This paper tries to characterize volcanic rocks through the development and application of an empirical geomechanical system. Geotechnical information was collected from the samples from several Atlantic Ocean islands...This paper tries to characterize volcanic rocks through the development and application of an empirical geomechanical system. Geotechnical information was collected from the samples from several Atlantic Ocean islands including Madeira, Azores and Canarias archipelagos. An empirical rock classification system termed as the volcanic rock system(VRS) is developed and presented in detail. Results using the VRS are compared with those obtained using the traditional rock mass rating(RMR) system. Data mining(DM) techniques are applied to a database of volcanic rock geomechanical information from the islands.Different algorithms were developed and consequently approaches were followed for predicting rock mass classes using the VRS and RMR classification systems. Finally, some conclusions are drawn with emphasis on the fact that a better performance was achieved using attributes from VRS.展开更多
From the commercial extract of the leaves of Stevia rebaudiana Bertoni, a new minor ent-kaurane diterpene glycoside having five β-D-glucopyranosyl units has been isolated. The chemical structure of the new compound w...From the commercial extract of the leaves of Stevia rebaudiana Bertoni, a new minor ent-kaurane diterpene glycoside having five β-D-glucopyranosyl units has been isolated. The chemical structure of the new compound was characterized as 13-[(2-O-β-D-glucopyranosyl-β-D-glucopyranosyl)oxy] ent-kaur-16-en-19-oic acid-(2-O-β-D-glucopyranosyl-6-O-β-D-glucopyranosyl-β-D-glucopyranosyl) ester (1) on the basis of extensive 1D (1H & 13C) and 2D NMR (TOCSY, HMQC, and HMBC), and High Resolution (HR) mass spectroscopic data as well as hydrolysis studies.展开更多
Restriction endonuclease analysis(REA),or restriction fragment length polymorphism(RFLP),was useful for identifying and determining the relatedness and putative identities of microbial strains(Tang et al.,1997)and for...Restriction endonuclease analysis(REA),or restriction fragment length polymorphism(RFLP),was useful for identifying and determining the relatedness and putative identities of microbial strains(Tang et al.,1997)and for characterizing and discriminating large numbers of samples inexpensively in the past。展开更多
Rebaudioside D3, a novel steviol glycoside, is produced by specific UDP-glycosyltransferase of rebaudioside E, a minor steviol glycoside of Stevia rebaudiana Bertoni. The complete proton and carbon NMR spectral assign...Rebaudioside D3, a novel steviol glycoside, is produced by specific UDP-glycosyltransferase of rebaudioside E, a minor steviol glycoside of Stevia rebaudiana Bertoni. The complete proton and carbon NMR spectral assignments of rebaudioside D3, 13-[(2-O-β-D-glucopyranosyl-6-O-β-D-glucopyranosyl-β-D-glucopyranosyl) oxy] ent-kaur-16-en-19-oic acid-(2-O-β-D-glucopyranosyl-β-D-glucopyranosyl) ester, was achieved by the extensive 1D and 2D NMR (1H and 13C, TOCSY, HMQC, HMBC) as well as mass spectral data. Further, hydrolysis studies were performed on rebaudioside D3 using acid and enzymatic studies to identify aglycone and sugar residues in its structure. Rebaudioside D3 is detected in the commercial extract of the leaves of Stevia rebaudiana by LC-MS analysis, suggesting rebaudioside D3 is a natural steviol glycoside.展开更多
The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characte...The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characterized using merely static seismic data.The effective quantitative characterization of the reservoirs has been an urgent problem to be solved.This study creatively proposes the"second quantitative characterization"technique with the combination of dynamic and static data based on the primary static quantitative characterization and fully considering lots of key influence factors when conducting characterization.In this technique,dynamic analysis methods such as well testing,production rate transient analysis,dynamic reserve evaluation and dynamic connectivity evaluation are used to get understandings on this kind of reservoir.These understandings are used as statistical parameters to constrain the inversion of seismic wave impedance to improve the relationship between wave impedance and porosity and determine the fracture-vug morphology,calculate dynamic reserves,and then a more accurate fracture-vugmodel can be selected and used to calculate the oil-water contact inversely based on the results of"second quantitative characterization".This method can lower the uncertainties in the primary quantitative characterization of fracture-vug reservoirs,enhance the accuracy of characterization results significantly,and has achieved good application results in the fracture-vug carbonate reservoirs of Tarim Basin.展开更多
With high computational capacity, e.g. many-core and wide floating point SIMD units, Intel Xeon Phi shows promising prospect to accelerate high-performance computing(HPC) applications. But the application of Intel Xeo...With high computational capacity, e.g. many-core and wide floating point SIMD units, Intel Xeon Phi shows promising prospect to accelerate high-performance computing(HPC) applications. But the application of Intel Xeon Phi on data analytics workloads in data center is still an open question. Phibench 2.0 is built for the latest generation of Intel Xeon Phi(KNL, Knights Landing), based on the prior work PhiBench(also named BigDataBench-Phi), which is designed for the former generation of Intel Xeon Phi(KNC, Knights Corner). Workloads of PhiBench 2.0 are delicately chosen based on BigdataBench 4.0 and PhiBench 1.0. Other than that, these workloads are well optimized on KNL, and run on real-world datasets to evaluate their performance and scalability. Further, the microarchitecture-level characteristics including CPI, cache behavior, vectorization intensity, and branch prediction efficiency are analyzed and the impact of affinity and scheduling policy on performance are investigated. It is believed that the observations would help other researchers working on Intel Xeon Phi and data analytics workloads.展开更多
