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关键词： TPACK   Scale development   Pre-service teacher   Science education   Programming   PEDAGOGICAL CONTENT KNOWLEDGE   EXPLORATORY FACTOR-ANALYSIS   COMPUTATIONAL THINKING   PRESERVICE TEACHERS   SAMPLE-SIZE   ASSESSMENT INSTRUMENT   TPACK   VALIDATION   CONSTRUCT  

摘要： Programming and computational thinking have been introduced into the curricula of several countries, also in relation to science and technology education. Preparing pre-service teachers for using programming in science education is therefore an important and relevant task. The purpose of this article is to describe what knowledge may be relevant for teachers who are to use programming in science and technology education and to propose a questionnaire to aid in assessing this knowledge. The proposed questionnaire can be used for tracking development over time and for identifying areas where teachers need more knowledge.

关键词： Noise measurement   Sparse matrices   Linear matrix inequalities   Computer science   Complexity theory   Upper bound   Pollution measurement   Leverage score   low rank   matrix completion   noise   LOW-RANK MATRIX   INCOHERENCE   ALGORITHM  

摘要： Completing low-rank matrices from subsampled measurements has received much attention in the past decade. Existing works indicate that O(nr log(2)(n)) datums are required to theoretically secure the completion of an n x n noisy matrix of rank r with high probability, under some quite restrictive assumptions: 1) the underlying matrix must be incoherent and 2) observations follow the uniform distribution. The restrictive-ness is partially due to ignoring the roles of the leverage score and the oracle information of each element. In this article, we employ the leverage scores to characterize the importance of each element and significantly relax assumptions to: 1) not any other structure assumptions are imposed on the underlying low-rank matrix and 2) elements being observed are appropriately dependent on their importance via the leverage score. Under these assumptions, instead of uniform sampling, we devise an ununiform/biased sampling procedure that can reveal the "importance" of each observed element. Our proofs are supported by a novel approach that phrases sufficient optimality conditions based on the Golfing scheme, which would be of independent interest to the wider areas. Theoretical findings show that we can provably recover an unknown n x n matrix of rank r from just about O(nr log(2)(n)) entries, even when the observed entries are cor-rupted with a small amount of noisy information. The empirical results align precisely with our theories.

关键词： business process innovation   human capital   machine learning   noncompete agreements   worker mobility   INFORMATION-TECHNOLOGY   ARTIFICIAL-INTELLIGENCE   COMPETITIVE ADVANTAGE   BIG DATA   LABOR   PRODUCTIVITY   INDUSTRY   GROWTH   ENTRY   ENFORCEABILITY  

摘要： Research SummaryWe investigate how worker mobility influences the adoption of a new technology using state-level changes to the enforceability of noncompete agreements as an exogenous shock to worker mobility. Using data on over 153,000 establishments from 2010 and 2018, we find that changes that facilitate worker movements are associated with a significant decline in the likelihood of adoption of machine learning. Moreover, we find that the magnitude of decline depends upon the size of the establishment, the extent of predictive analytics adoption in its industry, and the number of large establishments in the same industry-location. These results are consistent with the view that increases in outward worker mobility increase costs for adoption of a new technology that involves significant downstream investments in the early years of its *** SummarySuccessful business adoption of new technologies such as machine learning requires skilled workers with experience in implementing those technologies. In the early years of technology diffusion workers in early adopting businesses typically acquire these skills through on-the-job learning that is paid for by the adopter. So, if such early adopters face an increased risk of those skilled workers quitting, then their incentives to adopt the technology decrease. We examine this possibility using changes in noncompete enforceability as a proxy for changes in worker mobility and find that the likelihood of adopting machine learning decreases as the risk of worker mobility increases, particularly for larger establishments, establishments in industries where adoption may be more beneficial and in locations with many large competing establishments.

