987 resultados para IMBHs, Globular Clusters Core Dynamics, SINFONI, IFU, Adaptive Optics SPectroscopy


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Background Despite a revived interest in fat grafting procedures, clinicians still fail to demonstrate clearly the in vivo behavior of fat grafts as a dynamic tissue substitute. However, the basic principles in cellular biology teach us that cells can survive and develop, provided that a structural matrix exists that directs their behavior. The purpose of this in vitro study was to analyze that behavior of crude fat grafts, cultured on a three-dimensional laminin-rich matrix. Methods Nonprocessed, human fat biopsy specimens (approximately 1 mm) were inoculated on Matrigel-coated wells to which culture medium was added. The control group consisted of fat biopsy specimens embedded in medium alone. The cellular proliferation pattern was followed over 6 weeks. Additional cultures of primary generated cellular spheroids were performed and eventually subjected to adipogenic differentiation media. Results A progressive outgrowth of fibroblast-like cells from the core fat biopsy specimen was observed in both groups. Within the Matrigel group, an interconnecting three-dimensional network of spindle-shaped cells was established. This new cell colony reproduced spheroids that functioned again as solitary sources of cellular proliferation. Addition of differentiation media resulted in lipid droplet deposition in the majority of generated cells, indicating the initial steps of adipogenic differentiation. Conclusions The authors noticed that crude, nonprocessed fat biopsy specimens do have considerable potential for future tissue engineering-based applications, provided that the basic principles of developmental, cellular biology are respected. Spontaneous in vitro expansion of the stromal cells present in fat grafts within autologous and injectable matrices could create "off-the-shelf" therapies for reconstructive procedures.

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Analysing census and industry data at the metro and neighbourhood levels, this paper seeks to identify the location characteristics associated with artistic clusters and determine how these characteristics vary across different places. We find that the arts cannot be taken overall as an urban panacea, but rather that their impact is place-specific and policy ought to reflect these nuances. However, our work also finds that, paradoxically, the arts’ role in developing metro economies is as highly underestimated as it is overgeneralised. While arts clusters exhibit unique industry, scale and place-specific attributes, we also find evidence that they cluster in ‘innovation districts’, suggesting they can play a larger role in economic development. To this end, our results raise important questions and point toward new approaches for arts-based urban development policy that look beyond a focus on the arts as amenities to consider the localised dynamics between the arts and other industries.

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Service compositions enable users to realize their complex needs as a single request. Despite intensive research, especially in the area of business processes, web services and grids, an open and valid question is still how to manage service compositions in order to satisfy both functional and non-functional requirements as well as adapt to dynamic changes. In this paper we propose an (functional) architecture for adaptive management of QoS-aware service compositions. Comparing to the other existing architectures this one offers two major advantages. Firstly, this architecture supports various execution strategies based on dynamic selection and negotiation of services included in a service composition, contracting based on service level agreements, service enactment with flexible support for exception handling, monitoring of service level objectives, and profiling of execution data. Secondly, the architecture is built on the basis of well know existing standards to communicate and exchange data, which significantly reduces effort to integrate existing solutions and tools from different vendors. A first prototype of this architecture has been implemented within an EU-funded Adaptive Service Grid project. © 2006 Springer-Verlag.

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Goodbye Brigadoon examines the shifting role media production plays in the economic and cultural strategies of global cities in small market nations, specifically Glasgow, Scotland. In particular, this project focuses on the formation of a digital media village along the banks of the River Clyde to argue the site constitutes a logical component to Glasgow’s ongoing transformation into a cosmopolitan center. Yet, as the regional government’s economic strategies and policy directives work to transform the abandoned waterfront into a center of cultural activity, this project also underscores the contradictory cultural dynamics to emerge from media production’s new role in the post-industrial city. At its core, the media hub reveals a regional government more interested in the technology used to deliver “national” stories than the manner of the stories themselves or the cultural practices responsible for creating them. Indeed, Goodbye Brigadoon is most interested in how media professionals based at the emergent cluster negotiate a sense of cultural identity and creative license against the institutional constraints, policy matters, and commercial logic they also must navigate in their workaday rituals. Ultimately, the conclusions offered in this project argue for a more complicated conception of the global-local location where these professionals work. Glasgow’s digital media village, in other words, is much more than an innocuous site of competitive advantage, urban regeneration, and job growth. It is best understood as a site of intense social struggle and unequal power relations where local mediamakers often find the site’s impetus for multiplatform media production an institutionally enforced false promise at odds with the realities of creative labor in the city.

