143 resultados para Discrete components


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Electrochemical processes in mesoporous TiO2-Nafion thin films deposited on indium tin oxide (ITO) electrodes are inherently complex and affected by capacitance, Ohmic iR-drop, RC-time constant phenomena, and by potential and pH-dependent conductivity. In this study, large-amplitude sinusoidally modulated voltammetry (LASMV) is employed to provide access to almost purely Faradaic-based current data from second harmonic components, as well as capacitance and potential domain information from the fundamental harmonic for mesoporous TiO2-Nafion film electrodes. The LASMV response has been investigated with and without an immobilized one-electron redox system, ferrocenylmethyltrimethylammonium+. Results clearly demonstrate that the electron transfer associated with the immobilized ferrocene derivative follows two independent pathways i) electron hopping within the Nafion network and ii) conduction through the TiO2 backbone. The pH effect on the voltammetric response for the TiO2 reduction pathway (ii) can be clearly identified in the 2nd harmonic LASMV response with the diffusion controlled ferrocene response (i) acting as a pH independent reference. Application of second harmonic data derived from LASMV measurement, because of the minimal contribution from capacitance currents, may lead to reference-free pH sensing with systems like that found for ferrocene derivatives.

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Objective To explore the characteristics of regional distribution of cancer deaths in Shandong Province with the principle components analysis. Methods The principle components analysis with co-variance matrix for age-adjusted mortality rates and percentages of 20 types of cancer in 22 counties (cities) were carried out using SAS Software. Results Over 90% of the total information could be reflected by the top 3 principle components and the first principle component alone represented more than half of the overall regional variances. The first component mainly reflected the area differences of esophageal cancer. The second component mainly reflected the area differences of lung cancer, stomach cancer and liver cancer. The value of the first principal component scores showed a clear trend that the west areas possessed higher values and the east the lower values. Based on the top two components,the 22 counties (cities) could be divided into several geographical clusters. Conclusion The overall difference of regional distribution of cancers in Shandong is dominated by several major cancers including esophageal cancer, lung cancer, stomach cancer and liver cancer. Among them,esophageal cancer makes the largest contribution. If the range of counties (cities) analyzed could be further widened, the characteristics of regional distribution of cancer mortality would be better examined. Abstract in Chinese 目的 利用主成分分析探讨山东省恶性肿瘤死亡的地区分布特征. 方法 利用SAS软件对山东省22个县市区2004~2006午的20种恶性肿瘤标化死亡率和构成比分别进行协方差矩阵主成分分析. 结果 前3个主成分就反映了总体差异90%以上的信息,其中仅第1主成分就提供了总体差异一半以上的信息.第1主成分主要反映了食管癌的地区差异,第2主成分主要反映肺癌的地区差异,兼顾胃癌和肝癌.各地区第1主成分得分呈现西高东低的趋势,根据第1和第2主成分可以将调查地区分为若干类别,表现为明显的地理聚集性. 结论 山东省各地区恶性肿瘤死亡的总体差异主要取决于少数高发肿瘤,包括食管癌、肺癌、胃癌、肝癌等,其中以食管癌地位最为突出.如能进一步扩大分析范围,可更好地查明恶性肿瘤死亡的地区特征.

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Conditions of bridges deteriorate with age, due to different critical factors including, changes in loading, fatigue, environmental effects and natural events. In order to rate a network of bridges, based on their structural condition, the condition of the components of a bridge and their effects on behaviour of the bridge should be reliably estimated. In this paper, a new method for quantifying the criticality and vulnerability of the components of the railway bridges in a network will be introduced. The type of structural analyses for identifying the criticality of the components for carrying train loads will be determined. In addition to that, the analytical methods for identifying the vulnerability of the components to natural events whose probability of occurrence is important, such as, flood, wind, earthquake and collision will be determined. In order to maintain the practicality of this method to be applied to a network of thousands of railway bridges, the simplicity of structural analysis has been taken into account. Demand by capacity ratios of the components at both safety and serviceability condition states as well as weighting factors used in current bridge management systems (BMS) are taken into consideration. It will be explained what types of information related to the structural condition of a bridge is required to be obtained, recorded and analysed. The authors of this paper will use this method in a new rating system introduced previously. Enhancing accuracy and reliability of evaluating and predicting the vulnerability of railway bridges to environmental effects and natural events will be the significant achievement of this research.

