Self-replication and evolution of DNA crystals

Is it possible to create a simple physical system that is capable of replicating itself? Can such a system evolve interesting behaviors, thus allowing it to adapt to a wide range of environments? This paper presents a design for such a replicator constructed exclusively from synthetic DNA. The basis for the replicator is crystal growth: information is stored in the spatial arrangement of monomers and copied from layer to layer by templating. Replication is achieved by fragmentation of crystals, which produces new crystals that carry the same information. Crystal replication avoids intrinsic problems associated with template-directed mechanisms for replication of one-dimensional polymers. A key innovation of our work is that by using programmable DNA tiles as the crystal monomers, we can design crystal growth processes that apply interesting selective pressures to the evolving sequences. While evolution requires that copying occur with high accuracy, we show how to adapt error-correction techniques from algorithmic self-assembly to lower the replication error rate as much as is required

Evaluating e-portfolio Using by Learning Stages: A Case Study in an Interdisciplinary Program

This study conducts an investigation of posts in the e-portfolio platform of the program: “The interdisciplinary training program for talented college students in science.” Participants in this program were supposed to show their learning portfolios on this platform. Among the 2150 registered students, we randomly selected 126 students who have made at least 3 posts to become the target sample. By identifying the learning stages and posting styles shown by their posts, we find that students are mostly in the surface learning stages and weak in completing their learning portfolios. The results suggest that more strategies should be learned in e-portfolio use. In addition, some related issues about learning performance are also discussed

Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors

Penalized regression is an attractive framework for variable selection problems. Often, variables possess a grouping structure, and the relevant selection problem is that of selecting groups, not individual variables. The group lasso has been proposed as a way of extending the ideas of the lasso to the problem of group selection. Nonconvex penalties such as SCAD and MCP have been proposed and shown to have several advantages over the lasso; these penalties may also be extended to the group selection problem, giving rise to group SCAD and group MCP methods. Here, we describe algorithms for fitting these models stably and efficiently. In addition, we present simulation results and real data examples comparing and contrasting the statistical properties of these methods

Non-linear regression models for Approximate Bayesian Computation

Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable. However the methods that use rejection suffer from the curse of dimensionality when the number of summary statistics is increased. Here we propose a machine-learning approach to the estimation of the posterior density by introducing two innovations. The new method fits a nonlinear conditional heteroscedastic regression of the parameter on the summary statistics, and then adaptively improves estimation using importance sampling. The new algorithm is compared to the state-of-the-art approximate Bayesian methods, and achieves considerable reduction of the computational burden in two examples of inference in statistical genetics and in a queueing model.Comment: 4 figures; version 3 minor changes; to appear in Statistics and Computin

Effects of Exogenous Cellulase Source on In Vitro Fermentation Characteristics and Methane Production of Crop Straws and Grasses

In vitro fermentation experiments were conducted to investigate the effects of 3 sources of exogenous cellulase products (EC) at 4 dose rates (DR) (0, 12, 37 and 62 IU/g of DM) on degradation of forage and methane production by mixed rumen micro-organisms of goats. The maximum gas production (Vf) of grasses was higher (P<0.001) in Neocallimastix patriciarum (NP) group than those in Trichoderma reesei (TR) and Trichoderma longibrachiatum (TL) groups. Quadratic increases in dry matter degradation (DMD) of forage and neutral detergent fiber (NDFD) of straw were observed for all EC, with optimum DR in the low range. Supplementation of EC originated from TR and NP increased (P<0.001) DMD of forage compared to that from TL. Addition of EC originated from TR and NP also decreased pH value, ammonia nitrogen (NH3-N) and methane (CH4) production compared to that from TL. Quadratic decreases in pH value, NH3-N and CH4 of forage were noted for EC of TR and NP, and with optimum DR in the low range. For short chain fatty acid, the EC of NP increased total volatile fatty acid (TVFA) and acetate concentration and the ratio of acetate to propionate of forage compared with EC of TL and TR, and with optimum DR in the low to medium range. It was concluded that the source of EC differed in fiber degradation and methane emission, and with optimum DR of TR in the low range (from 12 to 37 U/g DM) in improving fiber degradation and decreasing methane emission

Plastic Flow in Two-Dimensional Solids

A time-dependent Ginzburg-Landau model of plastic deformation in two-dimensional solids is presented. The fundamental dynamic variables are the displacement field \bi u and the lattice velocity {\bi v}=\p {\bi u}/\p t. Damping is assumed to arise from the shear viscosity in the momentum equation. The elastic energy density is a periodic function of the shear and tetragonal strains, which enables formation of slips at large strains. In this work we neglect defects such as vacancies, interstitials, or grain boundaries. The simplest slip consists of two edge dislocations with opposite Burgers vectors. The formation energy of a slip is minimized if its orientation is parallel or perpendicular to the flow in simple shear deformation and if it makes angles of $\pm \pi/4$ with respect to the stretched direction in uniaxial stretching. High-density dislocations produced in plastic flow do not disappear even if the flow is stopped. Thus large applied strains give rise to metastable, structurally disordered states. We divide the elastic energy into an elastic part due to affine deformation and a defect part. The latter represents degree of disorder and is nearly constant in plastic flow under cyclic straining.Comment: 16pages, Figures can be obtained at http://stat.scphys.kyoto-u.ac.jp/index-e.htm

Correlation dynamics between electrons and ions in the fragmentation of D2_2 molecules by short laser pulses

We studied the recollision dynamics between the electrons and D$_2^+$ ions following the tunneling ionization of D$_2$ molecules in an intense short pulse laser field. The returning electron collisionally excites the D$_2^+$ ion to excited electronic states from there D$_2^+$ can dissociate or be further ionized by the laser field, resulting in D$^+$ + D or D$^+$ + D$^+$, respectively. We modeled the fragmentation dynamics and calculated the resulting kinetic energy spectrum of D$^+$ to compare with recent experiments. Since the recollision time is locked to the tunneling ionization time which occurs only within fraction of an optical cycle, the peaks in the D$^+$ kinetic energy spectra provides a measure of the time when the recollision occurs. This collision dynamics forms the basis of the molecular clock where the clock can be read with attosecond precision, as first proposed by Corkum and coworkers. By analyzing each of the elementary processes leading to the fragmentation quantitatively, we identified how the molecular clock is to be read from the measured kinetic energy spectra of D$^+$ and what laser parameters be used in order to measure the clock more accurately.Comment: 13 pages with 14 figure