913 resultados para nature-based


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The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

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Since 1999, the National Commission for the Knowledge and Use of the Biodiversity (CONABIO) in Mexico has been developing and managing the “Operational program for the detection of hot-spots using remote sensing techniques”. This program uses images from the MODerate resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites and from the Advanced Very High Resolution Radiometer of the National Oceanic and Atmospheric Administration (NOAA-AVHRR), which are operationally received through the Direct Readout station (DR) at CONABIO. This allows the near-real time monitoring of fire events in Mexico and Central America. In addition to the detection of active fires, the location of hot spots are classified with respect to vegetation types, accessibility, and risk to Nature Protection Areas (NPA). Besides the fast detection of fires, further analysis is necessary due to the considerable effects of forest fires on biodiversity and human life. This fire impact assessment is crucial to support the needs of resource managers and policy makers for adequate fire recovery and restoration actions. CONABIO attempts to meet these requirements, providing post-fire assessment products as part of the management system in particular for satellite-based burnt area mapping. This paper provides an overview of the main components of the operational system and will present an outlook to future activities and system improvements, especially the development of a burnt area product. A special focus will also be placed on the fire occurrence within NPAs of Mexico

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Virus capsids are primed for disassembly, yet capsid integrity is key to generating a protective immune response. Foot-and-mouth disease virus (FMDV) capsids comprise identical pentameric protein subunits held together by tenuous noncovalent interactions and are often unstable. Chemically inactivated or recombinant empty capsids, which could form the basis of future vaccines, are even less stable than live virus. Here we devised a computational method to assess the relative stability of protein-protein interfaces and used it to design improved candidate vaccines for two poorly stable, but globally important, serotypes of FMDV: O and SAT2. We used a restrained molecular dynamics strategy to rank mutations predicted to strengthen the pentamer interfaces and applied the results to produce stabilized capsids. Structural analyses and stability assays confirmed the predictions, and vaccinated animals generated improved neutralizing-antibody responses to stabilized particles compared to parental viruses and wild-type capsids.

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CLEC-2 is a member of new family of C-type lectin receptors characterized by a cytosolic YXXL downstream of three acidic amino acids in a sequence known as a hemITAM (hemi-immunoreceptor tyrosine-based activation motif). Dimerization of two phosphorylated CLEC-2 molecules leads to recruitment of the tyrosine kinase Syk via its tandem SH2 domains and initiation of a downstream signaling cascade. Using Syk-deficient and Zap-70-deficient cell lines we show that hemITAM signaling is restricted to Syk and that the upstream triacidic amino acid sequence is required for signaling. Using surface plasmon resonance and phosphorylation studies, we demonstrate that the triacidic amino acids are required for phosphorylation of the YXXL. These results further emphasize the distinct nature of the proximal events in signaling by hemITAM relative to ITAM receptors.

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With the fast development of wireless communications, ZigBee and semiconductor devices, home automation networks have recently become very popular. Since typical consumer products deployed in home automation networks are often powered by tiny and limited batteries, one of the most challenging research issues is concerning energy reduction and the balancing of energy consumption across the network in order to prolong the home network lifetime for consumer devices. The introduction of clustering and sink mobility techniques into home automation networks have been shown to be an efficient way to improve the network performance and have received significant research attention. Taking inspiration from nature, this paper proposes an Ant Colony Optimization (ACO) based clustering algorithm specifically with mobile sink support for home automation networks. In this work, the network is divided into several clusters and cluster heads are selected within each cluster. Then, a mobile sink communicates with each cluster head to collect data directly through short range communications. The ACO algorithm has been utilized in this work in order to find the optimal mobility trajectory for the mobile sink. Extensive simulation results from this research show that the proposed algorithm significantly improves home network performance when using mobile sinks in terms of energy consumption and network lifetime as compared to other routing algorithms currently deployed for home automation networks.

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The timing and nature of the penultimate deglaciation, also known as Termination II (T-II), is subject of controversial discussions due to the scarcity of precisely-dated palaeoclimate records. Here we present a new precisely-dated and highly-resolved multi-proxy stalagmite record covering T-II from the high alpine Schafsloch Cave in Switzerland, an area where climate is governed by the North Atlantic. The inception of stalagmite growth at 137.4 ± 1.4 kyr before present (BP) indicates the presence of drip water and cave air temperatures of above 0°C, and is related to a climate-induced change in the thermal state (from cold- to warm-based) of the glacier above the cave. The cessation of stalagmite growth between 133.1 ± 0.7 and 131.9 ± 0.6 kyr BP is most likely related to distinct drop in temperature associated with Heinrich stadial 11. The resumption of stalagmite growth at 131.9 ± 0.6 kyr BP is accompanied by an abrupt increase in temperature and precipitation as indicated by distinct shifts in the oxygen and carbon isotopic composition as well as in trace element concentrations. The mid-point of T-II is around 131.8 ± 0.6 kyr BP in the Schafsloch Cave record is significantly earlier compared to the age of 129.1 ± 0.1 kyr BP in the Sanbao Cave record from China. The different ages between both records can be best explained by the competing effects of insolation and glacial boundary forcing on seasonality and snow cover extent in Eurasia.