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Background Hemorrhagic fever with renal syndrome (HFRS) is a rodent-borne disease caused by many serotypes of hantaviruses. In China, HFRS has been recognized as a severe public health problem with 90% of the total reported cases in the world. This study describes the spatiotemporal dynamics of HFRS cases in China and identifies the regions, time, and populations at highest risk, which could help the planning and implementation of key preventative measures. Methods Data on all reported HFRS cases at the county level from January 2005 to December 2012 were collected from Chinese Center for Disease Control and Prevention. Geographic Information System-based spatiotemporal analyses including Local Indicators of Spatial Association and Kulldorff's space-time scan statistic were performed to detect local high-risk space-time clusters of HFRS in China. In addition, cases from high-risk and low-risk counties were compared to identify significant demographic differences. Results A total of 100,868 cases were reported during 2005–2012 in mainland China. There were significant variations in the spatiotemporal dynamics of HFRS. HFRS cases occurred most frequently in June, November, and December. There was a significant positive spatial autocorrelation of HFRS incidence during the study periods, with Moran's I values ranging from 0.46 to 0.56 (P<0.05). Several distinct HFRS cluster areas were identified, mainly concentrated in northeastern, central, and eastern of China. Compared with cases from low-risk areas, a higher proportion of cases were younger, non-farmer, and floating residents in high-risk counties. Conclusions This study identified significant space-time clusters of HFRS in China during 2005–2012 indicating that preventative strategies for HFRS should be particularly focused on the northeastern, central, and eastern of China to achieve the most cost-effective outcomes.

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Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. This study explored spatio-temporal distribution and clustering of locally-acquired dengue cases in Queensland State, Australia and identified target areas for effective interventions. A computerised locally-acquired dengue case dataset was collected from Queensland Health for Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Dengue hot spots were detected using SatScan method. Descriptive spatial analysis showed that a total of 2,398 locally-acquired dengue cases were recorded in central and northern regions of tropical Queensland. A seasonal pattern was observed with most of the cases occurring in autumn. Spatial and temporal variation of dengue cases was observed in the geographic areas affected by dengue over time. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in tropical Queensland, Australia. There is a clear evidence for the existence of statistically significant clusters of dengue and these clusters varied over time. These findings enabled us to detect and target dengue clusters suggesting that the use of geospatial information can assist the health authority in planning dengue control activities and it would allow for better design and implementation of dengue management programs.

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The problem of separability in recent models of classical relativistic interacting particles is examined. This physical requirement is shown to be more subtle than naive separability of all the constraints defining the system: it is adequate to be able to canonically transform the time-fixing constraints from an unseparated to a separated form when clusters emerge. Viewing separability in this way, and within a specific framework, we are led to a new no-interaction theorem which states the incompatibility of nontrivial interaction with relativistic invariance, separability, and invariant world lines for more than two particles.

