Isolated lung perfusion (ILP) has been historically used as a method to study basic lung physiologic concepts using animal models. More recently, ILP has been applied in lung transplantation and thoracic oncology. In lung transplantation, ILP has been used to assess physiological integrity of donor lungs after the organ is removed from the donor. This procedure is called Ex vivo Lung Perfusion ...

Inductive Logic Programming (ILP) systems construct explanations for data in terms of domain-speciic background information. How does the quality of this information aaect the performance of an ILP system? Results from experiments concerned with learning simple programs for list processing suggest that performance is sensitive to the type and amount of background knowledge provided. In particul...

The goal of inductive logic programming (ILP) is to search for a hypothesis that generalises training examples and background knowledge (BK). To improve performance, we introduce an approach that, before searching hypothesis, first discovers "where not search". We use given BK discover constraints on hypotheses, such as number cannot be both even odd. the bootstrap constraint-driven ILP system....

Industry is increasingly overwhelmed by large-volume-data. For example, the pharmaceutical industry generates vast quantities of data both internally as a side-eeect of screening tests and combinato-rial chemistry, as well as externally from sources such as the human genome project. Industry is also becoming predominantly knowledge-driven. Increased understanding not only improves products, but...

Joint inference approaches such as Integer Linear Programming (ILP) and Markov Logic Networks (MLNs) have recently been successfully applied to many natural language processing (NLP) tasks, often outperforming their pipeline counterparts. However, MLNs are arguably much less popular among NLP researchers than ILP. While NLP researchers who desire to employ these joint inference frameworks do no...

Integrated Layer Processing (ILP) has been presented as an implementation technique to improve communication protocol performance by reducing the number of memory references. Previous research has however not pointed out that in some circumstances ILP can significantly increase the number of memory references, resulting in lower communication throughput. We explore the performance effects of ap...

Inductive Logic Programming (ILP) systems have been largely applied to classification problems with a considerable success. The use of ILP systems in problems requiring numerical reasoning capabilities has been far less successful. Current systems have very limited numerical reasoning capabilities, which limits the range of domains where the ILP paradigm may be applied. This paper proposes impr...

We present a framework for the Induction of Functional Logic Programs (IFLP) from facts. This can be seen as an extension to the now consolidated field of Inductive Logic Programming (ILP). Inspired in the inverse resolution operator of ILP, we study the reversal of narrowing, the more usual operational mechanism for Functional Logic Programming. We also generalize the selection criteria for gu...

This paper presents an integer linear programming (ILP) technique to partition and schedule Synchronous Data Flow (SDF) graphs onto heterogeneous execution architectures. Our ILP formulation gives a partition and schedule for SDF graphs, which provide the optimal execution time. We incorporate new methods of exploiting stateless data-parallelism on a heterogeneous architecture. We quantitativel...

The insulin/insulin-like peptides (ILPs) regulate key events in physiology, including neural plasticity. However, the cellular and circuit mechanisms whereby ILPs regulate learning remain largely unknown. Here, we characterize two ILPs that play antagonistic roles in aversive olfactory learning of C. elegans. We show that the ILP ins-6 acts from ASI sensory neurons to enable learning by repress...