Two-neutron transfer reaction mechanisms in 12^{12}C(6^6He,4^{4}He)14^{14}C using a realistic three-body 6^{6}He model

The reaction mechanisms of the two-neutron transfer reaction $^{12}$C($^6$He,$^4$He) have been studied at 30 MeV at the TRIUMF ISAC-II facility using the SHARC charged-particle detector array. Optical potential parameters have been extracted from the analysis of the elastic scattering angular distribution. The new potential has been applied to the study of the transfer angular distribution to the 2$^+_2$ 8.32 MeV state in $^{14}$C, using a realistic 3-body $^6$He model and advanced shell model calculations for the carbon structure, allowing to calculate the relative contributions of the simultaneous and sequential two-neutron transfer. The reaction model provides a good description of the 30 MeV data set and shows that the simultaneous process is the dominant transfer mechanism. Sensitivity tests of optical potential parameters show that the final results can be considerably affected by the choice of optical potentials. A reanalysis of data measured previously at 18 MeV however, is not as well described by the same reaction model, suggesting that one needs to include higher order effects in the reaction mechanism.Comment: 9 pages, 9 figure

Parents just don't understand: Parent-offspring conflict over mate choice

Previous research reveals that children and parents are not in complete agreement over which traits are most important for the mate of the child. Children tend to prefer traits that suggest genetic quality, whereas parents prefer characteristics that suggest high parental investment and cooperation with the ingroup. Using a sample of parents, mothers (n = 234) and fathers (n =240) the hypothesis was supported; parents perceived characteristics indicating a lack of genetic quality as being more unacceptable to the child, while characteristics indicating a lack of parental investment and cooperation with the ingroup were more unacceptable to themselves. Sex differences between mothers and fathers and sons and daughters were explored

Neonicotinoids thiamethoxam and clothianidin adversely affect the colonisation of invertebrate populations in aquatic microcosms

Surface waters are sometimes contaminated with neonicotinoids: a widespread, persistent, systemic class of insecticide with leaching potential. Previous ecotoxicological investigations of this chemical class in aquatic ecosystems have largely focused on the impacts of the neonicotinoid imidacloprid; few empirical, manipulative studies have investigated the effect on invertebrate abundances of two other neonicotinoids which are now more widely used: clothianidin and thiamethoxam. In this study, we employ a simple microcosm semi-field design, incorporating a one-off contamination event, to investigate the effect of these pesticides at field-realistic levels (ranging from 0 to 15 ppb) on invertebrate colonisation and survival in small ephemeral ponds. In line with previous research on neonicotinoid impacts on aquatic invertebrates, significant negative effects of both neonicotinoids were found. There were clear differences between the two chemicals, with thiamethoxam generally producing stronger negative effects than clothianidin. Populations of Chironomids (Diptera) and Ostracoda were negatively affected by both chemicals, while Culicidae appeared to be unaffected by clothianidin at the doses used. Our data demonstrate that field-realistic concentrations of neonicotinoids are likely to reduce populations of invertebrates found in ephemeral ponds, which may have knock on effects up the food chain. We highlight the importance of developing pesticide monitoring schemes for European surface waters

On the effects of recursive convolutional layers in convolutional neural networks

The Recursive Convolutional Layer (RCL) is a module that wraps a recursive feedback loop around a convolutional layer (CL). The RCL has been proposed to address some of the shortcomings of Convolutional Neural Networks (CNNs), as its unfolding increases the depth of a network without increasing the number of weights. We investigated the “naïve” substitution of CL with RCL on three base models: a 4-CL model, ResNet, DenseNet and their RCL-ized versions: C-FRPN, R-ResNet, and R-DenseNet using five image classification datasets. We find that this one-to-one replacement significantly improves the performances of the 4-CL model, but not those of ResNet or DenseNet. This led us to investigate the implication of the RCL substitution on the 4-CL model which reveals, among a number of properties, that RCLs are particularly efficient in shallow CNNs. We proceeded to re-visit the first set of experiments by gradually transforming the 4-CL model and the C-FRPN into respectively ResNet and R-ResNet, and find that the performance improvement is largely driven by the training regime whereas any depth increase negatively impacts the RCL-ized version. We conclude that the replacement of CLs by RCLs shows great potential in designing high-performance shallow CNNs

Clouds, circulation and climate sensitivity

Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks