Single-particle tracking is a technique that allows for quantitative analysis of the localization and movement of particles. In this technique, trajectories are constructed by determining and connecting the positions of individual particles from consecutive images. Recent advances have made it possible to track hundreds of particles in an individual cell by labeling the particles of interest with photoactivatable or photoconvertible fluorescent proteins and tracking one or a few at a time. Single-particle tracking can be used to study the diffusion of particles. Here, we use intracellular single-particle tracking and trajectory simulations to study the diffusion of the fluorescent protein mEos2 in living Escherichia coli cells. Our data are consistent with a simple model in which mEos2 diffuses normally at 13 µm2 s−1 in the E. coli cytoplasm. Our approach can be used to study the diffusion of intracellular particles that can be labeled with mEos2 and are present at high copy numbers. Single-particle tracking can also be used to determine whether an individual particle is bound or free if the free particle diffuses significantly faster than its binding targets and remains bound or free for a long time. Here, we use single-particle tracking in living E. coli cells to determine the fractions of free ribosomal subunits, classify individual subunits as free or mRNA-bound, and quantify the degree of exclusion of bound and free subunits separately. We show that, unlike bound subunits, free subunits are not excluded from the nucleoid. This finding strongly suggests that translation of nascent mRNAs can start throughout the nucleoid, which reconciles the spatial separation of DNA and ribosomes with co-transcriptional translation. We also show that, after translation inhibition, free subunit precursors are partially excluded from the compacted nucleoid. This finding indicates that it is active translation that normally allows ribosomal subunits to assemble on nascent mRNAs throughout the nucleoid and that the effects of translation inhibitors are enhanced by the limited access of ribosomal subunits to nascent mRNAs in the compacted nucleoid.

The circulation and gradual transformation in properties of oceanic water masses is a matter of great interest for short-term weather and biological forecasting, as well as long-term climate change. It is usually agreed that the Nordic Seas between Greenland and Norway are key to these transformations since they are an important producer of dense water, a process central to the theory of the global thermohaline circulation. In this study, one component of this deep water is examined – that formed in the Nordic Seas themselves from the inflowing North Atlantic Current. Using Lagrangian particle tracking applied to a 50-year global ocean hindcast simulation, it is concluded that only about 6% of the inflowing North Atlantic Current is thus transformed, and that most of these transformations occur in boundary currents. Furthermore, it is found that the densified North Atlantic water attains only medium depths instead of joining the deep overflows. The model’s poor representation of vertical mixing, however, limits the applicability of this study to deep water formation.

Essen, Universiẗat, Diss., 2005--Duisburg.

No description available.

Fluid jet polishing (FJP) is a new advanced polishing technology that finds applications in many industries, especially in the optics industry. With the broad application of various surfaces in optics, the sub-micrometric scale and the nanometric surface roughness accuracy are major challenges. Fluid jet polishing is a technology developed from abrasive water jet machining. This technology is a water jet cutting technology, which uses high-pressure flow to cut/remove materials. In this thesis, the working principle, and simulations, as well as verification of fluid jet polishing are thoroughly investigated. The verification of fluid jet polishing in this thesis includes velocity distribution and material removal derivations. The amount of material removed is directly related to the impact velocity of a particle with a surface, which helps define its abrasive particle velocity. During polishing, the particles travel in a solution called slurry. Due to the relatively similar velocity of the particles and the slurry, the particles and the slurry are assumed to be traveling at the same rate. In this thesis, three specific examples are investigated through the creation of an advanced model using FLUENT, a computational fluid dynamics software. The model simulates the particle path during the fluid jet polishing process, and this thesis compares the simulation results to prior analytical and experimental results. The results indicate that the fluid jet polishing erosion area at a particular location is axisymmetric when the 2D cross-section shape is investigated. As the impingement angle of the fluid jet is reduced, the center dead area, where no polishing is observed, approaches zero. vii Additionally, the horizontal component of the velocity vector initially increases then decreases as one moves away from the center stagnation point. Finally, this thesis demonstrates that the erosion depth into the surface that is polished increases when the working pressure of the fluid is increased. This thesis finds that when the distance between the fluid jet and the workpiece is 7 mm, material removal is maximum.

