A Dynamical Systems Model for Language Change

Formalizing linguists' intuitions of language change as a dynamical system, we quantify the time course of language change including sudden vs. gradual changes in languages. We apply the computer model to the historical loss of Verb Second from Old French to modern French, showing that otherwise adequate grammatical theories can fail our new evolutionary criterion.

Selecting Relevant Genes with a Spectral Approach

Array technologies have made it possible to record simultaneously the expression pattern of thousands of genes. A fundamental problem in the analysis of gene expression data is the identification of highly relevant genes that either discriminate between phenotypic labels or are important with respect to the cellular process studied in the experiment: for example cell cycle or heat shock in yeast experiments, chemical or genetic perturbations of mammalian cell lines, and genes involved in class discovery for human tumors. In this paper we focus on the task of unsupervised gene selection. The problem of selecting a small subset of genes is particularly challenging as the datasets involved are typically characterized by a very small sample size ?? the order of few tens of tissue samples ??d by a very large feature space as the number of genes tend to be in the high thousands. We propose a model independent approach which scores candidate gene selections using spectral properties of the candidate affinity matrix. The algorithm is very straightforward to implement yet contains a number of remarkable properties which guarantee consistent sparse selections. To illustrate the value of our approach we applied our algorithm on five different datasets. The first consists of time course data from four well studied Hematopoietic cell lines (HL-60, Jurkat, NB4, and U937). The other four datasets include three well studied treatment outcomes (large cell lymphoma, childhood medulloblastomas, breast tumors) and one unpublished dataset (lymph status). We compared our approach both with other unsupervised methods (SOM,PCA,GS) and with supervised methods (SNR,RMB,RFE). The results clearly show that our approach considerably outperforms all the other unsupervised approaches in our study, is competitive with supervised methods and in some case even outperforms supervised approaches.

Kinetics and dynamics measured using IntraCavity Laser Absorption Spectroscopy

IntraCavity Laser Absorption Spectroscopy (ICLAS) is a high-resolution, high sensitivity spectroscopic method capable of measuring line positions, linewidths, lineshapes, and absolute line intensities with a sensitivity that far exceeds that of a traditional multiple pass absorption cell or Fourier Transform spectrometer. From the fundamental knowledge obtained through these measurements, information about the underlying spectroscopy, dynamics, and kinetics of the species interrogated can be derived. The construction of an ICLA Spectrometer will be detailed, and the measurements utilizing ICLAS will be discussed, as well as the theory of operation and modifications of the experimental apparatus. Results include: i) Line intensities and collision-broadening coefficients of the A band of oxygen and previously unobserved, high J, rotational transitions of the A band, hot-band transitions, and transitions of isotopically substituted species. ii) High-resolution (0.013 cm-1) spectra of the second overtone of the OH stretch of trans-nitrous acid recorded between 10,230 and 10,350 cm-1. The spectra were analyzed to yield a complete set of rotational parameters and an absolute band intensity, and two groups of anharmonic perturbations were observed and analyzed. These findings are discussed in the context of the contribution of overtone-mediated processes to OH radical production in the lower atmosphere.