Approximate expressions for modulation speed and threshold for performance optimization of biaxially compressive strain quantum-well lasers

Simple analytical expressions for transparency, threshold, and relaxation oscillation corner frequency are derived for biaxial strain quantum-well lasers. An optimal operating point loss for high speed operation (in the absence of nonlinear gain) is established which varies as the square root of the number of quantum wells. The corresponding relaxation oscillation frequency is found to depend only on fundamental quantities. Its power dependence is [vR(max) = (87 GHz õm^3/mW) (Powerout/Vmode)^1/2) where Vmode is the mode volume

Contextuality-by-Default: A Brief Overview of Ideas, Concepts, and Terminology

This paper is a brief overview of the concepts involved in measuring the degree of contextuality and detecting contextuality in systems of binary measurements of a finite number of objects. We discuss and clarify the main concepts and terminology of the theory called "contextuality-by-default," and then discuss a possible generalization of the theory from binary to arbitrary measurements.Comment: Lecture Notes in Computer Science 9535 (with the corrected list of authors) (2016

Genome wide expression profiling reveals suppression of host defence responses during colonisation by Neisseria meningitides but not N. lactamica.

Both Neisseria meningitidis and the closely related bacterium Neisseria lactamica colonise human nasopharyngeal mucosal surface, but only N. meningitidis invades the bloodstream to cause potentially life-threatening meningitis and septicaemia. We have hypothesised that the two neisserial species differentially modulate host respiratory epithelial cell gene expression reflecting their disease potential. Confluent monolayers of 16HBE14 human bronchial epithelial cells were exposed to live and/or dead N. meningitidis (including capsule and pili mutants) and N. lactamica, and their transcriptomes were compared using whole genome microarrays. Changes in expression of selected genes were subsequently validated using Q-RT-PCR and ELISAs. Live N. meningitidis and N. lactamica induced genes involved in host energy production processes suggesting that both bacterial species utilise host resources. N. meningitidis infection was associated with down-regulation of host defence genes. N. lactamica, relative to N. meningitidis, initiates up-regulation of proinflammatory genes. Bacterial secreted proteins alone induced some of the changes observed. The results suggest N. meningitidis and N. lactamica differentially regulate host respiratory epithelial cell gene expression through colonisation and/or protein secretion, and that this may contribute to subsequent clinical outcomes associated with these bacteria

Crystal structure of the 3C protease from South African Territories type 2 foot-and-mouth disease virus

The replication of foot-and-mouth disease virus (FMDV) is dependent on the virus-encoded 3C protease (3Cpro). As in other picornaviruses, 3Cpro performs most of the proteolytic processing of the polyprotein expressed from the single open reading frame in the RNA genome of the virus. Previous work revealed that the 3Cpro from serotype A – one of the seven serotypes of FMDV – adopts a trypsin-like fold. Phylogenetically the FMDV serotypes are grouped into two clusters, with O, A, C, and Asia 1 in one, and the three South African Territories serotypes, (SAT-1, SAT-2 and SAT-3) in another. We report here the cloning, expression and purification of 3C proteases from four SAT serotype viruses (SAT2/GHA/8/91, SAT1/NIG/5/81, SAT1/UGA/1/97, and SAT2/ZIM/7/83) and the crystal structure at 3.2 Å resolution of 3Cpro from SAT2/GHA/8/91)

Ultrafast processing of pixel detector data with machine learning frameworks

Modern photon science performed at high repetition rate free-electron laser (FEL) facilities and beyond relies on 2D pixel detectors operating at increasing frequencies (towards 100 kHz at LCLS-II) and producing rapidly increasing amounts of data (towards TB/s). This data must be rapidly stored for offline analysis and summarized in real time. While at LCLS all raw data has been stored, at LCLS-II this would lead to a prohibitive cost; instead, enabling real time processing of pixel detector raw data allows reducing the size and cost of online processing, offline processing and storage by orders of magnitude while preserving full photon information, by taking advantage of the compressibility of sparse data typical for LCLS-II applications. We investigated if recent developments in machine learning are useful in data processing for high speed pixel detectors and found that typical deep learning models and autoencoder architectures failed to yield useful noise reduction while preserving full photon information, presumably because of the very different statistics and feature sets between computer vision and radiation imaging. However, we redesigned in Tensorflow mathematically equivalent versions of the state-of-the-art, "classical" algorithms used at LCLS. The novel Tensorflow models resulted in elegant, compact and hardware agnostic code, gaining 1 to 2 orders of magnitude faster processing on an inexpensive consumer GPU, reducing by 3 orders of magnitude the projected cost of online analysis at LCLS-II. Computer vision a decade ago was dominated by hand-crafted filters; their structure inspired the deep learning revolution resulting in modern deep convolutional networks; similarly, our novel Tensorflow filters provide inspiration for designing future deep learning architectures for ultrafast and efficient processing and classification of pixel detector images at FEL facilities.Comment: 9 pages, 9 figure

Direct determination of the ambipolar diffusion length in strained InxGa1−xAs/InP quantum wells by cathodoluminescence

The ambipolar diffusion length is measured in strained InxGa1−xAs/InP quantum wells for several mole fractions in the interval 0.3<x<0.8 by cathodoluminescence. The ambipolar diffusion length is found to have a significantly higher value in the lower indium mole fraction samples corresponding to tensile-strained wells. This longer diffusion length for the tensile samples is consistent with results of carrier lifetime experiments by M. C. Wang, K. Kash, C. E. Zah, R. Bhat, and S. L. Chuang [Appl. Phys. Lett. 62, 166 (1993)]

To what extent does the self-consistent mean-field exist?

A non-convergent difficulty near level-repulsive region is discussed within the self-consistent mean-field theory. It is shown by numerical and analytic studies that the mean-field is not realized in the many-fermion system when quantum fluctuations coming from two-body residual interaction and quadrupole deformation are larger than an energy difference between two avoided crossing orbits. An analytic condition indicating a limitation of the mean-field concept is derived for the first time

Investigation of Structural Dynamics of Enzymes and Protonation States of Substrates Using Computational Tools.

This review discusses the use of molecular modeling tools, together with existing experimental findings, to provide a complete atomic-level description of enzyme dynamics and function. We focus on functionally relevant conformational dynamics of enzymes and the protonation states of substrates. The conformational fluctuations of enzymes usually play a crucial role in substrate recognition and catalysis. Protein dynamics can be altered by a tiny change in a molecular system such as different protonation states of various intermediates or by a significant perturbation such as a ligand association. Here we review recent advances in applying atomistic molecular dynamics (MD) simulations to investigate allosteric and network regulation of tryptophan synthase (TRPS) and protonation states of its intermediates and catalysis. In addition, we review studies using quantum mechanics/molecular mechanics (QM/MM) methods to investigate the protonation states of catalytic residues of β-Ketoacyl ACP synthase I (KasA). We also discuss modeling of large-scale protein motions for HIV-1 protease with coarse-grained Brownian dynamics (BD) simulations