检索结果-南通市图书馆

维普期刊数据库

Glutamate oxidase-integrated biomimetic Fe_(3)O_(4) hybrids as cascade nanozymes for glutamate detection

在线全文

学校读者我要写书评

暂无评论

Particuology 2024年第5期88卷 192-200页

作者： Peikun Li Yanchao Wang Xiuyan Luo Zixin Geng jiahui jia Ruirui Wang jiandong Cui Hongjie Bian Shiru jia State Key Laboratory of Food Nutrition and Safety Laboratory of Industrial Fermentation MicrobiologyMinistry of EducationTianjin University of Science and TechnologyTianjin300457China Sports Department Hebei University of Science and TechnologyShijiazhang050000China Research Center for Fermentation Engineering of Hebei College of Bioscience and BioengineeringHebei University of Science and TechnologyShijiazhang050000China

Herein,a new nanozyme/natural enzyme hybrid biosensor was established for ultrasensitive l-glutamic acid(L-Glu)*** Fe_(3)O_(4) nanoparticles with peroxidase-like activity and stability was used as a nanozyme and carrier for immobilizing l-Glutamate oxidase(GLOD)through Schiffff base reaction to construct a chem-enzyme cascade *** resultant Fe_(3)O_(4)-GOLD exhibited a wide linear range(10−500μM)and a low detection limit of 6.03μM for L-Glu ***,the Fe_(3)O_(4)-GOLD exhibited excellent pH stability,thermal stability,reusability and storage *** repeated nine cycles,Fe_(3)O_(4)-GOLD still retained 70%of its initial ***,Fe_(3)O_(4)-GOLD maintained 50%of its initial activity after storage for 20 days,while free GLOD only retained 20%of its initial *** strategy of integrating biomimetic Fe 3 O4 and natural enzymes for cascade catalysis makes it possible to design an efficient and stable chemo-enzyme composite catalysts,which are promising for applications in biosensing and biomimetic catalysis.

关键词： Fe_(3)O_(4) nanozyme GLOD Chemo-enzymes Glutamate detection

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

静电纺PET纤维膜对空气的过滤性能研究

化工新型材料 2016年第2期44卷 237-239,243页

作者：顾广东李秀艳贾彬彬北京服装学院材料科学与工程学院北京100029

通过控制电纺时间制备了6种不同厚度的静电纺PET纤维膜,采用扫描电子显微镜和全自动透气量仪分别对纤维膜的微观形貌和透气性进行了分析研究,并将纤维膜与空调扇结合制成简易的空气净化器,在1m3的实验室中测试其对空气中颗粒物在特定条... 详细信息

通过控制电纺时间制备了6种不同厚度的静电纺PET纤维膜,采用扫描电子显微镜和全自动透气量仪分别对纤维膜的微观形貌和透气性进行了分析研究,并将纤维膜与空调扇结合制成简易的空气净化器,在1m3的实验室中测试其对空气中颗粒物在特定条件下的过滤性能。结果表明,在一定时间范围内,随着纺丝时间的增加,提高纤维的含量可以提升纤维膜对空气中颗粒物的过滤效果。

关键词： PET 静电纺丝纳米纤维膜空气过滤

维普期刊数据库

Optimization of the co-closing law of guide vanes and blades for bulb turbines based on CFD

在线全文

学校读者我要写书评

暂无评论

Journal of Hydrodynamics 2024年第2期36卷 363-377页

作者： Hui Liu Yun-fa Lin Yong-guang Cheng Song Xue Mao-jia Tang jian Zhang jia-yi Fan State Key Laboratory of Water Resources Engineering and Management Wuhan UniversityWuhan430072China Dongfang Electric Machinery Co. Ltd.Deyang618000China

The load rejection transient process of bulb turbine units is critical to safety of hydropower stations,and determining appropriate closing laws of guide vanes(GVs)and runner blades(RBs)for this process is of *** this study,we proposed a procedure to optimize the co-closing law of GVs and RBs by using computational fluid dynamics(CFD),combined with the design of experiment(DOE)method,approximation model,and genetic optimization *** sensitivity of closing law parameters on the histories of head,speed,and thrust was analyzed,and a two-stage GVs’closing law associating with a linear RBs’closing law was *** results show that GVs dominate the transient characteristics by controlling the change of *** GVs’first-stage closing speed while shortening first-stage closing time can not only significantly reduce the maximum rotational speed but also suppress the water hammer pressure;slowing GVs’second-stage closing speed is conducive to controlling the maximum reverse axial *** directly affect the runner *** RBs’closing speed can further reduce the rotational speed and the maximum reverse axial *** safety margin of each control parameter,flow patterns,and pressure pulsations of a practical hydropower station were all improved after optimization,demonstrating the effectiveness of this method.

