抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release. SciPy has become a de facto standard for leveraging scientific algorithms in the Python programming language, with more than 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories, and millions of downloads per year. This includes usage of SciPy in almost half of all machine learning projects on GitHub, and usage by high profile projects including LIGO gravitational wave analysis and creation of the first-ever image of a black hole (M87). The library includes functionality spanning clustering, Fourier transforms, integration, interpolation, file I/O, linear algebra, image processing, orthogonal distance regression, minimization algorithms, signal processing, sparse matrix handling, computational geometry, and statistics. In this work, we provide an overview of the capabilities and development practices of the SciPy library and highlight some recent technical developments.

/pdf/scipy-1-0-fundamental-algorithms-for-scientific-computing-in-111lr790ol.pdf

SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

http://brainimaging.waisman.wisc.edu/~chung/neuro.processing/literature/rubinov.2010.NI.network.pdf

Complex network measures of brain connectivity: uses and interpretations.

Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves1 and in the first imaging of a black hole2. Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis. NumPy is the primary array programming library for Python; here its fundamental concepts are reviewed and its evolution into a flexible interoperability layer between increasingly specialized computational libraries is discussed.

/pdf/array-programming-with-numpy-31s3jl24ra.pdf

Array programming with NumPy

SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.

/pdf/scipy-1-0-fundamental-algorithms-for-scientific-computing-in-45othhotbu.pdf

SciPy 1.0: fundamental algorithms for scientific computing in Python.

The local atomic structure and phonons in Ba0.5Sr0.5TiO3

We have made a direct and nanometer scale observation of single 180° domain walls in 500 μm thick ferroelectric LiTaO3 by using a collection mode Near-Field Scanning Optical Microscope. We unambiguously identify single domain walls by simultaneously recording nanometer scale topographic and optical images. The polarization rotation of a linear polarized laser beam due to the birefringence at the domain wall is optically imaged with 80–100nm spatial resolution. Next we have made a direct nanometer scale study of the mobility of a single 180° domain wall under a uniform applied electric field using the same technique. The mobility of the domain walls is strongly influenced by sub-surface pinning defects.

Observation and mobility study of single 180° domain wall using a near-field scanning optical microscope

NetworkX Documentation Release 1.0.dev1415

We present real-time studies of nucleation and growth of 180° ferroelectric domains in congruent LiTaO3 under an external electric field using optical microscopy. The measured wall velocities are an order of magnitude higher than those reported before using ex-situ techniques. Merger of growing domains form serrated fronts which show a futher order of magnitude increase in wall velocity. A time dependent velocity is required in the Avrami theory to explain the change in domain area versus time at a constant electric field. We believe that these features of domain switching must be considered when studying ferroelectrics in general.

Ferroelectric domain kinetics in congruent LiTaO3

Recent years have seen the successful use of continuum models--based on the minimization of an appropriate nonconvex free energy--to explain some of the complicated microstructure which is commonly observed in shape memory alloys, magnetostrictive materials, ferro- electrics, etc. However, due to their inherent static nature such models cannot provide insight into important dynamic phenomena such as: the growth of microstructure, the evolution of phase boundaries, or the eventual fate of metastable structures. We describe the behavior of some simple dynamical models of shape-memory alloys which display the formation of microstructure. The focus is on models whose underlying bulk free energy do not attain a minimum, possessing sequences of configurations with finer and finer microstructure that converge weakly to nonminimizing states. The effects of viscoelastic damping on the stability of steady state solutions, the propagation of phase boundaries, and the long-time approach to minimum energy states is discussed.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Pieter J. Swart

Papers

The local atomic structure and phonons in Ba0.5Sr0.5TiO3

Observation and mobility study of single 180° domain wall using a near-field scanning optical microscope

NetworkX Documentation Release 1.0.dev1415

Ferroelectric domain kinetics in congruent LiTaO3

Evolution of microstructure in displacive phase transformations