关键词： Drug resistance   Infectious diseases   Indigenous health   Rural health services  

摘要： Background: Rates of antimicrobial resistance (AMR) for some pathogens in Australia are considerably higher in rural and remote compared to urban regions. The inaugural Hot North Antimicrobial Academy was a 9-month educational programme aimed to build workforce knowledge and capacity in antimicrobial use, audit, stewardship, surveillance and drug resistance in remote primary health care. Methods: The Academy was advertised to Aboriginal and Torres Strait Islander, regional and remote healthcare workers. Participants were Aboriginal health practitioners, nurses, pharmacists and doctors from Queensland, Northern Territory, South Australia and Western Australia working in remote primary health care with a focus on Indigenous health. Due to COVID-19 restrictions, the Academy ran virtually from February-November 2021 using Microsoft Teams. The Academy was evaluated using surveys and yarning circles to assess impact and knowledge gain. Results: Participants and faculty from across Australia attended 19 lectures and mentorship sessions. Eleven participants commenced and eight (73%) completed the Academy. The Academy raised participants awareness of AMR guidelines, governance and generating change; built confidence in advocacy; grew knowledge about drug resistant infections; and created a community of AMR champions in Indigenous health. Conclusion: The evaluation confirmed the Academy met the needs of participants, provided opportunities to move stewardship from tertiary hospitals into Indigenous and remote clinics and developed skills in research, audit, stewardship and advocacy for all involved. All sessions were recorded for future use, with facilitation by the National Aboriginal Community Controlled Health Organisation (NACCHO) in future years. 2024 The Author(s). Published by Elsevier B.V. on behalf of Australasian College for Infection Prevention and Control. This is an open access article under the CC BY-NC-ND license (http:// creativeco

关键词： Inclusivity   Popular culture   Educational settings   Body positivity   Fat phobia   WEIGHT STIGMA  

摘要： Purpose-This paper aims to address weight-based bullying as a persistent issue among adolescents. Fat phobia, rooted in societal biases against overweight individuals, leads to social exclusion and discrimination, negatively impacting mental health and equality. Educational settings suffer from the profound effects of fat phobia, creating a toxic atmosphere that distracts from learning and marginalizes students who don't conform to traditional physical norms. Design/methodology/approach-This paper combines historical analysis, literature review and critical discourse analysis. It examines the historical roots of fat phobia, explores the impact of societal influences, analyzes contemporary educational practices and the use of popular culture as a innovative tool. Findings-Leveraging popular culture in anti-fat phobia education effectively challenges stereotypes. Educators empower students to critically analyze media depictions, encouraging empathy and inclusivity. Current events serve as critical teaching tools, sparking discussions on intersecting discrimination forms and equity. Practical implications-This paper emphasizes the urgent need to comprehensively address fat phobia in education, advocating for a shift in societal attitudes toward body diversity. Popular culture can serve as an educational tool to create inclusive classrooms where all students are valued and free from weight-based discrimination. Social implications-This paper emphasizes the urgent need to comprehensively address fat phobia in education, advocating for a shift in societal attitudes toward body diversity. Popular culture can serve as an educational tool to create inclusive classrooms where all students are valued and free from weight-based discrimination. Originality/value-The originality and value of this paper lie in its multi-faceted approach to examining weight-based discrimination, its historical context, practical educational strategies, and the innovative use of popular culture as a

摘要： Starting from Picasso's quote ("Computers are useless. They can only give you answers"), we discuss the introduction of generative artificial intelligence (AI), including generative adversarial networks (GANs) and transformer-based architectures such as large language models (LLMs) in radiology, where their potential in reporting, image synthesis, and analysis is notable. However, the need for improvements, evaluations, and regulations prior to clinical use is also clear. Integration of LLMs into clinical workflow needs cautiousness, to avoid or at least mitigate risks associated with false diagnostic suggestions. We highlight challenges in synthetic image generation, inherent biases in AI models, and privacy concerns, stressing the importance of diverse training datasets and robust data privacy measures. We examine the regulatory landscape, including the 2023 Executive Order on AI in the United States and the 2024 AI Act in the European Union, which set standards for AI applications in healthcare. This manuscript contributes to the field by emphasizing the necessity of maintaining the human element in medical procedures while leveraging generative AI, advocating for a "machines-in-the-loop" approach.

摘要： Preface: The 1st Pancasakti International Conferences Engineering and Computer Science 2022, AIP Conference Proceedings, Volume 2952, Issue 1, 23 July 2024, 010