The morphological and functional characteristics of neurons are quite varied and complex. There is a need for a comprehensive approach for distinguishing and classifying neurons. Similar to the biological species clas...The morphological and functional characteristics of neurons are quite varied and complex. There is a need for a comprehensive approach for distinguishing and classifying neurons. Similar to the biological species classification system, this study proposes a morphological classification system for neurons based on principal component analysis. Based on four principal components of neuronal morphology derived from principal component analysis, a nomenclature system for neurons was obtained. This system can accurately distinguish between the same type of neuron from different species.展开更多
A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a loc...A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a local area but ignore the morphological characteristics of the peak area.This paper proposes three indices based on the morphological characteristics of peaks and their spatial relationship with ridge lines:convexity mean index(CM-index),convexity standard deviation(CSD-index),and convexity imbalance index(CIBindex).We develop computation methods to extract peaks from digital elevation model(DEM).Subsequently,the initial peaks extracted by neighborhood statistics are classified using the proposed indices.The method is evaluated in the Qinghai Tibet Plateau and the Loess Plateau in China.An ASTER Global DEM(ASTGTM2 DEM)with a grid size of 30 m is chosen to assess the suitability of the proposed mountain peak extraction and classification method in different geomorphic regions.DEM data with grid sizes of 30 m and 5 m are used for the Loess Plateau.The mountain peak extraction and classification results obtained from the different resolution DEM are compared.The experimental results show that:(1)The CM-index and the CSDindex accurately reflect the concave or convex morphology of the surface and can be used as supplements to existing surface morphological indices.(2)The three indices can identify pseudo mountain peaks and classify the remaining peaks into single ridge peak(SR-Peak)and multiple ridge intersection peak(MRI-Peak).The visual inspection results show that the classification accuracy in the different study areas exceeds 75%.(3)The number of peaks is significantly higher for the 5 m DEM than for the 30 m DEM because more peaks can be detected at a finer resolution.展开更多
Automatic diagnosis may help to decrease human based diagnosis error and assist physicians to focus on the correct disease and its treatment and to avoid wasting time on diagnosis. In this paper computer aided diagnos...Automatic diagnosis may help to decrease human based diagnosis error and assist physicians to focus on the correct disease and its treatment and to avoid wasting time on diagnosis. In this paper computer aided diagnosis is applied to the brain CT image processing. We compared performance of morphological operations in extracting three types of features, i.e. gray scale, symmetry and texture. Some classifiers were applied to classify normal and abnormal brain CT images. It showed that morphological operations can improve the result of accuracy. Moreover SVM classifier showed better result than other classifiers.展开更多
The Cheng index distinguishes indica andjaponica rice based on six taxonomic traits.This index has been widely used for classifi- cation of indica and japonica varieties in China.In this study,a double haploid(DH)popu...The Cheng index distinguishes indica andjaponica rice based on six taxonomic traits.This index has been widely used for classifi- cation of indica and japonica varieties in China.In this study,a double haploid(DH)popula-tion derived from anther culture of ZYQ8/JX17 F,a typical inter-subspecies hybrid,was used to investigate the six taxonomictraits,i.e.leaf hairiness(LH),color of hullwhen heading(CHH),hairiness of hull(HH),length of the first and second panicle internode(LPI),length/width of grain(L/W),andphenol reaction(PH).The morphological in- dex(MI)was also calculated.Based on themolecular linkage map constructed from this展开更多
The hidden dimension of the urban morphology is the underlying the urban morphological rules system.The number of these rules has increased and their application tends to become more complex.The urban morphosis based ...The hidden dimension of the urban morphology is the underlying the urban morphological rules system.The number of these rules has increased and their application tends to become more complex.The urban morphosis based digital approaches tends to become widespread.However,achieving the target values for all the rules is difficult.This impacts the social,environmental and aesthetic objectives of these rules.This paper proposes a classification of urban morphological rules to assist the digital morphosis of urban form.The aim is to endow the system of rules with a hierarchy,which can make efficient the automatic generation of the urban forms respectful of the urban law.Thus,this work promotes the concerns of artificial intelligence in urban morphology.展开更多
