Impact of the European Clinical Trials Directive on prospective academic clinical trials associated with BMT

The European Clinical Trials Directive (EU 2001; 2001/20/EC) was introduced to improve the efficiency of commercial and academic clinical trials. Concerns have been raised by interested organizations and institutions regarding the potential for negative impact of the Directive on non-commercial European clinical research. Interested researchers within the European Group for Blood and Marrow Transplantation (EBMT) were surveyed to determine whether researcher experiences confirmed this view. Following a pilot study, an internet-based questionnaire was distributed to individuals in key research positions in the European haemopoietic SCT community. Seventy-one usable questionnaires were returned from participants in different EU member states. The results indicate that the perceived impact of the European Clinical Trials Directive has been negative, at least in the research areas of interest to the EBMT

Going beyond Visualization. Verbalization as Complementary Medium to Explain Machine Learning Models

In this position paper, we argue that a combination of visualization and verbalization techniques is beneficial for creating broad and versatile insights into the structure and decision-making processes of machine learning models. Explainability of machine learning models is emerging as an important area of research. Hence, insights into the inner workings of a trained model allow users and analysts, alike, to understand the models, develop justifications, and gain trust in the systems they inform. Explanations can be generated through different types of media, such as visualization and verbalization. Both are powerful tools that enable model interpretability. However, while their combination is arguably more powerful than each medium separately, they are currently applied and researched independently. To support our position that the combination of the two techniques is beneficial to explain machine learning models, we describe the design space of such a combination and discuss arising research questions, gaps, and opportunities

Bring it to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis

Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach

Combination Forecasts of Bond and Stock Returns: An Asset Allocation Perspective

We investigate the out-of-sample forecasting ability of the HML, SMB, momentum, short-term and long-term reversal factors along with their size and value decompositions on U.S. bond and stock returns for a variety of horizons ranging from the short run (1 month) to the long run (2 years). Our findings suggest that these factors contain significantly more information for future bond and stock market returns than the typically employed financial variables. Combination of forecasts of the empirical factors turns out to be particularly successful, especially from an an asset allocation perspective. Similar findings pertain to the European and Japanese markets

Quantifying Stock Price Response to Demand Fluctuations

We address the question of how stock prices respond to changes in demand. We quantify the relations between price change $G$ over a time interval $\Delta t$ and two different measures of demand fluctuations: (a) $\Phi$, defined as the difference between the number of buyer-initiated and seller-initiated trades, and (b) $\Omega$, defined as the difference in number of shares traded in buyer and seller initiated trades. We find that the conditional expectations $<G >_{\Omega}$ and $_{\Phi}$ of price change for a given $\Omega$ or $\Phi$ are both concave. We find that large price fluctuations occur when demand is very small --- a fact which is reminiscent of large fluctuations that occur at critical points in spin systems, where the divergent nature of the response function leads to large fluctuations.Comment: 4 pages (multicol fomat, revtex

A Dirac-Hartree-Bogoliubov approximation for finite nuclei

We develop a complete Dirac-Hartree-Fock-Bogoliubov approximation to the ground state wave function and energy of finite nuclei. We apply it to spin-zero proton-proton and neutron-neutron pairing within the Dirac-Hartree-Bogoliubov approximation (we neglect the Fock term), using a zero-range approximation to the relativistic pairing tensor. We study the effects of the pairing on the properties of the even-even nuclei of the isotopic chains of Ca, Ni and Sn (spherical) and Kr and Sr (deformed), as well as the $N$=28 isotonic chain, and compare our results with experimental data and with other recent calculations.Comment: 43 pages, RevTex, 13 figure

First results of the air shower experiment KASCADE

The main goals of the KASCADE (KArlsruhe Shower Core and Array DEtector) experiment are the determination of the energy spectrum and elemental composition of the charged cosmic rays in the energy range around the knee at ca. 5 PeV. Due to the large number of measured observables per single shower a variety of different approaches are applied to the data, preferably on an event-by-event basis. First results are presented and the influence of the high-energy interaction models underlying the analyses is discussed.Comment: 3 pages, 3 figures included, to appear in the TAUP 99 Proceedings, Nucl. Phys. B (Proc. Suppl.), ed. by M. Froissart, J. Dumarchez and D. Vignau

Evaluation of two interaction techniques for visualization of dynamic graphs

Several techniques for visualization of dynamic graphs are based on different spatial arrangements of a temporal sequence of node-link diagrams. Many studies in the literature have investigated the importance of maintaining the user's mental map across this temporal sequence, but usually each layout is considered as a static graph drawing and the effect of user interaction is disregarded. We conducted a task-based controlled experiment to assess the effectiveness of two basic interaction techniques: the adjustment of the layout stability and the highlighting of adjacent nodes and edges. We found that generally both interaction techniques increase accuracy, sometimes at the cost of longer completion times, and that the highlighting outclasses the stability adjustment for many tasks except the most complex ones.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

Transmission of Methicillin‐Resistant Staphylococcus aureus Infection Through Solid Organ Transplantation: Confirmation Via Whole Genome Sequencing

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109324/1/ajt12898.pd