888 resultados para Completely monotonic functions
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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.
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Australian TV News: New Forms, Functions, and Futures examines the changing relationships between television, politics and popular culture. Drawing extensively on qualitative audience research and industry interviews, this book demonstrates that while ‘infotainment’ and satirical programmes may not follow the journalism orthodoxy (or, in some cases, reject it outright), they nevertheless play an important role in the way everyday Australians understand what is happening in the world. This therefore throws into question some longstanding assumptions about what form TV news should take, the functions it ought to serve, and the future prospects of the fourth estate.
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Whether to keep products segregated (e.g., unbundled) or integrate some or all of them (e.g., bundle) has been a problem of profound interest in areas such as portfolio theory in finance, risk capital allocations in insurance and marketing of consumer products. Such decisions are inherently complex and depend on factors such as the underlying product values and consumer preferences, the latter being frequently described using value functions, also known as utility functions in economics. In this paper, we develop decision rules for multiple products, which we generally call ‘exposure units’ to naturally cover manifold scenarios spanning well beyond ‘products’. Our findings show, e.g. that the celebrated Thaler's principles of mental accounting hold as originally postulated when the values of all exposure units are positive (i.e. all are gains) or all negative (i.e. all are losses). In the case of exposure units with mixed-sign values, decision rules are much more complex and rely on cataloging the Bell number of cases that grow very fast depending on the number of exposure units. Consequently, in the present paper, we provide detailed rules for the integration and segregation decisions in the case up to three exposure units, and partial rules for the arbitrary number of units.
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We define a pair-correlation function that can be used to characterize spatiotemporal patterning in experimental images and snapshots from discrete simulations. Unlike previous pair-correlation functions, the pair-correlation functions developed here depend on the location and size of objects. The pair-correlation function can be used to indicate complete spatial randomness, aggregation or segregation over a range of length scales, and quantifies spatial structures such as the shape, size and distribution of clusters. Comparing pair-correlation data for various experimental and simulation images illustrates their potential use as a summary statistic for calibrating discrete models of various physical processes.
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Currently, mass spectrometry-based metabolomics studies extend beyond conventional chemical categorization and metabolic phenotype analysis to understanding gene function in various biological contexts (e.g., mammalian, plant, and microbial). These novel utilities have led to many innovative discoveries in the following areas: disease pathogenesis, therapeutic pathway or target identification, the biochemistry of animal and plant physiological and pathological activities in response to diverse stimuli, and molecular signatures of host-pathogen interactions during microbial infection. In this review, we critically evaluate the representative applications of mass spectrometry-based metabolomics to better understand gene function in diverse biological contexts, with special emphasis on working principles, study protocols, and possible future development of this technique. Collectively, this review raises awareness within the biomedical community of the scientific value and applicability of mass spectrometry-based metabolomics strategies to better understand gene function, thus advancing this application's utility in a broad range of biological fields
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Members of the insulin-like growth factor (IGF) family have been shown to play critical roles in normal growth and development, as well as in tumour biology. The IGF system is complex and the biological effects of the IGFs are determined by their diverse interactions between many molecules, including their interactions with extracellular matrix (ECM) proteins. Recent studies have demonstrated that IGFs associate with the ECM protein vitronectin (VN) through IGF-binding proteins (IGFBP) and that this interaction modulates IGF-stimulated biological functions, namely cell migration and cell survival through the cooperative involvement of the type-I IGF receptor (IGF-1R) and VN-binding integrins. Since IGFs play important roles in the transformation and progression of breast cancer and VN has been found to be over-expressed at the leading edge of breast tumours, this project aimed to describe the effects of IGF-I:VN interactions on breast cell function. This was undertaken to dissect the molecular mechanisms underlying IGF-I:VN-induced responses and to design inhibitors to block the effects of such interactions. The studies described herein demonstrate that the increase in migration of MCF-7 breast