Large potential steps at weakly interacting metal-insulator interfaces

Potential steps exceeding 1 eV are regularly formed at metal|insulator interfaces, even when the interaction between the materials at the interface is weak physisorption. From first-principles calculations on metal|h-BN interfaces we show that these potential steps are only indirectly sensitive to the interface bonding through the dependence of the binding energy curves on the van der Waals interaction. Exchange repulsion forms the main contribution to the interface potential step in the weakly interacting regime, which we show with a simple model based upon a symmetrized product of metal and h-BN wave functions. In the strongly interacting regime, the interface potential step is reduced by chemical bonding

Wild clocks: preface and glossary

No abstract available

Band gaps in incommensurable graphene on hexagonal boron nitride

Devising ways of opening a band gap in graphene to make charge-carrier masses finite is essential for many applications. Recent experiments with graphene on hexagonal boron nitride (h-BN) offer tantalizing hints that the weak interaction with the substrate is sufficient to open a gap, in contradiction of earlier findings. Using many-body perturbation theory, we find that the small observed gap is what remains after a much larger underlying quasiparticle gap is suppressed by incommensurability. The sensitivity of this suppression to a small modulation of the distance separating graphene from the substrate suggests ways of exposing the larger underlying gap

Exploring two methods of usability testing: concurrent versus retrospective think-aloud protocols

Think-aloud protocols are commonly used for the usability testing of instructional documents, Web sites and interfaces. This paper addresses the benefits and drawbacks of two think-aloud variations: the traditional concurrent think-aloud method and the less familiar retrospective think-aloud protocols. It also offers an outline of a long-term research project designed to empirically investigate the value of both variants. The results of a first comparative study indicate that, although the two methods have distinct differences, they do seem to produce a similar outcome. A more detailed description of the results will be offered during the presentation

Analyzing the interaction between facilitator and participants in two variants of the think-aloud method.

This paper focuses on the interaction between test participants and test facilitator in two variants of the think-aloud method. In a first, explorative study, we analyzed think-aloud transcripts from two usability tests: a concurrent think-aloud test and a constructive interaction test. The results of our analysis show that while the participants in both studies never explicitly addressed the facilitator, the think-aloud participants showed more signs of awareness of the facilitator than the participants in the constructive interaction test. This finding may have practical implications for the validity of the two methods

Schottky barriers at hexagonal boron nitride/metal interfaces: a first principles study

The formation of a Schottky barrier at the interface between a metal and hexagonal boron nitride (h-BN) is studied using density functional theory. For metals whose work functions range from 4.2 to 6.0 eV, we find Schottky barrier heights for holes between 1.2 and 2.3 eV. A central role in determining the Schottky barrier height is played by a potential step of between 0.4 and 1.8 eV that is formed at the metal|h-BN interface and effectively lowers the metal work function. If h-BN is physisorbed, as is the case on fcc Cu, Al, Au, Ag and Pt(111) substrates, the interface potential step is described well by a universal function that depends only on the distance separating h-BN from the metal surface. The interface potential step is largest when h-BN is chemisorbed, which is the case for hcp Co and Ti (0001) and for fcc Ni and Pd (111) substrates

A hybrid version of swan for fast and efficient practical wave modelling

In the Netherlands, for coastal and inland water applications, wave modelling with SWAN has become a main ingredient. However, computational times are relatively high. Therefore we investigated the parallel efficiency of the current MPI and OpenMP versions of SWAN. The MPI version is not that efficient as the OpenMP version within a single node. Therefore, in this paper we propose a hybrid version of SWAN. It combines the efficiency of the current OpenMP version on shared memory with the capability of the current MPI version to distribute memory over nodes. We describe the numerical algorithm. With numerical experiments for important applications we show the potential of this hybrid version, We further optimize the approach and illustrate the behavior for larger number of nodes. Parallel I/O will be subject of future research