No description available.

This thesis describes searches for a heavy charged Higgs boson decaying into a top and bottom quark pair, and the development of a hardware track trigger with theATLAS experiment. The data for the two searches was collected with the ATLAS detector at the Large Hadron Collider(LHC) with pp collision energies of √s = 8 and 13 TeV, and corresponds to an integrated luminosity of 20.3 and 13.2 fb-1 respectively. The main background for this signal is the production of tt̄ pairs with additional heavy flavor radiation. The searches with a single lepton in the final state found no evidence of a charged Higgs boson, and set 95% CLS upper limits on the production times branching ratio for masses ranging between 200-1000 GeV. The preparation of using the final state with two leptons in future searches is discussed. The design of a hardware track trigger based on pattern matching and linear track fitting was studied for the purpose of reducing the high event rates of the High-Luminosity LHC, which is expected to provide pp collisions with a luminosity about five times the nominal value, in the second half of the 2020’s. A simulation framework was developed to emulate the pattern matching and was used to test its ability to filter hits in high pile-up environments. The results of this simulation, together with simulations of the track fitting and latency, show that such a track trigger is a viable option for the ATLAS experiment in the High Luminosity-LHC era.

[pt] Foi desenvolvido um sistema de mediação de campo completo de velocidade de escoamento de fluidos. A técnica empregada é conhecida como Particle Tracking Velocimetry (PTV). As medidas foram determinadas a partir de imagens de trajetórias de partículas em suspensão no fluido. As imagens foram digitalizadas e processadas automaticamente em um microcomputador. O processamento foi feito por um software dedicado que identifica as trajetórias e calcula as velocidades associadas. Para comparação dos resultados obtidos o sistema desenvolvido foi aplicado a um escoamento cujo perfil de velocidade é conhecido. Foram analisadas as influências nos resultados de características das imagens e de seu processamento. / [en] A system for full field velocity measurement in fluid flows has been developed. The technique employed is known as Particle Tracking Velocimetry (PTV). Velocity measurements have been performed based on images of particles seeded in the fluid. The images have been digitized and automatically processed in a micro-computer. Image processing tecniques have been employed using a dedicated software that identifies particles trajectories and calculates associated velocities. To compare the results obtained, the system developed was applied to test flows with known velocity profiles. A detailed uncertainty analisys developed revealed the influence. On the results. of the image characteristics and processing procedures.

The objective of this research is to evaluate a coastal prediction system under various real world scenarios to test the efficacy of the system as a management tool in Tampa Bay. The prediction system, comprised of a three-dimensional numerical circulation model and a Lagrangian based particle tracking model, simulates oceanographic scenarios in the bay for past (hindcast), present (nowcast) and future (forecast) time frames. Instantaneous velocity output from the numerical circulation model drives the movement of particles, each representing a fraction of the total material, within the model grid cells. This work introduces a probability calculation that allows for rapid analysis of bay-wide particle transport. At every internal time step a ratio between the number of particles in each individual model grid cell to the total number of particles in the entire model domain is calculated. These ratios, herein called transport quotients, are used to construct probability maps showing locations in Tampa Bay most likely to be impacted by the contaminant. The coastal prediction system is first evaluated using dimensionless particles during an anhydrous ammonia spill. In subsequent studies biological and chemical characteristics are incorporated into the transport quotient calculations when constructing probability maps. A salinity tolerance is placed on particles representing Karenia brevis during hindcast simulations of a harmful algal bloom in the bay. Photobleaching rates are incorporated into probability maps constructed from hindcast simulations of seasonal colored dissolved organic matter (CDOM) transport. The coastal prediction system is made more robust with the inclusion of biological parameters overlaid on top of the circulation dynamics. The system successfully describes the basic physical mechanisms underlying the transport of contaminants in the bay under various real world scenarios. The calculation of transport quotients during the simulations in order to develop probability maps is a novel concept when simulating particle transport but one which can be used in real-time to support the management decisions of environmental agencies in the bay area.

