Suchergebnisse

While there has been a surge of studies on English as a foreign language (EFL) teachers' emotions and identities in research engagement, limited attention has been paid to how they integrate teacher and researcher identities and negotiate different emotions in research practice over time. Drawing on data from a variety of sources over a decade, this longitudinal self-narrative study investigated how an EFL academic (the author) negotiated and navigated conflicting identities and emotions in the process of becoming a teacher-researcher in a changing context. The findings unfolded the changes in her emotions and professional identity development over the course of her 10-year research journey, beginning as a discontented and perplexed performer with weak emotional resilience, progressing to a pressured and strenuous follower with moderate emotional resilience, and finally becoming a relentless and resolute integrator with strong emotional resilience. Her final integration of teacher and researcher identities represented her redemption on this bumpy journey. Implications for EFL teachers, school leaders, and education policymakers on how to help EFL academics integrate professional identities were also discussed.

Lu-Hua Gao, Qing-He Nie, Xi-Tai Zhao Center of Infectious Diseases, Second Affiliated Hospital, Air-Force Military Medical University, Xi'an 710038, People's Republic of ChinaCorrespondence: Qing-He NieCenter of Infectious Diseases, Second Affiliated Hospital, Air-Force Military Medical University, 569 Xinsi Road, Baqiao District, Xi'an 710038, People's Republic of ChinaEmail nhqxan2020@163.comAbstract: Hepatitis C is a major health problem worldwide, frequently resulting in cirrhosis and increasing the risk of hepatocellular carcinoma significantly. In recent years, the advent of direct-acting antivirals (DAAs) has dramatically improved the therapeutic outcomes in hepatitis C patients. In the last two years, several new DAA combinations have been approved for the treatment of the hepatitis C virus (HCV) infection, including elbasvir/grazoprevir, sofosbuvir/velpatasvir, sofosbuvir/velpatasvir/voxilaprevir, and glecaprevir/pibrentasvir. The newly approved DAA regimens may be prescribed with other drugs simultaneously, increasing the potential of pharmacokinetic interactions. Therefore, the knowledge and management of drug–drug interactions (DDIs) with DAAs should be considered a key issue in HCV therapy. This review summarizes researches of DDIs focusing on newly approved DAAs (elbasvir, grazoprevir, velpatasvir, voxilaprevir, glecaprevir, pibrentasvir) for patients undergoing HCV treatment to provide clinical consideration for comedication. With respect to DDIs, newly approved DAA regimens, including elbasvir/grazoprevir, sofosbuvir/velpatasvir, sofosbuvir/velpatasvir/voxilaprevir, and glecaprevir/pibrentasvir, are safely applicable.Keywords: drug–drug interaction, direct-acting antiviral, chronic hepatitis C, pharmacokinetic, comedication

The aim of this paper is to propose an attribute recognition model, so that it can be used to simultaneously estimate the public transit network system. Based on the analysis of a variety of factors influencing the public transit network, quantitative research has been conducted with reference to the attribute recognition theory in order to make scientific decision‐making. On the basis of defining attribute measure, this paper presents the attribute recognition model suggesting the attribute recognition theory that can be used to evaluate the public transit network. The reliability of the new method can be explained using real data of the survey on the public transit network in China. The applied results offer scientific reference for instructing and controlling urban traffic by the Government. The main advantages of the new model are in contexts where internal linkage and shared inputs between activities can be considered. The structure of this mode is more realistic than that of the conventional one. First published online: 10 Feb 2011

The aim of this paper is to propose an attribute recognition model, so that it can be used to simultaneously estimate the public transit network system. Based on the analysis of a variety of factors influencing the public transit network, quantitative research has been conducted with reference to the attribute recognition theory in order to make scientific decision‐making. On the basis of defining attribute measure, this paper presents the attribute recognition model suggesting the attribute recognition theory that can be used to evaluate the public transit network. The reliability of the new method can be explained using real data of the survey on the public transit network in China. The applied results offer scientific reference for instructing and controlling urban traffic by the Government. The main advantages of the new model are in contexts where internal linkage and shared inputs between activities can be considered. The structure of this mode is more realistic than that of the conventional one. First published online: 10 Feb 2011

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors, namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in the wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors, namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in the wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.

COVID-19 has disrupted normal life and has enforced a substantial change in the policies, priorities and activities of individuals, organisations and governments. These changes are proving to be a catalyst for technology and innovation. In this paper, we discuss the pandemic's potential impact on the adoption of the Internet of Things (IoT) in various broad sectors, namely healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT. Our perspective and forecast of this impact on IoT adoption is based on a thorough research literature review, a careful examination of reports from leading consulting firms and interactions with several industry experts. For each of these sectors, we also provide the details of notable IoT initiatives taken in the wake of COVID-19. We also highlight the challenges that need to be addressed and important research directions that will facilitate accelerated IoT adoption.