The body in the library: adventures in realism

This essay looks at two aspects of the virtual ‘material world’ of realist fiction: objects encountered by the protagonist and the latter’s body. Taking from Sartre two angles on the realist pact by which readers agree to lend their bodies, feelings, and experiences to the otherwise ‘languishing signs’ of the text, it goes on to examine two sets of first-person fictions published between 1902 and 1956 — first, four modernist texts in which banal objects defy and then gratify the protagonist, who ends up ready and almost able to write; and, second, three novels in which the body of the protagonist is indeterminate in its sex, gender, or sexuality. In each of these cases, how do we as readers make texts work for us as ‘an adventure of the body’

Public Health Laboratories: Unprepared and Overwhelmed

Addresses the role of public health labs within the public health system and their ability to respond to specific chemical weapon events. Provides recommendations for improving response to terrorism as well as more conventional threats

Thermal conduction in molecular chains: Non-Markovian effects

We study the effect of non-Markovian reservoirs on the heat conduction properties of short to intermediate size molecular chains. Using classical molecular dynamics simulations, we show that the distance dependence of the heat current is determined not only by the molecular properties, rather it is also critically influenced by the spectral properties of the heat baths for both harmonic and anharmonic molecular chains. For highly correlated reservoirs the current of an anharmonic chain may exceed the flux of the corresponding harmonic system. Our numerical results are accompanied by a simple single-mode heat conduction model that can capture the intricate distance dependence obtained numerically

Auctions with Severely Bounded Communication

We study auctions with severe bounds on the communication allowed: each bidder may only transmit t bits of information to the auctioneer. We consider both welfare- and profit-maximizing auctions under this communication restriction. For both measures, we determine the optimal auction and show that the loss incurred relative to unconstrained auctions is mild. We prove non-surprising properties of these kinds of auctions, e.g., that in optimal mechanisms bidders simply report the interval in which their valuation lies in, as well as some surprising properties, e.g., that asymmetric auctions are better than symmetric ones and that multi-round auctions reduce the communication complexity only by a linear factor

F as in Fat: How Obesity Policies Are Failing in America, 2005

Examines national and state obesity rates and government policies. Challenges the research community to focus on major research questions to inform policy decisions, and policymakers to pursue actions to combat the obesity crisis

Large-scale structure and the redshift-distance relation

In efforts to demonstrate the linear Hubble law v = Hr from galaxy observations, the underlying simplicity is often obscured by complexities arising from magnitude-limited data. In this paper we point out a simple but previously unremarked fact: that the shapes and orientations of structures in redshift space contain in themselves independent information about the cosmological redshift-distance relation. The orientations of voids in the CfA slice support the Hubble law, giving a redshift-distance power index p = 0.83 +/- 0.36 (void data from Slezak, de Lapparent, & Bijoui 1993) or p = 0.99 +/- 0.38 (void data from Malik & Subramanian 1997).Comment: 11 pages (AASTeX), 4 figures, to appear in the Astrophysical Journal Letter

Information based clustering

In an age of increasingly large data sets, investigators in many different disciplines have turned to clustering as a tool for data analysis and exploration. Existing clustering methods, however, typically depend on several nontrivial assumptions about the structure of data. Here we reformulate the clustering problem from an information theoretic perspective which avoids many of these assumptions. In particular, our formulation obviates the need for defining a cluster "prototype", does not require an a priori similarity metric, is invariant to changes in the representation of the data, and naturally captures non-linear relations. We apply this approach to different domains and find that it consistently produces clusters that are more coherent than those extracted by existing algorithms. Finally, our approach provides a way of clustering based on collective notions of similarity rather than the traditional pairwise measures.Comment: To appear in Proceedings of the National Academy of Sciences USA, 11 pages, 9 figure

Motif Discovery through Predictive Modeling of Gene Regulation

We present MEDUSA, an integrative method for learning motif models of transcription factor binding sites by incorporating promoter sequence and gene expression data. We use a modern large-margin machine learning approach, based on boosting, to enable feature selection from the high-dimensional search space of candidate binding sequences while avoiding overfitting. At each iteration of the algorithm, MEDUSA builds a motif model whose presence in the promoter region of a gene, coupled with activity of a regulator in an experiment, is predictive of differential expression. In this way, we learn motifs that are functional and predictive of regulatory response rather than motifs that are simply overrepresented in promoter sequences. Moreover, MEDUSA produces a model of the transcriptional control logic that can predict the expression of any gene in the organism, given the sequence of the promoter region of the target gene and the expression state of a set of known or putative transcription factors and signaling molecules. Each motif model is either a $k$-length sequence, a dimer, or a PSSM that is built by agglomerative probabilistic clustering of sequences with similar boosting loss. By applying MEDUSA to a set of environmental stress response expression data in yeast, we learn motifs whose ability to predict differential expression of target genes outperforms motifs from the TRANSFAC dataset and from a previously published candidate set of PSSMs. We also show that MEDUSA retrieves many experimentally confirmed binding sites associated with environmental stress response from the literature.Comment: RECOMB 200