MD and SCA simulations of He and H bombardment of fuzz in bcc elements

We present results of MD simulations of low energy He ion bombardment of low density fuzz in bcc elements. He ions can penetrate several micrometers into sparse fuzz, which allows for a sufficient He flux through it to grow the fuzz further. He kinetic energy falls off exponentially with penetration depth. A BCA code was used to carry out the same ion bombardment on the same fuzz structures as in MD simulations, but with simpler, 10 million times faster calculations. Despite the poor theoretical basis of the BCA at low ion energies, and the use of somewhat different potentials in MD and BCA calculations, the ion penetration depths predicted by BCA are only similar to 12% less than those predicted by MD. The MD-BCA differences are highly systematic and trends in the results of the two methods are very similar. We have carried out more than 200 BCA calculation runs of ion bombardment of fuzz, in which parameters in the ion bombardment process were varied. For most parameters, the results show that the ion bombardment process is quite generic. The ion species (He or H), ion mass, fuzz element (W, Ta, Mo, Fe) and fuzz element lattice parameter turned out to have a modest influence on ion penetration depths at most. An off-normal angle of incidence strongly reduces the ion penetration depth. Increasing the ion energy increases the ion penetration, but the rate by which ion energy drops off at high ion energies follows the same exponential pattern as at lower energies. (C) 2017 Elsevier B.V. All rights reserved.Peer reviewe

MD and SCA simulations of He and H bombardment of fuzz in bcc elements

We present results of MD simulations of low energy He ion bombardment of low density fuzz in bcc elements. He ions can penetrate several micrometers into sparse fuzz, which allows for a sufficient He flux through it to grow the fuzz further. He kinetic energy falls off exponentially with penetration depth. A BCA code was used to carry out the same ion bombardment on the same fuzz structures as in MD simulations, but with simpler, 10 million times faster calculations. Despite the poor theoretical basis of the BCA at low ion energies, and the use of somewhat different potentials in MD and BCA calculations, the ion penetration depths predicted by BCA are only similar to 12% less than those predicted by MD. The MD-BCA differences are highly systematic and trends in the results of the two methods are very similar. We have carried out more than 200 BCA calculation runs of ion bombardment of fuzz, in which parameters in the ion bombardment process were varied. For most parameters, the results show that the ion bombardment process is quite generic. The ion species (He or H), ion mass, fuzz element (W, Ta, Mo, Fe) and fuzz element lattice parameter turned out to have a modest influence on ion penetration depths at most. An off-normal angle of incidence strongly reduces the ion penetration depth. Increasing the ion energy increases the ion penetration, but the rate by which ion energy drops off at high ion energies follows the same exponential pattern as at lower energies. (C) 2017 Elsevier B.V. All rights reserved.Peer reviewe

Congenital Prosopagnosia: Multistage Anatomical and Functional Deficits in Face Processing Circuitry

Face recognition is a primary social skill which depends on a distributed neural network. A pronounced face recognition deficit in the absence of any lesion is seen in congenital prosopagnosia. This study investigating 24 congenital prosopagnosic subjects and 25 control subjects aims at elucidating its neural basis with fMRI and voxel-based morphometry. We found a comprehensive behavioral pattern, an impairment in visual recognition for faces and buildings that spared long-term memory for faces with negative valence. Anatomical analysis revealed diminished gray matter density in the bilateral lingual gyrus, the right middle temporal gyrus, and the dorsolateral prefrontal cortex. In most of these areas, gray matter density correlated with memory success. Decreased functional activation was found in the left fusiform gyrus, a crucial area for face processing, and in the dorsolateral prefrontal cortex, whereas activation of the medial prefrontal cortex was enhanced. Hence, our data lend strength to the hypothesis that congenital prosopagnosia is explained by network dysfunction and suggest that anatomic curtailing of visual processing in the lingual gyrus plays a substantial role. The dysfunctional circuitry further encompasses the fusiform gyrus and the dorsolateral prefrontal cortex, which may contribute to their difficulties in long-term memory for complex visual information. Despite their deficits in face identity recognition, processing of emotion related information is preserved and possibly mediated by the medial prefrontal cortex. Congenital prosopagnosia may, therefore, be a blueprint of differential curtailing in networks of visual cognition

A Current Induced Transition in atomic-sized contacts of metallic Alloys

We have measured conductance histograms of atomic point contacts made from the noble-transition metal alloys CuNi, AgPd, and AuPt for a concentration ratio of 1:1. For all alloys these histograms at low bias voltage (below 300 mV) resemble those of the noble metals whereas at high bias (above 300 mV) they resemble those of the transition metals. We interpret this effect as a change in the composition of the point contact with bias voltage. We discuss possible explanations in terms of electromigration and differential diffusion induced by current heating.Comment: 5 pages, 6 figure

Towards Transparent Linguistic Analysis of Dutch Newspaper Article Genres using Machine Learning

Systematic study of genre in newspapers sheds light on the development of journalism discourse. The genre conventions that can be discerned in a newspaper text signal the underlying discursive norms and practices of journalism as a profession. Historical newspapers are increasingly becoming available thanks to digital newspaper archives (in the Netherlands available through Delpher.nl), providing the opportunity for large-scale empirical research. However, the digital archives do not contain fine-grained genre information that is required for this purpose. Therefore, we use machine learning to automatically assign genre labels to newspaper articles.Machine learning facilitates substantial improvements to the outcomes of existing research by providing increased amounts of enriched data. However, the decision-making process of the machine learning pipeline needs to be verified. Our previous findings (Bilgin et al., 2018) show that accuracy scores alone are not enough to assess the performance of these pipelines and that making an informed choice not only empowers optimal study of the historical development of genre, but also increases the trustworthiness of the results. This work shows that employing a transparent approach driven by model interpretability facilitates fair comparison as well as validation of the underlying decision-making criteria of the machine learning pipelines. The criteria are presented in the form of important features, creating insights on interactions between genre-related linguistic features and bag-of-words features.</p