Stochastic embedding DFT: theory and application to p-nitroaniline

Over this past decade, we combined the idea of stochastic resolution of identity with a variety of electronic structure methods. In our stochastic Kohn-Sham DFT method, the density is an average over multiple stochastic samples, with stochastic errors that decrease as the inverse square root of the number of sampling orbitals. Here we develop a stochastic embedding density functional theory method (se-DFT) that selectively reduces the stochastic error (specifically on the forces) for a selected sub-system(s). The motivation, similar to that of other quantum embedding methods, is that for many systems of practical interest the properties are often determined by only a small sub-system. In stochastic embedding DFT two sets of orbitals are used: a deterministic one associated with the embedded subspace, and the rest which is described by a stochastic set. The method is exact in the limit of large number of stochastic samples. We apply se-DFT to study a p-nitroaniline molecule in water, where the statistical errors in the forces on the system (the p-nitroaniline molecule) are reduced by an order of magnitude compared with non-embedding stochastic DFT

Modeling the Temporal Nature of Human Behavior for Demographics Prediction

Mobile phone metadata is increasingly used for humanitarian purposes in developing countries as traditional data is scarce. Basic demographic information is however often absent from mobile phone datasets, limiting the operational impact of the datasets. For these reasons, there has been a growing interest in predicting demographic information from mobile phone metadata. Previous work focused on creating increasingly advanced features to be modeled with standard machine learning algorithms. We here instead model the raw mobile phone metadata directly using deep learning, exploiting the temporal nature of the patterns in the data. From high-level assumptions we design a data representation and convolutional network architecture for modeling patterns within a week. We then examine three strategies for aggregating patterns across weeks and show that our method reaches state-of-the-art accuracy on both age and gender prediction using only the temporal modality in mobile metadata. We finally validate our method on low activity users and evaluate the modeling assumptions.Comment: Accepted at ECML 2017. A previous version of this paper was titled 'Using Deep Learning to Predict Demographics from Mobile Phone Metadata' and was accepted at the ICLR 2016 worksho

Chlamydia Hijacks ARF GTPases To Coordinate Microtubule Posttranslational Modifications and Golgi Complex Positioning.

The intracellular bacterium Chlamydia trachomatis develops in a parasitic compartment called the inclusion. Posttranslationally modified microtubules encase the inclusion, controlling the positioning of Golgi complex fragments around the inclusion. The molecular mechanisms by which Chlamydia coopts the host cytoskeleton and the Golgi complex to sustain its infectious compartment are unknown. Here, using a genetically modified Chlamydia strain, we discovered that both posttranslationally modified microtubules and Golgi complex positioning around the inclusion are controlled by the chlamydial inclusion protein CT813/CTL0184/InaC and host ARF GTPases. CT813 recruits ARF1 and ARF4 to the inclusion membrane, where they induce posttranslationally modified microtubules. Similarly, both ARF isoforms are required for the repositioning of Golgi complex fragments around the inclusion. We demonstrate that CT813 directly recruits ARF GTPases on the inclusion membrane and plays a pivotal role in their activation. Together, these results reveal that Chlamydia uses CT813 to hijack ARF GTPases to couple posttranslationally modified microtubules and Golgi complex repositioning at the inclusion.IMPORTANCEChlamydia trachomatis is an important cause of morbidity and a significant economic burden in the world. However, how Chlamydia develops its intracellular compartment, the so-called inclusion, is poorly understood. Using genetically engineered Chlamydia mutants, we discovered that the effector protein CT813 recruits and activates host ADP-ribosylation factor 1 (ARF1) and ARF4 to regulate microtubules. In this context, CT813 acts as a molecular platform that induces the posttranslational modification of microtubules around the inclusion. These cages are then used to reposition the Golgi complex during infection and promote the development of the inclusion. This study provides the first evidence that ARF1 and ARF4 play critical roles in controlling posttranslationally modified microtubules around the inclusion and that Chlamydia trachomatis hijacks this novel function of ARF to reposition the Golgi complex

Density-functional embedding using a plane-wave basis

The constrained electron density method of embedding a Kohn-Sham system in a substrate system (first described by P. Cortona, Phys. Rev. B {\bf 44}, 8454 (1991) and T.A. Wesolowski and A. Warshel, J. Phys. Chem {\bf 97}, 8050 (1993)) is applied with a plane-wave basis and both local and non-local pseudopotentials. This method divides the electron density of the system into substrate and embedded electron densities, the sum of which is the electron density of the system of interest. Coupling between the substrate and embedded systems is achieved via approximate kinetic energy functionals. Bulk aluminium is examined as a test case for which there is a strong interaction between the substrate and embedded systems. A number of approximations to the kinetic-energy functional, both semi-local and non-local, are investigated. It is found that Kohn-Sham results can be well reproduced using a non-local kinetic energy functional, with the total energy accurate to better than 0.1 eV per atom and good agreement between the electron densities.Comment: 11 pages, 4 figure