cancer cells in response to the IGF-I:IGFBP-5:VN complex is accompanied by differential expression of genes known to be involved in migration, invasion and/or survival, including Tissue-factor (TF), Stratifin (SFN), Ephrin-B2, Sharp-2 and PAI-1. This „migration gene signature‟ was confirmed using real-time PCR analysis. Substitution of the native IGF-I within the IGF-I:IGFBP:VN complex with the IGF-I analogue, \[L24]\[A31]-IGF-I, which has a reduced affinity for the IGF-1R, failed to stimulate cell migration and interestingly, also failed to induce the differential gene expression. This supports the involvement of the IGF-1R in mediating these changes in gene expression. Furthermore, lentiviral shRNA-mediated stable knockdown of TF and SFN completely abrogated the increased cell migration induced by IGF-I:IGFBP:VN complexes in MCF-7 cells. Indeed, when these cells were grown in 3D Matrigel™ cultures a decrease in the overall size of the 3D spheroids in response to the IGF-I:IGFBP:VN complexes was observed compared to the parental MCF-7 cells. This suggests that TF and SFN have a role in complex-stimulated cell survival. Moreover, signalling studies performed on cells with the reduced expression of either TF or SFN had a decreased IGF-1R activation, suggesting the involvement of signalling pathways downstream of IGF-1R in TF- and/or SFN-mediated cell migration and cell survival. Taken together, these studies provide evidence for a common mechanism activated downstream of the IGF-1R that induces the expression of the „migration gene signature‟ in response to the IGF-I:IGFBP:VN complex that confers breast cancer cells the propensity to migrate and survive. Given the functional significance of the interdependence of ECM and growth factor (GF) interactions in stimulating processes key to breast cancer progression, this project aimed at developing strategies to prevent such growth factor:ECM interactions in an effort to inhibit the downstream functional effects. This may result in the reduction in the levels of ECM-bound IGF-I present in close proximity to the cells, thereby leading to a reduction in the stimulation of IGF-1R present on the cell surface. Indeed, the inhibition of IGF-I-mediated effects through the disruption of its association with ECM would not alter the physiological levels of IGF-I and potentially only exert effects in situations where abnormal over expression of ECM proteins are found; namely carcinomas and hyperproliferative diseases. In summary, this PhD project has identified novel, innovative and realistic strategies that can be used in vitro to inhibit the functions exerted by the IGF-I:IGFBP:VN multiprotein complexes critical for cancer progression, with a potential to be translated into in vivo investigations. Furthermore, TF and SFN were found to mediate IGF-I:IGFBP:VN-induced effects, thereby revealing their potential to be used as therapeutic targets or as predictive biomarkers for the efficacy of IGF-1R targeting therapies in breast cancer patients. In addition to its therapeutic and clinical scope, this PhD project has significantly contributed to the understanding of the role of the IGF system in breast tumour biology by providing valuable new information on the mechanistic events underpinning IGF-I:VN-mediated effects on breast cell functions. Furthermore, this is the first instance where favourable binding sites for IGF-II, IGFBP-3 and IGFBP-5 on VN have been identified. Taken together, this study has functionally characterised the interactions between IGF-I and VN and through innovative strategies has provided a platform for the development of novel therapies targeting these interactions and their downstream effects.
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Sequences with optimal correlation properties are much sought after for applications in communication systems. In 1980, Alltop (\emph{IEEE Trans. Inf. Theory} 26(3):350-354, 1980) described a set of sequences based on a cubic function and showed that these sequences were optimal with respect to the known bounds on auto and crosscorrelation. Subsequently these sequences were used to construct mutually unbiased bases (MUBs), a structure of importance in quantum information theory. The key feature of this cubic function is that its difference function is a planar function. Functions with planar difference functions have been called \emph{Alltop functions}. This paper provides a new family of Alltop functions and establishes the use of Alltop functions for construction of sequence sets and MUBs.
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This paper presents a comprehensive formal security framework for key derivation functions (KDF). The major security goal for a KDF is to produce cryptographic keys from a private seed value where the derived cryptographic keys are indistinguishable from random binary strings. We form a framework of five security models for KDFs. This consists of four security models that we propose: Known Public Inputs Attack (KPM, KPS), Adaptive Chosen Context Information Attack (CCM) and Adaptive Chosen Public Inputs Attack(CPM); and another security model, previously defined by Krawczyk [6], which we refer to as Adaptive Chosen Context Information Attack(CCS). These security models are simulated using an indistinguisibility game. In addition we prove the relationships between these five security models and analyse KDFs using the framework (in the random oracle model).
