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  • Highly efficient conversion of laser energy to hard X-rays in high intensity laser-solid simulations

    Authors: S. Morris, A. Robinson, C. Ridgers
    DOI: 10.1063/5.0055398
    Submitted by Stuart_Morris      

    Why should we attempt to reproduce this paper?

    There are many applications to multi-MeV X-rays. Their penetrative properties make them good for scanning dense objects for industry, and their ionising properties can destroy tumours in radiotherapy. They are also around the energy of nuclear transitions, so they can trigger nuclear reactions to break down nuclear waste into medical isotopes, or to reveal smuggled nuclear-materials for port security. Laser-driven X-ray generation offers a compact and efficient way to create a bright source of X-rays, without having to construct a large synchrotron. To fully utilise this capability, work on optimising the target design and understanding the underlying X-ray mechanisms are essential. The hybrid-PIC code is in a unique position to model the full interaction, so its ease-of-use and reproducibility are crucial for this field to develop.

  • PlanGAN: Model-based Planning With Sparse Rewards and Multiple Goals

    Authors: Henry Charlesworth and Giovanni Montana
    Submitted by gmontana74      
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper proposes a probabilistic planner that can solve goal-conditional tasks such as complex continuous control problems. The approach reaches state-of-the-art performance when compared to current deep reinforcement learning algorithms. However, the method relies on an ensemble of deep generative models and is computationally intensive. It would be interesting to reproduce the results presented in this paper on their robotic manipulation and navigation problems as these are very challenging problems that current reinforcement learning methods cannot easily solve (and when they do, they require a significantly larger number of experiences). Can the results be reproduced out-of-the-box with the provided code?

  • REMoDNaV: robust eye-movement classification for dynamic stimulation

    Authors: Asim H. Dar, Adina S. Wagner, Michael Hanke
    DOI: https://doi.org/10.3758/s13428-020-01428-x
    Submitted by adswa    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   3
    Why should we attempt to reproduce this paper?

    In theory, reproducing this paper should only require a clone of a public Git repository, and the execution of a Makefile (detailed in the README of the paper repository at https://github.com/psychoinformatics-de/paper-remodnav). We've set up our paper to be dynamically generated, retrieving and installing the relevant data and software automatically, and we've even created a tutorial about it, so that others can reuse the same setup for their work. Nevertheless, we've for example never tried it out across different operating systems - who knows whether it works on Windows? We'd love to share the tips and tricks we found to work, and even more love feedback on how to improve this further.

  • Investigation into the annotation of protocol sequencing steps in the sequence read archive

    Authors: Alnasir, Jamie, and Hugh P. Shanahan.
    Submitted by hub-admin  

    Why should we attempt to reproduce this paper?

    Metadata annotation is key to reproducibility in sequencing experiments. Reproducing this research using the scripts provided will also show the current level of annotation in years since 2015 when the paper was published.

    Tags: Python SQL
  • Where should new parkrun events be located? Modelling the potential impact of 200 new events on socio-economic inequalities in access and participation

    Authors: Schneider PP, Smith RA, Bullas AM, Bayley T, Haake SS, Brennan A, Goyder E
    Submitted by hub-admin    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   3
    Why should we attempt to reproduce this paper?

    If all went right, the analysis should be fully reproducible without the need to make any adjustments. The paper aims to find optimal locations for new parkruns, but we were not 100% sure how 'optimal' should be defined. We provide a few examples, but the code was meant to be flexible enough to allow potential decision makers to specify their own, alternative objectives. The spatial data set is also quite interesting and fun to play around with. Cave: The full analysis takes a while to run (~30+ min) and might require >= 8gb ram.

  • Population structure and phenotypic variation of Sclerotinia sclerotiorum from dry bean (Phaseolus vulgaris) in the United States

    Authors: Kamvar ZN, Amaradasa BS, Jhala R, McCoy S, Steadman JR, Everhart SE
    DOI: 10.7717/peerj.4152
    Submitted by hub-admin    
      Mean reproducibility score:   6.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper is reproduced weekly in a docker container on continuous integration, but it is also set up to work via local installs as well. It would be interesting to see if it's reproducible with a human operator who knows nothing of the project or toolchain.

    Tags: R make Docker
  • Bayesian determination of the effect of a deep eutectic solvent on the structure of lipid monolayers

    Authors: "McCluskey, Andrew R. and Sanchez-Fernandez, Adrian and Edler, Karen J. and Parker, Stephen C. and Jackson, Andrew J. and Campbell, Richard A. and Arnold, Thomas
    DOI: DOI https://doi.org/10.1039/C9CP00203K
    Submitted by hub-admin    
      Mean reproducibility score:   8.5/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    I believe this represents the only example of a reproducible paper from scattering data collected at Diamond Light Source (UK) and the Institute Laue-Langevin (France)

    Tags: Python make

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