The name of Vertisol is derived from Latin “vertere” meaning to invert. This case restricts development of soil horizons in profile. These soils have the capacity to swell and shrink, inducing cracks in the upper pa...The name of Vertisol is derived from Latin “vertere” meaning to invert. This case restricts development of soil horizons in profile. These soils have the capacity to swell and shrink, inducing cracks in the upper parts of the soil and distinctive soil structure throughout the soil. The formation of these specific features are caused by a heavy texture, a dominance of swelling clay in the fine fraction and marked changes in moisture content. The swell-shrink behavior is attributed to the wetting and drying of the soil mass. In this study, morphology, physico-chemical characteristics and classification of vertisols that were formed on alluvial delta plains, were investigated. Those soils formed on the Bafra Plain found in the K?z?l?rmak Delta and located in the central Black Sea region of Turkey. All studied Vertisols are characterised by a dark colour in surface soil, a heavy clayey texture, hardpan formation under top soil (high bulk density a high compaction) and very high COLE values. In addition, they have deep wide-opened desiccation cracks at the surface, slickensides at the middle part of the profiles and a poor differentiation of their horizons. Physico-chemically, the studied soils are slightly basic to very basic, non-saline and poor in organic matter, which is slightly higher in the surface horizon. In addition, cation exchange capacity, sum of exchangeable bases and base saturation of soils are very high. On the basis of morphological and physicochemical analysis, soil profiles were classified as Sodic Haplustert, Typic Calciaquert, Sodic Calciustert according to Soil Taxonomy (Soil Survey Staff, 1975 and 1999) and as Sodic Vertisol and Calcic Vertisol according to FAO/ISRIC (2006) classification systems.展开更多
High-resolution hyper-spectral image (HHR) provides both detailed structural and spectral information for urban study. However, due to the inherent correlation between spectral bands and within-class variability in th...High-resolution hyper-spectral image (HHR) provides both detailed structural and spectral information for urban study. However, due to the inherent correlation between spectral bands and within-class variability in the data, the data processing of HHR is a challenging work. In this paper, based on spectral mixture analysis theory, a new stack of parts description features were extracted, and then incorporated with a stack of morphology based spatial features. Partially supervised constrained energy minimization (CEM) and unsupervised nonnegative matrix factorization (NMF) were used to extract the part-features. The joint features were then integrated by SVM classifier. The advantages of this method are the representation of physical composition of the urban area by the parts-features and the show of multi-scale structure information by morphology profiles. Experiments with an airborne hyper-spectral data flightline over the Washington DC Mall were performed, and the performance of the proposed algorithm was evaluated in comparison with well-known nonparametric weighted feature extraction (NWFE) and feature selection method. The results shown that the proposed features-joint scheme consistently outperforms the traditional methods, and so can provide an effective option for processing HHR data in urban area.展开更多
Soybean leaf morphology is one of the most important morphological and biological characteristics of soybean.The germplasm gene differences of soybeans can lead to different phenotypic traits,among which soybean leaf ...Soybean leaf morphology is one of the most important morphological and biological characteristics of soybean.The germplasm gene differences of soybeans can lead to different phenotypic traits,among which soybean leaf morphology is an important parameter that directly reflects the difference in soybean germplasm.To realize the morphological classification of soybean leaves,a method was proposed based on deep learning to automatically detect soybean leaves and classify leaf morphology.The morphology of soybean leaves included lanceolate,oval,ellipse and round.First,an image collection platform was designed to collect images of soybean leaves.Then,the feature pyramid networks–single shot multibox detector(FPN-SSD)model was proposed to detect the top leaflets of soybean leaves on the collected images.Finally,a classification model based on knowledge distillation was proposed to classify different morphologies of soybean leaves.The obtained results indicated an overall classification accuracy of 0.956 over a private dataset of 3200 soybean leaf images,and the accuracy of classification for each morphology was 1.00,0.97,0.93 and 0.94.The results showed that this method could effectively classify soybean leaf morphology and had great application potential in analyzing other phenotypic traits of soybean.展开更多
