Faculty Opinions recommendation of Steady-state cross-correlations for live two-colour super-resolution localization data sets.

2015 ◽  
Author(s):  
Akihiro Kusumi
Keyword(s):  
Steady State ◽  
Super Resolution ◽  
Data Sets ◽  
Cross Correlations ◽  
Localization Data

scholarly journals Steady-state cross-correlations for live two-colour super-resolution localization data sets

2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Matthew B. Stone ◽  
Sarah L. Veatch
Keyword(s):  
Steady State ◽  
Dynamic Systems ◽  
Cross Correlation ◽  
Super Resolution ◽  
Cell Receptor ◽  
Live Cells ◽  
Data Sets ◽  
Lyn Kinase ◽  
Cross Correlations ◽  
Localization Data

Abstract Cross-correlation of super-resolution images gathered from point localizations allows for robust quantification of protein co-distributions in chemically fixed cells. Here this is extended to dynamic systems through an analysis that quantifies the steady-state cross-correlation between spectrally distinguishable probes. This methodology is used to quantify the co-distribution of several mobile membrane proteins in both vesicles and live cells, including Lyn kinase and the B-cell receptor during antigen stimulation.

Selection of one-dimensional sedimentation: models for on-line use

1995 ◽  
Vol 31 (2) ◽  
pp. 193-204 ◽  
Author(s):  
Koen Grijspeerdt ◽  
Peter Vanrolleghem ◽  
Willy Verstraete
Keyword(s):  
Steady State ◽  
Selection Criteria ◽  
Data Sets ◽  
Concentration Profiles ◽  
A Posteriori ◽  
One Dimensional ◽  
On Line ◽  
Dynamic Concentration ◽  
Selection Of ◽  
Modelling Task

A comparative study of several recently proposed one-dimensional sedimentation models has been made. This has been achieved by fitting these models to steady-state and dynamic concentration profiles obtained in a down-scaled secondary decanter. The models were evaluated with several a posteriori model selection criteria. Since the purpose of the modelling task is to do on-line simulations, the calculation time was used as one of the selection criteria. Finally, the practical identifiability of the models for the available data sets was also investigated. It could be concluded that the model of Takács et al. (1991) gave the most reliable results.

scholarly journals Optimizing galaxy samples for clustering measurements in photometric surveys

2019 ◽  
Vol 491 (3) ◽  
pp. 3535-3552 ◽  
Author(s):  
Dimitrios Tanoglidis ◽  
Chihway Chang ◽  
Joshua Frieman
Keyword(s):  
Cold Dark Matter ◽  
Sample Selection ◽  
Gaussian Model ◽  
Small Subset ◽  
Data Sets ◽  
Trade Off ◽  
Cosmological Constraints ◽  
Dark Energy Survey ◽  
Galaxy Sample ◽  
Cross Correlations

ABSTRACT When analysing galaxy clustering in multiband imaging surveys, there is a trade-off between selecting the largest galaxy samples (to minimize the shot noise) and selecting samples with the best photometric redshift (photo-z) precision, which generally includes only a small subset of galaxies. In this paper, we systematically explore this trade-off. Our analysis is targeted towards the third-year data of the Dark Energy Survey (DES), but our methods hold generally for other data sets. Using a simple Gaussian model for the redshift uncertainties, we carry out a Fisher matrix forecast for cosmological constraints from angular clustering in the redshift range z = 0.2–0.95. We quantify the cosmological constraints using a figure of merit (FoM) that measures the combined constraints on Ωm and σ8 in the context of Λ cold dark matter (ΛCDM) cosmology. We find that the trade-off between sample size and photo-z precision is sensitive to (1) whether cross-correlations between redshift bins are included or not, and (2) the ratio of the redshift bin width δz to the photo-z precision σz. When cross-correlations are included and the redshift bin width is allowed to vary, the highest FoM is achieved when δz ∼ σz. We find that for the typical case of 5−10 redshift bins, optimal results are reached when we use larger, less precise photo-z samples, provided that we include cross-correlations. For samples with higher σz, the overlap between redshift bins is larger, leading to higher cross-correlation amplitudes. This leads to the self-calibration of the photo-z parameters and therefore tighter cosmological constraints. These results can be used to help guide galaxy sample selection for clustering analysis in ongoing and future photometric surveys.

