Institution
University of North Texas
Education•Denton, Texas, United States•
About: University of North Texas is a education organization based out in Denton, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 11866 authors who have published 26984 publications receiving 705376 citations. The organization is also known as: Fight, North Texas & UNT.
Papers published on a yearly basis
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Mohammad H. Forouzanfar1, Lily Alexander1, H. Ross Anderson2, Victoria F Bachman1 +718 more•Institutions (295)
TL;DR: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) as mentioned in this paper provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution.
1,656 citations
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Stony Brook University1, University of Minnesota2, University of Notre Dame3, University of Vermont4, University of Toronto5, Boston University6, University of Maryland, Baltimore7, Duke University8, University of Kansas9, King's College London10, Columbia University11, Broad Institute12, Purdue University13, University of Iowa14, University of Georgia15, Texas A&M University16, Oklahoma State University–Stillwater17, University of Groningen18, Florida State University19, Uniformed Services University of the Health Sciences20, Bryn Mawr College21, University of North Texas22, University of Otago23, University at Buffalo24, University of Arizona25, University of New South Wales26, Northwestern University27, Emory University28, University of Kentucky29, University of Pittsburgh30, Brown University31
TL;DR: The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies and provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response.
Abstract: The reliability and validity of traditional taxonomies are limited by arbitrary boundaries between psychopathology and normality, often unclear boundaries between disorders, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. These taxonomies went beyond evidence available on the structure of psychopathology and were shaped by a variety of other considerations, which may explain the aforementioned shortcomings. The Hierarchical Taxonomy Of Psychopathology (HiTOP) model has emerged as a research effort to address these problems. It constructs psychopathological syndromes and their components/subtypes based on the observed covariation of symptoms, grouping related symptoms together and thus reducing heterogeneity. It also combines co-occurring syndromes into spectra, thereby mapping out comorbidity. Moreover, it characterizes these phenomena dimensionally, which addresses boundary problems and diagnostic instability. Here, we review the development of the HiTOP and the relevant evidence. The new classification already covers most forms of psychopathology. Dimensional measures have been developed to assess many of the identified components, syndromes, and spectra. Several domains of this model are ready for clinical and research applications. The HiTOP promises to improve research and clinical practice by addressing the aforementioned shortcomings of traditional nosologies. It also provides an effective way to summarize and convey information on risk factors, etiology, pathophysiology, phenomenology, illness course, and treatment response. This can greatly improve the utility of the diagnosis of mental disorders. The new classification remains a work in progress. However, it is developing rapidly and is poised to advance mental health research and care significantly as the relevant science matures. (PsycINFO Database Record
1,635 citations
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TL;DR: A current snapshot of high-throughput computational materials design is provided, and the challenges and opportunities that lie ahead are highlighted.
Abstract: High-throughput computational materials design is an emerging area of materials science. By combining advanced thermodynamic and electronic-structure methods with intelligent data mining and database construction, and exploiting the power of current supercomputer architectures, scientists generate, manage and analyse enormous data repositories for the discovery of novel materials. In this Review we provide a current snapshot of this rapidly evolving field, and highlight the challenges and opportunities that lie ahead.
1,568 citations
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TL;DR: A simulation devoted to covering the steps involved in typical firefighter training known as REVAS, one of many examples covered by Karl Kapp (2012) in his new book, The gamification of learning and instruction: game-based methods and strategies for training and education.
Abstract: DriveGamification in Learning and EducationGamify Your ClassroomGamification of LearningThe Impact of the 4th Industrial Revolution on Engineering EducationThe Gamification of Learning in Virtual WorldsGamification in English Teaching and LearningGamification with MoodleGame Design for LearningActionable GamificationThe Gamification of Learning and Instruction FieldbookGame-Based Learning and the Power of PlayGamification MindsetGamification in Higher EducationGamification in Education: Breakthroughs in Research and PracticeThe Gamification of Learning and InstructionLernen mit Big DataAugmented Reality Games IIDas Design Thinking PlaybookGamify your LifePlay to LearnGamification of Learning and Teaching in SchoolsGamification in Education and BusinessData Analytics Approaches in Educational Games and Gamification SystemsDie Kunst des Game DesignsDie Wirkung von Gamification auf Motivation und LeistungLehrerdämmerungGamificationGamestor mingGamification for Interactive LearningHandbook of Research on Solving Modern Healthcare Challenges With GamificationBesser als die Wirklichkeit!MicrolearningTelekommunikation und FremdsprachenunterrichtTransforming Learning and
1,559 citations
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TL;DR: In this paper, the interaction process and performance of culturally homogeneous and culturally diverse groups were studied for 17 weeks, and the results showed that homogeneous groups scored higher on both process effectiveness and performance effectiveness.
Abstract: The interaction process and performance of culturally homogeneous and culturally diverse groups were studied for 17 weeks. Initially, homogeneous groups scored higher on both process and performance effectiveness. Over time, both types of group showed improvement on process and performance, and the between-group differences converged. By week 17, there were no differences in process or overall performance, but the heterogeneous groups scored higher on two task measures, Implications for management and future research are given.
1,447 citations
Authors
Showing all 12053 results
Name | H-index | Papers | Citations |
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Steven N. Blair | 165 | 879 | 132929 |
Scott D. Solomon | 137 | 1145 | 103041 |
Richard A. Dixon | 126 | 603 | 71424 |
Thomas E. Mallouk | 122 | 549 | 52593 |
Hong-Cai Zhou | 114 | 489 | 66320 |
Qian Wang | 108 | 2148 | 65557 |
Boris I. Yakobson | 107 | 443 | 45174 |
J. N. Reddy | 106 | 926 | 66940 |
David Spiegel | 106 | 733 | 46276 |
Charles A. Nelson | 103 | 557 | 40352 |
Robert J. Vallerand | 98 | 301 | 41840 |
Gerald R. Ferris | 93 | 332 | 29478 |
Michael H. Abraham | 89 | 726 | 37868 |
Jere H. Mitchell | 88 | 337 | 24386 |
Alan Needleman | 86 | 373 | 39180 |