"... The occurrence and duration of latching dynamics is found through simulations to depend critically on the strength of local attractor states, expressed in the Potts model by a parameter w. Here we describe with simulations and then analytically the boundaries between distinct phases of no latching, of transient and sustained latching, deriving a phase diagram in the plane w-T, where T parametrizes thermal noise effects. Implications for real cortical dynamics are briefly reviewed in the conclusions."

"This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the efficiency of the sensorimotor loop in biological organisms, but also from considerations stemming from curiosity-driven learning. Empowemerment measures, for agent-environment systems with stochastic transitions, how much influence an agent has on its environment, but only that influence that can be sensed by the agent sensors. It is an information-theoretic generalization of joint controllability (influence on environment) and observability (measurement by sensors) of the environment by the agent, both controllability and observability being usually defined in control theory as the dimensionality of the control/observation spaces.…"

"We review the observations and the basic laws describing the essential aspects of collective motion -- being one of the most common and spectacular manifestation of coordinated behavior. Our aim is to provide a balanced discussion of the various facets of this highly multidisciplinary field, including experiments, mathematical methods and models for simulations, so that readers with a variety of background could get both the basics and a broader, more detailed picture of the field. The observations we report on include systems consisting of units ranging from macromolecules through metallic rods and robots to groups of animals and people. Some emphasis is put on models that are simple and realistic enough to reproduce the numerous related observations and are useful for developing concepts for a better understanding of the complexity of systems consisting of many simultaneously moving entities. As such, these models allow the establishing of a few fundamental principles of flocking. In particular, it is demonstrated, that in spite of considerable differences, a number of deep analogies exist between equilibrium statistical physics systems and those made of self-propelled (in most cases living) units. In both cases only a few well defined macroscopic/collective states occur and the transitions between these states follow a similar scenario, involving discontinuity and algebraic divergences."

"We study instabilities and pattern formation in reaction-diffusion layers that are diffusively coupled. For two-layer systems of identical two-component reactions, we analyze the stability of homogeneous steady states by exploiting the block symmetric structure of the linear problem. There are eight possible primary bifurcation scenarios, including a Turing-Turing bifurcation that involves two disparate length scales whose ratio may be tuned via the inter-layer coupling. For systems of $n$-component layers and non-identical layers, the linear problem's block form allows approximate decomposition into lower-dimensional linear problems if the coupling is sufficiently weak. As an example, we apply these results to a two-layer Brusselator system. The competing length scales engineered within the linear problem are readily apparent in numerical simulations of the full system. Selecting a $sqrt{2}$:1 length scale ratio produces an unusual steady square pattern."

"This short paper introduces a new way by which to design production system rules. An indirect encoding scheme is presented which views such rules as protein complexes produced by the temporal behaviour of an artificial genetic regulatory network. This initial study begins by using a simple Boolean regulatory network to produce traditional ternary-encoded rules before moving to a fuzzy variant to produce real-valued rules. Competitive performance is shown with related genetic regulatory networks and rule-based systems on benchmark problems."

"We propose distributed algorithms to automatically deploy a team of mobile robots to partition and provide coverage of a non-convex environment. To handle arbitrary non-convex environments, we represent them as graphs. Our partitioning and coverage algorithm requires only short-range, unreliable pairwise "gossip" communication. The algorithm has two components: (1) a motion protocol to ensure that neighboring robots communicate at least sporadically, and (2) a pairwise partitioning rule to update territory ownership when two robots communicate. By studying an appropriate dynamical system on the space of partitions of the graph vertices, we prove that territory ownership converges to a pairwise-optimal partition in finite time. This new equilibrium set represents improved performance over common Lloyd-type algorithms. Additionally, we detail how our algorithm scales well for large teams in large environments and how the computation can run in anytime with limited resources. Finally, we report on large-scale simulations in complex environments and hardware experiments using the Player/Stage robot control system."

