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Learning Discriminatory Information for Object Detection on Urine Sediment Image

工程与科学中的计算机建模(英文) 2024年第1期138卷 411-428页

作者： Sixian Chan Binghui Wu Guodao Zhang Yuan Yao hongqiang wang College of Computer Science and Technology Zhejiang University of TechnologyHangzhou310023China The Hefei Institutes of Physical Science Chinese Academy of SciencesHefei230071China Department of Digital Media Technology Hangzhou Dianzi UniversityHangzhou310018China School of Computer Science University of Nottingham Ningbo ChinaNingbo315100China

In clinical practice,the microscopic examination of urine sediment is considered an important in vitro examination with many broad applications.Measuring the amount of each type of urine sediment allows for screening,diagnosis and evaluation of kidney and urinary tract disease,providing insight into the specific type and severity.However,manual urine sediment examination is labor-intensive,time-consuming,and subjective.Traditional machine learning based object detection methods require hand-crafted features for localization and classification,which have poor generalization capabilities and are difficult to quickly and accurately detect the number of urine sediments.Deep learning based object detection methods have the potential to address the challenges mentioned above,but these methods require access to large urine sediment image datasets.Unfortunately,only a limited number of publicly available urine sediment datasets are currently available.To alleviate the lack of urine sediment datasets in medical image analysis,we propose a new dataset named UriSed2K,which contains 2465 high-quality images annotated with expert guidance.Two main challenges are associated with our dataset:a large number of small objects and the occlusion between these small objects.Our manuscript focuses on applying deep learning object detection methods to the urine sediment dataset and addressing the challenges presented by this dataset.Specifically,our goal is to improve the accuracy and efficiency of the detection algorithm and,in doing so,provide medical professionals with an automatic detector that saves time and effort.We propose an improved lightweight one-stage object detection algorithm called Discriminatory-YOLO.The proposed algorithm comprises a local context attention module and a global background suppression module,which aid the detector in distinguishing urine sediment features in the image.The local context attention module captures context information beyond the object region,while the global background suppression module e

关键词： Object detection attention mechanism medical image urine sediment

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Comparative evaluation of SPE methods for biotoxicity assessment of water and wastewater:Linkage between chemical extracting efficiency and biotoxicity outcome

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Journal of Environmental Sciences 2024年第8期142卷 33-42页

作者： Jiawei Zhou Shihao wang Xiwei He hongqiang Ren Xu-Xiang Zhang State Key Laboratory of Pollution Control and Resource Reuse School of EnvironmentNanjing UniversityNanjing 210023China

Biotoxicity assessment results of environmental waters largely depend on the sample extraction protocols that enrich pollutants to meet the effect-trigger thresholds of bioassays.However,more chemical mixture does not necessarily translate to higher combined biotoxicity.Thus,there is a need to establish the link between chemical extracting efficiency and biotoxicity outcome to standardize extraction methods for biotoxicity assessment of environmental waters.This study compares the performance of five different extraction phases in solid phase extraction(SPE),namely HLB,HLB+Coconut,C18 cartridge,C18 disk and Strata-X,and evaluated their chemical extracting efficiencies and biotoxicity outcomes.We quantitatively assessed cytotoxicity,acute toxicity,genotoxicity,estrogenic activity,and neurotoxicity of the extracts using in vitro bioassays and characterized the chemical extracting efficiencies of the SPE methods through chemical recoveries of 23 model compounds with different polarities and total organic carbon.Using Pareto ranking,we identified HLB+Coconut as the optimal SPE method,which exhibited the highest level of water sample biotoxicity and recovered the most chemicals in water samples.We found that the biotoxicity outcomes of the extracted water samples significantly and positively correlated with the chemical extracting efficiencies of the SPE methods.Moreover,we observed synchronous changing patterns in biotoxicity outcome and chemical extracting efficiencies in response to increasing sample volumes per cartridge(SVPC)during SPE.Our findings underscore that higher chemical extracting efficiency of SPE corresponds to higher biotoxicity outcome of environmental water samples,providing a scientific basis for standardization of SPE methods for adequate assessment of biotoxicities of environmental waters.

