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| 1 | The spatial distribution of forest carbon sinks and sources in China显示文摘Forest ecosystems play an important role in the global carbon cycle.The implementation of the United Nations Framework Convention on Climate Change(UNFCCC) and the Kyoto Protocol has made the study of forest ecosystem carbon cycling a hot topic of scientific research globally.This paper utilized Chinese national forest inventory data sets(for the periods 1984-1988 and 1999-2003),the vegetation map of China(1:1000000),and the spatially explicit net primary productivity(NPP) data sets derived with the remote sensing-based light use efficiency model(CASA model).We quantitatively estimated the spatial distribution of carbon sinks and sources of forest vegetation(with a resolution of 1 km) using the spatial downscaling technique.During the period 1984 to 2003 the forest vegetation in China represented a carbon sink.The total storage of carbon increased by 0.77 PgC,with a mean of 51.0TgCa 1.The total carbon sink was 0.88PgC and carbon source was 0.11 PgC during the study period.The carbon sink and carbon source of forest vegetation in China showed a clear spatial distribution pattern.Carbon sinks were mainly located in subtropical and temperate regions,with the highest values in Hainan Province,Hengduan mountain ranges,Changbai mountain ranges in Jilin,and south and northwest of the Da Hinggan Mountains;carbon sources were mainly distributed from the northeast to southwestern areas in China,with the highest values mainly concentrated in southern Yunnan Province,central Sichuan Basin,and northern Da Hinggan Mountains.Increase in NPP was strongly correlated with carbon sink strength.The regression model showed that more than 80% of the variation in the modeled carbon sinks in Northeast,Northern,Northwest and Southern China were explained by the variation in NPP increase.There was a strong relationship between carbon sink strength and forest stand age. | LIU ShuangNa ZHOU Tao WEI LinYan SHU Yang | 2012 | Chinese Science Bulletin2012，57，14： | 27 |
| 2 | Application of Pore Evolution and Fracture Development Coupled Models in the Prediction of Reservoir 'Sweet Spots' in Tight Sandstones显示文摘<正>The Chang-6~3 reservoir in the Huaqing area has widely developed tight sandstone reservoirs characterized by'thick sand layers,but not rich in oil',and it is thus necessary to further study its oil and gas enrichment law.This study builds porosity and fracture development | ZHANG Linyan ZHUO Xizhun MA Licheng CHEN Xiaoshuai SONG Licai ZHOU Xingui | 2015 | Acta Geologica Sinica(English Edition)2015，89，3： | 3 |
| 3 | Hydrocarbon migration in fracture-cave systems of carbonate reservoirs under tectonic stresses:A modeling study显示文摘The Tahe oilfield,located in the southwest of the Akekule nosing structure,northern Tarim basin,was the most prolific oilfield targeting at the Ordovician carbonate reservoirs in China.The reservoir space was dominant with fracture-cave systems commonly induced by tectonics and karstification.Although hydrocarbon production had proceeded for two decades in the Tahe oilfiled,the control of oil and gas accumulations was still doubtful.In this work,the periodic fluid flow induced by cyclic tectonic stresses was proposed as the mechanism of hydrocarbon migration in the fracture-cave systems of carbonate reservoirs.The fracture networks formed conduits for fluid flow,and the fluid pressure in caves transmitted from stress field provided the driving force.The constitutive equations were established among stresses,fracture densities and flow velocities.Four quasi-3D geological models were constructed to simulate the flow velocities on the Ordovician surface of Akekule nosing structure in the critical tectonic stages.The simulated results supplied indicative information on oil and gas migration and accumulation in the tectonic stages.Combining with the oil and gas charge history,a conceptual model was built to reveal the multi-stage oil and gas charge and accumulation in the Ordovician of Akekule nosing structure. | Chenjun Huang Geyun Liu Yongsheng Ma Xingui Zhou Linyan Zhang Jinyin Yin Jinrui Guo | 2019 | Petroleum Research2019，4，4： | 2 |
