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A Cross-Domain Ontology Semantic Representation Based on NCBI-BlueBERT Embedding

Chinese Journal of Electronics 2022年第5期31卷 860-869页

作者： zhao lingling WANG Junjie WANG Chunyu GUO Maozu Faculty of Computing Harbin Institute of Technology Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical University Beijing Key Laboratory of Intelligent Processing for Building Big Data School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture

A common but critical task in biological ontologies data analysis is to compare the difference between ontologies. There have been numerous ontologybased semantic-similarity measures proposed in specific ontology domain, but it still remains a challenge for crossdomain ontologies comparison. An ontology contains the scientific natural language description for the corresponding biological aspect. Therefore, we develop a new method based on natural language processing(NLP) representation model bidirectional encoder representations from transformers(BERT) for cross-domain semantic representation of biological ontologies. This article uses the BERT model to represent the word-level of the ontologies as a set of vectors, facilitating the semantic analysis or comparing the biomedical entities named in an ontology or associated with ontology terms. We evaluated the ability of our method in two experiments: calculating similarities of pair-wise disease ontology and human phenotype ontology terms and predicting the pair-wise of proteins interaction. The experimental results demonstrated the comparative performance. This gives promise to the development of NLP methods in biological data analysis.

关键词： human phenotype ontology cross-domain semantic representation natural language description pair-wise disease ontology data analysis bidirectional encoder representations NLP protein interaction diseases proteins natural language processing ontologies (artificial intelligence) natural language processing representation neural nets bioinformatics semantic-similarity measures cross-domain ontology semantic representation semantic analysis NCBI-BlueBERT embedding biological ontology data analysis

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Deformation Analysis of Micro/Nano Indentation and Diamond Grinding on Optical Glasses

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Chinese Journal of Mechanical Engineering 2012年第3期25卷 411-418页

作者： zhao Qingliang zhao lingling GUO Bing STEPHENSIN David CORBETT John School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Materials Department Cranfield UniversityCranfieldBedford MK43 OALUK School of Applied Sciences Cranfield UniversityCranfieldBedford MK43 OALUK

The previous research of precision grinding optical glasses with electrolytic in process dressing （ELID） technology mainly concentrated on the action of ELID and machining parameters when grinding, which aim at generating very ＂smoothed＂ surfaces and reducing the subsurface damage. However, when grinding spectrosil 2000 and BK7 glass assisted with ELID technology, a deeply comparative study on material removal mechanism and the wheel wear behaviors have not been given yet. In this paper, the micro/nano indentation technique is initially applied for investigating the mechanical properties of optical glasses, whose results are then refereed to evaluate the machinability. In single grit diamond scratching on glasses, the scratching traces display four kinds of scratch characteristics according to different material removal modes. In normal grinding experiments, the result shows BK7 glass has a better machinability than that of spectrosil 2000, corresponding to what the micro/nano indentation vent revealed. Under the same grinding depth parameters, the smaller amplitude of acoustic emission （AE） raw signals, grinding force and grinding force ratio correspond to a better surface quality. While for these two kinds of glasses, with the increasing of grinding depth, the variation trends of the surface roughness, the force ratio, and the AE raw signals are contrary, which should be attributed to different material removal modes. Moreover, the SEM micrographs of used wheels surface indicate that diamond grains on the wheel surface after grinding BK7 glass are worn more severely than that of spectrosil 2000. The proposed research analyzes what happened in the grinding process with different material removal patterns, which can provide a basis for producing high-quality optical glasses and comprehensively evaluate the surface and subsurface integrity of optical glasses.

关键词： optical glasses micro/nano indentation single grit diamond scratching material removal mode surface integrity electrolytic in process dressing (ELID)

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An ACE/CRIS-observation-based Galactic Cosmic Rays heavy nuclei spectra model Ⅱ

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Science China(Physics,Mechanics & Astronomy) 2020年第1期63卷 100-111页

作者： Shuai Fu lingling zhao Gary PZank Miao Wang Yong Jiang Institute of Space Weather Nanjing University of Information Science and TechnologyNanjing 210044China Center for Space Plasma and Aeronomic Research(CSPAR) University of Alabama in HuntsvilleHuntsville AL 35805USA Department of Space Science University of Alabama in HuntsvilleHuntsville AL 35899USA

