27 resultados para Polímers -- Proves


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Fac-ruthenium(II) tris-(5-carboxy-2,2'-bipyridine) has been synthesised as a single geometric isomer for the first time, and proves to be a good "building-block" to introduce new functionality with retention of the isomeric integrity.

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We study the structural effects produced by the quantization of vibrational degrees of freedom in periodic crystals at zero temperature. To this end we introduce a methodology based on mapping a suitable subspace of the vibrational manifold and solving the Schrödinger equation in it. A number of increasingly accurate approximations ranging from the quasiharmonic approximation (QHA) to the vibrational self-consistent field (VSCF) method and the exact solution are described. A thorough analysis of the approximations is presented for model monatomic and hydrogen-bonded chains, and results are presented for a linear H-F chain where the potential-energy surface is obtained via first-principles electronic structure calculations. We focus on quantum nuclear effects on the lattice constant and show that the VSCF is an excellent approximation, meaning that correlation between modes is not extremely important. The QHA is excellent for covalently bonded mildly anharmonic systems, but it fails for hydrogen-bonded ones. In the latter, the zero-point energy exhibits a nonanalytic behavior at the lattice constant where the H atoms center, which leads to a spurious secondary minimum in the quantum-corrected energy curve. An inexpensive anharmonic approximation of noninteracting modes appears to produce rather good results for hydrogen-bonded chains for small system sizes. However, it converges to the incorrect QHA results for increasing size. Isotope effects are studied for the first-principles H-F chain. We show how the lattice constant and the H-F distance increase with decreasing mass and how the QHA proves to be insufficient to reproduce this behavior.

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Quantification of nanoparticles in biological systems (i.e., cells, tissues and organs) is becoming a vital part of nanotoxicological and nanomedical fields. Dose is a key parameter when assessing behavior and any potential risk of nanomaterials. Various techniques for nanoparticle quantification in cells and tissues already exist but will need further development in order to make measurements reliable, reproducible and intercomparable between different techniques. Microscopy allows detection and location of nanoparticles in cells and has been used extensively in recent years to characterize nanoparticles and their pathways in living systems. Besides microscopical techniques (light microscopy and electron microscopy mainly), analytical techniques such as mass spectrometry, an established technique in trace element analysis, have been used in nanoparticle research. Other techniques require 'labeled particles, fluorescently, radioactively or magnetically. However, these techniques lack spatial resolution and subcellular localization is not possible. To date, only electron microscopy offers the resolving power to determine accumulation of nanoparticles in cells due to its ability to image particles individually. So-called super-resolution light microscopy techniques are emerging to provide sufficient resolution on the light microscopy level to image or 'see particles as individual particles. Nevertheless, all microscopy techniques require statistically sound sampling strategies in order to provide quantitative results. Stereology is a well-known sampling technique in various areas and, in combination with electron microscopy, proves highly successful with regard to quantification of nanoparticle uptake by cells. © 2010 Future Medicine Ltd.

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A two-dimensional mathematical model for evaluating the simultaneous heat and moisture migration in porous building materials was proposed. Vapor content and temperature were chosen as the principal driving potentials. The numerical solution was based on the control volume finite difference technique with fully implicit scheme in time. Two validation experiments were developed in this study. The evolution of transient moisture distributions in both one-dimensional and two-dimensional cases was measured. A comparison between experimental results and those obtained by the numerical model proves that they are fully consistent with each other. The model can be easily integrated into a whole building heat, air and moisture transfer model. Another main advantage of the present numerical method lies in the fact that the required moisture transport properties are comparatively simple and easy to determine.

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In this paper the use of eigenvalue stability analysis of very large dimension aeroelastic numerical models arising from the exploitation of computational fluid dynamics is reviewed. A formulation based on a block reduction of the system Jacobian proves powerful to allow various numerical algorithms to be exploited, including frequency domain solvers, reconstruction of a term describing the fluid–structure interaction from the sparse data which incurs the main computational cost, and sampling to place the expensive samples where they are most needed. The stability formulation also allows non-deterministic analysis to be carried out very efficiently through the use of an approximate Newton solver. Finally, the system eigenvectors are exploited to produce nonlinear and parameterised reduced order models for computing limit cycle responses. The performance of the methods is illustrated with results from a number of academic and large dimension aircraft test cases.