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Adaptation to replicate environments is often achieved through similar phenotypic solutions. Whether selection also produces convergent genomic changes in these situations remains largely unknown. The variable groundsel, Senecio lautus, is an excellent system to investigate the genetic underpinnings of convergent evolution, because morphologically similar forms of these plants have adapted to the same environments along the coast of Australia. We compared range-wide patterns of genomic divergence in natural populations of this plant and searched for regions putatively affected by natural selection. Our results indicate that environmental adaptation followed complex genetic trajectories, affecting multiple loci, implying both the parallel recruitment of the same alleles and the divergence of completely different genomic regions across geography. An analysis of the biological functions of candidate genes suggests that adaptation to coastal environments may have occurred through the recruitment of different genes participating in similar processes. The relatively low genetic convergence that characterizes the parallel evolution of S. lautus forms suggests that evolution is more constrained at higher levels of biological organization.
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Background: The insulin-like growth factor (IGF) system is composed of ligands and receptors which regulate cell proliferation, survival, differentiation and migration. Some functions are regulated via intracellular signaling cascades, others by involvement of the extracellular milieu, including binding proteins and other extracellular matrix proteins. However, understanding of their functions and the exact nature of these interactions remains incomplete. Methods: IGF-I was PEGylated at its lysine sites - K27, K65 and K68. Binding of PEG-IGF-I to the IGFBPs was analyzed using BIAcore and its ability to activate the IGF-IR was assessed using IGF-IR phosphorylation assay. Furthermore, functional consequences of PEGylating the lysine residues of IGF-I was investigated using cell viability and cell migration assays. In addition, particular downstream signaling pathways regularly implicated in these mechanisms were also dissected using phospho-AKT and phospho-ERK1/2 assays. Results: In this study, IGF-I specifically PEGylated at lysine 27 (PEG-K27), 65 (PEG-K65) or 68 (PEG-K68) were employed. Receptor phosphorylation was only reduced by 2-fold with PEG-K65 and PEG-K68 over all the time points tested, and as observed in two cell types, 3T3 fibroblasts and MCF-7 breast cancer cells. PEGylation at K27 resulted in a much larger effect, with more than 10-fold lower activation for 3T3 fibroblasts and a ~3 fold reduced IGF-IR activation for MCF-7 breast cancer cells over 15 minutes. In addition, all PEG-IGF-I variants demonstrated a ten-fold reduction in the association rate to IGF binding proteins (IGFBPs). Functionally, all PEG variants completely lost their ability to induce cell migration in the presence of IGFBP-3/vitronectin (VN) complexes as compared to IGF-I; in contrast, cell viability was fully preserved. Further investigations into the downstream signaling pathways revealed that the PI3-K/AKT pathway was preferentially affected upon treatment with the PEG-IGF-I variants compared to the MAPK/ERK pathway. Conclusion: PEGylation of IGF-I has an impact on cell migration but not cell viability. General significance: PEG-IGF-I may differentially modulate IGF-I mediated functions that are dependent on its interaction with its receptor as well as key extracellular proteins such as VN and IGFBPs.
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The importance of applying unsaturated soil mechanics to geotechnical engineering design has been well understood. However, the consumption of time and the necessity for a specific laboratory testing apparatus when measuring unsaturated soil properties have limited the application of unsaturated soil mechanics theories in practice. Although methods for predicting unsaturated soil properties have been developed, the verification of these methods for a wide range of soil types is required in order to increase the confidence of practicing engineers in using these methods. In this study, a new permeameter was developed to measure the hydraulic conductivity of unsaturated soils using the steady-state method and directly measured suction (negative pore-water pressure) values. The apparatus is instrumented with two tensiometers for the direct measurement of suction during the tests. The apparatus can be used to obtain the hydraulic conductivity function of sandy soil over a low suction range (0-10 kPa). Firstly, the repeatability of the unsaturated hydraulic conductivity measurement, using the new permeameter, was verified by conducting tests on two identical sandy soil specimens and obtaining similar results. The hydraulic conductivity functions of the two sandy soils were then measured during the drying and wetting processes of the soils. A significant hysteresis was observed when the hydraulic conductivity was plotted against the suction. However, the hysteresis effects were not apparent when the conductivity was plotted against the volumetric water content. Furthermore, the measured unsaturated hydraulic conductivity functions were compared with predictions using three different predictive methods that are widely incorporated into numerical software. The results suggest that these predictive methods are capable of capturing the measured behavior with reasonable agreement.