The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphologic...The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphological structures and Land Surface Temperature(LST)characteristics,these two types of characteristics have rarely been fully integrated and used for functional area classification.In this paper,a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features.First,metrics are constructed from three levels,namely,building,road and region,which are used to portray urban morphology;LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics:the average temperature,maximum temperature,temperature difference and standard deviation of temperature.Then,the functional areas are classified into four categories:service/public land,commercial land,residential land and industrial land.A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas.The effectiveness of the proposed framework is tested in the study area of Shenzhen City,Guangdong Province.The results show that the combined classification accuracy of the proposed classification method is 0.85,which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features.The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification.展开更多
To classify the Chinese wintersweet（Chimonanthus praecox） cultivars and to study their evolution based on pollen morphology.Pollens of 12 representative wintersweet cultivars were examined by scanning electron micro...To classify the Chinese wintersweet（Chimonanthus praecox） cultivars and to study their evolution based on pollen morphology.Pollens of 12 representative wintersweet cultivars were examined by scanning electron microscopy（SEM）.Q-cluster analysis was carried out based on the observation results.Results are as follows：（1） The pollen grains were 2lobed circular in polar view,elliptic in equatorial view.The pollen shapes were spheroidal or super-spheroidal by P/E（polar axis length/equatorial axis length） criteria.（2） According to pollen exine ornamentation,it was indicated that white wintersweet is most original.Yellow floral group could be classified into three subgroups：purple-hearted,halo-hearted and yellow-hearted type.Their evolutionary relationship was purple-hearted halo-hearted yellow-hearted.（3） Different wintersweet cultivars showed a different exine sculpture.Palynological analysis could be used in the classification of wintersweet cultivars.The result of cluster analysis indicated that the cultivars could be classified into three groups with a similarity coefficient of 0.41.Each group had similar pollen exine sculpture.It was found that the palynological classification coincided well with morphological classification.Our results support the suggestion that purple streaks or patches of inner-petals should be served as the first-order criteria in wintersweet classification.展开更多
Morphologic characteristic and classification description of female octopus Pareledone turqueti collected by R/V Xuelong during the 22nd Expedition in the Antarctic waters is discussed.The results indicate that this s...Morphologic characteristic and classification description of female octopus Pareledone turqueti collected by R/V Xuelong during the 22nd Expedition in the Antarctic waters is discussed.The results indicate that this species belongs to suborder Incirrina,Family Octopodidae,Subfamily Eledoninae,Genus Pareledone,Pareledone turqueti.It is characterized by having soft and smooth skin without papillae,funnel organ VV-shaped,crop,ink sac,anterior and posterior salivary gland present,developed radulae with 7 small heterodont teeth,gills with 7 lamellae on the inner and outer demibranch respectively.Arms moderate with uniserial suckers no enlarged,arm formula is Ⅱ=III.I=IV,web formula is c=d.e.b.a.展开更多
The classification of seedlings is important to ensure the viability of seedlings after transplantation and is acknowledged as a key factor in forestation and environmental improvement. Based on numerous papers on aut...The classification of seedlings is important to ensure the viability of seedlings after transplantation and is acknowledged as a key factor in forestation and environmental improvement. Based on numerous papers on automatic seedling classification (ASC), the seedling grading theory, traditional grading methods, the background and the proceeding of ASC techniques are described. The automation of the measurement of seedling morphological characteristics by photoelectric meters and computer vision is studied, and the automatic methods of the current grading systems are described respectively. And the further researches on ASC by computer vision are proposed.展开更多
Living gymnosperms comprise four major groups:cycads,Ginkgo,conifers,and gnetophytes.Relationships among/within these lineages have not been fully resolved.Next generation sequencing has made available a large number ...Living gymnosperms comprise four major groups:cycads,Ginkgo,conifers,and gnetophytes.Relationships among/within these lineages have not been fully resolved.Next generation sequencing has made available a large number of sequences,including both plastomes and single-copy nuclear genes,for reconstruction of solid phylogenetic trees.Recent advances in gymnosperm phylogenomic studies have updated our knowledge of gymnosperm systematics.Here,we review major advances of gymnosperm phylogeny over the past 10 years and propose an updated classification of extant gymnosperms.This new classification includes three classes(Cycadopsida,Ginkgoopsida,and Pinopsida),five subclasses(Cycadidae,Ginkgoidae,Cupressidae,Pinidae,and Gnetidae),eight orders(Cycadales,Ginkgoales,Araucariales,Cupressales,Pinales,Ephedrales,Gnetales,and Welwitschiales),13 families,and 86 genera.We also described six new tribes including Acmopyleae Y.Yang,Austrocedreae Y.Yang,Chamaecyparideae Y.Yang,Microcachrydeae Y.Yang,Papuacedreae Y.Yang,and Prumnopityeae Y.Yang,and made 27 new combinations in the genus Sabina.展开更多
