995 resultados para antecedent conditions


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Polycrystalline silver is used to catalytically oxidise methanol to formaldehyde. This paper reports the results of extensive investigations involving the use of environmental scanning electron microscopy (ESEM) to monitor structural changes in silver during simulated industrial reaction conditions. The interaction of oxygen, nitrogen, and water, either singly or in combination, with a silver catalyst at temperatures up to 973 K resulted in the appearance of a reconstructed silver surface. More spectacular was the effect an oxygen/methanol mixture had on the silver morphology. At a temperature of ca. 713 K pinholes were created in the vicinity of defects as a consequence of subsurface explosions. These holes gradually increased in size and large platelet features were created. Elevation of the catalyst temperature to 843 K facilitated the wholescale oxygen induced restructuring of the entire silver surface. Methanol reacted with subsurface oxygen to produce subsurface hydroxyl species which ultimately formed water in the subsurface layers of silver. The resultant hydrostatic pressure forced the silver surface to adopt a "hill and valley" conformation in order to minimise the surface free energy. Upon approaching typical industrial operating conditions widespread explosions occurred on the catalyst and it was also apparent that the silver surface was extremely mobile under the applied conditions. The interaction of methanol alone with silver resulted in the initial formation of pinholes primarily in the vicinity of defects, due to reaction with oxygen species incorporated in the catalyst during electrochemical synthesis. However, dramatic reduction in the hole concentration with time occurred as all the available oxygen became consumed. A remarkable correlation between formaldehyde production and hole concentration was found.

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The effect of oxidation and reduction conditions upon the morphology of polycrystalline silver catalysts has been investigated by means of in situ Fourier-transform infrared (FTIR) spectroscopy. Characterization of the sample was achieved by inspection of the νas(COO) band profile of adsorbed formate, recorded after dosing with formic acid at ambient temperature. Evidence was obtained for the existence of a silver surface reconstructed by the presence of subsurface oxygen in addition to the conventional family of Ag(111) and Ag(110) crystal faces. Oxidation at 773 K facilitated the reconstruction of silver planes due to the formation of subsurface oxygen species. Prolonged oxygen treatment at 773 K also caused particle fragmentation as a consequence of excessive oxygen penetration of the silver catalyst at defect sites. It was also deduced that the presence of oxygen in the gas phase stabilized the growth of silver planes which could form stronger bonds with oxygen. In contrast, high-temperature thermal treatment in vacuum induced significant sintering of the silver catalyst. Reduction at 773 K resulted in substantial quantities of dissolved hydrogen (and probably hydroxy species) in the bulk silver structure. Furthermore, enhanced defect formation in the catalyst was also noted, as evidenced by the increased concentration of formate species associated with oxygen-reconstructed silver faces.

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Grading osteoarthritic tissue has, until now, been a laboratory process confined to research activities. This thesis establishes a scientific protocol that extends osteoarthritic tissue ranking to surgical practice. The innovative protocol, which now incorporates the structural degeneration of collagen, enhances the traditional Modified Mankin ranking system, enabling its application to real time decision during surgery. Because it is fast and without time consuming laboratory process, it would potentially enable the cataloguing of tissues in osteoarthritic joints in all compartments of diseased joints during surgery for epistemological study and insight into the manifestation of osteoarthritis across age, gender, occupation, physical activities and race.

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NAPLAN RESULTS HAVE gained socio-political prominence and have been used as indicators of educational outcomes for all students, including Indigenous students. Despite the promise of open and in-depth access to NAPLAN data as a vehicle for intervention, we argue that the use of NAPLAN data as a basis for teachers and schools to reduce variance in learning outcomes is insufficient. NAPLAN tests are designed to show statistical variance at the level of the school and the individual, yet do not factor in the sociocultural and cognitive conditions Indigenous students’ experience when taking the tests. We contend that further understanding of these influences may help teachers understand how to develop their classroom practices to secure better numeracy and literacy outcomes for all students. Empirical research findings demonstrate how teachers can develop their classroom practices from an understanding of the extraneous cognitive load imposed by test taking. We have analysed Indigenous students’ experience of solving mathematical test problems to discover evidence of extraneous cognitive load. We have also explored conditions that are more supportive of learning derived from a classroom intervention which provides an alternative way to both assess and build learning for Indigenous students. We conclude that conditions to support assessment for more equitable learning outcomes require a reduction in cognitive load for Indigenous students while maintaining a high level of expectation and participation in problem solving.

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A significant amount of speech data is required to develop a robust speaker verification system, but it is difficult to find enough development speech to match all expected conditions. In this paper we introduce a new approach to Gaussian probabilistic linear discriminant analysis (GPLDA) to estimate reliable model parameters as a linearly weighted model taking more input from the large volume of available telephone data and smaller proportional input from limited microphone data. In comparison to a traditional pooled training approach, where the GPLDA model is trained over both telephone and microphone speech, this linear-weighted GPLDA approach is shown to provide better EER and DCF performance in microphone and mixed conditions in both the NIST 2008 and NIST 2010 evaluation corpora. Based upon these results, we believe that linear-weighted GPLDA will provide a better approach than pooled GPLDA, allowing for the further improvement of GPLDA speaker verification in conditions with limited development data.