L'objet de cette thèse est l'étude quantitative du mouvement des particules intracellulaires, comme les protéines ou les molécules. L'estimation du mouvement des particules au sein de la cellule est en effet d'un intérêt majeur en biologie cellulaire puisqu'il permet de comprendre les interactions entre les différents composants de la cellule. Dans cette thèse, nous modélisons les trajectoires des particules avec des processus stochastiques puisque le milieu intra-cellulaire est soumis à de nombreux aléas. Les diffusions, des processus à trajectoires continues, permettent de modéliser un large panel de mouvements intra-cellulaires. Les biophysiciens distinguent trois principaux types de diffusion: le mouvement brownien, la super-diffusion et la sous-diffusion. Ces différents types de mouvement correspondent à des scénarios biologiques distincts. Le déplacement d'une particule évoluant sans contrainte dans le cytosol ou dans le plasma membranaire est modélisée par un mouvement brownien; la particule ne se déplace pas dans une direction précise et atteint sa destination en un temps long en moyenne. Les particules peuvent aussi être propulsées par des moteurs moléculaires le long des microtubules et filaments d'actine du cytosquelette de la cellule. Leur mouvement est alors modélisé par des super-diffusions. Enfin, la sous-diffusion peut être observée dans deux situations: i/ lorsque la particule est confinée dans un micro domaine, ii/ lorsqu’elle est ralentie par l'encombrement moléculaire et doit se frayer un chemin parmi des obstacles mobiles ou immobiles. Nous présentons un test statistique pour effectuer la classification des trajectoires en trois groupes: brownien, super-diffusif et sous-diffusif. Nous développons également un algorithme pour détecter les ruptures de mouvement le long d’une trajectoire. Nous définissons les temps de rupture comme les instants où la particule change de régime de diffusion (brownien, sous-diffusif ou super-diffusif). Enfin, nous associons une méthode de regroupement avec notre procédure de test pour identifier les micro domaines dans lesquels des particules sont confinées. De telles zones correspondent à des lieux d’interactions moléculaires dans la cellule. / In this thesis, we are interested in quantifying the dynamics of intracellular particles, as proteins or molecules, inside living cells. In fact, inference on the modes of mobility of molecules is central in cell biology since it reflects the interactions between the structures of the cell. We model the particle trajectories with stochastic processes as the interior of a living cell is a fluctuating environment. Diffusions are stochastic processes with continuous paths and can model a large range of intracellular movements. Biophysicists distinguish three main types of diffusions, namely Brownian motion, superdiffusion and subdiffusion. These different diffusion processes correspond to distinct biological scenarios. A particle evolving freely inside the cytosol or along the plasma membrane is modelled by Brownian motion; the particle does not travel along any particular direction and can take a very long time to go to a precise area in the cell. Active intracellular transport can overcome this difficulty so that motion is faster and direct specific. In this case, particles are carried by molecular motors along microtubular filament networks and their motion is modelled with superdiffusions. Subdiffusion can be observed in two cases i/ when the particle is confined in a microdomain, ii/ when the particle is hindered by molecular crowding and encounters dynamic or fixed obstacles. We develop a statistical test for classifying the observed trajectories into the three groups of diffusion of interest namely Brownian motion, super-diffusion and subdiffusion. We also design an algorithm to detect the changes of dynamics along a single trajectory. We define the change points as the times at which the particle switches from one diffusion type (Brownian motion, superdiffusion or subdiffusion) to another. Finally, we combine a clustering algorithm with our test procedure to identify micro domains that is zones where the particles are confined. Molecular interactions of great importance for the functioning of the cell take place in such areas.