| 4 | Effect of high pressure carbon dioxide on the quality of carrot juice显示文摘 | Zhou Linyan Wang Yuanyuan Hu Xiaosong | 2009 | Innovative Food Science and Emerging Technologies2009，10，3： | 1 |
| 5 | Effect of high pressure carbon dioxide on the quality of carrot j uice显示文摘 | ZHOU Linyan WANG Yuanyuan HU Xiaosong | 2009 | Innov Food Sci Emerg Technol2009，10，： | 1 |
| 6 | Effect of high pressure carbon dioxide on the quality of carrot juice显示文摘 | ZHOU Linyan WANG Yuanyuan HU Xiaosong | | 0，，03： | 1 |
| 7 | Study on the Drought and Flood Disasters Formation Mechanism in Karat Regions of Middle Guangxi显示文摘 | Rui Zhou Chunqing Guo Qiuju Fu Linyan Pan | 2012 | Procedia Engineering2012，28，： | 1 |
| 8 | Effect of high pressure carbon dioxide on the quality of carrot juice显示文摘 | ZHOU Linyan WANG Yuanyuan HU Xiaosong | 2009 | Innovative Food Science and Emerging Technologies2009，10，3： | 1 |
| 9 | Drying kinetics and quality attributes of jujube ( Zizyphus jujuba Miller) slices dried by hot-air and short- and medium-wave infrared radiation显示文摘 | Qinqin Chen Jinfeng Bi Xinye Wu Jianyong Yi Linyan Zhou Yuhan Zhou | 2015 | LWT - Food Science and Technology2015，，2： | 1 |
| 10 | Design and performance of the LLRF control system for CSNS linac显示文摘Objective The China Spallation Neutron Source(CSNS)linac is designed with beam energy of 80 MeV and a peak current of 15 mA in the first phase.It consists of RFQ,two bunchers of medium-energy beam transmission line,four DTL tanks and one debuncher of linac-to-ring beam transmission line.Correspondingly,eight online RF power sources are used to power these accelerators.In order to stabilize the amplitude,phase and resonant frequency of the RF accelerating field,and minimize beam loss,we have established digital low-level RF(LLRF)control system.Methods The LLRF system includes RF reference line,analog module(AM),clock distribution module,digital control module(DCM),high-power protection module,timing and RF interlock module and so on.The DCM is mainly responsible for the stability of the RF field amplitude and phase,and RF interlock module can quickly cut off the RF drive in case of arc in the RF transmission system,VSWR over threshold or cavity vacuum fault and so on.Result During beam commissioning,all of eight online units of LLRF control system were operating stably and reliably.The amplitude and phase variations of the linac fields have been achieved about±0.4%and±0.15°with 10-mA beam loading,much better than the design requirements of±1%in amplitude and±1°in phase.Conclusion With the help of this system,we achieved stable operation under different beam loads.Also,many important progresses have been achieved in the LLRF control system for amore convenient operation and a higher stability performance.This article describes the design and implementation of the LLRF for CSNS linac. | Linyan Rong Zhencheng Mu Jian Li Zhexin Xie Wenzhong Zhou Bo Wang Maliang Wan Meifei Liu Xinan Xu | 2020 | Radiation Detection Technology and Methods2020，4，2： | 1 |
| 11 | Quality eval- uation of yellow peach chips prepared by explosion puffing drying显示文摘 | Lyu Jian Zhou Linyan Bi Jinfeng | 2015 | J Food Sci Technol2015，52，12： | 1 |
| 12 | Predicting microbial extracellular electron transfer activity in paddy soils with soil physicochemical properties using machine learning显示文摘Soil extracellular electron transfer(EET)is a pivotal biological process within the realm of soil.Unfortunately,EET suffers from a lack of predictive models.Herein,an intricately crafted machine learning model has been developed for the purpose of predicting soil EET by using the physicochemical properties of soil as independent input variables and the EET capabilities in terms of current density(j_(max))and Coulombic charge(C_(out))as dependent output variables.An autoencoder ensemble stacking(AES)model was developed to address the aforementioned issue by integrating support vector machine,multilayer perceptron,extreme gradient boosting,and light gradient boosting machine algorithms as the stacking algorithms.With 10-fold crossvalidation,the AES model exhibited notable improvements in predicting j_(max)and C_(out),with average test R^(2)values of 0.83 and 0.84,respectively,surpassing those of single machine learning(ML)models and the basic ensemble model.By utilizing partial correlation plots(PDPs),Shapley Additive explanations(SHAP)values,and SHAP decision plots,we