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Effects of the Spatial Coupling of Water and Fertilizer on the Chlorophyll Fluorescence Parameters of Winter Wheat Leaves

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Agricultural Sciences in China 2011年第12期10卷 1923-1931页

作者： shen Yu-fang LI shi-qing State Key Laboratory of Soil Erosion and Dryland Farming on Loess Plateau/Northwest A＆F University Yangling 712100 P.R.China

Wheat is an important agricultural crop in the Loess region of China, where there is drought stress and low availability of soil nitrogen and phosphorus. Using a pulse modulation fluorometer, we studied the effects of water, nitrogen, and phosphorus on the kinetic parameters of chlorophyll fluorescence in winter wheat. The wheat was grown in layered columns of Eum-Orthic Anthrosol （Cinnamon soil）, with the water content and nutrient composition of each layer controlled. The results showed that the kinetic parameters of chlorophyll fluorescence were sensitive to water stress. The basic fluorescence （F0） of leaves was higher in the dry treatment （0-30 cm layer at 40-45% of field capacity, 30-90 cm at 75-80% of field capacity） compared to the wet treatment （entire soil column at 75-80% of field capacity）. The maximal fluorescence （Fm）, the variable fluorescence （Fv）, the photochemical efficiency （Fv/Fm） and potential activites （Fv/F0） of photosystem 2 （PS2） were significantly lower in the dry treatment. Although drought stress impaired PS2 function, this effect was significantly ameliorated by applying P or NP fertilizer, but not N alone. P application increased FJFm, both in well-watered and water stressed plants, especially when fertilizer was applied throughout the column or within the top 30 em of soil. A combined fertilizer improved photosynthesis in well watered plants, with Fm and F,fFm being the highest when fertilizer was applied throughout the columns. For drought stressed, plants FJFm was significantly greater when combined fertilizer was added within the top 30 cm of soil. We concluded that, when growing winter wheat in both arid and semi-arid parts of the Loess region of China, it is important to guarantee the nutrient supply in the top 30 cm of the soil.

关键词： water stress nutrient spatial coupling chlorophyll fluorescence column experiment

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SHEsis PCA: A GPU-Based Software to Correct for Population Stratification that Efficiently Accelerates the Process for Handling Genome-Wide Datasets

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Journal of Genetics and Genomics 2015年第8期42卷 445-453页

作者： Jiawei shen Zhiqiang Li Yongyong shi Bio-X Institutes Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education) Shanghai Jiao Tong University Institute of Social Cognitive and Behavioral Sciences Shanghai Jiao Tong University School of Bio-medical Engineering Shanghai Jiao Tong University Shanghai Changning Mental Health Center

Population stratification is a problem in genetic association studies because it is likely to highlight loci that underlie the population structure rather than disease-related loci. At present, principal component analysis （PCA） has been proven to be an effective way to correct for population stratification. However, the conventional PCA algorithm is time-consuming when dealing with large datasets. We developed a Graphic processing unit （GPU）-based PCA software named SHEsisPCA （http：//***/***） that is highly parallel with a highest speedup greater than 100 compared with its CPU version. A cluster algorithm based on X-means was also implemented as a way to detect population subgroups and to obtain matched cases and controls in order to reduce the genomic inflation and increase the power. A study of both simulated and real datasets showed that SHEsisPCA ran at an extremely high speed while the accuracy was hardly reduced. Therefore, SHEsisPCA can help correct for population stratification much more efficiently than the conventional CPU-based algorithms.