"Cellular behavior is governed by gene regulatory processes that are intrinsically dynamic and nonlinear, and are subject to non-negligible amounts of random fluctuations. Such conditions are ubiquitous in physical systems, where they have been studied for decades using the tools of statistical and nonlinear physics. The goal of this review is to show how approaches traditionally used in physics can help in reaching a systems-level understanding of living cells. To that end, we present an overview of the dynamical phenomena exhibited by genetic circuits and their functional significance. We also describe the theoretical and experimental approaches that are being used to unravel the relationship between circuit structure and function in dynamical cellular processes under the influence of noise, both at the single-cell level and in cellular populations, where intercellular coupling plays an important role."

"Much of the complexity observed in gene regulation originates from cooperative protein-DNA binding. While studies of the target search of proteins for their specific binding sites on the DNA have revealed design principles for the quantitative characteristics of protein-DNA interactions, no such principles are known for the cooperative interactions between DNA-binding proteins. We consider a simple theoretical model for two interacting transcription factor (TF) species, searching for and binding to two adjacent target sites hidden in the genomic background. We study the kinetic competition of a dimer search pathway and a monomer search pathway, as well as the steady-state regulation function mediated by the two TFs over a broad range of TF-TF interaction strengths. Using a transcriptional AND-logic as exemplary functional context, we identify the functionally desirable regime for the interaction. We find that both weak and very strong TF-TF interactions are favorable, albeit with different characteristics. However, there is also an unfavorable regime of intermediate interactions where the genetic response is prohibitively slow."

"The response of complex networks to perturbations is of utmost importance in areas as diverse as ecosystem management, emergency response, and cell reprogramming. A fundamental property of networks is that the perturbation of one node can affect other nodes, in a process that may cause the entire or substantial part of the system to change behavior and possibly collapse. Recent research in metabolic and food-web networks has demonstrated the concept that network damage caused by external perturbations can often be mitigated or reversed by the application of compensatory perturbations. Compensatory perturbations are constrained to be physically admissible and amenable to implementation on the network. However, the systematic identification of compensatory perturbations that conform to these constraints remains an open problem. Here, we present a method to construct compensatory perturbations that can control the fate of general networks under such constraints. Our approach accounts for the full nonlinear behavior of real complex networks and can bring the system to a desirable target state even when this state is not directly accessible. Applications to genetic networks show that compensatory perturbations are effective even when limited to a small fraction of all nodes in the network and that they are far more effective when limited to the highest-degree nodes. The approach is conceptually simple and computationally efficient, making it suitable for the rescue, control, and reprogramming of large complex networks in various domains."

"The design of genetic networks with specific functions is one of the major goals of synthetic biology. However, constructing biological devices that work "as required" remains challenging, while the cost of uncovering flawed designs experimentally is large. To address this issue, we propose a fully automated framework that allows the correctness of synthetic gene networks to be formally verified in silico from rich, high level functional specifications.
Given a device, we automatically construct a mathematical model from experimental data characterizing the parts it is composed of. The specific model structure guarantees that all experimental observations are captured and allows us to construct finite abstractions through polyhedral operations. The correctness of the model with respect to temporal logic specifications can then be verified automatically using methods inspired by model checking.
Overall, our procedure is conservative but it can filter through a large number of potential device designs and select few that satisfy the specification to be implemented and tested further experimentally. Illustrative examples of the application of our methods to the design of simple synthetic gene networks are included."

"Efficient collaborative decision making is an important challenge for multiagent systems. Finding optimal joint actions is especially challenging when each agent has only imperfect information about the state of its environment. Such problems can be modeled as collaborative Bayesian games in which each agent receives private information in the form of its type. However, representing and solving such games requires space and computation time exponential in the number of agents. This article introduces collaborative graphical Bayesian games (CGBGs), which facilitate more efficient collaborative decision making by decomposing the global payoff function as the sum of local payoff functions that depend on only a few agents. We propose a framework for the efficient solution of CGBGs based on the insight that they posses two different types of independence, which we call agent independence and type independence. In particular, we present a factor graph representation that captures both forms of independence and thus enables efficient solutions. In addition, we show how this representation can provide leverage in sequential tasks by using it to construct a novel method for decentralized partially observable Markov decision processes. Experimental results in both random and benchmark tasks demonstrate the improved scalability of our methods compared to several existing alternatives."

