Decomposition Methods for Large Scale LP Decoding

When binary linear error-correcting codes are used over symmetric channels, a relaxed version of the maximum likelihood decoding problem can be stated as a linear program (LP). This LP decoder can be used to decode error-correcting codes at bit-error-rates comparable to state-of-the-art belief propagation (BP) decoders, but with significantly stronger theoretical guarantees. However, LP decoding when implemented with standard LP solvers does not easily scale to the block lengths of modern error correcting codes. In this paper we draw on decomposition methods from optimization theory, specifically the Alternating Directions Method of Multipliers (ADMM), to develop efficient distributed algorithms for LP decoding. The key enabling technical result is a "two-slice" characterization of the geometry of the parity polytope, which is the convex hull of all codewords of a single parity check code. This new characterization simplifies the representation of points in the polytope. Using this simplification, we develop an efficient algorithm for Euclidean norm projection onto the parity polytope. This projection is required by ADMM and allows us to use LP decoding, with all its theoretical guarantees, to decode large-scale error correcting codes efficiently. We present numerical results for LDPC codes of lengths more than 1000. The waterfall region of LP decoding is seen to initiate at a slightly higher signal-to-noise ratio than for sum-product BP, however an error floor is not observed for LP decoding, which is not the case for BP. Our implementation of LP decoding using ADMM executes as fast as our baseline sum-product BP decoder, is fully parallelizable, and can be seen to implement a type of message-passing with a particularly simple schedule.Comment: 35 pages, 11 figures. An early version of this work appeared at the 49th Annual Allerton Conference, September 2011. This version to appear in IEEE Transactions on Information Theor

Anti-CRISPR-mediated control of gene editing and synthetic circuits in eukaryotic cells.

Repurposed CRISPR-Cas molecules provide a useful tool set for broad applications of genomic editing and regulation of gene expression in prokaryotes and eukaryotes. Recent discovery of phage-derived proteins, anti-CRISPRs, which serve to abrogate natural CRISPR anti-phage activity, potentially expands the ability to build synthetic CRISPR-mediated circuits. Here, we characterize a panel of anti-CRISPR molecules for expanded applications to counteract CRISPR-mediated gene activation and repression of reporter and endogenous genes in various cell types. We demonstrate that cells pre-engineered with anti-CRISPR molecules become resistant to gene editing, thus providing a means to generate "write-protected" cells that prevent future gene editing. We further show that anti-CRISPRs can be used to control CRISPR-based gene regulation circuits, including implementation of a pulse generator circuit in mammalian cells. Our work suggests that anti-CRISPR proteins should serve as widely applicable tools for synthetic systems regulating the behavior of eukaryotic cells

Order-sorted Homeomorphic Embedding modulo Combinations of Associativity and/or Commutativity Axioms

[EN] The Homeomorphic Embedding relation has been amply used for defining termination criteria of symbolic methods for program analysis, transformation, and verification. However, homeomorphic embedding has never been investigated in the context of order-sorted rewrite theories that support symbolic execution methods modulo equational axioms. This paper generalizes the symbolic homeomorphic embedding relation to order-sorted rewrite theories that may contain various combinations of associativity and/or commutativity axioms for different binary operators. We systematically measure the performance of different, increasingly efficient formulations of the homeomorphic embedding relation modulo axioms that we implement in Maude. Our experimental results show that the most efficient version indeed pays off in practice.M. Alpuente and S. Escobar have been partially supported by the EU (FEDER) and the Spanish MCIU under grant RTI2018-094403-B-C32, by the Spanish Generalitat Valenciana under grant PROMETEO/2019/098, and by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 952215 (TAILOR). J. Meseguer has been supported by NRL under contract number N00173-17-1-G002. A. Cuenca-Ortega has been supported by the SENESCYT, Ecuador (scholarship program 2013).Alpuente Frasnedo, M.; Cuenca-Ortega, A.; Escobar Román, S.; Meseguer, J. (2020). Order-sorted Homeomorphic Embedding modulo Combinations of Associativity and/or Commutativity Axioms. Fundamenta Informaticae. 177(3-4):297-329. https://doi.org/10.3233/FI-2020-1991S2973291773-

High resolution multi-facies realizations of sedimentary reservoir and aquifer analogs

Geological structures are by nature inaccessible to direct observation. This can cause difficulties in applications where a spatially explicit representation of such structures is required, in particular when modelling fluid migration in geological formations. An increasing trend in recent years has been to use analogs to palliate this lack of knowledge, i.e., exploiting the spatial information from sites where the geology is accessible (outcrops, quarry sites) and transferring the observed properties to a study site deemed geologically similar. While this approach is appealing, it is difficult to put in place because of the lack of access to well-documented analog data. In this paper we present comprehensive analog data sets which characterize sedimentary structures from important groundwater hosting formations in Germany and Brazil. Multiple 2-D outcrop faces are described in terms of hydraulic, thermal and chemical properties and interpolated in 3-D using stochastic techniques. These unique data sets can be used by the wider community to implement analog approaches for characterizing reservoir and aquifer formations