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Detection of a temporal salient object benefits from visual stimulus-specific adaptation in avian midbrain inhibitory nucleus

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Integrative Zoology 2024年第2期19卷 288-306页

作者： Jiangtao WANG Xiaoping RAO Shuman HUANG Zhizhong WANG xiaoke niu Minjie ZHU Songwei WANG Li SHI Department of Automation Zhengzhou University School of Electrical EngineeringZhengzhouChina State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in WuhanKey Laboratory of Magnetic Resonance in Biological SystemsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhanChina Department of Automation Tsinghua UniversityBeijingChina

Food and predators are the most noteworthy objects for the basic survival of wild animals,and both are often deviant in both spatial and temporal domains and quickly attract an animal’s attention.Although stimulus-specific adaptation(SSA)is considered a potential neural basis of salient sound detection in the temporal domain,related research on visual SSA is limited and its relationship with temporal saliency is uncertain.The avian nucleus isthmi pars magnocellularis(Imc),which is central to midbrain selective attention network,is an ideal site to investigate the neural correlate of visual SSA and detection of a salient object in the time domain.Here,the constant order paradigm was applied to explore the visual SSA in the Imc of pigeons.The results showed that the firing rates of Imc neurons gradually decrease with repetitions of motion in the same direction,but recover when a motion in a deviant direction is presented,implying visual SSA to the direction of a moving object.Furthermore,enhanced response for an object moving in other directions that were not presented ever in the paradigm is also observed.To verify the neural mechanism underlying these phenomena,we introduced a neural computation model involving a recoverable synaptic change with a“center-surround”pattern to reproduce the visual SSA and temporal saliency for the moving object.These results suggest that the Imc produces visual SSA to motion direction,allowing temporal salient object detection,which may facilitate the detection of the sudden appearance of a predator.

关键词： adaptation attention model pigeon saliency

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Visual cognition of birds and its underlying neural mechanism:A review

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Avian Research 2022年第2期13卷 216-225页

作者： xiaoke niu Zhenyang Jiang Yanyan Peng Shuman Huang Zhizhong Wang Li Shi Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology School of Electrical EngineeringZhengzhou UniversityZhengzhou450001China Department of Automation Tsinghua UniversityBeijing100084China

Birds have acute vision and many remarkable visual cognition abilities,due to their unique living environment.The underlying neural mechanisms have also attracted interests of researchers in neuroscience.Here,we firstly summarize the visual cognition abilities of birds,and make a comparison with mammals.Secondly,the underlying neural mechanisms are presented,including histological structure of avian brain and visual pathways,typical experimental results and conclusions in electrochemistry and electrophysiology.The latter mainly focuses on several higher brain areas related to visual cognition,including mesopallium ventrolaterale,entopallium,visual Wulst,and nidopallium caudolaterale.Finally,we make a conclusion and provide a suggestion about future studies on revealing the neural mechanisms of avian visual cognition.This review presents a detailed understanding of avian visual cognition and would be helpful in ornithology studies in the field of cognitive neuroscience.

关键词： neural Visual cognition

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以高产优质稳产为目标的‘徐香’猕猴桃不同生长期叶片营养诊断研究

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园艺学报 2024年第6期51卷 1345-1360页

作者：董晓珂陈元磊牛友怡刘占德王南南西北农林科技大学园艺学院陕西杨凌712100

在陕西关中地区‘徐香’猕猴桃20个典型果园,2020年于果实发育后期,2021年于展叶期、果实膨大期和果实发育后期,测定共114份叶片样品元素含量,并于果实商品采收期测定果实产量、品质和树势相关指标,基于优质、高产、稳产评价,对叶片元... 详细信息

