1,314 research outputs found
Modelling of Pyroelectric Response in Inhomogeneous Ferroelectric-Semiconductor Films
We have modified Landau-Khalatnikov approach and shown that the pyroelectric
response of inhomogeneous ferroelectric-semiconductor films can be described by
using six coupled equations for six order parameters: average displacement, its
mean-square fluctuation and correlation with charge defects density
fluctuations, average pyroelectric coefficient, its fluctuation and correlation
with charge defects density fluctuations. Coupled equations demonstrate the
inhomogeneous reversal of pyroelectric response in contrast to the equations of
Landau-Khalatnikov type, which describe the homogeneous reversal with the sharp
pyroelectric coefficient peak near the thermodynamic coercive field value.
Within the framework of our model pyroelectric hysteresis loop becomes much
smoother, thinner and lower as well as pyroelectric coefficient peaks near the
coercive field completely disappear under the increase of disordering caused by
defects. This effect is similar to the well-known "square to slim transition"
of the ferroelectric hysteresis loops in relaxor ferroelectrics. Also the
increase of defect concentration leads to the drastic decrease of the coercive
field typical for disordered ferroelectrics. Usually pyroelectric hysteresis
loops of doped and inhomogeneous ferroelectrics have typical smooth shape
without any pyroelectric coefficient peaks and coercive field values much lower
than the thermodynamic one. Therefore our approach qualitatively explains
available experimental results. Rather well quantitative agreement between our
modelling and typical Pb(Zr,Ti)O3-film pyroelectric and ferroelectric loops has
been obtained.Comment: 14 pages, 5 figure
Consumer preferences for teledermoscopy screening to detect melanoma early
Introduction: ‘Store and forward’ teledermoscopy is a technology with potential advantages for melanoma screening. Any large-scale implementation of this technology is dependent on consumer acceptance. Aim: To investigate preferences for melanoma screening options compared with skin self-examination in adults considered to be at increased risk of developing skin cancer. Methods: A discrete choice experiment was completed by 35 consumers, all of whom had prior experience with the use of teledermoscopy, in Queensland, Australia. Participants made 12 choices between screening alternatives described by seven attributes including monetary cost. A mixed logit model was used to estimate the relative weights that consumers place on different aspects of screening, along with the marginal willingness to pay for teledermoscopy as opposed to screening at a clinic. Results: Overall, participants preferred screening/diagnosis by a health professional rather than skin self-examination. Key drivers of screening choice were for results to be reviewed by a dermatologist; a higher detection rate; fewer non-cancerous moles being removed in relation to every skin cancer detected; and less time spent away from usual activities. On average, participants were willing to pay AUD110 to have teledermoscopy with dermatologist review available to them as a screening option. Discussion and conclusions: Consumers preferentially value aspects of care that are more feasible with a teledermoscopy screening model, as compared with other skin cancer screening and diagnosis options. This study adds to previous literature in the area which has relied on the use of consumer satisfaction scales to assess the acceptability of teledermoscopy
Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels
This is the final version of the article. Available from Public Library of Science via the DOI in this record.Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.This work was funded by the UK Engineering and Physical Sciences Research Council, grant number EP/I017445/1
Progressive Neural Networks
Learning to solve complex sequences of tasks--while both leveraging transfer
and avoiding catastrophic forgetting--remains a key obstacle to achieving
human-level intelligence. The progressive networks approach represents a step
forward in this direction: they are immune to forgetting and can leverage prior
knowledge via lateral connections to previously learned features. We evaluate
this architecture extensively on a wide variety of reinforcement learning tasks
(Atari and 3D maze games), and show that it outperforms common baselines based
on pretraining and finetuning. Using a novel sensitivity measure, we
demonstrate that transfer occurs at both low-level sensory and high-level
control layers of the learned policy
Depicting a protein's two faces: GPCR classification by phylogenetic tree‐based HMMs
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/116379/1/feb2s0014579303011128.pd
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