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Gemcitabine is indicated in combination with cisplatin as first-line therapy for solid tumours including non-small cell lung cancer (NSCLC), bladder cancer and mesothelioma. Gemcitabine is an analogue of pyrimidine cytosine and functions as an anti-metabolite. Structurally, however, gemcitabine has similarities to 5-aza-2-deoxycytidine (decitabine/Dacogen®), a DNA methyltransferase inhibitor (DNMTi). NSCLC, mesothelioma and prostate cancer cell lines were treated with decitabine and gemcitabine. Reactivation of epigenetically silenced genes was examined by RT-PCR/qPCR. DNA methyltransferase activity in nuclear extracts and recombinant proteins was measured using a DNA methyltransferase assay, and alterations in DNA methylation status were examined using methylation-specific PCR (MS-PCR) and pyrosequencing. We observe a reactivation of several epigenetically silenced genes including GSTP1, IGFBP3 and RASSF1A. Gemcitabine functionally inhibited DNA methyltransferase activity in both nuclear extracts and recombinant proteins. Gemcitabine dramatically destabilised DNMT1 protein. However, DNA CpG methylation was for the most part unaffected by gemcitabine. In conclusion, gemcitabine both inhibits and destabilises DNA methyltransferases and reactivates epigenetically silenced genes having activity equivalent to decitabine at concentrations significantly lower than those achieved in the treatment of patients with solid tumours. This property may contribute to the anticancer activity of gemcitabine.
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The Chlamydia trachomatis serine protease HtrA (CtHtrA) has recently been demonstrated to be essential during the replicative phase of the chlamydial developmental cycle. A chemical inhibition strategy (serine protease inhibitor JO146) was used to demonstrate this essential role and it was found that the chlamydial inclusions diminish in size and are lost from the cell after CtHtrA inhibition without formation of viable elementary bodies. The inhibitor (JO146) was used in this study to investigate the role of CtHtrA for penicillin persistence and heat stress model conditionscultures for Chlamydia trachomatis. JO146 addition during penicillin persistence resulted in only minor reductions (~1 log) in the final viable infectious yield after persistent Chlamydia were reverted from persistence. However, JO146 treatment during the reversion and recovery from penicillin persistence was completely lethal for Chlamydia trachomatis. JO146 was completely lethal when added either during heat stress conditions, or during the recovery from heat stress conditions. These data together indicate that CtHtrA has essential roles during some stress environments (heat shock), recovery from stress environments (heat shock and penicillin persistence), as well as the previously characterised essential role during the replicative phase of the chlamydial developmental cycle. Thus, CtHtrA is an essential protease with both replicative phase and stress condition functions for Chlamydia trachomatis.
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It is widely acknowledged that effective asset management requires an interdisciplinary approach, in which synergies should exist between traditional disciplines such as: accounting, engineering, finance, humanities, logistics, and information systems technologies. Asset management is also an important, yet complex business practice. Business process modelling is proposed as an approach to manage the complexity of asset management through the modelling of asset management processes. A sound foundation for the systematic application and analysis of business process modelling in asset management is, however, yet to be developed. Fundamentally, a business process consists of activities (termed functions), events/states, and control flow logic. As both events/states and control flow logic are somewhat dependent on the functions themselves, it is a logical step to first identify the functions within a process. This research addresses the current gap in knowledge by developing a method to identify functions common to various industry types (termed core functions). This lays the foundation to extract such functions, so as to identify both commonalities and variation points in asset management processes. This method describes the use of a manual text mining and a taxonomy approach. An example is presented.
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Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.