关键词： Population stratification Principal component analysis Graphic processing unit Cluster Matched cases and controls Genetic studies

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Digital Forensics for Recoloring via Convolutional Neural Network

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Computers, Materials & Continua 2020年第1期62卷 1-16页

作者： Zhangyi shen Feng Ding Yunqing shi Electrical and Computer Engineering Department New Jersey Institute of Technology323 Martin Luther King BLVDNewark NJ 07102USA Computer Science Department State University of New York Albany1400 Washington AveAlbany NY 12222USA

As a common medium in our daily life,images are important for most people to gather *** are also people who edit or even tamper images to deliberately deliver false information under different ***,in digital forensics,it is necessary to understand the manipulating history of *** requires to verify all possible manipulations applied to *** all the image editing manipulations,recoloring is widely used to adjust or repaint the colors in *** color information is an important visual information that image can ***,it is necessary to guarantee the correctness of color in digital *** the other hand,many image retouching or editing applications or software are equipped with recoloring *** enables ordinary people without expertise of image processing to apply recoloring for ***,in order to secure the color information of images,in this paper,a recoloring detection method is *** method is based on convolutional neural network which is quite popular in recent *** the traditional linear classifier,the proposed method can be employed for binary classification as well as multiple labels *** classification performance of different structure for the proposed architecture is also investigated in this paper.

关键词： Image forensics machine learning convolutional neural network recoloring

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A scoping review of methodologies for applying artificial intelligence to physical activity interventions

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Journal of Sport and Health Science 2024年第3期13卷 428-441页

作者： Ruopeng An jing shen Junjie Wang Yuyi Yang Brown School Washington UniversitySt.LouisMO 63130USA Department of Physical Education China University of Geosciences BeijingBeijing 100083China School of Kinesiology and Health Promotion Dalian University of TechnologyDalian 116024China Division of Computational and Data Sciences Washington UniversitySt.LouisMO 63130USA

Purpose This scoping review aimed to offer researchers and practitioners an understanding of artificial intelligence(AI)applications in physical activity(PA)interventions;introduce them to prevalent machine learning(ML),deep learning(DL),and reinforcement learning(RL)algorithms;and encourage the adoption of AI *** A scoping review was performed in PubMed,Web of Science,Cochrane Library,and EBSCO focusing on AI applications for promoting PA or predicting related behavioral or health *** methodologies were summarized and categorized to identify synergies,patterns,and trends informing future ***,a concise primer on predominant AI methodologies within the realm of PA was provided to bolster understanding and broader *** The review included 24 studies that met the predetermined eligibility *** models were found effective in detecting significant patterns of PA behavior and associations between specific factors and intervention *** studies comparing AI models to traditional statistical approaches reported higher prediction accuracy for AI models on test *** of different AI models yielded mixed results,likely due to model performance being highly dependent on the dataset and *** increasing trend of adopting state-of-the-art DL and RL models over standard ML was observed,addressing complex human–machine communication,behavior modification,and decision-making *** key areas for future AI adoption in PA interventions emerged:personalized PA interventions,real-time monitoring and adaptation,integration of multimodal data sources,evaluation of intervention effectiveness,expanding access to PA interventions,and predicting and preventing *** The scoping review highlights the potential of AI methodologies for advancing PA *** the field progresses,staying informed and exploring emerging AI-driven strategies is essential for achieving significant improveme

关键词： Artificial intelligence Intervention Machine learning Neural network Physical activity

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Environmental impacts of domestic resource extraction in China

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Ecosystem Health and Sustainability 2019年第1期5卷 67-78,I0013页

作者： shen Zhao He-Ming Wang Wei-Qiang Chen Dong Yang jing-Ru Liu Feng shi State Environmental Protection Key Laboratory of Eco-Industry Northeastern UniversityShenyangChina Key Lab of Urban Environment and Health Institute of Urban EnvironmentChinese Academy of ScienceXiamenFujianChina Xiamen Key Lab of Urban Metabolism XiamenFujianChina SDAS Key Laboratory of Scientific Decision-Making Institute of Science and Technology for Development of ShandongQilu University of Technology(Shandong Academy of Sciences)JinanChina Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijingChina

Introduction:The rapid development of economy has led to extensive raw material consumption and relevant environmental damage in *** analyze environmental impacts and identify materials resulting in these environmental effects via raw material extraction,we combine economy-wide material flow accounting and life-cycle analysis methods to estimate environmental impacts of Chinese domestic extraction(DE)during the period of 1992–*** relationship between these increasing environmental impacts and Chinese GDP was also explored by decoupling ***:Results show that Chinese DE increased by 372%during 1992–*** global warming potential,abiotic depletion potential,and respiratory inorganics of Chinese DE increased by 195%,46%,and 408%,*** terms of specific materials,extraction of iron ores,gravel and sand,and coal induced the most environmental *** relationship between environmental impacts and Chinese GDP/DE was characterized by relative ***:To minimize the environmental impacts of extraction,we recommend that the Chinese government improve its extraction techniques and reduce excess demand for materials with large extraction such as iron ores,gravel and sand,and *** also recommend researching alternative materials for scarce resources like molybdenum,gold,and fluorite.

