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Surface-adaptive interfaces:Bioresorbable ultrasound biomedical devices for noninvasive monitoring and imaging of deep-tissue homeostasis

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The Innovation 2024年第4期5卷 19-20页

作者： Jiyu Li Yingying zhou Xiazi huang Puxiang Lai Yuan huang department of Biomedical Engineering City University of Hong KongHong Kong SARChina The Hong Kong Polytechnic university Shenzhen Research Institute Shenzhen 999077China College of Professional and Continuing Education The Hong Kong Polytechnic UniversityHong Kong SARChina Photonics Research Institute The Hong Kong Polytechnic UniversityHong Kong SARChina Cardiac Surgery Centre Fuwai HospitalNational Center for Cardiovascular DiseasesChinese Academy of Medical SciencesPeking Union Medical CollegeBeijing 100037China

Homeostasis,a self-regulating process within our bodies,dynamically adjusts internal conditions to maintain equilibrium in response to external *** homeostasis provides valuable pathophysiological insights for patients,particularly after surgery,while traditional clinical instruments that are capable of monitoring various physiological parameters such as body temperature,blood pressure,and blood glucose levels facilitate real-time health management for individuals and healthcare professionals.1 Nevertheless,current medical approaches for regular deep-tissue homeostasis monitoring systems confront critical obstacles,notably in terms of their invasiveness,sensitivity,and ability for continuous monitoring,including1(1)insufficiency in multimodal sensing capability at shallow depths,(2)inadequate adaptation to the shapes and contours of tissues,and(3)sluggish responses to changes in the fluid dynamics and movements of organs or ***,technologies like X-ray imaging,computed tomography,and biopsies,for instance,are generally cumbersome,expensive,and impractical for ongoing and real-time ***,for the aforementioned techniques,a lack of sensitivity for detecting early changes in tissue homeostasis or the aptitude for efficiently tracking patient health status post-surgery is generally observed.

关键词： homeostasis maintain mentioned

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Effects of the inlet particle spatial distribution on the performance of a gas-solid cyclone separator

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Particuology 2024年第2期85卷 133-145页

作者： Yuge Yao Manxia Shang Xiwei Ke Zhong huang Tuo zhou Junfu Lyu Key Laboratory for Thermal Science and Power Engineering of Ministry of Education Department of Energy and Power EngineeringTsinghua UniversityBeijing100084China

The present study was aimed at the inlet particle spatial distribution of a gas-solid separator with high solid loading and investigated its effects on cyclone performance and the inner flow *** flow fields of a cyclone with different rectangular particle flow areas on the inlet surface were numerically simulated using a four-way coupling *** simulated results indicate that reducing the inlet particle flow area and lowing the inlet particle position can effectively reduce the scattered particles inside the cyclone separator and enhance the separation *** gathering the particles to the centerline can also weaken the particle *** particles near the roof account for the swirling particle ceiling *** inlet particle spatial distribution affects the pressure drop mainly by affecting the gas tangential velocity in the cylinder ***,compared to the hori-zontal particle distribution on the inlet surface,the vertical particle distribution has greater effects on cyclone performance.

关键词： Gas-solid cyclone Inlet particle spatial distribution Four-way coupling Separation efficiency Scattered particle

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Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

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International Journal of Mining Science and Technology 2024年第3期34卷 323-337页

作者： Hongwei huang Chen Wu Mingliang zhou Jiayao Chen Tianze Han Le Zhang Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji UniversityShanghai 200092China department of Geotechnical Engineering Tongji UniversityShanghai 200092China School of Civil Engineering Beijing Jiaotong UniversityBeijing 100044China Qingdao Guoxin Second Jiaozhou Bay Subsea Tunnel Co. Ltd.Qingdao 266071China

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel *** tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative ***,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality *** this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak *** site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is *** the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete *** utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

关键词： Rock mass quality Tunnel faces Incomplete multi-source dataset Improved Swin Transformer Bayesian networks

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High-performance formaldehyde prediction for indoor air quality assessment using time series deep learning

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Building Simulation 2024年第3期17卷 415-429页

作者： Liu Lu Xinyu huang Xiaojun zhou Junfei Guo Xiaohu Yang Jinyue Yan School of Human Settlements and Civil Engineering Xi’an Jiaotong UniversityXi’anChina department of Building Environment and Energy Engineering The Hong Kong Polytechnic UniversityKowloonHong KongChina Future Energy Profile School of BusinessSocietyand EngineeringMälardalen UniversityVästeråsSweden

