910 resultados para Dynamic changes


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The premise of this dissertation is to create a highly integrated platform that combines the most current recording technologies for brain research through the development of new algorithms for three-dimensional (3D) functional mapping and 3D source localization. The recording modalities that were integrated include: Electroencephalography (EEG), Optical Topographic Maps (OTM), Magnetic Resonance Imaging (MRI), and Diffusion Tensor Imaging (DTI). This work can be divided into two parts: The first part involves the integration of OTM with MRI, where the topographic maps are mapped to both the skull and cortical surface of the brain. This integration process is made possible through the development of new algorithms that determine the probes location on the MRI head model and warping the 2D topographic maps onto the 3D MRI head/brain model. Dynamic changes of the brain activation can be visualized on the MRI head model through a graphical user interface. The second part of this research involves augmenting a fiber tracking system, by adding the ability to integrate the source localization results generated by commercial software named Curry. This task involved registering the EEG electrodes and the dipole results to the MRI data. Such Integration will allow the visualization of fiber tracts, along with the source of the EEG, in a 3D transparent brain structure. The research findings of this dissertation were tested and validated through the participation of patients from Miami Children Hospital (MCH). Such an integrated platform presented to the medical professionals in the form of a user-friendly graphical interface is viewed as a major contribution of this dissertation. It should be emphasized that there are two main aspects to this research endeavor: (1) if a dipole could be situated in time at its different positions, its trajectory may reveal additional information on the extent and nature of the brain malfunction; (2) situating such a dipole trajectory with respect to the fiber tracks could ensure the preservation of these fiber tracks (axons) during surgical interventions, preserving as a consequence these parts of the brain that are responsible for information transmission.

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One in 3,000 people in the US are born with cystic fibrosis (CF), a genetic disorder affecting the reproductive system, pancreas, and lungs. Lung disease caused by chronic bacterial and fungal infections is the leading cause of morbidity and mortality in CF. Identities of the microbes are traditionally determined by culturing followed by phenotypic and biochemical assays. It was first thought that the bacterial infections were caused by a select handful of bacteria such as S. aureus, H. influenzae, B. cenocepacia, and P. aeruginosa. With the advent of PCR and molecular techniques, the polymicrobial nature of the CF lung became evident. The CF lung contains numerous bacteria and the communities are diverse and unique to each patient. The total complexity of the bacterial infections is still being determined. In addition, only a few members of the fungal communities have been identified. Much of the fungal community composition is still a mystery. This dissertation addresses this gap in knowledge. A snap shot of CF sputa bacterial community was obtained using the length heterogeneity-PCR community profiling technique. The profiles show that south Florida CF patients have a unique, diverse, and dynamic bacterial community which changes over time. The identities of the bacteria and fungi present were determined using the state-of-the-art 454 sequencing. Sequencing results show that the CF lung microbiome contains commonly cultured pathogenic bacteria, organisms considered a part of the healthy core biome, and novel organisms. Understanding the dynamic changes of these identified microbes will ultimately lead to better therapeutical interventions. Early detection is key in reducing the lung damage caused by chronic infections. Thus, there is a need for accurate and sensitive diagnostic tests. This issue was addressed by designing a bacterial diagnostic tool targeted towards CF pathogens using SPR. By identifying the organisms associated with the CF lung and understanding their community interactions, patients can receive better treatment and live longer.

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Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

