There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

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

BACKGROUND Heat and electricity are two forms of energy that are at opposite ends of a spectrum Heat is ubiquitous, but with low quality, whereas electricity is versatile, but its production is demanding Thermoelectrics offers a simple and environmentally friendly solution for direct heat-to-electricity conversion A thermoelectric (TE) device can directly convert heat emanating from the Sun, radioisotopes, automobiles, industrial sectors, or even the human body to electricity Electricity also can drive a TE device to work as a solid-state heat pump for distributed spot-size refrigeration TE devices are free of moving parts and feasible for miniaturization, run quietly, and do not emit greenhouse gasses The full potential of TE devices may be unleashed by working in tandem with other energy-conversion technologies Thermoelectrics found niche applications in the 20th century, especially where efficiency was of a lower priority than energy availability and reliability Broader (beyond niche) application of thermoelectrics in the 21st century requires developing higher-performance materials The figure of merit, ZT, is the primary measure of material performance Enhancing the ZT requires optimizing the adversely interdependent electrical resistivity, Seebeck coefficient, and thermal conductivity, as a group On the microscopic level, high material performance stems from a delicate concert among trade-offs between phase stability and instability, structural order and disorder, bond covalency and ionicity, band convergence and splitting, itinerant and localized electronic states, and carrier mobility and effective mass ADVANCES Innovative transport mechanisms are the fountain of youth of TE materials research In the past two decades, many potentially paradigm-changing mechanisms were identified, eg, resonant levels, modulation doping, band convergence, classical and quantum size effects, anharmonicity, the Rashba effect, the spin Seebeck effect, and topological states These mechanisms embody the current states of understanding and manipulating the interplay among the charge, lattice, orbital, and spin degrees of freedom in TE materials Many strategies were successfully implemented in a wide range of materials, eg, V2VI3 compounds, VVI compounds, filled skutterudites and clathrates, half-Heusler alloys, diamond-like structured compounds, Zintl phases, oxides and mixed-anion oxides, silicides, transition metal chalcogenides, and organic materials In addition, advanced material synthesis and processing techniques, for example, melt spinning, self-sustaining heating synthesis, and field-assisted sintering, helped reach a much broader phase space where traditional metallurgy and melt-growth recipes fell short Given the ubiquity of heat and the modular aspects of TE devices, these advances ensure that thermoelectrics plays an important role as part of a solutions package to address our global energy needs OUTLOOK The emerging roles of spin and orbital states, new breakthroughs in multiscale defect engineering, and controlled anharmonicity may hold the key to developing next generation TE materials To accelerate exploring the broad phase space of higher multinary compounds, we need a synergy of theory, machine learning, three-dimensional printing, and fast experimental characterizations We expect this synergy to help refine current materials selection and make TE materials research more data driven We also expect increasing efforts to develop high-performance materials out of nontoxic and earth-abundant elements The desire to move away from Freon and other refrigerant-based cooling should shift TE materials research from power generation to solid-state refrigeration International round-robin measurements to cross-check the high ZT values of emerging materials will help identify those that hold the most promise We hope the renewable energy landscape will be reshaped if the recent trend of progress continues into the foreseeable future

http://science.sciencemag.org/content/sci/357/6358/eaak9997.full.pdf

Advances in thermoelectric materials research: Looking back and moving forward

Recently, Wireless Sensor Networks (WSNs) have attracted lot of attention due to their pervasive nature and their wide deployment in Internet of Things, Cyber Physical Systems, and other emerging areas. The limited energy associated with WSNs is a major bottleneck of WSN technologies. To overcome this major limitation, the design and development of efficient and high performance energy harvesting systems for WSN environments are being explored. We present a comprehensive taxonomy of the various energy harvesting sources that can be used by WSNs. We also discuss various recently proposed energy prediction models that have the potential to maximize the energy harvested in WSNs. Finally, we identify some of the challenges that still need to be addressed to develop cost-effective, efficient, and reliable energy harvesting systems for the WSN environment.

Energy harvesting in wireless sensor networks: A comprehensive review

The miltifractal properties and scaling behaviour of the exchange rate variations of the Iranian rial against the US dollar from a daily perspective is numerically investigated. For this purpose the multifractal detrended fluctuation analysis (MF-DFA) is used. Through multifractal analysis, the scaling exponents, generalized Hurst exponents, generalized fractal dimensions and singularity spectrum are derived. Moreover, contribution of two major sources of multifractality, that is, fat-tailed probability distributions and nonlinear temporal correlations are studied.

A multifractal detrended fluctuation description of Iranian rial–US dollar exchange rate

A Multifractal Detrended Fluctuation Description of Iranian Rial-US Dollar Exchange Rate

https://iopscience.iop.org/article/10.7567/JJAP.56.05DA04/pdf

Thermoelectric silicides: A review

We report an empirical study of Tehran Price Index (TEPIX). To analyze our data we use various methods like as, rescaled range analysis (R/S), modified rescaled range analysis (Lo’s method), Detrended Fluctuation Analysis (DFA) and generalized Hurst exponents analysis. Based on numerical results, the scaling range of TEPIX returns is specified, long memory effect or long range correlation property in this market is investigated, characteristic exponent for probability distribution function of TEPIX returns is derived and finally the stage of development in Tehran Stock Exchange is determined.

https://arxiv.org/pdf/physics/0412067.pdf

Application of multifractal measures to Tehran price index

We use multifractal detrended fluctuation analysis (MF-DFA) to numerically investigate correlation, persistence, multifractal properties and scaling behavior of the hourly spot prices for the Spain electricity exchange-Compania O Peradora del Mercado de Electricidad (OMEL). Through multifractal analysis, fluctuations behavior, the scaling exponents and generalized Hurst exponents are studied. Moreover, contribution of fat-tailed probability distributions and nonlinear temporal correlations to multifractality is studied.

Payam Norouzzadeh

Papers

A multifractal detrended fluctuation description of Iranian rial–US dollar exchange rate

A Multifractal Detrended Fluctuation Description of Iranian Rial-US Dollar Exchange Rate

Thermoelectric silicides: A review

Application of multifractal measures to Tehran price index

Anti-correlation and multifractal features of Spain electricity spot market