824 research outputs found

    The Effects of Non-Contingent Extrinsic and Intrinsic Rewards on Memory Consolidation

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    Emotional and arousing treatments given shortly after learning enhance delayed memory retrieval in animal and human studies. Positive affect and reward induced prior to a variety of cognitive tasks enhance performance, but their ability to affect memory consolidation has not been investigated before. Therefore, we investigated the effects of a small, non-contingent, intrinsic or extrinsic reward on delayed memory retrieval. Participants (n = 108) studied and recalled a list of 30 affectively neutral, imageable nouns. Experimental groups were then given either an intrinsic reward (e.g., praise) or an extrinsic reward (e.g., $1). After a one-week delay, participants’ retrieval performance for the word list was significantly better in the extrinsic reward groups, whether the reward was expected or not, than in controls. Those who received the intrinsic reward performed somewhat better than controls, but the difference was not significant. Thus, at least some forms of arousal and reward, even when semantically unrelated to the learned material, can effectively modulate memory consolidation. These types of treatments might be useful for the development of new memory intervention strategies

    The Impact of Increasing Fuel Costs on Future Outdoor Recreation Participation

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    Exact date of working paper unknown

    Community Development Perspectives of Ohio Appalachians: A Regional Study

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    Factors affecting unemployment status among residents of a lesser developed region of Ohio

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    A Test of a Vested Interests Perspective in a Reservoir Impacted Community

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    Updating and Validating the Rheumatic Disease Comorbidity Index to ICD-10-CM

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    Background/Objective: Comorbidities can contribute to increased risk for mortality and disability in individuals with rheumatoid arthritis (RA)1,2. The Rheumatic Disease Comorbidity Index (RDCI) assesses 11 comorbidities and produces a weighted score (0-9) that accurately predicts several health outcomes3. The RDCI was developed with self-report data and later validated with ICD-9-CM codes collected from administrative data3,4. On October 1, 2015, the U.S. transitioned to ICD-10-CM, resulting in a nearly five-fold increase in the number of codes available to classify conditions5. Our objective was to update the RDCI by translating it into ICD-10-CM. Methods: We defined an ICD-9-CM cohort and an ICD-10-CM cohort using patient data from the Veterans Affairs Rheumatoid Arthritis Registry (VARA). ICD-10-CM codes were generated by converting ICD-9-CM codes using tools that provide suggested crosswalks, and the codes were reviewed by a physician to assess clinical relevance. Comorbidities were collected from national VA administrative data over a two-year period in both cohorts (ICD-9-CM: October 1, 2013 to September 30, 2015; ICD-10-CM: January 1, 2016 to December 31, 2017). Comorbidity frequencies were compared using Cohen’s Kappa, and RDCI scores were compared using Intraclass Correlation Coefficients (ICC). Results: Both the ICD-9-CM cohort (n=1,082) and ICD-10-CM cohort (n=1,446) were predominantly male (ICD-9-CM: 89%; ICD-10-CM: 87%), Caucasian (ICD-9-CM: 76%; ICD-10-CM: 73%), and middle to old-aged (ICD-9-CM: 67.3 ± 10.2 years; ICD-10-CM: 68.2 ± 10.0 years). Prevalence of comorbidities were similar between coding systems, with absolute differences less than 4% (range: 0.28 to 3.91). Myocardial infarction, hypertension, diabetes mellitus, depression, stroke, other cardiovascular, lung disease, and cancer had moderate agreement or higher (range κ: 0.47 to 0.84), while fracture and ulcer/stomach problem had slight and fair agreement, respectively (κ = 0.13; κ = 0.27)6,7. The RDCI scores were 2.95 ± 1.73 (mean ± SD) for the ICD-9-CM cohort and 2.93 ± 1.75 for the ICD-10-CM cohort. RDCI scores had moderate agreement (ICC: 0.71; 95% CI: 0.68-0.74)8 among individuals who were observed during both the ICD-9-CM and ICD-10-CM eras. Conclusion: We have mapped the RDCI from ICD-9-CM to ICD-10-CM codes, generating comparable RDCI scores in a large RA registry. Individual comorbidity agreement varied, with more chronic conditions such as diabetes and hypertension having higher agreement and more acute conditions such as fractures and ulcer/stomach problems having lower agreement. The updated RDCI can be used in clinical outcomes research with ICD-10-CM era patient data.https://digitalcommons.unmc.edu/surp2021/1043/thumbnail.jp

    Grammatical Error Correction: A Survey of the State of the Art

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    Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as missing prepositions and mismatched subject-verb agreement, but also orthographic and semantic errors, such as misspellings and word choice errors respectively. The field has seen significant progress in the last decade, motivated in part by a series of five shared tasks, which drove the development of rule-based methods, statistical classifiers, statistical machine translation, and finally neural machine translation systems which represent the current dominant state of the art. In this survey paper, we condense the field into a single article and first outline some of the linguistic challenges of the task, introduce the most popular datasets that are available to researchers (for both English and other languages), and summarise the various methods and techniques that have been developed with a particular focus on artificial error generation. We next describe the many different approaches to evaluation as well as concerns surrounding metric reliability, especially in relation to subjective human judgements, before concluding with an overview of recent progress and suggestions for future work and remaining challenges. We hope that this survey will serve as comprehensive resource for researchers who are new to the field or who want to be kept apprised of recent developments
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