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A phylogenetic approach identifies patterns of beta diversity and floristic subregions of the Qinghai-Tibet Plateau

Plant Diversity 2024年第1期46卷 59-69页

作者： Haibin Yu man Yang Zixin Lu weitao Wang Fangyuan Yu Yonghua Zhang Xue Yin Hongjun Yu Junjie Hu David C.Deane Key Laboratory of Conservation and Application in Biodiversity of South China School of Life SciencesGuangzhou UniversityGuangzhou 510006China School of Ecology Sun Yat-Sen UniversityShenzhen 510275China School of Geography and Remote Sensing Guangzhou UniversityGuangzhou 510006China College of Life and Environmental Science Wenzhou UniversityWenzhou 325035China Centre for Future Landscapes and Department of Environment and Genetics La Trobe UniversityBundooraVIC 3083Australia

Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic regions.In this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet Plateau.We also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the QTP.We also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic difference.The environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic instability.Hierarchical dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the QTP.Our results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.

关键词： Biogeographical regionalization Phylogenetic beta diversity Seed plants Sørensen dissimilarity Qinghai-Tibet Plateau

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Review of Computational Approaches to Optimization Problems in Inhomogeneous Rods and Plates

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Communications on Applied Mathematics and Computation 2024年第1期6卷 236-256页

作者： weitao Chen Chiu-Yen Kao Department of Mathematics University of California at Riverside900 University AveRiversideCA92521USA Department of Mathematical Sciences Claremont McKenna College850 Columbia AveClaremontCA91711USA

In this paper,we review computational approaches to optimization problems of inhomogeneous rods and plates.We consider both the optimization of eigenvalues and the localization of eigenfunctions.These problems are motivated by physical problems including the determination of the extremum of the fundamental vibration frequency and the localization of the vibration displacement.We demonstrate how an iterative rearrangement approach and a gradient descent approach with projection can successfully solve these optimization problems under different boundary conditions with different densities given.

关键词： Inhomogeneous rods and plates Bi-Laplacian Optimization of eigenvalues Localization of eigenfunctions Rearrangement

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Perturbation of autophagy pathways in murine alveolar macrophage by 2D TMDCs is chalcogen-dependent

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Journal of Environmental Sciences 2024年第1期135卷 97-107页

作者： Xiaofei Zhou weitao Jin Rui Zhang Xuan Mao Jianbo Jia Hongyu Zhou College of Science&Technology Hebei Agricultural UniversityHuanghua 061100China Institute of Environmental Research at Greater Bay Area Key Laboratory for Water Quality and Conservation of the Pearl River DeltaMinistry of EducationGuangzhou UniversityGuangzhou 510006China

Increasing risks of incidental and occupational exposures to two-dimensional transition metal dichalcogenides(2D TMDCs)due to their broad application in various areas raised their public health concerns.While the composition-dependent cytotoxicity of 2D TMDCs has been well-recognized,how the outer chalcogenide atoms and inner transition metal atoms differentially contribute to their perturbation on cell homeostasis at non-lethal doses remains to be identified.In the present work,we compared the autophagy induction and related mechanisms in response to WS_(2),NbS_(2),WSe_(2)and Nb Se_(2)nanosheets exposures in MH-S murine alveolar macrophages.All these 2D TMDCs had comparable physicochemical properties,overall cytotoxicity and capability in triggering autophagy in MH-S cells,but showed outer chalcogen-dependent subcellular localization and activation of autophagy pathways.Specifically,WS_(2)and NbS_(2)nanosheets adhered on the cell surface and internalized in the lysosomes,and triggered m TOR-dependent activation of autophagy.Meanwhile,WSe_(2)and Nb Se_(2)nanosheets had extensive distribution in cytoplasm of MH-S cells and induced autophagy in an m TOR-independent manner.Furthermore,the 2D TMDCs-induced perturbation on autophagy aggravated the cytotoxicity of respirable benzo[a]pyrene.These findings provide a deeper insight into the potential health risk of environmental 2D TMDCs from the perspective of homeostasis perturbation.

