An improved perturbation approach to the 2D Edwards polymer -- corrections to scaling

We present the results of a new perturbation calculation in polymer statistics which starts from a ground state that already correctly predicts the long chain length behaviour of the mean square end--to--end distance $\langle R_N^2 \rangle\$, namely the solution to the 2~dimensional~(2D) Edwards model. The $\langle R_N^2 \rangle$ thus calculated is shown to be convergent in $N$, the number of steps in the chain, in contrast to previous methods which start from the free random walk solution. This allows us to calculate a new value for the leading correction--to--scaling exponent~$\Delta$. Writing $\langle R_N^2 \rangle = AN^{2\nu}(1+BN^{-\Delta} + CN^{-1}+...)$, where $\nu = 3/4$ in 2D, our result shows that $\Delta = 1/2$. This value is also supported by an analysis of 2D self--avoiding walks on the {\em continuum}.Comment: 17 Pages of Revtex. No figures. Submitted to J. Phys.

The role of thermal and lubricant boundary layers in the transient thermal analysis of spur gears

An improved convection heat-transfer model has been developed for the prediction of the transient tooth surface temperature of spur gears. The dissipative quality of the lubricating fluid is shown to be limited to the capacity extent of the thermal boundary layer. This phenomenon can be of significance in the determination of the thermal limit of gears accelerating to the point where gear scoring occurs. Steady-state temperature prediction is improved considerably through the use of a variable integration time step that substantially reduces computer time. Computer-generated plots of temperature contours enable the user to animate the propagation of the thermal wave as the gears come into and out of contact, thus contributing to better understanding of this complex problem. This model has a much better capability at predicting gear-tooth temperatures than previous models

Unsupervised Domain Adaptation for 3D Keypoint Estimation via View Consistency

In this paper, we introduce a novel unsupervised domain adaptation technique for the task of 3D keypoint prediction from a single depth scan or image. Our key idea is to utilize the fact that predictions from different views of the same or similar objects should be consistent with each other. Such view consistency can provide effective regularization for keypoint prediction on unlabeled instances. In addition, we introduce a geometric alignment term to regularize predictions in the target domain. The resulting loss function can be effectively optimized via alternating minimization. We demonstrate the effectiveness of our approach on real datasets and present experimental results showing that our approach is superior to state-of-the-art general-purpose domain adaptation techniques.Comment: ECCV 201

Bayesian Student-t Stochastic Volatility Models

This paper considers a Student-t stochastic volatility (SV) model using full Bayesian approach. A new two-stage scale mixtures respresentation for the Student-t density is proposed and used to speed up the efficiency of the Markov chain monte Carlo sampling scheme

Addressing the interplay between apoptosis and glucose metabolism in liver cirrhosis and hcc

Introduction: Pro-inflammatory signalling in the liver promotes the appearance of a metabolic phenotype that involves the transition from mitochondrial respiration to aerobic glycolysis. It was demonstrated that this metabolic shift occurs during the transition from healthy and early stage of liver injury (NAFLD/NASH, ALD to late stage of disease (i.e. cirrhosis), and further escalates during HCC development.1,2This metabolic signature enables dividing cells to satisfy anabolic and energetic needs for biomass production and to suppress apoptotic signalling, which is consistent with increased compensatory hepatic cell proliferation typical of cirrhotic and HCC livers. However other studies in contrast have suggested that hepatocytes are unable to sustain glycolysis during late stage of chronic liver disease.3 Method: We used unbiased gene expression analyses of microarray datasets to investigate the expression of glycolytic genes in cirrhotic and HCC livers and correlated their expression with patient outcome. Furthermore, by using a combination of in vitro and in vivo analyses we have characterised the abilities of a novel anti-apoptotic gene to regulate aerobic glycolysis in liver cirrhosis and HCC. Results: mRNA profiling showed significantly higher expression of glycolytic transcripts in cirrhotic and HCC livers compared to normal quiescent livers (P < 0.05). Up regulation of Glut1, Hk1, Hk2, G6PI, and PFKLwas seen in HCC livers compared to their adjacent non-tumour tissues (P < 0.001). Notably, expression of enzymes regulating mitochondrial activity (Pdha, Pdk) was unchanged between non-tumour tissues and late stage of HCC. Moreover, up regulation of a novel anti-apoptotic gene positively correlated with increased expression of glycolytic transcripts in a group of cirrhotic patients prospectively classified as poor prognosis based on HCC development, and promotes the aerobic glycolysis of hepatoma cells. Conclusion: In summary, our findings delineate a putative link between aerobic glycolysis and suppression of apoptosis that is an important part of the progression of cirrhosis to HCC. The identification of the mechanism regulating this link may lead to design new therapeutic strategies for human liver disease

