Discrete-time complementary models and smoothing algorithms: The correlated noise case

The concept of complementary models for discrete-time linear finite-dimensional systems with correlated observation and process noise is developed. Using this concept, a new algorithm for the fixed interval smoothing problem is obtained. The new algorithm offers great flexibility with respect to changes in the initial state variancePi_{0}. Next, the relationship among the new smoothing algorithm, the two-filter smoother, and the reversed-time Kalman filter is explored. It is shown that a similarity transformation on the Hamiltonian system simultaneously produces the new smoothing algorithm, as well as the reversed-time Kalman filter.     

Gambling, health and age: Data from the National Epidemiologic Survey on Alcohol and Related Conditions.

The health effects of recreational gambling are presently unclear, particularly across age groups. Theories of healthy aging suggest that social activities, including gambling, may be beneficial to the health of older adults. Using cross-sectional data from the National Epidemiologic Survey on Alcohol and Related Conditions (N=43,093), the authors examined associations between gambling (categorized as nongambling, recreational gambling, or problem/pathological gambling) and health and functioning measures stratified by age (40-64 years and ≥65). Problem/pathological gambling was uniformly associated with poorer health measures among both younger and older adults. Among younger respondents, poorer health measures were also found among recreational gamblers. However, among older respondents, recreational gambling was associated not only with some negative measures (e.g., obesity) but also with some positive measures (e.g., better physical and mental functioning). Longitudinal studies are needed to clarify the relationship between gambling and health in older adults in the context of healthy aging. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback.

A content-based image retrieval (CBIR) framework for diverse collection of medical images of different imaging modalities, anatomic regions with different orientations and biological systems is proposed. Organization of images in such a database (DB) is well defined with predefined semantic categories; hence, it can be useful for category-specific searching. The proposed framework consists of machine learning methods for image prefiltering, similarity matching using statistical distance measures, and a relevance feedback (RF) scheme. To narrow down the semantic gap and increase the retrieval efficiency, we investigate both supervised and unsupervised learning techniques to associate low-level global image features (e.g., color, texture, and edge) in the projected PCA-based eigenspace with their high-level semantic and visual categories. Specially, we explore the use of a probabilistic multiclass support vector machine (SVM) and fuzzy c-mean (FCM) clustering for categorization and prefiltering of images to reduce the search space. A category-specific statistical similarity matching is proposed in a finer level on the prefiltered images. To incorporate a better perception subjectivity, an RF mechanism is also added to update the query parameters dynamically and adjust the proposed matching functions. Experiments are based on a ground-truth DB consisting of 5000 diverse medical images of 20 predefined categories. Analysis of results based on cross-validation (CV) accuracy and precision-recall for image categorization and retrieval is reported. It demonstrates the improvement, effectiveness, and efficiency achieved by the proposed framework.     

Linoleic Acid Rich Oil Seeds

The fatty acid composition of Cupressus semprevirens, Cupressus torulosa, Cupressus funebris, Cuppressus lusitanica, Cupressus macrocarpa and Cupressus arizonica seed oils had been determined.     

Activation of particulate guanylyl cyclase by Vibrio vulnificus hemolysin

Recently we reported that Vibrio vulnificus hemolysin, an exotoxin produced by V. vulnificus, dilates rat thoracic aorta via elevated cGMP levels without affecting nitric oxide synthase. We investigated the mechanism further by observing the guanylyl cyclase activities in cytosolic, membrane, unfractionated, or reconstituted preparations. Hemolysin did not activate guanylyl cyclase in the membrane or cytosolic fraction, while it activated guanylyl cyclase in unfractionated or reconstituted preparation. The increased activity was not inhibited by the HS-142-1, a microbial polysaccharide which antagonizes atrial natriuretic peptide receptor, or 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one (ODQ), a soluble guanylyl cyclase inhibitor. However, it was attenuated by 6-(phenylamino)-5,8-quinolinedione (LY 83.583), which inhibits the catalytic domain of both guanylyl cyclases, and by cholesterol, which blocks hemolysin-incorporation into the membrane. Removing ATP, a cofactor of particulate guanylyl cyclase, attenuated the activation and ATPgammaS, a non-phosphorylating analog, restored it. These results suggest that V. vulnificus hemolysin activates particulate guanylyl cyclase via hemolysin incorporation into the vascular smooth muscle cell membrane in cooperation with certain unidentified cytosolic component(s).     

