检索结果-南通市图书馆

Journal of Rare Earths 2024年第7期42卷 1298-1303,I0004页

作者： Pei-yu Liao yu-Quan Qi Zhen Li Jian-Hua Jia Ming-Liang Tong Key Laboratory of Bioinorganic and Synthetic Chemistry of Ministry of Education School of ChemistrySun Yat-Sen UniversityGuangzhou510006China

On account of the complicated magnetic exchange interactions between lanthanide ions,binuclear lanthanide complexes have broad application prospect in the field of single-molecule ***,it is necessary to develop reasonable bridging ligands to manipulate the directional assembly of binuclear lanthanide ***,we selected the macrocyclic ligand L^(N_(8)O_(2))to build up two new dilanthanide complexes[Ln_(2)(LN_(8)O_(2))(OpyO)_(2)(H_(2)O)2](NO_(3))_(2)(1-Ln,Ln=Dy,Tb;LN_(8)O_(2)=hexamethyl-tetraaza-dioxe-dipyrazolacycloicosaphane-2,9,12,19-tetraene;OpyOH=2-pyridinol-1-oxide).Dynamic magnetic studies show that 1-Dy exhibits slow relaxation behavior under a 1 kOe applied *** fitting analysis of relaxation times gives the effective energy barrier of 38.2 cm^(−1),and reveals that the slow magnetic relaxation behavior is dominated by the Orbach and Raman ***-resolution luminescence emission spectrum indicates the energy gap of 36.8 cm^(−1)between the ground state and the first excited state,consistent with the magnetic measurement results.1-Tb exhibits brilliant characteristic green light emission under UV light *** absolute quantum yield of 1-Tb is 44.8%,and its first-order fitted decay lifetime is 779.21μs at room *** study provides the way for directional construction of high-performance molecular materials with magnetic and optical dual-function.

关键词： Dilanthanide complexes Single-molecule magnets Macrocyclic ligand Photoluminescence behavior Rare earths

Growth of Ag/g-C_(3)N_(4) nanocomposites on nickel foam to enhance photocatalytic degradation of formaldehyde under visible light

在线全文

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第3期137卷 432-442页

作者： Ze Wang Zhi Huang Jiang yu Xiao Shao Weidong Peng Jie yu Yinying Jiang Department of Environmental Science and Engineering College of Architecture and EnvironmentSichuan UniversityChengdu 610065China Institute of New Energy and Low Carbon Technology Sichuan UniversityChengdu 610065China School of Agriculture and Environment University of Western AustraliaPerth 6907Western AustraliaAustralia Yibin Institute of Industrial Technology Sichuan UniversityYibin 644000China

Formaldehyde is a pollutant that significantly affects the indoor air ***,conventional remediation approaches can be challenging to deal with low-concentration formaldehyde in an indoor *** this study,Photocatalysts of Ag/graphitic carbon nitride(g-C_(3)N_(4))/Ni with 3D reticulated coral structure were prepared by thermal polymerization and liquid phase photo-deposition,using nickel foam(NF)as the *** demonstrated that when the Ag concentration was 3%,and the relative humidity was 60%,the Ni/Ag/g-C_(3)N_(4)showed the maximum degradation rate of formaldehyde at 90.19%under visible light irradiation,and the formaldehyde concentration after degradation was lower than the Hygienic standard stated by the Chinese *** porous structure of Ni/Ag/g-C_(3)N_(4)and the formation of Schottky junctions promoted the Adsorption efficiency and degradation of formaldehyde,while the nickel foam carrier effectively promoted the desorption of degradation ***,the degradation rate was only reduced by3.4%after 16 recycles,the three-dimensional porous structure extended the lifetime of the *** study provides a new strategy for the degradation of indoor formaldehyde at low concentrations.

关键词： Graphitic carbon nitride(g-C_(3)N_(4)) Nickel foam(NF) Ag Formaldehyde Photocatalysis

Data-driven modeling on anisotropic mechanical behavior of brain tissue with internal pressure

在线全文

学校读者我要写书评

暂无评论

Defence Technology（防务技术） 2024年第3期33卷 55-65页

作者： Zhiyuan Tang yu Wang Khalil I.Elkhodary Zefeng yu Shan Tang Dan Peng State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of Technology116023DalianPR China The Department of Mechanical Engineering The American University in CairoNew Cairo11835Egypt Department of Neurology The Second Hospital of Dalian Medical UniversityDalian116023PR China