关键词： Decoupling analysis economy-wide material flow accounting life cycle assessment environmental impact material flows

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Noise level estimation method with application to EMD-based signal denoising

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Journal of Systems Engineering and Electronics 2016年第4期27卷 763-771页

作者： Xiaoyu Li jing Jin Yi shen Yipeng Liu School of Astronautics Harbin Institute of Technology College of Information Engineering Zhejiang University of Technology

This paper proposes a new signal noise level estimation approach by local regions. The estimated noise variance is applied as the threshold for an improved empirical mode decomposition（EMD） based signal denoising method. The proposed estimation method can effectively extract the candidate regions for the noise level estimation by measuring the correlation coefficient between noisy signal and a Gaussian filtered signal. For the improved EMD based method, the situation of decomposed intrinsic mode function（IMFs） which contains noise and signal simultaneously are taken into account. Experimental results from two simulated signals and an X-ray pulsar signal demonstrate that the proposed method can achieve better performance than the conventional EMD and wavelet transform（WT） based denoising methods.

关键词： signal denoising empirical mode decomposition(EMD) Gaussian filter correlation coefficient noise level estimation

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Interpretable learning of voltage for electrode design of multivalent metal-ion batteries

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npj Computational Materials 2022年第1期8卷 1654-1661页

作者： Xiuying Zhang Jun Zhou jing Lu Lei shen Department of Physics National University of Singapore2 Science Drive 3Singapore117551Singapore State Key Laboratory of Mesoscopic Physics and Department of Physics Peking University100871BeijingPeople’s Republic of China Institute of Materials Research&Engineering A*STAR(Agency for ScienceTechnology and Research)2 Fusionopolis WayInnovisSingapore138634Singapore Collaborative Innovation Center of Quantum Matter 100871BeijingPeople’s Republic of China Department of Mechanical Engineering National University of Singapore9 Engineering Drive 1Singapore117575Singapore

Deep learning(DL)has indeed emerged as a powerful tool for rapidly and accurately predicting materials properties from big data,such as the design of current commercial Li-ion ***,its practical utility for multivalent metal-ion batteries(MIBs),the most promising future solution of large-scale energy storage,is limited due to scarce MIB data availability and poor DL model ***,we develop an interpretable DL model as an effective and accurate method for learning electrode voltages of multivalent MIBs(divalent magnesium,calcium,zinc,and trivalent aluminum)at small dataset limits(150–500).Using the experimental results as validation,our model is much more accurate than machine-learning models,which usually are better than DL in the small dataset *** the high accuracy,our feature-engineering-free DL model is explainable,which automatically extracts the atom covalent radius as the most important feature for the voltage learning by visualizing vectors from the layers of the neural *** presented model potentially accelerates the design and optimization of multivalent MIB materials with fewer data and less domain-knowledge restriction and is implemented into a publicly available online tool kit in http://***/for the battery community.

关键词： electrode magnesium radius

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Orthogonal array design for the optimization of stripping Sr(Ⅱ) from ionic liquids using supercritical CO2

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Chinese Journal of Chemical Engineering 2017年第1期25卷 26-31页

作者： Tao Yang jing Fu Qingde Chen Xinghai shen Beijing National Laboratory for Molecular Sciences ( BNLMS) Fundamental Science on Radiochemisrry and Radiation Chemistry Laboratory College of Chemistry and Molecular EngineeringPeking University Beijing 100871 China

