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Humanitarian agencies must be prepared to mobilize quickly in response to complex emergencies, and their effectiveness depends on their ability to identify, anticipate, and prepare for future needs. These are typically highly uncertain situations in which predictive modeling tools can be useful but challenging to build. To better understand the need for humanitarian support -- including shelter and assistance -- and strengthen contingency planning and protection efforts for displaced populations, we present a situational analysis tool to help anticipate the number of migrants and forcibly displaced persons that will cross a border in a humanitarian crisis. The tool consists of: (i) indicators of potential intent to move drawn from traditional and big data sources; (ii) predictive models for forecasting possible future movements; and (iii) a simulation of border crossings and shelter capacity requirements under different conditions. This tool has been specifically adapted to contingency planning in settings of high uncertainty, with an application to the Brazil-Venezuela border during the COVID-19 pandemic., Comment: 9 pages, 5 figures

The need for high-level autonomy and robustness of autonomous systems for missions in dynamic and remote environment has pushed developers to come up with new software architectures. A common architecture style is to summarize the capabilities of the robotic system into elementary actions, called skills, on top of which a skill management layer is implemented to structure, test and control the functional layer. However, current available verification tools only provide either mission-specific verification or verification on a model that does not replicate the actual execution of the system, which makes it difficult to ensure its robustness to unexpected events. To that end, a tool, SkiNet, has been developed to transform the skill-based architecture of a system into a Petri net modeling the state-machine behaviors of the skills and the resources they handle. The Petri net allows the use of model-checking, such as Linear Temporal Logic (LTL) or Computational Tree Logic (CTL), for the user to analyze and verify the model of the system., Comment: In Proceedings FMAS2022 ASYDE2022, arXiv:2209.13181

We perform detailed muon spin rotation ($\mu$SR) measurements in the classic antiferromagnet Fe$_2$O$_3$ and explain the spectra by considering dynamic population and dissociation of charge-neutral muon-polaron complexes. We show that charge-neutral muon states in Fe$_2$O$_3$, despite lacking the signatures typical of charge-neutral muonium centers in nonmagnetic materials, have a significant impact on the measured $\mu$SR frequencies and relaxation rates. Our identification of such polaronic muon centers in Fe$_2$O$_3$ suggests that isolated hydrogen (H) impurities form analogous complexes, and that H interstitials may be a source of charge carrier density in Fe$_2$O$_3$.

We report the discovery and characterisation of a super-Earth and a sub-Neptune transiting the bright ($K=8.8$), quiet, and nearby (37 pc) M3V dwarf TOI-1266. We validate the planetary nature of TOI-1266 b and c using four sectors of TESS photometry and data from the newly-commissioned 1-m SAINT-EX telescope located in San Pedro M\'artir (Mexico). We also include additional ground-based follow-up photometry as well as high-resolution spectroscopy and high-angular imaging observations. The inner, larger planet has a radius of $R=2.37_{-0.12}^{+0.16}$ R$_{\oplus}$ and an orbital period of 10.9 days. The outer, smaller planet has a radius of $R=1.56_{-0.13}^{+0.15}$ R$_{\oplus}$ on an 18.8-day orbit. The data are found to be consistent with circular, co-planar and stable orbits that are weakly influenced by the 2:1 mean motion resonance. Our TTV analysis of the combined dataset enables model-independent constraints on the masses and eccentricities of the planets. We find planetary masses of $M_\mathrm{p}$ = $13.5_{-9.0}^{+11.0}$ $\mathrm{M_{\oplus}}$ ($<36.8$ $\mathrm{M_{\oplus}}$ at 2-$\sigma$) for TOI-1266 b and $2.2_{-1.5}^{+2.0}$ $\mathrm{M_{\oplus}}$ ($<5.7$ $\mathrm{M_{\oplus}}$ at 2-$\sigma$) for TOI-1266 c. We find small but non-zero orbital eccentricities of $0.09_{-0.05}^{+0.06}$ ($<0.21$ at 2-$\sigma$) for TOI-1266 b and $0.04\pm0.03$ ($<0.10$ at 2-$\sigma$) for TOI-1266 c. The equilibrium temperatures of both planets are of $413\pm20$ K and $344\pm16$ K, respectively, assuming a null Bond albedo and uniform heat redistribution from the day-side to the night-side hemisphere. The host brightness and negligible activity combined with the planetary system architecture and favourable planet-to-star radii ratios makes TOI-1266 an exquisite system for a detailed characterisation., Comment: In press. Accepted for publication in Astronomy and Astrophysics on 20 July 2020

Most protocols for the high-throughput directed evolution of enzymes rely on random encapsulation to link phenotype and genotype. In order to optimize these approaches, or compare one to another, one needs a measure of their performance at extracting the best variants. We introduce here a new metric named the Selection Quality Index (SQI), which can be computed from a simple mock experiment with a known initial fraction of active variants. As opposed to previous approaches, our index integrates the random co-encapsulation of entities in compartments and comes with a straightforward experimental interpretation. We further show how this new metric can be used to extract general trends of protocol efficiency, or reveal hidden mechanisms such as a counterintuitive form of beneficial poisoning in the Compartmentalized Self-Replication protocol.

The recent years have seen the emergence of diseases which have spread very quickly all around the world either through human travels like SARS or animal migration like avian flu. Among the biggest challenges raised by infectious emerging diseases, one is related to the constant mutation of the viruses which turns them into continuously moving targets for drug and vaccine discovery. Another challenge is related to the early detection and surveillance of the diseases as new cases can appear just anywhere due to the globalization of exchanges and the circulation of people and animals around the earth, as recently demonstrated by the avian flu epidemics. For 3 years now, a collaboration of teams in Europe and Asia has been exploring some innovative in silico approaches to better tackle avian flu taking advantage of the very large computing resources available on international grid infrastructures. Grids were used to study the impact of mutations on the effectiveness of existing drugs against H5N1 and to find potentially new leads active on mutated strains. Grids allow also the integration of distributed data in a completely secured way. The paper presents how we are currently exploring how to integrate the existing data sources towards a global surveillance network for molecular epidemiology., Comment: 7 pages, submitted to Infectious Disorders - Drug Targets

Monte Carlo simulations are increasingly used in scintigraphic imaging to model imaging systems and to develop and assess tomographic reconstruction algorithms and correction methods for improved image quantitation. GATE (GEANT 4 Application for Tomographic Emission) is a new Monte Carlo simulation platform based on GEANT4 dedicated to nuclear imaging applications. This paper describes the GATE simulation of a prototype of scintillation camera dedicated to small animal imaging and consisting of a CsI(Tl) crystal array coupled to a position sensitive photomultiplier tube. The relevance of GATE to model the camera prototype was assessed by comparing simulated 99mTc point spread functions, energy spectra, sensitivities, scatter fractions and image of a capillary phantom with the corresponding experimental measurements. Results showed an excellent agreement between simulated and experimental data: experimental spatial resolutions were predicted with an error less than 100 mu m. The difference between experimental and simulated system sensitivities for different source-to-collimator distances was within 2%. Simulated and experimental scatter fractions in a [98-182 keV] energy window differed by less than 2% for sources located in water. Simulated and experimental energy spectra agreed very well between 40 and 180 keV. These results demonstrate the ability and flexibility of GATE for simulating original detector designs. The main weakness of GATE concerns the long computation time it requires: this issue is currently under investigation by the GEANT4 and the GATE collaborations

Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols, and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at the address http://www-lphe.epfl.ch/GATE/.