An observation-based Galactic Cosmic Ray(GCR)spectral model for heavy nuclei is *** and Qin[*** Phys.118,1837(2013)]proposed an empirical elemental GCR spectra model for nuclear charge 5≤z≤28 over the energy range^30 to 500 Me V/nuc,which is proved to be successful in predicting yearly averaged GCR heavy nuclei *** on the latest highly statistically precise measurements from ACE/CRIS,a further elemental GCR model with monthly averaged spectra is *** model can reproduce the past and predict the future GCR intensity monthly by correlating model parameters with the continuous sunspot number(SSN)*** effects of solar activity on GCR modulation are considered separately for odd and even solar *** with other comprehensive GCR models,our modeling results are satisfyingly consistent with the GCR spectral measurements from ACE/SIS and IMP-8,and have comparable prediction accuracy as the Badhwar&O’Neill 2014 model.A detailed error analysis is also ***,the GCR carbon and iron nuclei fluxes for the subsequent two solar cycles(SC 25 and 26)are predicted and they show a potential trend in reduced flux amplitude,which is suspected to be relevant to possible weak solar cycles.

关键词： Galactic Cosmic Rays spectral model solar modulation heavy nuclei

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Evolved clustering analysis of 300 MW boiler furnace pressure sequence based on entropy characterization

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Science China(Technological Sciences) 2016年第4期59卷 647-656页

作者： GU Hui REN ShaoJun SI FengQi XU ZhiGao zhao lingling Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education Southeast University

The furnace process is very important in boiler operation,and furnace pressure works as an important parameter in furnace ***,there is a need to analyze and monitor the pressure signal in ***,little work has been conducted on the relationship with the pressure sequence and boiler’s load under different working *** pressure sequence contains complex information,it demands feature extraction methods from multi-aspect *** this paper,fuzzy c-means analysis method based on weighted validity index(VFCM)has been proposed for the working condition classification based on feature *** deal with the fluctuating and time-varying pressure sequence,feature extraction is taken as nonlinear analysis based on entropy *** kinds of entropy values,extracted from pressure sequence in time-frequency domain,are studied as the clustering objects for work condition *** validity index,taking the close and separation degree into consideration,is calculated on the base of Silhouette index and Krzanowski-Lai index to obtain the optimal clustering *** time FCM runs,the weighted validity index evaluates the clustering result and the optimal clustering number will be obtained when it reaches the maximum *** datasets from UCI Machine Learning Repository are presented to certify the effectiveness in *** sequences got from a 300 MW boiler are then taken for case *** result of the pressure sequence case study with an error rate of 0.5332%shows the valuable information on boiler’s load and pressure sequence in *** relationship between boiler’s load and entropy values extracted from pressure sequence is ***,the method can be considered to be a reference method for data mining in other fluctuating and time-varying sequences.

关键词： furnace pressure sequence entropy validity index fuzzy c-means analysis method based on weighted validity index

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Glycoside-specific metabolomics combined with precursor isotopic labeling for characterizing plant glycosyltransferases

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Molecular Plant 2022年第10期15卷 1517-1532页

作者： Jie Wu Wentao Zhu Xiaotong Shan Jinyue Liu lingling zhao Qiao zhao Shenzhen Key Laboratory of Synthetic Genomics Guangdong Provincial Key Laboratory of Synthetic GenomicsCAS Key Laboratory of Quantitative Engineering BiologyShenzhen Institute of Synthetic BiologyShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Innovation Center of Pesticide Research Department of Applied ChemistryCollege of ScienceChina Agricultural UniversityBeijing 100193China Center for Plant Biology School of Life SciencesTsinghua UniversityBeijing 100084China