"In this paper a generalization of the Voronoi partition is used for solving a heterogeneous distributed locational optimization problem for autonomous agents, such as AGVs, UAVs, etc. The problem addressed is of optimal deployment of agents equipped with sensors, having heterogeneous capabilities, and limited range, to maximize sensor coverage. An objective function for optimal deployment of agents is formulated, and its critical points are determined. The optimal deployment is shown to be the generalized centroidal Voronoi configuration in which the agents are located at the centroids of the corresponding generalized Voronoi cells. Formal results on stability, convergence, and on spatial distribution of the proposed control laws responsible for agent motion, under some constraints on the agents' speeds and limit on sensor range are provided. The theoretical results are supported with illustrative simulation"

"Recent years are seeing an increasing need for on-line monitoring of teams of cooperating agents, e.g., for visualization, or performance tracking. However, in monitoring deployed teams, we often cannot rely on the agents to always communicate their state to the monitoring system. This paper presents a non-intrusive approach to monitoring by 'overhearing', where the monitored team's state is inferred (via plan-recognition) from team-members' routine communications, exchanged as part of their coordinated task execution, and observed (overheard) by the monitoring system. Key challenges in this approach include the demanding run-time requirements of monitoring, the scarceness of observations (increasing monitoring uncertainty), and the need to scale-up monitoring to address potentially large teams. To address these, we present a set of complementary novel techniques, exploiting knowledge of the social structures and procedures in the monitored team: (i) an efficient probabilistic plan-recognition algorithm, well-suited for processing communications as observations; (ii) an approach to exploiting knowledge of the team's social behavior to predict future observations during execution (reducing monitoring uncertainty); and (iii) monitoring algorithms that trade expressivity for scalability, representing only certain useful monitoring hypotheses, but allowing for any number of agents and their different activities to be represented in a single coherent entity. We present an empirical evaluation of these techniques, in combination and apart, in monitoring a deployed team of agents, running on machines physically distributed across the country, and engaged in complex, dynamic task execution. We also compare the performance of these techniques to human expert and novice monitors, and show that the techniques presented are capable of monitoring at human-expert levels, despite the difficulty of the task."

"In this paper we present a methodological framework that meets novel requirements emerging from upcoming types of accelerated and highly configurable neuromorphic hardware systems. We describe in detail a device with 45 million programmable and dynamic synapses that is currently under development, and we sketch the conceptual challenges that arise from taking this platform into operation. More specifically, we aim at the establishment of this neuromorphic system as a flexible and neuroscientifically valuable modeling tool that can be used by non-hardware-experts. We consider various functional aspects to be crucial for this purpose, and we introduce a consistent workflow with detailed descriptions of all involved modules that implement the suggested steps: The integration of the hardware interface into the simulator-independent model description language PyNN; a fully automated translation between the PyNN domain and appropriate hardware configurations; an executable specification of the future neuromorphic system that can be seamlessly integrated into this biology-to-hardware mapping process as a test bench for all software layers and possible hardware design modifications; an evaluation scheme that deploys models from a dedicated benchmark library, compares the results generated by virtual or prototype hardware devices with reference software simulations and analyzes the differences. The integration of these components into one hardware-software workflow provides an ecosystem for ongoing preparative studies that support the hardware design process and represents the basis for the maturity of the model-to-hardware mapping software. The functionality and flexibility of the latter is proven with a variety of experimental results."

