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Journal of Analysis and Testing 2024年第2期8卷 237-244页

作者： Fei yu yue Wang Caiyuan yu Wei Zhang Xuefeng Bai state Key Laboratory of Quality Research in Chinese Medicines Macao Institute for Applied Research in Medicine and HealthMacao University of Science and TechnologyTaipaMacao999078China Baotou Cancer Hospital Baotou014040Inner MongoliaChina

miR-18a has been identified as a significantly expressed microRNA(miRNA)in non-small cell lung cancer(NsCLC)and plays a vital role in cancer cell transformation,metastasis,and ***,a pair of binary probes from numerous probe pairs based on single nucleotide polymorphism analyses of miR-18a and miR-18b was first designed and screened to develop a Y-shaped ratio biosensor for accurate detection of serum miR-18a in *** special structure of the binary probes combined with the hairpin showed strong specificity for miR-18a,which was confirmed by polyacrylamide gel electrophoresis assay and square wave voltammetry ***,it is beneficial to immobilize single-stranded DNA(ssDNA)probes due to the large specific surface area of nanoporous gold,thereby improving the sensitivity of the *** Y-shaped ratio biosensor exhibited a wide detection range and can quantify the concentration of miR-18a in the range of 10 fmol/L–100 pmol/L,with a limit of detection of 0.211 fmol/L(s/N=3).Moreover,it exhibits excellent detection capabilities in serum samples since the biosensor showed a high selectivity toward the coexistence of miR-18a and ***,the prepared Y-shaped ratio biosensor is a highly sensitive and specific miR-18a detection tool,capable of identifying microscopic amounts of miR-18a in serum samples,providing great potential for early screening of NsCLC.

关键词： Nanoporous gold Y-shaped biosensor miR-18a NsCLC

Efficient degradation of aqueous dichloromethane by an enhanced microbial electrolysis cell:Degradation kinetics,microbial community and metabolic mechanisms

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Journal of Environmental sciences 2024年第5期139卷 150-159页

作者： Meng Wu Di Zhao Bing Gu ZiruWang Jun Hu Zhiliang yu Jianming yu College of Environment College of Biotechnology and BioengineeringCollaborative Innovation Center of Yangtze River Delta Region Green PharmaceuticalsZhejiang University of TechnologyHangzhou 310014China shentuo Environment(Hangzhou)Co.Ltd. Hangzhou 311121China Zhejiang Tianyi Environmental Co.Ltd. Hangzhou 310000China

Dichloromethane(DCM)has been listed as a toxic and harmful water pollutant,and its re moval needs *** electrolysis cells(MECs)are viewed as a promising alterna tive for pollutant removal,which can be strengthened from two aspects:microbial inocula tion and *** this study,the MEC for DCM degradation was inoculated with the ac tive sludge enhanced by Methylobacterium rhodesianum H13(strain H13)and then acclimated in the form of a microbial fuel cell(MFC).Both the introduction of strain H13 and the initi ation in MFC form significantly promoted DCM *** degradation kinetics were fitted by the Haldane model,with V_(max),K_(h),K_(i)and v_(max)values of 103.2 mg/L/hr,97.8 mg/L268.3 mg/L and 44.7 mg/L/hr/cm^(2),*** cyclic voltammogram implies that DCM redox reactions became easier with the setup of MEC,and the electrochemical impedance spectrogram shows that the acclimated and enriched microbes reduced the charge transfe resistance from the electrode to the *** the biofilm,the dominant genera shifted from Geobacter to Hyphomicrobium in acclimation ***,Methylobacterium played an increasingly important *** metabolism mainly occurred through the hydrolytic glutathione s-transferase pathway,given that the gene dcmA was identified rather than the dhlA and P450/*** exogenous electrons facilitated the reduction of GssG,directly o indirectly accelerating the GsH-catalyzed *** study provides support fo the construction of an efficient and stable MEC for DCM removal in water environment.