Glycosylation by uridine diphosphate-dependent glycosyltransferases(UGTs)in plants contributes to the complexity and diversity of secondary *** are generally promiscuous in their use of acceptors,making it challenging to reveal the function of UGTs in ***,we described an approach that combined glycoside-specific metabolomics and precursor isotopic labeling analysis to characterize UGTs in *** revisited the UGT72E cluster,which has been reported to catalyze the glycosylation of ***-specific metabolomics analysis reduced the number of differentially accumulated metabolites in the ugt72e1e2e3 mutant by at least 90%compared with that from traditional untargeted metabolomics *** addition to the two previously reported monolignol glycosides,a total of 62 glycosides showed reduced accumulation in the ugt72e1e2e3 mutant,22 of which were phenylalanine-derived glycosides,including 5-OH coniferyl alcohol-derived and lignan-derived glycosides,as confirmed by isotopic tracing of[^(13)C_(6)]-phenylalanine *** method revealed that UGT72Es could use coumarins as substrates,and genetic evidence showed that UGT72Es endowed plants with enhanced tolerance to low iron availability under alkaline *** the newly developed method,the function of UGT78D2 was also *** case studies suggest that this method can substantially contribute to the characterization of UGTs and efficiently investigate glycosylation processes,the complexity of which have been highly underestimated.

关键词： glycosyltransferases glycosides-specific metabolomics precursor isotopic labeling glucoside Arabidopsis thaliana phenylpropanoid coumarins

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Pedestrian wind flow prediction using spatial-frequency generative adversarial network

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Building Simulation 2024年第2期17卷 319-334页

作者： Pengyue Wang Maozu Guo Yingeng Cao Shimeng Hao Xiaoping Zhou lingling zhao School of Architecture and Urban Planning Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China

Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban *** pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical *** learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind ***,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow *** study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow *** the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial *** information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency *** spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced *** results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,*** also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind *** reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding *** enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind *** proposed spatial-frequen

关键词： pedestrian wind flow prediction generative adversarial network Gaussian kernel wavelet transform objective function

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High performance solid-state thermoelectric energy conversion via inorganic metal halide perovskites under tailored mechanical deformation

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Frontiers in Energy 2022年第4期16卷 581-594页

作者： Lifu YAN lingling zhao Guiting YANG Shichao LIU Yang LIU Shangchao LIN National Engineering Research Center of Turbo-Generator Vibration School of Energy and EnvironmentSoutheast UniversityNanjing 210096China State Key Laboratory of Space Power-Sources Technology Shanghai Institute of Space Power-SourcesShanghai 200245China Key Laboratory for Power Machinery and Engineering of the Ministry of Education School of Mechanical EngineeringShanghai Jiao Tong UniversityShanghai 200240China

Solid-state thermoelectric energy conversion devices attract broad research interests because of their great promises in waste heat recycling,space power generation,deep water power generation,and temperature control,but the search for essential thermoelectric materials with high performance still remains a great *** an emerging low cost,solution-processed thermoelectric material,inorganic metal halide perovskites CsPb(I_(1–x)Br_(x))_(3) under mechanical deformation is systematically investigated using the first-principle calculations and the Boltzmann transport *** is demonstrated that halogen mixing and mechanical deformation are efficient methods to tailor electronic structures and charge transport properties in CsPb(I_(1–x)Br_(x))_(3) *** mixing leads to band splitting and anisotropic charge transport due to symmetry-breakinginduced intrinsic *** band splitting reconstructs the band edge and can decrease the charge carrier effective mass,leading to excellent charge transport *** deformation can further push the orbital energies apart from each other in a more controllable manner,surpassing the impact from intrinsic *** anisotropic charge transport properties and ZT values are sensitive to the direction and magnitude of strain,showing a wide range of variation from 20%to 400%(with a ZT value of up to 1.85)compared with unstrained *** power generation efficiency of the thermoelectric device can reach as high as approximately 12%using mixed halide perovskites under tailored mechanical deformation when the heat-source is at 500 K and the cold side is maintained at 300 K,surpassing the performance of many existing bulk thermoelectric materials.

关键词： inorganic metal halide perovskites mechanical deformation thermoelectrics first-principle calculations Boltzmann transport theory

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UAV Online Path Planning Algorithm in a Low Altitude Dangerous Environment

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IEEE/CAA Journal of Automatica Sinica 2015年第2期2卷 173-185页

作者： Naifeng Wen lingling zhao Xiaohong Su Peijun Ma School of Computer Science and Technology Harbin Institute of Technology

