In vivo fluorescence has a wide application in analyzing microalgae, including assessing phytoplankton biomass, rates of primary production and physiological status. This study describes a preliminary investigation on...In vivo fluorescence has a wide application in analyzing microalgae, including assessing phytoplankton biomass, rates of primary production and physiological status. This study describes a preliminary investigation on the joint application of the three kinds of fluorescence analysis in the physiological study of microalgae. Flow cytometry and fluorescence spectrometry were used to obtain the in vivo static fluorescence information of pigments, and a Pulsed-Amplitude-Modulation chlorophyll fluorometer was used to detect the dynamic fluorescence of chlorophyll. The validity of the joint application was proved by analyzing two labora- tory cultured Arctic microalgae, Pseudo-nitzschia delicatissima （Bacillariophyceae） and Thalassiosira sp. The higher value of minimum fluorescence yield in dark-adapted state （Fo）, actual photochemical efficiency of PSll （ФPSII）, and electron transport rate （ETR） exhibited positive results in a higher cell abundance and chlorophyll a content of P. delicatissima; whereas higher fl-carotene content of Thalassiosira sp. played an important role in the protection of photosynthesis.展开更多
With the explosive growth of information, more and more organizations are deploying private cloud systems or renting public cloud systems to process big data. However, there is no existing benchmark suite for evaluati...With the explosive growth of information, more and more organizations are deploying private cloud systems or renting public cloud systems to process big data. However, there is no existing benchmark suite for evaluating cloud performance on the whole system level. To the best of our knowledge, this paper proposes the first benchmark suite CloudRank-D to benchmark and rank cloud computing sys- tems that are shared for running big data applications. We an- alyze the limitations of previous metrics, e.g., floating point operations, for evaluating a cloud computing system, and propose two simple metrics： data processed per second and data processed per Joule as two complementary metrics for evaluating cloud computing systems. We detail the design of CloudRank-D that considers representative applications, di- versity of data characteristics, and dynamic behaviors of both applications and system software platforms. Through experi- ments, we demonstrate the advantages of our proposed met- tics. In several case studies, we evaluate two small-scale de- ployments of cloud computing systems using CloudRank-D.展开更多
基金financially supported by the National Natural Science Foundation of China (Grant no.41076130)the SOA Youth Marine Science Foundation (Grant no.2010116)the Open Research Foundation of Laboratory of Marine Ecosystem and Biogeochemistry,SOA (Grant no.LMEB200902)
文摘In vivo fluorescence has a wide application in analyzing microalgae, including assessing phytoplankton biomass, rates of primary production and physiological status. This study describes a preliminary investigation on the joint application of the three kinds of fluorescence analysis in the physiological study of microalgae. Flow cytometry and fluorescence spectrometry were used to obtain the in vivo static fluorescence information of pigments, and a Pulsed-Amplitude-Modulation chlorophyll fluorometer was used to detect the dynamic fluorescence of chlorophyll. The validity of the joint application was proved by analyzing two labora- tory cultured Arctic microalgae, Pseudo-nitzschia delicatissima （Bacillariophyceae） and Thalassiosira sp. The higher value of minimum fluorescence yield in dark-adapted state （Fo）, actual photochemical efficiency of PSll （ФPSII）, and electron transport rate （ETR） exhibited positive results in a higher cell abundance and chlorophyll a content of P. delicatissima; whereas higher fl-carotene content of Thalassiosira sp. played an important role in the protection of photosynthesis.
文摘With the explosive growth of information, more and more organizations are deploying private cloud systems or renting public cloud systems to process big data. However, there is no existing benchmark suite for evaluating cloud performance on the whole system level. To the best of our knowledge, this paper proposes the first benchmark suite CloudRank-D to benchmark and rank cloud computing sys- tems that are shared for running big data applications. We an- alyze the limitations of previous metrics, e.g., floating point operations, for evaluating a cloud computing system, and propose two simple metrics： data processed per second and data processed per Joule as two complementary metrics for evaluating cloud computing systems. We detail the design of CloudRank-D that considers representative applications, di- versity of data characteristics, and dynamic behaviors of both applications and system software platforms. Through experi- ments, we demonstrate the advantages of our proposed met- tics. In several case studies, we evaluate two small-scale de- ployments of cloud computing systems using CloudRank-D.
