103 resultados para Yielding


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Silicon carbide (SiC) is an important orthopaedic material due to its inert nature and superior mechanical and tribological properties. Some of the potential applications of silicon carbide include coating for stents to enhance hemocompatibility, coating for prosthetic-bearing surfaces and uncemented joint prosthetics. This study is the first to explore nanomechanical response of single crystal 4H-SiC through quasistatic nanoindentation. Displacement controlled quasistatic nanoindentation experiments were performed on single crystal 4H-SiC specimen using a blunt Berkovich indenter (300 nm tip radius) at extremely fine indentation depths of 5 nm, 10 nm, 12 nm, 20 nm, 25 nm and 50 nm. Load-displacement curve obtained from the indentation experiments showed yielding or incipient plasticity in 4H-SiC typically at a shear stress of about 21 GPa (~an indentation depth of 33.8 nm) through a pop-in event. An interesting observation was that the residual depth of indent showed three distinct patterns: (i) Positive depth hysteresis above 33 nm, (ii) no depth hysteresis at 12 nm, and (iii) negative depth hysteresis below 12 nm. This contrasting depth hysteresis phenomenon is hypothesized to originate due to the existence of compressive residual stresses (upto 143 MPa) induced in the specimen by the polishing process prior to the nanoindentation

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Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

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SOMMARIO – Si presenta un macro modello di tipo reticolare in grado di riprodurre il comportamento in presenza di taglio e momento di nodi esterni trave-colonna di telai in calcestruzzo fibrorinforzato con fibre di acciaio
uncinato ed ordinario. Il caricamento del sistema è di tipo monotono come nel caso dell’analisi di pushover. Il modello considera la presenza di armature orizzontali e verticali della regione nodale e tiene in conto delle modalità
di rottura legate allo snervamento delle barre e allo schiacciamento delle regioni compresse in regime di sforzi pluriassiali. Il modello include le deformazioni flessionali della trave e della colonna in presenza di sforzo normale costante e restituisce la risposta del sistema colonna-nodo-trave (sub-assembralggio) tramite le curve carico-freccia all’estremità della semitrave. Per i singoli costituenti (trave, colonna e nodo) si è considerata la prima fessurazione, lo snervamento e lo schiacciamento delle regioni compresse e si sono fornite precise indicazioni sulla sequenza degli eventi che come è noto sono di fondamentale importanza per lo sviluppo di un progetto plastico che rispetti la gerarchia delle resistenze. Con l’uso del modello il controllo della gerarchia delle resistenze avviene a livello sezionale (lo snervamento delle barre deve avvenire prima dello schiacciamento delle regioni compresse) o di macro elemento (nella regione nodale lo snervamento delle staffe precede la crisi dei puntoni) e dell’intero elemento
sub-assemblaggio trave debole, colonna forte e nodo sovraresistente.
La risposta ottenuta con i modello proposto è in buon accordo con le risposte sperimentali disponibili in letteratura (almeno in termini di resistenza del sub-assemblaggio). Il modello è stato ulteriormente validato con analisi
numeriche agli elementi finiti condotte con il codice ATENA-2D. Le analisi numeriche sono state condotte utilizzando per il calcestruzzo fibroso adeguate leggi costitutive proposte dagli autori ed in grado di cogliere gli effetti
di softening e di resistenza residua a trazione legati alla presenza di fibre. Ulteriori sviluppi del modello saranno indirizzati a includere gli effetti di sfilamento delle barre d’armatura della trave e del conseguente degrado delle
tensioni d’aderenza per effetto di carichi monotonici e ciclici.

