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  • 1
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    PANGAEA
    In:  Supplement to: Gibbin, Emma M; Gavish, Assaf; Krueger, Thomas; Kramarsky-Winter, Esti; Shapiro, Orr; Guiet, Romain; Jensen, Louise; Vardi, Assaf; Meibom, Anders (2018): Vibrio coralliilyticus infection triggers a behavioural response and perturbs nutritional exchange and tissue integrity in a symbiotic coral. The ISME Journal, https://doi.org/10.1038/s41396-018-0327-2
    Publication Date: 2023-12-23
    Description: We conducted two isotope experiments (described in Gibbin et al. 2018) to determine how the presence of pathogens influences resource partitioning in the coral holobiont. Specifically, we quantified: 1) 13C-assimilation in Symbiodinium and the amount of 13C-labelled photosynthates that are assimilated by the host; 2) the metabolic turnover of 13C in Symbiodinium and in their host and 3) the incorporation of bacterial-derived N within the tissues of the coral holobiont. NanoSIMS images (either 40×40 or 50×50 µm in size) were obtained by rasterizing a 16 keV Cs+ primary ion beam, focused to a spot-size of 150 nm, across the sample surface. Settings (dwell time = 5 ms; number of pixels = 256×256, layers = 5) were kept constant between images. Data was extracted from drift-corrected images using L'IMAGE (Dr. Larry Nittler, Carnegie Institution of Washington). Regions of interest (ROIs) were drawn around individual symbiont cells and the host gastrodermis (excluding symbionts), using the contour lines on the 12C14N- image. These ROIs were then used to quantify the average enrichment of 13C and 15N in each partner. Our measured values are expressed as Atom Percent Excess (APE, in %).
    Type: Dataset
    Format: application/vnd.openxmlformats-officedocument.spreadsheetml.sheet, 47.6 kBytes
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  • 2
    Publication Date: 2024-01-06
    Description: The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples. The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from an optical particle counter ([EDM]; EDM180 GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) instrument acquiring continuously during the full course of the campaign. Aerosols pumped through one of the ([MAST-PUMP]) inlets were channeled through a conductive tubing of 1.9 cm inner diameter to four parallel 47mm filter holders installed in the rear hold using a vacuum pump (Diaphragm pumpME16 NT, VACUUBRAND BmbH & Co KG, Wertheim, Germany) at a minimum flow rate of 30 lpm (20lpm prior to may 2016). Air was conducted to an optical particle counter ([EDM]; EDM180 GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) measuring and counting particles in the size range 0.25 - 32 µm as a 30 minutes average, both the particle concentration (nb cm-3) together with its normalized size distribution (dN/dlogDp (nb cm-3 log(nm)-1) i.e., the concentration divided by the log of the width of the bin).
    Keywords: aerosol; DATE/TIME; Fondation Tara Expeditions; FondTara; LATITUDE; Log-normal particle size distribution; LONGITUDE; Optical particle counter ([EDM]; EDM180 GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) measuring and counting particles in 30 minutes average; Pacific Ocean; Particle concentration, standard deviation; Particle number, total; size distribution; SV Tara; TARA_2016-2018; Tara_Pacific; TARA_PACIFIC_2016-2018; Tara Pacific Expedition; UMS; Underway, multiple sensors
    Type: Dataset
    Format: text/tab-separated-values, 1851846 data points
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  • 3
    Publication Date: 2024-01-06
    Description: The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples. The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from an optical particle counter ([EDM]; EDM180 GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) instrument acquiring continuously during the full course of the campaign. Aerosols pumped through one of the ([MAST-PUMP]) inlets were channeled through a conductive tubing of 1.9 cm inner diameter to four parallel 47mm filter holders installed in the rear hold using a vacuum pump (Diaphragm pumpME16 NT, VACUUBRAND BmbH & Co KG, Wertheim, Germany) at a minimum flow rate of 30 lpm (20lpm prior to may 2016). Air was conducted to an optical particle counter ([EDM]; EDM180 GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) measuring and counting particles in the size range 0.25 - 32 µm every 60 seconds.