Region-Growing Algorithms （RGAs） are used to grade the quality of manufactured wood flooring. Traditional RGAs are hampered by prob- lems of long segmentation time and low inspection accuracy caused by neighborhood ...Region-Growing Algorithms （RGAs） are used to grade the quality of manufactured wood flooring. Traditional RGAs are hampered by prob- lems of long segmentation time and low inspection accuracy caused by neighborhood search. We used morphological reconstruction with the R com- ponent to construct a novel flaw segmentation method. We initially designed two template images for low and high thresholds, and these were used for seed optimization and inflation growth, respectively. Then the extraction of the flaw skeleton from the low threshold image was realized by applying the erosion termination rules. The seeds in the flaw skeleton were optimized by the pruning method. The geodesic inflection was applied by the high threshold template to realize rapid growth of the flaw area in the floor plate, and region filling and pruning operations were applied for margin optimization. Experi- ments were conducted on 512×512, 256×256 and 128×128 pixel sizes, re- spectively. The 256×256 pixel size proved superior in time-consumption at 0.06 s with accuracy of 100%. But with the region-growing method the same process took 0.22 s with accuracy of 70%. Compared with RGA, our pro- posed method can realize more accurate segmentation, and the speed and accuracy of segmentation can satisfy the requirements for on-line grading of wood flooring.展开更多
BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy viaendoscopic observation is subject to sampling error and interobserver variability.The Kimura-Takemoto classification system was ...BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy viaendoscopic observation is subject to sampling error and interobserver variability.The Kimura-Takemoto classification system was developed to overcome theselimitations.AIMTo compare the morphological classification of atrophic gastritis between theKimura-Takemoto system and the Updated Sydney system.METHODSA total of 169 patients with atrophic gastritis were selected according to diagnosisby the visual endoscopic Kimura-Takemoto method. Following the UpdatedKimura-Takemoto classification system, one antrum biopsy and five gastriccorpus biopsies were taken according to the visual stages of the Kimura-Takemoto system. The Updated Kimura-Takemoto classification system was thenapplied to each and showed 165 to have histological mucosal atrophy;theremaining 4 patients had no histological evidence of atrophy in any biopsy. The Updated Kimura-Takemoto classification was verified as a referencemorphological method and applied for the diagnosis of atrophic gastritis. Addingone more biopsy from the antrum to the six biopsies according to the Updated Kimura-Takemoto classification, constitutes the updated combined Kimura-Takemoto classification and Sydney system.RESULTSThe sensitivity for degree of mucosal atrophy assessed by the Updated Sydneysystem was 25% for mild, 36% for moderate, and 42% for severe, when comparedwith the Updated Kimura-Takemoto classification of atrophic gastritis formorphological diagnosis. Four types of multifocal atrophic gastritis wereidentified: sequential uniform (type 1;in 28%), sequential non-uniform (type 2;in7%), diffuse uniform (type 3;in 23%), diffuse non-uniform (type 4;in 24%), and"alternating atrophic – non-atrophic" (type 5;in 18%). The pattern of the spread ofatrophy, sequentially from the antrum to the cardiac segment of the stomach,which was described by the Updated Kimura-Takemoto system, washistologically confirmed in 82% of cases evaluated.CONCLUSIONThe Updated Sydney system is significantly inferior to the Updated Kimura-Takemoto classification for morphological verification of atrophic gastritis.展开更多
基金the National Natural Science Foundation of China, No. 10872069
文摘The morphological and functional characteristics of neurons are quite varied and complex. There is a need for a comprehensive approach for distinguishing and classifying neurons. Similar to the biological species classification system, this study proposes a morphological classification system for neurons based on principal component analysis. Based on four principal components of neuronal morphology derived from principal component analysis, a nomenclature system for neurons was obtained. This system can accurately distinguish between the same type of neuron from different species.