"There is an increasing need for automated support for humans monitoring the activity of distributed teams of cooperating agents, both human and machine. We characterize the domain-independent challenges posed by this problem, and describe how properties of domains influence the challenges and their solutions. We will concentrate on dynamic, data-rich domains where humans are ultimately responsible for team behavior. Thus, the automated aid should interactively support effective and timely decision making by the human. We present a domain-independent categorization of the types of alerts a plan-based monitoring system might issue to a user, where each type generally requires different monitoring techniques. We describe a monitoring framework for integrating many domain-specific and task-specific monitoring techniques and then using the concept of value of an alert to avoid operator overload. We use this framework to describe an execution monitoring approach we have used to implement Execution Assistants (EAs) in two different dynamic, data-rich, real-world domains to assist a human in monitoring team behavior. One domain (Army small unit operations) has hundreds of mobile, geographically distributed agents, a combination of humans, robots, and vehicles. The other domain (teams of unmanned ground and air vehicles) has a handful of cooperating robots. Both domains involve unpredictable adversaries in the vicinity. Our approach customizes monitoring behavior for each specific task, plan, and situation, as well as for user preferences. Our EAs alert the human controller when reported events threaten plan execution or physically threaten team members. Alerts were generated in a timely manner without inundating the user with too many alerts (less than 10 percent of alerts are unwanted, as judged by domain experts)."

"All this results in bacteria gambling all the time: some react to stimulus, some don't, some produce more proteins in response to it, some less. This leads to so called phenotypic heterogeneity, when otherwise (genetically) identical bacteria become very different in terms of their responses.

This could be a good thing and also could be a bad thing. Having a collection of different bugs instead of a clone army will provide certain versatility: some are ready for one conditions, and some are ready for others. For instance, some are ready to grow and divide right away and some are slower and more cautious. Both types of cells can be beneficial in different conditions: the active ones will drive the population growth, but will be sensitive to the antibiotic treatment, and the passive ones will wait until the treatment is over and then they will come to life. Sounds like a good strategy (and it has a name, this strategy - "bed hedging") and I guess it is exactly the reason why clone armies never caught on."

"… As a departure from such traditional trust models, we propose a generic, machine learning approach based trust framework where an agent uses its own previous transactions (with other agents) to build a knowledge base, and utilize this to assess the trustworthiness of a transaction based on associated features, which are capable of distinguishing successful transactions from unsuccessful ones. These features are harnessed using appropriate machine learning algorithms to extract relationships between the potential transaction and previous transactions.…"

"We study equilibrium configurations of swarming biological organisms subject to exogenous and pairwise endogenous forces. Beginning with a discrete dynamical model, we derive a variational description of the corresponding continuum population density. Equilibrium solutions are extrema of an energy functional, and satisfy a Fredholm integral equation. We find conditions for the extrema to be local minimizers, global minimizers, and minimizers with respect to infinitesimal Lagrangian displacements of mass. In one spatial dimension, for a variety of exogenous forces, endogenous forces, and domain configurations, we find exact analytical expressions for the equilibria.…"

"We have shown that there exists a large ensemble of minimal Boolean networks that show reliable and robust dynamics. The networks are minimal in the respect that the number of connections of a node is not larger than necessary for obtaining a desired reliable trajectory. A reliable trajectory is an attractor of the dynamics of the network that does not change when the update schedule is changed or randomized. This means that under parallel update, at each time step only one node changes its state. The reliable trajectories were chosen at random, given a fixed average number of flips per node. High robustness was achieved by using an evolutionary algorithm that modifies the update functions and that accepts only those changes that do not decrease robustness.…"

"Neuronal activity arises from an interaction between ongoing firing generated spontaneously by neural circuits and responses driven by external stimuli. Using mean-field analysis, we ask how a neural network that intrinsically generates chaotic patterns of activity can remain sensitive to extrinsic input. We find that inputs not only drive network responses, they also actively suppress ongoing activity, ultimately leading to a phase transition in which chaos is completely eliminated. The critical input intensity at the phase transition is a non-monotonic function of stimulus frequency, revealing a "resonant" frequency at which the input is most effective at suppressing chaos even though the power spectrum of the spontaneous activity peaks at zero and falls exponentially. A prediction of our analysis is that the variance of neural responses should be most strongly suppressed at frequencies matching the range over which many sensory systems operate."

