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https://www.selleckchem.com/products/gsk1120212-jtp-74057.html Our model explains why the errors from two control loops are additive and shows how the errors in each control loop can be decomposed into the errors caused by the limited speeds and accuracies of the components. These results demonstrate that an appropriate diversity in the properties of neurons across layers helps to create "diversity-enabled sweet spots," so that both fast and accurate control is achieved using slow or inaccurate components. To estimate the incidence of hospitalization for reversible cerebral vasoconstriction syndrome (RCVS), we identified RCVS-related hospital admissions across 11 U.S. states in 2016. We tested the validity of code I67.841 in 79 patients with hospital admissions for RCVS or other cerebrovascular diseases at one academic and one community hospital. After determining that this code had a sensitivity of 100% (95% CI, 82-100%) and a specificity of 90% (95% CI, 79-96%), we applied it to administrative data from the Healthcare Cost and Utilization Project on all ED visits and hospital admissions. Age- and sex-standardized RCVS incidence was calculated using census data. Descriptive statistics were used to analyze associated diagnoses. Across 5,067,250 hospital admissions in our administrative data, we identified 222 patients with a discharge diagnosis of RCVS in 2016. The estimated annual age- and sex-standardized incidence of RCVS hospitalization was 2.7 (95% CI, 2.4-3.1) cases per million adults. Many patients had concomitant neurologic diagnoses, including subarachnoid hemorrhage (37%), ischemic stroke (16%), and intracerebral hemorrhage (10%). In the 90 days before the index admission, 97 patients had an ED visit and 34 patients a hospital admission, most commonly for neurologic, psychiatric, and pregnancy-related diagnoses. Following discharge from the RCVS hospital admission, 58 patients had an ED visit and 31 had a hospital admission, most commonly for neurologic di

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