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42. Shakespeare and Company Project Dataset: Lending Library Books
- Author(s):
- Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Allen, Paige; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin Yun; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Gautreau, Violet; Gjaja, Alex; Green, Elspeth; Hart, Isaac; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Macksey, Elizabeth; Mahoney, Cate; Mancino, Francesca; McCarthy, Jesse D.; Naydan, Mary; Root, Sally; Ruehl, Isabel; Thode, Sylvie; Vandermel, Katherine; VanSant, Camey; Wulfman, Clifford E.
- Abstract:
- 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.
- Type:
- Dataset
- Issue Date:
- 29 January 2021
43. Shakespeare and Company Project Dataset: Lending Library Events
- Author(s):
- Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Allen, Paige; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin Yun; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Gautreau, Violet; Gjaja, Alex; Green, Elspeth; Hart, Isaac; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Macksey, Elizabeth; Mahoney, Cate; Mancino, Francesca; McCarthy, Jesse D.; Naydan, Mary; Root, Sally; Ruehl, Isabel; Thode, Sylvie; Vandermel, Katherine; VanSant, Camey; Wulfman, Clifford E.
- Abstract:
- 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.
- Type:
- Dataset
- Issue Date:
- 29 January 2021
44. Shakespeare and Company Project Dataset: Lending Library Members
- Author(s):
- Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Allen, Paige; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin Yun; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Gautreau, Violet; Gjaja, Alex; Green, Elspeth; Hart, Isaac; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Macksey, Elizabeth; Mahoney, Cate; Mancino, Francesca; McCarthy, Jesse D.; Naydan, Mary; Root, Sally; Ruehl, Isabel; Thode, Sylvie; Vandermel, Katherine; VanSant, Camey; Wulfman, Clifford E.
- Abstract:
- The Shakespeare and Company Project: Lending Library Members dataset includes information about approximately 5,600 members of Sylvia Beach's Shakespeare and Company lending library.
- Type:
- Dataset
- Issue Date:
- 29 January 2021
45. Shakespeare and Company Project Dataset: Lending Library Members, Books, Events
- Author(s):
- Kotin, Joshua; Koeser, Rebecca Sutton; Adair, Carl; Alagappan, Serena; Allen, Paige; Bauer, Jean; Browne, Oliver J.; Budak, Nick; Calver, Harriet; Chow, Jin Yun; Davis, Ian; Doroudian, Gissoo; Engel, Currie; Gautreau, Violet; Gjaja, Alex; Green, Elspeth; Hart, Isaac; Hicks, Benjamin; Joelson, Madeleine E.; Kelly, Carolyn; Krolewski, Sara; Li, Xinyi; Maag, Ellie; Macksey, Elizabeth; Mahoney, Cate; Mancino, Francesca; McCarthy, Jesse D.; Naydan, Mary; Root, Sally; Ruehl, Isabel; Thode, Sylvie; Vandermel, Katherine; VanSant, Camey; Wulfman, Clifford E.
- Abstract:
- 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).
- Type:
- Dataset
- Issue Date:
- 29 January 2021
46. CrvA and CrvB form a curvature-inducing module sufficient to induce cell shape complexity in Gram-negative bacteria
- Author(s):
- Martin, Nicholas R; Blackman, Edith; Bratton, Benjamin P; Chase, Katelyn J; Bartlett, Thomas M; Gitai, Zemer
- Abstract:
- Bacterial species have diverse cell shapes that enable motility, colonization, and virulence. The cell wall defines bacterial shape and is primarily built by two cytoskeleton-guided synthesis machines, the elongasome and the divisome. However, the mechanisms producing complex shapes, like the curved-rod shape of Vibrio cholerae, are incompletely defined. Previous studies have reported that species-specific regulation of cytoskeleton-guided machines enables formation of complex bacterial shapes such as cell curvature and cellular appendages. In contrast, we report that CrvA and CrvB are sufficient to induce complex cell shape autonomously of the cytoskeleton in V. cholerae. The autonomy of the CrvAB module also enables it to induce curvature in the Gram-negative species Escherichia coli, Pseudomonas aeruginosa, Caulobacter crescentus, and Agrobacterium tumefaciens. Using inducible gene expression, quantitative microscopy, and biochemistry we show that CrvA and CrvB circumvent the need for patterning via cytoskeletal elements by regulating each other to form an asymmetrically-localized, periplasmic structure that directly binds to the cell wall. The assembly and disassembly of this periplasmic structure enables dynamic changes in cell shape. Bioinformatics indicate that CrvA and CrvB may have diverged from a single ancestral hybrid protein. Using fusion experiments in V. cholerae, we find that a synthetic CrvA/B hybrid protein is sufficient to induce curvature on its own, but that expression of two distinct proteins, CrvA and CrvB, promotes more rapid curvature induction. We conclude that morphological complexity can arise independently of cell shape specification by the core cytoskeleton-guided synthesis machines.