Indoor air pollution resulting from volatile organic compounds(VOCs),especially formaldehyde,is a significant health concern needed to predict indoor formaldehyde concentration(Cf)in green intelligent building *** study develops a thermal and wet coupling calculation model of porous fabric to account for the migration of formaldehyde molecules in indoor air and cotton,silk,and polyester fabric with heat flux in Harbin,Beijing,Xi’an,Shanghai,Guangzhou,and Kunming,*** time-by-time indoor dry-bulb temperature(T),relative humidity(RH),and Cf,obtained from verified simulations,were collated and used as input data for the long short-term memory(LSTM)of the deep learning model that predicts indoor multivariate time series Cf from the secondary source effects of indoor fabrics(adsorption and release of formaldehyde).The trained LSTM model can be used to predict multivariate time series Cf at other emission times and *** LSTM-based model also predicted Cf with mean absolute percentage error(MAPE),symmetric mean absolute percentage error(SMAPE),mean absolute error(MAE),mean square error(MSE),and root mean square error(RMSE)that fell within 10%,10%,0.5,0.5,and 0.8,*** addition,the characteristics of the input dataset,model parameters,the prediction accuracy of different indoor fabrics,and the uncertainty of the data set are *** results show that the prediction accuracy of single data set input is higher than that of temperature and humidity input,and the prediction accuracy of LSTM is better than recurrent neural network(RNN).The method’s feasibility was established,and the study provides theoretical support for guiding indoor air pollution control measures and ensuring human health and safety.

关键词： multivariate time series formaldehyde concentration deep learning heat-humidity coupling mass transfer secondary source effect

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Properties of a family of merit functions and a merit function method for the NCP

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Applied Mathematics(A Journal of Chinese Universities) 2010年第4期25卷 379-390页

作者： LU Li-yong huang Zheng-hai HU Sheng-long department of Mathematics, School of Science, tianjin university, tianjin 300072, china department of Mathematics School of Science Tianjin University Tianjin China

A family of merit functions are proposed, which are the generalization of several existing merit functions. A number of favorable properties of the proposed merit functions are established. By using these properties, a merit function method for solving nonlinear complementarity problem is investigated, and the global convergence of the proposed algorithm is proved under some standard assumptions. Some preliminary numerical results are given.

关键词： Nonlinear complementarity problem NCP-function merit function merit function method.

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A proteomic landscape of pharmacologic perturbations for functional relevance

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Journal of Pharmaceutical Analysis 2024年第1期14卷 128-139页

作者： Zhiwei Liu Shangwen Jiang Bingbing Hao Shuyu Xie Yingluo Liu Yuqi huang heng Xu Cheng Luo Min huang Minjia Tan Jun-Yu Xu State Key Laboratory of Drug Research Shanghai Institute of Materia MedicaChinese Academy of SciencesShanghai201203China School of Chinese Materia Medica Nanjing University of Chinese MedicineNanjing210023China Zhongshan Institute for Drug Discovery Shanghai Institute of Materia MedicaChinese Academy of SciencesZhongshanGuangdong528400China State Key Laboratory of Pharmaceutical Biotechnology Nanjing UniversityNanjing210023China

Pharmacological perturbation studies based on protein-level signatures are fundamental for drug discovery. In the present study, we used a mass spectrometry (MS)-based proteomic platform to profile the whole proteome of the breast cancer MCF7 cell line under stress induced by 78 bioactive compounds. The integrated analysis of perturbed signal abundance revealed the connectivity between phenotypic behaviors and molecular features in cancer cells. Our data showed functional relevance in exploring the novel pharmacological activity of phenolic xanthohumol, as well as the noncanonical targets of clinically approved tamoxifen, lovastatin, and their derivatives. Furthermore, the rational design of synergistic inhibition using a combination of histone methyltransferase and topoisomerase was identified based on their complementary drug fingerprints. This study provides rich resources for the proteomic landscape of drug responses for precision therapeutic medicine.

关键词： Proteomics Drug Perturbation Drug target Drug combination

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Fluid identification and tight oil layer classification for the southwestern Mahu Sag,Junggar Basin using NMR logging-based spectrum decomposition

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Energy Geoscience 2024年第2期5卷 62-69页

作者： Wenbiao huang Yibing Guo Jun Qin Zhongchen Ba Zongbin Zhang Luning Bai heng Li School of Geosciences China University of Petroleum(East China)QingdaoShandong266580China Petrochina Xinjiang Oilfield Company KaramayXinjiang834000China

The intricate distribution of oil and water in tight rocks makes pinpointing oil layers *** conventional identification methods offer potential solutions,their limited accuracy precludes them from being effective in their applications to unconventional *** study employed nuclear magnetic resonance(NMR)spectrum decomposition to dissect the NMR T_(2)spectrum into multiple ***,it employed laboratory NMR experiments to ascertain the fluid properties of these sub-spectra,aiming to enhance identification *** findings indicate that fluids of distinct properties overlap in the T_(2)spectra,with bound water,movable water,bound oil,and movable oil appearing sequentially from the low-value zone to the high-value ***,an oil layer classification scheme was proposed,which considers the physical properties of reservoirs,oil-bearing capacity,and the characteristics of both mobility and the oil-water two-phase *** applied to tight oil layer identification,the scheme's outcomes align closely with actual test results.A horizontal well,deployed based on these findings,has produced high-yield industrial oil flow,underscoring the precision and dependability of this new approach.

