Regional brain development analysis through registration using anisotropic similarity, a constrained affine transformation

We propose a novel method to quantify brain growth in 3 arbitrary orthogonal directions of the brain or its sub-regions through linear registration. This is achieved by introducing a 9 degrees of freedom (dof) transformation called anisotropic similarity which is an affine transformation with constrained scaling directions along arbitrarily chosen orthogonal vectors. This gives the opportunity to extract scaling factors describing brain growth along those directions by registering a database of subjects onto a common reference. This information about directional growth brings insights that are not usually available in longitudinal volumetric analysis. The interest of this method is illustrated by studying the anisotropic regional and global brain development of 308 healthy subjects betwen 0 and 19 years old. A gender comparison of those scaling factors is also performed for four age-intervals. We demonstrate through these applications the stability of the method to the chosen reference and its ability to highlight growth differences accros regions and gender

Wave Function Microscopy of Quasibound Atomic States

In the 1980s Demkov, Kondratovich, and Ostrovsky and Kondratovich and Ostrovsky proposed an experiment based on the projection of slow electrons emitted by a photoionized atom onto a position-sensitive detector. In the case of resonant excitation, they predicted that the spatial electron distribution on the detector should represent nothing else but a magnified image of the projection of a quasibound electronic state. By exciting lithium atoms in the presence of a static electric field, we present in this Letter the first experimental photoionization wave function microscopy images where signatures of quasibound states are evident. Characteristic resonant features, such as (i) the abrupt change of the number of wave function nodes across a resonance and (ii) the broadening of the outer ring of the image (associated with tunneling ionization), are observed and interpreted via wave packet propagation simulations and recently proposed resonance tunneling mechanisms. The electron spatial distribution measured by our microscope is a direct macroscopic image of the projection of the microscopic squared modulus of the electron wave that is quasibound to the atom and constitutes the first experimental realization of the experiment proposed 30 years ago

Wave-function imaging of quasibound and continuum Stark states

Photoionization of an atom in the presence of a uniform static electric field provides the unique opportunity to expand and visualize the atomic wave function at a macroscopic scale. In a number of seminal publications dating back to the 1980s, Fabrikant, Demkov, Kondratovich, and Ostrovsky showed that this goal could be achieved by projecting slow (meV) photoionized electrons onto a position-sensitive detector and underlined the distinction between continuum and resonant contributions. The uncovering of resonant signatures was achieved fairly recently in experiments on the nonhydrogenic lithium atoms [Cohen et al., Phys. Rev. Lett. 110, 183001 (2013)]. The purpose of the present article is the general description of these findings, with emphasis on the various manifestations of resonant character. From this point of view, lithium has been chosen as an illustrative example between the two limiting cases of hydrogen, where resonance effects are more easily identified, and heavy atoms like xenon, where resonant effects were not observed

Nulling interferometry: performance comparison between Antarctica and other ground-based sites

Detecting the presence of circumstellar dust around nearby solar-type main sequence stars is an important pre-requisite for the design of future life-finding space missions such as ESA's Darwin or NASA's Terrestrial Planet Finder (TPF). The high Antarctic plateau may provide appropriate conditions to perform such a survey from the ground. We investigate the performance of a nulling interferometer optimised for the detection of exozodiacal discs at Dome C, on the high Antarctic plateau, and compare it to the expected performance of similar instruments at temperate sites. Based on the currently available measurements of the turbulence characteristics at Dome C, we adapt the GENIEsim software (Absil et al. 2006, A&A 448) to simulate the performance of a nulling interferometer on the high Antarctic plateau. To feed a realistic instrumental configuration into the simulator, we propose a conceptual design for ALADDIN, the Antarctic L-band Astrophysics Discovery Demonstrator for Interferometric Nulling. We assume that this instrument can be placed above the 30-m high boundary layer, where most of the atmospheric turbulence originates. We show that an optimised nulling interferometer operating on a pair of 1-m class telescopes located 30 m above the ground could achieve a better sensitivity than a similar instrument working with two 8-m class telescopes at a temperate site such as Cerro Paranal. The detection of circumstellar discs about 20 times as dense as our local zodiacal cloud seems within reach for typical Darwin/TPF targets in a integration time of a few hours. Moreover, the exceptional turbulence conditions significantly relax the requirements on real-time control loops, which has favourable consequences on the feasibility of the nulling instrument.Comment: 10 pages, accepted for publication in A&

