Landscape of wave focusing and localization at low frequencies

High-contrast scattering problems are special among classical wave systems as they allow for strong wave focusing and localization at low frequencies. We use an asymptotic framework to develop a landscape theory for high-contrast systems that resonate in a subwavelength regime. Our from-first-principles asymptotic analysis yields a characterization in terms of the generalized capacitance matrix, giving a discrete approximation of the three-dimensional scattering problem. We develop landscape theory for the generalized capacitance matrix and use it to predict the positions of three-dimensional wave focusing and localization in random and non-periodic systems of subwavelength resonators.     

Rapid Perturbation of Free‐Energy Landscapes: From In Vitro to In Vivo

Biological systems are often studied under the most “physiological” conditions possible. However, purposeful perturbation of biological systems can provide much information about their dynamics, robustness, and function. Such perturbations are particularly easy to apply at the interface of molecular biophysics and cellular biology, at which complex and highly regulated networks emerge from the behavior of individual biomolecules. Due to the size of diffusion coefficients and the length scale of biomolecules, the fastest timescales at this interface extend to below a microsecond. Thus perturbations must be induced and detected rapidly. We focus on examples of proteins and RNAs interacting with themselves (folding) or one another (binding, signaling). Beginning with general principles that have been learned from simple models and perturbation experiments in vitro, we progress to more complex environments that mimic aspects of the living cell, and finally rapid perturbation experiments in living cells. On the experimental side we highlight in particular two classes of rapid perturbation methods (nanoseconds to seconds) that have been traditionally employed in biophysical chemistry, but that will become increasingly important in cell biology and in vivo: fast relaxation techniques and phase‐sensitive modulation techniques. These techniques are now increasingly married with imaging to produce a spatiotemporal map of biomolecular stability, dynamics and, in the near future, interaction networks inside cells. Many important chemical processes occur on biologically fast timescales, and yet have important ramifications for slower biological networks.     

On the use of big-bang method to generate low-energy structures of atomic clusters modeled with pair potentials of different ranges

The efficiency of the so-called big-bang method for the optimization of atomic clusters is analysed in detail for Morse pair potentials with different ranges; here, we have used Morse potentials with four different ranges, from long- ρ = 3) to short-ranged ρ = 14) interactions. Specifically, we study the efficacy of the method in discovering low-energy structures, including the putative global minimum, as a function of the potential range and the cluster size. A new global minimum structure for long-ranged ρ = 3) Morse potential at the cluster size of n= 240 is reported. The present results are useful to assess the maximum cluster size for each type of interaction where the global minimum can be discovered with a limited number of big-bang trials.     

Are the native states of proteins kinetic traps?

Four proteins were selected to represent each of the four different CATH classes and, for each protein, three decoys were constructed with structures totally alien to the native state. The decoys were scored against the native state with the help of the AMBER force field, using three measures: the average energy, the average fluctuation and the resistance to a heat pulse. Two sets of simulations were performed, one with explicit solvent and the other with implicit solvent. The overall conclusion is that, of these three measures, the most successful in picking out the native states was the last one, since the native structures take a consistently longer time to be destabilized in this manner. However, the general conclusion is also that none of the measures is completely effective in discriminating all the decoys, a result that supports other studies, according to which the native state is reached by a kinetic step.     

千岛湖被子植物枝叶性状分化及其与种多度的关系

种间生态位分化是物种共存的重要原因,了解种间生态位分化特征对于推测物种多样性维持机制具有重要意义.植物的种间功能性状分化在一定程度上能够反映其生态位分化,进而导致植物在群落内的适合度差异.据此,本研究针对千岛湖地区75种常见木本被子植物,分析了8个与水分输导、资源获取和利用策略相关的功能性状分化,及其与物种多度的关系.主成分分析表明,种间功能性状的分化主要发生在比叶面积、叶绿素含量以及叶气孔密度上.8个性状中有5个,即叶绿素含量、叶片厚度、叶面积、比叶面积和最大树高具有一定程度的系统发育保守性(即Blombergs K的p0.05).功能性状间的相关性广泛存在,且在使用系统发育独立对比方法(phylogenetic independent contrast,PIC)控制系统发育的影响后,相关性大多仍然显著.单个性状以及所有性状的主成分1和主成分2与物种多度间均没有显著相关性.结果表明:千岛湖地区片段化次生马尾松林内木本被子植物的功能性状分化受系统发育和进化历史共同影响;且性状分化发生在主要的环境资源梯度(即光照和水分)上;但性状对处于演替过程中的片段化森林群落内的物种多度不一定会产生重要影响.     

