Morphology and lexicon of the Romany dialect of Kotel (Bulgaria).

This thesis describes the morphology and lexicon of the dialect of Romany spoken in Kotel, Bulgaria. The introduction shows the position of the dialect within Bulgarian Romany and gives brief details of its speakers (pp 12-15). A phonological transcription is used for the morphology and lexicon. This reveals the relationship between Kotel and other dialects, a relationship normally concealed by its phonetic system. The paradigmatic affixes added to nominals are listed with their variants and specimen paradigms are given (pp 16-31) . Verbs are similarly treated, with special notes on medio-passives and impersonal verbs (pp 32-42). The affixes used in building compound-words are listed with their variants and numerous examples (pp 43-59) o A brief note is included on some non-productive methods of word-formation (p. 60). The changes undergone by loan-words from Turkish and Bulgarian are summarized, together with the paradigmatic affixes used with loans from these languages and Greek (pp 61-66). Two texts are given in phonological transcription with a translation and notes, to illustrate the morphology (pp 67-94). A Romany-English lexicon follows, together with some shorter word-lists(pp 95-202) . The lexicon excludes those loan-words which are freely formed by stated rules from Turkish and Bulgarian, languages with which the people are familiar. Finally phonological rules are given which conver the symbols used up to this point into a broad phonetic transcription (pp 203-211), and a text in parallel phonological and phonetic transcription illustrates the application of these rules (pp 212-219). A concise bibliography concludes the study

Experimental Sonic Boom Measurements on a Mach 1.6 Cruise Low-Boom Configuration

A wind tunnel test has been conducted by Gulfstream Aerospace Corporation (GAC) to measure the sonic boom pressure signature of a low boom Mach 1.6 cruise business jet in the Langley Unitary Plan Wind Tunnel at Mach numbers 1.60 and 1.80. Through a cooperative agreement between GAC and the National Aeronautics and Space Administration (NASA), GAC provided NASA access to some of the experimental data and NASA is publishing these data for the sonic boom research community. On-track and off-track near field sonic boom pressure signatures were acquired at three separation distances (0.5, 1.2, and 1.7 reference body lengths) and three angles of attack (-0.26deg, 0.26deg, and 0.68deg). The model was blade mounted to minimize the sting effects on the sonic boom signatures. Although no extensive data analysis is provided, selected data are plotted to illustrate salient features of the data. All of the experimental sonic boom pressure data are tabulated. Schlieren images of the configuration are also included

Artificial intelligence in nursing: Priorities and opportunities from an international invitational think‐tank of the Nursing and Artificial Intelligence Leadership Collaborative

Funder: Fondation Brocher; Id: http://dx.doi.org/10.13039/100007461Funder: Leverhulme Centre for the Future of IntelligenceAbstract: Aim: To develop a consensus paper on the central points of an international invitational think‐tank on nursing and artificial intelligence (AI). Methods: We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3‐day invitational think tank in autumn 2019. Activities included a pre‐event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities. Implications for nursing: Nursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice. Conclusion: There are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems. Impact: We outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts

Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative

Aim To develop a consensus paper on the central points of an international invitational think-tank on nursing and artificial intelligence (AI).Methods We established the Nursing and Artificial Intelligence Leadership (NAIL) Collaborative, comprising interdisciplinary experts in AI development, biomedical ethics, AI in primary care, AI legal aspects, philosophy of AI in health, nursing practice, implementation science, leaders in health informatics practice and international health informatics groups, a representative of patients and the public, and the Chair of the ITU/WHO Focus Group on Artificial Intelligence for Health. The NAIL Collaborative convened at a 3-day invitational think tank in autumn 2019. Activities included a pre-event survey, expert presentations and working sessions to identify priority areas for action, opportunities and recommendations to address these. In this paper, we summarize the key discussion points and notes from the aforementioned activities.Implications for nursing Nursing's limited current engagement with discourses on AI and health posts a risk that the profession is not part of the conversations that have potentially significant impacts on nursing practice.Conclusion There are numerous gaps and a timely need for the nursing profession to be among the leaders and drivers of conversations around AI in health systems.Impact We outline crucial gaps where focused effort is required for nursing to take a leadership role in shaping AI use in health systems. Three priorities were identified that need to be addressed in the near future: (a) Nurses must understand the relationship between the data they collect and AI technologies they use; (b) Nurses need to be meaningfully involved in all stages of AI: from development to implementation; and (c) There is a substantial untapped and an unexplored potential for nursing to contribute to the development of AI technologies for global health and humanitarian efforts