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One in 3,000 people in the US are born with cystic fibrosis (CF), a genetic disorder affecting the reproductive system, pancreas, and lungs. Lung disease caused by chronic bacterial and fungal infections is the leading cause of morbidity and mortality in CF. Identities of the microbes are traditionally determined by culturing followed by phenotypic and biochemical assays. It was first thought that the bacterial infections were caused by a select handful of bacteria such as S. aureus, H. influenzae, B. cenocepacia, and P. aeruginosa. With the advent of PCR and molecular techniques, the polymicrobial nature of the CF lung became evident. The CF lung contains numerous bacteria and the communities are diverse and unique to each patient. The total complexity of the bacterial infections is still being determined. In addition, only a few members of the fungal communities have been identified. Much of the fungal community composition is still a mystery. This dissertation addresses this gap in knowledge. A snap shot of CF sputa bacterial community was obtained using the length heterogeneity-PCR community profiling technique. The profiles show that south Florida CF patients have a unique, diverse, and dynamic bacterial community which changes over time. The identities of the bacteria and fungi present were determined using the state-of-the-art 454 sequencing. Sequencing results show that the CF lung microbiome contains commonly cultured pathogenic bacteria, organisms considered a part of the healthy core biome, and novel organisms. Understanding the dynamic changes of these identified microbes will ultimately lead to better therapeutical interventions. Early detection is key in reducing the lung damage caused by chronic infections. Thus, there is a need for accurate and sensitive diagnostic tests. This issue was addressed by designing a bacterial diagnostic tool targeted towards CF pathogens using SPR. By identifying the organisms associated with the CF lung and understanding their community interactions, patients can receive better treatment and live longer.

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Reconstructing past modes of ocean circulation is an essential task in paleoclimatology and paleoceanography. To this end, we combine two sedimentary proxies, Nd isotopes (epsilon-Nd) and the 231Pa/230Th ratio, both of which are not directly involved in the global carbon cycle, but allow the reconstruction of water mass provenance and provide information about the past strength of overturning circulation, respectively. In this study, combined 231Pa/230Th and epsilon-Nd down-core profiles from six Atlantic Ocean sediment cores are presented. The data set is complemented by the two available combined data sets from the literature. From this we derive a comprehensive picture of spatial and temporal patterns and the dynamic changes of the Atlantic Meridional Overturning Circulation over the past ~25 ka. Our results provide evidence for a consistent pattern of glacial/stadial advances of Southern Sourced Water along with a northward circulation mode for all cores in the deeper (>3000 m) Atlantic. Results from shallower core sites support an active overturning cell of shoaled Northern Sourced Water during the LGM and the subsequent deglaciation. Furthermore, we report evidence for a short-lived period of intensified AMOC in the early Holocene.

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Proper organ patterning depends on a tight coordination between cell proliferation and differentiation. The patterning of Drosophila retina occurs both very fast and with high precision. This process is driven by the dynamic changes in signaling activity of the conserved Hedgehog (Hh) pathway, which coordinates cell fate determination, cell cycle and tissue morphogenesis. Here we show that during Drosophila retinogenesis, the retinal determination gene dachshund (dac) is not only a target of the Hh signaling pathway, but is also a modulator of its activity. Using developmental genetics techniques, we demonstrate that dac enhances Hh signaling by promoting the accumulation of the Gli transcription factor Cubitus interruptus (Ci) parallel to or downstream of fused. In the absence of dac, all Hh-mediated events associated to the morphogenetic furrow are delayed. One of the consequences is that, posterior to the furrow, dac- cells cannot activate a Roadkill-Cullin3 negative feedback loop that attenuates Hh signaling and which is necessary for retinal cells to continue normal differentiation. Therefore, dac is part of an essential positive feedback loop in the Hh pathway, guaranteeing the speed and the accuracy of Drosophila retinogenesis.

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Changes in cellular calcium concentration control a wide range of physiological processes, from the subsecond release of synaptic neurotransmitters, to the regulation of gene expression over months or years. Calcium can also trigger cell death through both apoptosis and necrosis, and so the regulation of cellular calcium concentration must be tightly controlled through the concerted action of pumps, channels and buffers that transport calcium into and out of the cell cytoplasm. A hallmark of cellular calcium signalling is its spatiotemporal complexity: stimulation of cells by a hormone or neurotransmitter leads to oscillations in cytoplasmic calcium concentration that can vary markedly in time course, amplitude, frequency, and spatial range. In this chapter we review some of the biological roles of calcium, the experimental characterisation of complex dynamic changes in calcium concentration, and attempts to explain this complexity using computational models. We consider the "toolkit" of cellular proteins which influence calcium concentration, describe mechanistic models of key elements of the toolkit, and fit these into the framework of whole cell models of calcium oscillations and waves. Finally, we will touch on recent efforts to use stochastic modelling to elucidate elementary calcium signal events, and how these may evolve into global signals.

