A power law in the exploratory behavior of the <Emphasis Type="Italic">Physarum</Emphasis> plasmodium

The plasmodium of Physarum polycephalum is a unicellular giant amoeba that grows up to macroscopic scale under appropriate condition, and is known to its computational abilities. In this study, we tried to observe the long-term exploratory behavior of the plasmodium in an open environment and to evaluate its efficiency. For this purpose, we developed an experimental system with an extendable substrate. As a result of the experiment, we found that the frequency distribution of the speed of plasmodial locomotion is fitted by power function. By simulation, we further tried to estimate the efficiency of the exploration implemented with the patterns from the plasmodium, and confirmed that it is actually effective.     

A synthetic genetic circuit whose signal-response curve is temperature-tunable from band-detection to sigmoidal behaviour

Programming new cellular functions by using synthetic gene circuits is a key goal in synthetic biology, and an important element of this process is the ability to couple to the information processing systems of the host cell using synthetic systems with various signal-response characteristics. Here, we present a synthetic gene system in Escherichia coli whose signal-response curve may be tuned from band detection (strongest response within a band of input concentrations) to a switch-like sigmoidal response, simply by altering the temperature. This change from a band-detection response to a sigmoidal response has not previously been implemented. The system allows investigation of a range of signal-response behaviours with minimal effort: a single system, once inserted into the cells, provides a range of response curves without any genetic alterations or replacement with other systems. By altering its output, the system may couple to other synthetic or natural genetic circuits, and thus serve as a useful modular component. A mathematical model has also been developed which captures the essential qualitative behaviours of the circuit.     

Computational Ability of Cells based on Cell Dynamics and Adaptability

Learning how biological systems solve problems could help to design new methods of computation. Information processing in simple cellular organisms is interesting, as they have survived for almost 1 billion years using a simple system of information processing. Here we discuss a well-studied model system: the large amoeboid Physarum plasmodium. This amoeba can find approximate solutions for combinatorial optimization problems, such as solving a maze or a shortest network problem. In this report, we describe problem solving by the amoeba, and the computational methods that can be extracted from biological behaviors. The algorithm designed based on Physarum is both simple and useful. Tutorial series of three invited papers

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Programmable reconfiguration of <Emphasis Type="Italic">Physarum</Emphasis> machines

Plasmodium of Physarum polycephalum is a large cell capable of solving graph-theoretic, optimization and computational geometry problems due to its unique foraging behavior. Also the plasmodium is a unique biological substrate that mimics universal storage modification machines, namely the Kolmogorov–Uspensky machine. In the plasmodium implementation of the storage modification machine data are represented by sources of nutrients and memory structure by protoplasmic tubes connecting the sources. In laboratory experiments and simulation we demonstrate how the plasmodium-based storage modification machine can be programmed. We show execution of the following operations with the active zone (where computation occurs): merge two active zones, multiply active zone, translate active zone from one data site to another, direct active zone. Results of the paper bear two-fold value: they provide a basis for programming unconventional devices based on biological substrates and also shed light on behavioral patterns of the plasmodium.     

A methodology to incorporate product mix variations in cellular manufacturing

The identification of part families and machine groups that form the cells is a major step in the development of a cellular manufacturing system and, consequently, a large number of concepts, theories and algorithms have been proposed. One common assumption for most of these cell formation algorithms is that the product mix remains stable over a period of time. In today’s world, the market demand is being shaped by consumers resulting in a highly volatile market. This has given rise to a new class of products characterized by low volume and high variety. To incorporate product mix changes into an existing cellular manufacturing system many important issues have to be tackled. In this paper, a methodology to incorporate new parts and machines into an existing cellular manufacturing system has been presented. The objective is to fit the new parts and machines into an existing cellular manufacturing system thereby increasing machine utilization and reducing investment in new equipment.     

Effects of cell size and configuration in cellular automata based prey–predator modelling

Cellular automata (CA) have shown to be a viable approach in ecological modelling, in particular when dealing with local interactions between species and their environment. In CA modelling complex patterns emerge on a global scale through the evolution of interactions at a local level. Although the validity of a cell-based approach has successfully been demonstrated in numerous cases, very few studies have been reported that address the effects of cell size and configuration on the behaviours of CA-based models. In this paper, the performance of a cellular automaton based prey–predator model (EcoCA) developed by the author was first calibrated against the classical Lotka–Volterra (LV) model. The model was then used to investigate effects of cell size and cellular configurations (viz. the ‘computational stencil’). By setting up systematic simulation scenarios it was observed that the choice of a particular cell size has a clear effect on the resulting spatial patterns, while different cellular configurations affect both spatial patterns and system stability. On the basis of these findings, it is proposed to use the principal spatial scale of the studied ecosystem as CA model cell size and to apply the Moore type cell configuration. Methods for identifying principal spatial scales have been developed and are presented here.     

