Parent and Child Psychological Factors in Pediatric Syncope and Other Somatic Symptoms.

The authors examined associations among parental and child adjustment, child syncope, somatic, and school problems. Participants were children (N = 56) ages 7-18 years with syncope. Measures included syncope severity, parental distress, and children's internalizing symptoms. For children diagnosed negative for neurocardiogenic syncope (NCS), their fathers' and their own psychological symptoms were positively associated with the severity of syncope, whereas their mothers' functioning was negatively associated with the severity of syncope. Also, for the negative NCS group, fathers' psychological functioning was associated with children's nonsyncope somatic complaints but not with their school problems. For the positive NCS group, few significant father-child associations were found, but several significant positive associations were revealed between mothers' psychological symptoms and their children's syncope as well as somatic and school problems. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Object detection using feature subset selection

Past work on object detection has emphasized the issues of feature extraction and classification, however, relatively less attention has been given to the critical issue of feature selection. The main trend in feature extraction has been representing the data in a lower dimensional space, for example, using principal component analysis (PCA). Without using an effective scheme to select an appropriate set of features in this space, however, these methods rely mostly on powerful classification algorithms to deal with redundant and irrelevant features. In this paper, we argue that feature selection is an important problem in object detection and demonstrate that genetic algorithms (GAs) provide a simple, general, and powerful framework for selecting good subsets of features, leading to improved detection rates. As a case study, we have considered PCA for feature extraction and support vector machines (SVMs) for classification. The goal is searching the PCA space using GAs to select a subset of eigenvectors encoding important information about the target concept of interest. This is in contrast to traditional methods selecting some percentage of the top eigenvectors to represent the target concept, independently of the classification task. We have tested the proposed framework on two challenging applications: vehicle detection and face detection. Our experimental results illustrate significant performance improvements in both cases.     

Computational models of a nano probe tip for static behaviors

It is difficult to predict the measurement bias arising from the compliance of the atomic force microscope (AFM) probe. The issue becomes particularly important in this situation where nanometer uncertainties are sought for measurements with dimensional probes composed of flexible carbon nanotubes mounted on AFM cantilevers. We have developed a finite element model for simulating the mechanical behavior of AFM cantilevers with carbon nanotubes attached. Spring constants of both the nanotube and cantilever in two directions are calculated using the finite element method with known Young's moduli of both silicon and multiwall nanotube as input data. Compliance of the nanotube-attached AFM probe tip may be calculated from the set of spring constants. This paper presents static models that together provide a basis to estimate uncertainties in linewidth measurement using nanotubes. In particular, the interaction between a multiwall nanotube tip and a silicon sample is modeled using the Lennard-Jones theory. Snap-in and snap-out of the probe tip in a scanning mode are calculated by integrating the compliance of the probe and the sample-tip interacting force model. Cantilever and probe tip deflections and points of contact are derived for both horizontal scanning of a plateau and vertically scanning of a wall. The finite element method and the Lennard-Jones model provide a means to analyze the interaction of the probe and sample and measurement uncertainty, including actual deflection and the gap between the probe tip and the measured sample surface.     

Three-dimensional image correction of tilted samples through coordinate transformation

In scanned probe measurements of micrometer- or nanometer-scale lines, it is nearly impossible to maintain the sample in a perfectly level position, and even a small amount of tilt can contribute to the accuracy of the result of the measure such as linewidth or step height. The current practice in image processing to deal with this problem is to conduct a line-by-line analysis to find the best fit of the substrate profile and subtract this background from all data points, thus describing 3D plane turns as a series of lines and processing them in succession in the x- or y-direction.In this paper a coordinate transformation method is proposed. The new coordinate system can be established on the basis of the inclined angle of the sample as well as the translation of three axes between the old coordinate system and the new coordinate system. The method can mathematically derive and hence correct all tilts around the x-, y- and z-axes and produce a leveled image simultaneously. Feature dimensions such as width, height, sidewall angle and pitch are calculated on the basis of simulated images using the coordinate transformation method and other methods. The result shows the advantage of the proposed method.     

Graduate training of scientist–practitioner-oriented clinical psychologists: Where we can improve.

To improve psychology graduate programs, the training provided by scientist- or practitioner-oriented graduate programs in clinical psychology is evaluated from the perspective of a director of clinical training in an American Psychological Association-approved internship. Areas in which graduate training may be improved are divided into knowledge, supervision, research, and professional development. Specific training deficits are enumerated, and suggestions for their remediation are offered. (15 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Bioinformatic Analysis of Na+, K+-ATPase Regulation through Phosphorylation of the Alpha-Subunit N-Terminus

The Na⁺, K⁺-ATPase is an integral membrane protein which uses the energy of ATP hydrolysis to pump Na⁺ and K⁺ ions across the plasma membrane of all animal cells. It plays crucial roles in numerous physiological processes, such as cell volume regulation, nutrient reabsorption in the kidneys, nerve impulse transmission, and muscle contraction. Recent data suggest that it is regulated via an electrostatic switch mechanism involving the interaction of its lysine-rich N-terminus with the cytoplasmic surface of its surrounding lipid membrane, which can be modulated through the regulatory phosphorylation of the conserved serine and tyrosine residues on the protein’s N-terminal tail. Prior data indicate that the kinases responsible for phosphorylation belong to the protein kinase C (PKC) and Src kinase families. To provide indications of which particular enzyme of these families might be responsible, we analysed them for evidence of coevolution via the mirror tree method, utilising coevolution as a marker for a functional interaction. The results obtained showed that the most likely kinase isoforms to interact with the Na⁺, K⁺-ATPase were the θ and η isoforms of PKC and the Src kinase itself. These theoretical results will guide the direction of future experimental studies.     

Kernel‐based gluten contamination of gluten‐free oatmeal complicates gluten assessment as it causes binary‐like test outcomes

Gluten‐free (GF) foods, whose claim compliance is controlled at the ‘serving level’, hold better chances of protecting gluten‐intolerant consumers. This is particularly true for GF oatmeal, as oats are easily contaminated with gluten‐rich kernels of wheat, rye and barley, which remain intact to the spoon as pill‐like flakes. A single contaminant kernel in otherwise pure oats results in GF labelling noncompliance, thereby posing a risk to patients with coeliac disease. Our in‐market survey of 965 GF oatmeal servings uncovered that one in fifty‐seven servings exceeded the GF labelling maximum of 20 mg kg^?1 (i.e. 20 ppm). The noncompliance pattern was ‘binary‐like’, with kernel‐based contamination the suspected pass/fail driver. We have highlighted probabilities of misassessment for various sample sizes in light of oat's natural propensity for kernel‐based contamination and proposed use of attribute‐based sampling for compliance assessment, thereby providing a way to assess/manage/control ‘rates of servings containing a contaminant kernel’ within acceptable limits with high confidence.