A novel ACO algorithm for optimization via reinforcement and initial bias

In this paper, we introduce the MAF-ACO algorithm, which emulates the foraging behavior of ants found in nature. In addition to the usual pheromone model present in ACO algorithms, we introduce an incremental learning component. We view the components of the MAF-ACO algorithm as stochastic approximation algorithms and use the ordinary differential equation (o.d.e.) method to analyze their convergence. We examine how the local stigmergic interaction of the individual ants results in an emergent dynamic programming framework. The MAF-ACO algorithm is also applied to the multi-stage shortest path problem and the traveling salesman problem. Research of Prof. V.S. Borkar was supported in part by grant no. III.5(157)/99-ET and a J.C. Bose Fellowship from the Department of Science and Technology, Government of India.     

基于中分辨率TM数据的湿地水生植被提取

利用湿地水生植被生长旺盛、光谱反射较强、光谱信息比较丰富的8月份中分辨率Landsat TM和ETM+多光谱遥感影像,采用面向对象的分类方法,进行野鸭湖湿地水生植被的提取。研究表明:在提取过程中,通过对原始影像进行主成分变换和穗帽变换,将主要信息与噪声分离,不仅减小了数据冗余和波段间的相关性,而且增大了影像上湿地水生植被与其他地物类型光谱和空间信息的差异性,并结合野外水生植被光谱特征分析,选择归一化植被指数NDVI与归一化水体指数NDWI辅助分类,构建特征波段或波段组合,然后,确定适当的隶属度函数和阈值范围,构建分类决策树,完成湿地水生植被的自动分类,提高了影像分割与面向对象分类的精度,取得了较为理想的湿地水生植被提取结果。2002年和2008年两景影像的总体分类精度分别达到86.5%和85.44%,表明中分辨率TM影像可以满足湿地水生植被提取的需要,又因为其具有较高的波谱分辨率、极为丰富的信息量、相对较低的价格、长时间序列,可以作为近20a湿地水生植被提取和动态变化监测的主要数据源。     

Evaluation of different domain-based methods in protein interaction prediction

Protein-protein interactions (PPIs) play an important role in many biological functions. PPIs typically involve binding between domains, the basic units of protein folding, evolution and function. Identifying domain-domain interactions (DDIs) would aid understanding PPI networks. Recently, many computational methods aimed to infer DDIs from databases of interacting proteins and subsequently used the inferred DDIs to predict new PPIs. We attempt to describe systematically current domain-based approaches including the association method, maximum likelihood estimation and parsimonious explanation method. The performance of these methods at inferring DDIs and predicting PPIs was evaluated comparatively. We observe that each method generates artefacts in certain situations and discuss biases in the available benchmark sets.     

Allocation of environmental burdens in co-product systems: Process and product-related burdens (part 2)

ISO 14041 requires that allocation by physical causality must reflect the quantitative changes in product outputs or functions and will not necessarily be in proportion to simple physical measure such as mass. This paper examines the instances where physical causality can be represented by mass. However, it also goes further than ISO to demonstrate that the type of causality in the system is not necessarily always the same and can change depending on the way the system is operated. Whole system modelling and the marginal allocation approach are used to identify the correct type of causality for different operating states of the system and the corresponding changes in the environmental burdens. This is generally not possible with the other allocation methods, also examined in this paper. Both process- and product-related burdens are considered and the approach is illustrated by a reference to an existing system producing five boron co-products     

农户生态系统定量分析和演替导向的研究

文章研究了农户生态系统定量分析和演替导向方法,对线性规划方法有新的应用和认识,提出了制约强度、制约幅度、制约作用量的新概念,并首次用于对农户生态系统管理中的限制因素定量分析,从而指导农户生态系统的演替,并取得明显的实践效果。同时,对线性规划方法在农业生态系统分析中的进一步应用进行了讨论。     