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The emergence of mass spectrometry-based proteomics has revolutionized the study of proteins and their abundances, functions, interactions, and modifications. However, in a multicellular organism, it is difficult to monitor dynamic changes in protein synthesis in a specific cell type within its native environment. In this thesis, we describe methods that enable the metabolic labeling, purification, and analysis of proteins in specific cell types and during defined periods in live animals. We first engineered a eukaryotic phenylalanyl-tRNA synthetase (PheRS) to selectively recognize the unnatural L-phenylalanine analog p-azido-L-phenylalanine (Azf). Using Caenorhabditis elegans, we expressed the engineered PheRS in a cell type of choice (i.e. body wall muscles, intestinal epithelial cells, neurons, pharyngeal muscles), permitting proteins in those cells -- and only those cells -- to be labeled with azides. Labeled proteins are therefore subject to "click" conjugation to cyclooctyne-functionalized affnity probes, separation from the rest of the protein pool and identification by mass spectrometry. By coupling our methodology with heavy isotopic labeling, we successfully identified proteins -- including proteins with previously unknown expression patterns -- expressed in targeted subsets of cells. While cell types like body wall or pharyngeal muscles can be targeted with a single promoter, many cells cannot; spatiotemporal selectivity typically results from the combinatorial action of multiple regulators. To enhance spatiotemporal selectivity, we next developed a two-component system to drive overlapping -- but not identical -- patterns of expression of engineered PheRS, restricting labeling to cells that express both elements. Specifically, we developed a split-intein-based split-PheRS system for highly efficient PheRS-reconstitution through protein splicing. Together, these tools represent a powerful approach for unbiased discovery of proteins uniquely expressed in a subset of cells at specific developmental stages.

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iGrooving is a generative music mobile application specifically designed for runners. The application’s foundation is a step-counter that is programmed using the iPhone’s built-in accelerometer. The runner’s steps generate the tempo of the performance by mapping each step to trigger a kick-drum sound file. Additionally, different sound files are triggered at specific step counts to generate the musical performance, allowing the runner a level of compositional autonomy. The sonic elements are chosen to promote a meditative aspect of running. iGrooving is conceived as a biofeedback-stimulated musical instrument and an environment for creating generative music processes with everyday technologies, inspiring us to rethink our everyday notions of musical performance as a shared experience. Isolation, dynamic changes, and music generation are detailed to show how iGrooving facilitates novel methods for music composition, performance and audience participation.

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This paper analyzes the impact of change processes experienced by many student populations when completing primary education (1st-6th grade) and starting secondary education (7th-11th grade). Based on the research conducted, this paper describes situations and aspects that may result in conditional factors for the student’s adjustment at this level: time-space changes, as well as organizational and dynamic changes that would set the new educational environment and social context in which this new stage will be developed. Such conditional factors that affect learning in incoming students: programs, teaching methodology, learning styles and new evaluation methods will be discussed. As a result of this research, a proposal is presented to facilitate transition from primary to the secondary education. This proposal includes guidelines for awareness and strengthening of pedagogical mediation, which would contribute to the permanence of students from all types of institutions in the education system.  (1) [Translator’s note: The Costa Rican education system is composed of primary education (1st-6th grade) and secondary education (7th-11th grade).]

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This paper presents a new multi-output DC/DC converter topology that has step-up and step-down conversion capabilities. In this topology, several output voltages can be generated which can be used in different applications such as multilevel converters with diode-clamped topology or power supplies with several voltage levels. Steady state and dynamic equations of the proposed multi-output converter have been developed, that can be used for steady state and transient analysis. Two control techniques have been proposed for this topology based on constant and dynamic hysteresis band height control to address different applications. Simulations have been performed for different operating modes and load conditions to verify the proposed topology and its control technique. Additionally, a laboratory prototype is designed and implemented to verify the simulation results.