在陕西关中地区‘徐香’猕猴桃20个典型果园,2020年于果实发育后期,2021年于展叶期、果实膨大期和果实发育后期,测定共114份叶片样品元素含量,并于果实商品采收期测定果实产量、品质和树势相关指标,基于优质、高产、稳产评价,对叶片元素进行3种营养诊断:诊断施肥综合法(DRIS)、适宜值偏差百分数法(DOP)和组分营养诊断法(CND),并利用概率分级法(适宜范围法的衍生法)建立叶片元素适宜范围,为生产上‘徐香’猕猴桃养分资源周年管理提供科学依据。结果表明,不同生长期叶片的元素含量差异显著,且与果实产量、品质和树势均相关。利用CND拐点值法分别建立叶片元素分析参数与产量、品质综合得分和树势的函数关系,据此从114个样本中筛选到14个高效群体。利用高效群体计算参比值,并对剩余100个低效群体进行DRIS、DOP和CND诊断,结果表明,低效群体展叶期Ca和Fe缺乏,Mn、Cl和P过量;果实膨大期N和Ca缺乏,Mg和Cl过量;果实发育后期Ca缺乏,Cl、Mn和N过量。利用概率分级法建立的‘徐香’猕猴桃叶片元素适宜范围为:展叶期N 35~40、P 3.0~3.8、K 21~26、Ca 15~20、Mg 2.5~3.0和Cl 3.0~4.5 g·kg-1,Fe 100~180、Mn 50~80、Cu 14~20、Zn 21~30和B 32~45 mg·kg-1;果实膨大期N 29~35、P 1.4~1.8、K 9~16、Ca 37~44、Mg 6.0~7.8和Cl 3.5~5.5 g·kg-1,Fe 175~250、Mn 85~200、Cu 8.5~15.0、Zn 15~30和B 55~85 mg·kg-1;果实发育后期N 20~24、P 1.3~1.7、K 7~14、Ca 42~51、Mg 7~9和Cl 3~5 g·kg-1,Fe 180~250、Mn 80~160、Cu 7~12、Zn 20~45和B 52~67 mg·kg-1。

关键词：猕猴桃叶片营养诊断 DRIS DOP CND 适宜范围

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In situ self-assembled organoid for osteochondral tissue regeneration with dual functional units

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Bioactive Materials 2023年第9期27卷 200-215页

作者： Zhen Yang Bin Wang Wei Liu xiaoke Li Kaini Liang Zejun Fan Jiao Jiao Li Yudi niu Zihao He Hui Li Du Wang Jianjing Lin Yanan Du Jianhao Lin Dan Xing Arthritis Clinical and Research Center Peking University People’s HospitalNo.11 Xizhimen South StreetBeijing100044China Arthritis Institute Peking UniversityBeijing100044China Department of Orthopedic Surgery The First Affiliated HospitalZhejiang University School of MedicineHangzhou310006China Beijing CytoNiche Biotechnology Co.Ltd Beijing10081China Department of Orthopedics Shanxi Medical University Second Affiliated HospitalTaiyuan030001China Department of Biomedical Engineering School of MedicineTsinghua-Peking Center for Life SciencesTsinghua UniversityBeijing10084China School of Biomedical Engineering Faculty of Engineering and ITUniversity of Technology SydneySydneyAustralia Department of Sports Medicine and Rehabilitation Peking University Shenzhen HospitalShenzhenChina

The regeneration of hierarchical osteochondral units is challenging due to difficulties in inducing spatial,directional and controllable differentiation of mesenchymal stem cells(MSCs)into cartilage and bone compartments.Emerging organoid technology offers new opportunities for osteochondral regeneration.In this study,we developed gelatin-based microcryogels customized using hyaluronic acid(HA)and hydroxyapatite(HYP),respectively for inducing cartilage and bone regeneration(denoted as CH-Microcryogels and OS-Microcryogels)through in vivo self-assembly into osteochondral organoids.The customized microcryogels showed good cytocompatibility and induced chondrogenic and osteogenic differentiation of MSCs,while also demonstrating the ability to self-assemble into osteochondral organoids with no delamination in the biphasic cartilage-bone structure.Analysis by mRNA-seq showed that CH-Microcryogels promoted chondrogenic differentiation and inhibited inflammation,while OS-Microcryogels facilitated osteogenic differentiation and suppressed the immune response,by regulating specific signaling pathways.Finally,the in vivo engraftment of pre-differentiated customized microcryogels into canine osteochondral defects resulted in the spontaneous assembly of an osteochondral unit,inducing simultaneous regeneration of both articular cartilage and subchondral bone.In conclusion,this novel approach for generating self-assembling osteochondral organoids utilizing tailor-made microcryogels presents a highly promising avenue for advancing the field of tissue engineering.

