Finding k-Dissimilar Paths with Minimum Collective Length

Shortest path computation is a fundamental problem in road networks. However, in many real-world scenarios, determining solely the shortest path is not enough. In this paper, we study the problem of finding k-Dissimilar Paths with Minimum Collective Length (kDPwML), which aims at computing a set of paths from a source s to a target t such that all paths are pairwise dissimilar by at least \theta and the sum of the path lengths is minimal. We introduce an exact algorithm for the kDPwML problem, which iterates over all possible s-t paths while employing two pruning techniques to reduce the prohibitively expensive computational cost. To achieve scalability, we also define the much smaller set of the simple single-via paths, and we adapt two algorithms for kDPwML queries to iterate over this set. Our experimental analysis on real road networks shows that iterating over all paths is impractical, while iterating over the set of simple single-via paths can lead to scalable solutions with only a small trade-off in the quality of the results.Comment: Extended version of the SIGSPATIAL'18 paper under the same titl

Operon conservation and the evolution of trans-splicing in the phylum Nematoda

The nematode Caenorhabditis elegans is unique among model animals in that many of its genes are cotranscribed as polycistronic pre-mRNAs from operons. The mechanism by which these operonic transcripts are resolved into mature mRNAs includes trans-splicing to a family of SL2-like spliced leader exons. SL2-like spliced leaders are distinct from SL1, the major spliced leader in C. elegans and other nematode species. We surveyed five additional nematode species, representing three of the five major clades of the phylum Nematoda, for the presence of operons and the use of trans-spliced leaders in resolution of polycistronic pre-mRNAs. Conserved operons were found in Pristionchus pacificus, Nippostrongylus brasiliensis, Strongyloides ratti, Brugia malayi, and Ascaris suum. In nematodes closely related to the rhabditine C. elegans, a related family of SL2-like spliced leaders is used for operonic transcript resolution. However, in the tylenchine S. ratti operonic transcripts are resolved using a family of spliced leaders related to SL1. Non-operonic genes in S. ratti may also receive these SL1 variants. In the spirurine nematodes B. malayi and A. suum operonic transcripts are resolved using SL1. Mapping these phenotypes onto the robust molecular phylogeny for the Nematoda suggests that operons evolved before SL2-like spliced leaders, which are an evolutionary invention of the rhabditine lineage

The Role of a Hot Gas Environment on the Evolution of Galaxies

Most spiral galaxies are found in galaxy groups with low velocity dispersions; most E/S0 galaxies are found in galaxy groups with relatively high velocity dispersions. The mass of the hot gas we can observe in the E/S0 groups via their thermal X-ray emission is, on average, as much as the baryonic mass of the galaxies in these groups. By comparison, galaxy clusters have as much or more hot gas than stellar mass. Hot gas in S-rich groups, however, is of low enough temperature for its X-ray emission to suffer heavy absorption due to Galactic HI and related observational effects, and hence is hard to detect. We postulate that such lower temperature hot gas does exist in low velocity dispersion, S-rich groups, and explore the consequences of this assumption. For a wide range of metallicity and density, hot gas in S-rich groups can cool in far less than a Hubble time. If such gas exists and can cool, especially when interacting with HI in existing galaxies, then it can help link together a number of disparate observations, both Galactic and extragalactic, that are otherwise difficult to understand.Comment: 16 pages with one figure. ApJ Letters, in pres

Renormalization of Crumpled Manifolds

We consider a model of D-dimensional tethered manifold interacting by excluded volume in R^d with a single point. By use of intrinsic distance geometry, we first provide a rigorous definition of the analytic continuation of its perturbative expansion for arbitrary D, 0 < D < 2. We then construct explicitly a renormalization operation, ensuring renormalizability to all orders. This is the first example of mathematical construction and renormalization for an interacting extended object with continuous internal dimension, encompassing field theory.Comment: 10 pages (1 figure, included), harvmac, SPhT/92-15

Study protocol: NITric oxide during cardiopulmonary bypass to improve Recovery in Infants with Congenital heart defects (NITRIC trial): a randomised controlled trial