Approximating Mexican highways with slime mould

Plasmodium of Physarum polycephalum is a single cell visible by unaided eye. During its foraging behavior the cell spans spatially distributed sources of nutrients with a protoplasmic network. The geometrical structure of the protoplasmic networks allows the plasmodium to optimize transport of nutrients between remote parts of its body. Assuming major Mexican cities are sources of nutrients that need to be distributed across Mexico, how much does the structure of the Physarum protoplasmic network correspond to the structure of Mexican Federal highway network? To address the issue we undertook a series of laboratory experiments with living P. polycephalum. We represent geographical locations of major cities (19 locations) by oat flakes, place a piece of plasmodium in the area corresponding to Mexico city, record the plasmodium’s foraging behavior and extract topology of the resulting nutrient transport networks. Results of our experiments show that the protoplasmic network formed by Physarum is isomorphic, subject to limitations imposed, to a network of principal highways. Ideas and results in the paper may contribute towards future developments in bio-inspired road planning.     

Rough set models of Physarum machines

In this paper, we consider transition system models of behaviour of Physarum machines in terms of rough set theory. A Physarum machine, a biological computing device implemented in the plasmodium of Physarum polycephalum (true slime mould), is a natural transition system. In the behaviour of Physarum machines, one can notice some ambiguity in Physarum motions that influences exact anticipation of states of machines in time. To model this ambiguity, we propose to use rough set models created over transition systems. Rough sets are an appropriate tool to deal with rough (ambiguous, imprecise) concepts in the universe of discourse.     

Implicit learning as a design strategy for learning games: Alert Hockey

Concussion education and prevention for youth hockey players has been an issue of recent concern amongst sport medicine practitioners and hockey’s administrative bodies. This article details the assessment of a sports-action hockey video game that aims to reduce the aggressive and negligent behaviours that can lead to concussions. The game, termed Alert Hockey, was designed to modify game playing behaviour by embedding an implicit teaching mechanism within the gameplay. In Alert Hockey, participants were expected to learn by simply playing to win, in contrast to playing to learn. We studied learning in an experimental simulated environment where the possibility to win the game was exaggerated as a consequence of desirable safety behaviours (positive learning group) and effectively reduced as a consequence of undesirable (negative learning group) behaviour. The positive learning group significantly improved their mean score on a composite behavioural indicator compared with no significant change amongst control group participants. The results demonstrate that implicit learning embedded in a sports-action game can lead to changes in game-play behaviour.     

A review of: “Posture. Sitting,standing, chair design and exercise.” By D. ZACHARKOW. (Springfield,IL: Charles C. Thomas, 1988.) [Pp. xxi + 433.] US$49·75. ISBN 0-398-05418-5.

Drivers experiencing rush hour congestion were interviewed using cellular telephones to study stress and coping responses. Measures were taken of each driver's predisposition to stress (trait stress) as well as their reactions to the experience of either low or high traffic congestion (state stress). Two interviews were conducted during the trip when drivers experienced both low and high congestion conditions. Although state stress was greatest for all drivers experiencing the high congestion condition, a trait X situation interaction was obtained, indicating that stress levels were highest for high trait stress drivers experiencing the congested roadway. In terms of trait coping behaviours, participants indicated a preference for direct over indirect behaviours. A greater variety of direct and indirect behaviours were reported in high congestion. Reports of aggressive behaviours showed the greatest increase from low to high congestion. Comments on the use of cellular telephones in methodology are offered.     