关键词： Mesenchymal stem cells Self-assembly Microcryogels Osteochondral regeneration Organoid

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Visual object tracking- classical and contemporary approaches

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Frontiers of Computer Science 2016年第1期10卷 167-188页

作者： Ahmad ALI Abdul JALIL Jianwei niu xiaoke ZHAO Saima RATHORE Javed AHMED Muhammad AKSAM IFTIKHAR Department of Computer and Information Sciences Pakistan Institute of Engineering & Applied Sciences Islamabad 44000 Pakistan State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing 100191 China Department of Electrical (Telecom) Engineering NUST Military College of Signals Islamabad 44000 Pakistan COMSATS Institute of Information Technology Lahore 54000 Pakistan

Visual object tracking （VOT） is an important sub- field of computer vision. It has widespread application do- mains, and has been considered as an important part of surveillance and security system. VOA facilitates finding the position of target in image coordinates of video frames. While doing this, VOA also faces many challenges such as noise, clutter, occlusion, rapid change in object appearances, highly maneuvered （complex） object motion, illumination changes. In recent years, VOT has made significant progress due to availability of low-cost high-quality video cameras as well as fast computational resources, and many modern techniques have been proposed to handle the challenges faced by VOT. This article introduces the readers to 1） VOT and its applica- tions in other domains, 2） different issues which arise in it, 3） various classical as well as contemporary approaches for object tracking, 4） evaluation methodologies for VOT, and 5） online resources, i.e., annotated datasets and source code available for various tracking techniques.

关键词： visual object tracking computer vision imageprocessing point tracking kernel tracking silhouette track-ing

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Determination of Effective Response Time Window to Visual Object in Object-oriented Task of Birds

Determination of Effective Response Time Window to Visual Ob...

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第40届中国控制会议

作者： xiaoke niu Shangfei Yang Zhenyang Jiang Yanyan Peng Hong Yang Henan Key Laboratory of Brain Science and Brain Computer Interface Technology School of Electrical EngineeringZhengZhou University The First Affiliated Hospital of Zhengzhou University ZhengZhou University

Determination of effective visual response time window is premise of studying object cognition and decision-making mechanisms in avian object-oriented task.However,it is difficult to determine the effective response time window for freely moving birds.In this study,video data of pigeon’s face in the target-oriented task was collected,and a neural network algorithm based on Faster RCNN was applied to train pigeon face prediction model,which was further used to predict the time window of pigeon observing the specific image target.The length of time window were estimated based on the statistical results of 177 trials,and the specific time window for each trial was then determined by combining the start frame that contained pigeon’s frontal faces.Finally,the proposed method was verified using data from two pigeons trained for object-oriented task.Taking the firing rates feature population recorded from pigeon’s ectostriatum as an example,the mean firing rate during the estimated effective time window and the original mean firing rate without the time window were sent to SVM and KNN classifier respectively to decode the observed object category.The comparison results showed that the classification accuracy of both classifiers were significantly improved with our method,proving that the proposed method could obtained effective response to specific visual object for freely moving birds.

关键词： Pigeon Face Recognition Faster-RCNN Goal-Oriented Visual Decoding

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Advances in artificial intelligence techniques drive the application of radiomics in the clinical research of hepatocellular carcinoma

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iLIVER 2022年第1期1卷 49-54页

作者： Jingwei Wei Meng niu Ouyang Yabo Yu Zhou xiaoke Ma Xue Yang Hanyu Jiang Hui Hui Hongyi Cao Binwei Duan Hongjun Li Dawei Ding Jie Tian Key Laboratory of Molecular Imaging Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Molecular Imaging Beijing 100190China Department of Interventional Radiology The First Affiliated Hospital of China Medical UniversityShenyangLiaoning110000China Beijing YouAn Hospital Capital Medical UniversityBeijing Institute of HepatologyBeijing100069China School of Life Science and Technology Xidian UniversityXi'anChina School of Computer Science and Technology Xidian UniversityXi'anShaanxiChina Department of Radiology Beijing Youan HospitalCapital Medical UniverstiyBeijing100069China Department of Radiology West China HospitalSichuan UniversityChengduSichuan 610041China Department of Pathology College of Basic Medical ScienceChina Medical UniversityShenyangLiaoning110000China The Department of General Surgery Center Beijing YouAn HospitalCapital Medical UniversityChina School of Bioengineering Beihang UniversityBeijing100191China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine Beihang UniversityBeijing100191China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and TechnologyXidian UniversityXi'anShaanxi710126China

