Background:Digital hemispherical photography(DHP)is widely used to estimate the leaf area index(LAI)of forest plots due to its advantages of high efficiency and low cost.A crucial step in the LAI estimation of forest ...Background:Digital hemispherical photography(DHP)is widely used to estimate the leaf area index(LAI)of forest plots due to its advantages of high efficiency and low cost.A crucial step in the LAI estimation of forest plots via DHP is choosing a sampling scheme.However,various sampling schemes involving DHP have been used for the LAI estimation of forest plots.To date,the impact of sampling schemes on LAI estimation from DHP has not been comprehensively investigated.Methods:In this study,13 commonly used sampling schemes which belong to five sampling types(i.e.dispersed,square,cross,transect and circle)were adopted in the LAI estimation of five Larix principis-rupprechtii plots(25m×25 m).An additional sampling scheme(with a sample size of 89)was generated on the basis of all the sample points of the 13 sampling schemes.Three typical inversion models and four canopy element clumping index(Ωe)algorithms were involved in the LAI estimation.The impacts of the sampling schemes on four variables,including gap fraction,Ωe,effective plant area index(PAIe)and LAI estimation from DHP were analysed.The LAI estimates obtained with different sampling schemes were then compared with those obtained from litter collection measurements.Results:Large differences were observed for all four variable estimates(i.e.gap fraction,Ωe,PAIe and LAI)under different sampling schemes.The differences in impact of sampling schemes on LAI estimation were not obvious for the three inversion models,if the fourΩe algorithms,except for the traditional gap-size analysis algorithm were adopted in the estimation.The accuracy of LAI estimation was not always improved with an increase in sample size.Moreover,results indicated that with the appropriate inversion model,Ωe algorithm and sampling scheme,the maximum estimation error of DHP-estimated LAI at elementary sampling unit can be less than 20%,which is required by the global climate observing system,except in forest plots with extremely large LAI values(~>6.0).However,obtaining an LAI from DHP with an estimation error lower than 5%is impossible regardless of which combination of inversion model,Ωe algorithm and sampling scheme is used.Conclusion:The LAI estimation of L.principis-rupprechtii forests from DHP was largely affected by the sampling schemes adopted in the estimation.Thus,the sampling scheme should be seriously considered in the LAI estimation.One square and two transect sampling schemes(with sample sizes ranging from 3 to 9)were recommended to be used to estimate the LAI of L.principis-rupprechtii forests with the smallest mean relative error(MRE).By contrast,three cross and one dispersed sampling schemes were identified to provide LAI estimates with relatively large MREs.展开更多
Mechanoluminescence has attracted increasing attentions because it can convert the kinetic energy during human daily motions into light to be used in sensors and displays. However, its practical applications are still...Mechanoluminescence has attracted increasing attentions because it can convert the kinetic energy during human daily motions into light to be used in sensors and displays. However, its practical applications are still hindered by the weak brightness and limited color while under large forces. Herein, we developed novel piezoluminescent devices(PLDs) which could effectively emit visible light under low pressing forces through the stress-concentration and enhancing deformation on the basis of carefully-designed array structures. The emitting colors were also tunable by using bilayer luminescent film under different pressures. This work not only provides a new strategy to effectively harvest mechanical energy into light,but also presents a scalable, low-cost and color-tunable PLD which shows great potentials in various applications such as luminescent floors, shoes and stress-activated displays.展开更多