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Objective This study compared the primary stability of two commercially available acetabular components from the same manufacturer, which differ only in geometry; a hemispherical and a peripherally enhanced design (peripheral self-locking (PSL)). The objective was to determine whether altered geometry resulted in better primary stability. Methods Acetabular components were seated with 0.8 mm to 2 mm interference fits in reamed polyethylene bone substrate of two different densities (0.22 g/cm3 and 0.45 g/cm3). The primary stability of each component design was investigated by measuring the peak failure load during uniaxial pull-out and tangential lever-out tests. Results There was no statistically significant difference in seating force (p = 0.104) or primary stability (pull-out p = 0.171, lever-out p = 0.087) of the two components in the low-density substrate. Similarly, in the high-density substrate, there was no statistically significant difference in the peak pull-out force (p = 0.154) or lever-out moment (p = 0.574) between the designs. However, the PSL component required a significantly higher seating force thanthe hemispherical cup in the high-density bone analogue (p = 0.006). Conclusions Higher seating forces associated with the PSL design may result in inadequate seating and increased risk of component malpositioning or acetabular fracture in the intra-operative setting in high-density bone stock. Our results, if translated clinically, suggest that a purely hemispherical geometry may have an advantage over a peripherally enhanced geometry in high density bone stock.

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Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

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Diagnostics of rotating machinery has developed significantly in the last decades, and industrial applications are spreading in different sectors. Most applications are characterized by varying velocities of the shaft and in many cases transients are the most critical to monitor. In these variable speed conditions, fault symptoms are clearer in the angular/order domains than in the common time/frequency ones. In the past, this issue was often solved by synchronously sampling data by means of phase locked circuits governing the acquisition; however, thanks to the spread of cheap and powerful microprocessors, this procedure is nowadays rarer; sampling is usually performed at constant time intervals, and the conversion to the order domain is made by means of digital signal processing techniques. In the last decades different algorithms have been proposed for the extraction of an order spectrum from a signal sampled asynchronously with respect to the shaft rotational velocity; many of them (the so called computed order tracking family) use interpolation techniques to resample the signal at constant angular increments, followed by a common discrete Fourier transform to shift from the angular domain to the order domain. A less exploited family of techniques shifts directly from the time domain to the order spectrum, by means of modified Fourier transforms. This paper proposes a new transform, named velocity synchronous discrete Fourier transform, which takes advantage of the instantaneous velocity to improve the quality of its result, reaching performances that can challenge the computed order tracking.

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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.

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Bone defect treatments can be augmented by mesenchymal stem cell (MSC) based therapies. MSC interaction with the extracellular matrix (ECM) of the surrounding tissue regulates their functional behavior. Understanding of these specific regulatory mechanisms is essential for the therapeutic stimulation of MSC in vivo. However, these interactions are presently only partially understood. This study examined in parallel, for the first time, the effects on the functional behavior of MSCs of 13 ECM components from bone, cartilage and hematoma compared to a control protein, and hence draws conclusions for rational biomaterial design. ECM components specifically modulated MSC adhesion, migration, proliferation, and osteogenic differentiation, for example, fibronectin facilitated migration, adhesion, and proliferation, but not osteogenic differentiation, whereas fibrinogen enhanced adhesion and proliferation, but not migration. Subsequently, the integrin expression pattern of MSCs was determined and related to the cell behavior on specific ECM components. Finally, on this basis, peptide sequences are reported for the potential stimulation of MSC functions. Based on the results of this study, ECM component coatings could be designed to specifically guide cell functions.

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Food literacy has emerged as a term to describe the everyday practicalities associated with healthy eating. The term is increasingly used in policy, practice, research and by the public; however, there is no shared understanding of its meaning. The purpose of this research was to develop a definition of food literacy which was informed by the identification of its components. This was considered from two perspectives: that of food experts which aimed to reflect the intention of existing policy and investment, and that of individuals, who could be considered experts in the everyday practicalities of food provisioning and consumption. Given that food literacy is likely to be highly contextual, this second study focused on disadvantaged young people living in an urban area who were responsible for feeding themselves. The Expert Study used a Delphi methodology (round one n = 43). The Young People’s Study used semi-structured, life-course interviews (n = 37). Constructivist Grounded Theory was used to analyse results. This included constant comparison of data within and between studies. From this, eleven components of food literacy were identified which fell into the domains of: planning and management; selection; preparation; and eating. These were used to develop a definition for the term “food literacy”.

