Steady-State Analysis of Load Balancing with Coxian-22 Distributed Service Times

This paper studies load balancing for many-server ($N$ servers) systems. Each server has a buffer of size $b-1,$ and can have at most one job in service and $b-1$ jobs in the buffer. The service time of a job follows the Coxian-2 distribution. We focus on steady-state performance of load balancing policies in the heavy traffic regime such that the normalized load of system is $\lambda = 1 - N^{-\alpha}$ for $0<\alpha<0.5.$ We identify a set of policies that achieve asymptotic zero waiting. The set of policies include several classical policies such as join-the-shortest-queue (JSQ), join-the-idle-queue (JIQ), idle-one-first (I1F) and power-of-$d$-choices (Po$d$) with $d=O(N^\alpha\log N)$. The proof of the main result is based on Stein's method and state space collapse. A key technical contribution of this paper is the iterative state space collapse approach that leads to a simple generator approximation when applying Stein's method

Statistically-secure ORAM with O~(log⁡2n)\tilde{O}(\log^2 n) Overhead

We demonstrate a simple, statistically secure, ORAM with computational overhead $\tilde{O}(\log^2 n)$; previous ORAM protocols achieve only computational security (under computational assumptions) or require $\tilde{\Omega}(\log^3 n)$ overheard. An additional benefit of our ORAM is its conceptual simplicity, which makes it easy to implement in both software and (commercially available) hardware. Our construction is based on recent ORAM constructions due to Shi, Chan, Stefanov, and Li (Asiacrypt 2011) and Stefanov and Shi (ArXiv 2012), but with some crucial modifications in the algorithm that simplifies the ORAM and enable our analysis. A central component in our analysis is reducing the analysis of our algorithm to a "supermarket" problem; of independent interest (and of importance to our analysis,) we provide an upper bound on the rate of "upset" customers in the "supermarket" problem

Отображение различий в восприятии времени и временной перспективы носителей украинской, американской и французской культур

У статті досліджено показники монохронності та поліхронності у сприйнятті часу представників української, американської та французької культур.In this article the indexes are probed in perception of time of representatives of the Ukrainian, American and French cultures.В статье исследованы показатели монохронности и полихронности в восприятии времени представителей украинской, американской и французской культур

tRNA is a new target for cleavage by a MazF toxin

Toxin-antitoxin (TA) systems play key roles in bacterial persistence, biofilm formation and stress responses. The MazF toxin from the Escherichia coli mazEF TA system is a sequence- and single-strand-specific endoribonuclease, and many studies have led to the proposal that MazF family members exclusively target mRNA. However, recent data indicate some MazF toxins can cleave specific sites within rRNA in concert with mRNA. In this report, we identified the repertoire of RNAs cleaved by Mycobacterium tuberculosis toxin MazF-mt9 using an RNA-seq-based approach. This analysis revealed that two tRNAs were the principal targets of MazF-mt9, and each was cleaved at a single site in either the tRNAPro14 D-loop or within the tRNALys43 anticodon. This highly selective target discrimination occurs through recognition of not only sequence but also structural determinants. Thus, MazF-mt9 represents the only MazF family member known to target tRNA and to require RNA structure for recognition and cleavage. Interestingly, the tRNase activity of MazF-mt9 mirrors basic features of eukaryotic tRNases that also generate stable tRNA-derived fragments that can inhibit translation in response to stress. Our data also suggest a role for tRNA distinct from its canonical adapter function in translation, as cleavage of tRNAs by MazF-mt9 downregulates bacterial growth

Kinetic modelling of quantitative proteome data predicts metabolic reprogramming of liver cancer

BACKGROUND: Metabolic alterations can serve as targets for diagnosis and cancer therapy. Due to the highly complex regulation of cellular metabolism, definite identification of metabolic pathway alterations remains challenging and requires sophisticated experimentation. METHODS: We applied a comprehensive kinetic model of the central carbon metabolism (CCM) to characterise metabolic reprogramming in murine liver cancer. RESULTS: We show that relative differences of protein abundances of metabolic enzymes obtained by mass spectrometry can be used to assess their maximal velocity values. Model simulations predicted tumour-specific alterations of various components of the CCM, a selected number of which were subsequently verified by in vitro and in vivo experiments. Furthermore, we demonstrate the ability of the kinetic model to identify metabolic pathways whose inhibition results in selective tumour cell killing. CONCLUSIONS: Our systems biology approach establishes that combining cellular experimentation with computer simulations of physiology-based metabolic models enables a comprehensive understanding of deregulated energetics in cancer. We propose that modelling proteomics data from human HCC with our approach will enable an individualised metabolic profiling of tumours and predictions of the efficacy of drug therapies targeting specific metabolic pathways

Analytical challenges in human plasma lipidomics: A winding path towards the truth

Human plasma lipidome has been extensively studied in many pathophysiological contexts with the hope of identifying biomarkers for early diagnostics and monitoring the progression and treatment of a broad spectrum of diseases. However, despite remarkable progress in lipidomics technologies, the concordance of lipidomics measurements between independent laboratories remains limited and not fulfilling the criteria of common laboratory diagnostics. Here we highlighted a few critical aspects of epidemiological studies of the plasma lipidome, including the selection of study cohorts, collection of plasma samples as well as extraction, identification and quantification of lipids. We argue that reporting the abundances of plasma lipids as molar concentrations is a key turning point during the transition of research lipidomics into a common tool of clinical diagnostics