Isotopic geochemistry of granitoids in the Jinshajiang suture zone, SW China

The Jinshajiang suture zone, located in the eastern part of the Tethyan tectonic domain, is noticeable for a large-scale distribution of Late Jurassic to Triassic granitoids. These granitoids were genetically related to the evolution of the Paleo-Tethys Ocean. The Beiwu, Linong and Lunong granitoids occur in the middle zone of the Jinshajiang Suture Zone, and possess similar geochemical features, indicating they share a common magma source. SIMS zircon U-Pb dating reveals the Beiwu, Linong and Lunong granitic intrusions were emplaced at 233.9±1.4 Ma (2 sigma), 233.1 ±1.4 Ma (2 sigma) and 231.0±1.6 Ma (2 sigma), respectively. All of these granitoids are enriched in abundances of Si (SiO2 =65.2-73.5 wt.%), and large-ion-lithophile-elements (LILEs), but depleted in high-field-strength-elements contents (HFSEs, e.g., Nb, Ta, Ti). In addition, they have low P2O5 contents (0.06-0.11 wt.%), A/CNK values ([molecular Al2O3/(CaO+Na2O+K2O)], mostly<1.1) and 10000Ga/Al ratios (1.7-2.2), consistent with the characteristics of I-type granites. In terms of isotopic compositions, these granitoids have high initial 87Sr/86Sr ratios (0.7078-0.7148), Pb isotopic compositions [(206Pb/204Pb)t=18.213-18.598, (207Pb/204Pb)t=15.637-15.730 and (208Pb/204Pb)t=38.323-38.791], zircon d18O values (7. per mil-9.3 per mil) and negative eNd(t) values (-5.1 to -6.7), suggesting they were predominantly derived from the continental crust. Their Nb/Ta ratios (average value=8.6) are consistent with those of the lower continental crust (LCC). However, variable ?Hf(t) values (-8.6 to +2.8) and the occurrences of mafic microgranular enclaves (MMEs) suggest that mantle-derived melts and lower crustal magmas were involved in the generation of these granitoids. Moreover, the high Pb isotopic ratios and elevated zircon d18O values of these rocks indicate a significant contribution of the upper crustal composition. We propose a model in which the Beiwu, Linong and Lunong granitoids were generated under a late collisional or post-collisional setting. It is possible that this collision was completed before Late Triassic. Decompression induced mantle-derived magmas underplated and provided the heat for the anatexis of the crust. Hybrid melts including mantle-derived and the lower crustal magmas were then generated. The hybrid melts thereafter ascended to a shallow depth and resulted in some degree of sedimentary rocks assimilation. Such three-component mixing magmas source and subsequent fractional crystallization could be responsible for the formation of the Beiwu, Linong and Lunong granitoids.

A mechanism of paraquat toxicity involving nitric oxide synthase

Paraquat (PQ) is a well described pneumotoxicant that produces toxicity by redox cycling with cellular diaphorases, thereby elevating intracellular levels of superoxide (O2⨪). NO synthase (NOS) has been shown to participate in PQ-induced lung injury. Current theory holds that NO reacts with O2⨪ generated by PQ to produce the toxin peroxynitrite. We asked whether NOS might alternatively function as a PQ diaphorase and reexamined the question of whether NO/O2⨪ reactions were toxic or protective. Here, we show that: (i) neuronal NOS has PQ diaphorase activity that inversely correlates with NO formation; (ii) PQ-induced endothelial cell toxicity is attenuated by inhibitors of NOS that prevent NADPH oxidation, but is not attenuated by those that do not; (iii) PQ inhibits endothelium-derived, but not NO-induced, relaxations of aortic rings; and (iv) PQ-induced cytotoxicity is potentiated in cytokine-activated macrophages in a manner that correlates with its ability to block NO formation. These data indicate that NOS is a PQ diaphorase and that toxicity of such redox-active compounds involves a loss of NO-related activity.

