The OSU Scheme for Congestion Avoidance in ATM Networks: Lessons Learnt and Extensions

The OSU scheme is a rate-based congestion avoidance scheme for ATM networks using explicit rate indication. This work was one of the first attempts to define explicit rate switch mechanisms and the Resource Management (RM) cell format in Asynchronous Transfer Mode (ATM) networks. The key features of the scheme include explicit rate feedback, congestion avoidance, fair operation while maintaining high utilization, use of input rate as a congestion metric, O(1) complexity. This paper presents an overview of the scheme, presents those features of the scheme that have now become common features of other switch algorithms and discusses three extensions of the scheme

Privacy Aware Experiments without Cookies

Consider two brands that want to jointly test alternate web experiences for their customers with an A/B test. Such collaborative tests are today enabled using \textit{third-party cookies}, where each brand has information on the identity of visitors to another website. With the imminent elimination of third-party cookies, such A/B tests will become untenable. We propose a two-stage experimental design, where the two brands only need to agree on high-level aggregate parameters of the experiment to test the alternate experiences. Our design respects the privacy of customers. We propose an estimater of the Average Treatment Effect (ATE), show that it is unbiased and theoretically compute its variance. Our demonstration describes how a marketer for a brand can design such an experiment and analyze the results. On real and simulated data, we show that the approach provides valid estimate of the ATE with low variance and is robust to the proportion of visitors overlapping across the brands.Comment: Technical repor

Hypertrophic cardiomyopathy clinical phenotype is independent of gene mutation and mutation dosage

<div><p>Over 1,500 gene mutations are known to cause hypertrophic cardiomyopathy (HCM). Previous studies suggest that cardiac β-myosin heavy chain (<i>MYH7)</i> gene mutations are commonly associated with a more severe phenotype, compared to cardiac myosin binding protein-C (<i>MYBPC3)</i> gene mutations with milder phenotype, incomplete penetrance and later age of onset. Compound mutations can worsen the phenotype. This study aimed to validate these comparative differences in a large cohort of individuals and families with HCM. We performed genome-phenome correlation among 80 symptomatic HCM patients, 35 asymptomatic carriers and 35 non-carriers, using an 18-gene clinical diagnostic HCM panel. A total of 125 mutations were identified in 14 genes. <i>MYBPC3</i> and <i>MYH7</i> mutations contributed to 50.0% and 24.4% of the HCM patients, respectively, suggesting that <i>MYBPC3</i> mutations were the most frequent cause of HCM in our cohort. Double mutations were found in only nine HCM patients (7.8%) who were phenotypically indistinguishable from single-mutation carriers. Comparisons of clinical parameters of <i>MYBPC3</i> and <i>MYH7</i> mutants were not statistically significant, but asymptomatic carriers had high left ventricular ejection fraction and diastolic dysfunction when compared to non-carriers. The presence of double mutations increases the risk for symptomatic HCM with no change in severity, as determined in this study subset. The pathologic effects of <i>MYBPC3</i> and <i>MYH7</i> were found to be independent of gene mutation location. Furthermore, HCM pathology is independent of protein domain disruption in both <i>MYBPC3</i> and <i>MYH7</i>. These data provide evidence that <i>MYBPC3</i> mutations constitute the preeminent cause of HCM and that they are phenotypically indistinguishable from HCM caused by <i>MYH7</i> mutations.</p></div

Genetic evaluation profile of the study cohort.

<p><b>A-C</b>, show the percentage of gene mutation contribution among all subjects (<b>A</b>); HCM (<b>B</b>); and AC (<b>C</b>). Pathogenic mutation distribution among the various causative genes (<b>D</b>). <i>MYBPC3</i> and <i>MYH7</i> mutations are causative in >80% of all subjects, irrespective of their current phenotypic pathogenicity.</p