quantitatively explained the impact and contribution of the input molecules on the AES model’s predictions of j_(max)and C_(out).In the context of the SHAP method for the AES model,total carbon(TC)was identified as the most correlated descriptor for j_(max),while total organic carbon(TOC)stood out as the most relevant descriptor for C_(out).In the prediction tasks of j_(max)and C_(out)within the AES model,employing a multitask ML approach allowed the model to benefit from the shared information of input variables,thereby enhancing its overall generalizability.This study provides a feasible tool for the prediction of soil EET from soil physiochemical properties and an advanced understanding of the relationship between soil physiochemical properties and EET capability. | OU JiaJun LUO XiaoShan LIU JunYang HUANG LinYan ZHOU LiHua YUAN Yong | 2024 | Science China(Technological Sciences)2024，67，1： | 0 |
| 13 | AlphaMobileSensing:A virtual testbed for mobile environmental monitoring显示文摘Environmental monitoring plays a critical role in creating and maintaining a comfortable,productive,and healthy environment.Built upon the advancements of robotics and data processing,mobile sensing demonstrates its potential to address problems regarding cost,deployment,and resolution that stationary monitoring encounters,which therefore has attracted increasing research attentions recently.To facilitate mobile sensing,two key algorithms are needed:the field reconstruction algorithm and the route planning algorithm.The field reconstruction algorithm is to reconstruct the entire environment field from spatially-and temporally-discrete measurements collected by the mobile sensors.The route planning algorithm is to instruct the mobile sensors where the mobile sensor needs to move to for the next measurements.The performance of mobile sensors highly depends on these two algorithms.However,developing and testing those algorithms in the real world is expensive,challenging,and time-consuming.To address these issues,we proposed and implemented an open-source virtual testbed,AlphaMobileSensing,that can be used to develop,test,and benchmark mobile sensing algorithms.AlphaMobileSensing aims to help users more easily develop and test the field reconstruction and route planning algorithms for mobile sensing solutions,without worrying about hardware fault,test accidents(such as collision during the test),etc.The separation of concerns can significantly reduce the cost of developing software solutions for mobile sensing.For versatility and flexibility,AlphaMobileSensing was wrapped up using the standardized interface of OpenAI Gym,and it also provides an interface for loading physical fields that were generated by numerical simulations as virtual test sites to perform mobile sensing and retrieving monitoring data.We demonstrated applications of the virtual testbed by implementing and testing algorithms for physical field reconstruction in both static and dynamic indoor thermal environments.AlphaMobileSensing provides a novel and flexible platform to develop,test,and benchmark mobile sensing algorithms more easily,conveniently,and efficiently.AlphaMobileSensing is open sourced at http://gffzz188fe103f8f1460asq6c0kxb5o6w56wwq.ffgz.tsg.suse.edu.cn/kishuqizhou/AlphaMobileSensing. | Qi Zhou Haoran Zhong Linyan Li Zhe Wang | 2023 | Building Simulation2023，16，7： | 0 |
| 14 | Discussing the Oil-Control Effects of the North Latitudinal 38° Belt in Central Part of the Ordos Basin显示文摘The Ordos Basin in the western part of the North China Craton is commonly believed to be a multi-controlled oilbearing basin.It is bounded by the Xing’an-Mongolian Orogen to the north,the Qingling Orogen to the south,the Lüliang mountain to the east and the Helanshan-Liupanshan mountain belt to the west.The interpretation of geophysical data reveals a latitudinal(38°)fault belt in the centre of the Ordos Basin,which controls the hydrocarbon generation,migration and accumulation in the basin.This study attempts | MA Licheng ZHANG Linyan WANG Zongxui ZHOU Xingui LI Chunlin CHEN Xiao | 2015 | Acta Geologica Sinica(English Edition)2015，89，2： | 0 |
| 15 | The Internet Banking Model and Comparative Study显示文摘 | Linyan Yang Xiaoyao Zhou | 2006 | China-USA Business Review2006，5，7： | 0 |
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