2,545 research outputs found
Controlling instabilities along a 3DVar analysis cycle by assimilating in the unstable subspace: a comparison with the EnKF
A hybrid scheme obtained by combining 3DVar with the Assimilation in the
Unstable Subspace (3DVar-AUS) is tested in a QG model, under perfect model
conditions, with a fixed observational network, with and without observational
noise. The AUS scheme, originally formulated to assimilate adaptive
observations, is used here to assimilate the fixed observations that are found
in the region of local maxima of BDAS vectors (Bred vectors subject to
assimilation), while the remaining observations are assimilated by 3DVar.
The performance of the hybrid scheme is compared with that of 3DVar and of an
EnKF. The improvement gained by 3DVar-AUS and the EnKF with respect to 3DVar
alone is similar in the present model and observational configuration, while
3DVar-AUS outperforms the EnKF during the forecast stage. The 3DVar-AUS
algorithm is easy to implement and the results obtained in the idealized
conditions of this study encourage further investigation toward an
implementation in more realistic contexts
Detecting unstable structures and controlling error growth by assimilation of standard and adaptive observations in a primitive equation ocean model
International audienceOceanic and atmospheric prediction is based on cyclic analysis-forecast systems that assimilate new observations as they become available. In such observationally forced systems, errors amplify depending on their components along the unstable directions; these can be estimated by Breeding on the Data Assimilation System (BDAS). Assimilation in the Unstable Subspace (AUS) uses the available observations to estimate the amplitude of the unstable structures (computed by BDAS), present in the forecast error field, in order to eliminate them and to control the error growth. For this purpose, it is crucial that the observational network can detect the unstable structures that are active in the system. These concepts are demonstrated here by twin experiments with a large state dimension, primitive equation ocean model and an observational network having a fixed and an adaptive component. The latter consists of observations taken each time at different locations, chosen to target the estimated instabilities, whose positions and features depend on the dynamical characteristics of the flow. The adaptive placement and the dynamically consistent assimilation of observations (both relying upon the estimate of the unstable directions of the data-forced system), allow to obtain a remarkable reduction of errors with respect to a non-adaptive setting. The space distribution of the positions chosen for the observations allows to characterize the evolution of instabilities, from deep layers in western boundary current regions, to near-surface layers in the eastward jet area
Researching protest on Facebook: developing an ethical stance for the study of Northern Irish flag protest pages
This paper adds to the emergent literature on Internet research ethics by exploring the ethical implications of researching the use of Facebook to organize the union flag protests in Northern Ireland in January 2013. These protests were viewed as a âlightning rodâ for loyalist dissatisfaction with the peace process, as well as a manifestation of their increasing alienation from their unionist political representatives. The covert observation of the Loyalist Peaceful Protest Updater (LPPU) page in January 2013 found some evidence to support the suggestion that social media had become a âsectarian battlegroundâ during the flag protests. This created an ethical dilemma in terms of what level of anonymity should be afforded to those who posted such content on the page. While there was no requirement to âpleaseâ unaware participants, the researcher was wary of inadvertently contributing to the online shaming of loyalists by groups such as Loyalists Against Democracy. Therefore, it was decided to only use direct quotes from public figures, such as the leaders of the flag protest movement, who would presumably have no expectation that their comments would remain private. The narratives of the ârank and fileâ protesters were conveyed through the use of direct quotes that could not be traced back to their authors and the paraphrasing of their comments. In light of the limitations of alternative strategies such as fabrication and word clouds, this was the most appropriate way to illustrate the themes from the LPPU without distorting the voices of these users
Intensificação da coloração da epiderme de pĂȘssegos cv. Eldorado, em função do uso de cobertura plĂĄstica no solo.