- Type:
- Dataset
- Issue Date:
- 2021
47. Data from "Vapor-liquid equilibrium of water with the MB-pol many-body potential"
- Author(s):
- Muniz, Maria Carolina; Gartner III, Thomas E.; Riera, Marc; Knight, Christopher; Yue, Shuwen; Paesani, Francesco; Panagiotopoulos, Athanassios Z.
- Abstract:
- This dataset contains all data (including input files, simulation trajectories as well as other data files and analysis scripts) related to the publication "Vapor-liquid equilibrium of water with the MB-pol many-body potential" by Muniz et al. in preparation (2021). In this work, we assessed the performance of the MB-pol many-body potential with respect to water's vapor-liquid equilibrium properties. Through the use of direct coexistence molecular dynamics, we calculated properties such as coexistence densities, surface tension, vapor pressures and enthalpy of vaporization. We found that MB-pol is able to predict these properties in good agreement with experimental data. The results attest to the chemical accuracy of MB-pol and its large range of application across water's phase diagram.
- Type:
- Dataset
- Issue Date:
- 2021
48. Data from "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water"
- Author(s):
- Gartner, Thomas III; Zhang, Linfeng; Piaggi, Pablo; Car, Roberto; Panagiotopoulos, Athanassios; Debenedetti, Pablo
- Abstract:
- This dataset contains all data related to the publication "Signatures of a liquid-liquid transition in an ab initio deep neural network model for water", by Gartner et al., 2020. In this work, we used neural networks to generate a computational model for water using high-accuracy quantum chemistry calculations. Then, we used advanced molecular simulations to demonstrate evidence that suggests this model exhibits a liquid-liquid transition, a phenomenon that can explain many of water's anomalous properties. This dataset contains links to all software used, all data generated as part of this work, as well as scripts to generate and analyze all data and generate the plots reported in the publication.
- Type:
- Dataset
- Issue Date:
- July 2020
49. A dual-mechanism antibiotic kills Gram-negative bacteria and avoids drug resistance
- Author(s):
- Martin, James K; Sheehan, Joseph P; Bratton, Benjamin P; Moore, Gabriel M; Mateus, André; Li, Sophia Hsin-Jung; Kim, Hahn; Rabinowitz, Joshua D; Typas, Athanasios; Savitski, Mikhail M; Wilson, Maxwell Z; Gitai, Zemer
- Abstract:
- The rise of antibiotic resistance and declining discovery of new antibiotics have created a global health crisis. Of particular concern, no new antibiotic classes have been approved for treating Gram-negative pathogens in decades. Here, we characterize a compound, SCH-79797, that kills both Gram-negative and Gram-positive bacteria through a unique dual-targeting mechanism of action (MoA) with undetectably-low resistance frequencies. To characterize its MoA, we combined quantitative imaging, proteomic, genetic, metabolomic, and cell-based assays. This pipeline demonstrates that SCH-79797 has two independent cellular targets, folate metabolism and bacterial membrane integrity, and outperforms combination treatments in killing MRSA persisters. Building on the molecular core of SCH-79797, we developed a derivative, Irresistin-16, with increased potency and showed its efficacy against Neisseria gonorrheae in a mouse vaginal infection model. This promising antibiotic lead suggests that combining multiple MoAs onto a single chemical scaffold may be an underappreciated approach to targeting challenging bacterial pathogens.
- Type:
- Dataset
- Issue Date:
- 20 May 2020
50. Data from a flume experiment of passive scalar diffusion within vegetation canopies using laser-induced fluorescence
- Author(s):
- Ghannam, Khaled; Poggi, Davide; Katul, Gabriel; Bou-Zeid, Elie
- Abstract:
- This dataset is a sequence of laser-induced fluorescence images of a dye injected in a channel flow with canopy-like stainless steel rods simulating a vegetation canopy stand. The data is acquired close to the channel bottom at z/h=0.2, where z is the height referenced to the channel bed and h is the canopy height. The dataset provides spatial distribution of scalar concentration in a plane parallel to the channel bed. The data has been used (but the data itself has not been published or available to the public) in previous work. The references are: Ghannam, K., Poggi, D., Porporato, A., & Katul, G. (2015). The spatio-temporal statistical structure and ergodic behaviour of scalar turbulence within a rod canopy. Boundary-Layer Meteorology,157(3), 447–460. Ghannam, K, Poggi, D., Bou-Zeid, E., Katul, G. (2020). Inverse cascade evidenced by information entropy of passive scalars in submerged canopy flows. Geophysical Research Letters (accepted).
- Type:
- Dataset
- Issue Date:
- 22 April 2020