This dataset includes information about approximately 6,000 books and other items with bibliographic data as well as summary information about when the item circulated in the Shakespeare and Company lending library and the number of times an item was borrowed or purchased.
The Shakespeare and Company Project: Lending Library Events dataset includes information about approximately 35,000 lending library events including membership activities such as subscriptions, renewals and reimbursements and book-related activities such as borrowing and purchasing. For events related to lending library cards that are available as digital surrogates, IIIF links are provided.
The Shakespeare and Company Project makes three datasets available to download in CSV and JSON formats. The datasets provide information about lending library members; the books that circulated in the lending library; and lending library events, including borrows, purchases, memberships, and renewals. The datasets may be used individually or in combination site URLs are consistent identifiers across all three. The DOIs for each dataset are as follows: Members (https://doi.org/10.34770/nsa4-3t76); Books (https://doi.org/10.34770/079z-h206); Events (https://doi.org/10.34770/rtbp-kv40).
Brunner, Claudia E.; Kiefer, Janik; Hansen, Martin O. L.; Hultmark, Marcus
Reynolds number effects on the aerodynamics of the moderately thick NACA 0021 airfoil were experimentally studied by means of surface-pressure measurements. The use of a high-pressure wind tunnel allowed for variation of the chord Reynolds number over a range of 5.0 × 10^5 ≤ Re_c ≤ 7.9 × 10^6. The angle of attack was incrementally increased and decreased over a range of 0° ≤ alpha ≤ 40°, spanning both the attached and stalled regime at all Reynolds numbers. As such, attached and separated conditions, as well as the static stall and reattachment processes were studied. A fundamental change in the flow behaviour was observed around Re_c= 2.0 × 10^6. As the Reynolds number was increased beyond this value, the stall type gradually shifted from trailing-edge stall to leading-edge stall. The stall angle and the maximum lift coefficient increased with Reynolds number. Once the flow was separated, the separation point moved upstream and the suction peak decreased in magnitude with increasing Reynolds number. Two distinct types of hysteresis in reattachment were observed.
One aspect of the interaction between fast ions and magnetohydrodynamic (MHD) instabilities is the fast ion transport. Coupled kink and tearing MHD instabilities have also been reported to cause fast ion transport. Recently, the ''kick" model has been developed to compute the evolution of the fast ion distribution from the neutral beam injection using instabilities as phase space resonance sources. The goal of this paper is to utilize the kick model to understand the physics of fast ion transport caused by the coupled kink and tearing modes. Soft X-ray diagnostics are used to identify the mode parameters in NSTX. The comparison of neutron rates measured and computed from time-dependent TRANSP simulation with the kick model shows the coupling of kink and tearing mode is important in determination of the fast ion transport. The numerical scan of the mode parameters shows that the relative phase of the kink and tearing modes and the overlapping of kink and tearing mode resonances in the phase space can affect the fast ion transport, suggesting that the synergy of the coupled modes may be causing the fast ion transpor
Chang, Claire H. C.; Lazaridi, Christina; Yeshurun, Yaara; Norman, Kenneth A.; Hasson, Uri
This study examined how the brain dynamically updates event representations by integrating new information over multiple minutes while segregating irrelevant input. A professional writer custom-designed a narrative with two independent storylines, interleaving across minute-long segments (ABAB). In the last (C) part, characters from the two storylines meet and their shared history is revealed. Part C is designed to induce the spontaneous recall of past events, upon the recurrence of narrative motifs from A/B, and to shed new light on them. Our fMRI results showed storyline-specific neural patterns, which were reinstated (i.e. became more active) during storyline transitions. This effect increased along the processing timescale hierarchy, peaking in the default mode network. Similarly, the neural reinstatement of motifs was found during part C. Furthermore, participants showing stronger motif reinstatement performed better in integrating A/B and C events, demonstrating the role of memory reactivation in information integration over intervening irrelevant events.
The dielectric function for "Astrodust" grain material is provided for different assumed values of the dust grain shape (spheroid axis ratio) and porosity (vacuum fraction), and fraction of the interstellar iron present as metallic inclusions. For each case, the dielectric function is obtained by requiring that the grains reproduce the observed infrared opacity, and match to a physically reasonable dielectric function at 1 micron, and extending to X-ray energies. The derived dielectric functions satisfy the Kramers-Kronig relations. Dielectric functions are provided from 1 Angstrom to 5 cm (12.4 keV to 2.59e-5 eV).
For each dielectric function, we also calculate absorption and scattering corss sections for spheroidal grains, for three orientations of the grain relative to incident linearly-polarized light, for wavelengths from the Lyman limit (0.0912 micron) to the microwave (4 cm), and grain "effective radii" a_eff from 3.162A to 5.012 micron.
Verdoolaege, G.; Kaye, S.M.; Angioni, C.; Kardaunn, O.W.J.F.; Maslov, M.; Romanelli, M.; Ryter, F.; Thomsen, K.
The multi-machine ITPA Global H-mode Confinement Database has been upgraded with new data from JET with the ITER-like wall and ASDEX Upgrade with the full tungsten wall. This paper describes the new database and presents results of regression analysis to estimate the global energy confinement scaling in H-mode plasmas using a standard power law. Various subsets of the database are considered, focusing on type of wall and divertor materials, confinement regime (all H-modes, ELMy H or ELM-free) and ITER-like constraints. Apart from ordinary least squares, two other, robust regression techniques are applied, which take into account uncertainty on all variables. Regression on data from individual devices shows that, generally, the confinement dependence on density and the power degradation are weakest in the fully metallic devices. Using the multi-machine scalings, predictions are made of the confinement time in a standard ELMy H-mode scenario in ITER. The uncertainty on the scaling parameters is discussed with a view to practically useful error bars on the parameters and predictions. One of the derived scalings for ELMy H-modes on an ITER-like subset is studied in particular and compared to the IPB98(y,2) confinement scaling in engineering and dimensionless form. Transformation of this new scaling from engineering variables to dimensionless quantities is shown to result in large error bars on the dimensionless scaling. Regression analysis in the space of dimensionless variables is therefore proposed as an alternative, yielding acceptable estimates for the dimensionless scaling. The new scaling, which is dimensionally correct within the uncertainties, suggests that some dependencies of confinement in the multi- machine database can be reconciled with parameter scans in individual devices. This includes vanishingly small dependence of confinement on line-averaged density and normalized plasma pressure (β), as well as a noticeable, positive dependence on effective atomic mass and plasma triangularity. Extrapolation of this scaling to ITER yields a somewhat lower confinement time compared to the IPB98(y, 2) prediction, possibly related to the considerably weaker dependence on major radius in the new scaling (slightly above linear). Further studies are needed to compare more flexible regression models with the power law used here. In addition, data from more devices concerning possible ‘hidden variables’ could help to determine their influence on confinement, while adding data in sparsely populated areas of the parameter space may contribute to further disentangling some of the global confinement dependencies in tokamak plasmas.