60 research outputs found
Tris(1,10-phenanthroline-κ2 N,N′)nickel(II) dinitrate tetrahydrate
In the title complex, [Ni(C12H8N2)3](NO3)2·4H2O, the NiII ion is octahedrally coordinated by three bidentate 1,10-phenanthroline ligands, each forming a five-membered chelate ring. In the crystal, O—H⋯O and C—H⋯O hydrogen bonds are present between the complex cations, nitrate anions and water molecules. O—H⋯O hydrogen bonds between the uncoordinated water molecules lead to the formation of a four-membered ring water cluster, with a planar configuration. There were an additional five grossly disordered water molecules in the asymmetric unit, which were removed by the subroutine SQUEEZE; these were were excluded in the calculation of the molecular weight, etc. π–π stacking interactions between the aromatic rings are also observed [centroid–centroid distances = 3.697 (2), 3.728 (2) and 3.761 (2) Å]
Study of in the vicinity of
Using 2917 of data accumulated at 3.773~,
44.5~ of data accumulated at 3.65~ and data accumulated
during a line-shape scan with the BESIII detector, the reaction
is studied considering a possible interference
between resonant and continuum amplitudes. The cross section of
,
, is found to have two
solutions, determined to be () pb with the phase angle
(0.11 pb at the 90% confidence level),
or ) pb with both of which
agree with a destructive interference. Using the obtained cross section of
, the cross section of , which is useful information for the future PANDA experiment, is
estimated to be either () nb ( nb at 90% C.L.) or
nb
Operational performance of a novel heat pump coupled with mini-channel PV/T and thermal panel in low solar radiation
Extraction, Structural Characterization, and Biological Functions of Lycium Barbarum Polysaccharides: A Review
Inclusion Complex of 2-Methyl Mercapto Phenothiazine with Hydroxy Propyl β-Cyclodextrin: Characterization and Cytotoxic Activity Evaluation
Floreon+ Modules: A Real-World HARPA Application in the High-End HPC System Domain
reserved9siThis chapter is centered around uncertainty computation with on-demand resource allocation for run-off prediction in a High-Performance Computer environment. Our research stands on a runtime operating system that automatically adapts resource allocation with the computation to provide precise outcomes before the time deadline. In our case, input data comes from several gauging stations, and when newly updated data arrives, models must be re-executed to provide accurate results immediately. Since the models run continuously (24/7), their computational demand is different during various hydrological events (e.g. periods with heavy rain and without any rain) and therefore computational resources have to be balanced according to the event severity. Although these kinds of models should run constantly, they are very computationally demanding during discrete periods of time, for example in the case of heavy rain. Then, the accuracy of the results must be as close as possible to reality. The work relies on the HARPA runtime resource manager that adapts resource allocation to the runtime-variable performance demand of applications. The resource assignment is temperature-aware: the application execution is dynamically migrated to the coolest cores, and this has a positive impact on the system reliability.mixedAntoni Portero, Radim Vavrik, Martin Golasowski, Jiri Sevcik, Giuseppe Massari, Simone Libutti, William Fornaciari, Stepan Kuchar, Vit VondrakPortero, Antoni; Vavrik, Radim; Golasowski, Martin; Sevcik, Jiri; Massari, Giuseppe; Libutti, Simone; Fornaciari, William; Kuchar, Stepan; Vondrak, Vi
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