160 research outputs found

    Donald Duck Holiday Game: A numerical analysis of a Game of the Goose role-playing variant

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    The 1996 Donald Duck Holiday Game is a role-playing variant of the historical Game of the Goose, involving characters with unique attributes, event squares, and random event cards. The objective of the game is to reach the camping before any other player does. We develop a Monte Carlo simulation model that automatically plays the game and enables analyzing its key characteristics. We assess the game on various metrics relevant to each playability. Numerical analysis shows that, on average, the game takes between 69 and 123 rounds to complete, depending on the number of players. However, durations over one hour (translated to human play time) occur over 25% of the games, which might reduce the quality of the gaming experience. Furthermore, we show that two characters are about 30% likely to win than the other three, primarily due to being exposed to fewer random events. We argue that the richer narrative of role-playing games may extend the duration for which the game remains enjoyable, such that the metrics cannot directly be compared to those of the traditional Game-of-the-Goose. Based on our analysis, we provide several suggestions to improve the game balance with only slight modifications. In a broader sense, we demonstrate that a basic Monte Carlo simulation suffices to analyze Game-of-the-Goose role-playing variants, verify how they score on criteria that contribute to an enjoyable game, and detect possible anomalies

    Smart Containers With Bidding Capacity: A Policy Gradient Algorithm for Semi-Cooperative Learning

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    Smart modular freight containers -- as propagated in the Physical Internet paradigm -- are equipped with sensors, data storage capability and intelligence that enable them to route themselves from origin to destination without manual intervention or central governance. In this self-organizing setting, containers can autonomously place bids on transport services in a spot market setting. However, for individual containers it may be difficult to learn good bidding policies due to limited observations. By sharing information and costs between one another, smart containers can jointly learn bidding policies, even though simultaneously competing for the same transport capacity. We replicate this behavior by learning stochastic bidding policies in a semi-cooperative multi agent setting. To this end, we develop a reinforcement learning algorithm based on the policy gradient framework. Numerical experiments show that sharing solely bids and acceptance decisions leads to stable bidding policies. Additional system information only marginally improves performance; individual job properties suffice to place appropriate bids. Furthermore, we find that carriers may have incentives not to share information with the smart containers. The experiments give rise to several directions for follow-up research, in particular the interaction between smart containers and transport services in self-organizing logistics.Comment: 15 page

    On the accuracy and precision of cardiac magnetic resonance T2 mapping: A high-resolution radial study using adiabatic T2 preparation at 3 T.

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    The goal of this study was to characterize the accuracy and precision of cardiac T2 mapping as a function of different factors including low signal-to-noise ratio (SNR), imaging in systole, and off-resonance frequencies. Bloch equation and Monte Carlo simulations were used to determine the influence of SNR and the choice of T2 preparation echo time (TET2prep ) increments on the accuracy and precision of high-resolution radial cardiac T2 mapping at 3.0 T. Healthy volunteers were scanned to establish the difference in precision and inter- and intraobserver variability between T2 mapping in diastole and systole, as well as the effect of SNR and off-resonance frequencies on the accuracy of T2 maps. The simulations demonstrated that a TET2prep increment of ∼0.75 times the T2 value of interest optimally increases the precision of the T2 fit. Systolic T2 maps were found to have a higher precision (P = 0.002), but similar inter- and intraobserver variability compared with diastolic T2 maps, whereas off-resonance frequencies beyond ± 100 Hz cause a significant decrease in both accuracy and precision (P < 0.05). This evaluation of the accuracy and precision of cardiac T2 mapping characterizes the major vulnerabilities of the technique and will help guide protocol definition of studies that include T2 mapping. Magn Reson Med 77:159-169, 2017. © 2016 Wiley Periodicals, Inc

    Combined Free-running 4D anatomical and flow MRI with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS).

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    BACKGROUND 4D flow MRI often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses Pilot Tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running 3D radial acquisitions, to create co-registered anatomy and flow images. METHODS Thirteen volunteers and two Marfan Syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional 2D flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0-4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation. RESULTS Blood-to-myocardium contrast ratio for SyNAPS 4D flow magnitude images (1.5±0.3) was significantly higher than for Native 4D flow (0.7±0.1, p<0.01), and was comparable to 2D flow (2.3±0.9, p=0.02). Image quality scores of SyNAPS 4D flow from the experts (MP: 1.9±0.3, ET: 2.5±0.5) were overall significantly higher than the scores from Native 4D flow (MP: 1.6±0.6, p=0.03, ET: 0.8±0.4, p<0.01) but still significantly lower than the scores from the reference 2D flow datasets (MP: 2.8±0.4, p<0.01, ET: 3.5±0.7, p<0.01). The Pearson correlation coefficient between the dynamic vessel area measured on SyNAPS 4D flow and that from 2D flow was 0.69±0.24 for the AAo and 0.83±0.10 for the DAo, whereas the Pearson correlation between Native 4D flow and 2D flow measurements was 0.12±0.48 for the AAo and 0.08±0.39 for the DAo. Linear correlations between SyNAPS 4D flow and 2D flow measurements of net volume (r2=0.83) and peak flow (r2=0.87) were larger than the correlations between Native 4D flow and 2D flow measurements of net volume (r2=0.79) and peak flow (r2=0.76). DISCUSSION AND CONCLUSION The feasibility and utility of SyNAPS was demonstrated for joint whole-heart anatomical and flow MRI without requiring ECG gating, respiratory navigators, or contrast agents. Using SyNAPS a high-contrast anatomical imaging sequence can be used to improve 4D flow measurements that often suffer from poor delineation of vessel boundaries in the absence of contrast agents

