4,648 research outputs found
Microsatellites reveal genetic differentiation among populations in an insect species with high genetic variability in dispersal, the codling moth, Cydia pomonella (L.) (Lepidoptera: Tortricidae)
Little is known about genetic differentiation and gene flow in populations of insect species that have a high genetic variability in dispersal but lack morphologically visible morphs that disperse. These characteristics apply to the codling moth, Cydia pomonella L. (Lepidoptera: Tortricidae), a major pest of fruits and nuts. Larvae were collected from three orchards each of pome fruits, stone fruits and nut trees in a major fruit growing area of Switzerland (Valais) and from six further (mainly apple) orchards throughout this country. Nine microsatellite loci were used to investigate genetic differentiation and the amount of gene flow among the sampled populations. All the loci were shown to be polymorphic in all populations. The number of alleles ranged from five to 15 over nine loci for the 15 populations. Significant genetic differentiation was noted among the populations from apple, apricot and walnut in the Valais region. Furthermore, among the eight populations sampled from apple in different geographic regions throughout Switzerland, AMOVA and pairwise FST analysis revealed significant population genetic differentiation even between populations collected from orchards 10 km apart. These results indicate that a distinct prevailing characteristic, in the present case the sedentary behaviour of the moth, can shape population architectur
Influence of Course Design on Learning Approaches and Academic Performance in Physical Therapy Students
AbstractThis study investigated (1) changes in learning approaches and academic performance between courses designed according to lecture-based learning or problem-based learning, (2) the relationship between academic performance and learning approaches. 32 students participated in this study. Studentsâ learning approaches were ascertained by the Approaches and Study Skills Inventory for Students. Summative results from each course indicated academic performance. The results showed that approximately 50% of students changed their learning approaches for different course designs. Furthermore, choice of learning approach influenced academic performance in a course designed according to problem-based learning but not in one designed according to lecture-based learning
Combined CI+MBPT calculations of energy levels and transition amplitudes in Be, Mg, Ca, and Sr
Configuration interaction (CI) calculations in atoms with two valence
electrons, carried out in the V(N-2) Hartree-Fock potential of the core, are
corrected for core-valence interactions using many-body perturbation theory
(MBPT). Two variants of the mixed CI+MBPT theory are described and applied to
obtain energy levels and transition amplitudes for Be, Mg, Ca, and Sr
Generation and Evolution of Spin Entanglement in NRQED
A complete analysis on the generation of spin entanglement from NRQED is
presented. The results of entanglement are obtained with relativistic
correction to the leading order of (v/c)^2. It is shown that to this order the
degree of entanglement of a singlet state does not change under time evolution
whereas the triplet state can change.Comment: 8 pages, 1 figure, to appear in Phys. Rev.
Structural and molecular basis of the assembly of the TRPP2/PKD1 complex
Mutations in PKD1 and TRPP2 account for nearly all cases of autosomal dominant polycystic kidney disease (ADPKD). These 2 proteins form a receptor/ion channel complex on the cell surface. Using a combination of biochemistry, crystallography, and a single-molecule method to determine the subunit composition of proteins in the plasma membrane of live cells, we find that this complex contains 3 TRPP2 and 1 PKD1. A newly identified coiled-coil domain in the C terminus of TRPP2 is critical for the formation of this complex. This coiled-coil domain forms a homotrimer, in both solution and crystal structure, and binds to a single coiled-coil domain in the C terminus of PKD1. Mutations that disrupt the TRPP2 coiled-coil domain trimer abolish the assembly of both the full-length TRPP2 trimer and the TRPP2/PKD1 complex and diminish the surface expression of both proteins. These results have significant implications for the assembly, regulation, and function of the TRPP2/PKD1 complex and the pathogenic mechanism of some ADPKD-producing mutations
Bayesian Assessment of Dynamic Quantile Forecasts
Methods for Bayesian testing and assessment of dynamic quantile forecasts are proposed. Specifically, Bayes factor analogues of popular frequentist tests for independence of violations from, and for correct coverage of a time series of, quantile forecasts are developed. To evaluate the relevant marginal likelihoods involved, analytic integration methods are utilised when possible, otherwise multivariate adaptive quadrature methods are employed to estimate the required quantities. The usual Bayesian interval estimate for a proportion is also examined in this context. The size and power properties of the proposed methods are examined via a simulation study, illustrating favourable comparisons both overall and with their frequentist counterparts. An empirical study employs the proposed methods, in comparison with standard tests, to assess the adequacy of a range of forecasting models for Value at Risk (VaR) in several financial market data series
Coupling of thermal and mass diffusion in regular binary thermal lattice-gases
We have constructed a regular binary thermal lattice-gas in which the thermal
diffusion and mass diffusion are coupled and form two nonpropagating diffusive
modes. The power spectrum is shown to be similar in structure as for the one in
real fluids, in which the central peak becomes a combination of coupled entropy
and concentration contributions. Our theoretical findings for the power spectra
are confirmed by computer simulations performed on this model.Comment: 5 pages including 3 figures in RevTex
Derivation of the cubic NLS and Gross-Pitaevskii hierarchy from manybody dynamics in based on spacetime norms
We derive the defocusing cubic Gross-Pitaevskii (GP) hierarchy in dimension
, from an -body Schr\"{o}dinger equation describing a gas of
interacting bosons in the GP scaling, in the limit . The
main result of this paper is the proof of convergence of the corresponding
BBGKY hierarchy to a GP hierarchy in the spaces introduced in our previous work
on the well-posedness of the Cauchy problem for GP hierarchies,
\cite{chpa2,chpa3,chpa4}, which are inspired by the solutions spaces based on
space-time norms introduced by Klainerman and Machedon in \cite{klma}. We note
that in , this has been a well-known open problem in the field. While our
results do not assume factorization of the solutions, consideration of
factorized solutions yields a new derivation of the cubic, defocusing nonlinear
Schr\"odinger equation (NLS) in .Comment: 44 pages, AMS Late
Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis
Value-at-Risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models are compared, including standard, threshold nonlinear and Markov switching GARCH specifications, plus standard and nonlinear stochastic volatility models, most considering four error probability distributions: Gaussian, Student-t, skewed-t and generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio of four Asia-Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global financial crisis. Results reveal that: (i) GARCH models out-performed stochastic volatility models in almost all cases; (ii) asymmetric volatility models were clearly favoured pre-crisis; while at the 1% level during and post-crisis, for a 1 day horizon, models with skewed-t errors ranked best, while IGARCH models were favoured at the 5% level; (iii) all models forecasted VaR less accurately and anti-conservatively post-crisi
Bayesian Forecasting for Financial Risk Management, Pre and Post the Global Financial Crisis
Value-at-Risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models are compared, including standard, threshold nonlinear and Markov switching GARCH specifications, plus standard and nonlinear stochastic volatility models, most considering four error probability distributions: Gaussian, Student-t, skewed-t and generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio of four Asia-Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global financial crisis. Results reveal that: (i) GARCH models out-performed stochastic volatility models in almost all cases; (ii) asymmetric volatility models were clearly favoured pre-crisis; while at the 1% level during and post-crisis, for a 1 day horizon, models with skewed-t errors ranked best, while IGARCH models were favoured at the 5% level; (iii) all models forecasted VaR less accurately and anti-conservatively post-crisi
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