Harry Eugene Stanley

Bio: Harry Eugene Stanley is an academic researcher from Boston University. The author has contributed to research in topics: Population & Interdependent networks. The author has an hindex of 20, co-authored 42 publications receiving 5722 citations.

Fractal Concepts in Surface Growth

Abstract: This book brings together two of the most exciting and widely studied subjects in modern physics: namely fractals and surfaces. To the community interested in the study of surfaces and interfaces, it brings the concept of fractals. To the community interested in the exciting field of fractals and their application, it demonstrates how these concepts may be used in the study of surfaces. The authors cover, in simple terms, the various methods and theories developed over the past ten years to study surface growth. They describe how one can use fractal concepts successfully to describe and predict the morphology resulting from various growth processes. Consequently, this book will appeal to physicists working in condensed matter physics and statistical mechanics, with an interest in fractals and their application. The first chapter of this important new text is available on the Cambridge Worldwide Web server: http://www.cup.cam.ac.uk/onlinepubs/Textbooks/textbookstop.html

Water: A Tale of Two Liquids

Abstract: Water is the most abundant liquid on earth and also the substance with the largest number of anomalies in its properties. It is a prerequisite for life and as such a most important subject of current research in chemical physics and physical chemistry. In spite of its simplicity as a liquid, it has an enormously rich phase diagram where different types of ices, amorphous phases, and anomalies disclose a path that points to unique thermodynamics of its supercooled liquid state that still hides many unraveled secrets. In this review we describe the behavior of water in the regime from ambient conditions to the deeply supercooled region. The review describes simulations and experiments on this anomalous liquid. Several scenarios have been proposed to explain the anomalous properties that become strongly enhanced in the supercooled region. Among those, the second critical-point scenario has been investigated extensively, and at present most experimental evidence point to this scenario. Starting from very low ...

On growth and form : fractal and non-fractal patterns in physics

Abstract: A. "The Course".- Growth: An Introduction.- Form: An Introduction to Self-Similarity and Fractal Behavior.- Scale-Invariant Diffusive Growth.- DLA in the Real World.- Percolation and Cluster Size Distribution.- Scaling Properties of the Probability Distribution for Growth Sites.- Computer Simulation of Growth and Aggregation Processes.- Rate Equation Approach to Aggregation Phenomena.- Experimental Methods for Studying Fractal Aggregates.- On the Rheology of Random Matter.- Development, Growth, and Form in Living Systems.- B. "The Seminars".- Aggregation of Colloidal Silica.- Dynamics of Fractals.- Fractal Viscous Fingers: Experimental Results.- Wetting Induced Aggregation.- Light Scattering from Aggregating Systems: Static, Dynamic (QELS) and Number Fluctuations.- Flocculation and Gelation in Cluster Aggregation.- Branched Polymers.- Dynamics of Aggregation Processes.- Fractal Properties of Clusters during Spinodal Decomposition.- Kinetic Gelation.- Dendritic Growth by Monte Carlo.- Flow through Porous Materials.- Crack Propagation and Onset of Failure.- The Theta Point.- Field Theories of Walks and Epidemics.- Transport Exponents in Percolation.- Non-Universal Critical Exponents for Transport in Percolating Systems.- Levy Walks Versus Levy Flights.- Growth Perimeters Generated by a Kinetic Walk: Butterflies, Ants and Caterpillars.- Asymptotic Shape of Eden Clusters.- Occupation Probability Scaling in DLA.- Fractal Singularities in a Measure and "How to Measure Singularities on a Fractal".- List of Participants.

