Zhu Qun Luo Qiaochuan Chen Yu Zhang Lijun Zhang bin hu Yuexing Han Qian Li State Key Laboratory of Advanced Special Steels&Shanghai Key Laboratory of Advanced Ferrometallurgy&School of Materials Science and Engineering Shanghai UniversityShanghaiChina School of Computer Engineering and Science Shanghai UniversityShanghaiChina College of Materials Science and Engineering Chongqing UniversityChongqingChina State Key Laboratory of Powder Metallurgy Central South UniversityChangshaChina CSMET Group Co. Ltd.ShanghaiChina Zhejiang Laboratory HangzhouChina National Engineering Research Center for Magnesium Alloy Chongqing UniversityChongqingChina National Key Laboratory of Advanced Casting Technologies Chongqing UniversityChongqingChina

Exploring the“composition-microstructure-property”relationship is a long-standing theme in materials ***,complex interactions make this area of research *** on the image processing and machine learning techniques,this paper proposes a multimodal fusion learning framework that comprehensively considers both composition and microstructure in prediction of the ultimate tensile strength(UTS)of Al-Si ***,the composition and image information are collected from the literature and supplementary experi-ments,followed by the image segmentation and quantitative analysis of eutectic Si ***,the quantitative analysis results are combined with other features for three-step feature screening,and 12 key features are ***,four machine-learning models(i.e.,decision tree,random forest,adaptive boosting,and extreme gradient boosting[XGBoost])are used to predict the UTS of Al-Si *** results show that the quantitative analysis method proposed in this paper is superior to Image-Pro Plus(IPP)software in some *** XGBoost model has the best prediction performance with R^(2)=***,five mixed features and their critical values that significantly affect UTS are *** study provides enlightenment for the prediction of UTS of Al-Si alloys from composition and microstructure,and would be applicable to other alloys.

关键词： Al-Si alloys image processing machine learning multimodal property prediction