544 research outputs found
A File System Abstraction for Sense and Respond Systems
The heterogeneity and resource constraints of sense-and-respond systems pose
significant challenges to system and application development. In this paper, we
present a flexible, intuitive file system abstraction for organizing and
managing sense-and-respond systems based on the Plan 9 design principles. A key
feature of this abstraction is the ability to support multiple views of the
system via filesystem namespaces. Constructed logical views present an
application-specific representation of the network, thus enabling high-level
programming of the network. Concurrently, structural views of the network
enable resource-efficient planning and execution of tasks. We present and
motivate the design using several examples, outline research challenges and our
research plan to address them, and describe the current state of
implementation.Comment: 6 pages, 3 figures Workshop on End-to-End, Sense-and-Respond Systems,
Applications, and Services In conjunction with MobiSys '0
Generalized Gaussian covariance analysis in multi-market risk assessment
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (p. 134-136).by Kenneth Chiu.M.S
A Revised Analysis of the Open Grid Services Infrastructure
This paper began its life as an unpublished technical review citeanalysis of the proposed Open Grid Services Architecture (OGSA) as described in the papers, ``The Physiology of the Grid'' citefoster by Ian Foster, Carl Kesselman, Jeffrey Nick and Steven Tuecke, and ``The Grid Service Specification (Draft 2/15/02) citeogsi'' by Foster, Kesselman, Tuecke and Karl Czajkowski, Jeffrey Frey and Steve Graham. However, much has changed since the publication of the original documents. The architecture has evolved substantially and the vast majority of our initial concerns have been addressed. In this paper we will describe the evolution of the specification from its original form to the current draft of 10/4/02 authored by S. Tuecke, K. Czajkowski, J. Frey, S. Graham, C. Kesselman, and P. Vanderbilt, which is now the central component of the Global Grid Forum Open Grid Service Infrastructure (OGSI) working group which is co-chaired by Steven Tuecke and David Snelling
Population structure of mitochondrial genomes in Saccharomyces cerevisiae
Background: Rigorous study of mitochondrial functions and cell biology in the budding yeast, Saccharomyces cerevisiae has advanced our understanding of mitochondrial genetics. This yeast is now a powerful model for population genetics, owing to large genetic diversity and highly structured populations among wild isolates. Comparative mitochondrial genomic analyses between yeast species have revealed broad evolutionary changes in genome organization and architecture. A fine-scale view of recent evolutionary changes within S. cerevisiae has not been possible due to low numbers of complete mitochondrial sequences. Results: To address challenges of sequencing AT-rich and repetitive mitochondrial DNAs (mtDNAs), we sequenced two divergent S. cerevisiae mtDNAs using a single-molecule sequencing platform (PacBio RS). Using de novo assemblies, we generated highly accurate complete mtDNA sequences. These mtDNA sequences were compared with 98 additional mtDNA sequences gathered from various published collections. Phylogenies based on mitochondrial coding sequences and intron profiles revealed that intraspecific diversity in mitochondrial genomes generally recapitulated the population structure of nuclear genomes. Analysis of intergenic sequence indicated a recent expansion of mobile elements in certain populations. Additionally, our analyses revealed that certain populations lacked introns previously believed conserved throughout the species, as well as the presence of introns never before reported in S. cerevisiae. Conclusions: Our results revealed that the extensive variation in S. cerevisiae mtDNAs is often population specific, thus offering a window into the recent evolutionary processes shaping these genomes. In addition, we offer an effective strategy for sequencing these challenging AT-rich mitochondrial genomes for small scale projects
STRIDE: Structure-guided Generation for Inverse Design of Molecules
Machine learning and especially deep learning has had an increasing impact on
molecule and materials design. In particular, given the growing access to an
abundance of high-quality small molecule data for generative modeling for drug
design, results for drug discovery have been promising. However, for many
important classes of materials such as catalysts, antioxidants, and
metal-organic frameworks, such large datasets are not available. Such families
of molecules with limited samples and structural similarities are especially
prevalent for industrial applications. As is well-known, retraining and even
fine-tuning are challenging on such small datasets. Novel, practically
applicable molecules are most often derivatives of well-known molecules,
suggesting approaches to addressing data scarcity. To address this problem, we
introduce , a generative molecule workflow that generates
novel molecules with an unconditional generative model guided by known
molecules without any retraining. We generate molecules outside of the training
data from a highly specialized set of antioxidant molecules. Our generated
molecules have on average 21.7% lower synthetic accessibility scores and also
reduce ionization potential by 5.9% of generated molecules via guiding
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