Scale and Translation Invariant Methods for Enhanced Time-Frequency Pattern Recognition

Time-frequency (t-f) analysis has clearly reached a certain maturity. One can now often provide striking visual representations of the joint time-frequency energy representation of signals. However, it has been difficult to take advantage of this rich source of information concerning the signal, especially for multidimensional signals. Properly constructed time-frequency distributions enjoy many desirable properties. Attempts to incorporate t-f analysis results into pattern recognition schemes have not been notably successful to date. Aided by Cohen's scale transform one may construct representations from the t-f results which are highly useful in pattern classification. Such methods can produce two dimensional representations which are invariant to time-shift, frequency-shift and scale changes. In addition, two dimensional objects such as images can be represented in a like manner in a four dimensional form. Even so, remaining extraneous variations often defeat the pattern classification approach. This paper presents a method based on noise subspace concepts. The noise subspace enhancement allows one to separate the desired invariant forms from extraneous variations, yielding much improved classification results. Examples from sound classification are discussed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47350/1/11045_2004_Article_181150.pd

Obesity resistant mechanisms in the Lean polygenic mouse model as indicated by liver transcriptome and expression of selected genes in skeletal muscle

<p>Abstract</p> <p>Background</p> <p>Divergently selected Lean and Fat mouse lines represent unique models for a polygenic form of resistance and susceptibility to obesity development. Previous research on these lines focused mainly on obesity-susceptible factors in the Fat line. This study aimed to examine the molecular basis of obesity-resistant mechanisms in the Lean line by analyzing various fat depots and organs, the liver transcriptome of selected metabolic pathways, plasma and lipid homeostasis and expression of selected skeletal muscle genes.</p> <p>Results</p> <p>Expression profiling using our custom Steroltalk v2 microarray demonstrated that Lean mice exhibit a higher hepatic expression of cholesterol biosynthesis genes compared to the Fat line, although this was not reflected in elevation of total plasma or liver cholesterol. However, FPLC analysis showed that protective HDL cholesterol was elevated in Lean mice. A significant difference between the strains was also found in bile acid metabolism. Lean mice had a higher expression of <it>Cyp8b1</it>, a regulatory enzyme of bile acid synthesis, and the <it>Abcb11 </it>bile acid transporter gene responsible for export of acids to the bile. Additionally, a higher content of blood circulating bile acids was observed in Lean mice. Elevated HDL and upregulation of some bile acids synthesis and transport genes suggests enhanced reverse cholesterol transport in the Lean line - the flux of cholesterol out of the body is higher which is compensated by upregulation of endogenous cholesterol biosynthesis. Increased skeletal muscle <it>Il6 </it>and <it>Dio2 </it>mRNA levels as well as increased activity of muscle succinic acid dehydrogenase (SDH) in the Lean mice demonstrates for the first time that changes in muscle energy metabolism play important role in the Lean line phenotype determination and corroborate our previous findings of increased physical activity and thermogenesis in this line. Finally, differential expression of <it>Abcb11 </it>and <it>Dio2 </it>identifies novel strong positional candidate genes as they map within the quantitative trait loci (QTL) regions detected previously in crosses between the Lean and Fat mice.</p> <p>Conclusion</p> <p>We identified novel candidate molecular targets and metabolic changes which can at least in part explain resistance to obesity development in the Lean line. The major difference between the Lean and Fat mice was in increased liver cholesterol biosynthesis gene mRNA expression, bile acid metabolism and changes in selected muscle genes' expression in the Lean line. The liver <it>Abcb11 </it>and muscle <it>Dio2 </it>were identified as novel positional candidate genes to explain part of the phenotypic difference between the Lean and Fat lines.</p

Cholesterol and Lipoprotein Dynamics in a Hibernating Mammal

Hibernating mammals cease feeding during the winter and rely primarily on stored lipids to fuel alternating periods of torpor and arousal. How hibernators manage large fluxes of lipids and sterols over the annual hibernation cycle is poorly understood. The aim of this study was to investigate lipid and cholesterol transport and storage in ground squirrels studied in spring, summer, and several hibernation states. Cholesterol levels in total plasma, HDL and LDL particles were elevated in hibernators compared with spring or summer squirrels. Hibernation increased plasma apolipoprotein A-I expression and HDL particle size. Expression of cholesterol 7 alpha-hydroxylase was 13-fold lower in hibernators than in active season squirrels. Plasma triglycerides were reduced by fasting in spring but not summer squirrels. In hibernators plasma β-hydroxybutyrate was elevated during torpor whereas triglycerides were low relative to normothermic states. We conclude that the switch to a lipid-based metabolism during winter, coupled with reduced capacity to excrete cholesterol creates a closed system in which efficient use of lipoproteins is essential for survival

On the origin of innovations—the opportunity vacuum as a conceptual model for the explanation of innovation

The aim of this paper is to transfer the innovation system (IS) approach to the microeconomic level, creating a conceptual framework which helps individual actors to explain, identify, and predict the origin of innovations. Based on the ongoing discussion about the applicability of boundedly rational search and, in particular, the metaphor of an opportunity landscape, the author has developed a conceptual framework for the origin of economic innovations, structured along three dimensions. First, the adjacent possible defines a narrow space of potential first-order combinations of exiting knowledge, which is the trajectory for the new developments in technology and science. Second, the adjacent feasible defines an area of expected cost reduction which enables the exploitation of the new technologies within a threshold. Finally, the adjacent acceptable represents a small area on the current edges of socially accepted behavior, which currently only innovators embrace, but soon will reach the early majority of adopters. It is, however, the moment when all three dimensions achieve an intersecting area, when the opportunity vacuum (OV) is created. The OV is a space, which strongly attracts innovation and often creates multiple inventions at the same time emerging independently. While this model is aimed at explaining the origin of economic innovations in retrospective, it can also be applied as a framing method to anticipate future economic novelty