AFQN: approximate Qn estimation in data streams

We present afqn (Approximate Fast Qn), a novel algorithm for approximate computation of the Qn scale estimator in a streaming setting, in the sliding window model. It is well-known that computing the Qn estimator exactly may be too costly for some applications, and the problem is a fortiori exacerbated in the streaming setting, in which the time available to process incoming data stream items is short. In this paper we show how to efficiently and accurately approximate the Qn estimator. As an application, we show the use of afqn for fast detection of outliers in data streams. In particular, the outliers are detected in the sliding window model, with a simple check based on the Qn scale estimator. Extensive experimental results on synthetic and real datasets confirm the validity of our approach by showing up to three times faster updates per second. Our contributions are the following ones: (i) to the best of our knowledge, we present the first approximation algorithm for online computation of the Qn scale estimator in a streaming setting and in the sliding window model; (ii) we show how to take advantage of our UDDSketch algorithm for quantile estimation in order to quickly compute the Qn scale estimator; (iii) as an example of a possible application of the Qn scale estimator, we discuss how to detect outliers in an input data stream

In situ and in vitro nutritional evaluation of rumen-protected lipids

Rumen-protected lipids are a class of products which is increasingly used in ruminant nutrition even if the results are not homogeneous. The different results may be due to different analytical or technological characteristics. Aim of this work was therefore to compare the in situ rumen behaviour of different soaps as well as their in vitro intestinal digestibility

Fast online computation of the Qn estimator with applications to the detection of outliers in data streams

We present FQN (Fast Qn), a novel algorithm for online computation of the Qn scale estimator. The algorithm works in the sliding window model, cleverly computing the Qn scale estimator in the current window. We thoroughly compare our algorithm for online Qn with the state of the art competing algorithm by Nunkesser et al., and show that FQN (i) is faster, requiring only O(s) time in the worst case where s is the length of the window (ii) its computational complexity does not depend on the input distribution and (iii) it requires less space. To the best of our knowledge, our algorithm is the first that allows online computation of the Qn scale estimator in worst case time linear in the size of the window. As an example of a possible application, besides its use as a robust measure of statistical dispersion, we show how to use the Qn estimator for fast detection of outliers in data streams. Extensive experimental results on both synthetic and real datasets confirm the validity of our approach

Fault Tolerance Analysis of a Bis-Ferrocene QCA Wire

Molecular Quantum Dot Cellular Automata (mQCA) are among the most promising emerging technologies for the expected theoretical operating frequencies (THz), the high device densities and the non-cryogenic working temperature. In this paper, we performed an analysis of the possible fabrication defects of a molecular QCA wire built with ad-hoc synthesized bis-ferrocene molecules. We then evaluated the fault tolerance of a real QCA device and assessed its performance in non-ideal conditions, by defining a new methodology for the fault analysis in the mQCA technology

Simulation of a molecular QCA wire

Molecular Quantum Dot Cellular Automata (MQCA) are among the most promising emerging technologies for the expected theoretical operating frequencies (THz), the high device densities and the non-cryogenic working temperature. In this work we simulated a molecular QCA wire, based on a molecule synthesized ad-hoc for this technology. The results discussed are obtained by means of iterative steps of ab-initio calculations

