962 resultados para assimilation window
Memory-Based Attentional Guidance: A Window to the Relationship between Working Memory and Attention
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Attention, the cognitive means by which we prioritize the processing of a subset of information, is necessary for operating efficiently and effectively in the world. Thus, a critical theoretical question is how information is selected. In the visual domain, working memory (WM)—which refers to the short-term maintenance and manipulation of information that is no longer accessible by the senses—has been highlighted as an important determinant of what is selected by visual attention. Furthermore, although WM and attention have traditionally been conceived as separate cognitive constructs, an abundance of behavioral and neural evidence indicates that these two domains are in fact intertwined and overlapping. The aim of this dissertation is to better understand the nature of WM and attention, primarily through the phenomenon of memory-based attentional guidance, whereby the active maintenance of items in visual WM reliably biases the deployment of attention to memory-matching items in the visual environment. The research presented here employs a combination of behavioral, functional imaging, and computational modeling techniques that address: (1) WM guidance effects with respect to the traditional dichotomy of top-down versus bottom-up attentional control; (2) under what circumstances the contents of WM impact visual attention; and (3) the broader hypothesis of a predictive and competitive interaction between WM and attention. Collectively, these empirical findings reveal the importance of WM as a distinct factor in attentional control and support current models of multiple-state WM, which may have broader implications for how we select and maintain information.
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In this paper, we will demonstrate the possibility of opening a new telecommunications transmission window around the 2 μm wavelength, in order to exploit the potential low loss of hollow-core photonic bandgap fibers, with the benefits of significantly lower non-linearity and latency. We will show recent efforts developing a dense wavelength division multiplexing testbed at this waveband, with 100 GHz spacing wavelength channels and 105 Gbit/s total capacity achieved.
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Iron stable isotope signatures (d56Fe) in hemolymph (bivalve blood) of the Antarctic bivalve Laternula elliptica were analyzed by Multiple Collector-Inductively Coupled Plasma-Mass Spectrometry (MC-ICP-MS) to test whether the isotopic fingerprint can be tracked back to the predominant sources of the assimilated Fe. An earlier investigation of Fe concentrations in L. elliptica hemolymph suggested that an assimilation of reactive and bioavailable Fe (oxyhydr)oxide particles (i.e. ferrihydrite), precipitated from pore water Fe around the benthic boundary, is responsible for the high Fe concentration in L. elliptica (Poigner et al., 2013, doi:10.1016/j.ecss.2013.10.027). At two stations in Potter Cove (King George Island, Antarctica) bivalve hemolymph showed mean d56Fe values of -1.19 ± 0.34 per mil and -1.04 ± 0.39 per mil, respectively, which is between 0.5 per mil and 0.85 per mil lighter than the pool of easily reducible Fe (oxyhydr)oxides of the surface sediments (-0.3 per mil to -0.6 per mil). This is in agreement with the enrichment of lighter Fe isotopes at higher trophic levels, resulting from the preferential assimilation of light isotopes from nutrition. Nevertheless, d56Fe hemolymph values from both stations showed a high variability, ranging between -0.21 per mil (value close to unaltered/primary Fe(oxyhydr)oxide minerals) and -1.91 per mil (typical for pore water Fe or diagenetic Fe precipitates), which we interpret as a "mixed" d56Fe signature caused by Fe assimilation from different sources with varying Fe contents and d56Fe values. Furthermore, mass dependent Fe fractionation related to physiological processes within the bivalve cannot be ruled out. This is the first study addressing the potential of Fe isotopes for tracing back food sources of bivalves.
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In the study, we establish centennial records of anthropogenic lead pollution at different locations in the North Atlantic (Iceland, USA, and Europe) by means of lead deposited in shells of the long-lived bivalve Arctica islandica. Due to local oceanographic and geological conditions we conclude that the lead concentrations in the Icelandic shell reflect natural influxes of lead into Icelandic waters. In comparison, the lead profile of the US shell is clearly driven by anthropogenic lead emissions transported from the continent to the ocean by westerly surface winds. Lead concentrations in the European North Sea shell, in contrast, are dominantly driven by local lead sources resulting in a much less conspicuous 1970s gasoline lead peak. In conclusion, the lead profiles of the three shells are driven by different influxes of lead, and yet, all support the applicability of Pb/Ca analyses of A. islandica shells to reconstruct location specific anthropogenic lead pollution.
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This paper highlights for the first time a full comprehension of the deformation procedure during the injection stretch blow moulding (ISBM) process of poly(ethylene terephthalate) (PET) containers, namely thin-walled rigid bottles. The processes required to form PET bottles are complicated and extensive; any development in understanding the nature of material deformation can potentially improve the bottle optimisation process. Removing the bottle mould and performing free-stretch-blow (FSB) experiments revealed insight into the bottle forming characteristics at various preform temperatures and blowing rates. Process outputs cavity pressure and stretch-rod force were recorded using at instrumented stretch-rod and preform surface strain mapping was determined using a combination of a unique patterning procedure and high speed stereoscopic digital image correlation. The unprecedented experimental analysis reveals that the deformation behaviour varies considerably with contrasting process input parameters. Investigation into the effect on deformation mode, strain rate and final bottle shape provide a basis for full understanding of the process optimisation and therefore how the process inputs may aid development of the preferred optimised container.
