44 research outputs found
Bounded Search Tree Algorithms for Parameterized Cograph Deletion: Efficient Branching Rules by Exploiting Structures of Special Graph Classes
Many fixed-parameter tractable algorithms using a bounded search tree have
been repeatedly improved, often by describing a larger number of branching
rules involving an increasingly complex case analysis. We introduce a novel and
general search strategy that branches on the forbidden subgraphs of a graph
class relaxation. By using the class of -sparse graphs as the relaxed
graph class, we obtain efficient bounded search tree algorithms for several
parameterized deletion problems. We give the first non-trivial bounded search
tree algorithms for the cograph edge-deletion problem and the trivially perfect
edge-deletion problems. For the cograph vertex deletion problem, a refined
analysis of the runtime of our simple bounded search algorithm gives a faster
exponential factor than those algorithms designed with the help of complicated
case distinctions and non-trivial running time analysis [21] and computer-aided
branching rules [11].Comment: 23 pages. Accepted in Discrete Mathematics, Algorithms and
Applications (DMAA
Renal pericytes: regulators of medullary blood flow
Regulation of medullary blood flow (MBF) is essential in maintaining normal kidney function. Blood flow to the medulla is supplied by the descending vasa recta (DVR), which arise from the efferent arterioles of juxtamedullary glomeruli. DVR are composed of a continuous endothelium, intercalated with smooth muscle-like cells called pericytes. Pericytes have been shown to alter the diameter of isolated and in situ DVR in response to vasoactive stimuli that are transmitted via a network of autocrine and paracrine signalling pathways. Vasoactive stimuli can be released by neighbouring tubular epithelial, endothelial, red blood cells and neuronal cells in response to changes in NaCl transport and oxygen tension. The experimentally described sensitivity of pericytes to these stimuli strongly suggests their leading role in the phenomenon of MBF autoregulation. Because the debate on autoregulation of MBF fervently continues, we discuss the evidence favouring a physiological role for pericytes in the regulation of MBF and describe their potential role in tubulo-vascular cross-talk in this region of the kidney. Our review also considers current methods used to explore pericyte activity and function in the renal medulla
A comprehensive SARS-CoV-2 and COVID-19 review, Part 2: host extracellular to systemic effects of SARS-CoV-2 infection
COVID-19, the disease caused by SARS-CoV-2, has caused significant morbidity and mortality worldwide. The betacoronavirus continues to evolve with global health implications as we race to learn more to curb its transmission, evolution, and sequelae. The focus of this review, the second of a three-part series, is on the biological effects of the SARS-CoV-2 virus on post-acute disease in the context of tissue and organ adaptations and damage. We highlight the current knowledge and describe how virological, animal, and clinical studies have shed light on the mechanisms driving the varied clinical diagnoses and observations of COVID-19 patients. Moreover, we describe how investigations into SARS-CoV-2 effects have informed the understanding of viral pathogenesis and provide innovative pathways for future research on the mechanisms of viral diseases
Passive Q-switching and mode-locking for the generation of nanosecond to femtosecond pulses
Generating the states of a binary stochastic system
AbstractAn important aspect of planning a communication or distribution system is assessing its performance when the components are subject to random failure. Since exact calculation of stochastic performances measures is usually difficult, the behavior of the system can instead be approximated by generating a subset of all system states. Specifically, we consider her e the generation of states of a binary stochastic system in order of nonincreasing probability. Such an ordering ensures that maximum coverage of the state space (in terms of probability) will be obtained for a specified number of generated states. We identify a particular discrete structure, a distributive lattice, underlying this generation problem, and use this structure to guide an algorithm for generating in order the states of the given system. Computational results suggest that the proposed method improves on existing algorithms for this generation problem