Modeling molecular transport in slit pores

We examine the transport of methane in microporous carbon by performing equilibrium and nonequilibrium molecular dynamics simulations over a range of pore sizes, densities, and temperatures. We interpret these simulation results using two models of the transport process. At low densities, we consider a molecular flow model, in which intermolecular interactions are neglected, and find excellent agreement between transport diffusion coefficients determined from simulation, and those predicted by the model. Simulation results indicate that the model can be applied up to fluid densities of the order to 0.1-1 nm(-3). Above these densities, we consider a slip flow model, combining hydrodynamic theory with a slip condition at the solid-fluid interface. As the diffusion coefficient at low densities can be accurately determined by the molecular flow model, we also consider a model where the slip condition is supplied by the molecular flow model. We find that both density-dependent models provide a useful means of estimating the transport coefficient that compares well with simulation. (C) 2004 American Institute of Physics.

Cycloviolacin H4, a hydrophobic cyclotide from Viola hederaceae

Cycloviolacin H4, a new macrocyclic miniprotein comprising 30 amino acid residues, was isolated from the underground parts of the Australian native violet Viola hederaceae. Its sequence, cyclo-(CAESCVWIPCTVTALLGCSCSNNVCYNGIP), was determined by nanospray tandem mass spectrometry and quantitative amino acid analysis. A knotted disuffide arrangement, which was designated as a cyclic cystine knot motif and characteristic to all known cyclotides, is proposed for stabilizing the molecular structure and folding. The cyclotide is classified in the bracelet subfamily of cyclotides due to the absence of a cis-Pro peptide bond in the circular peptide backbone. A model of its three-dimensional structure was derived based on the template of the homologous cyclotide vhr1 (Trabi et al. Plant Cell 2004, 16, 2204-2216). Cycloviolacin H4 exhibits the most potent hemolytic activity in cyclotides reported so far, and this activity correlates with the size of a surface-exposed hydrophobic patch. This work has thus provided insight into the factors that modulate the cytotoxic properties of cyclotides.

A survey on the adoption and usage of broadband internet

In spite of the increasing significance of broadband Internet, there are not many research papers explicitly addressing issues pertaining to its adoption and postadoption. Previous research on broadband has mainly focused on the supply side aspect at the national level, ignoring the importance of the demand side which may involve looking more deeply into the use, as well as factors impacting organizational and individual uptake. In an attempt to fill this gap, the current study empirically verifies an integrated theoretical model comprising the theory of planned behavior and the IS continuance model to examine factors influencing broadband Internet adoption and postadoption behavior of some 1,500 organizations in Singapore. Overall, strong support for the integrated model has been manifested by our results, providing insight into influential factors. At the adoption stage, perceived behavioral control has the greatest impact on behavioral intention. Our findings also suggest that, as compared to attitude, subjective norms and perceived behavioral control more significantly affect the broadband Internet adoption decision. At the postadoption stage, intention is no longer the only determinant of broadband Internet continuance; rather, initial usage was found to significantly affect broadband Internet continuance.

Numerical modelling of agglomerate degradation

In the processing industries particulate materials are often in the form of powders which themselves are agglomerations of much smaller sized particles. During powder processing operations agglomerate degradation occurs primarily as a result of collisions between agglomerates and between agglomerates and the process equipment. Due to the small size of the agglomerates and the very short duration of the collisions it is currently not possible to obtain sufficiently detailed quantitative information from real experiments to provide a sound theoretically based strategy for designing particles to prevent or guarantee breakage. However, with the aid of computer simulated experiments, the micro-examination of these short duration dynamic events is made possible. This thesis presents the results of computer simulated experiments on a 2D monodisperse agglomerate in which the algorithms used to model the particle-particle interactions have been derived from contact mechanics theories and, necessarily, incorporate contact adhesion. A detailed description of the theoretical background is included in the thesis. The results of the agglomerate impact simulations show three types of behaviour depending on whether the initial impact velocity is high, moderate or low. It is demonstrated that high velocity impacts produce extensive plastic deformation which leads to subsequent shattering of the agglomerate. At moderate impact velocities semi-brittle fracture is observed and there is a threshold velocity below which the agglomerate bounces off the wall with little or no visible damage. The micromechanical processes controlling these different types of behaviour are discussed and illustrated by computer graphics. Further work is reported to demonstrate the effect of impact velocity and bond strength on the damage produced. Empirical relationships between impact velocity, bond strength and damage are presented and their relevance to attrition and comminution is discussed. The particle size distribution curves resulting from the agglomerate impacts are also provided. Computer simulated diametrical compression tests on the same agglomerate have also been carried out. Simulations were performed for different platen velocities and different bond strengths. The results show that high platen velocities produce extensive plastic deformation and crushing. Low platen velocities produce semi-brittle failure in which cracks propagate from the platens inwards towards the centre of the agglomerate. The results are compared with the results of the agglomerate impact tests in terms of work input, applied velocity and damage produced.