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This study provides a general diversity analysis for joint complex diversity coding (CDC) and channel coding-based space-time-frequency codeing is provided. The mapping designs from channel coding to CDC are crucial for efficient exploitation of the diversity potential. This study provides and proves a sufficient condition of full diversity construction with joint three-dimensional CDC and channel coding, bit-interleaved coded complex diversity coding and symbol-interleaved coded complex diversity coding. Both non-iterative and iterative detections of joint channel code and CDC transmission are investigated. The proposed minimum mean-square error-based iterative soft decoding achieves the performance of the soft sphere decoding with reduced complexity.

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Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with different groups of growth-promoting hormones (dexamethasone, prednisolone, oestradiol) based on recorded metabolite profiles. Two methods of NMR analysis were investigated—a Carr–Purcell–Meiboom–Gill (CPMG)-pulse sequence technique and a conventional 1H NMR method using pre-extracted plasma. Using the CPMG method, 17 distinct metabolites could be identified from the spectra. 1H NMR analysis of extracted plasma facilitated identification of 23 metabolites—six more than the alternative method and all within the aromatic region. Multivariate statistical analysis of acquired data from both forms of NMR analysis separated the plasma metabolite profiles into distinct sample cluster sets representative of the different animal study groups. Samples from both sets of corticosteroid-treated animals—dexamethasone and prednisolone—were found to be clustered relatively closely and had similar alterations to identified metabolite panels. Distinctive metabolite profiles, different from those observed within plasma from corticosteroid-treated animal plasma, were observed in oestradiol-treated animals and samples from these animals formed a cluster spatially isolated from control animal plasma samples. These findings suggest the potential use of NMR methodologies of plasma metabolite analysis as a high-throughput screening technique to aid detection of growth promoter use.

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This paper presents a novel detection method for broken rotor bar fault (BRB) in induction motors based on Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT) and Simulated Annealing Algorithm (SAA). The performance of ESPRIT is tested with simulated stator current signal of an induction motor with BRB. It shows that even with a short-time measurement data, the technique is capable of correctly identifying the frequencies of the BRB characteristic components but with a low accuracy on the amplitudes and initial phases of those components. SAA is then used to determine their amplitudes and initial phases and shows satisfactory results. Finally, experiments on a 3kW, 380V, 50Hz induction motor are conducted to demonstrate the effectiveness of the ESPRIT-SAA-based method in detecting BRB with short-time measurement data. It proves that the proposed method is a promising choice for BRB detection in induction motors operating with small slip and fluctuant load.

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Ar photoionization is studied using the R-matrix formalism with emphasis on the simultaneous excitation of the residual A^r+ ion. Cross sections have been obtained for excitation of the 3p^4(3d,4s,4p) states. A comparison with experiments having a resolution of 70 meV shows reasonable agreement for the position and shape of resonance structures. The relative magnitude of the resonances proves to be more elusive. The partial cross section for excitation of the 3p^4(3Pe)4p(2P_3/2^o) and (2D_3/2^o) levels is treated in more detail. A comparison of LS-coupling calculations with high-resolution experimental results shows good agreement for both the excitation cross sections and the polarization of the fluorescence. We also predict the orientation for both levels. We demonstrate that the polarization of the fluorescence originating from the (2D_3/2^o) level can be employed to study spin-orbit effects in Ar photoionization.

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Previous research based on theoretical simulations has shown the potential of the wavelet transform to detect damage in a beam by analysing the time-deflection response due to a constant moving load. However, its application to identify damage from the response of a bridge to a vehicle raises a number of questions. Firstly, it may be difficult to record the difference in the deflection signal between a healthy and a slightly damaged structure to the required level of accuracy and high scanning frequencies in the field. Secondly, the bridge is going to have a road profile and it will be loaded by a sprung vehicle and time-varying forces rather than a constant load. Therefore, an algorithm based on a plot of wavelet coefficients versus time to detect damage (a singularity in the plot) appears to be very sensitive to noise. This paper addresses these questions by: (a) using the acceleration signal, instead of the deflection signal, (b) employing a vehicle-bridge finite element interaction model, and (c) developing a novel wavelet-based approach using wavelet energy content at each bridge section which proves to be more sensitive to damage than a wavelet coefficient line plot at a given scale as employed by others.

