A DNA-based in vitroGenetic Program.

In PNA-mediated Whiplash PCR (PWPCR), autonomous molecular computation is implemented by the recursive polymerase extension of a mixture of DNA hairpins. Like other methods based on exhaustive search, however, application to problem instances of realistic size is prevented by the exponential scaling of thesolution space. The tendency of evolving populations to minimize the sampling of large, low fitness basins suggests that a DNA-based evolutionary approach might be an effective alternative to exhaustive search. In this work, PWPCR is modified to support the evolution of a population of finite state machines. A practical, in vitroalgorithm for applying this architecture to evolve approximate solutions to instances of the NP-complete problem, Hamiltonian Pathis described in detail.

Automated segmentation and classification of multispectral magnetic resonance images of brain using artificial neural networks.

We present a fully automated process for segmentation and classification of multispectral magnetic resonance (MR) images. This hybrid neural network method uses a Kohonen self-organizing neural network for segmentation and a multilayer backpropagation neural network for classification. To separate different tissue types, this process uses the standard T1-, T2-, and PD-weighted MR images acquired in clinical examinations. Volumetric measurements of brain structures, relative to intracranial volume, were calculated for an index transverse section in 14 normal subjects (median age 25 years; seven male, seven female). This index slice was at the level of the basal ganglia, included both genu and splenium of the corpus callosum, and generally, showed the putamen and lateral ventricle. An intraclass correlation of this automated segmentation and classification of tissues with the accepted standard of radiologist identification for the index slice in the 14 volunteers demonstrated coefficients (ri) of 0.91, 0.95, and 0.98 for white matter, gray matter, and ventricular cerebrospinal fluid (CSF), respectively. An analysis of variance for estimates of brain parenchyma volumes in five volunteers imaged five times each demonstrated high intrasubject reproducibility with a significance of at least p < 0.05 for white matter, gray matter, and white/gray partial volumes. The population variation, across 14 volunteers, demonstrated little deviation from the averages for gray and white matter, while partial volume classes exhibited a slightly higher degree of variability. This fully automated technique produces reliable and reproducible MR image segmentation and classification while eliminating intra- and interobserver variability.

Unanswered questions about the criminalization of therapist-patient sex.

Even though much has been written about the issue of criminalization of therapist-patient sex, many questions about the issue remain unanswered, raising doubts about the wisdom of nationwide adoption of criminalizing legislation. From a philosophical standpoint, we need to understand more fully what thoughts, emotions, and behaviors constitute consent. Furthermore we must determine how much value to give consent in relation to other social values and goals. From a clinical standpoint we still need a better understanding of what constitutes the therapist-patient relationship: what it is and when it is over. We must also examine more carefully the nature of power within a psychotherapeutic relationship. From a legal standpoint we must determine how criminalization affects constitutional privacy rights, as embodied both in state constitutions and the federal Constitution. From an empirical standpoint we need to assess the efficacy of current criminalization statutes and determine their effect on tort compensation for patient victims. We also need to assess the practical application of these statutes by juries. Without more thorough analysis of all the issues raised, the criminalization of patient-therapist sex by state legislatures may in fact cause more harm than good.