Improved production of industrially relevant recombinant proteins: application of multi-factorial design of experiments and scalable process modelling

The work described in this thesis focuses on the use of a design-of-experiments approach in a multi-well mini-bioreactor to enable the rapid establishments of high yielding production phase conditions in yeast, which is an increasingly popular host system in both academic and industrial laboratories. Using green fluorescent protein secreted from the yeast, Pichia pastoris, a scalable predictive model of protein yield per cell was derived from 13 sets of conditions each with three factors (temperature, pH and dissolved oxygen) at 3 levels and was directly transferable to a 7 L bioreactor. This was in clear contrast to the situation in shake flasks, where the process parameters cannot be tightly controlled. By further optimisating both the accumulation of cell density in batch and improving the fed-batch induction regime, additional yield improvement was found to be additive to the per cell yield of the model. A separate study also demonstrated that improving biomass improved product yield in a second yeast species, Saccharomyces cerevisiae. Investigations of cell wall hydrophobicity in high cell density P. pastoris cultures indicated that cell wall hydrophobin (protein) compositional changes with growth phase becoming more hydrophobic in log growth than in lag or stationary phases. This is possibly due to an increased occurrence of proteins associated with cell division. Finally, the modelling approach was validated in mammalian cells, showing its flexibility and robustness. In summary, the strategy presented in this thesis has the benefit of reducing process development time in recombinant protein production, directly from bench to bioreactor.

Learning from Geometry

Subspaces and manifolds are two powerful models for high dimensional signals. Subspaces model linear correlation and are a good fit to signals generated by physical systems, such as frontal images of human faces and multiple sources impinging at an antenna array. Manifolds model sources that are not linearly correlated, but where signals are determined by a small number of parameters. Examples are images of human faces under different poses or expressions, and handwritten digits with varying styles. However, there will always be some degree of model mismatch between the subspace or manifold model and the true statistics of the source. This dissertation exploits subspace and manifold models as prior information in various signal processing and machine learning tasks.

A near-low-rank Gaussian mixture model measures proximity to a union of linear or affine subspaces. This simple model can effectively capture the signal distribution when each class is near a subspace. This dissertation studies how the pairwise geometry between these subspaces affects classification performance. When model mismatch is vanishingly small, the probability of misclassification is determined by the product of the sines of the principal angles between subspaces. When the model mismatch is more significant, the probability of misclassification is determined by the sum of the squares of the sines of the principal angles. Reliability of classification is derived in terms of the distribution of signal energy across principal vectors. Larger principal angles lead to smaller classification error, motivating a linear transform that optimizes principal angles. This linear transformation, termed TRAIT, also preserves some specific features in each class, being complementary to a recently developed Low Rank Transform (LRT). Moreover, when the model mismatch is more significant, TRAIT shows superior performance compared to LRT.

The manifold model enforces a constraint on the freedom of data variation. Learning features that are robust to data variation is very important, especially when the size of the training set is small. A learning machine with large numbers of parameters, e.g., deep neural network, can well describe a very complicated data distribution. However, it is also more likely to be sensitive to small perturbations of the data, and to suffer from suffer from degraded performance when generalizing to unseen (test) data.

From the perspective of complexity of function classes, such a learning machine has a huge capacity (complexity), which tends to overfit. The manifold model provides us with a way of regularizing the learning machine, so as to reduce the generalization error, therefore mitigate overfiting. Two different overfiting-preventing approaches are proposed, one from the perspective of data variation, the other from capacity/complexity control. In the first approach, the learning machine is encouraged to make decisions that vary smoothly for data points in local neighborhoods on the manifold. In the second approach, a graph adjacency matrix is derived for the manifold, and the learned features are encouraged to be aligned with the principal components of this adjacency matrix. Experimental results on benchmark datasets are demonstrated, showing an obvious advantage of the proposed approaches when the training set is small.