关键词： Chalcogen group Autophagy pathway Cell function Endosomal escape Inhalation toxicity

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Kinematic calibration method with high measurement efficiency and robust identification for hybrid machine tools

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Chinese Journal of Aeronautics 2024年第3期37卷 468-482页

作者： Liping WANG Mengyu LI Guang YU weitao LI Xiangyu KONG State Key Laboratory of Tribology Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China Beijing Key Laboratory of Precision/Ultra-precision manufacturing Equipment and Control Beijing 100084China

Geometric error is the main factor affecting the machining accuracy of hybrid machine tools.Kinematic calibration is an effective way to improve the geometric accuracy of hybrid machine tools.The necessity to measure both position and orientation at each pose,as well as the instability of identification in case of incomplete measurements,severely affects the application of traditional calibration methods.In this study,a kinematic calibration method with high measurement efficiency and robust identification is proposed to improve the kinematic accuracy of a five-axis hybrid machine tool.First,the configuration is introduced,and an error model is derived.Further,by investigating the mechanism error characteristics,a measurement scheme that only requires tool centre point position error measurement and one alignment operation is proposed.Subsequently,by analysing the effects of unmeasured degrees of freedom(DOFs)on other DOFs,an improved nonlinear least squares method based on virtual measurement values is proposed to achieve stable parameter identification in case of incomplete measurement,without introducing additional parameters.Finally,the proposed calibration method is verified through simulations and experiments.The proposed method can efficiently accomplish the kinematic calibration of the hybrid machine tool.The accuracy of the hybrid machine tool is significantly improved after calibration,satisfying actual aerospace machining requirements.

关键词： Hybrid machine tool Calibration Measurement scheme Improved nonlinear least squares method Virtual measurement values

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The design and engineering strategies of metal tellurides for advanced metal-ion batteries

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Journal of Energy Chemistry 2024年第2期89卷 579-598,I0013页

作者： Wenmiao Zhao Xiaoyuan Shi Bo Liu Hiroshi Ueno Ting Deng weitao Zheng Key Laboratory of Automobile Materials of MOE School of Materials Science and EngineeringJilin Provincial International Cooperation Key Laboratory of High-Efficiency Clean Energy MaterialsJilin UniversityChangchun 130012JilinChina Key Laboratory of Polyoxometalate Science of Ministry of Education Northeast Normal UniversityChangchun 130024JilinChina Key Laboratory of Preparation and Application of Environmental Friendly Materials(Jilin Normal University) Ministry of EducationChangchun 130103JilinChina Creative Interdisciplinary Research Division The Frontier Research Institute for Interdisciplinary Sciences(FRIS)Department of ChemistryGraduate School of ScienceTohoku UniversitySendai 980-8578Japan

Owning various crystal structures and high theoretical capacity,metal tellurides are emerging as promising electrode materials for high-performance metal-ion batteries(MBs).Since metal telluride-based MBs are quite new,fundamental issues raise regarding the energy storage mechanism and other aspects affecting electrochemical performance.Severe volume expansion,low intrinsic conductivity and slow ion diffusion kinetics jeopardize the performance of metal tellurides,so that rational design and engineering are crucial to circumvent these disadvantages.Herein,this review provides an in-depth discussion of recent investigations and progresses of metal tellurides,beginning with a critical discussion on the energy storage mechanisms of metal tellurides in various MBs.In the following,recent design and engineering strategies of metal tellurides,including morphology engineering,compositing,defect engineering and heterostructure construction,for high-performance MBs are summarized.The primary focus is to present a comprehensive understanding of the structural evolution based on the mechanism and corresponding effects of dimension control,composition,electron configuration and structural complexity on the electrochemical performance.In closing,outlooks and prospects for future development of metal tellurides are proposed.This work also highlights the promising directions of design and engineering strategies of metal tellurides with high performance and low cost.

关键词： Metal tellurides Metal-ion battery Energy storage mechanism Material design and engineering

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p38 MAPK inhibitor SB202190 suppresses ferroptosis in the glutamate-induced retinal excitotoxicity glaucoma model

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Neural Regeneration Research 2024年第10期19卷 2299-2309页

作者： Lemeng Feng Chao Wang Cheng Zhang Wulong Zhang Weiming Zhu Ye He Zhaohua Xia weitao Song National Clinical Research Center for Geriatric Diseases Xiangya Hospital of Central South UniversityChangshaHunan ProvinceChina Eye Center of Xiangya Hospital Central South UniversityChangshaHunan ProvinceChina Hunan Key Laboratory of Ophthalmology ChangshaHunan ProvinceChina