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The magnetoelectric coupling in multiferroic materials is promising for a wide range of applications, yet manipulating magnetic ordering by electric field proves elusive to obtain and difficult to control. In this paper, we explore the prospect of controlling magnetic ordering in misfit strained bismuth ferrite (BiFeO3, BFO) films, combining theoretical analysis, numerical simulations, and experimental characterizations. Electric field induced transformation from a tetragonal phase to a distorted rhombohedral one in strain engineered BFO films has been identified by thermodynamic analysis, and realized by scanning probe microscopy (SPM) experiment. By breaking the rotational symmetry of a tip-induced electric field as suggested by phase field simulation, the morphology of distorted rhombohedral variants has been delicately controlled and regulated. Such capabilities enable nanoscale control of magnetoelectric coupling in strain engineered BFO films that is difficult to achieve otherwise, as demonstrated by phase field simulations.

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In this article I consider the debate over whether line 1520b ought to be read as the emended “hond sweng” or the scribal “hord swenge.” It is a small point philologically but it raises interesting cultural and literary questions about the attitude of the Beowulf poet to arms and armour, to aggressive and defensive war gear, and to swords in particular. It has widely been assumed that swords are important in Beowulf and yet, the question of what their significance might be has received very little attention. Throughout the poem the hero is plagued by breaking, melting, and failing swords. He borrows, finds, and is given swords but unlike other English and Germanic heroes he is never identified with a single, great sword. I suggest that this is because, ultimately, Beowulf is conceived as a hondbana, a designation which has implications for what kind of a hero he proves to be.

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This paper presents a scalable, statistical ‘black-box’ model for predicting the performance of parallel programs on multi-core non-uniform memory access (NUMA) systems. We derive a model with low overhead, by reducing data collection and model training time. The model can accurately predict the behaviour of parallel applications in response to changes in their concurrency, thread layout on NUMA nodes, and core voltage and frequency. We present a framework that applies the model to achieve significant energy and energy-delay-square (ED2) savings (9% and 25%, respectively) along with performance improvement (10% mean) on an actual 16-core NUMA system running realistic application workloads. Our prediction model proves substantially more accurate than previous efforts.

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In this study, low loading platinum nanoparticles (Pt NPs) have been highly dispersed on reduced graphene oxide-supported WC nanocrystallites (Pt-WC/RGO) via program-controlled reduction-carburization technique and microwave-assisted method. The scanning electron microscopy and transmission electron microscopy results show that WC nanocrystallites are homogeneously decorated on RGO, and Pt NPs with a size of ca. 3 nm are dispersed on both RGO and WC. The prepared Pt-WC/RGO is used as an electrocatalyst for methanol oxidation reaction (MOR). Compared with the Pt/RGO, commercial carbon-supported Pt (Pt/C) and PtRu alloy (PtRu/C) electrocatalysts, the Pt-WC/RGO composites demonstrate higher electrochemical active surface area and excellent electrocatalytic activity toward the methanol oxidation, such as better tolerance toward CO, higher peak current density, lower onset potential and long-term stability, which could be attributed to the characterized RGO support, highly dispersed Pt NPs and WC nanocrystallites and the valid synergistic effect resulted from the increased interface between WC and Pt. The present work proves that Pt-WC/RGO composites could be a promising alternative catalyst for direct methanol fuel cells where WC plays the important role as a functional additive in preparing Pt-based catalysts because of its CO tolerance and lower price. 

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Purpose: The purpose of this paper is to present an artificial neural network (ANN) model that predicts earthmoving trucks condition level using simple predictors; the model’s performance is compared to the respective predictive accuracy of the statistical method of discriminant analysis (DA).

Design/methodology/approach: An ANN-based predictive model is developed. The condition level predictors selected are the capacity, age, kilometers travelled and maintenance level. The relevant data set was provided by two Greek construction companies and includes the characteristics of 126 earthmoving trucks.

Findings: Data processing identifies a particularly strong connection of kilometers travelled and maintenance level with the earthmoving trucks condition level. Moreover, the validation process reveals that the predictive efficiency of the proposed ANN model is very high. Similar findings emerge from the application of DA to the same data set using the same predictors.

Originality/value: Earthmoving trucks’ sound condition level prediction reduces downtime and its adverse impact on earthmoving duration and cost, while also enhancing the maintenance and replacement policies effectiveness. This research proves that a sound condition level prediction for earthmoving trucks is achievable through the utilization of easy to collect data and provides a comparative evaluation of the results of two widely applied predictive methods.