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In recent years a number of urban sustainability assessment frameworks are developed to better inform policy formulation and decision-making processes. This paper introduces one of these attempts in developing a comprehensive assessment tool—i.e., Micro-level Urban-ecosystem Sustainability IndeX (MUSIX). Being an indicator-based indexing model, MUSIX investigates the environmental impacts of land-uses on urban sustainability by measuring urban ecosystem components in local scale. The paper presents the methodology of MUSIX and demonstrates the performance of the model in a pilot test-bed—i.e., in Gold Coast, Australia. The model provides useful insights on the sustainability performance of the test-bed area. The parcel-scale findings of the indicators are used to identify local problems considering six main issues of urban development—i.e., hydrology; ecology; pollution; location; design, and; efficiency. The composite index score is used to propose betterment strategies to guide the development of local area plans in conjunction with the City's Planning Scheme. In overall, this study has shown that parcel-scale environmental data provides an overview of the local sustainability in urban areas as in the example of Gold Coast, which can also be used for setting environmental policy, objectives and targets.

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An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.

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To this day, realizations in the standard-model of (lossy) trapdoor functions from discrete-log-type assumptions require large public key sizes, e.g., about Θ(λ 2) group elements for a reduction from the decisional Diffie-Hellman assumption (where λ is a security parameter). We propose two realizations of lossy trapdoor functions that achieve public key size of only Θ(λ) group elements in bilinear groups, with a reduction from the decisional Bilinear Diffie-Hellman assumption. Our first construction achieves this result at the expense of a long common reference string of Θ(λ 2) elements, albeit reusable in multiple LTDF instantiations. Our second scheme also achieves public keys of size Θ(λ), entirely in the standard model and in particular without any reference string, at the cost of a slightly more involved construction. The main technical novelty, developed for the second scheme, is a compact encoding technique for generating compressed representations of certain sequences of group elements for the public parameters.

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Heparan sulfate proteoglycans cooperate with basic fibroblast growth factor (bFGF/FGF2) signaling to control osteoblast growth and differentiation, as well as metabolic functions of osteoblasts. FGF2 signaling modulates the expression and activity of Runt-related transcription factor 2 (Runx2/Cbfa1), a key regulator of osteoblast proliferation and maturation. Here, we have characterized novel Runx2 target genes in osteoprogenitors under conditions that promote growth arrest while not yet permitting sustained phenotypic maturation. Runx2 enhances expression of genes related to proteoglycan-mediated signaling, including FGF receptors (e.g., FGFR2 and FGFR3) and proteoglycans (e.g., syndecans [Sdc1, Sdc2, Sdc3], glypicans [Gpc1], versican [Vcan]). Runx2 increases expression of the glycosyltransferase Exostosin-1 (Ext1) and heparanase, as well as alters the relative expression of N-linked sulfotransferases (Ndst1 = Ndst2 > Ndst3) and enzymes mediating O-linked sulfation of heparan sulfate (Hs2st > Hs6st) or chondroitin sulfate (Cs4st > Cs6st). Runx2 cooperates with FGF2 to induce expression of Sdc4 and the sulfatase Galns, but Runx2 and FGF2 suppress Gpc6, thus suggesting intricate Runx2 and FGF2 dependent changes in proteoglycan utilization. One functional consequence of Runx2 mediated modulations in proteoglycan-related gene expression is a change in the responsiveness of bone markers to FGF2 stimulation. Runx2 and FGF2 synergistically enhance osteopontin expression (>100 fold), while FGF2 blocks Runx2 induction of alkaline phosphatase. Our data suggest that Runx2 and the FGF/proteoglycan axis may form an extracellular matrix (ECM)-related regulatory feed-back loop that controls osteoblast proliferation and execution of the osteogenic program.

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Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.