"Developing large-scale distributed applications can be a daunting task. object-based environments have attempted to alleviate problems by providing distributed objects that look like local objects. We advocate that this approach has actually only made matters worse, as the developer needs to be aware of many intricate internal details in order to adequately handle partial failures. The result is an increase of application complexity. We present an alternative in which distribution transparency is lessened in favor of clearer semantics. In particular, we argue that a developer should always be offered the unambiguous semantics of local objects, and that distribution comes from copying those objects to where they are needed. We claim that it is often sufficient to provide only small, immutable objects, along with facilities to group objects into clusters."

"We use computer simulation to study crystal-forming model proteins equipped with interactions that are both orientationally specific and nonspecific. Distinct dynamical pathways of crystal formation can be selected by tuning the strengths of these interactions. When the nonspecific interaction is strong, liquidlike clustering can precede crystallization; when it is weak, growth can proceed via ordered nuclei. Crystal yields are in certain parameter regimes enhanced by the nonspecific interaction, even though it promotes association without local crystalline order. Our results suggest that equipping nanoscale components with weak nonspecific interactions (such as depletion attractions) can alter both their dynamical pathway of assembly and optimize the yield of the resulting material."

"As we continue to monitor the markets for evidence of Quote Stuffing and Strange Sequences (Crop Circles), we find that there are dozens if not hundreds of examples to choose from on any given day. As such, this page will be updated often with charts demonstrating this activity.

The common theme with the charts shown on this page is they are obviously all generated in code and are algorithmic. Some demonstrate bizarre price or size cycling, some demonstrate large burst of quotes in extremely short time frames and some will demonstrate both. In most cases these sequences are from a single exchange with no other exchange quoting in the same time frame."

"While analyzing HFT (High Frequency Trading) quote counts, we were shocked to find cases where one exchange was sending an extremely high number of quotes for one stock in a single second: as high as 5,000 quotes in 1 second! During May 6, there were hundreds of times that a single stock had over 1,000 quotes from one exchange in a single second. Even more disturbing, there doesn't seem to be any economic justification for this. In many of the cases, the bid/offer is well outside the National Best Bid/Offer (NBBO). We decided to analyze a handful of these cases in detail and graphed the sequential bid/offers to better understand them. What we discovered was a manipulative device with destabilizing effect."

"Working in Winfree's abstract tile assembly model, we show that a constant-size tile assembly system can be programmed through relative tile concentrations to build an n x n square with high probability, for any sufficiently large n. This answers an open question of Kao and Schweller (Randomized Self-Assembly for Approximate Shapes, ICALP 2008), who showed how to build an approximately n x n square using tile concentration programming, and asked whether the approximation could be made exact with high probability. We show how this technique can be modified to answer another question of Kao and Schweller, by showing that a constant-size tile assembly system can be programmed through tile concentrations to assemble arbitrary finite *scaled shapes*, which are shapes modified by replacing each point with a c x c block of points, for some integer c. …"

"The possibility of microscopic swimming by extraction of energy from an external flow is discussed, focusing on the migration of a simple trimer across a linear shear flow. The geometric properties of swimming, together with the possible generalization to the case of a vesicle, are analyzed.The mechanism of energy extraction from the flow appears to be the generalization to a discrete swimmer of the tank-treading regime of a vesicle. The swimmer takes advantage of the external flow by both extracting energy for swimming and "sailing" through it. The migration velocity is found to scale linearly in the stroke amplitude, and not quadratically as in a quiescent fluid. This effect turns out to be connected with the non-applicability of the scallop theorem in the presence of external flow fields."

"Biological networks of interacting agents exhibit similar topological properties for a wide range of scales, from cellular to ecological levels, suggesting the existence of a common evolutionary origin. A general evolutionary mechanism based on global stability has been proposed recently [J I Perotti, O V Billoni, F A Tamarit, D R Chialvo, S A Cannas, Phys. Rev. Lett. 103, 108701 (2009)]. This mechanism is incorporated into a model of a growing network of interacting agents in which each new agent's membership in the network is determined by the agent's effect on the network's global stability. We show that, out of this stability constraint, several topological properties observed in biological networks emerge in a self organized manner. The influence of the stability selection mechanism on the dynamics associated to the resulting network is analyzed as well."

