967 resultados para Lloyd, James--1728-1810


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Contains medical cases copied by James Lloyd (1728-1810), primarily between 1751 and 1754, from Mr. Steed, an apothecary at Guy's Hospital in London, England. The volume has additional medical cases dating from 1780 to 1787. Lloyd transcribed the names, ages, and symptoms of the patients, as well as the medicines and medical care delivered to them. The volume is divided into chapters based on the type of case, which included vision loss; fluor albus, or leucorrhoea; diabetes; and dysentery. There is also a letter pasted into the volume addressed to Dr. Brigham of the Boston Medical Library Association from Lloyd's great-grandson, dated 4 November 1887.

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"Principal works consulted": p. 249

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Reprinted with additions from "Notes and queries."

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Mode of access: Internet.

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Afterwards reprinted with title Narrative of the voyages round the world performed by Captain James Cook.

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Adapted and abridged from the biography by Andrew Kippis.

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Amer. Art. Assoc., catalog, 4-6 Feb. 1919 (Townsend sale) no. 560, describes as the 1st ed. with these ill.; only ed. cited in BM 238:106 and NUC pre-1956 591:538.

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Includes bibliographies and indexes.

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First published in London, 1788, under title: The life of Captain James Cook.

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Added t.-p., illus., v. 1.

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Mode of access: Internet.

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Provision of credit has being identified as an important instrument for improving the welfare of smallholder farmers directly and for enhancing productive capacity through financing investment by the farmers in their human and physical capital. This study investigated the individual and household characteristics that influence credit market access in Amathole District Municipality, Eastern Cape Province, South Africa, using a cross sectional data from smallholder farmers’ household survey. The aim is to provide a better understanding of the households’ level socio-economic characteristics, not only because they influence household’s demand for credit but also due to the fact that potential lenders are most likely to base their assessment of borrowers’ creditworthiness on such characteristics. The results of the logistic regression suggest that credit market access was significantly influenced by variables such as gender, education, households’ income, value of assets, savings, dependency ratio, repayment capacity and social capital. Implications for rural credit delivery are discussed.

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Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (μ) and the heat flux negative feedback (α), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback, μ, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of α in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback, α SW, are the main source of model uncertainty in α. Most models do not successfully represent the negative αSW in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled α SW biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect α SW. We further show that the negative latent heat flux feedback, α LH, exhibits less diversity than α SW and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model αLH differences.