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您的检索式：作者名="Xingyuan Du"
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| 1 | Spatiotemporal pattern of urban forest leaf area index in response to rapid urbanization and urban greening显示文摘Rapid urbanization and urban greening have caused great changes to urban forests in China. Understanding spatiotemporal patterns of urban forest leaf area index(LAI) under rapid urbanization and urban greening is important for urban forest planning and management. We evaluated the potential for estimating urban forest LAI spatiotemporally by using Landsat TM imagery. We collected three scenes of Landsat TM(thematic mapper)images acquired in 1997, 2004 and 2010 and conducted a field survey to collect urban forest LAI. Finally, spatiotemporal maps of the urban forest LAI were created using a NDVI-based urban forest LAI predictive model.Our results show that normalized differential vegetation index(NDVI) could be used as a predictor for urban forest LAI similar to natural forests. Both rapid urbanization and urban greening contribute to the changing process of urban forest LAI. The urban forest has changed considerably from 1997 to 2010. Urban vegetated pixels decreased gradually from 1997 to 2010 due to intensive urbanization.Leaf area for the study area was 216.4, 145.2 and173.7 km^2 in the years 1997, 2004 and 2010, respectively.Urban forest LAI decreased sharply from 1997 to 2004 and increased slightly from 2004 to 2010 because of numerous greening policies. The urban forest LAI class distributions were skewed toward low values in 1997 and 2004. Moreover, the LAI presented a decreasing trend from suburban to downtown areas. We demonstrate the usefulness of TM remote-sensing in understanding spatiotemporal changing patterns of urban forest LAI under rapid urbanization and urban greening. | Zhibin Ren Yunxia Du Xingyuan He Ruiliang Pu Haifeng Zheng Haide Hu | 2018 | Journal of Forestry Research2018，29，3： | 4 |
| 2 | All-optical computing based on convolutional neural networks显示文摘The rapid development of information technology has fueled an ever-increasing demand for ultrafast and ultralow-en-ergy-consumption computing.Existing computing instruments are pre-dominantly electronic processors,which use elec-trons as information carriers and possess von Neumann architecture featured by physical separation of storage and pro-cessing.The scaling of computing speed is limited not only by data transfer between memory and processing units,but also by RC delay associated with integrated circuits.Moreover,excessive heating due to Ohmic losses is becoming a severe bottleneck for both speed and power consumption scaling.Using photons as information carriers is a promising alternative.Owing to the weak third-order optical nonlinearity of conventional materials,building integrated photonic com-puting chips under traditional von Neumann architecture has been a challenge.Here,we report a new all-optical comput-ing framework to realize ultrafast and ultralow-energy-consumption all-optical computing based on convolutional neural networks.The device is constructed from cascaded silicon Y-shaped waveguides with side-coupled silicon waveguide segments which we termed“weight modulators”to enable complete phase and amplitude control in each waveguide branch.The generic device concept can be used for equation solving,multifunctional logic operations as well as many other mathematical operations.Multiple computing functions including transcendental equation solvers,multifarious logic gate operators,and half-adders were experimentally demonstrated to validate the all-optical computing performances.The time-of-flight of light through the network structure corresponds to an ultrafast computing time of the order of several picoseconds with an ultralow energy consumption of dozens of femtojoules per bit.Our approach can be further expan-ded to fulfill other complex computing tasks based on non-von Neumann architectures and thus paves a new way for on-chip all-optical computing. | Kun Liao Ye Chen Zhongcheng Yu Xiaoyong Hu Xingyuan Wang Cuicui Lu Hongtao Lin Qingyang Du Juejun Hu Qihuang Gong | 2021 | Opto-Electronic Advances2021，4，11： | 3 |
| 3 | Visible transparent,infrared stealthy polymeric films with nanocoating of ITO@MXene enable efficient passive radiative heating and solar/electric thermal conversion显示文摘Visible transparent yet low infrared-emissivity(ε)polymeric materials are highly anticipated in many applications,whereas the fabrication of which remains a formidable challenge.Herein,visible transparent,flexible,and low-εpolymeric films were fabricated by nanocoating decoration of indium tin oxide(ITO)and MXene on polyethylene terephthalate(PET)film surface through magnetron sputtering and spray coating,respectively.The obtained PET-ITO@MXene(PET-IM)film exhibits lowεof 24.7%and high visible transmittance exceeding 50%,endowing it with excellent visible transparent infrared stealthy by reducing human skin radiation temperature from 32 to 20.8°C,and remarkable zero-energy passive radiative heating capability(5.7°C).Meanwhile,the transparent low-εPET-IM film has high solar absorptivity and electrical conductivity,enabling superior solar/electric to thermal conversion performance.Notably,the three heating modes of passive radiative and active solar/electric can be integrated together to cope with complex heating scenarios.These visible transparent low-εpolymeric films are highly promising in infrared stealth,building daylighting and thermal management,and personal precision heating. | Xingyuan Du Xiangxin Li Yuxuan Zhang Xinyi Guo Zhengji Li Yanxia Cao Yanyu Yang Wanjie Wang Jianfeng Wang | 2023 | Nano Research2023，16，2： | 1 |
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