D.M. Wilkes

Among the many clinical decisions that psychiatrists must make, assessment of a patient's risk of committing suicide is definitely among the most important, complex, and demanding. When reviewing his clinical experience, one of the authors observed that successful predictions of suicidality were often based on the patient's voice independent of content. The voices of suicidal patients judged to be high-risk near-term exhibited unique qualities, which distinguished them from nonsuicidal patients. We investigated the discriminating power of two excitation-based speech parameters, vocal jitter and glottal flow spectrum, for distinguishing among high-risk near-term suicidal, major depressed, and nonsuicidal patients. Our sample consisted of ten high-risk near-term suicidal patients, ten major depressed patients, and ten nondepressed control subjects. As a result of two sample statistical analyses, mean vocal jitter was found to be a significant discriminator only between suicidal and nondepressed control groups (p < 0.05). The slope of the glottal flow spectrum, on the other hand, was a significant discriminator between all three groups (p < 0.05). A maximum likelihood classifier, developed by combining the a posteriori probabilities of these two features, yielded correct classification scores of 85% between near-term suicidal patients and nondepressed controls, 90% between depressed patients and nondepressed controls, and 75% between near-term suicidal patients and depressed patients. These preliminary classification results support the hypothesized link between phonation and near-term suicidal risk. However, validation of the proposed measures on a larger sample size is necessary.

An approach to model order determination based on the minimum description length (MDL) criterion is proposed and shown to depend on the minimum eigenvalues of a covariance matrix derived from the observed data. A selection procedure for estimating the model order by means of the MDL method is proposed. Examples are given to illustrate the significantly improved accuracy of the technique.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Due to their ability to detect clusters with irregular boundaries, minimum spanning tree-based clustering algorithms have been widely used in practice. However, in such clustering algorithms, the search for nearest neighbor in the construction of minimum spanning trees is the main source of computation and the standard solutions take O(N^{2}) time. In this paper, we present a fast minimum spanning tree-inspired clustering algorithm, which, by using an efficient implementation of the cut and the cycle property of the minimum spanning trees, can have much better performance than O(N^{2}).

Prefiltering a given discrete signal has been shown to be an essential and necessary step in applications using unbalanced multiwavelets. In this paper, we develop two methods to obtain optimal second-order approximation preserving prefilters for a given orthogonal multiwavelet basis. These procedures use the prefilter construction introduced in part I of this paper. The first prefilter optimization scheme exploits the Taylor series expansion of the prefilter combined with the multiwavelet. The second one is achieved by minimizing the energy compaction ratio (ECR) of the wavelet coefficients for an experimentally determined average input spectrum. We use both methods to find prefilters for the cases of the DGHM and Chui-Lian (CL) multiwavelets. We then compare experimental results using these filters in an image compression scheme. Additionally, using the DGHM multiwavelet with the optimal prefilters from the first scheme, we find that quadratic input signals are annihilated by the high-pass portion of the filter bank at the first level of decomposition.

Cholinergic neurotransmission supports motor, autonomic, and cognitive function and is compromised in myasthenias, cardiovascular diseases, and neurodegenerative disorders. Presynaptic uptake of choline via the sodium-dependent, hemicholinium-3-sensitive choline transporter (CHT) is believed to sustain acetylcholine (ACh) synthesis and release. Analysis of this hypothesis in vivo is limited in mammals because of the toxicity of CHT antagonists and the early postnatal lethality of CHT-/- mice (Ferguson et al., 2004). In Caenorhabditis elegans, in which cholinergic signaling supports motor activity and mutant alleles impacting ACh secretion and response can be propagated, we investigated the contribution of CHT (CHO-1) to facets of cholinergic neurobiology. Using the cho-1 promoter to drive expression of a translational, green fluorescent protein-CHO-1 fusion (CHO-1:GFP) in wild-type and kinesin (unc-104) mutant backgrounds, we establish in the living nematode that the transporter localizes to cholinergic synapses, and likely traffics on synaptic vesicles. Using embryonic primary cultures, we demonstrate that CHO-1 mediates hemicholinium-3-sensitive, high-affinity choline uptake that can be enhanced with depolarization in a Ca(2+)-dependent manner supporting ACh synthesis. Although homozygous cho-1 null mutants are viable, they possess 40% less ACh than wild-type animals and display stress-dependent defects in motor activity. In a choline-free liquid environment, cho-1 mutants demonstrate premature paralysis relative to wild-type animals. Our findings establish a requirement for presynaptic choline transport activity in vivo in a model amenable to a genetic dissection of CHO-1 regulation.