bitstream/item/31610/1/comunicado83.pd
Recommended from our members
Developing a dynamically based assimilation method for targeted and standard observations
International audienceIn a recent study, a new method for assimilating observations has been proposed and applied to a small size nonlinear model. The assimilation is obtained by confining the analysis increment in the unstable subspace of the Observation-Analysis-Forecast (OAF) cycle system, in order to systematically eliminate the dynamically unstable components, present in the forecast error, which are responsible for error growth. Based on the same ideas, applications to more complex models and different, standard and adaptive, observation networks are in progress. Observing System Simulation Experiments (OSSE), performed with an atmospheric quasi-geostrophic model, with a restricted "land" area where vertical profiles are systematically observed, and a wider "ocean" area where a single supplementary observation is taken at each analysis time, are reviewed. The adaptive observation is assimilated either with the proposed method or, for comparison, with a 3-D VAR scheme. The performance of the dynamic assimilation is very good: a reduction of the error of almost an order of magnitude is obtained in the data void region. The same method is applied to a primitive equation ocean model, where "satellite altimetry" observations are assimilated. In this standard observational configuration, preliminary results show a less spectacular but significant improvement obtained by the introduction of the dynamical assimilation
Estimating the Volume of Unknown Inclusions in an Electrically Conducting Body with Voltage Measurements
We propose a novel technique to estimate the total volume of unknown insulating inclusions in an electrically conducting body from voltage measurements. Unlike conventional Electrical Impedance Tomography (EIT) systems that usually exhibit low spatial resolution and accuracy, the proposed device is composed of a pair of driving electrodes which, supplied with a known sinusoidal voltage, create a current density field inside a region of interest. The electrodes are designed to generate a current density field in the region of interest that is uniform, to a good approximation, when the inclusions are not present. A set of electrodes with a polygonal geometry is used for four-wires resistance measurements. The proposed technique has been tested designing a low cost prototype, where all electrodes are on the bottom of the conducting body, showing good performances. Such a device may be used to monitor the volume of biological cells inside cell culture dishes or the volume of blood clots in micro-channels in lab-on-a-chip biosensor
Clinical Features of SARS-CoV-2 Infection in Older Adults
The COVID-19 clinical presentation is extremely heterogenous and, in older people, it is influenced not simply by chronologic age but also by common geriatric syndromes, such as multimorbidity, motor disability, and frailty. Consequently, although typical respiratory symptoms remain the most frequent clinical presentation of COVID-19 in all age classes, in older patients, atypical symptoms (including but not limited to delirium and hyporexia) are more common than in middle-aged adults and have been associated with adverse outcomes. Moreover, some studies described the tendency of COVID-19 presenting symptoms to aggregate in clusters, and this approach seems to better capture the complexity of COVID-19 disease. The prognostic value of COVID-19 symptom clusters, however, is currently poorly investigated, especially in the older population
On the Approximability of Digraph Ordering
Given an n-vertex digraph D = (V, A) the Max-k-Ordering problem is to compute
a labeling maximizing the number of forward edges, i.e.
edges (u,v) such that (u) < (v). For different values of k, this
reduces to Maximum Acyclic Subgraph (k=n), and Max-Dicut (k=2). This work
studies the approximability of Max-k-Ordering and its generalizations,
motivated by their applications to job scheduling with soft precedence
constraints. We give an LP rounding based 2-approximation algorithm for
Max-k-Ordering for any k={2,..., n}, improving on the known
2k/(k-1)-approximation obtained via random assignment. The tightness of this
rounding is shown by proving that for any k={2,..., n} and constant
, Max-k-Ordering has an LP integrality gap of 2 -
for rounds of the
Sherali-Adams hierarchy.
A further generalization of Max-k-Ordering is the restricted maximum acyclic
subgraph problem or RMAS, where each vertex v has a finite set of allowable
labels . We prove an LP rounding based
approximation for it, improving on the
approximation recently given by Grandoni et al.
(Information Processing Letters, Vol. 115(2), Pages 182-185, 2015). In fact,
our approximation algorithm also works for a general version where the
objective counts the edges which go forward by at least a positive offset
specific to each edge.
The minimization formulation of digraph ordering is DAG edge deletion or
DED(k), which requires deleting the minimum number of edges from an n-vertex
directed acyclic graph (DAG) to remove all paths of length k. We show that
both, the LP relaxation and a local ratio approach for DED(k) yield
k-approximation for any .Comment: 21 pages, Conference version to appear in ESA 201
- âŠ