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1.
Creating and disseminating knowledge through research and teaching has long been regarded as the hallmark of the modern university. However, new university business models have called into question the ‘bundling’ of teaching and research, and sustained research on the relationship between teaching and research has found little evidence of an insoluble connection between the two activities. In this article, we explore the relationship between teaching and research from the perspective of universities’ institutional discourse. We use corpus-assisted discourse analysis to examine the relationship between research and teaching as presented in two sets of institutional texts currently influential in UK Higher Education: Research Excellence Framework environment statements and Teaching Excellence Framework provider submissions (a total of 2143 documents and 12,492,071 words). Our findings show that, while universities emphasise the value of research to their teaching, they do not always emphasise (or sometimes even decry) the influence of teaching on their research. We empirically evidence that, according to what universities themselves write in institutional texts, teaching and research are not always in a mutually beneficial entanglement, but often rather a one-way relationship in which research expertise and institutional prestige are used to bolster claims of teaching excellence. This has implications for the communication of both the vision and the purpose of a university in regulatory exercises and wider policy, but also speaks to the broader idea and practice of being a university in the twenty-first century.  相似文献   
2.
体医融合和非医疗健康干预可以有效促进疾病管理与健康服务模式的形成,但体医融合项目治理初期仍然受到理念融合、体医融资、部门协同等因素的影响。该文以病毒、人体免疫与体育运动的体医融合关系视角,依据共生理论对体医融合项目的风险治理逻辑进行了阐述。采用文献资料法、数理统计法等对体医融合项目风险治理的相关个案进行了整理,并基于NVIVO11.0质性分析软件对体医融合个案进行识别分析,构建了体医融合项目风险治理的影响因素评价指标体系,包括13个一级指标30个二级指标。最后提出了体医融合项目风险治理的路径选择(1)将体医融合理念提升至构建公共卫生保障体系战略的高度;(2)落地变现体医融合项目购买方案;(3)打造政府精准购买体医融合项目区块链。  相似文献   
3.
ABSTRACT

The aims of this study were to identify profiles of sedentary behaviour (SB) patterns, based on leisure-time self-reported SB modalities (screen, educative, social, and relaxing) and to evaluate changes in these profiles over 2 years among Spanish youth aged 8–18 years. Latent profile analysis (LPA), a data-driven analytic approach, was used to identify groups of boys and girls (n = 1553; 48% girls; mean±SD age: 12.56 ± 2.49 y) with distinct SB profiles using the SB modalities (time/d) as input variables. Latent transition analysis, an extension of LPA that uses longitudinal data, was used to analyse 2-year changes in these profiles. At baseline, four and three SB profiles were found among boys (labelled: screen, educative, social, and relaxing) and girls (labelled: screen/social, educative, and relaxing), respectively. Overall, more girls (range: 48%-67%) had the same profile over time, than boys (40%-52%). Participants with a screen or relaxing SB profile at baseline were more likely to have an educative profile after 2 years. Youth with a social and an educative SB profile at baseline were more likely to transition to profiles characterized by higher screen and social SB, respectively. Using a novel and person-centered approach, this study identified gender-specific SB profiles that were moderately stable over time.  相似文献   
4.
Genetic variation in the angiotensin II type 1 receptor (AT1R) has an important effect on the outcome of acute coronary syndrome (ACS) initiated treatment with captopril. This study aims to investigate the impact of genetic polymorphism of AT1R (rs5186 and rs275651) on the ACS outcome in Iraqi patients treated with captopril. A total of 250 Iraqi individuals with ACS were included in this case—control study and they were divided into two study groups; Study group 1 included 125 participants who were prescribed captopril, 25 mg twice daily and study group 2 included 125 participants who received no captopril as part of their ACS treatment (control study). The AT1R gene (rs5186) CC genotype was found to be associated with ST-elevation myocardial infarction (STEMI) (Odd’s ratio (O.R) = 1.2, P = 0.7), while AC was associated with Non-ST-elevation myocardial infarction (NSTEMI) and unstable angina (UA) (O.R = 1.2, P = 0.8). AC genotype is more prone to have Percutaneous coronary intervention (PCI) after ACS attack (O.R = 1.2, P = 0.6). CC genotype had a risk to get less improvement (O.R = 1.6, P = 0.5), so might require higher doses of captopril during acute coronary insult. The AT1R gene (rs275651) AA genotype was associated with UA (O.R = 1.3, P = 0.9). AA and AT genotypes were more prone to have PCI after ACS attack (O.R = 3.9 P = 0.2, O.R = 3.5, P = 0.3 respectively) and thus requiring higher doses of captopril. We conclude that the AT1R rs5186, rs275651 genetic polymorphisms might partially affect the clinical outcome of ACS patients treated with captopril and might have captopril resistance which requires higher doses.  相似文献   
5.