基金supported by Anhui Province Universities Outstanding Talented Person Support Project(No.gxyq2022097)Major Project of Natural Science Research of Anhui Provincial Department of Education(No.2022AH040150,No.KJ2021ZD0130,No.KJ2021ZD0131)+5 种基金Key Project of Natural Science Research of Anhui Provincial Department of Education(Grant No.KJ2020A0721)The guiding plan project of Chuzhou science and Technology Bureau(No.2021ZD008)“113”Industry Innovation Team of Chuzhou city in Anhui provincethe Project of Natural Science Research of An-hui Provincial Department of Education(No.2022AH030112,No.2022AH040156)the Academic Foundation for Top Talents in Disciplines of Anhui Universities(No.gxbj ZD2022069)the Innovation Program for Returned Overseas Chinese Scholars of Anhui Province(No.2021LCX014)。
文摘A peak is an important topographic feature crucial in quantitative geomorphic feature analysis,digital geomorphological mapping,and other fields.Most peak extraction methods are based on the maximum elevation in a local area but ignore the morphological characteristics of the peak area.This paper proposes three indices based on the morphological characteristics of peaks and their spatial relationship with ridge lines:convexity mean index(CM-index),convexity standard deviation(CSD-index),and convexity imbalance index(CIBindex).We develop computation methods to extract peaks from digital elevation model(DEM).Subsequently,the initial peaks extracted by neighborhood statistics are classified using the proposed indices.The method is evaluated in the Qinghai Tibet Plateau and the Loess Plateau in China.An ASTER Global DEM(ASTGTM2 DEM)with a grid size of 30 m is chosen to assess the suitability of the proposed mountain peak extraction and classification method in different geomorphic regions.DEM data with grid sizes of 30 m and 5 m are used for the Loess Plateau.The mountain peak extraction and classification results obtained from the different resolution DEM are compared.The experimental results show that:(1)The CM-index and the CSDindex accurately reflect the concave or convex morphology of the surface and can be used as supplements to existing surface morphological indices.(2)The three indices can identify pseudo mountain peaks and classify the remaining peaks into single ridge peak(SR-Peak)and multiple ridge intersection peak(MRI-Peak).The visual inspection results show that the classification accuracy in the different study areas exceeds 75%.(3)The number of peaks is significantly higher for the 5 m DEM than for the 30 m DEM because more peaks can be detected at a finer resolution.
文摘Automatic diagnosis may help to decrease human based diagnosis error and assist physicians to focus on the correct disease and its treatment and to avoid wasting time on diagnosis. In this paper computer aided diagnosis is applied to the brain CT image processing. We compared performance of morphological operations in extracting three types of features, i.e. gray scale, symmetry and texture. Some classifiers were applied to classify normal and abnormal brain CT images. It showed that morphological operations can improve the result of accuracy. Moreover SVM classifier showed better result than other classifiers.
文摘The Cheng index distinguishes indica andjaponica rice based on six taxonomic traits.This index has been widely used for classifi- cation of indica and japonica varieties in China.In this study,a double haploid(DH)popula-tion derived from anther culture of ZYQ8/JX17 F,a typical inter-subspecies hybrid,was used to investigate the six taxonomictraits,i.e.leaf hairiness(LH),color of hullwhen heading(CHH),hairiness of hull(HH),length of the first and second panicle internode(LPI),length/width of grain(L/W),andphenol reaction(PH).The morphological in- dex(MI)was also calculated.Based on themolecular linkage map constructed from this
文摘The hidden dimension of the urban morphology is the underlying the urban morphological rules system.The number of these rules has increased and their application tends to become more complex.The urban morphosis based digital approaches tends to become widespread.However,achieving the target values for all the rules is difficult.This impacts the social,environmental and aesthetic objectives of these rules.This paper proposes a classification of urban morphological rules to assist the digital morphosis of urban form.The aim is to endow the system of rules with a hierarchy,which can make efficient the automatic generation of the urban forms respectful of the urban law.Thus,this work promotes the concerns of artificial intelligence in urban morphology.