关键词： Dichloromethane Microbial electrolysis cells Metabolic pathways Electron transfer Degradation kinetics

An integrative mathematical model of microwave ion thruster for mHz-frequency thrust noise analysis

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Chinese Journal of Aeronautics 2024年第4期37卷 121-136页

作者： Xiang NIU Hui LIU Daren yu Plasma Propulsion Laboratory Harbin Institute of TechnologyHarbin 150001China

Many high-precision space missions need thrusters to produce thrust with low noise to compensate for disturbances and ensure satellite platform stability. Microwave ion thruster is characterized with a wide thrust range and potential for these missions. A cost-effective and accurate mathematical model is crucial for mHz-frequency thrust noise analysis and feedback controller design. The Particle-In-Cell(PIC) and global models are two common simulation tools. The PIC model is characterized with high accuracy but huge computation cost, which is difficult to analyze long-time performance characteristics. Now, the global model is only used for the discharge chamber with low accuracy and cannot reflect ion extraction properties. In this paper, an integrative mathematical model is built for a 1-cm microwave ion thruster and can reflect ion beamlet divergence and impingement on the Accelerator Grid(AG). simulation results show good agreement with experiments at 0.06 sccm. However, the model demonstrates worse consistency with experiments when the flux increases to 0.1 sccm, which may be because the influence of neutral gas on the Electron Cyclotron Resonance(ECR) is not considered in the model. A long-time(1000 s) simulation is conducted with this model under 35 μN. It takes 3 hrs, and the thrust noise reaches 1 μN/Hz^(0.5) at 1 mHz.

关键词： Electric propulsion Microwave ion thruster Integrative model sheath property Ion beamlet divergence Thrust noise Plasma

Polymer-to-Monomers Chemically Recyclable Poly(imide-imine)Plastics with Extreme-Condition Resistance and Flame Retardancy

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Chinese Journal of Polymer science 2024年第10期42卷 1525-1535,I0012页

作者： Zhen-yu Wang Xiao-Kong Liu state Key Laboratory of supramolecular structure and Materials College of ChemistryJilin UniversityChangchun130012China

Polyimides are a family of high-tech plastics that have irreplaceable applications in the fields of aerospace,defense,and opto-electronics,but polyimides are difficult to be reprocessed and recycled at the end of their service life,resulting in a significant waste of ***,it is of great significance to develop recyclable polyimides with comparable properties to the commercial ***,we report a novel polymer-to-monomers chemically recyclable poly(imide-imine)(PtM-CR-PII)plastic,synthesized by cross-linking the amine-terminated aromatic bisimide monomer and the hexa-vanillin terminated cyclophosphazene monomer via dynamic imine *** PtM-CR-PII plastic exhibits comparable mechanical and thermal properties as well as chemical stability to the commercial *** PtM-CR-PII plastic possesses a high Young’s modulus of≈3.2 GPa and a tensile strength as high as≈108 MPa,which also exhibits high thermal stability with a glass transition temperature of≈220℃.Moreover,the PtM-CR-PII plastic exhibits outstanding waterproofness,acid/alkali-resistance,and solvent-resistance,its appearance and mechanical properties can be well maintained after long-term soaking in water,highly concentrated acid and base,and various organic ***,the cyclophosphazene moieties endow the PtM-CR-PII plastic with excellent flame *** PtM-CR-PII plastic exhibits the highest UL-94 flame-retarding rating of V-0 and a limiting oxygen index(LOI)value of 45.5%.Importantly,the PtM-CR-PII plastic can be depolymerized in an organic solvents-acid mixture medium at room temperature,allowing easy separation and recovery of both monomers in high *** recovered pure monomers can be used to regenerate new PtM-CR-PII plastics,enabling sustainable polymer-monomers-polymer circulation.

关键词： Chemical recyclability Polyimides Polyimines Dynamic imine bonds Mechanical properties Chemical stability

A Comparison of Four Neural Networks Algorithms on Locomotion Intention Recognition of Lower Limb Exoskeleton Based on Multi-source Information

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Journal of Bionic Engineering 2024年第1期21卷 224-235页

作者： Duojin Wang Xiaoping Gu Hongliu yu Institute of Rehabilitation Engineering and Technology University of Shanghai for Science and Technology516 Jungong RoadShanghai 200093China shanghai Engineering Research Center of Assistive Devices 516 Jungong RoadShanghai 200093China

Lower Limb Exoskeletons(LLEs)are receiving increasing attention for supporting activities of daily *** such active systems,an intelligent controller may be *** this paper,we proposed a locomotion intention recognition system based on time series data sets derived from human motion *** of input data and Deep Learning(DL)algorithms,this framework enables the detection and prediction of users’movement *** makes it possible to predict the detection of locomotion modes,allowing the LLEs to provide smooth and seamless *** pre-processed eight subjects were used as input to classify four scenes:standing/Walking on Level Ground(s/WOLG),Up the stairs(Us),Down the stairs(Ds),and Walking on Grass(WOG).The result showed that the ResNet performed optimally compared to four algorithms(CNN,CNN-LsTM,ResNet,and ResNet-Att)with an approximate evaluation indicator of 100%.It is expected that the proposed locomotion intention system will significantly improve the safety and the effectiveness of LLE due to its high accuracy and predictive performance.

