Biomedical subjects

Steve Lawrence

Publications and source records attributed to Steve Lawrence.

3 recordsLinked to original sources

PubMed2004

Extracting knowledge from the World Wide Web.

The World Wide Web provides a unprecedented opportunity to automatically analyze a large sample of interests and activity in the world. We discuss methods for extracting knowledge from the web by randomly sampling and analyzing hosts and pages, and by analyzing the link structure of the web and how links accumulate over time. A variety of interesting and valuable information can be extracted, such as the distribution of web pages over domains, the distribution of interest in different areas, communities related to different topics, the nature of competition in different categories of sites, and the degree of communication between different communities or countries.

Artificial Intelligence↗

PubMed2003

Glycogen synthesis in muscle fibers during active recovery from intense exercise.

PURPOSE: There is evidence that active recovery impairs glycogen repletion in skeletal muscles of fasted individuals. Our main goal was to examine the impact of active recovery on the glycogen stores of the different muscle fiber types. METHODS: Eight endurance-trained individuals cycled for 2.5 min at 130% [OV0312]O(2peak) followed by a 30-s all-out cycling sprint. After exercise, the participants were subjected to either a passive recovery or an active recovery protocol that consisted of pedalling for 45 min at 40% [OV0312]O(2peak). RESULTS: During active recovery, blood lactate and pH returned more rapidly toward preexercise levels than during passive recovery. In contrast, average muscle glycogen content remained at stable levels during active recovery (209 +/- 32 and 202 +/- 30 mmol.kg-1 at 0 and 45 min of recovery, respectively) but increased significantly in response to passive recovery (from 185 +/- 27 to 283 +/- 42 mmol.kg-1). The pattern of change in periodic acid-Schiff staining intensity across muscle fibers suggests that the impact of active recovery on average muscle glycogen content is different from that observed at the levels of the individual muscle fibers, with active recovery having no effect on glycogen resynthesis in Type II muscle fibers but causing glycogen breakdown in Type I muscle fibers. Although active recovery was also associated with higher plasma catecholamines and lower insulin levels, such an unfavorable hormonal environment had no effect on glycogen resynthesis in Type II muscle fibers. CONCLUSION: Active recovery in comparison to passive recovery does not affect glycogen resynthesis in Type II muscle fibers despite being associated with an unfavorable hormonal environment but results in a marked glycogen mobilization in Type I muscle fibers.

Adult↗

PubMed2002

Winners don't take all: Characterizing the competition for links on the web.

As a whole, the World Wide Web displays a striking "rich get richer" behavior, with a relatively small number of sites receiving a disproportionately large share of hyperlink references and traffic. However, hidden in this skewed global distribution, we discover a qualitatively different and considerably less biased link distribution among subcategories of pages-for example, among all university homepages or all newspaper homepages. Although the connectivity distribution over the entire web is close to a pure power law, we find that the distribution within specific categories is typically unimodal on a log scale, with the location of the mode, and thus the extent of the rich get richer phenomenon, varying across different categories. Similar distributions occur in many other naturally occurring networks, including research paper citations, movie actor collaborations, and United States power grid connections. A simple generative model, incorporating a mixture of preferential and uniform attachment, quantifies the degree to which the rich nodes grow richer, and how new (and poorly connected) nodes can compete. The model accurately accounts for the true connectivity distributions of category-specific web pages, the web as a whole, and other social networks.

Journal Article↗