Preparation and spectroscopy of a metastable Mott insulator state with attractive interactions

We prepare and study a metastable attractive Mott insulator state formed with bosonic atoms in a three-dimensional optical lattice. Starting from a Mott insulator with Cs atoms at weak repulsive interactions, we use a magnetic Feshbach resonance to tune the interactions to large attractive values and produce a metastable state pinned by attractive interactions with a lifetime on the order of 10 seconds. We probe the (de-)excitation spectrum via lattice modulation spectroscopy, measuring the interaction dependence of two- and three-body bound state energies. As a result of increased on-site three-body loss we observe resonance broadening and suppression of tunneling processes that produce three-body occupation.Comment: 7 pages, 6 figure

MD simulation study on defect evolution and doping efficiency of p-type doping of 3C-SiC by Al ion implantation with subsequent annealing

We use molecular dynamics (MD) simulation with numerical characterisation and statistical analysis to study the mechanisms of damage evolution and p-type doping efficiency by aluminum (Al) ion implantation into 3C silicon carbide (SiC) with subsequent annealing. By incorporating the electronic stopping power for implantation, a more accurate description of the atomic-scale mechanisms of damage evolution and distribution in SiC can be obtained. The simulation results show a novel observation that the recrystallization process occurs in the region below the subsurface layer, and develops from amorphous-crystalline interface to the damage center region, which is a new insight into previously published studies. During surface recrystallization, significant compressive stress concentration occurs, and more structural phase transition atoms and dislocations formed at the damage-rich-crystalline interface. Another point of interest is that for low-dose implantation, more implantation-induced defects hamper the doping efficiency. Correspondingly, the correlation between lattice damage and doping efficiency becomes weaker as the implant dose increases under the same annealing conditions. Our simulation also predicts that annealing after high temperature (HT) implantation is more likely to lead to the formation of carbon vacancies (V-C).Peer reviewe

Neuroretinal hypoxic signaling in a new preclinical murine model for proliferative diabetic retinopathy

Diabetic retinopathy (DR) affects approximately one-third of diabetic patients and, if left untreated, progresses to proliferative DR (PDR) with associated vitreous hemorrhage, retinal detachment, iris neovascularization, glaucoma and irreversible blindness. In vitreous samples of human patients with PDR, we found elevated levels of hypoxia inducible factor 1 alpha (HIF1α). HIFs are transcription factors that promote hypoxia adaptation and have important functional roles in a wide range of ischemic and inflammatory diseases. To recreate the human PDR phenotype for a preclinical animal model, we generated a mouse with neuroretinal-specific loss of the von Hippel Lindau tumor suppressor protein, a protein that targets HIF1α for ubiquitination. We found that the neuroretinal cells in these mice overexpressed HIF1α and developed severe, irreversible ischemic retinopathy that has features of human PDR. Rapid progression of retinopathy in these mutant mice should facilitate the evaluation of therapeutic agents for ischemic and inflammatory blinding disorders. In addition, this model system can be used to manipulate the modulation of the hypoxia signaling pathways, for the treatment of non-ocular ischemic and inflammatory disorders

Pediatric radius torus fractures in x-rays—how computer vision could render lateral projections obsolete

It is an indisputable dogma in extremity radiography to acquire x-ray studies in at least two complementary projections, which is also true for distal radius fractures in children. However, there is cautious hope that computer vision could enable breaking with this tradition in minor injuries, clinically lacking malalignment. We trained three different state-of-the-art convolutional neural networks (CNNs) on a dataset of 2,474 images: 1,237 images were posteroanterior (PA) pediatric wrist radiographs containing isolated distal radius torus fractures, and 1,237 images were normal controls without fractures. The task was to classify images into fractured and non-fractured. In total, 200 previously unseen images (100 per class) served as test set. CNN predictions reached area under the curves (AUCs) up to 98% [95% confidence interval (CI) 96.6%–99.5%], consistently exceeding human expert ratings (mean AUC 93.5%, 95% CI 89.9%–97.2%). Following training on larger data sets CNNs might be able to effectively rule out the presence of a distal radius fracture, enabling to consider foregoing the yet inevitable lateral projection in children. Built into the radiography workflow, such an algorithm could contribute to radiation hygiene and patient comfort

On the Observable Behaviour of Composite Components

AbstractThe crucial strength of the component paradigm lies in the possibility to encapsulate behaviours. In this work, we focus on the observable behaviour of composite components which encapsulate the behaviour of (possibly large) assemblies of connected subcomponents. We first present our general component model which is equipped with a precise formal semantics allowing us to distinguish systematically different kinds of behaviours for ports, for components, and for component assemblies; technically we use UML2 notation for describing component structures and I/O-transition systems for behaviours. Then we investigate an efficient method for the computation of the observable behaviour of composite components which can circumvent the possibly infeasible intermediate computation of the usually complex behaviour of underlying assemblies if there are behaviourally neutral subcomponents. Finally, we utilise the fact that components are connected via ports such that checks for behavioural neutrality of components can be reduced to checks for behavioural neutrality of connected ports in the case of weakly deterministic port behaviours

Ab Initio Study of the Combined Effects of Alloying Elements and H on Grain Boundary Cohesion in Ferritic Steels

Hydrogen enhanced decohesion is expected to play a major role in ferritic steels, especially at grain boundaries. Here, we address the effects of some common alloying elements C, V, Cr, and Mn on the H segregation behaviour and the decohesion mechanism at a Σ 5 ( 310 ) [ 001 ] 36.9 ∘ grain boundary in bcc Fe using spin polarized density functional theory calculations. We find that V, Cr, and Mn enhance grain boundary cohesion. Furthermore, all elements have an influence on the segregation energies of the interstitial elements as well as on these elements’ impact on grain boundary cohesion. V slightly promotes segregation of the cohesion enhancing element C. However, none of the elements increase the cohesion enhancing effect of C and reduce the detrimental effect of H on interfacial cohesion at the same time. At an interface which is co-segregated with C, H, and a substitutional element, C and H show only weak interaction, and the highest work of separation is obtained when the substitute is Mn