文摘The name of Vertisol is derived from Latin “vertere” meaning to invert. This case restricts development of soil horizons in profile. These soils have the capacity to swell and shrink, inducing cracks in the upper parts of the soil and distinctive soil structure throughout the soil. The formation of these specific features are caused by a heavy texture, a dominance of swelling clay in the fine fraction and marked changes in moisture content. The swell-shrink behavior is attributed to the wetting and drying of the soil mass. In this study, morphology, physico-chemical characteristics and classification of vertisols that were formed on alluvial delta plains, were investigated. Those soils formed on the Bafra Plain found in the K?z?l?rmak Delta and located in the central Black Sea region of Turkey. All studied Vertisols are characterised by a dark colour in surface soil, a heavy clayey texture, hardpan formation under top soil (high bulk density a high compaction) and very high COLE values. In addition, they have deep wide-opened desiccation cracks at the surface, slickensides at the middle part of the profiles and a poor differentiation of their horizons. Physico-chemically, the studied soils are slightly basic to very basic, non-saline and poor in organic matter, which is slightly higher in the surface horizon. In addition, cation exchange capacity, sum of exchangeable bases and base saturation of soils are very high. On the basis of morphological and physicochemical analysis, soil profiles were classified as Sodic Haplustert, Typic Calciaquert, Sodic Calciustert according to Soil Taxonomy (Soil Survey Staff, 1975 and 1999) and as Sodic Vertisol and Calcic Vertisol according to FAO/ISRIC (2006) classification systems.
基金Supported by the Major State Basic Research Development Program(973Program)of China(No.2009CB723905)the National High TechnologyResearch and Development Program(863Program)of China(No.2009AA12Z114)the National Natural Science Foundation of China(Nos.40930532,40901213,40771139)
文摘High-resolution hyper-spectral image (HHR) provides both detailed structural and spectral information for urban study. However, due to the inherent correlation between spectral bands and within-class variability in the data, the data processing of HHR is a challenging work. In this paper, based on spectral mixture analysis theory, a new stack of parts description features were extracted, and then incorporated with a stack of morphology based spatial features. Partially supervised constrained energy minimization (CEM) and unsupervised nonnegative matrix factorization (NMF) were used to extract the part-features. The joint features were then integrated by SVM classifier. The advantages of this method are the representation of physical composition of the urban area by the parts-features and the show of multi-scale structure information by morphology profiles. Experiments with an airborne hyper-spectral data flightline over the Washington DC Mall were performed, and the performance of the proposed algorithm was evaluated in comparison with well-known nonparametric weighted feature extraction (NWFE) and feature selection method. The results shown that the proposed features-joint scheme consistently outperforms the traditional methods, and so can provide an effective option for processing HHR data in urban area.
基金Supported by Heilongjiang Province Philosophy and Social Science Research Planning Project(17TQB059)。
文摘Soybean leaf morphology is one of the most important morphological and biological characteristics of soybean.The germplasm gene differences of soybeans can lead to different phenotypic traits,among which soybean leaf morphology is an important parameter that directly reflects the difference in soybean germplasm.To realize the morphological classification of soybean leaves,a method was proposed based on deep learning to automatically detect soybean leaves and classify leaf morphology.The morphology of soybean leaves included lanceolate,oval,ellipse and round.First,an image collection platform was designed to collect images of soybean leaves.Then,the feature pyramid networks–single shot multibox detector(FPN-SSD)model was proposed to detect the top leaflets of soybean leaves on the collected images.Finally,a classification model based on knowledge distillation was proposed to classify different morphologies of soybean leaves.The obtained results indicated an overall classification accuracy of 0.956 over a private dataset of 3200 soybean leaf images,and the accuracy of classification for each morphology was 1.00,0.97,0.93 and 0.94.The results showed that this method could effectively classify soybean leaf morphology and had great application potential in analyzing other phenotypic traits of soybean.
基金supported by the National Natural Science Foundation of China[grant Nos 41971406,41871292]the Science and Technology Program of Guangdong Province[grant number 2018B020207002]the Science and Technology Program of Guangzhou,China[grant number 201803030034].
