Improving the connectivity of community detection-based hierarchical routing protocols in large-scale wsns

The recent growth in the use of wireless sensor networks (WSNs) in many applications leads to the raise of a core infrastructure for communication and data gathering in Cyber-Physical Systems (CPS). The communication strategy in most of the WSNs relies on hierarchical clustering routing protocols due to their ad hoc nature. In the bulk of the existing approaches some special nodes, named Cluster-Heads (CHs), have the task of assembling clusters and intermediate the communication between the cluster members and a central entity in the network, the Sink. Therefore, the overall efficiency of such protocols is highly dependent on the even distribution of CHs in the network. Recently, a community detection-based approach, named RLP, have shown interesting results with respect to the CH distribution and availability that potentially increases the overall WSN efficiency. Despite the better results of RLP regarding the literature, the adopted CH election algorithm may lead to a CH shortage throughout the network operation. In line with that, in this paper, we introduce an improved version of RLP, named HRLP. Our proposal includes a hybrid CH election algorithm which relies on a computationally cheap and distributed probabilistic-based CH recovery procedure to improve the network connectivity. Additionally, we provide a performance analysis of HRLP and its comparison to other protocols by considering a large-scale WSN scenario. The results evince the improvements achieved by the proposed strategy by means of the network connectivity and lifetime metrics. (C) 2016 The Authors. Published by Elsevier B.V.Federal University of São Paulo, Avenida Cesare Mansueto Giulio Lattes, 1201, Parque Tecnológico, 12247014, São José dos Campos-SP-BrazilFederal University of São Paulo, Avenida Cesare Mansueto Giulio Lattes, 1201, Parque Tecnológico, 12247014, São José dos Campos-SP-BrazilWeb of Scienc

Community detection by consensus genetic-based algorithm for directed networks

Finding communities in networks is a commonly used form of network analysis. There is a myriad of community detection algorithms in the literature to perform this task. In spite of that, the number of community detection algorithms in directed networks is much lower than in undirected networks. However, evaluation measures to estimate the quality of communities in undirected networks nowadays have its adaptation to directed networks as, for example, the well-known modularity measure. This paper introduces a genetic-based consensus clustering to detect communities in directed networks with the directed modularity as the fitness function. Consensus strategies involve combining computational models to improve the quality of solutions generated by a single model. The reason behind the development of a consensus strategy relies on the fact that recent studies indicate that the modularity may fail in detecting expected clusterings. Computational experiments with artificial LFR networks show that the proposed method was very competitive in comparison to existing strategies in the literature. (C) 2016 The Authors. Published by Elsevier B.V.Instituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP) Av. Cesare M. G. Lattes, 1201, Eugênio de Mello, São José dos Campos-SP, CEP: 12247-014, BrasilInstituto de Ciência e Tecnologia, Universidade Federal de São Paulo (UNIFESP) Av. Cesare M. G. Lattes, 1201, Eugênio de Mello, São José dos Campos-SP, CEP: 12247-014, BrasilWeb of Scienc

Computing Volume Bounds of Inclusions by EIT Measurements

The size estimates approach for Electrical Impedance Tomography (EIT) allows for estimating the size (area or volume) of an unknown inclusion in an electrical conductor by means of one pair of boundary measurements of voltage and current. In this paper we show by numerical simulations how to obtain such bounds for practical application of the method. The computations are carried out both in a 2D and a 3D setting.Comment: 20 pages with figure

Generalized methods and solvers for noise removal from piecewise constant signals. II. New methods

Removing noise from signals which are piecewise constant (PWC) is a challenging signal processing problem that arises in many practical scientific and engineering contexts. In the first paper (part I) of this series of two, we presented background theory building on results from the image processing community to show that the majority of these algorithms, and more proposed in the wider literature, are each associated with a special case of a generalized functional, that, when minimized, solves the PWC denoising problem. It shows how the minimizer can be obtained by a range of computational solver algorithms. In this second paper (part II), using this understanding developed in part I, we introduce several novel PWC denoising methods, which, for example, combine the global behaviour of mean shift clustering with the local smoothing of total variation diffusion, and show example solver algorithms for these new methods. Comparisons between these methods are performed on synthetic and real signals, revealing that our new methods have a useful role to play. Finally, overlaps between the generalized methods of these two papers and others such as wavelet shrinkage, hidden Markov models, and piecewise smooth filtering are touched on

Glucose-fructose beverages do not alter the effects of training on lactate metabolism