"How do living cells achieve sufficient abundances of functional protein complexes while minimizing promiscuous non-functional interactions between their proteins? Here we study this problem using a first-principle model of the cell whose phenotypic traits are directly determined from its genome through biophysical properties of protein structures and binding interactions in crowded cellular environment. The model cell includes three independent pathways, whose topologies of PPI subnetworks are different, but whose functional concentrations equally contribute to cell's fitness. The model cells evolve through genotypic mutations and phenotypic protein copy number variations. We found a strong relationship between evolved physical-chemical properties of protein interactions and their abundances due to a "frustration" effect: strengthening of functional interactions brings about hydrophobic surfaces, which make proteins prone to promiscuous binding.…"

"We consider the problem of computing a response curve for binary cellular automata -- that is, the curve describing the dependence of the density of ones after many iterations of the rule on the initial density of ones. We demonstrate how this problem could be approached using rule 130 as an example. For this rule, preimage sets of finite strings exhibit recognizable patterns, and it is therefore possible to compute both cardinalities of preimages of certain finite strings and probabilities of occurrence of these strings in a configuration obtained by iterating a random initial configuration $n$ times. Response curves can be rigorously calculated in both one- and two-dimensional versions of CA rule 130. We also discuss a special case of totally disordered initial configurations, that is, random configurations where the density of ones and zeros are equal to 1/2."

"Laboratory investigations have shown that a formal theory of fault-tolerance will be essential to harness nanoscale self-assembly as a medium of computation. Several researchers have voiced an intuition that self-assembly phenomena are related to the field of distributed computing. This paper formalizes some of that intuition. We construct tile assembly systems that are able to simulate the solution of the wait-free consensus problem in some distributed systems. (For potential future work, this may allow binding errors in tile assembly to be analyzed, and managed, with positive results in distributed computing, as a "blockage" in our tile assembly model is analogous to a crash failure in a distributed computing model.) …We show that solution of this strengthened consensus problem can be simulated by a two-dimensional tile assembly model only for two processes, whereas a three-dimensional tile assembly model can simulate its solution in a distributed system with any number of processes

"This paper introduces the theory and practice of formal verification of self-assembling systems. We interpret a well-studied abstraction of nanomolecular self assembly, the Abstract Tile Assembly Model (aTAM), into Computation Tree Logic (CTL), a temporal logic often used in model checking. We then consider the class of "rectilinear" tile assembly systems. This class includes most aTAM systems studied in the theoretical literature, and all (algorithmic) DNA tile self-assembling systems that have been realized in laboratories to date. We present a polynomial-time algorithm that, given a tile assembly system T as input, either provides a counterexample to T's rectilinearity or verifies whether T has a unique terminal assembly. …"

"The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems (AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics.…"

"…The conclusion is that nondeterminism confers extra power to assemble a shape from a small tile system, but unless the polynomial hierarchy collapses, it is computationally more difficult to exploit this power by finding the size of the smallest tile system, compared to finding the size of the smallest deterministic tile system."

"Eventually, a reversal towards smaller farms and less production of corn, soybeans and cotton may even result. Also, for a few years, U.S. input costs may escalate while other regions (not yet seeing superweeds) continue to use lower priced Roundup, making the cost of production lower in South America, for example. Consequent rising input costs here in the U.S. will include potentially higher new GMO seeds, chemicals, labor, and fuel. The volume of chemical use will potentially become much greater, more toxic, and more expensive."

"The paper is structured as follows. Methods of cultivating and experimenting with plasmodium of Physarum polycephalum are described in Sect. 2. In Sect. 3 we provide experimental evidence of ‘ballistic’ behavior of traveling plasmod- ium localizations. Experimental Physarum gates are discussed in Sect. 4. In Sect. 5 experimental results are supported by numerical simulation of propa- gating localizations. The gates are cascaded in one-bit half-adder in Sect. 6. Importance of non-nutrient substrate for gate implementation is highlighted in Sect. 7."