Superconductors with Topological Order

We propose a mechanism of superconductivity in which the order of the ground state does not arise from the usual Landau mechanism of spontaneous symmetry breaking but is rather of topological origin. The low-energy effective theory is formulated in terms of emerging gauge fields rather than a local order parameter and the ground state is degenerate on topologically non-trivial manifolds. The simplest example of this mechanism of superconductivty is concretely realized as global superconductivty in Josephson junction arrays.Comment: 4 pages, no figure

Multiscale simulations in simple metals: a density-functional based methodology

We present a formalism for coupling a density functional theory-based quantum simulation to a classical simulation for the treatment of simple metallic systems. The formalism is applicable to multiscale simulations in which the part of the system requiring quantum-mechanical treatment is spatially confined to a small region. Such situations often arise in physical systems where chemical interactions in a small region can affect the macroscopic mechanical properties of a metal. We describe how this coupled treatment can be accomplished efficiently, and we present a coupled simulation for a bulk aluminum system.Comment: 15 pages, 7 figure

Planar Dirac Electron in Coulomb and Magnetic Fields

The Dirac equation for an electron in two spatial dimensions in the Coulomb and homogeneous magnetic fields is discussed. For weak magnetic fields, the approximate energy values are obtained by semiclassical method. In the case with strong magnetic fields, we present the exact recursion relations that determine the coefficients of the series expansion of wave functions, the possible energies and the magnetic fields. It is found that analytic solutions are possible for a denumerably infinite set of magnetic field strengths. This system thus furnishes an example of the so-called quasi-exactly solvable models. A distinctive feature in the Dirac case is that, depending on the strength of the Coulomb field, not all total angular momentum quantum number allow exact solutions with wavefunctions in reasonable polynomial forms. Solutions in the nonrelativistic limit with both attractive and repulsive Coulomb fields are briefly discussed by means of the method of factorization.Comment: 18 pages, RevTex, no figure

Rigid urea and self-healing thiourea ethanolamine monolayers

A series of long-tail alkyl ethanolamine analogs containing amide-, urea-, and thiourea moieties was synthesized and the behavior of the corresponding monolayers was assessed on the Langmuir–Pockels trough combined with grazing incidence X-ray diffraction experiments and complemented by computer simulations. All compounds form stable monolayers at the soft air/water interface. The phase behavior is dominated by strong intermolecular headgroup hydrogen bond networks. While the amide analog forms well-defined monolayer structures, the stronger hydrogen bonds in the urea analogs lead to the formation of small three-dimensional crystallites already during spreading due to concentration fluctuations. The hydrogen bonds in the thiourea case form a two-dimensional network, which ruptures temporarily during compression and is recovered in a self-healing process, while in the urea clusters the hydrogen bonds form a more planar framework with gliding planes keeping the structure intact during compression. Because the thiourea analogs are able to self-heal after rupture, such compounds could have interesting properties as tight, ordered, and self-healing monolayers

Phase Ib study of the combination of pexidartinib (PLX3397), a CSF-1R inhibitor, and paclitaxel in patients with advanced solid tumors.

Purpose:To evaluate the safety, recommended phase II dose (RP2D) and efficacy of pexidartinib, a colony stimulating factor receptor 1 (CSF-1R) inhibitor, in combination with weekly paclitaxel in patients with advanced solid tumors. Patients and Methods:In part 1 of this phase Ib study, 24 patients with advanced solid tumors received escalating doses of pexidartinib with weekly paclitaxel (80 mg/m2). Pexidartinib was administered at 600 mg/day in cohort 1. For subsequent cohorts, the dose was increased by ⩽50% using a standard 3+3 design. In part 2, 30 patients with metastatic solid tumors were enrolled to examine safety, tolerability and efficacy of the RP2D. Pharmacokinetics and biomarkers were also assessed. Results:A total of 51 patients reported ≥1 adverse event(s) (AEs) that were at least possibly related to either study drug. Grade 3-4 AEs, including anemia (26%), neutropenia (22%), lymphopenia (19%), fatigue (15%), and hypertension (11%), were recorded in 38 patients (70%). In part 1, no maximum tolerated dose was achieved and 1600 mg/day was determined to be the RP2D. Of 38 patients evaluable for efficacy, 1 (3%) had complete response, 5 (13%) partial response, 13 (34%) stable disease, and 17 (45%) progressive disease. No drug-drug interactions were found. Plasma CSF-1 levels increased 1.6- to 53-fold, and CD14dim/CD16+ monocyte levels decreased by 57-100%. Conclusions:The combination of pexidartinib and paclitaxel was generally well tolerated. RP2D for pexidartinib was 1600 mg/day. Pexidartinib blocked CSF-1R signaling, indicating potential for mitigating macrophage tumor infiltration

A laboratory based edge-Illumination x-ray phase-contrast imaging setup with two-directional sensitivity

We report on a preliminary laboratory based x-ray phase-contrast imaging system capable of achieving two directional phase sensitivity thanks to the use of L-shaped apertures. We show that in addition to apparent absorption, two-directional differential phase images of an object can be quantitatively retrieved by using only three input images. We also verify that knowledge of the phase derivatives along both directions allows for straightforward phase integration with no streak artefacts, a known problem common to all differential phase techniques. In addition, an analytical method for 2-directional dark field retrieval is proposed and experimentally demonstrated