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The reduction of the health literacy concept to a functional relationship with text, does not acknowledge the range of information sources that people draw from in order to make informed decision about their health and treatment. Drawing from two studies that explored how people with two different but complex and life-threatening chronic health conditions, chronic kidney disease and HIV, a socio-cultural understanding of the practise of health literacy is described. Health information is experienced by patients as a chronic health condition landscape, and develops from three information sources; namely epistemic, social and corporeal sources. Participants in both studies used activities that involved orienting, sharing and creating information to map this landscape which was used to inform their decision-making. These findings challenge the traditional conceptions of health literacy and suggest an approach that views the landscape of chronic illness as being socially, physically and contextually constructed. This approach necessitates a recasting of health literacy away from a sole interest in skills and towards understanding how information practices facilitate people becoming health literate.

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This article examines the conditions of penal hope behind suggestions that the penal expansionism of the last three decades may be at a ‘turning point’. The article proceeds by outlining David Green’s (2013b) suggested catalysts of penal reform and considers how applicable they are in the Australian context. Green’s suggested catalysts are: the cycles and saturation thesis; shifts in the dominant conception of the offender; the global financial crisis (GFC) and budgetary constraints; the drop in crime; the emergence of the prisoner re‐entry movement; apparent shifts in public opinion; the influence of evangelical Christian ideas; and the Right on Crime initiative. The article then considers a number of other possible catalysts or forces: the role of trade unions; the role of courts; the emergence of recidivism as a political issue; the influence of ‘evidence based’/‘what works’ discourse; and the emergence of justice reinvestment (JR). The article concludes with some comments about the capacity of criminology and criminologists to contribute to penal reductionism, offering an optimistic assessment for the prospects of a reflexive criminology that engages in and engenders a wider politics around criminal justice issues.

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The ability of the technique of large-amplitude Fourier transformed (FT) ac voltammetry to facilitate the quantitative evaluation of electrode processes involving electron transfer and catalytically coupled chemical reactions has been evaluated. Predictions derived on the basis of detailed simulations imply that the rate of electron transfer is crucial, as confirmed by studies on the ferrocenemethanol (FcMeOH)-mediated electrocatalytic oxidation of ascorbic acid. Thus, at glassy carbon, gold, and boron-doped diamond electrodes, the introduction of the coupled electrocatalytic reaction, while producing significantly enhanced dc currents, does not affect the ac harmonics. This outcome is as expected if the FcMeOH (0/+) process remains fully reversible in the presence of ascorbic acid. In contrast, the ac harmonic components available from FT-ac voltammetry are predicted to be highly sensitive to the homogeneous kinetics when an electrocatalytic reaction is coupled to a quasi-reversible electron-transfer process. The required quasi-reversible scenario is available at an indium tin oxide electrode. Consequently, reversible potential, heterogeneous charge-transfer rate constant, and charge-transfer coefficient values of 0.19 V vs Ag/AgCl, 0.006 cm s (-1) and 0.55, respectively, along with a second-order homogeneous chemical rate constant of 2500 M (-1) s (-1) for the rate-determining step in the catalytic reaction were determined by comparison of simulated responses and experimental voltammograms derived from the dc and first to fourth ac harmonic components generated at an indium tin oxide electrode. The theoretical concepts derived for large-amplitude FT ac voltammetry are believed to be applicable to a wide range of important solution-based mediated electrocatalytic reactions.

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In order to establish the influence of the drying air characteristics on the drying performance and fluidization quality of bovine intestine for pet food, several drying tests have been carried out in a laboratory scale heat pump assisted fluid bed dryer. Bovine intestine samples were heat pump fluidized bed dried at atmospheric pressure and at temperatures below and above the materials freezing points, equipped with a continuous monitoring system. The investigation of the drying characteristics have been conducted in the temperature range −10 to 25 ◦C and the airflow in the range 1.5–2.5 m/s. Some experiments were conducted as single temperature drying experiments and others as two stage drying experiments employing two temperatures. An Arrhenius-type equation was used to interpret the influence of the drying air temperature on the effective diffusivity, calculated with the method of slopes in terms of energy activation, and this was found to be sensitive to the temperature. The effective diffusion coefficient of moisture transfer was determined by the Fickian method using uni-dimensional moisture movement in both moisture, removal by evaporation and combined sublimation and evaporation. Correlations expressing the effective moisture diffusivity and drying temperature are reported. Bovine particles were characterized according to the Geldart classification and the minimum fluidization velocity was calculated using the Ergun Equation and generalized equation for all drying conditions at the beginning and end of the trials. Walli’s model was used to categorize stability of the fluidization at the beginning and end of the dryingv for each trial. The determined Walli’s values were positive at the beginning and end of all trials indicating stable fluidization at the beginning and end for each drying condition.