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Environmental variation is a fact of life for all the species on earth: for any population of any particular species, the local environmental conditions are liable to vary in both time and space. In today's world, anthropogenic activity is causing habitat loss and fragmentation for many species, which may profoundly alter the characteristics of environmental variation in remaining habitat. Previous research indicates that, as habitat is lost, the spatial configuration of remaining habitat will increasingly affect the dynamics by which populations are governed. Through the use of mathematical models, this thesis asks how environmental variation interacts with species properties to influence population dynamics, local adaptation, and dispersal evolution. More specifically, we couple continuous-time continuous-space stochastic population dynamic models to landscape models. We manipulate environmental variation via parameters such as mean patch size, patch density, and patch longevity. Among other findings, we show that a mixture of high and low quality habitat is commonly better for a population than uniformly mediocre habitat. This conclusion is justified by purely ecological arguments, yet the positive effects of landscape heterogeneity may be enhanced further by local adaptation, and by the evolution of short-ranged dispersal. The predicted evolutionary responses to environmental variation are complex, however, since they involve numerous conflicting factors. We discuss why the species that have high levels of local adaptation within their ranges may not be the same species that benefit from local adaptation during range expansion. We show how habitat loss can lead to either increased or decreased selection for dispersal depending on the type of habitat and the manner in which it is lost. To study the models, we develop a recent analytical method, Perturbation expansion, to enable the incorporation of environmental variation. Within this context, we use two methods to address evolutionary dynamics: Adaptive dynamics, which assumes mutations occur infrequently so that the ecological and evolutionary timescales can be separated, and via Genotype distributions, which assume mutations are more frequent. The two approaches generally lead to similar predictions yet, exceptionally, we show how the evolutionary response of dispersal behaviour to habitat turnover may qualitatively depend on the mutation rate.

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In my thesis I have been studying the effects of population fragmentation and extinction-recolonization dynamics on genetic and evolutionary processes in the Glanville fritillary butterfly (Melitaea cinxia). By conducting crosses within and among newly-colonized populations and using several fitness measures, I found a strong decrease in fitness following colonization by a few related individuals, and a strong negative relationship between parental relatedness and offspring fitness. Thereafter, I was interested in determining the number and relatedness of individuals colonizing new populations, which I did using a set of microsatellites I had previously developed for this species. Additionally, I am interested in the evolution of key life-history traits. By following the lifetime reproductive success of males emerging at different times in a semi-natural setup, I demonstrated that protandry is adaptive in males, and I was able to rule out, for M. cinxia, alternative incidental hypotheses evoked to explain the evolution of protandry in insects. Finally, in work I did together with Prof. Hanna Kokko, I am proposing bet-hedging as a new mechanism that could explain the evolution of polyandry in M. cinxia.

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An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

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Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

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Peanut agglutinin is a homotetrameric nonglycosylated protein. The protein has a unique open quaternary structure. Molecular dynamics simulations have been employed follow the atomistic details of its unfolding at different temperatures. The early events of the deoligomerization of the protein have been elucidated in the present study. Simulation trajectories of the monomer as well as those of the tetramer have been compared and the tetramer is found to be substantially more stable than its monomeric counterpart. The tetramer shows retention of most of its.. secondary structure but considerable loss of the tertiary structure at high temperature. e generation of a This observation impies the molten globule-like intermediate in the later stages of deoligomerization. The quaternary structure of the protein has weakened to a large extent, but none of the subunits are separated. In addition, the importance of the metal-binding to the stability of the protein structure has also been investigated. Binding of the metal ions not only enhances the local stability of the metal-ion binding loop, but also imparts a global stability to the overall structure. The dynamics of different interfaces vary significantly as probed through interface clusters. The differences are substantially enhanced at higher temperatures. The dynamics and the stability of the interfaces have been captured mainly by cluster analysis, which has provided detailed information on the thermal deoligomerization of the protein.

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Oleate-capped ZnO:MgO nanocrystals have been synthesized that are soluble in nonpolar solvents and which emit strongly in the visible region (450−600 nm) on excitation by UV radiation. The visible emission involves recombination of trap states of the nanocrystalline ZnO core and has a higher quantum yield than the band gap UV exciton emission. The spectrally resolved dynamics of the trap states have been investigated by time-resolved emission spectroscopy. The time-evolution of the photoluminescence spectra show that there are, in fact, two features in the visible emission whose relative importance and efficiencies vary with time. These features originate from recombination involving trapped electrons and holes, respectively, and with efficiencies that depend on the occupancy of the trap density of states.

