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We also offer a list of recommended literature and discuss outcomes and implications of this project.The purpose of this study was to explore how the new teaching approaches and requirements because of COVID-19 impacted elementary teachers' self-efficacy, specifically instructional and engagement efficacy. The current study included 329 participants from across the United States who completed the Teacher Sense of Self-Efficacy Scale (TSES) subsections of instructional and engagement. The results found the average teacher efficacy scores for both instructional and engagement were lower than TSES scores of instructional and engagement in previous studies. The results also indicated teachers who were teaching virtually had the lowest instructional efficacy scores compared to teachers teaching in a hybrid or all in-person model. However, the results suggested no difference in engagement efficacy score based on the instructional approach. There was also no difference in both instructional and engagement efficacy based on previous accolades or teacher location.This article explores the question of devolution in the light of the Covid-19 pandemic's impact on English local government. Criticism of the government's handling of the crisis is widespread and tends to focus on the highly centralised nature of the British state. Here, we attribute the challenges faced by regional and local government in responding to the pandemic primarily to the asymmetric nature of power relations that characterise financial planning and control mechanisms, devised and overseen by the Treasury. We argue that the ongoing crisis underlines the need for a democratic form of devolution-including further fiscal powers for regional and local government-to support the economic recovery. In a context of increasing fiscal uncertainty, the Treasury should seek to unlock the existing powers of local leaders by reforming centralised budgetary constraints and taking accountability and monitoring mechanisms closer to citizens.The COVID-19 pandemic has prompted renewed attention among health professionals, Aboriginal community leaders, and social scientists to the need for culturally responsive preventative health measures and strategies. This article, a collaborative effort, involving Yanyuwa families from the remote community of Borroloola and two anthropologists with whom Yanyuwa have long associations, tracks the story of pandemics from the perspective of Aboriginal people in the Gulf region of northern Australia. It specifically orients the discussion of the current predicament of 'viral vulnerability' in the wake of COVID-19, relative to other pandemics, including the Hong Kong flu in 1969 and the Spanish flu decades earlier in 1919. This discussion highlights that culturally nuanced and prescribed responses to illness and threat of illness have a long history for Yanyuwa. Yanyuwa cultural repertoires have assisted in the process of making sense of massive change, in the form of past pandemics and the onset of sickness, the threat of illness with COVID-19 and the attribution of 'viral vulnerability' to this remote Aboriginal community. The aim is to centralise Yanyuwa voices in this story, as an important step in growing understandings of Aboriginal knowledge of pandemics and culturally relevant and controlled health responses and strategies for communal well-being.Radiology is characterized by constant change and is defined by technological progress. Artificial intelligence (AI) will change all aspects of practical work in pediatric radiology in the future. BVD-523 supplier Image acquisition, diagnosis recognition and segmentation as well as the recognition of tissue properties and their combination with big data will be the main areas of application in radiology. Higher effectiveness, acceleration of investigations and making the diagnosis as well as cost savings are expectations associated with the use of AI. Improved patient management, easier work for radiology assistants and pediatric radiologists as well as faster examination and diagnosis times mark the milestones of AI development in radiology. From appointment communication and device control to treatment recommendations and monitoring, the daily life will be changed by elements of AI. Pediatric radiologists must therefore be informed about the basics of AI and work together with data scientists in establishing and using AI elements.This paper examines whether the intensity of nonpharmaceutical interventions (NPIs) during the coronavirus disease 2019 (COVID-19) pandemic has differentially impacted the public sector labor market outcomes. This extends the analysis of the already documented negative economic consequences of COVID-19 and their dissimilarities with a typical economic crisis. To capture the intensity of the NPIs, we build a novel index (COVINDEX) using daily information on NPIs merged with state-level data on out-of-home mobility (Google data). We show that among individuals living in a typical state, NPI enforcement during COVID-19 reduces the likelihood of being employed (at work) by 5% with respect to the pre-COVID period and the hours worked by 1.3% using data on labor market outcomes from the monthly Current Population Survey and difference-in-difference models. This is a sizable amount representing the sector with the higher job security during the pandemic. Public sector workers in a typical state are 4 percentage points more likely to be at work than salaried workers in the private sector and 7 percentage points more likely to be at work than self-employed workers (the worst so far). Our results are robust to the endogeneity of the NPI measures and present empirical evidence of heterogeneity in response to the NPIs, with those in local employment being the hardest hit.We document the magnitudes of and mechanisms behind socioeconomic differences in travel behavior during the COVID-19 pandemic. We focus on King County, Washington, one of the first places in North America where COVID-19 was detected. We leverage novel and rich administrative and survey data on travel volumes, modes, and preferences for different demographic groups. Large average declines in travel and public transit use due to the pandemic and related policy responses mask substantial heterogeneity across socioeconomic groups. Travel declined considerably less among less-educated and lower-income individuals, even after accounting for mode substitution and variation across neighborhoods in the impacts of public transit service reductions. As policy became less restrictive and travel increased, the size of the socioeconomic gap in travel behavior remained stable, and remote work capabilities became increasingly important in explaining this gap. Our results imply that disparities in travel behavior across socioeconomic groups may become an enduring feature of the urban landscape.