关键词： Biotoxicity Chemical recovery Solid phase extraction Surface water Wastewater

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极端干旱与食草昆虫对草原群落的交互作用受干旱模式的影响

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Journal of Plant Ecology 2024年第3期17卷 128-140页

作者： Ye Luo Yuguang Ke hongqiang wang Chong Xu Qian Gu Qiang Yu Melinda D.Smith Rajabboy Madrimov Nuriddin Samatov Wei Yang Honghui Wu State Key Laboratory of Effcient Utilization of Arid and Semi-arid Arable Land in Northern China Institute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China Key Laboratory of Arable Land Quality Monitoring and Evaluation Ministry of Agriculture and Rural AffairsInstitute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China School of Grassland Science Beijing Forestry UniversityBeijing 100083China Department of Biology and Graduate Degree Program in Ecology Colorado State UniversityFort CollinsCO 80523USA Research Institute of Environment and Nature Conservation Technologies of the Ministry of Ecology Environmental Protectionand Climate Change of the Republic of UzbekistanTashkent 100043Uzbekistan Institute of Microbiology of the Academy of Sciences Tashkent 100128Uzbekistan Institute of Environment and Sustainable Development in Agriculture Chinese Academy of Agricultural SciencesBeijing 100081China

极端干旱和食草昆虫可以共同影响植物群落,并且它们的交互作用可能受到干旱模式的影响。然而,目前尚缺乏相关的观测证据。本研究以半干旱草原为研究对象,通过控制实验探讨了不同极端干旱模式与食草昆虫的交互作用对植物群落的影响。实... 详细信息

极端干旱和食草昆虫可以共同影响植物群落,并且它们的交互作用可能受到干旱模式的影响。然而,目前尚缺乏相关的观测证据。本研究以半干旱草原为研究对象,通过控制实验探讨了不同极端干旱模式与食草昆虫的交互作用对植物群落的影响。实验设置了3种干旱处理,分别为对照(自然降雨量)、慢性干旱(生长季5–8月减少66%降雨量)和急性干旱(6–7月完全无降雨)。在各小区设置了两种食草昆虫处理,分别是有食草昆虫和无食草昆虫。结果表明,食草昆虫和极端干旱及二者的交互作用对物种丰富度无显著影响。食草昆虫缓解了慢性干旱对总盖度的负面影响,而这种缓解作用在急性干旱下较低。食草昆虫对慢性干旱带来的负面效应具有更强的缓解作用,这主要是因为食草昆虫导致慢性干旱下适口性较高的杂类草(具有较低叶片碳含量、叶片干物质含量,以及较低叶片淀粉、钙、镁、锰含量)的大幅降低,进而降低了禾草的负面效应。上述结果表明,干旱和食草昆虫的交互作用受干旱模式的影响。通过调节植物的适口性来控制食草昆虫的采食行为,可以减轻极端干旱对草原生态系统的影响。

关键词：急性干旱慢性干旱半干旱草原食草昆虫极端气候

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Multiscale Characteristics and Connection Mechanisms of Attraction Networks:A Trajectory Data Mining Approach Leveraging Geotagged Data

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Chinese Geographical Science 2024年第3期34卷 533-547页

作者： JIANG hongqiang WEI Ye MEI Lin wang Zhaobo School of Resource and Environment Engineering Ludong UniversityYantai 264025China School of Geographical Sciences Northeast Normal UniversityChangchun 130024China Changchun University of Finance and Economics Changchun 130122China Jilin Jizhi City Architectural Design Co. LTDChangchun 130012China

