The hypothesis of a Hierarchy of the Sciences with physical sciences at the top, social sciences at the bottom, and biological sciences in-between is nearly 200 years old. This order is intuitive and reflected in many features of academic life, but whether it reflects the "hardness" of scientific research--i.e., the extent to which research questions and results are determined by data and theor...

The study of dynamic functions of large-scale biological networks has intensified in recent years. A critical component in developing an understanding of such dynamics involves the study of their hierarchical organization. We investigate the temporal hierarchy in biochemical reaction networks focusing on: (1) the elucidation of the existence of "pools" (i.e., aggregate variables) formed from co...

The concept of emergence and the related notion of 'downward causation' have arisen in numerous branches of science, and have also been extensively discussed in philosophy. Here, I examine emergence and downward causation in relation to evolutionary biology. I focus on the old, but ongoing discussion in evolutionary biology over the 'levels of selection' question: which level(s) of the biologic...

We extend previous collapsing results involving the exponential hierarchy by using recent hardness-randomness trade-off results. Specifically, we show that if the second level of the exponential hierarchy has polynomialsized circuits, then it collapses all the way down to MA.

Widely dispersed monitoring networks generate huge data volumes that are naturally organized via hierarchical aggregation. In a system that manages such data, applications pose periodic aggregate queries. In this paper we show how to efficiently process multiple periodic aggregate queries in a hierarchy. First, we use a novel query rewrite that optimally executes individual queries. Next, we sh...

Clustering is a task of assigning a set of objects into groups called clusters. In data mining, hierarchical clustering is a method of cluster analysis which seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two types:Agglomerative: This is a "bottom up" approach: each observation starts in its own cluster, and pairs of clusters are merged as one...

Current hierarchical text categorization (HTC) methods mainly fall into three directions: (1) Flat one-vs.-all approach, which flattens the hierarchy into independent nodes and trains a binary one-vs.-all classifier for each node. (2) Top-down method, which uses the hierarchical structure to decompose the entire problem into a set of smaller subproblems, and deals with such sub-problems in top-...

So far, it was unclear if social hierarchy could influence sensory or perceptual cognitive processes. We evaluated the effects of social hierarchy on these processes using a basic visual perceptual decision task. We constructed a social hierarchy where participants performed the perceptual task separately with two covertly simulated players (superior, inferior). Participants were faster (better...

Currently, social bookmarking systems provide intuitive support for browsing locally their content. A global view is usually presented by the tag cloud of the system, but it does not allow a conceptual drill-down, e. g., along a conceptual hierarchy. In this paper, we present a clustering approach for computing such a conceptual hierarchy for a given folksonomy. The hierarchy is complemented wi...