Discriminative Models for Multi-Class Object Layout

Many state-of-the-art approaches for object recognition reduce the problem to a 0-1 classification task. This allows one to leverage sophisticated machine learning techniques for training classifiers from labeled examples. However, these models are typically trained independently for each class using positive and negative examples cropped from images. At test-time, various post-processing heuristics such as non-maxima suppression (NMS) are required to reconcile multiple detections within and between different classes for each image. Though crucial to good performance on benchmarks, this post-processing is usually defined heuristically.     

A Cure for Bioengineering? A New Undergraduate Core Curriculum

Student interest, industry growth, and medical advances highlight a growing need for baccalaureate trained bioengineers. However, undergraduate bioengineering curricula have not kept pace with the recent rapid growth of biotechnology, bioinformatics, and cellular level bioengineering. It is the premise of this paper that a new baccalaureate core curriculum in cell and tissue engineering is needed to foster the full development of bioengineering as a core engineering discipline. Employment opportunities for baccalaureate Bioengineering graduates in the emerging biologically‐based engineering industry (e.g. bioinformatics, cell and tissue engineering, neural engineering) are increasing. We describe a new undergraduate B.S. bioengineering curriculum in cell and tissue engineering with an emphasis in interfacial molecular approaches. This curriculum is integrated with traditional bioengineering topics and has its technical emphasis in molecular biology, nanotechnology, and computational modeling. Thus, the future bioengineer can be expected to design, model, fabricate, and control living systems and their fundamental constituents at the same level of detail as an electrical engineer uses SPICE and CAD tools to develop a microelectronic or micro‐electro‐mechanical device. Such engineers would be expected to take their place in industry, graduate school, or medicine with a clear mastery of cell and tissue‐based bioengineering.     

Differential expression of two functional serine/threonine protein kinases from soybean that have an unusual acidic domain at the carboxy terminus

Two soybean cDNA clones, SPK-3 and SPK-4, encoding putative protein kinases were isolated and characterized. Both cDNAs encoded approximately 40-kDa serine/threonine kinases with unusual stretches of acidic amino acids in their carboxy-terminal regions, which are highly homologous to PKABA1 from wheat and ASKs from Arabidopsis. These kinases are encoded by one- or two-copy genes in the soybean genome. Notably, SPK-3 and -4 showed different patterns of expression in various soybean tissues. SPK-3 is highly expressed in dividing and elongating tissues of young seedlings but relatively weakly in tissues of mature plants. In contrast, SPK-4 showed relatively high and constitutive expression in all the tissues examined except for leaf tissues of mature plants. Although various stressors, such as dehydration and high salinity, increased the expression of both genes, the induction kinetics were different. The two genes also differed in their response to abscisic acid (ABA). SPK-3 was induced but SPK-4 was not affected by exogenously supplied abscisic acid. In accordance with these expression data analysis of the activity of a chimeric SPK-3 promoter::beta-glucuronidase (GUS) reporter gene by transient expression in tobacco leaves confirmed the inducibility of SPK-3 by salt and ABA. Polyclonal antibodies raised against a recombinant SPK-4 protein produced in Escherichia coli specifically recognized both recombinant SPK-3 and -4 proteins. Kinase assays using affinity-purified SPK-4/ antibody complexes with crude soybean extracts as substrate identified specific phosphorylation of two 41 and 170 kDa soybean proteins that were phosphorylated on serine residues. Taken together, our results suggest that SPK-3, and/or SPK-4 are functional serine protein kinase(s). Furthermore, SPK-3 and -4 may play different roles in the transduction of various environmental stresses.