[目的/意义] 通过构建二模复杂网络模型,揭示隐藏在海量文献中的隐性知识。[方法/过程] 通过NetworkX复杂网络工具包,依据任意两个节点的共现关系构建二模复杂网络模型;对网络模型中节点的共现关系进行加权,计算网络的拓扑信息并进行AP聚类,提取节点间的直接关系;采用AUC方法对AA、JC、加权改进的wAA和wJC等4种链路预测算法进行评价,遴选出最合适的预测算法,并对复杂网络的隐性关系进行预测分析。[结果/结论] 以潜在药物靶点挖掘为例进行的实证研究结果表明,wAA链路预测算法为最优的链路预测算法;二模复杂网络模型、指标和方法体系在美国化学文摘社数据库中的药物靶点挖掘中具有一定的有效性。下一步计划在其他数据库中或其他研究领域中进行尝试,以进一步验证该模型的通用性和有效性。  相似文献   
6.
王思茗  滕广青 《图书情报知识》2020,(3):109-118,F0003
[目的/意义]领域知识的跨学科交叉研究能够打破学科间的壁垒,有助于发现重大科学问题的解决方案。[研究设计/方法]基于图书情报学领域文献题录信息构建轻量级领域知识图谱,从中提取学科信息、国家信息、时间信息及其关联,采用时间与空间相结合的多维度分析方法,对学科交叉的演化进程以及国家差异进行跟踪与分析。[结论/发现]图书情报学领域内学科交叉现象日渐显著,各国家的学科交叉程度与倾向存在差异,一些目前尚不突出的交叉学科方向值得关注。[创新/价值]采用多维度视角分析学科交叉现象,相关结论可以为国家科技战略制定及学科发展规划提供有益参考。  相似文献   
7.
ABSTRACT

Olfaction has been described as one of the least studied of the senses. This has certainly proven true in Communication. This project applies Ethnography of Communication and Cultural Discourse Analysis to examine the role that olfaction plays in the cultural meaning systems of two speech communities: residents surrounding the Gowanus Canal and bereaved parents. The cultural hub used to explore the cultural significance of olfaction in both speech communities is feeling. The analyses illustrate how emotions are tied to associated sensations and further become activated through radiants of dwelling, relating and acting. The analysis also shows how olfaction may serve to unify and separate members of a community. The significance of this research encourages stretching the boundaries of communication studies by examining the less studied physical senses and the boundaries of Cultural Discourse Analysis by providing distinctions that others can incorporate when examining feelings.  相似文献   
8.
Child maltreatment is a complex and multifaceted construct in need of advanced statistical techniques to improve its measurement. The current study compared the predictive utility of a cumulative index to a factor analytic approach for constructing a measure of maltreatment. Data were from Waves III and IV of the National Longitudinal Study of Adolescent to Adult Health (Wave III: n = 14,800; Wave IV: n = 12,288). As adults, participants retrospectively reported on their childhood experiences of physical abuse, sexual abuse, emotional abuse, physical neglect, supervisory neglect, and social services investigations. Both the cumulative index and a two-factor solution showed evidence of convergent validity, predicting lifetime incidence of homelessness, being paid for sex, and various measures of running away or living apart from biological parents, and prospectively predicting depression, substance use, and criminal behavior. The latent variables, derived from a factor analytic approach, had greater explanatory power for many outcomes compared to the cumulative index, even when controlling for sociodemographic variables. Results suggest that factor analysis is a better methodology than a cumulative index for measuring maltreatment in large datasets when explanatory power for external outcomes is of greatest concern.  相似文献   
9.
In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.  相似文献   
10.
Cross-Company Churn Prediction (CCCP) is a domain of research where one company (target) is lacking enough data and can use data from another company (source) to predict customer churn successfully. To support CCCP, the cross-company data is usually transformed to a set of similar normal distribution of target company data prior to building a CCCP model. However, it is still unclear which data transformation method is most effective in CCCP. Also, the impact of data transformation methods on CCCP model performance using different classifiers have not been comprehensively explored in the telecommunication sector. In this study, we devised a model for CCCP using data transformation methods (i.e., log, z-score, rank and box-cox) and presented not only an extensive comparison to validate the impact of these transformation methods in CCCP, but also evaluated the performance of underlying baseline classifiers (i.e., Naive Bayes (NB), K-Nearest Neighbour (KNN), Gradient Boosted Tree (GBT), Single Rule Induction (SRI) and Deep learner Neural net (DP)) for customer churn prediction in telecommunication sector using the above mentioned data transformation methods. We performed experiments on publicly available datasets related to the telecommunication sector. The results demonstrated that most of the data transformation methods (e.g., log, rank, and box-cox) improve the performance of CCCP significantly. However, the Z-Score data transformation method could not achieve better results as compared to the rest of the data transformation methods in this study. Moreover, it is also investigated that the CCCP model based on NB outperform on transformed data and DP, KNN and GBT performed on the average, while SRI classifier did not show significant results in term of the commonly used evaluation measures (i.e., probability of detection, probability of false alarm, area under the curve and g-mean).  相似文献   
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