Fast and Compact Distributed Verification and Self-Stabilization of a DFS Tree

We present algorithms for distributed verification and silent-stabilization of a DFS(Depth First Search) spanning tree of a connected network. Computing and maintaining such a DFS tree is an important task, e.g., for constructing efficient routing schemes. Our algorithm improves upon previous work in various ways. Comparable previous work has space and time complexities of $O(n\log \Delta)$ bits per node and $O(nD)$ respectively, where $\Delta$ is the highest degree of a node, $n$ is the number of nodes and $D$ is the diameter of the network. In contrast, our algorithm has a space complexity of $O(\log n)$ bits per node, which is optimal for silent-stabilizing spanning trees and runs in $O(n)$ time. In addition, our solution is modular since it utilizes the distributed verification algorithm as an independent subtask of the overall solution. It is possible to use the verification algorithm as a stand alone task or as a subtask in another algorithm. To demonstrate the simplicity of constructing efficient DFS algorithms using the modular approach, We also present a (non-sielnt) self-stabilizing DFS token circulation algorithm for general networks based on our silent-stabilizing DFS tree. The complexities of this token circulation algorithm are comparable to the known ones

Liquid Level Sensing System

A liquid level sensing system includes waveguides disposed in a liquid and distributed along a path with a gap between adjacent waveguides. A source introduces electromagnetic energy into the waveguides at a first end of the path. A portion of the electromagnetic energy exits the waveguides at a second end of the path. A detector measures the portion of the electromagnetic energy exiting the second end of the path

A Time-Space Tradeoff for Triangulations of Points in the Plane

In this paper, we consider time-space trade-offs for reporting a triangulation of points in the plane. The goal is to minimize the amount of working space while keeping the total running time small. We present the first multi-pass algorithm on the problem that returns the edges of a triangulation with their adjacency information. This even improves the previously best known random-access algorithm

Prediction Model to Identify Patients at Risk of 30-Day Treatment Failure in Patients With Staphylococcus aureus Bacteremia

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Morbidity from in-hospital complications is greater than treatment failure in patients with Staphylococcus aureus bacteraemia

Background: Various studies have identified numerous factors associated with poor clinical outcomes in patients with Staphylococcus aureus bacteraemia (SAB). A new study was created to provide deeper insight into in-hospital complications and risk factors for treatment failure. Methods: Adult patients hospitalised with Staphylococcus aureus bacteraemia (SAB) were recruited prospectively into a multi-centre cohort. The primary outcome was treatment failure at 30 days (composite of all-cause mortality, persistent bacteraemia, or recurrent bacteraemia), and secondary measures included in-hospital complications and mortality at 6- and 12-months. Data were available for 222 patients recruited from February 2011 to December 2012. Results: Treatment failure at 30-days was recorded in 14.4% of patients (30-day mortality 9.5%). Multivariable analysis predictors of treatment failure included age > 70 years, Pitt bacteraemia score ≥ 2, CRP at onset of SAB > 250 mg/L, and persistent fevers after SAB onset; serum albumin at onset of SAB, receipt of appropriate empiric treatment, recent healthcare attendance, and performing echocardiography were protective. 6-month and 12-month mortality were 19.1% and 24.2% respectively. 45% experienced at least one in-hospital complication, including nephrotoxicity in 19.5%. Conclusions: This study demonstrates significant improvements in 30-day outcomes in SAB in Australia. However, we have identified important areas to improve outcomes from SAB, particularly reducing renal dysfunction and in-hospital treatment-related complications

Identification of Termite Species and Subspecies of the Genus Zootermopsis Using Near-Infrared Reflectance Spectroscopy

Dampwood termites of the genus Zootermopsis (Isoptera: Termopsidae) are an abundant group of basal termites found in temperate forests of western North America. Three species are currently recognized in the genus and one of these species is subdivided into two subspecies. Although morphological and genetic characters are useful in differentiating among the three species and the two subspecies, respectively, only hydrocarbon analysis can enable differentiation both among the three species and the two subspecies. Due to the limitations of hydrocarbon analysis, such as the need for fresh specimens, alternative methods that could rapidly and accurately identify Zootermopsis would be useful. Using a partial least squares analysis of near-infrared spectra, each of the Zootermopsis species and subspecies were identified with greater than 95% and 80% accuracy, respectively. Neural network analysis of the near-infrared spectra successfully enabled the identification of the species and subspecies with greater than 99% accuracy. The inexpensive, reproducible, and rapid nature of near-infrared spectroscopy makes it a viable alternative to morphological, hydrocarbon, or genetic analysis for identifying Zootermopsis

CALIBRATION AND APPLICATION OF NUCLEAR TRACK DETECTORS FOR HIGH-TEMPERATURE PLASMA DIAGNOSTICS

Abstract The paper reports on features of so-called solid-state nuclear track detectors (SSNTDs), their calibration measurements performed with known ion beams, and their different applications for detailed studies of charged particle emissions from various high-temperatures plasma facilities