Since 1985, samples with a total weight of more than 14,000 kg, mainly from three key sections in western and northwestern Hunan, South China, have been processed for conodonts. In strata older than the late Late Camb...Since 1985, samples with a total weight of more than 14,000 kg, mainly from three key sections in western and northwestern Hunan, South China, have been processed for conodonts. In strata older than the late Late Cambrian paraconodonts have proved useful for stratigraphic subdivision and correlation. Thirteen conodont zones are proposed in the Middle Cambrian through lowermost Ordovician. The correlation between these zones and those of North China, western U. S.A., western Newfoundland, Canada, and Iran is discussed. In ascending order, these 13 zones are as follows: The Gapparodus bisulcatus-Westergaardodina brevidens Zone, Shandongodus priscus-Hunanognathus tricuspidatus Zone, Westergaardodina quadrata Zone, Westergaardodina matsushitai-W. grandidens Zone, Westergaardodina lui-W. am Zone, Westergaardodina cf. calix-Prooneotodus rotundatus Zone, Proconodontus tenuiserratus Zone, Proconodontus Zone, Eoconodontus Zone, Cordylodus proavus Zone, Cordylodus intermedius Zone, Cordylodus lindstromi Zone, and Cordylodus angulatus Zone (lower part). The Westergaardodina lui-W. ani and Westergaardodina cf. calix-Prooneotodus rotundatus Zones replace the Westergaardodina proligula and Westergaardodina cf. behrae-Prooneotodus rotundatus Zones, respectively, in the lowermost Upper Cambrian. Two new species (Westergaardodina Iui and Westergaardodina ani) and one conditionally identified species (Westergaardodina cf. calix) are described.展开更多
Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon （SOC） for the soils of Ohio, USA. Specific objective of the st...Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon （SOC） for the soils of Ohio, USA. Specific objective of the study was to estimate the spatial distribution of SOC density （C stock per unit area） to 1.0-m depth for soils of Ohio using geographically weighted regression （GWR）, and compare the results with that obtained from multiple linear regression （MLR）. About 80% of the analytical data were used for calibration and 20% for validation. A total of 20 variables including terrain attributes, climate data, bedrock geology, and land use data were used for mapping the SOC density. Results showed that the GWR provided better estimations with the lowest （3.81 kg m-2） root mean square error （RMSE） than MLR approach Total estimated SOC pool for soils in Ohio ranged from 727 to 742 Tg. This study demon strates that, the local spatial statistical technique, the GWR can perform better in capturing the spatial distribution of SOC across the study region as compared to other global spatial statistical techniques such as MLR. Thus, GWR enhances the accuracy for mapping SOC density.展开更多
Diabasbrottet, selected by the International Subcommisson on Ordovician Stratigraphy and in 2002 ratified by the International Commission on Stratigraphy as the GSSP of the Second (Upper) Stage of the Lower Ordovician...Diabasbrottet, selected by the International Subcommisson on Ordovician Stratigraphy and in 2002 ratified by the International Commission on Stratigraphy as the GSSP of the Second (Upper) Stage of the Lower Ordovician, is located on the Hunneberg Mountain in southwestern Sweden. The stratigraphic succession represents an outer shelf environment near the Baltic Shield margin. The shale-dominated, biostratigraphically complete, richly fossiliferous boundary interval is completely exposed in a disused quarry. The GSSP is in the lower TФyen Shale 2.1 m above the top of the Cambrian and is marked by the first appearance of the graptolite Tetragraptus approximatus Nicholson. The boundary interval contains a diverse graptolite fauna and biostratigraphically diagnostic conodonts and trilobites that make it possible to define the boundary in terms of zone schemes based on these groups. In this respect, the Diabasbrottet and nearby sections are unique in the world among described localities having this boundary interval. Based on the appearance of T. approximatus, the base of the Second Stage can be identified in many graptolitiferous successions round the world but this level is currently more difficult to recognize precisely in some carbonate sequences outside Baltoscandia. We propose the Second Stage be called the Floan Stage. It is named for the Village of Flo, which is situated about 5 km southeast of the GSSP.展开更多
