An Aching for Affection

As humans, we’ve needed companionship from the beginning of time. Therefore, what does a true relationship look like in today’s society? In this world of newly emerging relationships, many people have either experienced, seen, or heard of a toxic relationship. This article dives deep into what makes a toxic relationship, how to notice the red flags, and how to ultimately fix or end it

Learning First-Order Definitions of Functions

First-order learning involves finding a clause-form definition of a relation from examples of the relation and relevant background information. In this paper, a particular first-order learning system is modified to customize it for finding definitions of functional relations. This restriction leads to faster learning times and, in some cases, to definitions that have higher predictive accuracy. Other first-order learning systems might benefit from similar specialization.Comment: See http://www.jair.org/ for any accompanying file

Hermitian and skew hermitian forms over local rings

We study the classification problem of possibly degenerate hermitian and skew hermitian bilinear forms over local rings where 2 is a unit

Actin filament assembly by bacterial factors VopL/F: Which end is up?

Competing models have been proposed for actin filament nucleation by the bacterial proteins VopL/F. In this issue, Burke et al. (2017. J. Cell Biol. https://doi.org/10.1083/jcb.201608104) use direct observation to demonstrate that VopL/F bind the barbed and pointed ends of actin filaments but only nucleate new filaments from the pointed end

Discovering Regression Rules with Ant Colony Optimization

The majority of Ant Colony Optimization (ACO) algorithms for data mining have dealt with classification or clustering problems. Regression remains an unexplored research area to the best of our knowledge. This paper proposes a new ACO algorithm that generates regression rules for data mining applications. The new algorithm combines components from an existing deterministic (greedy) separate and conquer algorithm—employing the same quality metrics and continuous attribute processing techniques—allowing a comparison of the two. The new algorithm has been shown to decrease the relative root mean square error when compared to the greedy algorithm. Additionally a different approach to handling continuous attributes was investigated showing further improvements were possible