Urban tourism is considered a complex system,and multiscale exploration of the organizational patterns of attraction networks has become a topical issue in urban tourism,so exploring the multiscale characteristics and connection mechanisms of attraction networks is important for understanding the linkages between attractions and even the future destination planning.This paper uses geotagging data to compare the links between attractions in Beijing,China during four different periods:the pre-Olympic period(2004–2007),the Olympic Games and subsequent‘heat period’(2008–2013),the post-Olympic period(2014–2019),and the COVID-19(Corona Virus Disease 2019)pandemic period(2020–2021).The aim is to better understand the evolution and patterns of attraction networks at different scales in Beijing and to provide insights for tourism planning in the destination.The results show that the macro,meso-,and microscales network characteristics of attraction networks have inherent logical relationships that can explain the commonalities and differences in the development process of tourism networks.The macroscale attraction network degree Matthew effect is significant in the four different periods and exhibits a morphological monocentric structure,suggesting that new entrants are more likely to be associated with attractions that already have high value.The mesoscale links attractions according to the common purpose of tourists,and the results of the community segmentation of the attraction networks in the four different periods suggest that the functional polycentric structure describes their clustering effect,and the weak links between clusters result from attractions bound by incomplete information and distance,and the functional polycentric structure with a generally more efficient network of clusters.The pattern structure at the microscale reveals the topological transformation relationship of the regional collaboration pattern,and the attraction network structure in the four different periods has a very similar importance prof

关键词： attraction network travel mobility polycentric structure network motif connectivity mechanism destination management organization(DMO) destination planning Beijing,China

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Three-dimensionally ordered macroporous(3DOM) structure promoted the activity and H_(2)O poisoning resistance of Ce Mn/3DOM-TiO_(2) catalyst in NH_(3)-SCR

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Journal of Rare Earths 2024年第3期42卷 523-533,I0004页

作者： Yaqin Hu Shipeng Ding Chenchen Tan Peng Wu Guobo Li Sheng wang hongqiang Yang Yaping Zhang Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education School of Energy and EnvironmentSoutheast UniversityNanjing210096China State Power Environmental Protection Research Institute Nanjing210031China

NH_(3)-SCR is an effective mean of NOxremoval in the non-electric industry, however, the high activation temperature and poor H_(2)O resistance of SCR catalysts posed a barrier to its application. In this work, a series of three-dimensionally ordered macroporous(3DOM) catalysts were synthesized via a colloidal crystal template(CCT) method, and various characterizations were carried out to explore the physicochemical property of catalysts. The experiment results reveal that Ce_(0.2)Mn_(0.2)/3DOM-TiO_(2) catalyst presents the excellent low-temperature catalytic activity of nearly 100% at 100℃. Furthermore, the enhanced H_(2)O resistance is achieved, certified by the unaffected NO remove at 150℃ in the participation of 15 vol% H_(2)O. The characterizations results exhibit that the improved dispersion of the active component and enhanced redox ability are conducive to the low-temperature catalytic activity. N_(2) adsorption and desorption experiments indicate that catalyst with 3DOM support possesses a larger pore diameter and specific surface area, which may weaken the condensation of H_(2)O in the microporosity of catalysts and improved the H_(2)O resistance of the catalyst. In situ DRIFTS results manifest that Ce_(0.2)Mn_(0.2)/3DOM-TiO_(2) catalyst could not only absorb more NH_(3) and generate more surface-active sites, but inhibit the competitive adsorption between H_(2)O and SCR reactants.

关键词： 3DOM material NH_(3)-SCR H_(2)O resistance Low-temperature Cerium Rare earths

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Rational Design of High-Performance PEO/Ceramic Composite Solid Electrolytes for Lithium Metal Batteries

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Nano-Micro Letters 2023年第6期15卷 155-189页

作者： Yanxia Su Fei Xu Xinren Zhang Yuqian Qiu hongqiang wang State Key Laboratory of Solidification Processing Centre for Nano Energy MaterialsSchool of Materials Science and EngineeringNorthwestern Polytechnical UniversityShaanxi Joint Laboratory of Graphene(NPU)Xi’an 710072People’s Republic of China