关键词： Bulb turbine load rejection transient process double regulation closing law optimization computational fluid dynamics(CFD)

Sulfated peptides and their receptors:Key regulators of plant development and stress adaptation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Plant Communications 2024年第6期5卷 44-56页

作者： Liming He Liangfan Wu jia Li Ministry of Education Key Laboratory of Cell Activities and Stress Adaptations School of Life SciencesLanzhou UniversityLanzhou 730000China Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design School of Life SciencesGuangzhou UniversityGuangzhou 510006China

Four distinct types of sulfated peptides have been identiﬁed in Arabidopsis *** peptides play crucial roles in regulating plant development and stress *** studies have revealed that Xan-thomonas and Meloidogyne can secrete plant-like sulfated peptides,exploiting the plant sulfated peptide signaling pathway to suppress plant *** the past three decades,receptors for these four types of sulfated peptides have been identiﬁed,all of which belong to the leucine-rich repeat receptor-like protein kinase subfamily.A number of regulatory proteins have been demonstrated to play important roles in their corresponding signal transduction *** this review,we comprehensively summarize the discov-eries of sulfated peptides and their receptors,mainly in Arabidopsis *** also discuss their known biological functions in plant development and stress ***,we put forward a number of ques-tions for reference in future studies.

关键词： peptide hormone sulfated peptide receptor-like protein kinase plant development stress adaptation

A dynamical neural network approach for distributionally robust chance-constrained Markov decision process

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China Mathematics 2024年第6期67卷 1395-1418页

作者： Tian Xia jia Liu Zhiping Chen School of Mathematics and Statistics Xi’an Jiaotong UniversityXi’an710049China

In this paper,we study the distributionally robust joint chance-constrained Markov decision *** the logarithmic transformation technique,we derive its deterministic reformulation with bi-convex terms under the moment-based uncertainty *** cope with the non-convexity and improve the robustness of the solution,we propose a dynamical neural network approach to solve the reformulated optimization *** results on a machine replacement problem demonstrate the efficiency of the proposed dynamical neural network approach when compared with the sequential convex approximation approach.

关键词： Markov decision process chance constraints distributionally robust optimization moment-based ambiguity set dynamical neural network

维普期刊数据库

Biderivations of Hom-Lie Algebras and Superalgebras

在线全文

学校读者我要写书评

暂无评论

Acta Mathematica Sinica,English Series 2024年第10期40卷 2337-2358页

作者： La Mei YUAN jia Xin LI School of Mathematics Harbin Institute of Technology

On Hom-Lie algebras and superalgebras, we introduce the notions of biderivations and linear commuting maps, and compute them for some typical Hom-Lie algebras and superalgebras,including the q-deformed W(2, 2) algebra... 详细信息

关键词： 17A30 17A60 17B05 17B60 17B70 biderivations Hom-Lie algebras linear commuting maps q-deformed W(2 2) algebra q-deformed Witt algebra q-deformed Witt superalgebra

Enhancing Image Description Generation through Deep Reinforcement Learning:Fusing Multiple Visual Features and Reward Mechanisms

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第2期78卷 2469-2489页

作者： Yan Li Qiyuan Wang Kaidi jia School of Cyber Security Gansu University of Political Science and LawLanzhou730070China