Hepatocellular carcinoma(HCC)remains the most common malignancy to threaten public health globally.With advances in artificial intelligence techniques,radiomics for HCC management provides a novel perspective to solve unmet needs in clinical settings,and reveals pixel-level radiological information for medical imaging big data,correlating the radiological phenotype with targeted clinical issues.Conventional radiomics pipelines depend on handcrafted engineering features,and further deep learning-based radiomics pipelines are supplemented with deep features calculated via self-learning strategies.During the past decade,radiomics has been widely applied in accurate diagnoses and pathological or biological behavior evaluation,as well as in prognosis prediction.In this review,we systematically introduce the main pipelines of artificial intelligence-based radiomics and their efficacy in the clinical studies of HCC.

关键词： Artificial intelligence Diagnosis Hepatocellular carcinoma Prognosis Radiomics

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Preliminary report on methane emissions from the Three Gorges Reservoir in the summer drainage period

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Journal of Environmental Sciences 2011年第12期23卷 2029-2033页

作者： Fei Lu Le Yang xiaoke Wang Xiaonan Duan Yujing Mu Wenzhi Song Feixiang Zheng Junfeng niu Lei Tong Hua Zheng Yongjuan Zhou Jiangxiao Qiu Zhiyun Ouyang State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China Graduate University of Chinese Academy of Sciences Beijing 100049 China General Office of Chinese Academy of Sciences Beijing 100864 China Laboratory of Atmospheric Chemistry and Air Pollution Control Techniques Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China

Recently reported summertime methane （CH4） emissions （6.7 ± 13.3 mg CH4/（m2·hr）） from newly created marshes in the drawdown area of the Three Gorges Reservoir （TGR）, China have triggered broad concern in academic circles and among the public. The CH4 emissions from TGR water surfaces and drawdown areas were monitored from 3rd June to 16th October 2010 with floating and static chambers and gas chromatography. The average CH4 emission flux from permanently flooded areas in Zigui, Wushan and Yunyang Counties was （0.33 ± 0.09） mg CH4/（m2·hr）. In half of these hottest months of the year, the wilderness, cropland and deforested drawdown sites were aerobic and located above water level, and the CH4 emissions were very small, ranging from a sink at 0.12 mg CH4/（m2·hr） to a source at 0.08 mg CH4/（m2·hr） except for one mud-covered site after flood. Mean CH4 emission in flooded drawdown sites was 0.34 mg CH4/（m2·hr）. The emissions from the rice paddy sites in the drawdown area were averaged at （4.86 ± 2.31） mg CH4/（m2·hr）. Excepting the rice-paddy sites, these results show much lower emission levels than previously reported. Our results indicated considerable spatial and temporal variation in CH4 emissions from the TGR. Human activities and occasional events, such as flood, may also affect emission levels. Long-term CH4 measurements and modeling in a large region are necessary to accurately estimate greenhouse gas emissions from the TGR.

关键词： methane the Three Gorges Reservoir drawdown area summer drainage uncertainty flood

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基于ZIF-8/PAN复合薄膜的柔性丙酮气体传感器

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化学学报 2022年第7期80卷 946-955页

作者：牛犇翟振宇郝肖柯任婷莉李从举北京市高校节能与环保工程研究中心北京100083 北京科技大学能源与环境工程学院北京100083

ZIF-8是一种Zn基金属有机骨架材料, 可以吸附丙酮气体从而作为电容式丙酮传感器的气敏材料, 然而ZIF-8的传统使用形式为粉末态, 这导致其不能成为具备柔性的整体, 从而限制了传感器的柔性. 结合包埋种子和二次生长法将ZIF-8与纳米纤维... 详细信息

