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.

Random graphs

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

/pdf/functional-nucleic-acid-sensors-k8tlieshyr.pdf

Functional Nucleic Acid Sensors

We describe an autonomous DNA nanorobot capable of transporting molecular payloads to cells, sensing cell surface inputs for conditional, triggered activation, and reconfiguring its structure for payload delivery. The device can be loaded with a variety of materials in a highly organized fashion and is controlled by an aptamer-encoded logic gate, enabling it to respond to a wide array of cues. We implemented several different logical AND gates and demonstrate their efficacy in selective regulation of nanorobot function. As a proof of principle, nanorobots loaded with combinations of antibody fragments were used in two different types of cell-signaling stimulation in tissue culture. Our prototype could inspire new designs with different selectivities and biologically active payloads for cell-targeting tasks.

http://science.sciencemag.org/content/sci/335/6070/831.full.pdf

A logic-gated nanorobot for targeted transport of molecular payloads

Since benchmarks drive computer science research and industry product development, which ones we use and how we evaluate them are key questions for the community. Despite complex runtime tradeoffs due to dynamic compilation and garbage collection required for Java programs, many evaluations still use methodologies developed for C, C++, and Fortran. SPEC, the dominant purveyor of benchmarks, compounded this problem by institutionalizing these methodologies for their Java benchmark suite. This paper recommends benchmarking selection and evaluation methodologies, and introduces the DaCapo benchmarks, a set of open source, client-side Java benchmarks. We demonstrate that the complex interactions of (1) architecture, (2) compiler, (3) virtual machine, (4) memory management, and (5) application require more extensive evaluation than C, C++, and Fortran which stress (4) much less, and do not require (3). We use and introduce new value, time-series, and statistical metrics for static and dynamic properties such as code complexity, code size, heap composition, and pointer mutations. No benchmark suite is definitive, but these metrics show that DaCapo improves over SPEC Java in a variety of ways, including more complex code, richer object behaviors, and more demanding memory system requirements. This paper takes a step towards improving methodologies for choosing and evaluating benchmarks to foster innovation in system design and implementation for Java and other managed languages.

/pdf/the-dacapo-benchmarks-java-benchmarking-development-and-3pc03s7g9q.pdf

The DaCapo benchmarks: java benchmarking development and analysis

We revisit the problem of constructing strategies for simple position games. We derive a general, executable formalism for describing game rules and desired strategy properties. We present the outcomes for several variants of the familiar game of tic-tac-toe.

Computing Game Strategies

We study a model of multi-legged catalytic molecular walkers that abstract a class of recently developed synthetic molecular motors. We focus on their kinetics of release of catalytic product, delineating the influence of chemical kinetic parameters, geometric configuration, loss from surface, and bulk kinetics. We show that such walkers can achieve a uniform rate of release over long time scales, which can be exploited in applications. ECAL Topics: Molecular Motors; DNA Computing; Applications in Nanotechnology, Compilable Matter, or Medicine.

Catalytic Molecular Walkers: Aspects of Product Release

On Models for Object Lifetimes.

Echo state networks (ESN), a type of reservoir computing (RC) architecture, are efficient and accurate artificial neural systems for time series processing and learning. An ESN consists of a core of recurrent neural networks, called a reservoir, with a small number of tunable parameters to generate a high-dimensional representation of an input, and a readout layer which is easily trained using regression to produce a desired output from the reservoir states. Certain computational tasks involve real-time calculation of high-order time correlations, which requires nonlinear transformation either in the reservoir or the readout layer. Traditional ESN employs a reservoir with sigmoid or tanh function neurons. In contrast, some types of biological neurons obey response curves that can be described as a product unit rather than a sum and threshold. Inspired by this class of neurons, we introduce a RC architecture with a reservoir of product nodes for time series computation. We find that the product RC shows many properties of standard ESN such as short-term memory and nonlinear capacity. On standard benchmarks for chaotic prediction tasks, the product RC maintains the performance of a standard nonlinear ESN while being more amenable to mathematical analysis. Our study provides evidence that such networks are powerful in highly nonlinear tasks owing to high-order statistics generated by the recurrent product node reservoir.

Product Reservoir Computing: Time-Series Computation with Multiplicative Neurons

Molecular spiders are nanoscale walkers made with catalytic DNA legs attached to a rigid body. They move in a matrix of DNA substrates, cleaving them and leaving behind product DNA strands. Unlike a self-avoiding walker, a spider is able to revisit the products. However, the legs cleave and detach from substrates more slowly than they detach from products. This difference in residence time and the presence of multiple legs make a spider move differently from an ordinary random walker. The number of legs, and their lengths, can be varied, and this defines the spider's local gait, which affects its behavior in global tasks. In this work we define an abstract model of molecular spiders, and within it we study the efficiency of maze exploration as a function of the spider structure. For a fixed geometry, there is an optimal setting of chemical kinetics parameters that minimizes the mean time to traverse a maze.

Darko Stefanovic

Papers

Computing Game Strategies

Catalytic Molecular Walkers: Aspects of Product Release

On Models for Object Lifetimes.

Product Reservoir Computing: Time-Series Computation with Multiplicative Neurons

Maze exploration with molecular-scale walkers