End-of-Life Infrastructure Economics for "Clean Vehicles" in the United States

Rising fuel prices and concern over emissions are prompting automakers and legislators to introduce and evaluate "clean vehicles" throughout the United States. Hybrid electric vehicles (HEVs) are now on the roads, electric vehicles (EVs) have been test marketed, and niche vehicles such as high-fuel-economy microcars are being considered for introduction. As these vehicles proliferate and mature, they will eventually reach their end of life (EOL). In the United States, an extensive recycling infrastructure exists for conventional, internal combustion engine (ICE) vehicles. Its primary constituents are the disassembler and the shredder. These industries, as well as battery recyclers, are expected to play integral roles in the EOL processing of clean vehicles.
A model of the automobile-recycling infrastructure and goal programming techniques are used to assess the materials streams and process profitabilities for several different clean vehicles. Two-seat EVs with lead-acid or NiMH batteries are compared with two- and four-seat HEVs and microcars. Changes to the nonferrous content in the vehicle bodies are explored and compared for the effect on processing profit-ability. Despite limitations associated with the linearity of goal programming techniques, application of this tool can still provide informative first-order results. Results indicate that although these clean vehicles may not garner the same profit levels as conventional ICE vehicles, they are profitable to process if there are markets for parts and if there are sufficient quantities of nonferrous materials.     

Dynamics alignment: comparison of protein dynamics in the SCOP database

A novel methodology for comparison of protein dynamics is presented. Protein dynamics is calculated using the Gaussian network model and the modes of motion are globally aligned using the dynamic programming algorithm of Needleman and Wunsch, commonly used for sequence alignment. The alignment is fast and can be used to analyze large sets of proteins. The methodology is applied to the four major classes of the SCOP database: "all alpha proteins," "all beta proteins," "alpha and beta proteins," and "alpha/beta proteins". We show that different domains may have similar global dynamics. In addition, we report that the dynamics of "all alpha proteins" domains are less specific to structural variations within a given fold or superfamily compared with the other classes. We report that domain pairs with the most similar and the least similar global dynamics tend to be of similar length. The significance of the methodology is that it suggests a new and efficient way of mapping between the global structural features of protein families/subfamilies and their encoded dynamics.     

Decision science for effective management of populations subject to stochasticity and imperfect knowledge

Many species are threatened by human activity through processes such as habitat modification, water management, hunting, and introduction of invasive species. These anthropogenic threats must be mitigated as efficiently as possible because both time and money available for mitigation are limited. For example, it is essential to address the type and degree of uncertainties present to derive effective management strategies for managed populations. Decision science provides the tools required to produce effective management strategies that can maximize or minimize the desired objective(s) based on imperfect knowledge, taking into account stochasticity. Of particular importance are questions such as how much of available budgets should be invested in reducing uncertainty and which uncertainties should be reduced. In such instances, decision science can help select efficient environmental management actions that may be subject to stochasticity and imperfect knowledge. Here, we review the use of decision science in environmental management to demonstrate the utility of the decision science framework. Our points are illustrated using examples from the literature. We conclude that collaboration between theoreticians and practitioners is crucial to maximize the benefits of decision science’s rational approach to dealing with uncertainty.     

Generalized Verlet Algorithm for Efficient Molecular Dynamics Simulations with Long-range Interactions

For the purpose of molecular dynamics simulations of large biopolymers we have developed a new method to accelerate the calculation of long-range pair interactions (e.g. Coulomb interaction). The algorithm introduces distance classes to schedule updates of non-bonding interactions and to avoid unnecessary computations of interactions between particles which are far apart. To minimize the error caused by the updating schedule, the Verlet integration scheme has been modified. The results of the method are compared to those of other approximation schemes as well as to results obtained by numerical integration without approximation. For simulation of a protein with 12 637 atoms our approximation scheme yields a reduction of computer time by a factor of seven. The approximation suggested can be implemented on sequential as well as on parallel computers. We describe an implementation on a (Transputer-based) MIMD machine with a systolic ring architecture.