快速城市化背景下宁波北仑绿地系统演化及生态服务响应

城市绿地是城市自然生态系统的重要组成部分, 我国东南沿海地区是城市化速度最快的区域之一, 快速城市化导致建设用地的大量增加, 并引起区域绿地景观格局及生态价值的显著变化. 本文选取东南沿海中部的宁波市北仑区为研究区域, 以其1990、1995、2000、2005、2010和2015年6期土地利用变化数据为基础提取绿地, 借助ArcGIS和Fragstats软件, 应用景观生态学方法和基于专家知识的生态系统服务价值化方法对快速城市化背景下北仑区绿地景观动态演化及其生态价值变化进行了研究. 结果表明: (1)绿地是北仑区的主要景观类型, 1990~2015年间快速城市化导致北仑区1406hm2绿地转化为建设用地; (2)北仑区绿地景观异质性减弱, 趋于集中式发展, 整体破碎度降低; (3)截止2015年, 绿地的生态服务价值总量比1990年减少了6%, 生态环境出现恶化, 主要是建设用地占用绿地导致生态总价值下降; (4)北仑区绿地系统生态价值等级由中心向外围降低呈不规则环状, 且高价值区逐渐向东南方向减少并转变为较低价值区.     

基于Quickbird影像的中小城市绿地景观格局分析——以乐清市为例

摘要：基于2009年Quickbird影像数据解译获得的乐清市城区绿地分布图,在GIS的支持下,运用景观生态学的原理和方法,对城区绿地景观格局进行了较系统的分析.结果表明：绿地景观结构不尽合理,以公园绿地为优势类型,道路绿地与居住绿地明显偏少;全区绿地多样性指数偏低,绿地类型不够丰富;绿地景观整体破碎度较高,其中新区的破碎度高于老区;绿地斑块分维数偏低,斑块形状较规则,缺乏自然形状,人工痕迹较重.论文对分析结果进行了讨论,并针对上述问题提出了相应的对策和建议,以期能为其他中小城市绿地格局分析与绿地建设提供参考.     

场地自然环境与景观构筑物结构形态的互动

自然环境是场地的构成要素之一,也是建筑物赖以存在的物质前提.有关自然环境与建筑之间的关系,通常存在2类观点,即认为两者为异质系统以及将两者视为有机整体.将此2种观点引入景观构筑物这类特殊景观建筑的设计中,深入剖析不同视角主导下截然不同的结构构思与表现方法,并以翔实而丰富的案例进行佐证.研究表明,场地自然环境是景观构筑物结构构思的制约因素与结构形态的外在形式动力,而景观构筑物以最终的结构形态反作用于自然环境,表达不同的环境主张.两者之间的互动有效拓展了景观构筑物的设计思想与方法,推动自然环境与建筑的关系朝着良性、可持续的方向发展.     

Thermodynamic Consistency of the Cushman Method of Computing the Configurational Entropy of a Landscape Lattice

There has been a recent surge of interest in theory and methods for calculating the entropy of landscape patterns, but relatively little is known about the thermodynamic consistency of these approaches. I posit that for any of these methods to be fully thermodynamically consistent, they must meet three conditions. First, the computed entropies must lie along the theoretical distribution of entropies as a function of total edge length, which Cushman showed was a parabolic function following from the fact that there is a normal distribution of permuted edge lengths, the entropy is the logarithm of the number of microstates in a macrostate, and the logarithm of a normal distribution is a parabolic function. Second, the entropy must increase over time through the period of the random mixing simulation, following the expectation that entropy increases in a closed system. Third, at full mixing, the entropy will fluctuate randomly around the maximum theoretical value, associated with a perfectly random arrangement of the lattice. I evaluated these criteria in a test condition involving a binary, two-class landscape using the Cushman method of directly applying the Boltzmann relation (s = klogW) to permuted landscape configurations and measuring the distribution of total edge length. The results show that the Cushman method directly applying the classical Boltzmann relation is fully consistent with these criteria and therefore fully thermodynamically consistent. I suggest that this method, which is a direct application of the classical and iconic formulation of Boltzmann, has advantages given its direct interpretability, theoretical elegance, and thermodynamic consistency.