Big data analytics is emerging as one kind of the most important workloads in modern data centers. Hence,it is of great interest to identify the method of achieving the best performance for big data analytics workload...Big data analytics is emerging as one kind of the most important workloads in modern data centers. Hence,it is of great interest to identify the method of achieving the best performance for big data analytics workloads running on state-of-the-art SMT( simultaneous multithreading) processors,which needs comprehensive understanding to workload characteristics. This paper chooses the Spark workloads as the representative big data analytics workloads and performs comprehensive measurements on the POWER8 platform,which supports a wide range of multithreading. The research finds that the thread assignment policy and cache contention have significant impacts on application performance. In order to identify the potential optimization method from the experiment results,this study performs micro-architecture level characterizations by means of hardware performance counters and gives implications accordingly.展开更多
Multisensor data fusion （MDF） is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross ...Multisensor data fusion （MDF） is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross a wide spectrum in military and civilian areas. With the rapid evolution of computers and the proliferation of micro-mechanical/electrical systems sensors, the utilization of MDF is being popularized in research and applications. This paper focuses on application of MDF for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme was established on the basis of feature extraction and merge of data from multiple sensors. This scheme integrates artificial neural networks for high performance pattern recognition. A number of successful applications in areas of NDI （Non-Destructive Inspection） corrosion detection, food quality and safety characterization, and precision agriculture are described and discussed in order to motivate new applications in these or other areas. This paper gives an overall picture of using the MDF method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.展开更多
In the paper, firstly, based on new non-tensor-product-typed partially inverse divided differences algorithms in a recursive form, scattered data interpolating schemes are constructed via bivariate continued fractions...In the paper, firstly, based on new non-tensor-product-typed partially inverse divided differences algorithms in a recursive form, scattered data interpolating schemes are constructed via bivariate continued fractions with odd and even nodes, respectively. And equivalent identities are also obtained between interpolated functions and bivariate continued fractions. Secondly, by means of three-term recurrence relations for continued fractions, the characterization theorem is presented to study on the degrees of the numerators and denominators of the interpolating continued fractions. Thirdly, some numerical examples show it feasible for the novel recursive schemes. Meanwhile, compared with the degrees of the numera- tors and denominators of bivariate Thiele-typed interpolating continued fractions, those of the new bivariate interpolating continued fractions are much low, respectively, due to the reduc- tion of redundant interpolating nodes. Finally, the operation count for the rational function interpolation is smaller than that for radial basis function interpolation.展开更多
Geophysical techniques can help to bridge the inherent gap that exists with regard to spatial resolution and coverage for classical hydrological methods. This has led to the emergence of a new and rapidly growing rese...Geophysical techniques can help to bridge the inherent gap that exists with regard to spatial resolution and coverage for classical hydrological methods. This has led to the emergence of a new and rapidly growing research domain generally referred to as hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters, their inherent trade-off between resolution and range, as well as the notoriously site-specific nature of petrophysical parameter relations, the fundamental usefulness of multi-method surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database into a unified model of the probed subsurface region that is consistent with all available measurements. To this end, we present a novel approach toward hydrogeophysical data integration based on a Monte-Carlo-type conditional stochastic simulation method that we consider to be particularly suitable for high-resolution local-scale studies. Monte Carlo techniques are flexible and versatile, allowing for accounting for a wide variety of data and constraints of differing resolution and hardness, and thus have the potential of providing, in a geostatistical sense, realistic models of the pertinent target parameter distributions. Compared to more conventional approaches, such as co-kriging or cluster analysis, our approach provides significant ad- vancements in the way that larger-scale structural information eontained in the hydrogeophysieal data can be accounted for. After outlining the methodological background of our algorithm, we present the results of its application to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the detailed local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to a field dataset collected at the Boise Hydrogeophysical Research Site. Finally, we compare the performance of our data integration approach to that of more conventional methods with regard to the prediction of flow and transport phenomena in highly heterogeneous media and discuss the implications arising.展开更多