Composite solid electrolytes(CSEs)with poly(ethylene oxide)(PEO)have become fairly prevalent for fabricating high-performance solid-state lithium metal batteries due to their high Li~+solvating capability,flexible processability and low cost.However,unsatisfactory room-temperature ionic conductivity,weak interfacial compatibility and uncontrollable Li dendrite growth seriously hinder their progress.Enormous efforts have been devoted to combining PEO with ceramics either as fillers or major matrix with the rational design of two-phase architecture,spatial distribution and content,which is anticipated to hold the key to increasing ionic conductivity and resolving interfacial compatibility within CSEs and between CSEs/electrodes.Unfortunately,a comprehensive review exclusively discussing the design,preparation and application of PEO/ceramic-based CSEs is largely lacking,in spite of tremendous reviews dealing with a broad spectrum of polymers and ceramics.Consequently,this review targets recent advances in PEO/ceramicbased CSEs,starting with a brief introduction,followed by their ionic conduction mechanism,preparation methods,and then an emphasis on resolving ionic conductivity and interfacial compatibility.Afterward,their applications in solid-state lithium metal batteries with transition metal oxides and sulfur cathodes are summarized.Finally,a summary and outlook on existing challenges and future research directions are proposed.

关键词： Composite solid electrolytes Ionic conductivity Interfacial compatibility Ion conduction pathways Li metal batteries

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Pluggable multitask diffractive neural networks based on cascaded metasurfaces

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Opto-Electronic Advances 2024年第2期7卷 23-31页

作者： Cong He Dan Zhao Fei Fan hongqiang Zhou Xin Li Yao Li Junjie Li Fei Dong Yin-Xiao Miao Yongtian wang Lingling Huang Beijing Engineering Research Center of Mixed Reality and Advanced Display Key Laboratory of Photoelectronic Imaging Technology and System of Ministry of Education of ChinaSchool of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China Institute of Modern Optics Tianjin Key Laboratory of Optoelectronic Sensor and Sensing Network TechnologyNankai UniversityTianjin 300350China Department of Physics and Optoelectronics Faculty of ScienceBeijing University of TechnologyBeijing 100124China Beijing National Laboratory for Condensed Matter Physics Institute of PhysicsChinese Academy of SciencesBeijing 100191China Beijing Aerospace Institute for Metrology and Measurement Technology Beijing 100076China

Optical neural networks have significant advantages in terms of power consumption,parallelism,and high computing speed,which has intrigued extensive attention in both academic and engineering communities.It has been considered as one of the powerful tools in promoting the fields of imaging processing and object recognition.However,the existing optical system architecture cannot be reconstructed to the realization of multi-functional artificial intelligence systems simultaneously.To push the development of this issue,we propose the pluggable diffractive neural networks(P-DNN),a general paradigm resorting to the cascaded metasurfaces,which can be applied to recognize various tasks by switching internal plug-ins.As the proof-of-principle,the recognition functions of six types of handwritten digits and six types of fashions are numerical simulated and experimental demonstrated at near-infrared regimes.Encouragingly,the proposed paradigm not only improves the flexibility of the optical neural networks but paves the new route for achieving high-speed,low-power and versatile artificial intelligence systems.

关键词： optical neural networks diffractive deep neural networks cascaded metasurfaces

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Exploring device physics of perovskite solar cell via machine learning with limited samples

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Journal of Energy Chemistry 2024年第7期94卷 441-448页

作者： Shanshan Zhao Jie wang Zhongli Guo hongqiang Luo Lihua Lu Yuanyuan Tian Zhuoying Jiang Jing Zhang Mengyu Chen Lin Li Cheng Li School of Electronic Science and Engineering Xiamen UniversityXiamen 361005FujianChina Future Display Institute of Xiamen Xiamen 361005FujianChina

Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.