关键词： Lower limb exoskeletons(LLEs) Locomotion intention ResNet Multi-source

Design and Gait Planning of a Worm-inspired Metameric Robot for Pipe Crawling

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Journal of Bionic Engineering 2024年第3期21卷 1265-1277页

作者： yu Liu Qingbiao shi Zhen Chen Pen-Tung sah Institute of Micro-Nano science and Technology Xiamen UniversityXiamen361102China

The earthworm has been attracted much attention in the research and development of biomimetic robots due to their unique locomotion mechanism,compact structure,and small motion *** paper presents a new design and prototype of a worm-inspired metameric robot with a movement pattern similar to that of *** robot consists of multiple telescopic modules connected in series through joint *** telescopic module mimics the contraction and elongation motion modes of the earthworm segments.A kinematic and dynamic analysis is conducted on the telescopic module,and an input torque calculation method is provided to ensure sufficient friction between the robot and the pipe *** gait modes of the prototype robot for straight and turning locomotion are introduced,and these modes are extended to robots constructed by different numbers of telescopic *** addition,a method is proposed to increase the friction between the robot and the pipe wall in the aforementioned gait modes without changing the robot structure,thereby improving the robot’s motion ability in *** theoretical model of gait modes has also been validated through gait *** findings of this paper would provide a useful basis for the design,modeling,and control of future worm inspired robots.

关键词： Bio-inspired robot spatial linkage mechanism Kinematics model Peristaltic locomotion

state-sensitive convolutional sparse coding for potential biomarker identification in brain signals

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science China(Information sciences) 2024年第5期67卷 270-286页

作者： Puli WANG yu QI Gang PAN College of Computer science and Technology Zhejiang University state Key Laboratory of Brain-Machine Intelligence Zhejiang University MOE Frontier science Center for Brain science and Brain-machine Integration Zhejiang University Affiliated Mental Health Center & Hangzhou seventh People's Hospital Zhejiang University School of Medicine

The identification of prototypical waveforms, such as sleep spindles and epileptic spikes, is crucial for the diagnosis of neurological disorders. These prototypical waveforms are usually recurrently presented in certain brain states, serving as potential biomarkers for clinical evaluations. Convolutional sparse coding(CsC) approaches have demonstrated strength in identifying recurrent patterns in time-series. However,existing CsC approaches do not explicitly explore state-specific patterns, making it difficult to identify state-related biomarkers. To address this problem, we propose state-sensitive CsC to learn state-specific prototypical waveforms. specifically, we model signals of a certain state with specific waveforms that only appear frequently in this state and background waveforms that are independent of states. Based on this,state-sensitive CsC separates state-specific waveforms from background ones explicitly by incorporating incoherence constraints into optimizations. Experiments with epilepsy brain signals demonstrate that our approach can effectively identify prototypical waveforms in pre-ictal states, providing potential biomarkers for seizure prediction. Our approach provides a promising tool for automatic biomarker candidate identification.

关键词： convolutional sparse coding prototypical waveforms state-specific dictionary biomarker identification neural signal processing

MsADCN:Multi-scale Attentional Densely Connected Network for Automated Bone Age Assessment

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Computers, Materials & Continua 2024年第2期78卷 2225-2243页

作者： Yanjun yu Lei yu Huiqi Wang Haodong Zheng Yi Deng College of Computer and Information science Chongqing Normal UniversityChongqing401331China College of Mathematics and statistics Chongqing UniversityChongqing401331China

Bone age assessment(BAA)helps doctors determine how a child’s bones grow and develop in clinical *** BAA methods rely on clinician expertise,leading to time-consuming predictions and inaccurate *** deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional *** operation is costly and *** address these problems,we propose a multi-scale attentional densely connected network(MsADCN)in this *** constructs a multi-scale dense connectivity mechanism,which can avoid overfitting,obtain the local features effectively and prevent gradient vanishing even in limited training ***,MsADCN designs multi-scale structures in the densely connected network to extract fine-grained features at different ***,coordinate attention is embedded to focus on critical features and automatically locate the regions of interest(ROI)without additional *** addition,to improve the model’s generalization,transfer learning is applied to train the proposed MsADCN on the public dataset IMDB-WIKI,and the obtained pre-trained weights are loaded onto the Radiological society of North America(RsNA)***,label distribution learning(LDL)and expectation regression techniques are introduced into our model to exploit the correlation between hand bone images of different ages,which can obtain stable age *** experiments confirm that our model can converge more efficiently and obtain a mean absolute error(MAE)of 4.64 months,outperforming some state-of-the-art BAA methods.