In recent years, the deep web has become ex- tremely popular. Like any other data source, data mining on the deep web can produce important insights or summaries of results. However, data mining on the deep web is cha...In recent years, the deep web has become ex- tremely popular. Like any other data source, data mining on the deep web can produce important insights or summaries of results. However, data mining on the deep web is chal- lenging because the databases cannot be accessed directly, and therefore, data mining must be performed by sampling the datasets. The samples, in turn, can only be obtained by querying deep web databases with specific inputs. In this pa- per, we target two related data mining problems, association mining and differential rule mining. These are proposed to ex- tract high-level summaries of the differences in data provided by different deep web data sources in the same domain. We develop stratified sampling methods to perform these min- ing tasks on a deep web source. Our contributions include a novel greedy stratification approach, which recursively pro- cesses the query space of a deep web data source, and con- siders both the estimation error and the sampling costs. We have also developed an optimized sample allocation method that integrates estimation error and sampling costs. Our ex- perimental results show that our algorithms effectively and consistently reduce sampling costs, compared with a strat- ified sampling method that only considers estimation error. In addition, compared with simple random sampling, our al- gorithm has higher sampling accuracy and lower sampling costs.展开更多
Background:Mass cytometry(CyTOF)gives unprecedented opportunity to simultaneously measure up to 40 proteins in single cells,with a theoretical potential to reach 100 proteins.This high-dimensional single-cell informat...Background:Mass cytometry(CyTOF)gives unprecedented opportunity to simultaneously measure up to 40 proteins in single cells,with a theoretical potential to reach 100 proteins.This high-dimensional single-cell information can be very useful in dissecting mechanisms of cellular activity.In particular,measuring abundances of signaling proteins like phospho-proteins can provide detailed information on the dynamics of single-cell signaling processes.However,computational analysis is required to reconstruct such networks with a mechanistic model.Methods:We propose our Mass cytometry Signaling Network Analysis Code(McSNAC),a new software capable of reconstructing signaling networks and estimating their kinetic parameters from CyTOF data.McSNAC approximates signaling networks as a network of first-order reactions between proteins.This assumption often breaks down as signaling reactions can involve binding and unbinding,enzymatic reactions,and other nonlinear constructions.Furthermore,McSNAC may be limited to approximating indirect interactions between protein species,as cytometry experiments are only able to assay a small fraction of protein species involved in signaling.Results:We carry out a series of in silico experiments here to show(1)McSNAC is capable of accurately estimating the ground-truth model in a scalable manner when given data originating from a first-order system;(2)McSNAC is capable of qualitatively predicting outcomes to perturbations of species abundances in simple second-order reaction models and in a complex in silico nonlinear signaling network in which some proteins are unmeasured.Conclusions:These findings demonstrate that McSNAC can be a valuable screening tool for generating models of signaling networks from time-stamped CyTOF data.展开更多
基金This study was supported by the National Natural Science Foundation of China(Grants 4037200140072007+3 种基金49772083 to Dong Xiping)by the Laboratory of Paleobiology and Stratigraphy,Nanjing Institute of Geology and Palaeontology,Chinese Academy of Sciences(Grant 023106 to Dong Xiping)by the Research Fund for Doctoral Program of High Education(Grant 2000000127 to Dong Xiping)by a travel grant from the Ohio State University(to Stig M.Bergstrom).
文摘Since 1985, samples with a total weight of more than 14,000 kg, mainly from three key sections in western and northwestern Hunan, South China, have been processed for conodonts. In strata older than the late Late Cambrian paraconodonts have proved useful for stratigraphic subdivision and correlation. Thirteen conodont zones are proposed in the Middle Cambrian through lowermost Ordovician. The correlation between these zones and those of North China, western U. S.A., western Newfoundland, Canada, and Iran is discussed. In ascending order, these 13 zones are as follows: The Gapparodus bisulcatus-Westergaardodina brevidens Zone, Shandongodus priscus-Hunanognathus tricuspidatus Zone, Westergaardodina quadrata Zone, Westergaardodina matsushitai-W. grandidens Zone, Westergaardodina lui-W. am Zone, Westergaardodina cf. calix-Prooneotodus rotundatus Zone, Proconodontus tenuiserratus Zone, Proconodontus Zone, Eoconodontus Zone, Cordylodus proavus Zone, Cordylodus intermedius Zone, Cordylodus lindstromi Zone, and Cordylodus angulatus Zone (lower part). The Westergaardodina lui-W. ani and Westergaardodina cf. calix-Prooneotodus rotundatus Zones replace the Westergaardodina proligula and Westergaardodina cf. behrae-Prooneotodus rotundatus Zones, respectively, in the lowermost Upper Cambrian. Two new species (Westergaardodina Iui and Westergaardodina ani) and one conditionally identified species (Westergaardodina cf. calix) are described.