Group testing with Random Pools: Phase Transitions and Optimal Strategy

The problem of Group Testing is to identify defective items out of a set of objects by means of pool queries of the form "Does the pool contain at least a defective?". The aim is of course to perform detection with the fewest possible queries, a problem which has relevant practical applications in different fields including molecular biology and computer science. Here we study GT in the probabilistic setting focusing on the regime of small defective probability and large number of objects, $p \to 0$ and $N \to \infty$. We construct and analyze one-stage algorithms for which we establish the occurrence of a non-detection/detection phase transition resulting in a sharp threshold, $\bar M$, for the number of tests. By optimizing the pool design we construct algorithms whose detection threshold follows the optimal scaling $\bar M\propto Np|\log p|$. Then we consider two-stages algorithms and analyze their performance for different choices of the first stage pools. In particular, via a proper random choice of the pools, we construct algorithms which attain the optimal value (previously determined in Ref. [16]) for the mean number of tests required for complete detection. We finally discuss the optimal pool design in the case of finite $p$

Have you forgotten? A method to assess if machine learning models have forgotten data

In the era of deep learning, aggregation of data from several sources is a common approach to ensuring data diversity. Let us consider a scenario where several providers contribute data to a consortium for the joint development of a classification model (hereafter the target model), but, now one of the providers decides to leave. This provider requests that their data (hereafter the query dataset) be removed from the databases but also that the model `forgets' their data. In this paper, for the first time, we want to address the challenging question of whether data have been forgotten by a model. We assume knowledge of the query dataset and the distribution of a model's output. We establish statistical methods that compare the target's outputs with outputs of models trained with different datasets. We evaluate our approach on several benchmark datasets (MNIST, CIFAR-10 and SVHN) and on a cardiac pathology diagnosis task using data from the Automated Cardiac Diagnosis Challenge (ACDC). We hope to encourage studies on what information a model retains and inspire extensions in more complex settings.Comment: Accepted by MICCAI 202

Synchronized pulses generated at 20 eV and 90 eV for attosecond pump-probe experiments

The development of attosecond pulses across different photon energies is an essential precursor to performing pump–probe attosecond experiments in complex systems, where the potential of attosecond science1 can be further developed2,3. We report the generation and characterization of synchronized extreme ultraviolet (90 eV) and vacuum ultraviolet (20 eV) pulses, generated simultaneously via high-harmonic generation. The vacuum ultraviolet pulses are well suited for pump–probe experiments that exploit the high photo-ionization cross-sections of many molecules in this spectral region4 as well as the higher photon flux due to the higher conversion efficiency of the high harmonic generation process at these energies5. We temporally characterized all pulses using the attosecond streaking technique6 and the FROG-CRAB retrieval method7. We report 576 ± 16 as pulses at 20 eV and 257 ± 21 as pulses at 90 eV. Our demonstration of synchronized attosecond pulses at different photon energies, which are inherently jitter-free due to the common-path geometry implemented, offers unprecedented possibilities for pump–probe studies

Robust And Scalable Learning Of Complex Dataset Topologies Via Elpigraph

Large datasets represented by multidimensional data point clouds often possess non-trivial distributions with branching trajectories and excluded regions, with the recent single-cell transcriptomic studies of developing embryo being notable examples. Reducing the complexity and producing compact and interpretable representations of such data remains a challenging task. Most of the existing computational methods are based on exploring the local data point neighbourhood relations, a step that can perform poorly in the case of multidimensional and noisy data. Here we present ElPiGraph, a scalable and robust method for approximation of datasets with complex structures which does not require computing the complete data distance matrix or the data point neighbourhood graph. This method is able to withstand high levels of noise and is capable of approximating complex topologies via principal graph ensembles that can be combined into a consensus principal graph. ElPiGraph deals efficiently with large and complex datasets in various fields from biology, where it can be used to infer gene dynamics from single-cell RNA-Seq, to astronomy, where it can be used to explore complex structures in the distribution of galaxies.Comment: 32 pages, 14 figure

Carbon K-edge x-ray emission spectroscopy of gas phase ethylenic molecules

We report on the C K-edge x-ray absorption spectra and the resonant (RXES) and non-resonant (NXES) x-ray emission spectra of ethylene, allene and butadiene in the gas phase. The RXES and NXES show clear differences for the different molecules. Overall both types of spectra are more structured for ethylene and allene, than for butadiene. Using density functional theory–restricted open shell configuration interaction single calculations, we simulate the spectra with remarkable agreement with the experiment. We identify the spectral features as being due to transitions involving localised 1s orbitals. For allene, there are distinct spectral bands that reflect transitions predominantly from either the central or terminal carbon atoms. These results are discussed in the context of ultrafast x-ray studies aimed at detecting the passage through conical intersections in polyatomic molecules

Digital correction of residual straylight in FLEX images

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