Cognitive radio networks (CRNs) have emerged as advanced and promising paradigm to exploit the existing wireless spectrum opportunistically. It is crucial for users in CRNs to search for neighbors via rendezvous process and thereby establish the communication links to exchange the information necessary for spectrum management and channel contention etc. This paper focuses on the design of algorithms for blind rendezvous, i.e., rendezvous without using any central controller and common control channel (CCC). We propose a jump-stay based channel-hopping (CH) algorithm for blind rendezvous. The basic idea is to generate CH sequence in rounds and each round consists of a jump-pattern and a stay-pattern. Users "jump" on available channels in the jump-pattern while "stay" on a specific channel in the stay-pattern. Compared with the existing CH algorithms, our algorithm achieves the following advances: i) guaranteed rendezvous without the need of timesynchronization; ii) applicability to rendezvous of multi-user and multi-hop scenarios. We derive the maximum time-torendezvous (TTR) and the upper-bound of expected TTR of our algorithm for both 2-user and multi-user scenarios (shown in Table I). Extensive simulations are further conducted to evaluate performance of our algorithm.

Researchers have suggested fluctuating asymmetry (FA) as an indicator of environmental stress and have usually tested this assertion by examining relations between FA of single traits and stress. Fluctuating asymmetry stress relations are real but are typically weak and difficult to detect. Researchers would like to maximize the probability of detecting FA-stress relations when they exist. We assert that analyses based on the FA of multiple traits may provide better methods for detecting stress. In this article, we used computer simulations to compare the ability of six analyses to detect differences in FA between stressed and unstressed populations. We show that the optimal analysis depends upon the underlying form of the FA distributions. We also show that two of the analyses had inflated Type I errors in some situations. Finally, we quantify the advantage of our preferred analysis over those of single-trait FA in detecting stress.

Background: Surgical mortality data are collected routinely in high-income countries, yet virtually no low-or middle-income countries have outcome surveillance in place. The aim was prospectively to collect worldwide mortality data following emergency abdominal surgery, comparing findings across countries with a low, middle or high Human Development Index (HDI).Methods: This was a prospective, multicentre, cohort study. Self-selected hospitals performing emergency surgery submitted prespecified data for consecutive patients from at least one 2-week interval during July to December 2014. Postoperative mortality was analysed by hierarchical multivariable logistic regression.

Given a set of intervals (pairs of real numbers), we look at the problem of finding a minimal partition of this set such that no element of the partition contains two overlapping intervals. We exhibit a Θ(N log N) algorithm which is optimal. The problem has applications in LSI layout design and job scheduling

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