文摘Historical database of National Soil Survey Center containing 1424 geo-referenced soil profiles was used in this study for estimating the organic carbon （SOC） for the soils of Ohio, USA. Specific objective of the study was to estimate the spatial distribution of SOC density （C stock per unit area） to 1.0-m depth for soils of Ohio using geographically weighted regression （GWR）, and compare the results with that obtained from multiple linear regression （MLR）. About 80% of the analytical data were used for calibration and 20% for validation. A total of 20 variables including terrain attributes, climate data, bedrock geology, and land use data were used for mapping the SOC density. Results showed that the GWR provided better estimations with the lowest （3.81 kg m-2） root mean square error （RMSE） than MLR approach Total estimated SOC pool for soils in Ohio ranged from 727 to 742 Tg. This study demon strates that, the local spatial statistical technique, the GWR can perform better in capturing the spatial distribution of SOC across the study region as compared to other global spatial statistical techniques such as MLR. Thus, GWR enhances the accuracy for mapping SOC density.
文摘Diabasbrottet, selected by the International Subcommisson on Ordovician Stratigraphy and in 2002 ratified by the International Commission on Stratigraphy as the GSSP of the Second (Upper) Stage of the Lower Ordovician, is located on the Hunneberg Mountain in southwestern Sweden. The stratigraphic succession represents an outer shelf environment near the Baltic Shield margin. The shale-dominated, biostratigraphically complete, richly fossiliferous boundary interval is completely exposed in a disused quarry. The GSSP is in the lower TФyen Shale 2.1 m above the top of the Cambrian and is marked by the first appearance of the graptolite Tetragraptus approximatus Nicholson. The boundary interval contains a diverse graptolite fauna and biostratigraphically diagnostic conodonts and trilobites that make it possible to define the boundary in terms of zone schemes based on these groups. In this respect, the Diabasbrottet and nearby sections are unique in the world among described localities having this boundary interval. Based on the appearance of T. approximatus, the base of the Second Stage can be identified in many graptolitiferous successions round the world but this level is currently more difficult to recognize precisely in some carbonate sequences outside Baltoscandia. We propose the Second Stage be called the Floan Stage. It is named for the Village of Flo, which is situated about 5 km southeast of the GSSP.
文摘In recent years, the deep web has become ex- tremely popular. Like any other data source, data mining on the deep web can produce important insights or summaries of results. However, data mining on the deep web is chal- lenging because the databases cannot be accessed directly, and therefore, data mining must be performed by sampling the datasets. The samples, in turn, can only be obtained by querying deep web databases with specific inputs. In this pa- per, we target two related data mining problems, association mining and differential rule mining. These are proposed to ex- tract high-level summaries of the differences in data provided by different deep web data sources in the same domain. We develop stratified sampling methods to perform these min- ing tasks on a deep web source. Our contributions include a novel greedy stratification approach, which recursively pro- cesses the query space of a deep web data source, and con- siders both the estimation error and the sampling costs. We have also developed an optimized sample allocation method that integrates estimation error and sampling costs. Our ex- perimental results show that our algorithms effectively and consistently reduce sampling costs, compared with a strat- ified sampling method that only considers estimation error. In addition, compared with simple random sampling, our al- gorithm has higher sampling accuracy and lower sampling costs.
文摘Background:Mass cytometry(CyTOF)gives unprecedented opportunity to simultaneously measure up to 40 proteins in single cells,with a theoretical potential to reach 100 proteins.This high-dimensional single-cell information can be very useful in dissecting mechanisms of cellular activity.In particular,measuring abundances of signaling proteins like phospho-proteins can provide detailed information on the dynamics of single-cell signaling processes.However,computational analysis is required to reconstruct such networks with a mechanistic model.Methods:We propose our Mass cytometry Signaling Network Analysis Code(McSNAC),a new software capable of reconstructing signaling networks and estimating their kinetic parameters from CyTOF data.McSNAC approximates signaling networks as a network of first-order reactions between proteins.This assumption often breaks down as signaling reactions can involve binding and unbinding,enzymatic reactions,and other nonlinear constructions.Furthermore,McSNAC may be limited to approximating indirect interactions between protein species,as cytometry experiments are only able to assay a small fraction of protein species involved in signaling.Results:We carry out a series of in silico experiments here to show(1)McSNAC is capable of accurately estimating the ground-truth model in a scalable manner when given data originating from a first-order system;(2)McSNAC is capable of qualitatively predicting outcomes to perturbations of species abundances in simple second-order reaction models and in a complex in silico nonlinear signaling network in which some proteins are unmeasured.Conclusions:These findings demonstrate that McSNAC can be a valuable screening tool for generating models of signaling networks from time-stamped CyTOF data.