ZIF-8是一种Zn基金属有机骨架材料, 可以吸附丙酮气体从而作为电容式丙酮传感器的气敏材料, 然而ZIF-8的传统使用形式为粉末态, 这导致其不能成为具备柔性的整体, 从而限制了传感器的柔性. 结合包埋种子和二次生长法将ZIF-8与纳米纤维结合成纤维型柔性材料, 并将其作为气敏层制备了柔性电容式丙酮气体传感器. 该传感器在9种常见挥发性有机化合物中表现出良好的选择性, 对250~2000 cm^(3)/m^(3)的丙酮气体具有灵敏的响应、良好的循环响应及长期稳定性. 值得注意的是该柔性传感器不仅在室温下进行传感, 而且在弯折180°的状态下对丙酮气体的响应值与不弯折(0°)状态下几乎一致, 在200次以内的180°弯折-恢复后同样表现出了传感性能的稳定, 表明了其在柔性传感器方面的潜力.

关键词：金属有机骨架材料纳米纤维挥发性有机化合物(VOCs)气体传感器电容柔性包埋种子法

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Advances in the Application of Perovskite Materials

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Nano-Micro Letters 2023年第10期15卷 334-381页

作者： Lixiu Zhang Luyao Mei Kaiyang Wang Yinhua Lv Shuai Zhang Yaxiao Lian xiaoke Liu Zhiwei Ma Guanjun Xiao Qiang Liu Shuaibo Zhai Shengli Zhang Gengling Liu Ligang Yuan Bingbing Guo Ziming Chen Keyu Wei Aqiang Liu Shizhong Yue Guangda niu Xiyan Pan Jie Sun Yong Hua Wu‑Qiang Wu Dawei Di Baodan Zhao Jianjun Tian Zhijie Wang Yang Yang Liang Chu Mingjian Yuan Haibo Zeng Hin‑Lap Yip Keyou Yan Wentao Xu Lu Zhu Wenhua Zhang Guichuan Xing Feng Gao Liming Ding Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing 100190People’s Republic of China University of Chinese Academy of Sciences Beijing 100049People’s Republic of China Department of Physics Link.ping University58183 Link.pingSweden Institute of Applied Physics and Materials Engineering University of MacaoMacao 999078People’s Republic of China School of Materials Science and Engineering Yunnan UniversityKunming 650091People’s Republic of China School of Microelectronics Science and Technology Sun Yat-sen UniversityZhuhai 519082People’s Republic of China College of Electronic Information and Optical Engineering Nankai UniversityTianjin 300350People’s Republic of China Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of TechnologyShenzhen 518055People’s Republic of China School of Materials Science and Engineering Nanjing University of Science and TechnologyNanjing 210094People’s Republic of China College of Optical Science and Engineering Zhejiang UniversityHangzhou 310027People’s Republic of China State Key Laboratory of Superhard Materials Jilin UniversityChangchun 130012People’s Republic of China College of Electronic and Optical Engineering Nanjing University of Posts and TelecommunicationsNanjing 210023People’s Republic of China School of Chemistry Sun Yat-sen UniversityGuangzhou 510006People’s Republic of China School of Environment and Energy South China University of TechnologyGuangzhou 510000People’s Republic of China Department of Chemistry Imperial College LondonLondon W120BZUK College of Chemistry Nankai UniversityTianjin 300071People’s Republic of China Institute for Advanced Materials and Technology University of Science and Technology BeijingBeijing 100083People’s Republic of China Institute of Semiconductors Chinese Academy of SciencesBeijing 100083People’s Republic of China School

Nowadays, the soar of photovoltaic performance of perovskite solar cells has set off a fever in the study of metal halide perovskite materials. The excellent optoelectronic properties and defect tolerance feature allow metal halide perovskite to be employed in a wide variety of applications. This article provides a holistic review over the current progress and future prospects of metal halide perovskite materials in representative promising applications, including traditional optoelectronic devices(solar cells, light-emitting diodes, photodetectors, lasers), and cutting-edge technologies in terms of neuromorphic devices(artificial synapses and memristors) and pressure-induced emission. This review highlights the fundamentals, the current progress and the remaining challenges for each application, aiming to provide a comprehensive overview of the development status and a navigation of future research for metal halide perovskite materials and devices.

关键词： Perovskites Optoelectronic devices Neuromorphic devices Pressure-induced emission

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