关键词： Bone age assessment deep learning attentional densely connected network muti-scale

Optimized parameters of downhole all-metal PDM based on genetic algorithm

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Petroleum science 2024年第4期21卷 2663-2676页

作者： Jia-Xing Lu Ling-Rong Kong yu Wang Chao Feng yu-Lin Gao China University of Geosciences (Beijing) Key Laboratory on Deep Geo-Drilling Technology of Ministry of Natural Resources

Currently, deep drilling operates under extreme conditions of high temperature and high pressure,demanding more from subterranean power motors. The all-metal positive displacement motor, known for its robust performance, is a critical choice for such drilling. The dimensions of the PDM are crucial for its performance output. To enhance this, optimization of the motor's profile using a genetic algorithm has been undertaken. The design process begins with the computation of the initial stator and rotor curves based on the equations for a screw cycloid. These curves are then refined using the least squares method for a precise fit. Following this, the PDM's mathematical model is optimized, and motor friction is assessed. The genetic algorithm process involves encoding variations and managing crossovers to optimize objective functions, including the isometric radius coefficient, eccentricity distance parameter,overflow area, and maximum slip speed. This optimization yields the ideal profile parameters that enhance the motor's output. Comparative analyses of the initial and optimized output characteristics were conducted, focusing on the effects of the isometric radius coefficient and overflow area on the motor's performance. Results indicate that the optimized motor's overflow area increased by 6.9%, while its rotational speed reduced by 6.58%. The torque, as tested by Infocus, saw substantial improvements of38.8%. This optimization provides a theoretical foundation for improving the output characteristics of allmetal PDMs and supports the ongoing development and research of PDM technology.

关键词： Positive displacement motor Genetic algorithm Profile optimization Matlab programming Overflow area

Network Intrusion Traffic Detection Based on Feature Extraction

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Computers, Materials & Continua 2024年第1期78卷 473-492页

作者： Xuecheng yu Yan Huang yu Zhang Mingyang song Zhenhong Jia College of Information science and Engineering Xinjiang UniversityUrumqi830046China Network Department China Mobile Communications Group Xinjiang CoLtd.UrumqiUrumqi830011China Xinjiang signal Detection and Processing Key Laboratory Xinjiang UniversityUrumqi830000China

With the increasing dimensionality of network traffic,extracting effective traffic features and improving the identification accuracy of different intrusion traffic have become critical in intrusion detection systems(IDs).However,both unsupervised and semisupervised anomalous traffic detection methods suffer from the drawback of ignoring potential correlations between features,resulting in an analysis that is not an optimal ***,in order to extract more representative traffic features as well as to improve the accuracy of traffic identification,this paper proposes a feature dimensionality reduction method combining principal component analysis and Hotelling’s T^(2) and a multilayer convolutional bidirectional long short-term memory(MsC_BiLsTM)classifier model for network traffic intrusion *** method reduces the parameters and redundancy of the model by feature extraction and extracts the dependent features between the data by a bidirectional long short-term memory(BiLsTM)network,which fully considers the influence between the before and after *** network traffic is first characteristically downscaled by principal component analysis(PCA),and then the downscaled principal components are used as input to Hotelling’s T^(2) to compare the differences between *** datasets with outliers,Hotelling’s T^(2) can help identify the groups where the outliers are located and quantitatively measure the extent of the ***,a multilayer convolutional neural network and a BiLsTM network are used to extract the spatial and temporal features of network traffic *** empirical consequences exhibit that the suggested approach in this manuscript attains superior outcomes in precision,recall and F1-score juxtaposed with the prevailing *** results show that the intrusion detection accuracy,precision,and F1-score of the proposed MsC_BiLsTM model for the CIC-IDs 2017 dataset are 98.71%,95.97%,and 90.22%.

关键词： Network intrusion traffic detection PCA Hotelling’s T^(2) BiLsTM