Image Registration and Predictive Modeling: Learning the Metric on the Space of Diffeomorphisms

We present a method for metric optimization in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework, by treating the induced Riemannian metric on the space of diffeomorphisms as a kernel in a machine learning context. For simplicity, we choose the kernel Fischer Linear Discriminant Analysis (KLDA) as the framework. Optimizing the kernel parameters in an Expectation-Maximization framework, we define model fidelity via the hinge loss of the decision function. The resulting algorithm optimizes the parameters of the LDDMM norm-inducing differential operator as a solution to a group-wise registration and classification problem. In practice, this may lead to a biology-aware registration, focusing its attention on the predictive task at hand such as identifying the effects of disease. We first tested our algorithm on a synthetic dataset, showing that our parameter selection improves registration quality and classification accuracy. We then tested the algorithm on 3D subcortical shapes from the Schizophrenia cohort Schizconnect. Our Schizophrenia-Control predictive model showed significant improvement in ROC AUC compared to baseline parameters

Electron transport lifetimes in InSb/Al1-xInxSb quantum well 2DEGs

We report magnetotransport measurements of InSb/Al1-xInxSb modulation doped quantum well (QW) structures and the extracted transport ( ) tt and quantum (tq) lifetime of carriers at low temperature (<2K.) We consider conventional transport lifetimes over a range of samples with different doping levels and carrier densities, and deduce different transport regimes dependent on QW state filling calculated from self-consistent Schrödinger–Poisson modelling. For samples where only the lowest QW subband is occupied at electron densities of 2.13 10 ´ 11 cm−2 and 2.54 10 ´ 11 cm−2 quantum lifetimes of tq » 0.107 ps, and tq » 0.103 ps are extracted from Shubnikov–de Haas oscillations below a magnetic field of 0.8 T. The extracted ratios of transport to quantum lifetimes, t t t q » 17 and t t t q » 20 are similar to values reported in other binary QW two-dimensional electron gas systems, but are inconsistent with predictions from transport modelling which assumes that remote ionized donors are the dominant scattering mechanism. We find the low t t t q ratio and the variation in transport mobility with carrier density cannot be explained by reasonable levels of background impurities or well width fluctuations. Thus, there is at least one additional scattering mechanism unaccounted for, most likely arising from structural defects

The Stokes Phenomenon and Quantum Tunneling for de Sitter Radiation in Nonstationary Coordinates

We study quantum tunneling for the de Sitter radiation in the planar coordinates and global coordinates, which are nonstationary coordinates and describe the expanding geometry. Using the phase-integral approximation for the Hamilton-Jacobi action in the complex plane of time, we obtain the particle-production rate in both coordinates and derive the additional sinusoidal factor depending on the dimensionality of spacetime and the quantum number for spherical harmonics in the global coordinates. This approach resolves the factor of two problem in the tunneling method.Comment: LaTex 10 pages, no figur

The Subleading Term of the Strong Coupling Expansion of the Heavy-Quark Potential in a N=4\mathcal N=4 Super Yang-Mills Plasma

Applying the AdS/CFT correspondence, the expansion of the heavy-quark potential of the ${\cal N}$ supersymmetric Yang-Mills theory at large $N_c$ is carried out to the sub-leading term in the large 't Hooft coupling at nonzero temperatures. The strong coupling corresponds to the semi-classical expansion of the string-sigma model, the gravity dual of the Wilson loop operator, with the sub-leading term expressed in terms of functional determinants of fluctuations. The contributions of these determinants are evaluated numerically.Comment: 17 pages in JHEP3, typos fixed, updated version to be published in JHE

Finite-region stabilization via dynamic output feedback for 2-D Roesser models

Finite-region stability (FRS), a generalization of finite-time stability, has been used to analyze the transient behavior of discrete two-dimensional (2-D) systems. In this paper, we consider the problem of FRS for discrete 2-D Roesser models via dynamic output feedback. First, a sufficient condition is given to design the dynamic output feedback controller with a state feedback-observer structure, which ensures the closed-loop system FRS. Then, this condition is reducible to a condition that is solvable by linear matrix inequalities. Finally, viable experimental results are demonstrated by an illustrative example

Vitellogenin Underwent Subfunctionalization to Acquire Caste and Behavioral Specific Expression in the Harvester Ant Pogonomyrmex barbatus

PMCID: PMC3744404This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication

Microbial fuel cells: a green and alternative source for bioenergy production

Microbial fuel cell (MFC) represents one of the green technologies for the production of bioenergy. MFCs using microalgae produce bioenergy by converting solar energy into electrical energy as a function of metabolic and anabolic pathways of the cells. In the MFCs with bacteria, bioenergy is generated as a result of the organic substrate oxidation. MFCs have received high attention from researchers in the last years due to the simplicity of the process, the absence in toxic by-products, and low requirements for the algae growth. Many studies have been conducted on MFC and investigated the factors affecting the MFC performance. In the current chapter, the performance of MFC in producing bioenergy as well as the factors which influence the efficacy of MFCs is discussed. It appears that the main factors affecting MFC’s performance include bacterial and algae species, pH, temperature, salinity, substrate, mechanism of electron transfer in an anodic chamber, electrodes materials, surface area, and electron acceptor in a cathodic chamber. These factors are becoming more influential and might lead to overproduction of bioenergy when they are optimized using response surface methodology (RSM)

A psychophysical measurement on subjective well-being and air pollution

Although the physical effects of air pollution on humans are well documented, there may be even greater impacts on the emotional state and health. Surveys have traditionally been used to explore the impact of air pollution on people’s subjective well-being (SWB). However, the survey techniques usually take long periods to properly match the air pollution characteristics from monitoring stations to each respondent’s SWB at both disaggregated spatial and temporal levels. Here, we used air pollution data to simulate fixed-scene images and psychophysical process to examine the impact from only air pollution on SWB. Findings suggest that under the atmospheric conditions in Beijing, negative emotions occur when PM2.5 (particulate matter with a diameter less than 2.5 µm) increases to approximately 150 AQI (air quality index). The British observers have a stronger negative response under severe air pollution compared with Chinese observers. People from different social groups appear to have different sensitivities to SWB when air quality index exceeds approximately 200 AQI