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The division of Research Information Science and Computing RISC is the cornerstone of the scientific utilization of Information Technology at Partners HealthCare. This training video was developed by a subcommittee of the NIH Animal Research Advisory Committee to assist in the development of proper surgical skills when performing survival surgery on rodents. It illustrates the most common practices used in the NIH intramural research program and survival rodent surgery standards established by the NIH Guidelines for Survival Rodent Surgery. The screenshot below will then be displayed. Select General Training in Survival Rodent Surgery and view the video. After completing the video, return to Aseptic Technique course to complete the quiz. If you are experiencing problems accessing or using Blackboard, be sure to check the MyHudsonValley Portal Blackboard FAQ page. Additionally, the Support and Tutorials tab in Blackboard provides tutorials on many common tasks. NOTE: Students with course content related questions i. e. assignment or test questions, grading policy, deadlines, etc.
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In total, there are just about 120 million American households. So when we talk about the top one percent, we are looking at the top 1. 2 million households. Breaking the 120 million homes down by race, according to the U. S. Census, there are nearly 83 million white households, and there are just about 14 million black households. Here is where the economic picture gets clearer. A few years ago when economic inequality was just becoming a national topic, theGrio supported by MSNBC, wrote a piece titled "Who are the Black 1%". In this article, they showed that nearly 96. 1 percent of the 1. 2 million households in the top one percent by income were white, a total of about 1,150,000 households.
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The second motivation for our investigation of attention is to understand the impact of attention on trading. The new idea is that trading can be decomposed into an attention decision and a separate decision to trade conditional on paying attention. The former is driven by a demand for information, while the latter is a pure or post attention trading decision that takes the attention decision as given. Aggregate trading combines patterns in both components. A new feature of our analysis is that we identify behavioral motives for these two components of trading separately. Patterns in logins reflect attention behavior driven by information utility bursts, such as the ostrich effect, as well as by monitoring for potential trading opportunities. In contrast, conditional trading is, by definition, purged of the effects of changes in attention. Positive feedbacks between lagged returns and conditional trading are consistent with realization utility bursts as gains and losses are definitively booked and fluctuation in investor confidence Daniel, Hirshleifer, and Subrahmanyam 1998; Gervais and Odean 2001, while a negative correlation can be caused by stop loss trading and bargain hunting. Optimal tax loss realization is not a consideration in trading here, since our trading sample includes only tax exempt accounts. Hypothesis 4: Patterns in aggregate attention and conditional trading differ due to differing underlying economic drivers. Hypothesis 4: Patterns in aggregate attention and conditional trading differ due to differing underlying economic drivers.
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