Accurate characte rization of the fault system is crucial for the exploration and development of fractu red reservoirs.The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspo...Accurate characte rization of the fault system is crucial for the exploration and development of fractu red reservoirs.The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspot.In this way,the fault structures of different scales can be identified and the characterization details of complex fault systems can be enriched by analyzing and fusing the fault-induced responses in multi-azimuth and multi-type seismic attributes.However,the current fusion methods are still in the stage of violent information stacking in utilizing fault information of multi-azimuth and multi-type seismic attributes,and the fault or fracture semantics in multi-type attributes are not fully considered and utilized.In this work,we propose a physic-guided multi-azimuth multi-type seismic attributes intelligent fusion method,which can mine fracture semantics from multi-azimuth seismic data and realize the effective fusion of fault-induced abnormal responses in multi-azimuth seismic coherence and curvature with the cooperation of the deep learning model and physical knowledge.The fused result can be used for multi-azimuth comprehensive characterization for multi-scale faults.The proposed method is successfully applied to an ultra-deep carbonate field survey.The results indicate the proposed method is superior to self-supervised-based,principal-component-analysis-based,and weighted-average-based fusion methods in fault characterization accuracy,and some medium-scale and microscale fault illusions in multi-azimuth seismic coherence and curvature can be removed in the fused result.展开更多
文摘This paper tries to characterize volcanic rocks through the development and application of an empirical geomechanical system. Geotechnical information was collected from the samples from several Atlantic Ocean islands including Madeira, Azores and Canarias archipelagos. An empirical rock classification system termed as the volcanic rock system(VRS) is developed and presented in detail. Results using the VRS are compared with those obtained using the traditional rock mass rating(RMR) system. Data mining(DM) techniques are applied to a database of volcanic rock geomechanical information from the islands.Different algorithms were developed and consequently approaches were followed for predicting rock mass classes using the VRS and RMR classification systems. Finally, some conclusions are drawn with emphasis on the fact that a better performance was achieved using attributes from VRS.
文摘From the commercial extract of the leaves of Stevia rebaudiana Bertoni, a new minor ent-kaurane diterpene glycoside having five β-D-glucopyranosyl units has been isolated. The chemical structure of the new compound was characterized as 13-[(2-O-β-D-glucopyranosyl-β-D-glucopyranosyl)oxy] ent-kaur-16-en-19-oic acid-(2-O-β-D-glucopyranosyl-6-O-β-D-glucopyranosyl-β-D-glucopyranosyl) ester (1) on the basis of extensive 1D (1H & 13C) and 2D NMR (TOCSY, HMQC, and HMBC), and High Resolution (HR) mass spectroscopic data as well as hydrolysis studies.
基金supported by the National Natural Science Foundation of China (31570155 and 31370199)"Young Top-notch Talents" of the Guangdong Province Special Support Program (2014)+3 种基金the Excellent Young Teacher Training Plan of Guangdong Province (Yq2013039)the Guangzhou Healthcare Collaborative Innovation Major Project (201400000002)funded by the China Scholarship Council (CSC No. 201508440056) as a Visiting Scholar (2015-2016)supported by a summer research grant to D.S. from the Office of the Vice President for Research at George Mason University
文摘Restriction endonuclease analysis(REA),or restriction fragment length polymorphism(RFLP),was useful for identifying and determining the relatedness and putative identities of microbial strains(Tang et al.,1997)and for characterizing and discriminating large numbers of samples inexpensively in the past。
文摘Rebaudioside D3, a novel steviol glycoside, is produced by specific UDP-glycosyltransferase of rebaudioside E, a minor steviol glycoside of Stevia rebaudiana Bertoni. The complete proton and carbon NMR spectral assignments of rebaudioside D3, 13-[(2-O-β-D-glucopyranosyl-6-O-β-D-glucopyranosyl-β-D-glucopyranosyl) oxy] ent-kaur-16-en-19-oic acid-(2-O-β-D-glucopyranosyl-β-D-glucopyranosyl) ester, was achieved by the extensive 1D and 2D NMR (1H and 13C, TOCSY, HMQC, HMBC) as well as mass spectral data. Further, hydrolysis studies were performed on rebaudioside D3 using acid and enzymatic studies to identify aglycone and sugar residues in its structure. Rebaudioside D3 is detected in the commercial extract of the leaves of Stevia rebaudiana by LC-MS analysis, suggesting rebaudioside D3 is a natural steviol glycoside.