Image description task is the intersection of computer vision and natural language processing,and it has important prospects,including helping computers understand images and obtaining information for the visually *** study presents an innovative approach employing deep reinforcement learning to enhance the accuracy of natural language descriptions of *** method focuses on refining the reward function in deep reinforcement learning,facilitating the generation of precise descriptions by aligning visual and textual features more *** approach comprises three key ***,it utilizes Residual Network 101(ResNet-101)and Faster Region-based Convolutional Neural Network(Faster R-CNN)to extract average and local image features,respectively,followed by the implementation of a dual attention mechanism for intricate feature ***,the Transformer model is engaged to derive contextual semantic features from textual ***,the generation of descriptive text is executed through a two-layer long short-term memory network(LSTM),directed by the value and reward *** with the image description method that relies on deep learning,the score of Bilingual Evaluation Understudy(BLEU-1)is 0.762,which is 1.6%higher,and the score of BLEU-4 is ***-based Image Description Evaluation(CIDEr)scored 0.998,Recall-Oriented Understudy for Gisting Evaluation(ROUGE)scored 0.552,the latter improved by 0.36%.These results not only attest to the viability of our approach but also highlight its superiority in the realm of image *** research can explore the integration of our method with other artificial intelligence(AI)domains,such as emotional AI,to create more nuanced and context-aware systems.

关键词： Image description deep reinforcement learning attention mechanism

A New Encrypted Traffic Identification Model Based on VAE-LSTM-DRN

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第1期78卷 569-588页

作者： Haizhen Wang Jinying Yan Na jia College of Computer and Control Engineering Qiqihar UniversityQiqihar161006China Heilongjiang Key Laboratory of Big Data Network Security Detection and Analysis Qiqihar UniversityQiqiharChina

Encrypted traffic identification pertains to the precise acquisition and categorization of data from traffic datasets containing imbalanced and obscured *** extraction of encrypted traffic attributes and their subsequent identification presents a formidable *** existing models have predominantly relied on direct extraction of encrypted traffic data from imbalanced datasets,with the dataset’s imbalance significantly affecting the model’s *** the present study,a new model,referred to as UD-VLD(Unbalanced Dataset-VAE-LSTM-DRN),was proposed to address above *** proposed model is an encrypted traffic identification model for handling unbalanced *** encoder of the variational autoencoder(VAE)is combined with the decoder and Long-short term Memory(LSTM)in UD-VLD model to realize the data enhancement processing of the original unbalanced *** enhanced data is processed by transforming the deep residual network(DRN)to address neural network gradient-related ***,the data is classified and *** UD-VLD model integrates the related techniques of deep learning into the encrypted traffic recognition technique,thereby solving the processing problem for unbalanced *** UD-VLD model was tested using the publicly available Tor dataset and VPN *** UD-VLD model is evaluated against other comparative models in terms of accuracy,loss rate,precision,recall,F1-score,total time,and ROC *** results reveal that the UD-VLD model exhibits better performance in both binary and multi classification,being higher than other encrypted traffic recognition models that exist for unbalanced ***,the evaluation performance indicates that the UD-VLD model effectivelymitigates the impact of unbalanced data on traffic *** can serve as a novel solution for encrypted traffic identification.

关键词： Data enhancement LSTM deep residual network VAE

Towards imbalanced motion:part-decoupling network for video portrait segmentation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第7期67卷 197-210页

作者： Tianshu YU Changqun XIA jia LI State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang University Peng Cheng Laboratory

Video portrait segmentation(VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, the simplicity of existing VPS datasets leads to a limitation on extensive research of the task. In this work, we propose a new intricate large-scale multi-scene video portrait segmentation dataset MVPS consisting of 101 video clips in 7 scenario categories,in which 10843 sampled frames are finely annotated at the pixel level. The dataset has diverse scenes and complicated background environments, which is the most complex dataset in VPS to our best *** the observation of a large number of videos with portraits during dataset construction, we find that due to the joint structure of the human body, the motion of portraits is part-associated, which leads to the different parts being relatively independent in motion. That is, the motion of different parts of the portraits is imbalanced. Towards this imbalance, an intuitive and reasonable idea is that different motion states in portraits can be better exploited by decoupling the portraits into parts. To achieve this, we propose a part-decoupling network(PDNet) for VPS. Specifically, an inter-frame part-discriminated attention(IPDA)module is proposed which unsupervisedly segments portrait into parts and utilizes different attentiveness on discriminative features specified to each different part. In this way, appropriate attention can be imposed on portrait parts with imbalanced motion to extract part-discriminated correlations, so that the portraits can be segmented more accurately. Experimental results demonstrate that our method achieves leading performance with the comparison to state-of-the-art methods.

关键词： video portrait segmentation imbalanced motion unsupervised part decoupling motion correlation inter-frame attention