"The results from the computational approximation of Physarum support the findings of [15] that the organism can be used to construct simple logic gates, and also the computing schemes within this paper which explored the creation of more complex combined gates and half adder circuitry. The findings suggest that, although such circuits can indeed be built, the presence of both timing errors and junctional (search) errors would severely limit the effectiveness and practicality with even more complex circuits."

"… In contrast, we show that temperature 1 self-assembly in 3 dimensions, even when growth is restricted to at most 1 step into the third dimension, is capable of simulating a large class of temperature 2 systems, in turn permitting the simulation of arbitrary Turing machines and the assembly of $n\times n$ squares in near optimal $O(\log n)$ tile complexity. Further, we consider temperature 1 probabilistic assembly in 2D, and show that with a logarithmic scale up of tile complexity and shape scale, the same general class of temperature $\tau=2$ systems can be simulated with high probability, yielding Turing machine simulation and $O(\log^2 n)$ assembly of $n\times n$ squares with high probability. Our results show a sharp contrast in achievable tile complexity at temperature 1 if either growth into the third dimension or a small probability of error are permitted. …"

"Microbial ecosystems have been widely used in industrial production, but the inter-relationships of organisms within them haven't been completely clarified due to complex composition and structure of natural microbial ecosystems. So it is challenging for ecologists to get deep insights on how ecosystems function and interplay with surrounding environments. But the recent progresses in synthetic biology show that construction of artificial ecosystems where relationships of species are comparatively clear could help us further uncover the meadow of those tiny societies. By using two quorum-sensing signal transduction circuits, this research designed, simulated and constructed a synthetic ecosystem where various population dynamics formed by changing environmental factors."

"The first category is best termed Design as an Exploration of Production. This category is the largest in terms of the number of .MGX products it contains, and is made up of products whose central interest is an exploration of what rapid manufacturing technologies can produce, which conventional technologies cannot. It is typified by complex detailing on both the interior and exterior of the product, geometries which would be impossible to achieve were any form of tooling required."

"The 'Primer' is a well-known Life pattern used to calculate prime numbers. The pattern expands in two directions, resembles a breeder, and emits a stream of spaceships representing prime numbers. The presence or absence of a spaceship at a particular generation indicates whether the number is prime or composite. It works by testing whether each integer is divisible by any smaller integer, apart from itself and 1. This is similar in principle to the Sieve of Eratosthenes."

"This looks a whole lot like the initializer block in Rails 2.3, but the Application object, not a global configuration object, now has the configuration information. Similarly, routes.rb now begins YourApp::Application.routes.draw. The application object lives in the center of Railties in Rails 3, providing a core object that the rest of the frameworks can build on."

"We’ve been writing a “feature” for every new client request on that project – for each user-created ticket we handle, we create a .feature file (and include the ticket number in the feature title), and write steps for that request. This means that we have acceptance tests for all new client requests on that project. This approach may seem a little strange, but it’s been helpful, and we’re very happy with it so far. We’ll likely take a different approach if we use Cucumber on a project from scratch.

Now you have no excuse if your projects aren’t doing any kind of top-down testing, so get out there and write some acceptance tests!"

"Here’s what duplication removal does, structurally. It allows you to pull out redundant bits of pulp from big sections, yielding smaller sections, but the side effect is that you end up with more fascia. Duplication removal increases the ratio of fascia to pulp. If the amount of pulp you are able to remove exceeds the size of the fascia you introduce, the net amount of code decreases, otherwise it might increase.

In general, I think that a high fascia to pulp ratio is better for maintenance. It gives us is a higher surface area to volume ratio for our code. This can enhance testability and make it easier to compose new software – we already have smaller more understandable pieces."

generalizable for many domains, not just software development: "However, as a program evolves, there’s a good chance that the Design In Code will not include all the good things we now understand. We have a better Design In Head. When the design in our head is enough better than the one in the code, it can pay off to bring the code closer to what we now understand."