基金Supported by the General Program of Natural Science Foundation of China(51874346).
文摘The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characterized using merely static seismic data.The effective quantitative characterization of the reservoirs has been an urgent problem to be solved.This study creatively proposes the"second quantitative characterization"technique with the combination of dynamic and static data based on the primary static quantitative characterization and fully considering lots of key influence factors when conducting characterization.In this technique,dynamic analysis methods such as well testing,production rate transient analysis,dynamic reserve evaluation and dynamic connectivity evaluation are used to get understandings on this kind of reservoir.These understandings are used as statistical parameters to constrain the inversion of seismic wave impedance to improve the relationship between wave impedance and porosity and determine the fracture-vug morphology,calculate dynamic reserves,and then a more accurate fracture-vugmodel can be selected and used to calculate the oil-water contact inversely based on the results of"second quantitative characterization".This method can lower the uncertainties in the primary quantitative characterization of fracture-vug reservoirs,enhance the accuracy of characterization results significantly,and has achieved good application results in the fracture-vug carbonate reservoirs of Tarim Basin.
基金Supported by the National High Technology Research and Development Program of China(No.2015AA015308)the National Key Research and Development Plan of China(No.2016YFB1000600,2016YFB1000601)the Major Program of National Natural Science Foundation of China(No.61432006)
文摘With high computational capacity, e.g. many-core and wide floating point SIMD units, Intel Xeon Phi shows promising prospect to accelerate high-performance computing(HPC) applications. But the application of Intel Xeon Phi on data analytics workloads in data center is still an open question. Phibench 2.0 is built for the latest generation of Intel Xeon Phi(KNL, Knights Landing), based on the prior work PhiBench(also named BigDataBench-Phi), which is designed for the former generation of Intel Xeon Phi(KNC, Knights Corner). Workloads of PhiBench 2.0 are delicately chosen based on BigdataBench 4.0 and PhiBench 1.0. Other than that, these workloads are well optimized on KNL, and run on real-world datasets to evaluate their performance and scalability. Further, the microarchitecture-level characteristics including CPI, cache behavior, vectorization intensity, and branch prediction efficiency are analyzed and the impact of affinity and scheduling policy on performance are investigated. It is believed that the observations would help other researchers working on Intel Xeon Phi and data analytics workloads.
基金Supported by the National High Technology Research and Development Program of China(No.2015AA015308)the State Key Development Program for Basic Research of China(No.2014CB340402)
文摘Big data analytics is emerging as one kind of the most important workloads in modern data centers. Hence,it is of great interest to identify the method of achieving the best performance for big data analytics workloads running on state-of-the-art SMT( simultaneous multithreading) processors,which needs comprehensive understanding to workload characteristics. This paper chooses the Spark workloads as the representative big data analytics workloads and performs comprehensive measurements on the POWER8 platform,which supports a wide range of multithreading. The research finds that the thread assignment policy and cache contention have significant impacts on application performance. In order to identify the potential optimization method from the experiment results,this study performs micro-architecture level characterizations by means of hardware performance counters and gives implications accordingly.
文摘Multisensor data fusion （MDF） is an emerging technology to fuse data from multiple sensors in order to make a more accurate estimation of the environment through measurement and detection. Applications of MDF cross a wide spectrum in military and civilian areas. With the rapid evolution of computers and the proliferation of micro-mechanical/electrical systems sensors, the utilization of MDF is being popularized in research and applications. This paper focuses on application of MDF for high quality data analysis and processing in measurement and instrumentation. A practical, general data fusion scheme was established on the basis of feature extraction and merge of data from multiple sensors. This scheme integrates artificial neural networks for high performance pattern recognition. A number of successful applications in areas of NDI （Non-Destructive Inspection） corrosion detection, food quality and safety characterization, and precision agriculture are described and discussed in order to motivate new applications in these or other areas. This paper gives an overall picture of using the MDF method to increase the accuracy of data analysis and processing in measurement and instrumentation in different areas of applications.
