cellular and tissue activities highly depend on environmental ph. murine lung tissue, when cultured properly in-vitro, is a potent producer of hematopoietic growth factors. we have studied the effect of ph on the production of hematopoietic growth factors and protein synthesis by the murine lung in-vitro. various concentrations of nahc03 were used to adjust the ph of the culture medium under co...

We present an algorithm for computing both functional dependency and unateness of combinational and sequential Boolean functions represented as logic networks. The algorithm uses SAT-based techniques from Combinational Equivalence Checking (CEC) and Automatic Test Pattern Generation (ATPG) to compute the dependency matrix of multi-output Boolean functions. Additionally, the classical dependency...

The hippocampus is thought to be an associative memory "convergence zone," binding together the multimodal elements of an experienced event into a single engram. This predicts a degree of dependency between the retrieval of the different elements comprising an event. We present data from a series of studies designed to address this prediction. Participants vividly imagined a series of person-lo...

Cellular and tissue activities highly depend on environmental pH. Murine lung tissue, when cultured properly in-vitro, is a potent producer of hematopoietic growth factors. We have studied the effect of pH on the production of hematopoietic growth factors and protein synthesis by the murine lung in-vitro. Various concentrations of NaHC03 were used to adjust the pH of the culture medium unde...

Many recently reported machine learning approaches to the acquisition of information extraction (IE) patterns have used dependency trees as the basis for their pattern representations (Yangarber et al., 2000a; Yangarber, 2003; Sudo et al., 2003; Stevenson and Greenwood, 2005). While varying results have been reported for the resulting IE systems little has been reported about the ability of dep...

The use of feature discretization (FD) is useful in several machine learning and pattern recognition tasks. By attaining adequate and compact data representations, FD may improve the performance of many methods. It is often the case that learning with discrete data representations yields both lower training time and better accuracy, as compared to the use of the original features. Moreover, FD ...

The refactoring of large systems is difficult, with the possibility of many refactorings having to be done before any useful benefit is attained. We present a novel approach to detect starting points for the architectural refactoring of large and complex systems based on the analysis and manipulation of the type dependency graph extracted from programs. The proposed algorithm is based on the si...