A new type of charged defect in amorphous chalcogenides

We report on density-functional-based tight-binding (DFTB) simulations of a series of amorphous arsenic sulfide models. In addition to the charged coordination defects previously proposed to exist in chalcogenide glasses, a novel defect pair, [As4]--[S3]+, consisting of a four-fold coordinated arsenic site in a seesaw configuration and a three-fold coordinated sulfur site in a planar trigonal configuration, was found in several models. The valence-alternation pairs S3+-S1- are converted into [As4]--[S3]+ pairs under HOMO-to-LUMO electronic excitation. This structural transformation is accompanied by a decrease in the size of the HOMO-LUMO band gap, which suggests that such transformations could contribute to photo-darkening in these materials.Comment: 5 pages, 2 figure

Influence of copper on the electronic properties of amorphous chalcogenides

We have studied the influence of alloying copper with amorphous arsenic sulfide on the electronic properties of this material. In our computer-generated models, copper is found in two-fold near-linear and four-fold square-planar configurations, which apparently correspond to Cu(I) and Cu(II) oxidation states. The number of overcoordinated atoms, both arsenic and sulfur, grows with increasing concentration of copper. Overcoordinated sulfur is found in trigonal planar configuration, and overcoordinated (four-fold) arsenic is in tetrahedral configuration. Addition of copper suppresses the localization of lone-pair electrons on chalcogen atoms, and localized states at the top of the valence band are due to Cu 3d orbitals. Evidently, these additional Cu states, which are positioned at the same energies as the states due to ([As4]-)-([S_3]+) pairs, are responsible for masking photodarkening in Cu chalcogenides

Resonant electron heating and molecular phonon cooling in single C60_{60} junctions

We study heating and heat dissipation of a single \c60 molecule in the junction of a scanning tunneling microscope (STM) by measuring the electron current required to thermally decompose the fullerene cage. The power for decomposition varies with electron energy and reflects the molecular resonance structure. When the STM tip contacts the fullerene the molecule can sustain much larger currents. Transport simulations explain these effects by molecular heating due to resonant electron-phonon coupling and molecular cooling by vibrational decay into the tip upon contact formation.Comment: Accepted in Phys. Rev. Let

Dynamical generalization of a solvable family of two-electron model atoms with general interparticle repulsion

Holas, Howard and March [Phys. Lett. A {\bf 310}, 451 (2003)] have obtained analytic solutions for ground-state properties of a whole family of two-electron spin-compensated harmonically confined model atoms whose different members are characterized by a specific interparticle potential energy u($r_{12}$). Here, we make a start on the dynamic generalization of the harmonic external potential, the motivation being the serious criticism levelled recently against the foundations of time-dependent density-functional theory (e.g. [J. Schirmer and A. Dreuw, Phys. Rev. A {\bf 75}, 022513 (2007)]). In this context, we derive a simplified expression for the time-dependent electron density for arbitrary interparticle interaction, which is fully determined by an one-dimensional non-interacting Hamiltonian. Moreover, a closed solution for the momentum space density in the Moshinsky model is obtained.Comment: 5 pages, submitted to J. Phys.

Quality control for more reliable integration of deep learning-based image segmentation into medical workflows

Machine learning algorithms underpin modern diagnostic-aiding software, whichhas proved valuable in clinical practice, particularly in radiology. However,inaccuracies, mainly due to the limited availability of clinical samples fortraining these algorithms, hamper their wider applicability, acceptance, andrecognition amongst clinicians. We present an analysis of state-of-the-artautomatic quality control (QC) approaches that can be implemented within thesealgorithms to estimate the certainty of their outputs. We validated the mostpromising approaches on a brain image segmentation task identifying whitematter hyperintensities (WMH) in magnetic resonance imaging data. WMH are acorrelate of small vessel disease common in mid-to-late adulthood and areparticularly challenging to segment due to their varied size, anddistributional patterns. Our results show that the aggregation of uncertaintyand Dice prediction were most effective in failure detection for this task.Both methods independently improved mean Dice from 0.82 to 0.84. Our workreveals how QC methods can help to detect failed segmentation cases andtherefore make automatic segmentation more reliable and suitable for clinicalpractice.<br

How to predict relapse in leukemia using time series data: A comparative in silico study

Risk stratification and treatment decisions for leukemia patients are regularly based on clinical markers determined at diagnosis, while measurements on system dynamics are often neglected. However, there is increasing evidence that linking quantitative time-course information to disease outcomes can improve the predictions for patient-specific treatment responses. We designed a synthetic experiment simulating response kinetics of 5,000 patients to compare different computational methods with respect to their ability to accurately predict relapse for chronic and acute myeloid leukemia treatment. Technically, we used clinical reference data to first fit a model and then generate de novo model simulations of individual patients’ time courses for which we can systematically tune data quality (i.e. measurement error) and quantity (i.e. number of measurements). Based hereon, we compared the prediction accuracy of three different computational methods, namely mechanistic models, generalized linear models, and deep neural networks that have been fitted to the reference data. Reaching prediction accuracies between 60 and close to 100%, our results indicate that data quality has a higher impact on prediction accuracy than the specific choice of the particular method. We further show that adapted treatment and measurement schemes can considerably improve the prediction accuracy by 10 to 20%. Our proof-of-principle study highlights how computational methods and optimized data acquisition strategies can improve risk assessment and treatment of leukemia patients

Atomistic simulations of self-trapped exciton formation in silicon nanostructures: The transition from quantum dots to nanowires

Using an approximate time-dependent density functional theory method, we calculate the absorption and luminescence spectra for hydrogen passivated silicon nanoscale structures with large aspect ratio. The effect of electron confinement in axial and radial directions is systematically investigated. Excited state relaxation leads to significant Stokes shifts for short nanorods with lengths less than 2 nm, but has little effect on the luminescence intensity. The formation of self-trapped excitons is likewise observed for short nanostructures only; longer wires exhibit fully delocalized excitons with neglible geometrical distortion at the excited state minimum.Comment: 10 pages, 4 figure

Revival of the magnetar PSR J1622-4950: observations with MeerKAT, Parkes, XMM-Newton, Swift, Chandra, and NuSTAR

New radio (MeerKAT and Parkes) and X-ray (XMM-Newton, Swift, Chandra, and NuSTAR) observations of PSR J1622-4950 indicate that the magnetar, in a quiescent state since at least early 2015, reactivated between 2017 March 19 and April 5. The radio flux density, while variable, is approximately 100x larger than during its dormant state. The X-ray flux one month after reactivation was at least 800x larger than during quiescence, and has been decaying exponentially on a 111+/-19 day timescale. This high-flux state, together with a radio-derived rotational ephemeris, enabled for the first time the detection of X-ray pulsations for this magnetar. At 5%, the 0.3-6 keV pulsed fraction is comparable to the smallest observed for magnetars. The overall pulsar geometry inferred from polarized radio emission appears to be broadly consistent with that determined 6-8 years earlier. However, rotating vector model fits suggest that we are now seeing radio emission from a different location in the magnetosphere than previously. This indicates a novel way in which radio emission from magnetars can differ from that of ordinary pulsars. The torque on the neutron star is varying rapidly and unsteadily, as is common for magnetars following outburst, having changed by a factor of 7 within six months of reactivation.Comment: Published in ApJ (2018 April 5); 13 pages, 4 figure