989 resultados para Ideal Type


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Enlightened by the discovery of graphenes, a variety of inorganic analogues have been synthesized and characterized in recent years. Solvated Nb1-xWxS2 analogues of graphene-type sheets were prepared by lithiation and exfoliation of multistacked Nb1-xWxS2 coin roll nanowires (CRNWs), followed by in situ functionalization with gold nanoparticles to synthesize gold-loaded Nb1-xWxS2/Au nanocomposites. The Nb1-xWxS2 nanosheets and the corresponding Nb1-xWxS2/Au nanocomposites were characterized by high resolution electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDX), scanning transmission electron microscopy (STEM), dynamic light scattering (DLS) and scanning force microscopy (AFM). The graphene-type sheets are stable in water and other solvents and can be functionalized similarly as chalcogen-terminated surfaces (e.g. with Au nanoparticles).

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High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

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Sortase A is a membrane enzyme responsible for the anchoring of surface-exposed proteins to the cell wall envelope of Gram-positive bacteria. As a well-studied member of the sortase subfamily catalysing the cell wall anchoring of important virulence factors to the surface of staphylococci, enterococci and streptococci, sortase A plays a critical role in Gram-positive bacterial pathogenesis. It is thus considered a promising target for the development of new anti-infective drugs that aim to interfere with important Gram-positive virulence mechanisms, such as adhesion to host tissues, evasion of host defences, and biofilm formation. The additional properties of sortase A as an enzyme that is not required for Gram-positive bacterial growth or viability and is conveniently located on the cell membrane making it more accessible to inhibitor targeting, constitute additional reasons reinforcing the view that sortase A is an ideal target for anti-virulence drug development. Many inhibitors of sortase A have been identified to date using high-throughput or in silico screening of compound libraries (synthetic or natural), and while many have proved useful tools for probing the action model of the enzyme, several are also promising candidates for the development into potent inhibitors. This review is focused on the most promising sortase A inhibitor compounds that are currently in development as leads towards a new class of anti-infective drugs that are urgently needed to help combat the alarming increase in antimicrobial resistance.

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A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

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Introduction Research highlights patients with dual diagnoses of type 2 diabetes and acute coronary syndrome (ACS) have higher readmission rates and poorer health outcomes than patients with singular chronic conditions. Despite this, there is a lack of education programs targeted for this dual diagnosis population to improve self-management and decrease negative health outcomes. There is evidence to suggest that internet based interventions may improve health outcomes for patients with singular chronic conditions, however there is a need to develop an evidence base for ACS patients with comorbid diabetes. There is a growing awareness of the importance of a participatory model in developing effective online interventions. That is, internet interventions are more effective if end users’ perceptions of the intervention are incorporated in their final development prior to testing in large scale trials. Objectives This study investigated patients’ perspectives of the web-based intervention designed to promote self-management of the dual conditions in order to refine the intervention prior to clinical trial evaluation. Methods An interpretive approach with thematic analysis was used to obtain deeper understanding regarding participants’ experience when using web-application interventions for patients with ACS and type 2 diabetes. Semi-structured interviews were undertaken on a purposive sample of 30 patients meeting strict inclusion and exclusion criteria to obtain their perspectives on the program. Results Preliminary results indicate patients with dual diagnoses express more complex needs than those with a singular condition. Participants express a positive experience with the proposed internet intervention and emerging themes include that the web page is seen as easy to use and comforting as a support, in that patients know they are not alone. Further results will be reported as they become available. Conclusion The results indicate potential for patient acceptability of the newly developed internet intervention for patients with ACS and comorbid diabetes. Incorporation of patient perspectives into the final development of the intervention is likely to maximise successful outcomes of any future trials that utilise this intervention. Future quantitative evaluation of the effectiveness of the intervention is being planned.

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This study investigated interactions of protein-cleaving enzymes (or proteases) that promote prostate cancer progression. It provides the first evidence of a novel regulatory network of protease activity at the surface of cells. The proteases kallikrein-related peptidases 4 and 14, and matrix metalloproteinases 3 and 9 are cleaved at the cell surface by the cell surface proteases hepsin and TMPRSS2. These cleavage events potentially regulate activation of downstream targets of kallikrein 4 and 14 such as cell surface signalling via the protease-activated receptors (PARs) and cell growth-promoting factors such as hepatocyte-growth factor.

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In this paper we present concrete collision and preimage attacks on a large class of compression function constructions making two calls to the underlying ideal primitives. The complexity of the collision attack is above the theoretical lower bound for constructions of this type, but below the birthday complexity; the complexity of the preimage attack, however, is equal to the theoretical lower bound. We also present undesirable properties of some of Stam’s compression functions proposed at CRYPTO ’08. We show that when one of the n-bit to n-bit components of the proposed 2n-bit to n-bit compression function is replaced by a fixed-key cipher in the Davies-Meyer mode, the complexity of finding a preimage would be 2 n/3. We also show that the complexity of finding a collision in a variant of the 3n-bits to 2n-bits scheme with its output truncated to 3n/2 bits is 2 n/2. The complexity of our preimage attack on this hash function is about 2 n . Finally, we present a collision attack on a variant of the proposed m + s-bit to s-bit scheme, truncated to s − 1 bits, with a complexity of O(1). However, none of our results compromise Stam’s security claims.