Interferon-γ （IFN-γ） triggers macrophage for inflammation response by activating the intracellular JAK-STAT1 signaling. Suppressor of cytokine signaling 1 （SOCS1） and protein tyrosine phosphatases can negatively...Interferon-γ （IFN-γ） triggers macrophage for inflammation response by activating the intracellular JAK-STAT1 signaling. Suppressor of cytokine signaling 1 （SOCS1） and protein tyrosine phosphatases can negatively modulate IFN-γ signaling. Here, we identify a novel negative feedback loop mediated by STAT3-SOCS3, which is tightly controlled by SENP1 via de-SUMOylation of protein tyrosine phosphatase 1B （PTPIB）, in IFN-y signaling. SENP1-deficient macrophages show defects in IFN-γ signaling and M1 macrophage activation. PTP1B in SENP1-deficient macrophages is highly SUMOylated, which reduces PTP1B-induced de-phosphorylation of STAT3. Activated STAT3 then suppresses STAT1 activation via SOCS3 induction in SENP1-deficient macro- phages. Accordingly, SENP1-deficient macrophages show reduced ability to resist Listerio rnonocytogenes infection. These results reveal a crucial role of SENP1-controlled STAT1 and STAT3 balance in rnacrophage polarization.展开更多
The vagina contains at least a billion microbial cells,dominated by lactobacilli.Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age,as w...The vagina contains at least a billion microbial cells,dominated by lactobacilli.Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age,as well as cervical,fecal,and salivary samples from a second cohort of 632 women.Factors such as pregnancy history,delivery history,cesarean section,and breastfeeding were all more important than menstrual cycle in shaping the microbiome,and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data.Greater proportion of Bifidobacterium breve was seen with older age at sexual debut.The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history.Potential markers for lack of menstrual regularity,heavy flow,dysmenorrhea,and contraceptives were also identified.Lactobacilli were rare during breastfeeding or post-menopause.Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome.Gut and salivary microbiomes,plasma vitamins,metals,amino acids,and hormones showed associations with the vagino-cervical microbiome.Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.展开更多
We propose a linear mapping relationship between the polarization of the fundamental mode and the cylindrical vector(CV)modes on the first-order Poincaresphere(FOPS)in fiber.The new method is based on the fourdimensio...We propose a linear mapping relationship between the polarization of the fundamental mode and the cylindrical vector(CV)modes on the first-order Poincaresphere(FOPS)in fiber.The new method is based on the fourdimensional complex Jones matrices in terms of the linearly polarized mode bases.With our theoretical model,an all-fiber approach to generate arbitrary CV beams on the FOPS is proposed theoretically and verified experimentally.In the experiment,through the combination of a mode converter and a two-segment cascaded few-mode fiber with fixed stresses,it is possible to generate all CV modes on the FOPS by only adjusting the polarization of the fundamental mode.The Stokes parameters of the output light are measured to verify our scheme,which shows good agreement with the theoretical prediction.The method may provide a convenient way to generate CV beams and evolve the polarization states in any path on the FOPS,which is expected to have potential applications in encoding information and quantum computation.展开更多
This paper presents a novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder(DCAE)for small negative samples.The proposed DCAE scheme combines the advantages of supervised learning and unsupe...This paper presents a novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder(DCAE)for small negative samples.The proposed DCAE scheme combines the advantages of supervised learning and unsupervised learning.In order to reduce the high cost of training Deep Neural Networks,this paper pre-trained the Convolutional Neural Networks(CNN)through open labelled datasets.Through transferring learning,the encoder part of the traditional Convolutional Auto-Encoder was replaced by the first three layers of the CNN,and a small number of defect samples were used to fine-tune the parameters.A threshold discrimination scheme was designed to evaluate the model detection,realising the self-explosion detection of insulator by judging the residual result and abnormal score.The experimental results show that compared with the existing insulator self-explosion detection schemes,the proposed scheme can reduce the model training time by up to 40%,and the recognition accuracy can reach 97%.Moreover,this model does not need a large number of insulator labelled data and is especially suitable for small negative sample application.展开更多
基金the National Science Foundation of China(Grant Nos.41871233,41371330 , 41001203).
