1,725,799 research outputs found
Ice falls, below Old Man's Cave. Compare #2865.
No full textIce falls, below Old Man's Cave. Compare #2865. (from T. J. Parkins). Item #330
Socio-demographic characteristics of the study participants (n = 2865).
No full textSocio-demographic characteristics of the study participants (n = 2865).</p
Begonnen mit Zugangs-Nr. 2218 am 27.11.68 : Abgeschlossen mit der Zugangs-Nr. 2865 am [28.5.97]
No full textBEGONNEN MIT ZUGANGS-NR. 2218 AM 27.11.68 : ABGESCHLOSSEN MIT DER ZUGANGS-NR. 2865 AM [28.5.97]
Zugangs- und Abgangsverzeichnis der Abteilung L = Liszt-Bibliothek. (-)
Begonnen mit Zugangs-Nr. 2218 am 27.11.68 : Abgeschlossen mit der Zugangs-Nr. 2865 am [28.5.97] (IV) ( - )
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Wilson, John W. (SC 2865)
No full textFinding aid and full text (click on Additional Files below) for Manuscripts Small Collection 2865. Letter, 2 July 1864, of John W. Wilson, Company B, 2nd Kentucky Battalion Cavalry, written from Bristol, Virginia to the father of Private James Minter informing him that his son was killed at the 2nd Battle of Mt. Sterling, Kentucky and praising his character. Includes associated data on Wilson and Minter
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Abstract 2865: Protection from chemotherapy-induced alopecia by cytotech lbs API 31543 in a multichemotherapy course model of chloroleukemia
No full textAbstract
Alopecia remains the one side-effect of chemotherapy for which there is no therapeutic intervention. We have recently developed a multi-course chemotherapy rat model of transplantable chloroleukemia (MIAC51) in which to study Chemotherapy-[[Unsupported Character - Codename &shy;]]Induced Alopecia (CIA). This model provides the opportunity to study CIA and the cancer cells throughout multiple courses of chemotherapy. In the present study, we investigated the effect of calcitriol in a proprietary delivery system, Cytotech Labs API 31543 to protect from CIA using the following chemotherapy regimens: cyclophosphamide; cyclophosphamide and doxorubicin; cyclophosphamide, doxorubicin and cytarabine; cyclophosphamide, paclitaxel and etoposide; doxorubicin, paclitaxel and etoposide. Animals were injected intraperitoneally with 1×105 MIAC51 on day 5. Thereafter, 0.2µg of API 31543 or vehicle control was applied topically over the head area daily starting on day 6 for 6 consecutive days for the first course. Rats were isolated for 6 hours. Subsequently, the treated area was cleaned with soap and water and rats were returned to their litters. For the first cycle, chemotherapy regimens were administered on day 13, intraperitoneally in a total volume of 0.1 mL. Animals positive for leukemic cells in smears were euthanized on day 23. On day 31, a second anagen cycle was induced by clipping the hair in the neck area on leukemia survivors. Animals were then treated with 0.2 µg API 31543 on day 40 for 6 days in the shaven area. Chemotherapy regimens were then administered on day 46. In both cycles, alopecia was recorded 10 days after the last dose of chemotherapy. Neonatal rats treated with 0.2µg of API 31543 in the head area exhibited localized protection. Similarly, in the adult rats 0.2µg of API 31543 exerted a localized protective effect at the site of application. In both groups, rats that received chemotherapy alone became totally alopecic. Pretreatment with API 31543 protected the hair follicles against chemotherapy without having an effect on the efficacy of chemotherapy treatment of leukemia. In summary, the results herein set a solid foundation for clinical investigation of API 31543.
Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2865.</jats:p
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
DBLP-derived labeled data for author name disambiguation
No full textThis is a DBLP-derived labeled data originally created by Dr. C. Lee Giles at Penn State University and filtered for duplicate removal and error correction by Dr. Jinseok Kim at University of Michigan. For more details, see references below.1. Kim, Jinseok (2018). Evaluating author name disambiguation for digital libraries: a case of DBLP. Scientometrics. doi:10.1007/s11192-018-2824-5 2. Kim, Jinseok & Kim, Jenna (2018). The impact of imbalanced training data on machine learning for author name disambiguation. Scientometrics. doi: 10.1007/s11192-018-2865-9Each row refers to an author name instance with following feature information separated by tab.author name: full name string extracted from DBLPunique author id: labels assigned manually by Dr. C. Lee Giles's teampaper id: assigned by Dr. Jinseok Kimauthor list: names of authors in the byline of the paperyear: publication yearvenue: conference or journal namestitle: stopwords removed and stemmed by the Porter's stemmerIf you want to use this dataset, please consider to cite papers below.For the original dataset: Han, H., Giles, L., Zha, H., Li, C., & Tsioutsiouliklis, K. (2004). Two Supervised Learning Approaches for Name Disambiguation in Author Citations. JCDL 2004: Proceedings of the Fourth ACM/IEEE Joint Conference on Digital Libraries, 296-305. doi:10.1145/996350.996419For the filtered dataset: 1. Kim, Jinseok (2018). Evaluating author name disambiguation for digital libraries: a case of DBLP. Scientometrics. doi:10.1007/s11192-018-2824-5 or2. Kim, Jinseok & Kim, Jenna (2018). The impact of imbalanced training data on machine learning for author name disambiguation. Scientometrics. doi: 10.1007/s11192-018-2865-9</div
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