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Network diagnosis in Wireless Sensor Networks (WSNs) is a difficult task due to their improvisational nature, invisibility of internal running status, and particularly since the network structure can frequently change due to link failure. To solve this problem, we propose a Mobile Sink (MS) based distributed fault diagnosis algorithm for WSNs. An MS, or mobile fault detector is usually a mobile robot or vehicle equipped with a wireless transceiver that performs the task of a mobile base station while also diagnosing the hardware and software status of deployed network sensors. Our MS mobile fault detector moves through the network area polling each static sensor node to diagnose the hardware and software status of nearby sensor nodes using only single hop communication. Therefore, the fault detection accuracy and functionality of the network is significantly increased. In order to maintain an excellent Quality of Service (QoS), we employ an optimal fault diagnosis tour planning algorithm. In addition to saving energy and time, the tour planning algorithm excludes faulty sensor nodes from the next diagnosis tour. We demonstrate the effectiveness of the proposed algorithms through simulation and real life experimental results.

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We show that the significantly different effective temperatures (T(eff)) achieved by the luminous blue variable AG Carinae during the consecutive visual minima of 1985-1990 (T(eff) similar or equal to 22,800 K) and 2000-2001 (T(eff) similar or equal to 17,000 K) place the star on different sides of the bistability limit, which occurs in line-driven stellar winds around T(eff) similar to 21,000 K. Decisive evidence is provided by huge changes in the optical depth of the Lyman continuum in the inner wind as T(eff) changes during the S Dor cycle. These changes cause different Fe ionization structures in the inner wind. The bistability mechanism is also related to the different wind parameters during visual minima: the wind terminal velocity was 2-3 times higher and the mass-loss rate roughly two times smaller in 1985-1990 than in 2000-2003. We obtain a projected rotational velocity of 220 +/- 50 km s(-1) during 1985-1990 which, combined with the high luminosity (L(star) = 1.5 x 10(6) L(circle dot)), puts AG Car extremely close to the Eddington limit modified by rotation (Omega Gamma limit): for an inclination angle of 90 degrees, Gamma(Omega) greater than or similar to 1.0 for M(circle dot) less than or similar to 60. Based on evolutionary models and mass budget, we obtain an initial mass of similar to 100 M(circle dot) and a current mass of similar to 60-70 M(circle dot) for AG Car. Therefore, AG Car is close to, if not at, the Omega Gamma limit during visual minimum. Assuming M = 70 M(circle dot), we find that Gamma(Omega) decreases from 0.93 to 0.72 as AG Car expands toward visual maximum, suggesting that the star is not above the Eddington limit during maximum phases.

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A novel technique for selecting the poles of orthonormal basis functions (OBF) in Volterra models of any order is presented. It is well-known that the usual large number of parameters required to describe the Volterra kernels can be significantly reduced by representing each kernel using an appropriate basis of orthonormal functions. Such a representation results in the so-called OBF Volterra model, which has a Wiener structure consisting of a linear dynamic generated by the orthonormal basis followed by a nonlinear static mapping given by the Volterra polynomial series. Aiming at optimizing the poles that fully parameterize the orthonormal bases, the exact gradients of the outputs of the orthonormal filters with respect to their poles are computed analytically by using a back-propagation-through-time technique. The expressions relative to the Kautz basis and to generalized orthonormal bases of functions (GOBF) are addressed; the ones related to the Laguerre basis follow straightforwardly as a particular case. The main innovation here is that the dynamic nature of the OBF filters is fully considered in the gradient computations. These gradients provide exact search directions for optimizing the poles of a given orthonormal basis. Such search directions can, in turn, be used as part of an optimization procedure to locate the minimum of a cost-function that takes into account the error of estimation of the system output. The Levenberg-Marquardt algorithm is adopted here as the optimization procedure. Unlike previous related work, the proposed approach relies solely on input-output data measured from the system to be modeled, i.e., no information about the Volterra kernels is required. Examples are presented to illustrate the application of this approach to the modeling of dynamic systems, including a real magnetic levitation system with nonlinear oscillatory behavior.