基金Supported by the Special Funds Tianyuan for the National Natural Science Foundation of China(Grant No.11426086)the Fundamental Research Funds for the Central Universities(Grant No.2016B08714)the Natural Science Foundation of Jiangsu Province for the Youth(Grant No.BK20160853)
文摘In the paper, firstly, based on new non-tensor-product-typed partially inverse divided differences algorithms in a recursive form, scattered data interpolating schemes are constructed via bivariate continued fractions with odd and even nodes, respectively. And equivalent identities are also obtained between interpolated functions and bivariate continued fractions. Secondly, by means of three-term recurrence relations for continued fractions, the characterization theorem is presented to study on the degrees of the numerators and denominators of the interpolating continued fractions. Thirdly, some numerical examples show it feasible for the novel recursive schemes. Meanwhile, compared with the degrees of the numera- tors and denominators of bivariate Thiele-typed interpolating continued fractions, those of the new bivariate interpolating continued fractions are much low, respectively, due to the reduc- tion of redundant interpolating nodes. Finally, the operation count for the rational function interpolation is smaller than that for radial basis function interpolation.
基金supported by the Swiss National Science Foundation
文摘Geophysical techniques can help to bridge the inherent gap that exists with regard to spatial resolution and coverage for classical hydrological methods. This has led to the emergence of a new and rapidly growing research domain generally referred to as hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters, their inherent trade-off between resolution and range, as well as the notoriously site-specific nature of petrophysical parameter relations, the fundamental usefulness of multi-method surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database into a unified model of the probed subsurface region that is consistent with all available measurements. To this end, we present a novel approach toward hydrogeophysical data integration based on a Monte-Carlo-type conditional stochastic simulation method that we consider to be particularly suitable for high-resolution local-scale studies. Monte Carlo techniques are flexible and versatile, allowing for accounting for a wide variety of data and constraints of differing resolution and hardness, and thus have the potential of providing, in a geostatistical sense, realistic models of the pertinent target parameter distributions. Compared to more conventional approaches, such as co-kriging or cluster analysis, our approach provides significant ad- vancements in the way that larger-scale structural information eontained in the hydrogeophysieal data can be accounted for. After outlining the methodological background of our algorithm, we present the results of its application to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the detailed local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to a field dataset collected at the Boise Hydrogeophysical Research Site. Finally, we compare the performance of our data integration approach to that of more conventional methods with regard to the prediction of flow and transport phenomena in highly heterogeneous media and discuss the implications arising.
基金sponsorship of the National Natural Science Foundation of China (42430809, 42030103)the Basic Research Funds for Northeast Petroleum University in Heilongjiang Province (2025GPL-01)。
文摘Accurate characte rization of the fault system is crucial for the exploration and development of fractu red reservoirs.The fault characterization technique based on multi-azimuth and multi-attribute fusion is a hotspot.In this way,the fault structures of different scales can be identified and the characterization details of complex fault systems can be enriched by analyzing and fusing the fault-induced responses in multi-azimuth and multi-type seismic attributes.However,the current fusion methods are still in the stage of violent information stacking in utilizing fault information of multi-azimuth and multi-type seismic attributes,and the fault or fracture semantics in multi-type attributes are not fully considered and utilized.In this work,we propose a physic-guided multi-azimuth multi-type seismic attributes intelligent fusion method,which can mine fracture semantics from multi-azimuth seismic data and realize the effective fusion of fault-induced abnormal responses in multi-azimuth seismic coherence and curvature with the cooperation of the deep learning model and physical knowledge.The fused result can be used for multi-azimuth comprehensive characterization for multi-scale faults.The proposed method is successfully applied to an ultra-deep carbonate field survey.The results indicate the proposed method is superior to self-supervised-based,principal-component-analysis-based,and weighted-average-based fusion methods in fault characterization accuracy,and some medium-scale and microscale fault illusions in multi-azimuth seismic coherence and curvature can be removed in the fused result.