文摘Background:Digital hemispherical photography(DHP)is widely used to estimate the leaf area index(LAI)of forest plots due to its advantages of high efficiency and low cost.A crucial step in the LAI estimation of forest plots via DHP is choosing a sampling scheme.However,various sampling schemes involving DHP have been used for the LAI estimation of forest plots.To date,the impact of sampling schemes on LAI estimation from DHP has not been comprehensively investigated.Methods:In this study,13 commonly used sampling schemes which belong to five sampling types(i.e.dispersed,square,cross,transect and circle)were adopted in the LAI estimation of five Larix principis-rupprechtii plots(25m×25 m).An additional sampling scheme(with a sample size of 89)was generated on the basis of all the sample points of the 13 sampling schemes.Three typical inversion models and four canopy element clumping index(Ωe)algorithms were involved in the LAI estimation.The impacts of the sampling schemes on four variables,including gap fraction,Ωe,effective plant area index(PAIe)and LAI estimation from DHP were analysed.The LAI estimates obtained with different sampling schemes were then compared with those obtained from litter collection measurements.Results:Large differences were observed for all four variable estimates(i.e.gap fraction,Ωe,PAIe and LAI)under different sampling schemes.The differences in impact of sampling schemes on LAI estimation were not obvious for the three inversion models,if the fourΩe algorithms,except for the traditional gap-size analysis algorithm were adopted in the estimation.The accuracy of LAI estimation was not always improved with an increase in sample size.Moreover,results indicated that with the appropriate inversion model,Ωe algorithm and sampling scheme,the maximum estimation error of DHP-estimated LAI at elementary sampling unit can be less than 20%,which is required by the global climate observing system,except in forest plots with extremely large LAI values(~>6.0).However,obtaining an LAI from DHP with an estimation error lower than 5%is impossible regardless of which combination of inversion model,Ωe algorithm and sampling scheme is used.Conclusion:The LAI estimation of L.principis-rupprechtii forests from DHP was largely affected by the sampling schemes adopted in the estimation.Thus,the sampling scheme should be seriously considered in the LAI estimation.One square and two transect sampling schemes(with sample sizes ranging from 3 to 9)were recommended to be used to estimate the LAI of L.principis-rupprechtii forests with the smallest mean relative error(MRE).By contrast,three cross and one dispersed sampling schemes were identified to provide LAI estimates with relatively large MREs.
基金supported by the National Key R&D Program of China (2016YFA0203302)the National Natural Science Foundation of China (21634003, 51573027, 51673043, 21604012, 21805044, 21875042, 11602058, and 11872150)+3 种基金Shanghai Science and Technology Committee (16JC1400702, 17QA1400400, 18QA1400700, and 18QA1400800)Shanghai Municipal Education Commission (2017-01-07-00-07-E00062)Shanghai Chenguang Program (16CG01)Yanchang Petroleum Group
文摘Mechanoluminescence has attracted increasing attentions because it can convert the kinetic energy during human daily motions into light to be used in sensors and displays. However, its practical applications are still hindered by the weak brightness and limited color while under large forces. Herein, we developed novel piezoluminescent devices(PLDs) which could effectively emit visible light under low pressing forces through the stress-concentration and enhancing deformation on the basis of carefully-designed array structures. The emitting colors were also tunable by using bilayer luminescent film under different pressures. This work not only provides a new strategy to effectively harvest mechanical energy into light,but also presents a scalable, low-cost and color-tunable PLD which shows great potentials in various applications such as luminescent floors, shoes and stress-activated displays.
文摘Interferon-γ （IFN-γ） triggers macrophage for inflammation response by activating the intracellular JAK-STAT1 signaling. Suppressor of cytokine signaling 1 （SOCS1） and protein tyrosine phosphatases can negatively modulate IFN-γ signaling. Here, we identify a novel negative feedback loop mediated by STAT3-SOCS3, which is tightly controlled by SENP1 via de-SUMOylation of protein tyrosine phosphatase 1B （PTPIB）, in IFN-y signaling. SENP1-deficient macrophages show defects in IFN-γ signaling and M1 macrophage activation. PTP1B in SENP1-deficient macrophages is highly SUMOylated, which reduces PTP1B-induced de-phosphorylation of STAT3. Activated STAT3 then suppresses STAT1 activation via SOCS3 induction in SENP1-deficient macro- phages. Accordingly, SENP1-deficient macrophages show reduced ability to resist Listerio rnonocytogenes infection. These results reveal a crucial role of SENP1-controlled STAT1 and STAT3 balance in rnacrophage polarization.