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This thesis concerns the dynamics of nanoparticle impacts on solid surfaces. These impacts occur, for instance, in space, where micro- and nanometeoroids hit surfaces of planets, moons, and spacecraft. On Earth, materials are bombarded with nanoparticles in cluster ion beam devices, in order to clean or smooth their surfaces, or to analyse their elemental composition. In both cases, the result depends on the combined effects of countless single impacts. However, the dynamics of single impacts must be understood before the overall effects of nanoparticle radiation can be modelled. In addition to applications, nanoparticle impacts are also important to basic research in the nanoscience field, because the impacts provide an excellent case to test the applicability of atomic-level interaction models to very dynamic conditions. In this thesis, the stopping of nanoparticles in matter is explored using classical molecular dynamics computer simulations. The materials investigated are gold, silicon, and silica. Impacts on silicon through a native oxide layer and formation of complex craters are also simulated. Nanoparticles up to a diameter of 20 nm (315000 atoms) were used as projectiles. The molecular dynamics method and interatomic potentials for silicon and gold are examined in this thesis. It is shown that the displacement cascade expansionmechanism and crater crown formation are very sensitive to the choice of atomic interaction model. However, the best of the current interatomic models can be utilized in nanoparticle impact simulation, if caution is exercised. The stopping of monatomic ions in matter is understood very well nowadays. However, interactions become very complex when several atoms impact on a surface simultaneously and within a short distance, as happens in a nanoparticle impact. A high energy density is deposited in a relatively small volume, which induces ejection of material and formation of a crater. Very high yields of excavated material are observed experimentally. In addition, the yields scale nonlinearly with the cluster size and impact energy at small cluster sizes, whereas in macroscopic hypervelocity impacts, the scaling 2 is linear. The aim of this thesis is to explore the atomistic mechanisms behind the nonlinear scaling at small cluster sizes. It is shown here that the nonlinear scaling of ejected material yield disappears at large impactor sizes because the stopping mechanism of nanoparticles gradually changes to the same mechanism as in macroscopic hypervelocity impacts. The high yields at small impactor size are due to the early escape of energetic atoms from the hot region. In addition, the sputtering yield is shown to depend very much on the spatial initial energy and momentum distributions that the nanoparticle induces in the material in the first phase of the impact. At the later phases, the ejection of material occurs by several mechanisms. The most important mechanism at high energies or at large cluster sizes is atomic cluster ejection from the transient liquid crown that surrounds the crater. The cluster impact dynamics detected in the simulations are in agreement with several recent experimental results. In addition, it is shown that relatively weak impacts can induce modifications on the surface of an amorphous target over a larger area than was previously expected. This is a probable explanation for the formation of the complex crater shapes observed on these surfaces with atomic force microscopy. Clusters that consist of hundreds of thousands of atoms induce long-range modifications in crystalline gold.

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This paper presents a complete asymptotic analysis of a simple model for the evolution of the nocturnal temperature distribution on bare soil in calm clear conditions. The model is based on a simplified flux emissivity scheme that provides a nondiffusive local approximation for estimating longwave radiative cooling near ground. An examination of the various parameters involved shows that the ratio of the characteristic radiative to the diffusive timescale in the problem is of order 10(-3), and can therefore be treated as a small parameter (mu). Certain other plausible approximations and linearization lead to a new equation whose asymptotic solution as mu --> 0 can be written in closed form. Four regimes, consishttp://eprints.iisc.ernet.in/cgi/users/home?screen=EPrint::Edit&eprintid=27192&stage=core#tting of a transient at nominal sunset, a radiative-diffusive boundary ('Ramdas') layer on ground, a boundary layer transient and a radiative outer solution, are identified. The asymptotic solution reproduces all the qualitative features of more exact numerical simulations, including the occurrence of a lifted temperature minimum and its evolution during night, ranging from continuing growth to relatively sudden collapse of the Ramdas layer.