Focus of Contrast Aspects in Makua: Syntactic and Semantic Evidence

Proceedings of the Fifth Annual Meeting of the Berkeley Linguistics Society (1979), pp. 362-37

Using Synthetic Worlds for Work and Learning

Synthetic worlds [Castronova 2005] are graphically-rich, three-dimensional (3D), electronic environments where members assume an embodied persona (i.e., avatars) and engage in socializing, competitive quests, and economic transactions with globally distributed others. Frequently categorized as technologies of play, synthetic worlds range from massively multiplayer online games (MMOGs) such as World of Warcraft, to virtual reality environments such as Second Life. Increasingly, educators, researchers and corporations are recognizing these 3D online spaces as legitimate communication media, thereby blurring the lines between work and play, and between reality and virtuality. In this panel, presented at the 2007 International Conference on Information Systems, we explore how the fluid work-play and reality-virtuality boundaries are negotiated and managed in practice. The panelists will rely on their research, conducted in educational, corporate and game environments, to address questions about learning, working and playing in these new media spaces

Machine learning using digitized herbarium specimens to advance phenological research

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases

A Situated Perspective on Natural-Language Processing

this paper. The research repro'ted on was made possible by a gift from the System Development Foundation to CSLI [ would like to thank the foundation for helping to create an environment in which multi-disciplinary research projects such as the S[E are both encouraged and supporte