A hybrid SWAN version for fast and efficient practical wave modelling

In the Netherlands, for coastal and inland water applications, wave modelling with SWAN has become a main ingredient. However, computational times are relatively high. Therefore we investigated the parallel efficiency of the current MPI and OpenMP versions of SWAN. The MPI version is not that efficient as the OpenMP version within a single node. Therefore, in this paper we propose a hybrid version of SWAN. It combines the efficiency of the current OpenMP version on shared memory with the capability of the current MPI version to distribute memory over nodes. We describe the numerical algorithm. With initial numerical experiments we show the potential of this hybrid version. Parallel I/O, further optimization, and behavior for larger number of nodes will be subject of future research

Real time automatic scene classification

This work has been done as part of the EU VICAR (IST) project and the EU SCOFI project (IAP). The aim of the first project was to develop a real time video indexing classification annotation and retrieval system. For our systems, we have adapted the approach of Picard and Minka [3], who categorized elements of a scene automatically with so-called ’stuff’ categories (e.g., grass, sky, sand, stone). Campbell et al. [1] use similar concepts to describe certain parts of an image, which they named “labeled image regions”. However, they did not use these elements to classify the topic of the scene. Subsequently, we developed a generic approach for the recognition of visual scenes, where an alphabet of basic visual elements (or “typed patches”) is used to classify the topic of a scene. We define a new image element: a patch, which is a group of adjacent pixels within an image, described by a specific local pixel distribution, brightness, and color. In contrast with pixels, a patch as a whole can incorporate semantics. A patch is described by a HSI color histogram with 16 bins and by three texture features (i.e., the variance and two values based on the two eigen values of the covariance matrix of the Intensity values of a mask ran over the image. For more details on the features used we refer to Israel et al. [2]. We aimed at describing each image as a vector with a fixed size and with information about the position of patches that is not strict (strict position would limit generalization). Therefore, a fixed grid is placed over the image and each grid cell is segmented into patches, which are then categorized by a patch classifier. For each grid cell a frequency vector of its classified patches is calculated. These vectors are concate- nated. The resulting vector describes the complete image. Several grids were applied and several patch sizes with the grid cells were tested. Grid size of 3x2 combined with patches of size 16x16 provided the best system performance. For the two classification phases of our system, back-propagation networks were trained: (i) classification of the patches and (ii) classification of the image vector, as a whole. The system was tested on the classification of eight categories of scenes from the Corel database: interiors, city/street, forest, agriculture/countryside, desert, sea, portrait, and crowds. Each of these categories were relevant for the VICAR project. Based upon their relevance for these eight categories of scenes, we choose nine categories for the classification of the patches: building, crowd, grass, road, sand, skin, sky, tree, and water. This approach was found to be successful (for classification of the patches 87.5% correct, and classification of the scenes 73.8% correct). An advantage of our method is its low computational complexity. Moreover, the classified patches themselves are intermediate image representations and can be used for image classification, image segmentation as well as for image matching. A disadvantage is that the patches with which the classifiers were trained had to be manually classified. To solve this drawback, we currently develop algorithms for automatic extraction of relevant patch types. Within the IST project VICAR, a video indexing system was built for the Netherlands Institute for Sound and Vision1, consisting of four independent mod- ules: car recognition, face recognition, movement recognition (of people) and scene recognition. The latter module was based upon the afore mentioned approach. Within the IAP project SCOFI, a real time Internet pornography filter was built, based upon this approach. The system is currently running on several schools in Europe. Within the SCOFI filtering system, our image classification system (with a performance of 92% correct) works together with a text classi- fication system that includes a proxy server (FilterX, developed by Demokritos, Greece) to classify web-pages. Its total performance is 0% overblocking and 1% underblocking

Required Evidence for Clinical Applications of Liquid Biopsy Using Especially CTCs in Lung Cancer

As therapies have become more and more dependent on tumor as well as patient characteristics, obtaining tumor material has become of great importance. Liquid biopsies hold much potential as shown by a large amount of evidence across several studies. Clinical applications for circulating tumor cells (CTCs) are unfortunately still lacking. In part this is due to a lack of studies comparing liquid biopsies to conventional diagnostics and response measurements as well as studies showing that liquid biopsies can be used to switch therapies leading to improved outcomes. However, liquid biopsies using ctDNA for specific markers such as EGFR, ALK, ROS1 or RET have clinical applications because specific drugs are available