Stochastic optimization makes it possible to track a slowly varying subspace underlying streaming data. By approximating local neighborhoods using affine subspaces, a slowly varying manifold can be efficiently tracked as well, even with corrupted and noisy data. The more the local neighborhoods, the better the approximation, but the higher the computational complexity. A multiscale approximation scheme is proposed, where the local approximating subspaces are organized in a tree structure. Splitting and merging of the tree nodes then allows efficient control of the number of neighbourhoods. Deviation (of each datum) from the learned model is estimated, yielding a series of statistics for anomaly detection. This framework extends the classical {\em changepoint detection} technique, which only works for one dimensional signals. Simulations and experiments highlight the robustness and efficacy of the proposed approach in detecting an abrupt change in an otherwise slowly varying low-dimensional manifold.

Forces of agglomeration and dispersal in rural business networks: a social network analysis

Two concepts in rural economic development policy have been the focus of much research and policy action: the identification and support of clusters or networks of firms and the availability and adoption by rural businesses of Information and Communication Technologies (ICT). From a theoretical viewpoint these policies are based on two contrasting models, with clustering seen as a process of economic agglomeration, and ICT-mediated communication as a means of facilitating economic dispersion. The study’s conceptual framework is based on four interrelated elements: location, interaction, knowledge, and advantage, together with the concept of networks which is employed as an operationally and theoretically unifying concept. The research questions are developed in four successive categories: Policy, Theory, Networks, and Method. The questions are approached using a study of two contrasting groups of rural small businesses in West Cork, Ireland: (a) Speciality Foods, and (b) firms in Digital Products and Services. The study combines Social Network Analysis (SNA) with Qualitative Thematic Analysis, using data collected from semi-structured interviews with 58 owners or managers of these businesses. Data comprise relational network data on the firms’ connections to suppliers, customers, allies and competitors, together with linked qualitative data on how the firms established connections, and how tacit and codified knowledge was sourced and utilised. The research finds that the key characteristics identified in the cluster literature are evident in the sample of Speciality Food businesses, in relation to flows of tacit knowledge, social embedding, and the development of forms of social capital. In particular the research identified the presence of two distinct forms of collective social capital in this network, termed “community” and “reputation”. By contrast the sample of Digital Products and Services businesses does not have the form of a cluster, but matches more closely to dispersive models, or “chain” structures. Much of the economic and social structure of this set of firms is best explained in terms of “project organisation”, and by the operation of an individual rather than collective form of “reputation”. The rural setting in which these firms are located has resulted in their being service-centric, and consequently they rely on ICT-mediated communication in order to exchange tacit knowledge “at a distance”. It is this factor, rather than inputs of codified knowledge, that most strongly influences their operation and their need for availability and adoption of high quality communication technologies. Thus the findings have applicability in relation to theory in Economic Geography and to policy and practice in Rural Development. In addition the research contributes to methodological questions in SNA, and to methodological questions about the combination or mixing of quantitative and qualitative methods.