Activating constructive employee behavioural responses in a crisis: Examining the effects of pre‐crisis reputation and crisis communication strategies on employee voice behaviours

This study explores how organizational management can promote employee voice behaviours, as positive behavioural reactions with constructive ideas, in responding to organizational crisis. Using an experimental study (N = 640) among full‐time employees in the United States, the study found that pre‐crisis internal reputation and crisis communication strategies—accommodative response and stealing thunder—positively and directly affected constructive employee voice behaviours in a crisis situation. Furthermore, the study revealed how post‐crisis internal reputation mediates the influences of pre‐crisis internal reputation and stealing thunder on positive/constructive and negative/destructive employee voice behaviours. The findings of this study contribute to the theoretical development of crisis communication in the internal context of an organization, especially with respect to employee voice behaviours. The study also highlights an important practical implication for crisis managers who can activate and promote positive employee behaviour voices, thereby influencing leadership's strategic decision‐making in an organizational crisis.     

Efficient On-Line Frequency Allocation and Call Control in Cellular Networks

In this paper we consider communication issues arising in cellular (mobile) networks that utilize frequency division multiplexing (FDM) technology. In such networks, many users within the same geographical region can communicate simultaneously with other users of the network using distinct frequencies. The spectrum of available frequencies is limited; thus, efficient solutions to the frequency-allocation and the call-control problems are essential. In the frequency-allocation problem, given users that wish to communicate, the objective is to minimize the required spectrum of frequencies so that communication can be established without signal interference. The objective of the call-control problem is, given a spectrum of available frequencies and users that wish to communicate, to maximize the number of users served. We consider cellular, planar, and arbitrary network topologies. In particular, we study the on-line version of both problems using competitive analysis. For frequency allocation in cellular networks, we improve the best known competitive ratio upper bound of 3 achieved by the folklore Fixed Allocation algorithm, by presenting an almost tight competitive analysis for the greedy algorithm; we prove that its competitive ratio is between 2.429 and 2.5 . For the call-control problem, we present the first randomized algorithm that beats the deterministic lower bound of 3 achieving a competitive ratio between 2.469 and 2.651 for cellular networks. Our analysis has interesting extensions to arbitrary networks. Also, using Yao's Minimax Principle, we prove two lower bounds of 1.857 and 2.086 on the competitive ratio of randomized call-control algorithms for cellular and arbitrary planar networks, respectively.     

Real time modelling of the dynamic mechanical behaviour of PEMFC thanks to neural networks

Modelling complex dynamic mechanical systems, such as PEMFC, without any physical models is a difficult challenge but it could allow the monitoring of endurance tests of fuel cell systems. Neural networks are recognised as powerful numerical tools for predicting complex and nonlinear dynamic behaviours. They require only data limited to experimental inputs and outputs but the choice of an adapted architecture is critical. This paper presents a method for defining a neural network architecture optimised for the fuel cell systems. The associated experimental conditions specifying the vibration tests to train and validate were defined. They consist of swept sinus as well as random excitation forces. The resulting simulations are presented and analysed.     

Experiencing the Affective Diary

A diary is generally considered to be a book in which one keeps a regular record of events and experiences that have some personal significance. As such, it provides a useful means to privately express inner thoughts or to reflect on daily experiences, helping in either case to put them in perspective. Taking conventional diary keeping as our starting point, we have designed and built a digital diary, named Affective Diary, with which users can scribble their notes, but that also allows for bodily memorabilia to be recorded from body sensors and mobile media to be collected from users’ mobile phones. A premise that underlies the presented work is one that views our bodily experiences as integral to how we come to interpret and thus make sense of the world. We present our investigations into this design space in three related lines of inquiry: (1) a theoretical grounding for affect and bodily experiences; (2) a user-centred design process, arriving at the Affective Diary system; and (3) an exploratory end-user study of the Affective Diary with 4 users during several weeks of use. Through these three inquiries, our overall aim has been to explore the potential of a system that interleaves the physical and cultural features of our embodied experiences and to further examine what media-specific qualities such a design might incorporate. Concerning the media-specific qualities, the key appears to be to find a suitable balance where a system does not dictate what should be interpreted and, at the same time, lends itself to enabling the user to participate in the interpretive act. In the exploratory end-user study users, for the most part, were able to identify with the body memorabilia and together with the mobile data, it enabled them to remember and reflect on their past. Two of our subjects went even further and found patterns in their own bodily reactions that caused them to learn something about themselves and even attempt to alter their own behaviours.

