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13,679
Life Sciences
, 2011
"... The 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, alias: µTAS 2011(miniaturized total analysis systems), is a premier international forum for reporting advances in microfluidic systems, nanotechnology, and chemical and biological analysis, synthesis, and dete ..."
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The 15th International Conference on Miniaturized Systems for Chemistry and Life Sciences, alias: µTAS 2011(miniaturized total analysis systems), is a premier international forum for reporting advances in microfluidic systems, nanotechnology, and chemical and biological analysis, synthesis
The science of emotional intelligence
, 2005
"... This article presents a framework for emotiolllJl intelligenCl!, a set of skills hypothesized to contribute to the accurate appraisal and expression of emotion in oneself and in others, the effective regulation of emotion in self and others, and the use of feelings to motivate, plan, and achieve in ..."
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Cited by 887 (38 self)
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in one's life. We start by reviewing the debate about the adaptive versus maladaptive qualities of emotion. We then explore the literature on intelligence, and especiaUy social intelligence. to examine the place of emotion in traditional intelligence conceptions. A framework for integrating
Statistical Models in Environmental and Life Sciences
, 2006
"... Statistical models in environmental and life sciences ..."
Life Sciences
"... Researchers in various areas, e.g. medicine, agriculture and environmental sciences, use biomedical data sources and tools to answer different research questions or to solve various tasks, for instance, in drug discovery or in research on the influence of environmental factors on human health and di ..."
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and diseases. Due to this recent explosion of the amount of on-line accessible data and tools, finding the relevant sources and retrieving the relevant information is not an easy task. Further, often information from different sources needs to be integrated. The vision of a Semantic Web for life sciences
Life Science,
, 2016
"... A bacterial strain, CS12T, which was isolated from soil around a wastewater treatment plant, was subjected to a polyphasic taxonomic study using phenotypic characterizations and genetic methods. The cell wall of strain CS12T contains meso-diaminopimelic acid as the diamino acid but no arabinose and ..."
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A bacterial strain, CS12T, which was isolated from soil around a wastewater treatment plant, was subjected to a polyphasic taxonomic study using phenotypic characterizations and genetic methods. The cell wall of strain CS12T contains meso-diaminopimelic acid as the diamino acid but no arabinose and galactose. The predominant menaquinone is MK-8(H4). Mycolic acids are absent. Strain CS12T has a cellular fatty acid profile containing saturated, unsaturated, branched and 10-methyl fatty acids. The major fatty acids are iso-C16:0, C18:1 x9c and anteiso-C17:0. The GMC content is 69 mol%. A phylogenetic tree based on 16S rDNA sequences showed that strain CS12T forms an evolutionary lineage within the radiation enclosing the members of the family Intrasporangiaceae and, in particular, a coherent cluster with Janibacter limosus DSM 11140T. The level of 16S rDNA similarity between strain CS12T and J. limosus DSM 11140T is 98<7%. The phenotypic characteristics and DNA–DNA relatedness data indicate that strain CS12T should be distinguished from J. limosus DSM 11140T. Therefore, on the basis of the data presented, a new species of the genus Janibacter, Janibacter terrae, is proposed. The type strain of the new species is strain CS12T (flKCCM 80001T fl JCM 10705T).
Life Sciences
"... This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or sel ..."
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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier’s archiving and manuscript policies are encouraged to visit:
[life SCIENCES]
"... Functional magnetic resonance imaging (fMRI) is a noninvasive, powerful tool that has been utilized in both research and clinical arenas since the early 1990s [1] and has provided valuable insights to the understanding of the human brain function. fMRI has enabled researchers to directly study the t ..."
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Functional magnetic resonance imaging (fMRI) is a noninvasive, powerful tool that has been utilized in both research and clinical arenas since the early 1990s [1] and has provided valuable insights to the understanding of the human brain function. fMRI has enabled researchers to directly study the temporal and spatial changes in the brain as a function of various stimuli. Because it relies on the detection of small intensity changes over time, fMRI poses significant challenges for data analysis techniques. Traditional model-based analysis approaches—such as linear regression— are robust, yet often too rigid to capture the richness of the human brain activation. Independent component analysis (ICA), on the other hand, is a datacentric approach that provides a more flexible framework for the analysis of fMRI data. For simplicity and tractability, most fMRI analysis techniques to date have discarded the phase of the fMRI data. However, the phase information may be quite valuable for the analysis of the natively complex fMRI data. ICA facilitates the analysis of fMRI data in its complex form by eliminating the need to explicitly model the phase behavior. In what follows, we discuss the application of real and complex-valued ICA to fMRI data analysis and present two examples where ICA has proved particularly useful.
Results 1 - 10
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13,679