SUMMARY – A softened strut-and-tie macro model able to reproduce the flexural behavior of external beam-tocolumn joints with the presence of horizontal and vertical steel bars, including softening of compressed struts and yielding of main and secondary steel bars, is presented, to be used for the pushover analysis. The model proposed is able to calculate also the flexural response of fibrous reinforced concrete (FRC) beam-to-column sub-assemblages in term of a multilinear load-deflection curves. The model is able to take into account of the tensile behavior of main bars embedded in the surrounding concrete and of the softening of the compressed strut, the arrangement and percentage of the steel bars, the percentage and the geometry of steel fibers. First cracking, yielding of main steel and crushing of concrete were identified to determine the corresponding loads and displacement and to plot the simplified monotonic load-deflection curves of the sub-assemblages subjected in the column to constant vertical
load and at the tip of the beam to monotonically increasing lateral force. Through these load-delfection curves the component (beam, joint and column) that first collapse can be recognized and the capacity design can be verified.
The experimental results available in the literature are compared with the results obtained through the proposed model. Further, a validation of the proposed model is numerically made by using a non linear finite element program (ATENA-2D) able to analyze the flexural behavior of sub-assemblages.

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Buffering of Lewis acidic chlorometallate ionic liquids is a useful tool to modify their properties for electrochemical and catalytic applications. Lewis acidic chlorogallate(iii) ionic liquids containing the 1-octyl-3-methylimidazolium cation, buffered with sodium chloride, were studied using (71)Ga NMR spectroscopy and cyclic voltammetry. All the studied Lewis acidic compositions (0.50 < χGaCl3 ≤ 0.75) could be buffered to mild or moderate acidity, but not to neutrality. Electrodeposition of gallium from such buffered systems was possible, yielding deposits of improved morphology over the unbuffered ionic liquids, due to the constant melt composition maintained by the buffer. These findings were in a stark contrast with older studies on chloroaluminate(iii) ionic liquids buffered with sodium chloride.

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An approach for seismic damage identification of a single-storey steel concentrically braced frame (CBF) structure is presented through filtering and double integration of a recorded acceleration signal. A band-pass filter removes noise from the acceleration signal followed by baseline correction being used to reduce the drift in velocity and displacement during numerical integration. The pre-processing achieves reliable numerical integration that predicts the displacement response accurately when compared to the measured lateral in-plane displacement of the CBF structure. The lateral displacement of the CBF structure is used to infer buckling and yielding of bracing members through seismic tests. The level of interstorey drift of the CBF during a seismic excitation allows the yield and buckling of the bracing members to be identified and indirectly detects damage based on exceedance of calculated displacement limits. The calculated buckling and yielding displacement threshold limits used to identify damage are demonstrated to accurately identify initial buckling and yielding in the bracing members.

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Accessing chirally pure cis-diols from arenes using micro-organisms over-expressing toluene dioxygenase (TDO) is now well established, but the conversions remain low for the more toxic and volatile substrates. For such arenes, improved production has already been achieved in the presence of hydrophobic non-toxic ionic liquids (ILs) acting in the form of a reservoir for the arene substrate. Yet, the costs associated with such ILs require extensive process development to render them viable. Herein, we show that optimization of the hydrophobic IL's cationic moiety and of the IL's concentration are key to enhanced conversion yielding between a 2-5 fold yield increase in the conversion of four haloarenes (Ph-X; X = F, Cl, Br, I). Additionally, we report that hydrophilic imidazolium-based ILs offer opportunities to achieve similarly high yielding biotransformations, with further improved reaction rates (<6 h), and this at very low ILs' concentrations (0.0015 VIL/Vaq). We also demonstrate that the increased biotransformations are due to these ILs being inhibitors of cellular respiration processes and thus favoring the shunting of NADH and O2 towards the overexpressed biocatalytic process. © 2014 the Partner Organisations.

