Market-based sensor relocation by robot team inwireless sensor networks

Randomly scattered sensors may cause sensing holes and redundant sensors. In carrier-based sensor relocation, mobile robots (with limited capacity to carry sensors) pick up additional or redundant sensors and relocate them at sensing holes. In the only known localized algorithm, robots randomly traverse field and act based on identified pair of spare sensor and coverage hole. We propose a Market-based Sensor Relocation (MSR) algorithm, which optimizes sensor deployment location, and introduces bidding and coordinating among neighboring robots. Sensors along the boundary of each hole elect one of them as the representative, which bids to neighboring robots for hole filling service. Each robot randomly explores by applying Least Recently Visited policy. It chooses the best bid according to Cost over Progress ratio and fetches a spare sensor nearby to cover the corresponding sensing hole. Robots within communication range share their tasks to search for better possible solutions. Simulation shows that MSR outperforms the existing competing algorithm G-R3S2 significantly on total robot traversed path and energy, and time to cover holes, slightly on number of sensors needed to cover the hole and number of sensor messages for bidding and deployment location sharing.

Influences of Structural Damping and Buoyancy-Weight Ratio on Dynamic Responses of Submerged Floating Tunnel

The recent progress of submerged floating tunnel (SFT) investigation and SFT prototype (SFTP) project in Qiandao Lake (Zhejiang Province, P.R. China) is the background of this research. Structural damping effect is brought into present computation model in terms of Rayleigh damping. Based on the FEM computational results of SFTPs as a function of buoyancy-weight ratio (BWR) under hydrodynamic loads, the effect of BWR on the dynamic response of SFT is illustrated. In addition, human comfort index is adopted to discuss the comfort status of the SFTP.

A presumed joint pdf model for turbulent combustion with varying equivalence ratio

Modeling of the joint probability density function of the mixture fraction and progress variable with a given covariance value is studied. This modeling is validated using experimental and direct numerical simulation (DNS) data. A very good agreement with experimental data of turbulent stratified flames and DNS data of a lifted hydrogen jet flame is obtained. The effect of using this joint pdf modeling to calculate the mean reaction rate with a flamelet closure in Reynolds averaged Navier-Stokes (RANS) calculation of stratified flames is studied. The covariance effect is observed to be large within the flame brush. The results obtained from RANS calculations using this modeling for stratified jet- and rod-stabilized V-flames are discussed and compared to the measurements as a posteriori validation for the joint probability density function model with the flamelet closure. The agreement between the computed and measured values of flame and turbulence quantities is found to be good. © 2012 Copyright Taylor and Francis Group, LLC.

Statistics of reaction progress variable and mixture fraction gradients from DNS of turbulent partially premixed flames

Statistically planar turbulent partially premixed flames for different initial intensities of decaying turbulence have been simulated for global equivalence ratios = 0.7 and 1.0 using three-dimensional, simplified chemistry-based direct numerical simulations (DNS). The simulation parameters are chosen such that the flames represent the thin reaction zones regime combustion. A random bimodal distribution of equivalence ratio is introduced in the unburned gas ahead of the flame to account for the mixture inhomogeneity. The results suggest that the probability density functions (PDFs) of the mixture fraction gradient magnitude |Δξ| (i.e., P(|Δξ|)) can be reasonably approximated using a log-normal distribution. However, this presumed PDF distribution captures only the qualitative nature of the PDF of the reaction progress variable gradient magnitude |Δc| (i.e., P(|Δc|)). It has been found that a bivariate log-normal distribution does not sufficiently capture the quantitative behavior of the joint PDF of |Δξ| and |Δc| (i.e., P(|Δξ|, |Δc|)), and the agreement with the DNS data has been found to be poor in certain regions of the flame brush, particularly toward the burned gas side of the flame brush. Moreover, the variables |Δξ| and |Δc| show appreciable correlation toward the burned gas side of the flame brush. These findings are corroborated further using a DNS data of a lifted jet flame to study the flame geometry dependence of these statistics. © 2013 Copyright Taylor and Francis Group, LLC.