    Ultrafast and high-throughput mass spectrometric assay for therapeutic drug monitoring of antiretroviral drugs in pediatric HIV-1 infection applying dried blood spots

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    Kaletra® (Abott Laboratories) is a co-formulated medication used in the treatment of HIV-1-infected children, and it contains the two antiretroviral protease inhibitor drugs lopinavir and ritonavir. We validated two new ultrafast and high-throughput mass spectrometric assays to be used for therapeutic drug monitoring of lopinavir and ritonavir concentrations in whole blood and in plasma from HIV-1-infected children. Whole blood was blotted onto dried blood spot (DBS) collecting cards, and plasma was collected simultaneously. DBS collecting cards were extracted by an acetonitrile/water mixture while plasma samples were deproteinized with acetone. Drug concentrations were determined by matrix-assisted laser desorption/ionization-triple quadrupole tandem mass spectrometry (MALDI-QqQ-MS/MS). The application of DBS made it possible to measure lopinavir and ritonavir in whole blood in therapeutically relevant concentrations. The MALDI-QqQ-MS/MS plasma assay was successfully cross-validated with a commonly used high-performance liquid chromatography (HPLC)–ultraviolet (UV) assay for the therapeutic drug monitoring (TDM) of HIV-1-infected patients, and it showed comparable performance characteristics. Observed DBS concentrations showed as well, a good correlation between plasma concentrations obtained by MALDI-QqQ-MS/MS and those obtained by the HPLC-UV assay. Application of DBS for TDM proved to be a good alternative to the normally used plasma screening. Moreover, collection of DBS requires small amounts of whole blood which can be easily performed especially in (very) young children where collection of large whole blood amounts is often not possible. DBS is perfectly suited for TDM of HIV-1-infected children; but nevertheless, DBS can also easily be applied for TDM of patients in areas with limited or no laboratory facilities

    Structural basis for Mep2 ammonium transceptor activation by phosphorylation

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    Mep2 proteins are fungal transceptors that play an important role as ammonium sensors in fungal development. Mep2 activity is tightly regulated by phosphorylation, but how this is achieved at the molecular level is not clear. Here we report X-ray crystal structures of the Mep2 orthologues from Saccharomyces cerevisiae and Candida albicans and show that under nitrogen-sufficient conditions the transporters are not phosphorylated and present in closed, inactive conformations. Relative to the open bacterial ammonium transporters, non-phosphorylated Mep2 exhibits shifts in cytoplasmic loops and the C-terminal region (CTR) to occlude the cytoplasmic exit of the channel and to interact with His2 of the twin-His motif. The phosphorylation site in the CTR is solvent accessible and located in a negatively charged pocket ∼30 Å away from the channel exit. The crystal structure of phosphorylation-mimicking Mep2 variants from C. albicans show large conformational changes in a conserved and functionally important region of the CTR. The results allow us to propose a model for regulation of eukaryotic ammonium transport by phosphorylation

    Mechanism of Disruption of the Amt-GlnK Complex by PII-Mediated Sensing of 2-Oxoglutarate

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    GlnK proteins regulate the active uptake of ammonium by Amt transport proteins by inserting their regulatory T-loops into the transport channels of the Amt trimer and physically blocking substrate passage. They sense the cellular nitrogen status through 2-oxoglutarate, and the energy level of the cell by binding both ATP and ADP with different affinities. The hyperthermophilic euryarchaeon Archaeoglobus fulgidus possesses three Amt proteins, each encoded in an operon with a GlnK ortholog. One of these proteins, GlnK2 was recently found to be incapable of binding 2-OG, and in order to understand the implications of this finding we conducted a detailed structural and functional analysis of a second GlnK protein from A. fulgidus, GlnK3. Contrary to Af-GlnK2 this protein was able to bind both ATP/2-OG and ADP to yield inactive and functional states, respectively. Due to the thermostable nature of the protein we could observe the exact positioning of the notoriously flexible T-loops and explain the binding behavior of GlnK proteins to their interaction partner, the Amt proteins. A thermodynamic analysis of these binding events using microcalorimetry evaluated by microstate modeling revealed significant differences in binding cooperativity compared to other characterized PII proteins, underlining the diversity and adaptability of this class of regulatory signaling proteins
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