Brain tissue is one of the softest parts of the human body,composed of white matter and grey *** mechanical behavior of the brain tissue plays an essential role in regulating brain morphology and brain ***,traumatic brain injury(TBI)and various brain diseases are also greatly influenced by the brain's mechanical *** white matter or grey matter,brain tissue contains multiscale structures composed of neurons,glial cells,fibers,blood vessels,etc.,each with different mechanical *** such,brain tissue exhibits complex mechanical behavior,usually with strong nonlinearity,heterogeneity,and directional *** a constitutive law for multiscale brain tissue using traditional function-based approaches can be very ***,this paper proposes a data-driven approach to establish the desired mechanical model of brain *** focus on blood vessels with internal pressure embedded in a white or grey matter matrix material to demonstrate our *** matrix is described by an isotropic or anisotropic nonlinear elastic model.A representative unit cell(RUC)with blood vessels is built,which is used to generate the stress-strain data under different internal blood pressure and various proportional displacement loading *** generated stress-strain data is then used to train a mechanical law using artificial neural networks to predict the macroscopic mechanical response of brain tissue under different internal ***,the trained material model is implemented into finite element software to predict the mechanical behavior of a whole brain under intracranial pressure and distributed body *** with a direct numerical simulation that employs a reference material model,our proposed approach greatly reduces the computational cost and improves modeling *** predictions made by our trained model demonstrate sufficient ***,we find that the level of internal blood pressur

关键词： Data driven Constitutive law Anisotropy Brain tissue Internal pressure

More tree growth reduction due to consecutive drought and its legacy effect for a semiarid larch plantation in Northwest China

在线全文

学校读者我要写书评

暂无评论

Journal of Forestry Research 2024年第2期35卷 188-196页

作者： Yanfang Wan Pengtao yu Yanhui Wang Jiamei Li yushi Bai Yipeng yu Bingbing Liu Xiaocha Wei Key Laboratory of Forest Ecology and Environment of National Forestry and Grassland Administration Ecology and Nature Conservation InstituteChinese Academy of ForestryBeijing 100091People’s Republic of China

Extreme climate has increasingly led to negative impacts on forest ecosystems globally,especially in semiarid areas where forest ecosystems are more ***,it is poorly understood how tree growth is affected by different drought *** 2006–2009,the larch plantations in the semiarid areas of Northwest China were negatively affected by four consecutive dry years,which was a very rare phenomenon that may occur frequently under future climate *** this study,we analyzed the effect of these consecutive dry years on tree growth based on the data of the tree rings in the dominant layer of the forest canopy on a larch *** found that the tree-ring width index(RWI)in dry years was lower than that in normal years,and it experienced a rapidly decreasing trend from 2006 to 2009(slope=-0.139 year^(-1),r=-0.94)due to water supply deficits in those dry *** induced legacy effects of tree growth reduction,and consecutive dry years corresponded with greater growth reductions and legacy *** reductions and legacy effects were significantly stronger in the third and fourth consecutive dry years than that of single dry year(p<0.05),which might have been due to the cumulative stress caused by consecutive dry *** results showed that larch trees experienced greater tree growth reduction due to consecutive dry years and their legacy effect,and the trees had lower recovery rates after consecutive dry *** results highlight that consecutive dry years pose a new threat to plantations under climate warming,and thus,the effect of climate extremes on tree growth should be considered in growth models in semiarid areas.

关键词： Tree rings Drought effects Legacy effects Growth-climate relationships Larix principis-rupprechtii

Microstructure recognition of steels by machine learning based on visual attention mechanism

在线全文

学校读者我要写书评

暂无评论

Journal of Iron and Steel Research International 2024年第4期31卷 909-923页

作者： Xing-yu Chen Lin Cheng Cheng-yang Hu yu-peng Zhang Kai-ming Wu The State Key Laboratory of Refractories and Metallurgy Hubei Province Key Laboratory of Systems Science on Metallurgical ProcessingInternational Research Institute for Steel TechnologyCollaborative Center on Advanced SteelsWuhan University of Science and TechnologyWuhan 430081HubeiChina Metals Valley and Band(Foshan)Metallic Composite Materials Co. Ltd.Foshan 528000GuangdongChina

U-Net has achieved good performance with the small-scale datasets through skip connections to merge the features of the low-level layers and high-level layers and has been widely utilized in biomedical image segmentation as well as recent microstructure image segregation of the *** representative visual attention mechanism modules,named as squeeze-and-excitation networks,convolutional block attention module,and extended calibration algorithm,were intro-duced into the traditional U-Net architecture to further improve the prediction *** is found that compared with the original U-Net architecture,the evaluation index of the improved U-Net architecture has been significantly improved for the microstructure segmentation of the steels with the ferrite/martensite composite microstructure and pearlite/ferrite composite microstructure and the complex martensite/austenite island/bainite microstructure,which demonstrates the advantages of the utilization of the visual attention mechanism in the microstructure *** reasons for the accuracy improvement were discussed based on the feature maps analysis.