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Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

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The diagnostics of mechanical components operating in transient conditions is still an open issue, in both research and industrial field. Indeed, the signal processing techniques developed to analyse stationary data are not applicable or are affected by a loss of effectiveness when applied to signal acquired in transient conditions. In this paper, a suitable and original signal processing tool (named EEMED), which can be used for mechanical component diagnostics in whatever operating condition and noise level, is developed exploiting some data-adaptive techniques such as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED) and the analytical approach of the Hilbert transform. The proposed tool is able to supply diagnostic information on the basis of experimental vibrations measured in transient conditions. The tool has been originally developed in order to detect localized faults on bearings installed in high speed train traction equipments and it is more effective to detect a fault in non-stationary conditions than signal processing tools based on spectral kurtosis or envelope analysis, which represent until now the landmark for bearings diagnostics.

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In the field of rolling element bearing diagnostics envelope analysis, and in particular the squared envelope spectrum, have gained in the last years a leading role among the different digital signal processing techniques. The original constraint of constant operating speed has been relaxed thanks to the combination of this technique with the computed order tracking, able to resample signals at constant angular increments. In this way, the field of application of squared envelope spectrum has been extended to cases in which small speed fluctuations occur, maintaining the effectiveness and efficiency that characterize this successful technique. However, the constraint on speed has to be removed completely, making envelope analysis suitable also for speed and load transients, to implement an algorithm valid for all the industrial application. In fact, in many applications, the coincidence of high bearing loads, and therefore high diagnostic capability, with acceleration-deceleration phases represents a further incentive in this direction. This paper is aimed at providing and testing a procedure for the application of envelope analysis to speed transients. The effect of load variation on the proposed technique will be also qualitatively addressed.

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Diagnostics of rolling element bearings involves a combination of different techniques of signal enhancing and analysis. The most common procedure presents a first step of order tracking and synchronous averaging, able to remove the undesired components, synchronous with the shaft harmonics, from the signal, and a final step of envelope analysis to obtain the squared envelope spectrum. This indicator has been studied thoroughly, and statistically based criteria have been obtained, in order to identify damaged bearings. The statistical thresholds are valid only if all the deterministic components in the signal have been removed. Unfortunately, in various industrial applications, characterized by heterogeneous vibration sources, the first step of synchronous averaging is not sufficient to eliminate completely the deterministic components and an additional step of pre-whitening is needed before the envelope analysis. Different techniques have been proposed in the past with this aim: The most widely spread are linear prediction filters and spectral kurtosis. Recently, a new technique for pre-whitening has been proposed, based on cepstral analysis: the so-called cepstrum pre-whitening. Owing to its low computational requirements and its simplicity, it seems a good candidate to perform the intermediate pre-whitening step in an automatic damage recognition algorithm. In this paper, the effectiveness of the new technique will be tested on the data measured on a full-scale industrial bearing test-rig, able to reproduce the harsh conditions of operation. A benchmark comparison with the traditional pre-whitening techniques will be made, as a final step for the verification of the potentiality of the cepstrum pre-whitening.

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Diagnostics of rolling element bearings have been traditionally developed for constant operating conditions, and sophisticated techniques, like Spectral Kurtosis or Envelope Analysis, have proven their effectiveness by means of experimental tests, mainly conducted in small-scale laboratory test-rigs. Algorithms have been developed for the digital signal processing of data collected at constant speed and bearing load, with a few exceptions, allowing only small fluctuations of these quantities. Owing to the spreading of condition based maintenance in many industrial fields, in the last years a need for more flexible algorithms emerged, asking for compatibility with highly variable operating conditions, such as acceleration/deceleration transients. This paper analyzes the problems related with significant speed and load variability, discussing in detail the effect that they have on bearing damage symptoms, and propose solutions to adapt existing algorithms to cope with this new challenge. In particular, the paper will i) discuss the implication of variable speed on the applicability of diagnostic techniques, ii) address quantitatively the effects of load on the characteristic frequencies of damaged bearings and iii) finally present a new approach for bearing diagnostics in variable conditions, based on envelope analysis. The research is based on experimental data obtained by using artificially damaged bearings installed on a full scale test-rig, equipped with actual train traction system and reproducing the operation on a real track, including all the environmental noise, owing to track irregularity and electrical disturbances of such a harsh application.

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The transmission path from the excitation to the measured vibration on the surface of a mechanical system introduces a distortion both in amplitude and in phase. Moreover, in variable speed conditions, the amplification/attenuation and the phase shift, due to the transfer function of the mechanical system, varies in time. This phenomenon reduces the effectiveness of the traditionally tachometer based order tracking, compromising the results of a discrete-random separation performed by a synchronous averaging. In this paper, for the first time, the extent of the distortion is identified both in the time domain and in the order spectrum of the signal, highlighting the consequences for the diagnostics of rotating machinery. A particular focus is given to gears, providing some indications on how to take advantage of the quantification of the disturbance to better tune the techniques developed for the compensation of the distortion. The full theoretical analysis is presented and the results are applied to an experimental case.