Enabling Design and Simulation of Massive Parallel Nanoarchitectures

A common element in emerging nanotechnologies is the increasing complex- ity of the problems to face when attempting the design phase, because issues related to technology, specific application and architecture must be evalu- ated simultaneously. In several cases faced problems are known, but require a fresh re-think on the basis of different constraints not enforced by standard design tools. Among the emerging nanotechnologies, the two-dimensional structures based on nanowire arrays is promising in particular for massively parallel architec- tures. Several studies have been proposed on the exploration of the space of architectural solutions, but only a few derived high-level information from the results of an extended and reliable characterization of low-level structures. The tool we present is of aid in the design of circuits based on nanotech- nologies, here discussed in the specific case of nanowire arrays, as best candi- date for massively parallel architectures. It enables the designer to start from a standard High-level Description Languages (HDL), inherits constraints at physical level and applies them when organizing the physical implementation of the circuit elements and of their connections. It provides a complete simu- lation environment with two levels of refinement. One for DC analysis using a fast engine based on a simple switch level model. The other for obtaining transient performance based on automatic extraction of circuit parasitics, on detailed device (nanowire-FET) information derived by experiments or by existing accurate models, and on spice-level modeling of the nanoarray. Re- sults about the method used for the design and simulation of circuits based on nanowire-FET and nanoarray will be presente

Autonomous and self-sustained circadian oscillators displayed in human islet cells

Aims/hypothesis: Following on from the emerging importance of the pancreas circadian clock on islet function and the development of type 2 diabetes in rodent models, we aimed to examine circadian gene expression in human islets. The oscillator properties were assessed in intact islets as well as in beta cells. Methods: We established a system for long-term bioluminescence recording in cultured human islets, employing lentivector gene delivery of the core clock gene Bmal1 (also known as Arntl)-luciferase reporter. Beta cells were stably labelled using a rat insulin2 promoter fluorescent construct. Single-islet/cell oscillation profiles were measured by combined bioluminescence-fluorescence time-lapse microscopy. Results: Human islets synchronised in vitro exhibited self-sustained circadian oscillations of Bmal1-luciferase expression at both the population and single-islet levels, with period lengths of 23.6 and 23.9h, respectively. Endogenous BMAL1 and CRY1 transcript expression was circadian in synchronised islets over 48h, and antiphasic to REV-ERBα (also known as NR1D1), PER1, PER2, PER3 and DBP transcript circadian profiles. HNF1A and PDX1 exhibited weak circadian oscillations, in phase with the REV-ERBα transcript. Dispersed islet cells were strongly oscillating as well, at population and single-cell levels. Importantly, beta and non-beta cells revealed oscillatory profiles that were well synchronised with each other. Conclusions/interpretation: We provide for the first time compelling evidence for high-amplitude cell-autonomous circadian oscillators displayed in human pancreatic islets and in dispersed human islet cells. Moreover, these clocks are synchronised between beta and non-beta cells in primary human islet cell culture

Autonomous and self-sustained circadian oscillators displayed in human islet cells

Aims/hypothesis: Following on from the emerging importance of the pancreas circadian clock on islet function and the development of type 2 diabetes in rodent models, we aimed to examine circadian gene expression in human islets. The oscillator properties were assessed in intact islets as well as in beta cells. Methods: We established a system for long-term bioluminescence recording in cultured human islets, employing lentivector gene delivery of the core clock gene Bmal1 (also known as Arntl)-luciferase reporter. Beta cells were stably labelled using a rat insulin2 promoter fluorescent construct. Single-islet/cell oscillation profiles were measured by combined bioluminescence-fluorescence time-lapse microscopy. Results: Human islets synchronised in vitro exhibited self-sustained circadian oscillations of Bmal1-luciferase expression at both the population and single-islet levels, with period lengths of 23.6 and 23.9h, respectively. Endogenous BMAL1 and CRY1 transcript expression was circadian in synchronised islets over 48h, and antiphasic to REV-ERBα (also known as NR1D1), PER1, PER2, PER3 and DBP transcript circadian profiles. HNF1A and PDX1 exhibited weak circadian oscillations, in phase with the REV-ERBα transcript. Dispersed islet cells were strongly oscillating as well, at population and single-cell levels. Importantly, beta and non-beta cells revealed oscillatory profiles that were well synchronised with each other. Conclusions/interpretation: We provide for the first time compelling evidence for high-amplitude cell-autonomous circadian oscillators displayed in human pancreatic islets and in dispersed human islet cells. Moreover, these clocks are synchronised between beta and non-beta cells in primary human islet cell culture