UAV online path-planning in a low altitude dangerous environment with dense obstacles, static threats (STs) and dynamic threats (DTs), is a complicated, dynamic, uncertain and real-time problem. We propose a novel method to solve the problem to get a feasible and safe path. Firstly STs are modeled based on intuitionistic fuzzy set (IFS) to express the uncertainties in STs. The methods for ST assessment and synthesizing are presented. A reachability set (RS) estimator of DT is developed based on rapidly-exploring random tree (RRT) to predict the threat of DT. Secondly a subgoal selector is proposed and integrated into the planning system to decrease the cost of planning, accelerate the path searching and reduce threats on a path. Receding horizon (RH) is introduced to solve the online path planning problem in a dynamic and partially unknown environment. A local path planner is constructed by improving dynamic domain rapidly-exploring random tree (DDRRT) to deal with complex obstacles. RRT∗ is embedded into the planner to optimize paths. The results of Monte Carlo simulation comparing the traditional methods prove that our algorithm behaves well on online path planning with high successful penetration probability. © 2014 Chinese Association of Automation.

关键词： Algorithms Forestry Fuzzy sets Intelligent systems Monte Carlo methods Problem solving Social networking (online)

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Tailored morphology and highly enhanced phonon transport in polymer fibers:a multiscale computational framework

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npj Computational Materials 2019年第1期5卷 36-47页

作者： Shangchao Lin Zhuangli Cai Yang Wang lingling zhao Chenxi Zhai Institute of Engineering Thermophysics School of Mechanical and Power EngineeringShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjingJiangsu 210096China Department of Mechanical Engineering FAMU-FSU College of EngineeringFlorida State UniversityTallahasseeFL 32310USA

Although tremendous efforts have been devoted to enhance thermal conductivity in polymer fibers,correlation between the thermal-drawing conditions and the resulting chain alignment,crystallinity,and phonon transport properties have remained *** a carefully trained coarse-grained force field,we systematically interrogate the thermal-drawing conditions of bulk polyethylene samples using large-scale molecular dynamics *** optimal combination of moderate drawing temperature and strain rate is found to achieve highest degrees of chain alignment,crystallinity,and the resulting thermal *** combination is rationalized by competing effects in viscoelastic relaxation and condensed to the Deborah number,a predictive metric for the thermal-drawing protocols,showing a delicate balance between stress localizations and chain *** tensile deformation,the thermal conductivity of amorphous polyethylene is enhanced to 80% of the theoretical limit,that is,its pure crystalline *** effective-medium-theory model,based on the serial-parallel heat conducting nature of semicrystalline polymers,is developed here to predict the impacts from both chain alignment and crystallinity on thermal *** enhancement in thermal conductivity is mainly attributed to the increases in the intrinsic phonon mean free path and the longitudinal group *** work provides fundamental insights into the polymer thermal-drawing process and establishes a complete process–structure–property relationship for enhanced phonon transport in all-organic electronic devices and efficiency of polymeric heat dissipaters.

关键词： fibers transport phonon

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A MLP-Mixer and mixture of expert model for remaining useful life prediction of lithium-ion batteries

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Frontiers of Computer Science 2024年第5期18卷 1-10页

作者： lingling zhao Shitao SONG Pengyan WANG Chunyu WANG Junjie WANG Maozu GUO Faculty of Computing Harbin Institute of TechnologyHarbin 150001China School of Electrical Engineering Liaoning University of TechnologyJinzhou 121004China School of Computer Science Northeast Electric Power UniversityJilin 132000China Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China

Accurately predicting the Remaining Useful Life(RUL)of lithium-ion batteries is crucial for battery management *** learning-based methods have been shown to be effective in predicting RUL by leveraging battery capacity time series ***,the representation learning of features such as long-distance sequence dependencies and mutations in capacity time series still needs to be *** address this challenge,this paper proposes a novel deep learning model,the MLP-Mixer and Mixture of Expert(MMMe)model,for RUL *** MMMe model leverages the Gated Recurrent Unit and Multi-Head Attention mechanism to encode the sequential data of battery capacity to capture the temporal features and a re-zero MLP-Mixer model to capture the high-level ***,we devise an ensemble predictor based on a Mixture-of-Experts(MoE)architecture to generate reliable RUL *** experimental results on public datasets demonstrate that our proposed model significantly outperforms other existing methods,providing more reliable and precise RUL predictions while also accurately tracking the capacity degradation *** code and dataset are available at the website of github.

关键词： lithium-ion battery remaining useful life deep learning MLP-Mixer mixture-of-experts

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