Représentations et fusion des algèbres de Temperley-Lieb originale et diluée

Les algèbres de Temperley-Lieb originales, aussi dites régulières, apparaissent dans de nombreux modèles statistiques sur réseau en deux dimensions: les modèles d'Ising, de Potts, des dimères, celui de Fortuin-Kasteleyn, etc. L'espace d'Hilbert de l'hamiltonien quantique correspondant à chacun de ces modèles est un module pour cette algèbre et la théorie de ses représentations peut être utilisée afin de faciliter la décomposition de l'espace en blocs; la diagonalisation de l'hamiltonien s'en trouve alors grandement simplifiée. L'algèbre de Temperley-Lieb diluée joue un rôle similaire pour des modèles statistiques dilués, par exemple un modèle sur réseau où certains sites peuvent être vides; ses représentations peuvent alors être utilisées pour simplifier l'analyse du modèle comme pour le cas original. Or ceci requiert une connaissance des modules de cette algèbre et de leur structure; un premier article donne une liste complète des modules projectifs indécomposables de l'algèbre diluée et un second les utilise afin de construire une liste complète de tous les modules indécomposables des algèbres originale et diluée. La structure des modules est décrite en termes de facteurs de composition et par leurs groupes d'homomorphismes. Le produit de fusion sur l'algèbre de Temperley-Lieb originale permet de «multiplier» ensemble deux modules sur cette algèbre pour en obtenir un autre. Il a été montré que ce produit pouvait servir dans la diagonalisation d'hamiltoniens et, selon certaines conjectures, il pourrait également être utilisé pour étudier le comportement de modèles sur réseaux dans la limite continue. Un troisième article construit une généralisation du produit de fusion pour les algèbres diluées, puis présente une méthode pour le calculer. Le produit de fusion est alors calculé pour les classes de modules indécomposables les plus communes pour les deux familles, originale et diluée, ce qui vient ajouter à la liste incomplète des produits de fusion déjà calculés par d'autres chercheurs pour la famille originale. Finalement, il s'avère que les algèbres de Temperley-Lieb peuvent être associées à une catégorie monoïdale tressée, dont la structure est compatible avec le produit de fusion décrit ci-dessus. Le quatrième article calcule explicitement ce tressage, d'abord sur la catégorie des algèbres, puis sur la catégorie des modules sur ces algèbres. Il montre également comment ce tressage permet d'obtenir des solutions aux équations de Yang-Baxter, qui peuvent alors être utilisées afin de construire des modèles intégrables sur réseaux.

Using Social Worlds Theory to Explore Influences on Community Nurses’ Experiences of Providing Out of Hours Paediatric Palliative Care

Abstract Background: Paediatric oncology palliative care in the community is rare and nationally there is a lack of standardisation of out of hours nursing service provision. Objectives: This paper seeks to explore influences on the experiences of paediatric nurses providing out of hours palliative care within the family home to children with cancer. The study used social worlds theory to aid identification and demonstration of the findings. Methods: Twelve community-based palliative cases were purposively selected from children with cancer treated at one regional centre. Tape-recorded interviews were undertaken with 54 health professionals (general practitioners, community nurses and allied health professionals) involved in providing their palliative care and five facilitated case discussions completed. Data analysis followed a grounded theory approach; chronological comparative data analysis identifying generated themes. Social worlds theory was used as a framework to examine the data. Results: Nurses’ experiences are shaped by their social world and those of the nursing team,child and family and the inter-professional team providing the care. The lack of a formalised service, sub-optimal inter-professional working and impact of social worlds influence the experience of the nurse. Conclusions: Social worlds theory provided a new perspective in understanding these experiences based within a paediatric palliative care setting, knowledge that can be used to inform service provision.

Processus d’adaptation des personnes vivant avec la schizophrénie et ayant un soutien social limité

Résumé : La schizophrénie est un trouble mental grave qui affecte toutes les facettes de la vie de la personne. En outre, le manque de soutien social est un problème important qui contribue à l’aggravation de la maladie, notamment en influençant négativement la capacité d’adaptation. Chez les personnes atteintes de schizophrénie, la capacité à utiliser des stratégies d’adaptation adéquates et efficaces est essentielle afin d’améliorer la santé, le bien-être et la prévention des rechutes. Cette recherche utilise la conception de l’adaptation de Roy (2009). De nombreuses études confirment la présence de difficultés d’adaptation chez ces personnes. De plus, le processus d’adaptation lui-même reste mal connu. La question de recherche était : Quel est le processus d’adaptation des personnes vivant avec la schizophrénie lorsque leur soutien social est limité ? Cette question sous-tendait deux objectifs : 1) décrire le processus d’adaptation des personnes atteintes de schizophrénie dans un contexte de soutien social limité et 2) contribuer au développement du modèle de Roy dans le contexte des troubles mentaux graves. Le devis de recherche était la théorisation ancrée constructiviste, auprès de 30 personnes vivant avec la schizophrénie. Les données étaient composées d’entrevues et de résultats de trois questionnaires qui ont contribué à décrire de façon plus détaillée le profil des participants. Les résultats sont une modélisation du processus d’adaptation nommée « les filtres dans le processus d’adaptation des personnes vivant avec la schizophrénie ». Cette modélisation met en lumière le fait que le potentiel d’adaptation des personnes vivant avec la schizophrénie est affecté à la fois par des éléments de l’environnement social et des éléments inhérents à la maladie elle-même. Ces éléments altèrent la possibilité et la capacité à utiliser des stratégies d’adaptation adéquates et efficaces. Ces résultats de recherche pourraient permettre d’améliorer l’évaluation des personnes atteintes de schizophrénie et de diminuer les « inconnues » dans l’effet des interventions, tout comme de favoriser les actions visant à lutter contre les conditions sociales qui nuisent à l’adaptation.