The strontium ions extracted from the aqueous phase into 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide(C_2mimNTf2) with dicyclohexyl-18-crown-6(DCH18C6) was stripped effectively by supercritical CO_2(sc-CO_2).Hexafluoroacetylacetone(HFAA)-acetonitrile was found to be an excellent modifier of sc-CO_2 to enhance the stripping *** the orthogonal array design(OAD),OA_(25)(5~5)matrix was employed to optimize the stripping of Sr(Ⅱ) from the DCH 18C6-C_2mimNTf_2 *** of five experimental factors:temperature,pressure,concentration of HFAA,static and dynamic extraction times as well as each factor at five-levels on the stripping of Sr(Ⅱ) were *** effects of these parameters were treated by the analysis of variance(ANOVA).The results showed that Sr(II) could be nearly 100%extracted from the IL phase at 308 K,30 MPa,40 min of dynamic extraction and 60 mmol·L^(-1) HFAA in acetonitrile,***,the stripping mechanism was studied by ESI-MS.

关键词： Supercritical CO2 stripping Ionic liquid Strontium Orthogonal array design

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Microtextural evolution of different TRC AA8006 alloy sections with homogenization

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International Journal of Minerals,Metallurgy and Materials 2015年第3期22卷 292-301页

作者： Zhong-wei Chen Long-fei shen jing Zhao State Key Laboratory of Solidification Processing Northwestern Polytechnical University

Grain microtexture evolution in twin-roll cast AA8006 alloy sheets subjected to different treatments was investigated using elec- tron backscatter diffraction. The textures of rolling-transverse and normal-transverse sections were characterized in original as-cast twin-roll casting and cold-rolled samples as well as samples homogenized at 500℃for 8 h and at 580℃ for 4 h. It is found that grains on both the rolling-transverse and normal-transverse sections of cold-rolled samples are made fmer by rolling deformation and coarsened after homog- enization. Annealing temperature has a stronger effect on the microstructural evolution than annealing time. The grain growth direction is parallel to the normal-transverse section, while grain deformation is more stable on the rolling direction than on the normal direction. The rolling orientations display more obvious anisotropy on the normal-transverse sections than on the rolling-transverse sections. Grain recrys- tallization and growth occur much easier on the normal-transverse section than on the rolling-transverse section for samples homogenized at 500℃ for 8 h. A special misorientation relationship between cold deformation texture, such as S orientation { 123 } 〈634〉 and cube orienta- tion 〈110〉Xaxis [cubic], and recrystallization texture after homogenization, such as R orientation { 124}〈211〉 and P orientation {011 }〈122〉, is observed.

关键词： aluminum alloys textures twin-roll casting homogenization

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Compressive Mechanical Characteristics of Multi-layered Gradient Hydroxyapatite Reinforced Poly(Vinyl Alcohol) Gel Biomaterial

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Journal of Materials Science & Technology 2013年第6期29卷 551-556页

作者： Yusong Pan Qianqian shen Chengling Pan jing Wang School of Materials Science and Engineering Anhui University of Science and TechnologyHuainan 232001China

Functional gradient materials provided us a new concept for artificial articular cartilage design with gradient component and gradient structure where one side of the material is high free water content thereby providing excellent lubrication function and the opposite side of the material is high hydroxyapatite content, thereby improving the bioactivity of the material and stimulating cell growth. The goal of the present study was to develop a multi-layered gradient HA/PVA gel biocomposites through layer-by-layer casting method combing with freeze/thaw cycle technology. The various influence factors on the compressive strength and modulus of the multi-layered gradient biocomposites were investigated. The results showed that the compressive mechanical characteristics of the biocomposites were similar to that of natural articular cartilage. Both the compressive strength and modulus of the multi-layered gradient HA/PVA gel biocomposites increased exponentially with the rise of compressive strain ratio. Both the compressive strength and average compressive modulus of the biocomposites improved with the rise of freeze/thaw cycle times and total concentration of HA particles in the biocomposites, but they showed decreasing tendency with the rise of HA concentration difference between adjacent layers.

关键词： Multi-layered gradient HA/PVA gel biocomposites Freeze/thaw cycle times Strength Modulus

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