Glutamate excitotoxicity has been shown to play an important role in glaucoma, and glutamate can induce ferroptosis. The p38 mitogenactivated protein kinase(MAPK) pathway inhibitor SB202190 has a potential ability to suppress ferroptosis, and its downstream targets, such as p53, have been shown to be associated with ferroptosis. However, whether ferroptosis also occurs in retinal ganglion cells in response to glutamate excitotoxicity and whether inhibition of ferroptosis reduces the loss of retinal ganglion cells induced by glutamate excitotoxicity remain unclear. This study investigated ferroptosis in a glutamate-induced glaucoma rat model and explored the effects and molecular mechanisms of SB202190 on retinal ganglion cells. A glutamate-induced excitotoxicity model in R28 cells and an N-methyl-D-aspartate-induced glaucoma model in rats were used. In vitro experiments showed that glutamate induced the accumulation of iron and lipid peroxide and morphological changes of mitochondria in R28 cells, and SB202190 inhibited these changes. Glutamate induced the levels of p-p38 MAPK/p38 MAPK and SAT1 and decreased the expression levels of ferritin light chain, SLC7A11, and GPX4. SB202190 inhibited the expression of iron death-related proteins induced by glutamate. In vivo experiments showed that SB202190 attenuated N-methyl-D-aspartate-induced damage to rat retinal ganglion cells and improved visual function. These results suggest that SB202190 can inhibit ferroptosis and protect retinal ganglion cells by regulating ferritin light chain, SAT1, and SLC7A11/Gpx4 pathways and may represent a potential retina protectant.

关键词： ferroptosis glaucoma glutamate excitotoxicity p38 MAPK retinal ganglion cell SB202190

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CREDIT-X1local:A reference dataset for machine learning seismology from ChinArray in Southwest China

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Earthquake Science 2024年第2期37卷 139-157页

作者： Lu Li weitao Wang Ziye Yu Yini Chen Institute of Geophysics China Earthquake AdministrationBeijing 100081China Key Laboratory of Earthquake Source Physics China Earthquake AdministrationBeijing 100081China Zhejiang Earthquake Agency HangzhouZhejiang 310013China

High-quality datasets are critical for the development of advanced machine-learning algorithms in seismology.Here,we present an earthquake dataset based on the ChinArray Phase I records(X1).ChinArray Phase I was deployed in the southern north-south seismic zone(20°N-32°N,95°E-110°E)in 2011-2013 using 355 portable broadband seismic stations.CREDIT-X1local,the first release of the ChinArray Reference Earthquake Dataset for Innovative Techniques(CREDIT),includes comprehensive information for the 105,455 local events that occurred in the southern north-south seismic zone during array observation,incorporating them into a single HDF5 file.Original 100-Hz sampled three-component waveforms are organized by event for stations within epicenter distances of 1,000 km,and records of≥200 s are included for each waveform.Two types of phase labels are provided.The first includes manually picked labels for 5,999 events with magnitudes≥2.0,providing 66,507 Pg,42,310 Sg,12,823 Pn,and 546 Sn phases.The second contains automatically labeled phases for 105,442 events with magnitudes of−1.6 to 7.6.These phases were picked using a recurrent neural network phase picker and screened using the corresponding travel time curves,resulting in 1,179,808 Pg,884,281 Sg,176,089 Pn,and 22,986 Sn phases.Additionally,first-motion polarities are included for 31,273 Pg phases.The event and station locations are provided,so that deep learning networks for both conventional phase picking and phase association can be trained and validated.The CREDIT-X1local dataset is the first million-scale dataset constructed from a dense seismic array,which is designed to support various multi-station deep-learning methods,high-precision focal mechanism inversion,and seismic tomography studies.Additionally,owing to the high seismicity in the southern north-south seismic zone in China,this dataset has great potential for future scientific discoveries.

关键词： earthquake dataset machine learning Pg/Sg/Pn/Sn phase picking P-wave first-motion polarity

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Construction of smart propellant with multi-morphologies

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Defence Technology（防务技术） 2024年第3期33卷 180-185页

作者： weitao Yang Yuchen Gao Rui Hu manman Li Fengqi Zhao He Jiang Xuan Zhang Xi’an Modern Chemistry Research Institute Xi’an710065China Northwestern Polytechnical University Xi’an710072China

Smart materials,which exhibit shape memory behavior in response to external stimuli,have shown great potential for use in biomedical applications.In this study,an energetic composite was fabricated using a UV-assisted DIW 3D printing technique and a shape memory material(SMP)as the binder.This composite has the ability to reduce the impact of external factors and adjust gun propellant combustion behavior.The composition and 3D printing process were delineated,while the internal structure and shape memory performance of the composite material were studied.The energetic SMP composite exhibits an angle of reversal of 18 s at 70°,with a maximum elongation typically reaching up to 280% of the original length and a recovery length of approximately 105%during ten cycles.Additionally,thermal decomposition and combustion behavior were also demonstrated for the energetic SMP composite.