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This paper evaluates the potential of gabions as roadside safety barriers. Gabions have the capacity to blend into natural landscape, suggesting that they could be used as a safety barrier for low-volume road in scenic environments. In fact, gabions have already been used for this purpose in Nepal, but the impact response was not evaluated. This paper reports on numerical and experimental investigations performed on a new gabion barrier prototype. To assess the potential use as a roadside barrier, the optimal gabion unit size and mass were investigated using multibody analysis and four sets of 1:4 scaled crash tests were carried out to study the local vehicle-barrier interaction. The barrier prototype was then finalised and subjected to a TB31 crash test according to the European EN1317 standard for N1 safety barriers. The test resulted in a failure due to the rollover of the vehicle and tearing of the gabion mesh yielding a large working width. It was found that although the system potentially has the necessary mass to contain a vehicle, the barrier front face does not have the necessary stiffness and strength to contain the gabion stone filling and hence redirect the vehicle. In the EN1317 test, the gabion barrier acted as a ramp for the impacting vehicle, causing rollover. 

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Gas-to-liquid processes are generally used to convert natural gas or other gaseous hydrocarbons into liquid fuels via an intermediate syngas stream. This includes the production of liquid fuels from biomass-derived sources such as biogas. For example, the dry reforming of methane is done by reacting CH4 and CO2, the two main components of natural biogas, into more valuable products, i.e., CO and H2. Nickel containing perovskite type catalysts can promote this reaction, yielding good conversions and selectivities; however, they are prone to coke laydown under certain operating conditions. We investigated the addition of high oxygen mobility dopants such as CeO2, ZrO2, or YSZ to reduce carbon laydown, particularly using reaction conditions that normally result in rapid coking. While doping with YSZ, YDC, GDC, and SDC did not result in any improvement, we show that a Ni perovskite catalyst (Na0.5La0.5Ni0.3Al0.7O2.5) doped with 80.9 ZrO2 15.2 CeO2 gave the lowest amount of carbon formation at 800 °C and activity was maintained over the operating time.

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Major ampullate silk fibers of orb web-weaving spiders have impressive mechanical properties due to the fact that the underlying proteins partially fold into helical/amorphous structures, yielding relatively elastic matrices that are toughened by anisotropic nanoparticulate inclusions (formed from stacks of beta-sheets of the same proteins). In vivo the transition from soluble protein to solid fibers involves a combination of chemical and mechanical stimuli (such as ion exchange, extraction of water and shear forces). Here we elucidate the effects of such stimuli on the in vitro aggregation of engineered and recombinantly produced major ampullate silk-like proteins (focusing on structure-function relationships with respect to their primary structures), and discuss their relevance to the storage and assembly of spider silk proteins in vivo. (C) 2009 Elsevier Inc. All rights reserved.

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Many modeling problems require to estimate a scalar output from one or more time series. Such problems are usually tackled by extracting a fixed number of features from the time series (like their statistical moments), with a consequent loss in information that leads to suboptimal predictive models. Moreover, feature extraction techniques usually make assumptions that are not met by real world settings (e.g. uniformly sampled time series of constant length), and fail to deliver a thorough methodology to deal with noisy data. In this paper a methodology based on functional learning is proposed to overcome the aforementioned problems; the proposed Supervised Aggregative Feature Extraction (SAFE) approach allows to derive continuous, smooth estimates of time series data (yielding aggregate local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The SAFE paradigm enjoys several properties like closed form solution, incorporation of first and second order derivative information into the regressor matrix, interpretability of the generated functional predictor and the possibility to exploit Reproducing Kernel Hilbert Spaces setting to yield nonlinear predictive models. Simulation studies are provided to highlight the strengths of the new methodology w.r.t. standard unsupervised feature selection approaches. © 2012 IEEE.

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Despite the importance of laughter in social interactions it remains little studied in affective computing. Respiratory, auditory, and facial laughter signals have been investigated but laughter-related body movements have received almost no attention. The aim of this study is twofold: first an investigation into observers' perception of laughter states (hilarious, social, awkward, fake, and non-laughter) based on body movements alone, through their categorization of avatars animated with natural and acted motion capture data. Significant differences in torso and limb movements were found between animations perceived as containing laughter and those perceived as nonlaughter. Hilarious laughter also differed from social laughter in the amount of bending of the spine, the amount of shoulder rotation and the amount of hand movement. The body movement features indicative of laughter differed between sitting and standing avatar postures. Based on the positive findings in this perceptual study, the second aim is to investigate the possibility of automatically predicting the distributions of observer's ratings for the laughter states. The findings show that the automated laughter recognition rates approach human rating levels, with the Random Forest method yielding the best performance.

