955 resultados para Manuscripts, Dutch.


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A 21 page typescript accompanied by copies of vital records and a family tree.

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Family trees listing; newspaper clippings on Nazi period in Wertheim; inscriptions from Jewish cemetery in Schmieheim.

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Family tree of the Michael Mayer family. Contains memoir on Biebesheim. Also included are copies of photographs and vital records.

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Inventory lists of captured German documents; 1933-1945.

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Sotheby’s press release on occasion of an auction in New York, 1988 with a short biographical abstract of Albert Blum.

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Self-published book on the history of the Asch family.

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Manuscripts: "Schicksal der Leiwener Juden von der Zeit des Nationalsozialismus bis heute;" Geschichte der ehemaligen Judengemeinde in Leiwen." Contains references to the history of different Jewish families from Leiwen.

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Three volumes of genealogy and family trees of the Eberstadt family.

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Account of the Jewish community in Linnich, its history and its institutions.

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List of names, members of the Jewish community Papenburg (Aschendorf) from the earliest time to 1942; manuscript: "Geschichte der Juedischen Gemeinde Papenburg und Ihrer Familien".

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Typescript (photocopy) of a speach delivered by Prof. Friendly at the New York Marriott Marquis Hotel, June 10, 1988.

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In this Thesis, we develop theory and methods for computational data analysis. The problems in data analysis are approached from three perspectives: statistical learning theory, the Bayesian framework, and the information-theoretic minimum description length (MDL) principle. Contributions in statistical learning theory address the possibility of generalization to unseen cases, and regression analysis with partially observed data with an application to mobile device positioning. In the second part of the Thesis, we discuss so called Bayesian network classifiers, and show that they are closely related to logistic regression models. In the final part, we apply the MDL principle to tracing the history of old manuscripts, and to noise reduction in digital signals.

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It is recognised that patients with chronic disease are unable to remembercorrectly information provided by health care profesionals. The teach-back method is acknowledgedas a technique to improve patients’ understanding. Yet it is not used in nursing practice in Vietnam. Objectives This study sought to examine knowledge background of heart failure among cardiac nurses, introduce a education about heart failure self-management and the teach-back method to assist teaching patients on self-care. The study also wanted to explore if a short education could benefit nurses’ knowledge so they would be qualified to deliver education to patients. Methods A pre/post-test design was employed. Cardiac nurses from 3 hospitals (Vietnam National Heart Institute, E Hospital, Huu Nghi Hospital) were invited to attend a six-hour educational session which covered both the teach-back method and heart failure self-management. Role-play with scenarios were used to reinforce educational contents. The Dutch Heart Failure Knowledge Scale was used to assess nurses’ knowledge of heart failure at baseline and after the educational session. Results 20 nurses from3 selected hospitals participated. Average age was 34.5±7.9 years and years of nursing experience was 11.6±8.3. Heart failure knowledge score at the baseline was 12.7±1.2 and post education was 13.8±1.0. There was deficiency of nurses knowledge regarding fluid restriction among heart failure people, causes of worsening heart failure. Heart failure knowledge improved significantly following the workshop (p < 0.001). All nurses achieved an overall adequate knowledge score (≥11 of the maximum 15) at the end. 100% of nurses agreed that the teach-back method was effective and could be used to educate patients about heart failure self-management. Conclusions The results of this study have shown the effectiveness of the piloteducaiton in increasing nurses’ knowledge of heart failure. The teach-back method is accepted for Vietnamese nurses to use in routine cardiac practice.

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Digital image

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