    Keywords: aerosol; DATE/TIME; Fondation Tara Expeditions; FondTara; LATITUDE; LONGITUDE; Optical particle counter ([EDM]; EDM180 GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) measuring and counting particles in the size range 0.25 - 32 µm every 60 seconds; Pacific Ocean; Particle concentration, standard deviation; Particle number, total; size distribution; SV Tara; TARA_2016-2018; Tara_Pacific; TARA_PACIFIC_2016-2018; Tara Pacific Expedition; UMS; Underway, multiple sensors
    Type: Dataset
    Format: text/tab-separated-values, 30312 data points
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  • 4
    Publication Date: 2024-01-06
    Description: The Tara Pacific expedition (2016-2018) sampled coral ecosystems around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples. The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis. Here we provide the continuous dataset originating from scanning mobility particle sizer ([SMPS], SMPS-C GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) instruments acquiring continuously during the full course of the campaign. Aerosols pumped through one of the ([MAST-PUMP]) inlets were channeled through a conductive tubing of 1.9 cm inner diameter to four parallel 47mm filter holders installed in the rear hold using a vacuum pump (Diaphragm pumpME16 NT, VACUUBRAND BmbH & Co KG, Wertheim, Germany) at a minimum flow rate of 30 lpm (20lpm prior to may 2016). Air was conducted to a scanning mobility particle sizer ([SMPS], SMPS-C GRIMM Aerosol Technik Ainring GmbH & Co. KG, Ainring, Germany) measuring particles in the size range 0.025 – 0.70 µm. The SMPS was set to perform a full scan of particle distribution every 5 min. Data from [SMPS] are averaged at the 30 minute scale and provided both at the scale of particle concentration (nb cm-3) together with its normalized size distribution (dN/dlogDp (nb cm-3) i.e., the concentration divided by the log of the width of the bin).
    Keywords: aerosols; DATE/TIME; Fondation Tara Expeditions; FondTara; LATITUDE; Log-normal particle size distribution, normalized concentration at particle diameter 101.82 nm; Log-normal particle size distribution, normalized concentration at particle diameter 101.82 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 105.54 nm; Log-normal particle size distribution, normalized concentration at particle diameter 105.54 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 109.41 nm; Log-normal particle size distribution, normalized concentration at particle diameter 109.41 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 113.42 nm; Log-normal particle size distribution, normalized concentration at particle diameter 113.42 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 117.57 nm; Log-normal particle size distribution, normalized concentration at particle diameter 117.57 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 121.88 nm; Log-normal particle size distribution, normalized concentration at particle diameter 121.88 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 126.35 nm; Log-normal particle size distribution, normalized concentration at particle diameter 126.35 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 130.97 nm; Log-normal particle size distribution, normalized concentration at particle diameter 130.97 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 135.77 nm; Log-normal particle size distribution, normalized concentration at particle diameter 135.77 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 140.75 nm; Log-normal particle size distribution, normalized concentration at particle diameter 140.75 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 145.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 145.9 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 151.25 nm; Log-normal particle size distribution, normalized concentration at particle diameter 151.25 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 156.79 nm; Log-normal particle size distribution, normalized concentration at particle diameter 156.79 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 162.53 nm; Log-normal particle size distribution, normalized concentration at particle diameter 162.53 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 168.49 nm; Log-normal particle size distribution, normalized concentration at particle diameter 168.49 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 174.66 nm; Log-normal particle size distribution, normalized concentration at particle diameter 174.66 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 181.06 nm; Log-normal particle size distribution, normalized concentration at particle diameter 181.06 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 187.69 nm; Log-normal particle size distribution, normalized concentration at particle diameter 187.69 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 194.56 nm; Log-normal particle size distribution, normalized concentration at particle diameter 194.56 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 201.69 nm; Log-normal particle size distribution, normalized concentration at particle diameter 201.69 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 209.08 nm; Log-normal particle size distribution, normalized concentration at particle diameter 209.08 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 216.74 nm; Log-normal particle size distribution, normalized concentration at particle diameter 216.74 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 224.68 nm; Log-normal particle size distribution, normalized concentration at particle diameter 224.68 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 232.91 nm; Log-normal particle size distribution, normalized concentration at particle diameter 232.91 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 241.44 nm; Log-normal particle size distribution, normalized concentration at particle diameter 241.44 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 25.03 nm; Log-normal particle size distribution, normalized concentration at particle diameter 25.03 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 25.95 nm; Log-normal particle size distribution, normalized concentration at particle diameter 25.95 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 250.29 nm; Log-normal particle size distribution, normalized concentration at particle diameter 250.29 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 259.46 nm; Log-normal particle size distribution, normalized concentration at particle diameter 259.46 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 26.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 26.9 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 268.96 nm; Log-normal particle size distribution, normalized concentration at particle diameter 268.96 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 27.88 nm; Log-normal particle size distribution, normalized concentration at particle diameter 27.88 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 278.81 nm; Log-normal particle size distribution, normalized concentration at particle diameter 278.81 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 28.9 nm; Log-normal particle size distribution, normalized concentration at particle diameter 28.9 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 289.03 nm; Log-normal particle size distribution, normalized concentration at particle diameter 289.03 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 29.96 nm; Log-normal particle size distribution, normalized concentration at particle diameter 29.96 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 299.61 nm; Log-normal particle size distribution, normalized concentration at particle diameter 299.61 nm, standard deviation; Log-normal particle size distribution, normalized concentration at particle diameter 31.06 nm; Log-