文摘The classification of urban functional areas plays an important role in urban planning and resource management.Although previous studies have confirmed that different urban func-tional areas have different morphological structures and Land Surface Temperature(LST)characteristics,these two types of characteristics have rarely been fully integrated and used for functional area classification.In this paper,a new framework for classifying urban functional areas is proposed by combining urban morphological features and LST features.First,metrics are constructed from three levels,namely,building,road and region,which are used to portray urban morphology;LST is retrieved using thermal infrared remote sensing to reflect LST features with four metrics:the average temperature,maximum temperature,temperature difference and standard deviation of temperature.Then,the functional areas are classified into four categories:service/public land,commercial land,residential land and industrial land.A random forest algorithm is used to effectively fuse the features of these two categories and classify the functional areas.The effectiveness of the proposed framework is tested in the study area of Shenzhen City,Guangdong Province.The results show that the combined classification accuracy of the proposed classification method is 0.85,which is 0.26 higher than that of the classification model based on urban morphology and 0.1 higher than that of the classification model based on LST features.The proposed framework verifies that the integration of LST features into urban functional area classification is reliable and effectively combines urban morphology and LST features for functional area classification.
基金the DUS Project (Guidelines for the Conduct of Tests for Distinctness,Uniformity and Stability for Wintersweet,2006002) for funding assistance
文摘To classify the Chinese wintersweet（Chimonanthus praecox） cultivars and to study their evolution based on pollen morphology.Pollens of 12 representative wintersweet cultivars were examined by scanning electron microscopy（SEM）.Q-cluster analysis was carried out based on the observation results.Results are as follows：（1） The pollen grains were 2lobed circular in polar view,elliptic in equatorial view.The pollen shapes were spheroidal or super-spheroidal by P/E（polar axis length/equatorial axis length） criteria.（2） According to pollen exine ornamentation,it was indicated that white wintersweet is most original.Yellow floral group could be classified into three subgroups：purple-hearted,halo-hearted and yellow-hearted type.Their evolutionary relationship was purple-hearted halo-hearted yellow-hearted.（3） Different wintersweet cultivars showed a different exine sculpture.Palynological analysis could be used in the classification of wintersweet cultivars.The result of cluster analysis indicated that the cultivars could be classified into three groups with a similarity coefficient of 0.41.Each group had similar pollen exine sculpture.It was found that the palynological classification coincided well with morphological classification.Our results support the suggestion that purple streaks or patches of inner-petals should be served as the first-order criteria in wintersweet classification.
文摘Morphologic characteristic and classification description of female octopus Pareledone turqueti collected by R/V Xuelong during the 22nd Expedition in the Antarctic waters is discussed.The results indicate that this species belongs to suborder Incirrina,Family Octopodidae,Subfamily Eledoninae,Genus Pareledone,Pareledone turqueti.It is characterized by having soft and smooth skin without papillae,funnel organ VV-shaped,crop,ink sac,anterior and posterior salivary gland present,developed radulae with 7 small heterodont teeth,gills with 7 lamellae on the inner and outer demibranch respectively.Arms moderate with uniserial suckers no enlarged,arm formula is Ⅱ=III.I=IV,web formula is c=d.e.b.a.
基金This paper was supported by National Natural Science Foundation of China (Grant No. 39670607).
文摘The classification of seedlings is important to ensure the viability of seedlings after transplantation and is acknowledged as a key factor in forestation and environmental improvement. Based on numerous papers on automatic seedling classification (ASC), the seedling grading theory, traditional grading methods, the background and the proceeding of ASC techniques are described. The automation of the measurement of seedling morphological characteristics by photoelectric meters and computer vision is studied, and the automatic methods of the current grading systems are described respectively. And the further researches on ASC by computer vision are proposed.