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© 2014, Springer-Verlag Berlin Heidelberg.The frequency and severity of extreme events are tightly associated with the variance of precipitation. As climate warms, the acceleration in hydrological cycle is likely to enhance the variance of precipitation across the globe. However, due to the lack of an effective analysis method, the mechanisms responsible for the changes of precipitation variance are poorly understood, especially on regional scales. Our study fills this gap by formulating a variance partition algorithm, which explicitly quantifies the contributions of atmospheric thermodynamics (specific humidity) and dynamics (wind) to the changes in regional-scale precipitation variance. Taking Southeastern (SE) United States (US) summer precipitation as an example, the algorithm is applied to the simulations of current and future climate by phase 5 of Coupled Model Intercomparison Project (CMIP5) models. The analysis suggests that compared to observations, most CMIP5 models (~60 %) tend to underestimate the summer precipitation variance over the SE US during the 1950–1999, primarily due to the errors in the modeled dynamic processes (i.e. large-scale circulation). Among the 18 CMIP5 models analyzed in this study, six of them reasonably simulate SE US summer precipitation variance in the twentieth century and the underlying physical processes; these models are thus applied for mechanistic study of future changes in SE US summer precipitation variance. In the future, the six models collectively project an intensification of SE US summer precipitation variance, resulting from the combined effects of atmospheric thermodynamics and dynamics. Between them, the latter plays a more important role. Specifically, thermodynamics results in more frequent and intensified wet summers, but does not contribute to the projected increase in the frequency and intensity of dry summers. In contrast, atmospheric dynamics explains the projected enhancement in both wet and dry summers, indicating its importance in understanding future climate change over the SE US. The results suggest that the intensified SE US summer precipitation variance is not a purely thermodynamic response to greenhouse gases forcing, and cannot be explained without the contribution of atmospheric dynamics. Our analysis provides important insights to understand the mechanisms of SE US summer precipitation variance change. The algorithm formulated in this study can be easily applied to other regions and seasons to systematically explore the mechanisms responsible for the changes in precipitation extremes in a warming climate.

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La méthylation de l'ADN est une marque épigénétique importante chez les mammifères. Malgré le fait que la méthylation de la cytosine en 5' (5mC) soit reconnue comme une modification épigénétique stable, il devient de plus en plus reconnu qu'elle soit un processus plus dynamique impliquant des voies de méthylation et de déméthylation actives. La dynamique de la méthylation de l'ADN est désormais bien caractérisée dans le développement et dans le fonctionnement cellulaire des mammifères. Très peu est cependant connu concernant les implications régulatrices dans les réponses immunitaires. Pour se faire, nous avons effectué des analyses du niveau de transcription des gènes ainsi que du profilage épigénétique de cellules dendritiques (DCs) humaines. Ceux-ci ont été faits avant et après infection par le pathogène Mycobacterium tuberculosis (MTB). Nos résultats fournissent le premier portrait génomique du remodelage épigénétique survenant dans les DCs en réponse à une infection bactérienne. Nous avons constaté que les changements dans la méthylation de l'ADN sont omniprésents, identifiant 3,926 régions différentiellement méthylées lors des infections par MTB (MTB-RDMs). Les MTB-RDMs montrent un chevauchement frappant avec les régions génomiques marquées par les histones associées avec des régions amplificatrices. De plus, nos analyses ont révélées que les MTB-RDMs sont activement liées par des facteurs de transcription associés à l'immunité avant même d'être infecté par MTB, suggérant ces domaines comme étant des éléments d'activation dans un état de dormance. Nos données suggèrent que les changements actifs dans la méthylation jouent un rôle essentiel pour contrôler la réponse cellulaire des DCs à l'infection bactérienne.