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The metastable phase diagram of the BCC-based ordering equilibria in the Fe-Al-Mo system has been calculated via a truncated cluster expansion, through the combination of Full-Potential-Linear augmented Plane Wave (FP-LAPW) electronic structure calculations and of Cluster Variation Method (CVM) thermodynamic calculations in the irregular tetrahedron approximation. Four isothermal sections at 1750 K, 2000 K, 2250 K and 2500 K are calculated and correlated with recently published experimental data on the system. The results confirm that the critical temperature for the order-disorder equilibrium between Fe(3)Al-D0(3) and FeAl-B2 is increased by Mo additions, while the critical temperature for the FeAl-B2/A2 equilibrium is kept approximately invariant with increasing Mo contents. The stabilization of the Al-rich A2 phase in equilibrium with overstoichiometric B2-(Fe,Mo)Al is also consistent with the attribution of the A2 structure to the tau(2) phase, stable at high temperatures in overstoichiometric B2-FeAl. (C) 2009 Elsevier Ltd. All rights reserved.

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Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

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The interactions between three different protein antigens and dioctadecyldimethylammonium bromide (DODAB) dispersed in aqueous solutions from probe sonication or adsorbed its one bilayer onto particles was comparatively investigated. The three model proteins were bovine serum albumin (BSA), purified 18 kDa/14 kDa antigens from Taenia crassiceps (18/14-Tcra) and a recombinant, heat-shock protein hsp-18 kDa from Mycobacterium leprae. Protein-DODAB complexes in water solution were characterized by dynamic light scattering for sizing and zeta-potential analysis. Cationic complexes (80-100 nm of mean hydrodynamic diameter) displayed sizes similar to those of DODAB bilayer fragments (BF) in aqueous solution and good colloid stability over a range of DODAB and protein concentrations. The amount of cationic lipid required for attaining zero of zeta-potential at a given protein amount depended on protein nature being smaller for 18 kDa/14 kDa antigens than for BSA. Mean diameters for DODAB/protein complexes increased, whereas zeta-potentials decreased with NaCl or protein concentration. In mice, weak IgG production but significant cellular immune responses were induced by the complexes in comparison to antigens alone or carried by aluminum hydroxide as shown from IgG in serum determined by ELISA, delayed type hypersensitivity reaction from footpad swelling tests and cytokines analysis. The novel cationic adjuvant/protein complexes revealed good colloid stability and potential for vaccine design at a reduced DODAB concentration. (C) 2009 Elsevier Ltd. All rights reserved.

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The catalytic activity of Ni/La(2)O(3)-Al(2)O(3) Catalysts modified with noble metals(Pt and Pd) was investigated in the steam reforming of ethanol. The catalysts were characterized by ICP, S(BFT), X-ray diffraction, temperature-programmed reduction, UV-vis diffuse reflectance spectroscopy and X-ray absorption fine structure (XANES). The results showed that the formation of inactive nickel aluminate was prevented by the presence of La(2)O(3) dispersed on the alumina. The promoting effect of noble metals included a marked decrease in the reduction temperatures of NiO species interacting with the support. due to the hydrogen spillover effect, facilitating greatly the reduction of the promoted catalysts. it was seen that the addition of noble metal stabilized the Ni sites in the reduced state throughout the reaction, increasing ethanol conversion and decreasing coke formation, irrespective of the nature or loading of the noble metal. (C) 2009 Elsevier B.V. All rights reserved.

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Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor quality articles and should be removed from the database. The aim of this study is to classify the articles of Wikipedia into two classes class 0 (poor quality) and class 1(good quality) using the Adaptive Neuro Fuzzy Inference System (ANFIS) and data mining techniques. Two ANFIS are built using the Fuzzy Logic Toolbox [1] available in Matlab. The first ANFIS is based on the rules obtained from J48 classifier in WEKA while the other one was built by using the expert’s knowledge. The data used for this research work contains 226 article’s records taken from the German version of Wikipedia. The dataset consists of 19 inputs and one output. The data was preprocessed to remove any similar attributes. The input variables are related to the editors, contributors, length of articles and the lifecycle of articles. In the end analysis of different methods implemented in this research is made to analyze the performance of each classification method used.

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Provisioning of real-time multimedia sessions over wireless cellular network poses unique challenges due to frequent handoff and rerouting of a connection. For this reason, the wireless networks with cellular architecture require efficient user mobility estimation and prediction. This paper proposes using Robust Extended Kalman Filter as a location heading altitude estimator of mobile user for next cell prediction in order to improve the connection reliability and bandwidth efficiency of the underlying system. Through analysis we demonstrate that our algorithm reduces the system complexity (compared to existing approach using pattern matching and Kalman filter) as it requires only two base station measurements or only the measurement from the closest base station. Further, the technique is robust against system uncertainties due to inherent deterministic nature in the mobility model. Through simulation, we show the accuracy and simplicity in implementation of our prediction algorithm.