9,057 research outputs found
The angiographic demonstration following a fracture of the femur
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The interplay between instructional policy and its constituents: How mathematics teachers interact with and understand Principles and Standards for School Mathematics
Educational policies aimed at reforming school mathematics education have been disseminated at an increasing rate in recent years. The impact of such policies hinges on if and how constituents decide to implement the policy recommendations, and these decisions depend largely on constituents\u27 interpretations of the policy. Investigating how classroom teachers make sense of policy recommendations is particularly important, for teachers are the ones who ultimately decide what mathematics students learn, and how they learn it. This research followed a group of teachers as they studied a particular instructional policy, Principles and Standards for School Mathematics (NCTM, 2000). Fourteen middle school mathematics teachers formed a study group to read and discuss the document\u27s messages and recommendations. This study aimed to characterize the nature and content of teachers\u27 discussions, to trace the ideas teachers developed about the document, and to investigate the impact this experience had on teachers\u27 beliefs, knowledge, priorities, and classroom practice.
Data sources included audio and videotapes of sixteen study group sessions, teacher journal entries, electronic listserv discussions, interviews, and classroom observations. Analyses of the study group discussions were conducted in two phases. The first phase consisted of a turn-by-turn analysis of each teacher\u27s individual contributions to the conversations. The second phase consisted of a more global analysis in which each study group transcript was chunked into distinct conversational episodes. Coding schemes were developed to capture the major themes that emerged in the study group conversations, and to characterize the cognitive demand posed by the topic under discussion and by the group\u27s treatment of that topic.
Results indicate that teachers came to view the document from multiple lenses---as a warrant for their current beliefs or practices, a lever for effecting change, a tool for their own learning, and a curriculum map. The ways in which teachers came to view the document were related to the particular demands, priorities, and characteristics of their local school contexts. Results suggest that instructional policy documents like Principles and Standards can be generative---they can stimulate rich conversations among teachers, and such conversations are fruitful sites for teachers\u27 professional learning
Lyme disease in South Africa.
This article presents an overview of Lyme disease (LD) as it applies to neuropsychiatry and summarises research results on the epidemiology of LD in South Africa
Supplier diversification under binomial yield
Cataloged from PDF version of article.We consider supplier diversification in an EOQ type inventory setting with multiple suppliers and
binomial yields. We characterize the optimal policy for the model and show that, in this case, it does
not pay to diversify, in contrast to previous results in the random yield literature.
© 2008 Elsevier B.V. All rights reserved
Biological models of mental illness: implications for therapy development
Systems approaches are needed to recognise the complexity of the biological bases of psychiatric disease
ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patching
Security critical software, e.g., OpenSSL, comes with numerous side-channel
leakages left unpatched due to a lack of resources or experts. The situation
will only worsen as the pace of code development accelerates, with developers
relying on Large Language Models (LLMs) to automatically generate code. In this
work, we explore the use of LLMs in generating patches for vulnerable code with
microarchitectural side-channel leakages. For this, we investigate the
generative abilities of powerful LLMs by carefully crafting prompts following a
zero-shot learning approach. All generated code is dynamically analyzed by
leakage detection tools, which are capable of pinpointing information leakage
at the instruction level leaked either from secret dependent accesses or
branches or vulnerable Spectre gadgets, respectively. Carefully crafted prompts
are used to generate candidate replacements for vulnerable code, which are then
analyzed for correctness and for leakage resilience. From a cost/performance
perspective, the GPT4-based configuration costs in API calls a mere few cents
per vulnerability fixed. Our results show that LLM-based patching is far more
cost-effective and thus provides a scalable solution. Finally, the framework we
propose will improve in time, especially as vulnerability detection tools and
LLMs mature
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