关键词： Perovskite solar cell Machine learning Device physics Performance prediction Limited samples

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Laser-Derived Interfacial Confinement Enables Planar Growth of 2D SnS_(2) on Graphene for High-Flux Electron/Ion Bridging in Sodium Storage

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Nano-Micro Letters 2022年第6期14卷 65-80页

作者： Xiaosa Xu Fei Xu Xiuhai Zhang Changzhen Qu Jinbo Zhang Yuqian Qiu Rong Zhuang hongqiang wang State Key Laboratory of Solidification Processing Centre for Nano Energy MaterialsSchool of Materials Science and EngineeringNorthwestern Polytechnical UniversityShaanxi Joint Laboratory of Graphene(NPU)Xi’an 710072People’s Republic of China

Establishing covalent heterointerfaces with face-to-face contact is promising for advanced energy storage,while challenge remains on how to inhibit the anisotropic growth of nucleated crystals on the matrix.Herein,faceto-face covalent bridging in-between the 2 D-nanosheets/graphene heterostructure is constructed by intentionally prebonding of laser-manufactured amorphous and metastable nanoparticles on graphene,where the amorphous nanoparticles were designed via the competitive oxidation of Sn-O and Sn-S bonds,and metastable feature was employed to facilitate the formation of the C-S-Sn covalent bonding in-between the heterostructure.The face-to-face bridging of ultrathin SnS;nanosheets on graphene enables the heterostructure huge covalent coupling area and high loading and thus renders unimpeded electron/ion transfer pathways and indestructible electrode structure,and impressive reversible capacity and rate capability for sodium-ion batteries,which rank among the top in records of the SnS_(2)-based anodes.Present work thus provides an alternative of constructing heterostructures with planar interfaces for electrochemical energy storage and even beyond.

关键词： Laser-manufacturing Metastable Interfacial engineering Covalent bridging Na-storage

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Construction of internal electric field to suppress oxygen evolution of Ni-rich cathode materials at a high cutoff voltage

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Journal of Energy Chemistry 2022年第10期31卷 114-125,I0004页

作者： Youqi Chu Anjie Lai Qichang Pan Fenghua Zheng Youguo Huang hongqiang wang Qingyu Li Guangxi Key Laboratory of Low Carbon Energy Materials School of Chemistry and Pharmaceutical SciencesGuangxi Normal UniversityGuilin 541004GuangxiChina Guangxi New Energy Ship Battery Engineering Technology Research Center Guangxi Normal UniversityGuilin 541004GuangxiChina

The Nickel-rich layered cathode materials have been considered as promising cathode for lithium-ion batteries(LIBs),which due to it can achieve a high capacity of than 200 mAh g^(-1)under a high cutoff voltage of4.5 V.However,the nickel-rich layered cathode materials show severely capacity fading at high voltage cycling,induced by the hybrid O anion and cation redox promote O^(α-)(α<2)migration in the crystal lattice under high charge voltage,lead to the instability of the oxygen skeleton and oxygen evolution,promote the phase transition and electrolyte decomposition.Here,Li_(1-x)TMO_(2-y)/Li_(2)SO_(4) hybrid layer is designed by a simple pyrolysis method to enhance the high voltage cycle stability of NCM.In such constructed hybrid layer,the inner spinel structure of Li_(1-x)TMO_(2-y)layer is the electron-rich state,which could form an electron cloud coupling with the NCM with surface oxygen vacancies,while Li_(2)SO_(4) is p-type semiconductors,thus constructing a heterojunction interface of Li_(1-x)TMO_(2-y)//Li_(2)SO_(4) and Li_(1-x)TMO_(2-y)//NCM,thereby generating internal self-built electric fields to inhibit the outward migration of bulk oxygen anions.Moreover,the internal self-built electric fields could not only strengthen the bonding force between the Li_(1-x)TMO_(2-y)/Li_(2)SO_(4) hybrid layer and host NCM material,but also boost the charge transfer.As consequence,the modified NCM materials show excellent electrochemical performance with capacity retention of 97.7%and 90.1%after 200 cycles at 4.3 V and 4.5 V,respectively.This work provides a new idea for the development of high energy density applications of Nickel-rich layered cathode materials.

关键词： Ni-rich layered oxide Li_(1-x)TMO_(2-y)/Li_(2)SO_(4) Dual-modified Electrochemical performance

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