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This project develops the required guidelines to assure stable and accurate operation of Power-Hardware-in-the-Loop implementations. The proposals of this research have been theoretically analyzed and practically examined using a Real-Time Digital Simulator. In this research, the interaction between software simulated power network and the physical power system has been studied. The conditions for different operating regimes have been derived and the corresponding analyses have been presented.

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This paper investigates the effects of primary school choices on cognitive and non-cognitive development in children using data from the Longitudinal Study of Australian Children (LSAC). We militate against the measurement problems that are associated with individual unobserved heterogeneity by exploiting the richness of LSAC data and applying contemporary econometric approaches. We find that sending children to Catholic or other independent primary schools has no significant effect on their cognitive and non-cognitive outcomes. The literature now has evidence from three different continents that the returns to attending Catholic primary schools are no different than public schools.

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Epigenetic changes correspond to heritable modifications of the chromatin structure, which do not involve any alteration of the DNA sequence but nonetheless affect gene expression. These mechanisms play an important role in cell differentiation, but aberrant occurrences are also associated with a number of diseases, including cancer and neural development disorders. In particular, aberrant DNA methylation induced by H. Pylori has been found to be a significant risk factor in gastric cancer. To investigate the sensitivity of different genes and cell types to this infection, a computational model of methylation in gastric crypts is developed. In this article, we review existing results from physical experiments and outline their limitations, before presenting the computational model and investigating the influence of its parameters.

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Density functional theory (DFT) calculations were performed to study the structural, mechanical, electrical, optical properties, and strain effects in single-layer sodium phosphidostannate(II) (NaSnP). We find the exfoliation of single-layer NaSnP from bulk form is highly feasible because the cleavage energy is comparable to graphite and MoS2. In addition, the breaking strain of the NaSnP monolayer is comparable to other widely studied 2D materials, indicating excellent mechanical flexibility of 2D NaSnP. Using the hybrid functional method, the calculated band gap of single-layer NaSnP is close to the ideal band gap of solar cell materials (1.5 eV), demonstrating great potential in future photovoltaic application. Furthermore, strain effect study shows that a moderate compression (2%) can trigger indirect-to-direct gap transition, which would enhance the ability of light absorption for the NaSnP monolayer. With sufficient compression (8%), the single-layer NaSnP can be tuned from semiconductor to metal, suggesting great applications in nanoelectronic devices based on strain engineering techniques.

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Background Demand for essential plasma-derived products is increasing. Purpose This prospective study aims to identify predictors of voluntary non-remunerated whole blood (WB) donors becoming plasmapheresis donors. Methods Surveys were sent to WB donors who had recently (recent n = 1,957) and not recently donated (distant n = 1,012). Theory of Planned Behavior (TPB) constructs (attitude, subjective norm, self-efficacy) were extended with moral norm, anticipatory regret, and donor identity. Intentions and objective plasmapheresis donation for 527 recent and 166 distant participants were assessed. Results Multi-group analysis revealed that the model was a good fit. Moral norm and self-efficacy were positively associated while role identity (suppressed by moral norm) was negatively associated with plasmapheresis intentions. Conclusions The extended TPB was useful in identifying factors that facilitate conversion from WB to plasmapheresis donation. A superordinate donor identity may be synonymous with WB donation and, for donors with a strong moral norm for plasmapheresis, may inhibit conversion.

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In two fMRI experiments, participants named pictures with superimposed distractors that were high or low in frequency or varied in terms of age of acquisition. Pictures superimposed with low-frequency words were named more slowly than those superimposed with high-frequency words, and late-acquired words interfered with picture naming to a greater extent than early-acquired words. The distractor frequency effect (Experiment 1) was associated with increased activity in left premotor and posterior superior temporal cortices, consistent with the operation of an articulatory response buffer and verbal selfmonitoring system. Conversely, the distractor age-of-acquisition effect (Experiment 2) was associated with increased activity in the left middle and posterior middle temporal cortex, consistent with the operation of lexical level processes such as lemma and phonological word form retrieval. The spatially dissociated patterns of activity across the two experiments indicate that distractor effects in picture-word interference may occur at lexical or postlexical levels of processing in speech production.

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Social media platforms, that foster user generated content, have altered the ways consumers search for product related information. Conducting online searches, reading product reviews, and comparing products ratings, is becoming a more common information seeking pathway. This research demonstrates that info-active consumers are becoming less reliant on information provided by retailers or manufacturers, hence marketing generated online content may have a reduced impact on their purchasing behaviour. The results of this study indicate that beyond traditional methods of segmenting consumers, in the online context, new classifications such as info-active and info-passive would be beneficial in digital marketing. This cross-sectional, mixed-methods study is based on 43 in-depth interviews and an online survey with 500 consumers from 30 countries.