Strange nonchaotic attractors in noise driven systems

Strange nonchaotic attractors (SNAs) in noise driven systems are investigated. Before the transition to chaos, due to the effect of noise, a typical trajectory will wander between the periodic attractor and its nearby chaotic saddle in an intermittent way, forms a strange attractor gradually. The existence of SNAs is confirmed by simulation results of various critera both in map and continuous systems. Dimension transition is found and intermittent behavior is studied by peoperties of local Lyapunov exponent. The universality and generalization of this kind of SNAs are discussed and common features are concluded

Optical and electrical properties of efficiency enhanced polymer solar cells with Au nanoparticles in a PEDOT-PSS layer

We unveil new device physics and provide details of device mechanisms by investigating polymer solar cells (PSCs) incorporating Au nanoparticles (NPs) into the hole collection poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) layer. Theoretical and experimental results show that the very strong near field around Au NPs due to Localized Surface Plasmonic Resonance (LSPR) mainly distributes laterally along the PEDOT:PSS layer rather than vertically into the adjacent active layer, leading to minimal enhancement of light absorption in the active layer. This finding can be extended to a typical class of solar cells incorporating metallic NPs in spacing layers adjacent to the active layer. With optical effects proven to be minor contributors to device performance improvements, we investigate the electrical properties of the PSCs and obtain insights into the detailed device mechanisms. Improvements in power conversion efficiency (PCE) of solar cells are found to originate from the enlarged active layer/PEDOT:PSS interfacial area and improved PEDOT:PSS conductivity. At high NP concentrations, reduced exciton quenching at donor/acceptor junctions is found to cause PCE deterioration. Our findings indicate that it is highly important to investigate both optical and electrical effects for understanding and optimizing PSC performances. © 2011 The Royal Society of Chemistry.postprin

High-sensitivity troponin I concentrations are a marker of an advanced hypertrophic response and adverse outcomes in patients with aortic stenosis

Aims: High-sensitivity cardiac troponin I (cTnI) assays hold promise in detecting the transition from hypertrophy to heart failure in aortic stenosis. We sought to investigate the mechanism for troponin release in patients with aortic stenosis and whether plasma cTnI concentrations are associated with long-term outcome. Methods and results: Plasma cTnI concentrations were measured in two patient cohorts using a high-sensitivity assay. First, in the Mechanism Cohort, 122 patients with aortic stenosis (median age 71, 67% male, aortic valve area 1.0 ± 0.4 cm2) underwent cardiovascular magnetic resonance and echocardiography to assess left ventricular (LV) myocardial mass, function, and fibrosis. The indexed LV mass and measures of replacement fibrosis (late gadolinium enhancement) were associated with cTnI concentrations independent of age, sex, coronary artery disease, aortic stenosis severity, and diastolic function. In the separate Outcome Cohort, 131 patients originally recruited into the Scottish Aortic Stenosis and Lipid Lowering Trial, Impact of REgression (SALTIRE) study, had long-term follow-up for the occurrence of aortic valve replacement (AVR) and cardiovascular deaths. Over a median follow-up of 10.6 years (1178 patient-years), 24 patients died from a cardiovascular cause and 60 patients had an AVR. Plasma cTnI concentrations were associated with AVR or cardiovascular death HR 1.77 (95% CI, 1.22 to 2.55) independent of age, sex, systolic ejection fraction, and aortic stenosis severity. Conclusions: In patients with aortic stenosis, plasma cTnI concentration is associated with advanced hypertrophy and replacement myocardial fibrosis as well as AVR or cardiovascular death