关键词： Nuclear magnetic resonance Fluid identification Oil layer identification NMR T_(2)spectrum decomposition Normal distribution simulation

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Resonant Beam Communications:A New Design Paradigm and Challenges

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Journal of Communications and Information Networks 2024年第1期9卷 80-87页

作者： Yuanming Tian Dongxu Li Chuan huang Qingwen Liu Shengli zhou Future Network of Intelligence Institute and School of Science and Engineering the Chinese University of Hong KongShenzhen 518172China School of Science and Engineering and the Future Network of Intelligence Institute the Chinese University of Hong KongShenzhen 518172China College of Electronics and Information Engineering Tongji UniversityShanghai 201804China department of Electrical and Computer Engineering University of ConnecticutStorrsCT 06250USA

Resonant beam communications (RBCom), which adopts oscillating photons between two separate retroreflectors for information transmission, exhibits potential advantages over other types of wireless optical communications (WOC). However, echo interference generated by the modulated beam reflected from the receiver affects the transmission of the desired information. To tackle this challenge, a synchronization-based point-to-point RBCom system is proposed to eliminate the echo interference, and the design for the transmitter and receiver is discussed. Subsequently,the performance of the proposed RBCom is evaluated and compared with that of visible light communications(VLC)and free space optical communications (FOC). Finally, future research directions are outlined and several implementation challenges of RBCom systems are highlighted.

关键词： resonant beam communications(RBCom) wireless optical communications(WOC) echo interference elimination mobility multiple access

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Recent advances to address challenges in extracellular vesicle-based applications for lung cancer

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Acta Pharmaceutica Sinica B 2024年第9期14卷 3855-3875页

作者： Gaigai huang Wenshu Zheng Yu zhou Meihua Wan Tony Hu department of Clinical Laboratory the First People’s Hospital of Shuangliu District(West China Airport Hospital of Sichuan University)Chengdu 610200China Center for Cellular and Molecular Diagnostics Tulane University School of MedicineNew OrleansLA 70112USA department of Integrated Traditional Chinese and Western Medicine West China Hospital of Sichuan UniversityChengdu 610200China The First People’s Hospital of Shuangliu District(West china Airport Hospital of Sichuan university) Chengdu 610200China

Lung cancer,highly prevalent and the leading cause of cancer-related death globally,persists as a significant challenge due to the lack of definitive tumor markers for early diagnosis and personalized therapeutic ***,extracellular vesicles(EVs),functioning as natural carriers for intercellular communication,have received increasing attention due to their ability to traverse biological barriers and deliver diverse biological cargoes,including cytosolic proteins,cell surface proteins,microRNA,lncRNA,circRNA,DNA,and *** are increasingly recognized as a valuable resource for non-invasive liquid biopsy,as well as drug delivery platforms,and anticancer vaccines for precision medicine in lung ***,given the diagnostic and therapeutic potential of tumor-associated EVs for lung cancer,we discuss this topic from a translational *** delve into the specific roles that EVs play in lung cancer carcinogenesis and offer a particular perspective on how advanced engineering technologies can overcome the current challenges and expedite and/or enhance the translation of EVs from laboratory research to clinical settings.

关键词： Lung cancer Extracellular vesicles Therapy resistance Delivery Diagnostics Therapeutics Nanotechnology Engineering

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Deep learning-based lung sound analysis for intelligent stethoscope

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Military Medical Research 2024年第4期11卷 567-588页

作者： Dong-Min huang Jia huang Kun Qiao Nan-Shan Zhong Hong-zhou Lu Wen-Jin Wang department of Biomedical Engineering Southern University of Science and TechnologyShenzhen 518055GuangdongChina The Third People’s Hospital of Shenzhen Shenzhen 518112GuangdongChina Guangzhou Institute of Respiratory Health China State Key Laboratory of Respiratory DiseaseNational Clinical Research Center for Respiratory Diseasethe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510120China

Auscultation is crucial for the diagnosis of respiratory system ***,traditional stethoscopes have inherent limitations,such as inter-listener variability and subjectivity,and they cannot record respiratory sounds for offline/retrospective diagnosis or remote prescriptions in *** emergence of digital stethoscopes has overcome these limitations by allowing physicians to store and share respiratory sounds for consultation and *** this basis,machine learning,particularly deep learning,enables the fully-automatic analysis of lung sounds that may pave the way for intelligent *** review thus aims to provide a comprehensive overview of deep learning algorithms used for lung sound analysis to emphasize the significance of artificial intelligence(AI)in this *** focus on each component of deep learning-based lung sound analysis systems,including the task categories,public datasets,denoising methods,and,most importantly,existing deep learning methods,i.e.,the state-of-the-art approaches to convert lung sounds into two-dimensional(2D)spectrograms and use convolutional neural networks for the end-to-end recognition of respiratory diseases or abnormal lung ***,this review highlights current challenges in this field,including the variety of devices,noise sensitivity,and poor interpretability of deep *** address the poor reproducibility and variety of deep learning in this field,this review also provides a scalable and flexible open-source framework that aims to standardize the algorithmic workflow and provide a solid basis for replication and future extension:https://***/contactless-healthcare/Deep-Learning-for-Lung-Sound-Analysis.

关键词： Deep learning Lung sound analysis Respiratory sounds

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