Glucose-fructose beverages do not alter the effects of training on lactate metabolism Rosset R., Egli L., Cros J., Schneiter P. and Tappy L. and Lecoultre V. Department of Physiology, University of Lausanne, Lausanne, Switzerland. Introduction It is generally accepted that lactate is produced by skeletal muscle during exercise, and is either used in adjacent muscle fibers (lactate shuttle) or recycled to glucose in the liver. We have shown that ingestion of fructose-containing drinks stimulates lactate production and release from the liver during exercise, and that fructose-derived lactate is subsequently used as an energy substrate by muscle. The regulation of this liver to muscle fructose-lactate shuttle remains unknown. In this study, we assessed whether consumption of fructose-containing beverages alters the effects of training on fructose and lactate metabolism. Methods Two groups of eight sedentary male subjects were endurance-trained for three weeks while ingesting 489 mL/h of either a 9.8%-glucose 6.2%-fructose beverage (GLUFRU) or water (C) during exercise training sessions. An incremental test to exhaustion and a metabolic test were performed before and after the interventions to assess training adaptations and substrate use during endurance-type exercise. Indirect calorimetry, [1-13C]lactate and [6,6-2H2]glucose were used to calculate plasma lactate appearance, clearance and oxidation and glucose kinetics. Results Anthropometrics and performance parameters were similar in both groups at baseline. Plasma glucose concentrations (+1±3 vs. +3±3 % vs. baseline values), glucose rate of appearance (+3±7 vs. +2±3 %) and metabolic clearance (+6±8 vs. +1±5 %) remained stable after both GLUFRU and C training (all p=n.s.). Overall, lactate concentrations were decreased after intervention in both GLUFRU and C, but not differently between groups (-10±5 vs. -20±4 %; p<0.01 vs. baseline, p=n.s. between GLUFRU and C), as a result of an increased lactate metabolic clearance (+26.5±11.4 vs. +17.5±10.2 mL·min-1; p=0.01 vs. baseline, p=0.56 between GLUFRU and C). Lactate appearance (+10±6 vs. -4±9 %) and oxidation (+9±6 vs. - 6±9 %) remained unchanged across time and conditions (all p=n.s.). Maximal oxygen consumption (+287±53 vs. +249±104 mL·min-1) and power eliciting lactate threshold (+25±5 vs. +25±8 W) were similarly increased in GLUFRU and C (both p<0.01 vs. baseline, p=n.s. between GLUFRU and C). Discussion These data corroborate our earlier observation that fructose is converted into lactate by the liver and subsequently oxidized during exercise. Endurance training did not alter liver lactate release, but increased lactate metabolic clearance. The effects of endurance training were not differently altered by the consumption of fructose during training sessions, however

Tambora and the Mackerel Year: Phenology and Fisheries During an Extreme Climate Event

Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species—alewives, shad, herring, and mackerel—according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future

Desenvolvimento inicial do milho e atributos químicos do solo em função de diferentes doses de silicato de cálcio

Calcium silicate applied to the soil has an effect on plant nutrition since it is a source of silicon, calcium and magnesium. With the aim to evaluate the effect of doses of calcium silicate on soil chemical properties and on early development of corn, an experiment was conducted in a greenhouse, in pots containing eutroferric Oxisol, testing five rates of calcium silicate (0, 1.2; 2.4; 4.8 and 9.6 t ha-1) with four replications in a randomized complete block design. The levels of N, P, K, Ca and Mg in the plant shoot were evaluated, and, at the end of the experiment, shoot dry weight and plant height as well as Ca and Mg, and soil pH were also estimated. Shoot dry matter and plant height were not affected by fertilization with calcium silicate. The application of calcium silicate provided soil amendment, increasing the availability of calcium and magnesium, in addition to increasing the levels of N, K, Ca and Mg in the shoots of corn.O silicato de cálcio, quando aplicado ao solo, tem efeito sobre a nutrição das plantas, uma vez que é fonte de silício, cálcio e magnésio. Com o objetivo de avaliar o efeito de doses de silicato de cálcio sobre atributos químicos do solo e o desenvolvimento inicial da cultura do milho, realizou-se um experimento em casa de vegetação, em vasos com Latossolo Vermelho eutroférrico – LVef, para testar cinco doses de silicato de cálcio (0; 1,2; 2,4; 4,8 e 9,6 t ha-1) com quatro repetições em, delineamento experimental de blocos casualizados. Foram avaliados os teores N, P, K, Ca e Mg da parte aérea, e, ao final do experimento, a massa da matéria seca da parte aérea e altura de plantas, bem como os teores de Ca e Mg e pH do solo. A matéria seca da parte aérea e altura de plantas não foram influenciadas pela adubação com silicato de cálcio. A aplicação de silicato de cálcio promoveu uma ação corretiva no solo, com aumento da disponibilidade de cálcio e magnésio, além de promover incremento dos teores de N, K, Ca e Mg na parte aérea da cultura do milho

Planck-LFI radiometers' spectral response

The Low Frequency Instrument (LFI) is an array of pseudo-correlation radiometers on board the Planck satellite, the ESA mission dedicated to precision measurements of the Cosmic Microwave Background. The LFI covers three bands centred at 30, 44 and 70 GHz, with a goal bandwidth of 20% of the central frequency. The characterization of the broadband frequency response of each radiometer is necessary to understand and correct for systematic effects, particularly those related to foreground residuals and polarization measurements. In this paper we present the measured band shape of all the LFI channels and discuss the methods adopted for their estimation. The spectral characterization of each radiometer was obtained by combining the measured spectral response of individual units through a dedicated RF model of the LFI receiver scheme. As a consistency check, we also attempted end-to-end spectral measurements of the integrated radiometer chain in a cryogenic chamber. However, due to systematic effects in the measurement setup, only qualitative results were obtained from these tests. The measured LFI bandpasses exhibit a moderate level of ripple, compatible with the instrument scientific requirements.Comment: 16 pages, 9 figures, this paper is part of the Prelaunch status LFI papers published on JINST: http://www.iop.org/EJ/journal/-page=extra.proc5/jins