Représentations et fusion des algèbres de Temperley-Lieb originale et diluée

Les algèbres de Temperley-Lieb originales, aussi dites régulières, apparaissent dans de nombreux modèles statistiques sur réseau en deux dimensions: les modèles d'Ising, de Potts, des dimères, celui de Fortuin-Kasteleyn, etc. L'espace d'Hilbert de l'hamiltonien quantique correspondant à chacun de ces modèles est un module pour cette algèbre et la théorie de ses représentations peut être utilisée afin de faciliter la décomposition de l'espace en blocs; la diagonalisation de l'hamiltonien s'en trouve alors grandement simplifiée. L'algèbre de Temperley-Lieb diluée joue un rôle similaire pour des modèles statistiques dilués, par exemple un modèle sur réseau où certains sites peuvent être vides; ses représentations peuvent alors être utilisées pour simplifier l'analyse du modèle comme pour le cas original. Or ceci requiert une connaissance des modules de cette algèbre et de leur structure; un premier article donne une liste complète des modules projectifs indécomposables de l'algèbre diluée et un second les utilise afin de construire une liste complète de tous les modules indécomposables des algèbres originale et diluée. La structure des modules est décrite en termes de facteurs de composition et par leurs groupes d'homomorphismes. Le produit de fusion sur l'algèbre de Temperley-Lieb originale permet de «multiplier» ensemble deux modules sur cette algèbre pour en obtenir un autre. Il a été montré que ce produit pouvait servir dans la diagonalisation d'hamiltoniens et, selon certaines conjectures, il pourrait également être utilisé pour étudier le comportement de modèles sur réseaux dans la limite continue. Un troisième article construit une généralisation du produit de fusion pour les algèbres diluées, puis présente une méthode pour le calculer. Le produit de fusion est alors calculé pour les classes de modules indécomposables les plus communes pour les deux familles, originale et diluée, ce qui vient ajouter à la liste incomplète des produits de fusion déjà calculés par d'autres chercheurs pour la famille originale. Finalement, il s'avère que les algèbres de Temperley-Lieb peuvent être associées à une catégorie monoïdale tressée, dont la structure est compatible avec le produit de fusion décrit ci-dessus. Le quatrième article calcule explicitement ce tressage, d'abord sur la catégorie des algèbres, puis sur la catégorie des modules sur ces algèbres. Il montre également comment ce tressage permet d'obtenir des solutions aux équations de Yang-Baxter, qui peuvent alors être utilisées afin de construire des modèles intégrables sur réseaux.

Modeling the effect of asymmetric rolling on mechanical properties of Al-Mg alloys

The mechanical behavior under uniaxial tension of Al-Mg alloy 5182 pre-deformed in conventional rolling (CR), asymmetric rolling-continuous (ASRC), and asymmetric rolling-reversed (ASRR) was investigated and modeled with a rate dependent crystal plasticity finite element method and VPSC (Visco-Plastic Self Consistent) model. M-K theory combined with Yld2000 model by Barlat et al. (Int. J. Plasticity 2003, 19, 1297) was used to predict the strain-based and stress-based formability for AA 5182 material. It was concluded that the new ASRR process has very compatible formability with improved strength compared to CR process. These merits can be directly applied for clam-shell resistant design in rigid-packaging industry.

Predicting driving direction with weighted markov model

Driving direction prediction can be useful in different applications such as driver warning and route recommendation. In this paper, a framework is proposed to predict the driving direction based on weighted Markov model. First the city POI (Point of Interesting) map is generated from trajectory data using weighted PageRank algorithm. Then, a weighted Markov model is trained for the near term driving direction prediction based on the POI map and historical trajectories. The experimental results on real-world data set indicate that the proposed method can improve the original Markov prediction model by 10% at some circumstances and 5% overall.