Random fluctuations and pattern growth : experiments and models

Abstract: * Contents *.- Course 1: Random Fluctuations and Transport.- Some Themes and Common Tools.- Structure, Elasticity and Thermal Properties of Silica Networks.- Anomalous Diffusion and Fractons in Disordered Structures.- Fractons in Real Fractals.- Anomalous Transport in Disordered Structures: Effect of Additional Disorder.- Information Exponents for Transport in Regular Lattices and Fractals.- Anomalous Transport in Random Linear Structures.- Course 2: Random Growth Patterns: Aggregation.- Morphological Transitions in Pattern Growth Phenomena.- Visualization and Characterization of Microparticle Growth Patterns.- Origin of Fractal Roughness in Synthetic and Natural Materials.- Electrodeposition.- Course 3: Random Fluctuations in Fluid Systems.- Flow Patterns in Porous Media.- Viscous Fingering in a Circular Geometry.- Construction of a Radial Hele-Shaw Cell.- Growth and Viscous Fingers on Percolating Porous Media.- Structure of Miscible and Immiscible Displacement Fronts in Porous Media.- Dynamics of Invasion Percolation.- Course 4: Random Fluctuations in Liquid Crystals.- Directional Solidification of Liquid Crystals.- Interfacial Instabilities of Condensed Phase Domains in Lipid Monolayers.- Pattern Formation of Molecules Adsorbing on Lipid Monolayers.- Course 5: Random Fluctuations in "Solid" Materials.- to Dense Branching Morphology.- The Material Factors Leading to Dense Branching Morphology in Al:Ge Thin Films.- Theoretical Aspects of Polycrystalline Pattern Growth in Al/Ge Films.- Pattern Formation in Dendritic Solidification.- Relaxation of Excitations in Porous Solids.- Soap Bubbles-A Simple Model System for Solids.- Course 6: Fracture of Disordered Solids.- to Modern Ideas on Fracture Patterns.- Rupture in Random Media.- Fracture Experiments on Monolayers of Microspheres.- Simple Models for Colloidal Aggregation, Dielectric Breakdown and Mechanical Breakdown Patterns.- Dielectric Breakdown Patterns with a Growth Probability Threshold.- Course 7: Fluctuation Phenomena in Membranes and Random Surfaces.- The Statistical Mechanics of Crumpled Membranes.- Fluctuations in Fluid and Hexatic Membranes.- Unbinding Transition and Mutual Adhesion in General of DGDG Membranes.- Scaling Properties of Interfaces and Membranes.- Surfactants in Solution: An Experimental Tool to Study Fluctuating Surfaces.- Course 8: Convection, Turbulence and Multifractals.- to Convection.- Onset of Convection.- Waves and Plumes in Thermal Convection.- An Introduction to Multifractal Distribution Functions.- Multifractals in Convection and Aggregation.- Multifractal Analysis of Sedimentary Rocks.- Phase Transition on DLA.- Course 9: Random Fluctuations and Complex Systems.- Disordered Patterns in Deterministic Growth.- 1/f Versus 1/f? Noise.- A Simple Model of Molecular Evolution.- Scale Invariant Spacial and Temporal Fluctuations in Complex Systems.- The Upper Critical Dimension and ?-Expansion for Self-Organized Critical Phenomena.- Self-Organized Criticality and the Origin of Fractal Growth.- Finite Lifetime Effects in Models of Epidemics.- to Droplet Growth Processes: Simulations, Theory and Experiments.- List of Participants.

Robustness of a network formed by n interdependent networks with a one-to-one correspondence of dependent nodes.

Abstract: Many real-world networks interact with and depend upon other networks. We develop an analytical framework for studying a network formed by n fully interdependent randomly connected networks, each composed of the same number of nodes N. The dependency links connecting nodes from different networks establish a unique one-to-one correspondence between the nodes of one network and the nodes of the other network. We study the dynamics of the cascades of failures in such a network of networks (NON) caused by a random initial attack on one of the networks, after which a fraction p of its nodes survives. We find for the fully interdependent loopless NON that the final state of the NON does not depend on the dynamics of the cascades but is determined by a uniquely defined mutual giant component of the NON, which generalizes both the giant component of regular percolation of a single network (n=1) and the recently studied case of the mutual giant component of two interdependent networks (n=2). We also find that the mutual giant component does not depend on the topology of the NON and express it in terms of generating functions of the degree distributions of the network. Our results show that, for any n≥2 there exists a critical p=p(c)>0 below which the mutual giant component abruptly collapses from a finite nonzero value for p≥p(c) to zero for p 2, a RR NON is stable for any n with p(c)<1). This results arises from the critical role played by singly connected nodes which exist in an ER NON and enhance the cascading failures, but do not exist in a RR NON.

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

Abstract: 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。

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Epidemic processes in complex networks

Abstract: Complex networks arise in a wide range of biological and sociotechnical systems. Epidemic spreading is central to our understanding of dynamical processes in complex networks, and is of interest to physicists, mathematicians, epidemiologists, and computer and social scientists. This review presents the main results and paradigmatic models in infectious disease modeling and generalized social contagion processes.

Traffic and related self-driven many-particle systems

Abstract: Since the subject of traffic dynamics has captured the interest of physicists, many surprising effects have been revealed and explained. Some of the questions now understood are the following: Why are vehicles sometimes stopped by ``phantom traffic jams'' even though drivers all like to drive fast? What are the mechanisms behind stop-and-go traffic? Why are there several different kinds of congestion, and how are they related? Why do most traffic jams occur considerably before the road capacity is reached? Can a temporary reduction in the volume of traffic cause a lasting traffic jam? Under which conditions can speed limits speed up traffic? Why do pedestrians moving in opposite directions normally organize into lanes, while similar systems ``freeze by heating''? All of these questions have been answered by applying and extending methods from statistical physics and nonlinear dynamics to self-driven many-particle systems. This article considers the empirical data and then reviews the main approaches to modeling pedestrian and vehicle traffic. These include microscopic (particle-based), mesoscopic (gas-kinetic), and macroscopic (fluid-dynamic) models. Attention is also paid to the formulation of a micro-macro link, to aspects of universality, and to other unifying concepts, such as a general modeling framework for self-driven many-particle systems, including spin systems. While the primary focus is upon vehicle and pedestrian traffic, applications to biological or socio-economic systems such as bacterial colonies, flocks of birds, panics, and stock market dynamics are touched upon as well.