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Injection stretch blow moulding is a well-established method of forming thin-walled containers and has been extensively researched for numerous years. This paper is concerned with validating the finite element analysis of the free-stretch-blow process in an effort to progress the development of injection stretch blow moulding of poly(ethylene terephthalate). Extensive data was obtained experimentally over a wide process window accounting for material temperature and air flow rate, while capturing cavity pressure, stretch-rod reaction force and preform surface strain. This data was then used to assess the accuracy of the correlating FE simulation constructed using ABAQUS/Explicit solver and an appropriate viscoelastic material subroutine. Results reveal that the simulation is able to give good quantitative correlation for conditions where the deformation was predominantly equal biaxial whilst qualitative correlation was achievable when the mode of deformation was predominantly sequential biaxial. Overall the simulation was able to pick up the general trends of how the pressure, reaction force, strain rate and strain vary with the variation in preform temperature and air flow rate. The knowledge gained from these analyses provides insight into the mechanisms of bottle formation, subsequently improving the blow moulding simulation and allowing for reduction in future development costs.
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The androgen receptor (AR) is expressed in 60-80% of breast cancers (BC) across all molecular phenotypes, with a higher incidence in oestrogen receptor positive (ER+) BC compared to ER negative tumours. In ER+ disease, AR-expression has been linked to endocrine resistance which might be reversed with combined treatment targeting ER and AR. In triple negative BCs (TNBC), preclinical and clinical investigations have described a subset of patients that express the AR and are sensitive to androgen blockade, providing a novel therapeutic target. Enzalutamide, a potent 2nd generation anti-androgen, has demonstrated substantial preclinical and clinical anti-tumour activity in AR+ breast cancer. Short-term preoperative window of opportunity studies are a validated strategy for novel treatments to provide proof-of-concept and define the most appropriate patient population by directly assessing treatment effects in tumour tissue before and after treatment. The ARB study aims to assess the anti-tumour effects of enzalutamide in early ER+ breast cancer and TNBC, to identify the optimal target population for further studies and to directly explore the biologic effects of enzalutamide on BC and stromal cells. Methods: ARB is an international, investigator sponsored WOO phase II study in women with newly diagnosed primary ER+ BC or AR+ TNBC of ≥ 1cm. The study has two cohorts. In the ER+ cohort, postmenopausal patients will be randomised 2:1 to receive either enzalutamide (160mg OD) plus exemestane (50mg OD) or exemestane (25mg OD). In the TNBC cohort, AR+ will receive single agent treatment with enzalutamide (160mg OD). Study treatment is planned for 15–29 days, followed by surgery or neo-adjuvant therapy. Tissue and blood samples are collected before treatment and on the last day of study treatment. The primary endpoint is inhibition of tumour-cell proliferation, as measured by change in Ki67 expression, determined centrally by 2 investigators. Secondary endpoints include induction of apoptosis (Caspase3), circulating hormone levels and safety. ARB aims to recruit ≈235 patients from ≈40 sites in the UK, Germany, Spain and USA. The study is open to recruitment.
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We explore the impact of “game changers” on the dynamics of innovation over time in three problem domains, that of wilderness protection, women’s rights, and assimilation of indigenous children in Canada. Taking a specifically historical and cross-scale approach, we look at one social innovation in each problem domain. We explore the origins and history of the development of the National Parks in the USA, the legalization of contraception in the USA and Canada, and the residential school system in Canada. Based on a comparison of these cases, we identify three kinds of game changers, those that catalyze social innovation, which we define as “seminal,” those that disrupt the continuity of social innovation, which we label exogenous shocks, and those that provide opportunities for novel combinations and recombinations, which we label as endogamous game changers.
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Virtual Team Teaching (VTT) is a form of collaborative teaching and learning at the college level that involves two teachers with their respective classes working together in real time from two distant classrooms. This paper looks at collaboration that occurs during VTT practice in order to examine factors that support and inhibit collaboration. It is aimed at teachers, administrators, technical support, and pedagogical advisors concerned with collaborative practices at the college level. What kind of affordances does Virtual Team Teaching provide for teachers and students in terms of collaboration? 1) How do teachers collaborate to build the activities and content for a VTT session? 2) What are some of the outcomes of this collaboration between these teachers? 3) How do students collaborate across the two classrooms? 4) What are some outcomes of this collaboration between students? And 5) Does the teachers’ collaborative effort impact the students’ collaboration, and vice versa?
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One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.
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Observing system experiments (OSEs) are carried out over a 1-year period to quantify the impact of Argo observations on the Mercator Ocean 0.25° global ocean analysis and forecasting system. The reference simulation assimilates sea surface temperature (SST), SSALTO/DUACS (Segment Sol multi-missions dALTimetrie, d'orbitographie et de localisation précise/Data unification and Altimeter combination system) altimeter data and Argo and other in situ observations from the Coriolis data center. Two other simulations are carried out where all Argo and half of the Argo data are withheld. Assimilating Argo observations has a significant impact on analyzed and forecast temperature and salinity fields at different depths. Without Argo data assimilation, large errors occur in analyzed fields as estimated from the differences when compared with in situ observations. For example, in the 0–300 m layer RMS (root mean square) differences between analyzed fields and observations reach 0.25 psu and 1.25 °C in the western boundary currents and 0.1 psu and 0.75 °C in the open ocean. The impact of the Argo data in reducing observation–model forecast differences is also significant from the surface down to a depth of 2000 m. Differences between in situ observations and forecast fields are thus reduced by 20 % in the upper layers and by up to 40 % at a depth of 2000 m when Argo data are assimilated. At depth, the most impacted regions in the global ocean are the Mediterranean outflow, the Gulf Stream region and the Labrador Sea. A significant degradation can be observed when only half of the data are assimilated. Therefore, Argo observations matter to constrain the model solution, even for an eddy-permitting model configuration. The impact of the Argo floats' data assimilation on other model variables is briefly assessed: the improvement of the fit to Argo profiles do not lead globally to unphysical corrections on the sea surface temperature and sea surface height. The main conclusion is that the performance of the Mercator Ocean 0.25° global data assimilation system is heavily dependent on the availability of Argo data.
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