As an indispensable part of identity authentication,offline writer identification plays a notable role in biology,forensics,and historical document analysis.However,identifying handwriting efficiently,stably,and quick...As an indispensable part of identity authentication,offline writer identification plays a notable role in biology,forensics,and historical document analysis.However,identifying handwriting efficiently,stably,and quickly is still challenging due to the method of extracting and processing handwriting features.In this paper,we propose an efficient system to identify writers through handwritten images,which integrates local and global features from similar handwritten images.The local features are modeled by effective aggregate processing,and global features are extracted through transfer learning.Specifically,the proposed system employs a pre-trained Residual Network to mine the relationship between large image sets and specific handwritten images,while the vector of locally aggregated descriptors with double power normalization is employed in aggregating local and global features.Moreover,handwritten image segmentation,preprocessing,enhancement,optimization of neural network architecture,and normalization for local and global features are exploited,significantly improving system performance.The proposed system is evaluated on Computer Vision Lab(CVL)datasets and the International Conference on Document Analysis and Recognition(ICDAR)2013 datasets.The results show that it represents good generalizability and achieves state-of-the-art performance.Furthermore,the system performs better when training complete handwriting patches with the normalization method.The experimental result indicates that it’s significant to segment handwriting reasonably while dealing with handwriting overlap,which reduces visual burstiness.展开更多
Loquat(Eriobotrya japonica Lindl.)is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components.Confirming suitable reference genes for a set of loquat samples before qRT-...Loquat(Eriobotrya japonica Lindl.)is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components.Confirming suitable reference genes for a set of loquat samples before qRT-PCR experiments is essential for the accurate quantification of gene expression.In this study,eight candidate reference genes were selected from our previously published RNA-seq data,and primers for each candidate reference gene were designed and evaluated.The Cq values of the candidate reference genes were calculated by RT-qPCR in 31 different loquat samples,including 12 subgroups of developing or abiotic-stressed tissues.Different combinations of stable reference genes were screened according to a comprehensive rank,which was synthesized from the results of four algorithms,including the geNorm,NormFinder,BestKeeper andΔCt methods.The screened reference genes were verified by normalizing EjLGA1 in each subgroup.The obtained suitable combinations of reference genes for accurate normalization were GAPDH,EF1αand ACT for floral development;GAPDH,UBCE and ACT for fruit setting;EF1α,GAPDH and eIF2B for fruit ripening;ACT,EF1αand UBCE for leaves under heat stress;eIF2B,UBCE and EF1αfor leaves under freezing stress;EF1α,TUA and UBCE for leaves under salt stress;ACT,EF1αand eIF2B for immature pulp under freezing stress;ACT,UBCE and eIF2B for immature seeds under freezing stress;EF1α,eIF2B and UBCE for both immature pulp and seeds under freezing stress;UBCE,TUB and TUA for red-fleshed fruits under cold-storage stress;eIF2B,RPS3 and TUB for white-fleshed fruits under coldstorage stress;and eIF2B,UBCE and RPS3 for both red-and white-fleshed fruits under cold-storage stress.This study obtained different combinations of stable reference genes for accurate normalization in twelve subgroups of developing or abiotic-stressed tissues in loquat.To our knowledge,this is the first report to obtain stable reference genes for normalizing gene expression of abiotic-stressed tissues in E.japonica.The use of the three most stable reference genes could increase the reliability of future quantification experiments.展开更多
Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has ...Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.展开更多
Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are i...Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.展开更多
基金supported in part by the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX 20_0758in part by the Science and Technology Research Project of Jiangsu Public Security Department under Grant 2020KX005+1 种基金in part by the General Project of Philosophy and Social Science Research in Colleges and Universities in Jiangsu Province under Grant 2022SJYB0473in part by“Cyberspace Security”Construction Project of Jiangsu Provincial Key Discipline during the“14th Five Year Plan”.
文摘As an indispensable part of identity authentication,offline writer identification plays a notable role in biology,forensics,and historical document analysis.However,identifying handwriting efficiently,stably,and quickly is still challenging due to the method of extracting and processing handwriting features.In this paper,we propose an efficient system to identify writers through handwritten images,which integrates local and global features from similar handwritten images.The local features are modeled by effective aggregate processing,and global features are extracted through transfer learning.Specifically,the proposed system employs a pre-trained Residual Network to mine the relationship between large image sets and specific handwritten images,while the vector of locally aggregated descriptors with double power normalization is employed in aggregating local and global features.Moreover,handwritten image segmentation,preprocessing,enhancement,optimization of neural network architecture,and normalization for local and global features are exploited,significantly improving system performance.The proposed system is evaluated on Computer Vision Lab(CVL)datasets and the International Conference on Document Analysis and Recognition(ICDAR)2013 datasets.The results show that it represents good generalizability and achieves state-of-the-art performance.Furthermore,the system performs better when training complete handwriting patches with the normalization method.The experimental result indicates that it’s significant to segment handwriting reasonably while dealing with handwriting overlap,which reduces visual burstiness.
基金funded by the Natural Science Foundation of Fujian Province(2021J05240)Fujian Provincial Science and Technology Project(2021N5014,2022N5006)+1 种基金Research Project of Putian Science and Technology Bureau(2021ZP08,2021ZP09,2021ZP10,2021ZP11)Scientific Research Project of Putian University(2018064).
文摘Loquat(Eriobotrya japonica Lindl.)is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components.Confirming suitable reference genes for a set of loquat samples before qRT-PCR experiments is essential for the accurate quantification of gene expression.In this study,eight candidate reference genes were selected from our previously published RNA-seq data,and primers for each candidate reference gene were designed and evaluated.The Cq values of the candidate reference genes were calculated by RT-qPCR in 31 different loquat samples,including 12 subgroups of developing or abiotic-stressed tissues.Different combinations of stable reference genes were screened according to a comprehensive rank,which was synthesized from the results of four algorithms,including the geNorm,NormFinder,BestKeeper andΔCt methods.The screened reference genes were verified by normalizing EjLGA1 in each subgroup.The obtained suitable combinations of reference genes for accurate normalization were GAPDH,EF1αand ACT for floral development;GAPDH,UBCE and ACT for fruit setting;EF1α,GAPDH and eIF2B for fruit ripening;ACT,EF1αand UBCE for leaves under heat stress;eIF2B,UBCE and EF1αfor leaves under freezing stress;EF1α,TUA and UBCE for leaves under salt stress;ACT,EF1αand eIF2B for immature pulp under freezing stress;ACT,UBCE and eIF2B for immature seeds under freezing stress;EF1α,eIF2B and UBCE for both immature pulp and seeds under freezing stress;UBCE,TUB and TUA for red-fleshed fruits under cold-storage stress;eIF2B,RPS3 and TUB for white-fleshed fruits under coldstorage stress;and eIF2B,UBCE and RPS3 for both red-and white-fleshed fruits under cold-storage stress.This study obtained different combinations of stable reference genes for accurate normalization in twelve subgroups of developing or abiotic-stressed tissues in loquat.To our knowledge,this is the first report to obtain stable reference genes for normalizing gene expression of abiotic-stressed tissues in E.japonica.The use of the three most stable reference genes could increase the reliability of future quantification experiments.
文摘Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.
基金the National Natural Science Foundation of China under contract Nos 42090043 and 41876074the National Basic Research Program(973 Program)of China under contract No.2014CB441502.
文摘Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.