    Type: Dataset
    Format: text/tab-separated-values, 2410457 data points
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Distributed computing 10 (1997), S. 199-225 
    ISSN: 1432-0452
    Keywords: Key words: Knowledge-based program ; Protocol ; Reasoning about knowledge ; multi-agent system
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Summary.  Reasoning about activities in a distributed computer system at the level of the knowledge of individuals and groups allows us to abstract away from many concrete details of the system we are considering. In this paper, we make use of two notions introduced in our recent book to facilitate designing and reasoning about systems in terms of knowledge. The first notion is that of a knowledge-based program. A knowledge-based program is a syntactic object: a program with tests for knowledge. The second notion is that of a context, which captures the setting in which a program is to be executed. In a given context, a standard program (one without tests for knowledge) is represented by (i.e., corresponds in a precise sense to) a unique system. A knowledge-based program, on the other hand, may be represented by no system, one system, or many systems. In this paper, we provide a sufficient condition for a knowledge-based program to be represented in a unique way in a given context. This condition applies to many cases of interest, and covers many of the knowledge-based programs considered in the literature. We also completely characterize the complexity of determining whether a given knowledge-based program has a unique representation, or any representation at all, in a given finite-state context.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Biological cybernetics 64 (1990), S. 117-128 
    ISSN: 1432-0770
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Computer Science , Physics
    Notes: Abstract Under a 90° rotation of motor space relative to visual space, human two-dimensional aiming movements frequently take the form of smooth arcs such as spirals and semi-circles. A time-independent differential equation explains this tendency in terms of a rotation-induced vector field made up, at each point in the two-dimensional space, of two input vectors. One vector represents a visual error signal and the other represents a motor error signal. A trajectory's instantaneous direction of movement at each point can be described as the resultant of the two vectors. This mathematical formulation incorporates plausible visual-motor mechanisms and, when expressed in polar coordinates, leads to a new method for analyzing the spatial properties of movements (i.e., movement paths). Plots of the angle between the resultant and the target vector (φ) against distance from the target (r, in the polar representation) summarize the arc-shaped movement paths as a simple relation that can be analyzed statistically with respect to properties such as monotonicity. The polar representation is a plausible representation of visually-guided movements, with the visual error vector functioning as an objective function relative to which behavior is optimized. We extend the model and ther,φ movement path analysis to non-90° rotations, and we find that the model predicts an observed qualitative shift in behavior for rotations greater than 90°. It also predicts qualitatively different path shapes observed under visual-motor reflections.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    College Park, Md. : American Institute of Physics (AIP)
    The Journal of Chemical Physics 93 (1990), S. 7506-7507 
    ISSN: 1089-7690
    Source: AIP Digital Archive
    Topics: Physics , Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    College Park, Md. : American Institute of Physics (AIP)
    The Journal of Chemical Physics 112 (2000), S. 8743-8746 
    ISSN: 1089-7690
    Source: AIP Digital Archive
    Topics: Physics , Chemistry and Pharmacology
    Notes: I study the effect of intermolecular interactions on coherent tunneling racemization within the framework of the Hund double well model. Two self-consistent equations for the well population amplitudes, coupled by a tunneling matrix element, are used to describe the system dynamics. It is shown that the equations of motion are nonlinear due to the difference between homochiral interactions and heterochiral interactions. The consequence of this nonlinearity is that chiral molecular configurations are far more stable than expected by the Hund model for isolated molecules. Moreover, when the homochiral interactions are energetically favorable to heterochiral interactions (weaker homochiral repulsive interactions or stronger homochiral attractive interactions), spontaneous symmetry breaking may amplify the optical activity of a nearly racemic mixture. © 2000 American Institute of Physics.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    International journal of immunogenetics 16 (1989), S. 0 
    ISSN: 1744-313X
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Biology , Medicine
    Notes: We have used the 3-Methylcholanthrene induced T-10 fibrosarcoma tumour cell system (H-2b xH-2k)F1 to elucidate the possible correlation between metastatic potential, expression of individual H-2 antigens and susceptibility to NK cells.Transfection of the non-metastatic and NK sensitive IC9 cells (Db+, Dk-, Kb-, Kk-) with the H-2Dk gene, altered the metastatic phenotype of the parental cells, yet had no effect on the susceptibility of these tumour cells to lysis by NK and did not elicit a specific CTL response in syngeneic hosts. Variants of the metastatic and NK resistant IE7 clone (Db+, Dk+, Kb-, Kk-), lacking H-2Dk, were selected by treatment with monoclonal anti H-2Dk antibodies and complement. These variants were sensitive to NK and poorly or non metastatic. Retransfection of ‘Dk′loss’ variants with the H-2Dk gene, resulted in the isolation of several clones expressing a wide range of metastatic phenotypes but maintained sensitivity to NK. These results indicate that the H-2D region of the MHC and or closely linked genes may be involved in the complex interrelationship between target susceptibility to NK and metastasis.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 189 (1961), S. 90-95 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] ON February 13 and April 1, 1960, nuclear test devices, reportedly in the kiloton range, were exploded in southern Algeria. These tests followed a prolonged period during which no nuclear tests were conducted, with the result that fall-out of short-lived fission products had decreased to a very low ...
    Type of Medium: Electronic Resource
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