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A series of supramolecular aggregates were prepared using a poly(propylene oxide) poly(ethylene oxide) poly(propylene oxide) (PPO-PEO-PPO) block copolymer and beta- or alpha-cyclodextrins (CD). The combination of beta-CD and the copolymer yields inclusion complexes (IC) with polypseudorotaxane structures. These are formed by complexation of the PPO blocks with beta-CD molecules producing a powder precipitate with a certain crystallinity degree that can be evaluated by X-ray diffraction (XRD). In contrast, when combining alpha-CD with the block copolymer, the observed effect is an increase in the viscosity of the mixtures, yielding fluid gels. Two cooperative effects come into play: the complexation of PEO blocks with alpha-CD and the hydrophobic interactions between PPO blocks in aqueous media. These two combined interactions lead to the formation of a macromoleculaf network. The resulting fluid gels were characterized using different techniques such as differential scanning calorimetry (DSC), viscometry, and XRD measurements.

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Chemically ordered B2 FeRh exhibits a remarkable antiferromagnetic-ferromagnetic phase transition that is first order. It thus shows phase coexistence, usually by proceeding though nucleation at random defect sites followed by propagation of phase boundary domain walls. The transition occurs at a temperature that can be varied by doping other metals onto the Rh site. We have taken advantage of this to yield control over the transition process by preparing an epilayer with oppositely directed doping gradients of Pd and Ir throughout its height, yielding a gradual transition that occurs between 350 K and 500 K. As the sample is heated, a horizontal antiferromagnetic-ferromagnetic phase boundary domain wall moves gradually up through the layer, its position controlled by the temperature. This mobile magnetic domain wall affects the magnetisation and resistivity of the layer in a way that can be controlled, and hence exploited, for novel device applications.

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Retrospective clinical datasets are often characterized by a relatively small sample size and many missing data. In this case, a common way for handling the missingness consists in discarding from the analysis patients with missing covariates, further reducing the sample size. Alternatively, if the mechanism that generated the missing allows, incomplete data can be imputed on the basis of the observed data, avoiding the reduction of the sample size and allowing methods to deal with complete data later on. Moreover, methodologies for data imputation might depend on the particular purpose and might achieve better results by considering specific characteristics of the domain. The problem of missing data treatment is studied in the context of survival tree analysis for the estimation of a prognostic patient stratification. Survival tree methods usually address this problem by using surrogate splits, that is, splitting rules that use other variables yielding similar results to the original ones. Instead, our methodology consists in modeling the dependencies among the clinical variables with a Bayesian network, which is then used to perform data imputation, thus allowing the survival tree to be applied on the completed dataset. The Bayesian network is directly learned from the incomplete data using a structural expectation–maximization (EM) procedure in which the maximization step is performed with an exact anytime method, so that the only source of approximation is due to the EM formulation itself. On both simulated and real data, our proposed methodology usually outperformed several existing methods for data imputation and the imputation so obtained improved the stratification estimated by the survival tree (especially with respect to using surrogate splits).

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The intensity of surface enhanced Raman scattering from benzoic acid derivatives on mildly roughened, thermally evaporated Ag films shows a remarkably strong dependence on metal grain size. Large grained (slowly deposited) films give a superior response, by up to a factor of 10, to small grained (quickly deposited) films, with films of intermediate grain size yielding intermediate results. The optical field amplification underlying the enhancement mechanism is due to the excitation of surface plasmon polaritons (SPPs). Since surface roughness characteristics, as determined by STM, remain relatively constant as a function of deposition rate, it is argued that the contrast in Raman scattering is due to differences in elastic grain boundary scattering of SPPs (leading to different degrees of internal SPP damping), rather than differences in the interaction of SPPs with surface inhomogeneities.