Pairing computational and scaled physical models to determine permeability as a measure of cellular communication in micro- and nano-scale pericellular spaces

Cells, the living components of tissues, bathe in fluid. The pericellular fluid environment is a challenge to study due to the remoteness and complexity of its nanoscale fluid pathways. The degree to which the pericellular fluid environment modulates the transport of mechanical and molecular signals between cells and across tissues is unknown. As a consequence, experimental and computational studies have been limited and/or highly idealized. In this study we apply a fundamental fluid dynamics technique to measure pericellular permeability through scaled-up physical models obtained from high resolution microscopy. We assess permeability of physiologic tissue by tying together data from parallel experimental and computational models that account for specific structures of the flow cavities and cellular structures therein (cell body, cell process, pericellular matrix). A healthy cellular network devoid of cellular structure is shown to exhibit permeability on the order of 2.8 × 10⁻¹⁶ m²; inclusion of cellular structures reduces permeability to the order of 10⁻¹⁷ to 10⁻¹⁸ m². These permeability studies provide not only unprecedented quantitative experimental measures of the pericellular fluid environment but also provide a novel measure of “infrastructural integrity” that likely influences the efficiency of the cellular communication network across the tissue. Funding: National Institutes of Health, The Whitaker Foundation.     

Spatio-temporal organization of a cellular automaton model for computer network

It was unveiled by Ren et al. [Comput. Phys. Comm. (2001)] that congestion transition emerges in cellular automaton models for computer network and this NaSch network model with Q=1 has similar behaviours as the NaSch traffic model with maximum velocity v_max=1. For these two NaSch models, the main difference lies in a node cell contained in the NaSch network model. In this paper, we will focus on our further investigation on spatio-temporal organization of the NaSch network model. More interesting phenomena of phase transition are discovered. Firstly, fundamental diagram illustrates that when Q>1 for the NaSch network model it is significantly different from its counterpart, i.e. the NaSch traffic model in a road traffic system. The addition of a node cell, which is allowed to have more than one packets, will lead to generating a new phase. Secondly, in order to characterize phase transition occurred in the NaSch network model, an order parameter is presented with the use of the time average density of nearest-neighbor pairs m. The computational results obtained show that criticality will disappear in a strict sense if noise exists. Finally, two other numerical features, i.e. spatial correlation functions G(r) and relaxation times τ, are analyzed so as to deeply describe behaviours near critical points.     

Models for quantitative distributed systems and multi-valued logics

We investigate weighted asynchronous cellular automata (wACAs) with weights in valuation monoids. These automata form a distributed extension of weighted finite automata (wFAs) and allow us to model concurrency. Valuation monoids are abstract weight structures that include semirings and (non-distributive) bounded lattices but also offer the possibility to model average behaviours. We prove that wACAs and wFAs which satisfy an I-diamond property are equally expressive. The main result of this paper gives a characterization of this expressiveness by weighted monadic second-order logic.     

一种异常入侵检测中新的HMM训练方法

隐马尔可夫模型(HMM)已经被证明是一个对系统正常行为建模的好工具,但是它的Baum-Welch训练算法效率不高,训练过程需要很大的计算机资源,在实际的入侵检测中效率是不高的.本文提出了一个高效的用多观察序列来训练HMM的训练方案,我们的实验结果显示我们的训练方法能比传统的训练方法节省60%的时间.     

Magic-sets for localised analysis of Java bytecode

Static analyses based on denotational semantics can naturally model functional behaviours of the code in a compositional and completely context and flow sensitive way. But they only model the functional i.e., input/output behaviour of a program P, not enough if one needs P’s internal behaviours i.e., from the input to some internal program points. This is, however, a frequent requirement for a useful static analysis. In this paper, we overcome this limitation, for the case of mono-threaded Java bytecode, with a technique used up to now for logic programs only. Namely, we define a program transformation that adds new magic blocks of code to the program P, whose functional behaviours are the internal behaviours of P. We prove the transformation correct w.r.t. an operational semantics and define an equivalent denotational semantics, devised for abstract interpretation, whose denotations for the magic blocks are hence the internal behaviours of P. We implement our transformation and instantiate it with abstract domains modelling sharing of two variables, non-cyclicity of variables, nullness of variables, class initialisation information and size of the values bound to program variables. We get a static analyser for full mono-threaded Java bytecode that is faster and scales better than another operational pair-sharing analyser. It has the same speed but is more precise than a constraint-based nullness analyser. It makes a polyhedral size analysis of Java bytecode scale up to 1300 methods in a couple of minutes and a zone-based size analysis scale to still larger applications.