Recent Progress in Constraining the Equation of State of Dense Neutron-Rich Nuclear Matter with Heavy-Ion Reactions

The nuclear symmetry energy E-sym(rho) is the most uncertain part of the Equation of State (EOS) of dense neutron-rich nuclear matter. In this talk, we discuss the underlying physics responsible for the uncertain E-sym(rho) especially at supra-saturation densities, the circumstantial evidence for a super-soft E-sym(rho) from analyzing pi(-)/pi(+) ratio in relativistic heavy-ion collisions and its impacts on astrophysics and cosmology.

Ageing, solidarity and social protection in Latin America and the Caribbean: time for progress towards equality

Includes bibliography

Millennium development goals: progress towards the right to health in Latin america and the Caribbean

Includes bibliography

Increased atmospheric carbon dioxide concentration: effects on eucalypt rust (Puccinia psidii), C:N ratio and essential oils in eucalypt clonal plantlets

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Reduced platelet amyloid precursor protein ratio (APP ratio) predicts conversion from mild cognitive impairment to Alzheimer's disease

Studies have shown that platelet APP ratio (representing the percentage of 120-130 kDa to 110 kDa isoforms of the amyloid precursor protein) is reduced in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). In the present study, we sought to determine if baseline APP ratio predicts the conversion from MCI to AD dementia after 4 years of longitudinal assessment. Fifty-five older adults with varying degrees of cognitive impairment (34 with MCI and 21 with AD) were assessed at baseline and after 4 years. MCI patients were re-classified according to the conversion status upon follow-up: 25 individuals retained the diagnostic status of MCI and were considered as stable cases (MCI-MCI); conversely, in nine cases the diagnosis of dementia due to AD was ascertained. The APP ratio (APPr) was determined by the Western blot method in samples of platelets collected at baseline. We found a significant reduction of APPr in MCI patients who converted to dementia upon follow-up. These individuals had baseline APPr values similar to those of demented AD patients. The overall accuracy of APPr to identify subjects with MCI who will progress to AD was 0.74 +/- A 0.10, p = 0.05. The cut-off of 1.12 yielded a sensitivity of 75 % and a specificity of 75 %. Platelet APPr may be a surrogate marker of the disease process in AD, with potential implications for the assessment of abnormalities in the APP metabolism in patients with and at risk for dementia. However, diagnostic accuracy was relatively low. Therefore, studies in larger samples are needed to determine whether APPr may warrant its use as a biomarker to support the early diagnosis of AD.

Progress in x-ray spectroscopies for the study of advanced materials

This thesis work is focused on the use of selected core-level x-ray spectroscopies to study semiconductor materials of great technological interest and on the development of a new implementation of appearance potential spectroscopy. Core-level spectroscopies can be exploited to study these materials with a local approach since they are sensitive to the electronic structure localized on a chemical species present in the sample examined. This approach, in fact, provides important micro-structural information that is difficult to obtain with techniques sensitive to the average properties of materials. In this thesis work we present a novel approach to the study of semiconductors with core-level spectroscopies based on an original analysis procedure that leads to an insightful understanding of the correlation between the local micro-structure and the spectral features observed. In particular, we studied the micro-structure of Hydrogen induced defects in nitride semiconductors, since the analysed materials show substantial variations of optical and electronic properties as a consequence of H incorporation. Finally, we present a novel implementation of soft x-ray appearance potential spectroscopy, a core-level spectroscopy that uses electrons as a source of excitation and has the great advantage of being an in-house technique. The original set-up illustrated was designed to reach a high signal-to-noise ratio for the acquisition of good quality spectra that can then be analyzed in the framework of the real space full multiple scattering theory. This technique has never been coupled with this analysis approach and therefore our work unite a novel implementation with an original data analysis method, enlarging the field of application of this technique.