Institution
University of North Carolina at Charlotte
Education•Charlotte, North Carolina, United States•
About: University of North Carolina at Charlotte is a education organization based out in Charlotte, North Carolina, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 8772 authors who have published 22239 publications receiving 562529 citations. The organization is also known as: UNC Charlotte & UNCC.
Topics: Population, Poison control, Health care, Visualization, Mental health
Papers published on a yearly basis
Papers
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TL;DR: Both mechanical (anterior and inversion laxity) and functional (strength, dynamic balance) insufficiencies significantly contribute to the etiology of CAI.
Abstract: Background: The development of repetitive ankle sprains and persistent symptoms after initial ankle sprain has been termed chronic ankle instability (CAI). There is no clear indication of which mea...
243 citations
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TL;DR: As proposed, the relationship between meeting time demands and JAWB was moderated by task interdependence, meeting experience quality, and accomplishment striving, however, results were somewhat dependent on the time frame of a study and the operational definition used for meet time demands.
Abstract: Using an interruptions framework, this article proposes and tests a set of hypotheses concerning the relationship of meeting time demands with job attitudes and well-being (JAWB). Two Internet surveys were administered toemployees who worked 35 hr or more per week. Study 1 examined prescheduled meetings attended in a typical week (N = 676), whereas Study 2 investigated prescheduled meetings attended during the current day (N = 304). As proposed, the relationship between meeting time demands and JAWB was moderated by task interdependence, meeting experience quality, and accomplishment striving. However, results were somewhat dependent on the time frame of a study and the operational definition used for meeting time demands. Furthermore, perceived meeting effectiveness was found to have a strong, direct relationship with JAWB.
243 citations
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TL;DR: This study is the first to demonstrate that mindfulness-related pain relief is mechanistically distinct from placebo analgesia, and confirms the existence of multiple, cognitively driven, supraspinal mechanisms for pain modulation.
Abstract: Mindfulness meditation reduces pain in experimental and clinical settings. However, it remains unknown whether mindfulness meditation engages pain-relieving mechanisms other than those associated with the placebo effect (e.g., conditioning, psychosocial context, beliefs). To determine whether the analgesic mechanisms of mindfulness meditation are different from placebo, we randomly assigned 75 healthy, human volunteers to 4 d of the following: (1) mindfulness meditation, (2) placebo conditioning, (3) sham mindfulness meditation, or (4) book-listening control intervention. We assessed intervention efficacy using psychophysical evaluation of experimental pain and functional neuroimaging. Importantly, all cognitive manipulations (i.e., mindfulness meditation, placebo conditioning, sham mindfulness meditation) significantly attenuated pain intensity and unpleasantness ratings when compared to rest and the control condition ( p p = 0.032) and pain unpleasantness ( p p = 0.030) and pain unpleasantness ( p = 0.043) ratings more than sham mindfulness meditation. Mindfulness-meditation-related pain relief was associated with greater activation in brain regions associated with the cognitive modulation of pain, including the orbitofrontal, subgenual anterior cingulate, and anterior insular cortex. In contrast, placebo analgesia was associated with activation of the dorsolateral prefrontal cortex and deactivation of sensory processing regions (secondary somatosensory cortex). Sham mindfulness meditation-induced analgesia was not correlated with significant neural activity, but rather by greater reductions in respiration rate. This study is the first to demonstrate that mindfulness-related pain relief is mechanistically distinct from placebo analgesia. The elucidation of this distinction confirms the existence of multiple, cognitively driven, supraspinal mechanisms for pain modulation. SIGNIFICANCE STATEMENT Recent findings have demonstrated that mindfulness meditation significantly reduces pain. Given that the “gold standard” for evaluating the efficacy of behavioral interventions is based on appropriate placebo comparisons, it is imperative that we establish whether there is an effect supporting meditation-related pain relief above and beyond the effects of placebo. Here, we provide novel evidence demonstrating that mindfulness meditation produces greater pain relief and employs distinct neural mechanisms than placebo cream and sham mindfulness meditation. Specifically, mindfulness meditation-induced pain relief activated higher-order brain regions, including the orbitofrontal and cingulate cortices. In contrast, placebo analgesia was associated with decreased pain-related brain activation. These findings demonstrate that mindfulness meditation reduces pain through unique mechanisms and may foster greater acceptance of meditation as an adjunct pain therapy.
242 citations
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TL;DR: In this article, the authors apply theory and research on processes that lead to posttraumatic growth to survivors of violence and find that survivors often report positive changes in identity, philosophy, and goals.
242 citations
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TL;DR: A practical methodology to generate probabilistic load forecasts by performing quantile regression averaging on a set of sister point forecasts and it leads to dominantly better performance as measured by the pinball loss function and the Winkler score.
Abstract: The majority of the load forecasting literature has been on point forecasting, which provides the expected value for each step throughout the forecast horizon. In the smart grid era, the electricity demand is more active and less predictable than ever before. As a result, probabilistic load forecasting, which provides additional information on the variability and uncertainty of future load values, is becoming of great importance to power systems planning and operations. This paper proposes a practical methodology to generate probabilistic load forecasts by performing quantile regression averaging on a set of sister point forecasts. There are two major benefits of the proposed approach. It can leverage the development in the point load forecasting literature over the past several decades and it does not rely so much on high-quality expert forecasts, which are rarely achievable in load forecasting practice. To demonstrate the effectiveness of the proposed approach and make the results reproducible to the load forecasting community, we construct a case study using the publicly available data from the Global Energy Forecasting Competition 2014. Compared with several benchmark methods, the proposed approach leads to dominantly better performance as measured by the pinball loss function and the Winkler score.
242 citations
Authors
Showing all 8936 results
Name | H-index | Papers | Citations |
---|---|---|---|
Chao Zhang | 127 | 3119 | 84711 |
E. Magnus Ohman | 124 | 622 | 68976 |
Staffan Kjelleberg | 114 | 425 | 44414 |
Kenneth L. Davis | 113 | 622 | 61120 |
David Wilson | 102 | 757 | 49388 |
Michael Bauer | 100 | 1052 | 56841 |
David A. B. Miller | 96 | 702 | 38717 |
Ashutosh Chilkoti | 95 | 414 | 32241 |
Chi-Wang Shu | 93 | 529 | 56205 |
Gang Li | 93 | 486 | 68181 |
Tiefu Zhao | 90 | 593 | 36856 |
Juan Carlos García-Pagán | 90 | 348 | 25573 |
Denise C. Park | 88 | 267 | 33158 |
Santosh Kumar | 80 | 1196 | 29391 |
Chen Chen | 76 | 853 | 24974 |