关键词： Smart material Gun propellants Multi-morphologies Self-regulation

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3D bio-printed living nerve-like fibers refine the ecological niche for long-distance spinal cord injury regeneration

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Bioactive Materials 2023年第7期25卷 160-175页

作者： Jia Yang Kaiyuan Yang Weitao Man Jingchuan Zheng Zheng Cao Chun-Yi Yang Kunkoo Kim Shuhui Yang Zhaohui Hou Guihuai Wang Xiumei Wang State Key Laboratory of New Ceramics and Fine Processing Key Laboratory of Advanced MaterialsSchool of Materials Science and EngineeringTsinghua UniversityBeijing100084China Department of Neurosurgery Beijing Tsinghua Changgung HospitalSchool of Clinical MedicineTsinghua UniversityBeijing102218China School of Materials Science and Engineering Zhejiang-Mauritius Joint Research Center for BiomaterialsTissue Engineering Zhejiang Sci-Tech UniversityHangzhou310018China

3D bioprinting holds great promise toward fabricating biomimetic living constructs in a bottom-up assembly manner.To date,various emergences of living constructs have been bioprinted for in vitro applications,while the conspicuous potential serving for in vivo implantable therapies in spinal cord injury(SCI)has been relatively overlooked.Herein,living nerve-like fibers are prepared via extrusion-based 3D bioprinting for SCI therapy.The living nerve-like fibers are comprised of neural stem cells(NSCs)embedded within a designed hydrogel that mimics the extracellular matrix(ECM),assembled into a highly spatial ordered architecture,similar to densely arranged bundles of the nerve fibers.The pro-neurogenesis ability of these living nerve-like fibers is tested in a 4 mm-long complete transected SCI rat model.Evidence shows that living nerve-like fibers refine the ecological niche of the defect site by immune modulation,angiogenesis,neurogenesis,neural relay formations,and neural circuit remodeling,leading to outstanding functional reconstruction,revealing an evolution process of this living construct after implantation.This effective strategy,based on biomimetic living constructs,opens a new perspective on SCI therapies.

关键词： Neural stem cells Hydrogels 3D bioprinting Living constructs Spinal cord injury

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Accurate crop row recognition of maize at the seedling stage using lightweight network

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International Journal of Agricultural and Biological Engineering 2024年第1期17卷 189-198,I0001页

作者： Jian Wei Mengfan Zhang Caicong Wu Qin Ma weitao Wang Chuanfeng Wan College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Key Laboratory of Agricultural Machinery Monitoring and Big Data Applications Ministry of Agriculture and Rural AffairsBeijing 100083China

Accurate extraction of crop row is very important for automation of agricultural production.Crop rows are required for accurate machine guidance in agricultural production such as fertilization,plant protection,weeding and harvesting.In this study,an efficient crop row detection algorithm called Crop-BiSeNet V2 was proposed,which combined BiSeNet V2 with a spatial convolutional neural network.The proposed Crop-BiSeNet V2 detected crop rows in color images without the use of threshold and other pre-information such as number of rows.A data set had 2697 maize crop images was constructed in challenging field trial conditions such as variable light,shadows,presence of weeds,and irregular crop shape.The proposed system was experimentally determined to overcome the interference of different complex scenes.And it can be applied to crop rows of different numbers,straight lines and curves.Different analyses were performed to check the robustness of the algorithm.Comparing this algorithm with the Fully Convolutional Networks(FCN)algorithm,it exhibited superior performance and saved 84.85 ms.The accuracy rate reached 0.9811,and the detection speed reached 65.54 ms/frame.The Crop-BiSeNet V2 algorithm proposed in this study show strong generalization performance for seedling crop row recognition.It provides high-reliability technical support for crop row detection research and assists in the study of intelligent field operation machinery navigation.

关键词： computer vision crop row detection precision agriculture semantic segmentation

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