Introduction Congenital heart disease (CHD) is a major cause of infant mortality. Many infants with CHD require corrective surgery with most operations requiring cardiopulmonary bypass (CPB). CPB triggers a systemic inflammatory response which is associated with low cardiac output syndrome (LCOS), postoperative morbidity and mortality. Delivery of nitric oxide (NO) into CPB circuits can provide myocardial protection and reduce bypass-induced inflammation, leading to less LCOS and improved recovery. We hypothesised that using NO during CPB increases ventilator-free days (VFD) (the number of days patients spend alive and free from invasive mechanical ventilation up until day 28) compared with standard care. Here, we describe the NITRIC trial protocol. Methods and analysis The NITRIC trial is a randomised, double-blind, controlled, parallel-group, two-sided superiority trial to be conducted in six paediatric cardiac surgical centres. One thousand three-hundred and twenty infants <2 years of age undergoing cardiac surgery with CPB will be randomly assigned to NO at 20 ppm administered into the CPB oxygenator for the duration of CPB or standard care (no NO) in a 1:1 ratio with stratification by age (<6 and ≥6 weeks), single ventricle physiology (Y/N) and study centre. The primary outcome will be VFD to day 28. Secondary outcomes include a composite of LCOS, need for extracorporeal membrane oxygenation or death within 28 days of surgery; length of stay in intensive care and in hospital; and, healthcare costs. Analyses will be conducted on an intention-to-treat basis. Preplanned secondary analyses will investigate the impact of NO on host inflammatory profiles postsurgery. Ethics and dissemination The study has ethical approval (HREC/17/QRCH/43, dated 26 April 2017), is registered in the Australian New Zealand Clinical Trials Registry (ACTRN12617000821392) and commenced recruitment in July 2017. The primary manuscript will be submitted for publication in a peer-reviewed journal. Trial registration number ACTRN12617000821392.</p

Upper Bounding the Graph Edit Distance Based on Rings and Machine Learning

The graph edit distance (GED) is a flexible distance measure which is widely used for inexact graph matching. Since its exact computation is NP-hard, heuristics are used in practice. A popular approach is to obtain upper bounds for GED via transformations to the linear sum assignment problem with error-correction (LSAPE). Typically, local structures and distances between them are employed for carrying out this transformation, but recently also machine learning techniques have been used. In this paper, we formally define a unifying framework LSAPE-GED for transformations from GED to LSAPE. We also introduce rings, a new kind of local structures designed for graphs where most information resides in the topology rather than in the node labels. Furthermore, we propose two new ring based heuristics RING and RING-ML, which instantiate LSAPE-GED using the traditional and the machine learning based approach for transforming GED to LSAPE, respectively. Extensive experiments show that using rings for upper bounding GED significantly improves the state of the art on datasets where most information resides in the graphs' topologies. This closes the gap between fast but rather inaccurate LSAPE based heuristics and more accurate but significantly slower GED algorithms based on local search

Federated singular value decomposition for high-dimensional data

Federated learning (FL) is emerging as a privacy-aware alternative to classical cloud-based machine learning. In FL, the sensitive data remains in data silos and only aggregated parameters are exchanged. Hospitals and research institutions which are not willing to share their data can join a federated study without breaching confidentiality. In addition to the extreme sensitivity of biomedical data, the high dimensionality poses a challenge in the context of federated genome-wide association studies (GWAS). In this article, we present a federated singular value decomposition algorithm, suitable for the privacy-related and computational requirements of GWAS. Notably, the algorithm has a transmission cost independent of the number of samples and is only weakly dependent on the number of features, because the singular vectors corresponding to the samples are never exchanged and the vectors associated with the features are only transmitted to an aggregator for a fixed number of iterations. Although motivated by GWAS, the algorithm is generically applicable for both horizontally and vertically partitioned data.Open access funding provided by University Library of Southern DenmarkHorizon 2020http://dx.doi.org/10.13039/501100007601Bundesministerium für Bildung und Forschunghttp://dx.doi.org/10.13039/501100002347University Library of Southern Denmar

A nomenclature for restriction enzymes, DNA methyltransferases, homing endonucleases and their genes

A nomenclature is described for restriction endonucleases, DNA methyltransferases, homing endonucleases and related genes and gene products. It provides explicit categories for the many different Type II enzymes now identified and provides a system for naming the putative genes found by sequence analysis of microbial genome