关键词： Microstructure recognition-Steel Machine learning Visual attention mechanism Visualization

An improved construction algorithm of polar codes based on the frozen bits

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Optoelectronics Letters 2024年第3期20卷 157-162页

作者： yuAN Jianguo ZHANG Fengguo yu Linfeng PANG yu School of Optoelectronic Engineering Chongqing University of Posts and TelecommunicationsChongqing 400065China

In order to improve the problems that the minimum hamming weight(MHW) of the polar codes of the traditional Gaussian approximation(GA) construction is small and its performance is not good enough, an improved channel construction algorithm of polar codes based on frozen bits is proposed by combining the construction of the Reed-Muller(RM) code to effectively increase the MHW and analyzing the correcting and checking functions of the frozen bits in the successive cancellation list(SCL) decoding.

关键词： polar algorithm successive

Evaluating the historical,clinical,and cultural value of the Tian Hui Yi Jian

在线全文

学校读者我要写书评

暂无评论

Journal of Traditional Chinese Medicine 2024年第1期44卷 220-221页

作者： yu Linyong GU Man China Academy of Chinese Medical Sciences Beijing 100700China Institute for History of Medicine and Medical Literature China Academy of Chinese Medical SciencesBeijing 100700China

Tian Hui Yi Jian was compiled by the Tianhui Medical Manuscripts Compilation Group,which includes scholars from the Institute for History of Medicine and Medical Literature of the China Academy of Chinese Medical Sciences(CACMS),Chengdu University of Traditional Chinese Medicine,Chengdu Institute of Cultural Relics and Archaeology,and Jingzhou Cultural Relics Protection *** was published by the Cultural Relics Press in November *** volume includes images of eight medical manuscripts,along with the Team's annotations,and photographs of a lacquered figurine with meridian-channels and words on its surface.

关键词： surface Chengdu Tian

Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 1329-1343页

作者： Bowen yu Chunli Xie College of Mechanical and Electrical Engineering Northeast Forestry UniversityHarbin150040China

With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment *** analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing *** defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall *** research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization *** proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical *** have conducted validation of the proposed method using datasets derived from gearbox and bearing *** empirical outcomes underscore the superior defect detection capability of our *** demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.

关键词： Industrial defect detection deep learning intelligent manufacturing

^(4)He monolayer on graphene:a quantum Monte Carlo study

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Communications in Theoretical Physics 2024年第9期76卷 149-157页

作者： S yu M Boninsegni Department of Physics University of AlbertaEdmontonAlbertaT6G 2H5Canada

We revisit the problem of adsorption of a single^(4)He layer on graphene,focusing on the commensurate(C_(1/3))crystalline phase,specifically on whether it may possess a nonzero superfluid response,and on the existence of superfluid phases,either(metastable)liquid or vacancy-doped *** make use of canonical quantum Monte Carlo simulations at zero and finite temperature,based on a realistic microscopic model of the *** results confirm the absence of any superfluid response in the commensurate crystal,and that no thermodynamically stable uniform phase exists at lower *** evidence of a possibly long-lived,metastable superfluid phase at C_(1/3)coverage is ***,the results of ground-state projection methods and finite-temperature simulations are entirely consistent.

关键词： superfluidity low-dimensional systems quantum Monte Carlo helium supersolids

De-biased knowledge distillation framework based on knowledge infusion and label de-biasing techniques

在线全文

学校读者我要写书评

暂无评论

Journal of Electronic Science and Technology 2024年第3期22卷 57-68页

作者： Yan Li Tai-Kang Tian Meng-yu Zhuang yu-Ting Sun School of Economics and Management University of Electronic Science and Technology of ChinaChengdu611731China School of Economics and Management Beijing University of Posts and TelecommunicationBeijing100876China School of Electrical Engineering and Computer Science The University of QueenslandBrisbane4072Australia

Knowledge distillation,as a pivotal technique in the field of model compression,has been widely applied across various ***,the problem of student model performance being limited due to inherent biases in the teacher model during the distillation process still *** address the inherent biases in knowledge distillation,we propose a de-biased knowledge distillation framework tailored for binary classification *** the pre-trained teacher model,biases in the soft labels are mitigated through knowledge infusion and label de-biasing *** on this,a de-biased distillation loss is introduced,allowing the de-biased labels to replace the soft labels as the fitting target for the student *** approach enables the student model to learn from the corrected model information,achieving high-performance deployment on lightweight student *** conducted on multiple real-world datasets demonstrate that deep learning models compressed under the de-biased knowledge distillation framework significantly outperform traditional response-based and feature-based knowledge distillation models across various evaluation metrics,highlighting the effectiveness and superiority of the de-biased knowledge distillation framework in model compression.

关键词： De-biasing Deep learning Knowledge distillation Model compression