基金supported by the National Natural Science Foundation of China(31970205,31870206)the Metasequoia funding of the Nanjing Forestry University,China。
文摘Living gymnosperms comprise four major groups:cycads,Ginkgo,conifers,and gnetophytes.Relationships among/within these lineages have not been fully resolved.Next generation sequencing has made available a large number of sequences,including both plastomes and single-copy nuclear genes,for reconstruction of solid phylogenetic trees.Recent advances in gymnosperm phylogenomic studies have updated our knowledge of gymnosperm systematics.Here,we review major advances of gymnosperm phylogeny over the past 10 years and propose an updated classification of extant gymnosperms.This new classification includes three classes(Cycadopsida,Ginkgoopsida,and Pinopsida),five subclasses(Cycadidae,Ginkgoidae,Cupressidae,Pinidae,and Gnetidae),eight orders(Cycadales,Ginkgoales,Araucariales,Cupressales,Pinales,Ephedrales,Gnetales,and Welwitschiales),13 families,and 86 genera.We also described six new tribes including Acmopyleae Y.Yang,Austrocedreae Y.Yang,Chamaecyparideae Y.Yang,Microcachrydeae Y.Yang,Papuacedreae Y.Yang,and Prumnopityeae Y.Yang,and made 27 new combinations in the genus Sabina.
基金financially supported by the Fundamental Research Funds for the Central Universities(DL12EB04-03),(DL13CB02)the Natural Science Foundation of Heilongjiang Province(LC2011C25)
文摘Region-Growing Algorithms （RGAs） are used to grade the quality of manufactured wood flooring. Traditional RGAs are hampered by prob- lems of long segmentation time and low inspection accuracy caused by neighborhood search. We used morphological reconstruction with the R com- ponent to construct a novel flaw segmentation method. We initially designed two template images for low and high thresholds, and these were used for seed optimization and inflation growth, respectively. Then the extraction of the flaw skeleton from the low threshold image was realized by applying the erosion termination rules. The seeds in the flaw skeleton were optimized by the pruning method. The geodesic inflection was applied by the high threshold template to realize rapid growth of the flaw area in the floor plate, and region filling and pruning operations were applied for margin optimization. Experi- ments were conducted on 512×512, 256×256 and 128×128 pixel sizes, re- spectively. The 256×256 pixel size proved superior in time-consumption at 0.06 s with accuracy of 100%. But with the region-growing method the same process took 0.22 s with accuracy of 70%. Compared with RGA, our pro- posed method can realize more accurate segmentation, and the speed and accuracy of segmentation can satisfy the requirements for on-line grading of wood flooring.
文摘BACKGROUND The Updated Sydney system for visual evaluation of gastric mucosal atrophy viaendoscopic observation is subject to sampling error and interobserver variability.The Kimura-Takemoto classification system was developed to overcome theselimitations.AIMTo compare the morphological classification of atrophic gastritis between theKimura-Takemoto system and the Updated Sydney system.METHODSA total of 169 patients with atrophic gastritis were selected according to diagnosisby the visual endoscopic Kimura-Takemoto method. Following the UpdatedKimura-Takemoto classification system, one antrum biopsy and five gastriccorpus biopsies were taken according to the visual stages of the Kimura-Takemoto system. The Updated Kimura-Takemoto classification system was thenapplied to each and showed 165 to have histological mucosal atrophy;theremaining 4 patients had no histological evidence of atrophy in any biopsy. The Updated Kimura-Takemoto classification was verified as a referencemorphological method and applied for the diagnosis of atrophic gastritis. Addingone more biopsy from the antrum to the six biopsies according to the Updated Kimura-Takemoto classification, constitutes the updated combined Kimura-Takemoto classification and Sydney system.RESULTSThe sensitivity for degree of mucosal atrophy assessed by the Updated Sydneysystem was 25% for mild, 36% for moderate, and 42% for severe, when comparedwith the Updated Kimura-Takemoto classification of atrophic gastritis formorphological diagnosis. Four types of multifocal atrophic gastritis wereidentified: sequential uniform (type 1;in 28%), sequential non-uniform (type 2;in7%), diffuse uniform (type 3;in 23%), diffuse non-uniform (type 4;in 24%), and"alternating atrophic – non-atrophic" (type 5;in 18%). The pattern of the spread ofatrophy, sequentially from the antrum to the cardiac segment of the stomach,which was described by the Updated Kimura-Takemoto system, washistologically confirmed in 82% of cases evaluated.CONCLUSIONThe Updated Sydney system is significantly inferior to the Updated Kimura-Takemoto classification for morphological verification of atrophic gastritis.