文摘The vagina contains at least a billion microbial cells,dominated by lactobacilli.Here we perform metagenomic shotgun sequencing on cervical and fecal samples from a cohort of 516 Chinese women of reproductive age,as well as cervical,fecal,and salivary samples from a second cohort of 632 women.Factors such as pregnancy history,delivery history,cesarean section,and breastfeeding were all more important than menstrual cycle in shaping the microbiome,and such information would be necessary before trying to interpret differences between vagino-cervical microbiome data.Greater proportion of Bifidobacterium breve was seen with older age at sexual debut.The relative abundance of lactobacilli especially Lactobacillus crispatus was negatively associated with pregnancy history.Potential markers for lack of menstrual regularity,heavy flow,dysmenorrhea,and contraceptives were also identified.Lactobacilli were rare during breastfeeding or post-menopause.Other features such as mood fluctuations and facial speckles could potentially be predicted from the vagino-cervical microbiome.Gut and salivary microbiomes,plasma vitamins,metals,amino acids,and hormones showed associations with the vagino-cervical microbiome.Our results offer an unprecedented glimpse into the microbiota of the female reproductive tract and call for international collaborations to better understand its long-term health impact other than in the settings of infection or pre-term birth.
基金National Natural Science Foundation of China(61875019,61675034,61875020,61571067)Fund of State Key Laboratory of IPOC(BUPT)Fundamental Research Funds for the Central Universities.
文摘We propose a linear mapping relationship between the polarization of the fundamental mode and the cylindrical vector(CV)modes on the first-order Poincaresphere(FOPS)in fiber.The new method is based on the fourdimensional complex Jones matrices in terms of the linearly polarized mode bases.With our theoretical model,an all-fiber approach to generate arbitrary CV beams on the FOPS is proposed theoretically and verified experimentally.In the experiment,through the combination of a mode converter and a two-segment cascaded few-mode fiber with fixed stresses,it is possible to generate all CV modes on the FOPS by only adjusting the polarization of the fundamental mode.The Stokes parameters of the output light are measured to verify our scheme,which shows good agreement with the theoretical prediction.The method may provide a convenient way to generate CV beams and evolve the polarization states in any path on the FOPS,which is expected to have potential applications in encoding information and quantum computation.
基金Outstanding Youth Fund Project of Jiangxi Natural Science Foundation,Grant/Award Number:20202ACBL214021National Natural Science Foundation of China,Grant/Award Number:52167008,51867010+1 种基金Science and Technology Project of Education Department of Jiangxi Province,Grant/Award Number:GJJ210650Key Research and Development Program of Jiangxi Province,Grant/Award Number:20202BBGL73098。
文摘This paper presents a novel insulator defect detection scheme based on Deep Convolutional Auto-Encoder(DCAE)for small negative samples.The proposed DCAE scheme combines the advantages of supervised learning and unsupervised learning.In order to reduce the high cost of training Deep Neural Networks,this paper pre-trained the Convolutional Neural Networks(CNN)through open labelled datasets.Through transferring learning,the encoder part of the traditional Convolutional Auto-Encoder was replaced by the first three layers of the CNN,and a small number of defect samples were used to fine-tune the parameters.A threshold discrimination scheme was designed to evaluate the model detection,realising the self-explosion detection of insulator by judging the residual result and abnormal score.The experimental results show that compared with the existing insulator self-explosion detection schemes,the proposed scheme can reduce the model training time by up to 40%,and the recognition accuracy can reach 97%.Moreover,this model does not need a large number of insulator labelled data and is especially suitable for small negative sample application.