scholarly journals Sparsity Based Full Rank Polarimetric Reconstruction of Coherence Matrix T

2019 ◽  
Vol 11 (11) ◽  
pp. 1288 ◽  
Author(s):  
Hossein Aghababaee ◽  
Giampaolo Ferraioli ◽  
Laurent Ferro-Famil ◽  
Gilda Schirinzi ◽  
Yue Huang
Keyword(s):  
Super Resolution ◽  
Full Rank ◽  
Real Data ◽  
Natural Environments ◽  
Data Sets ◽  
Scattering Pattern ◽  
Component Decomposition ◽  
Resolution Imaging ◽  
Processing Techniques ◽  
Physical Features

In the frame of polarimetric synthetic aperture radar (SAR) tomography, full-ranks reconstruction framework has been recognized as a significant technique for fully characterization of superimposed scatterers in a resolution cell. The technique, mainly is characterized by the advantages of polarimetric scattering pattern reconstruction, allows physical feature extraction of the scatterers. In this paper, to overcome the limitations of conventional full-rank tomographic techniques in natural environments, a polarimetric estimator with advantages of super-resolution imaging is proposed. Under the frame of compressive sensing (CS) and sparsity based reconstruction, the profile of second order polarimetric coherence matrix T is recovered. Once the polarimetric coherence matrices of the scatterers are available, the physical features can be extracted using classical polarimetric processing techniques. The objective of this study is to evaluate the performance of the proposed full-rank polarimetric reconstruction by means of conventional three-component decomposition of T, and focusing on the consistency of vertical resolution and polarimetric scattering pattern of the scatterers. The outcomes from simulated and two different real data sets confirm that significant improvement can be achieved in the reconstruction quality with respect to conventional approaches.

scholarly journals Modelling Temperature Distribution in Alpine Glaciers

1984 ◽  
Vol 5 ◽  
pp. 18-22 ◽  
Author(s):  
Heinz Blatter ◽  
Wilfried Haeberli
Keyword(s):  
Steady State ◽  
Temperature Distribution ◽  
Swiss Alps ◽  
Ice Age ◽  
Temperature Fields ◽  
Data Sets ◽  
Mountain Glaciers ◽  
Numerical Instabilities ◽  
State Models ◽  
Glacier Flow

Modelling temperature distribution in non-temperate mountain glaciers presents problems not normally encountered when modelling ice sheets or ice shelves. These problems are mainly concerned with numerical instabilities caused by the high, nonuniform gradients of various input parameters (geometry, mass balance, surface temperature, and flow velocity). Steady-state solutions must be used to check and complete data sets, before using models of greater complexity to calculate temperature fields in a more realistic way. Test runs with a computer model, which allows for true two-dimensional solutions and realistic velocity fields, are described for two examples from the Swiss Alps. These steady-state calculations illustrate, in a semi-quantitative way, that advection of cold ice by glacier flow strongly influences the temperature distribution in both an existing large valley glacier with a cold accumulation zone (Grenzgletscher), and a large piedmont glacier of the last ice age, around 18 ka BP (Rheingletscher). Non-steady-state models are being prepared and tested for future calculations.

scholarly journals Multiple isotopic models using various kinetic fractionation coefficients to estimateδ18O of leaf water

2018 ◽  
Author(s):  
Yonge Zhang ◽  
Xinxiao Yu ◽  
Lihua Chen ◽  
Guodong Jia
Keyword(s):  
Steady State ◽  
Time Scale ◽  
Model Performance ◽  
Special Care ◽  
Leaf Water ◽  
Data Sets ◽  
Kinetic Fractionation ◽  
Improved Model ◽  
Material Exchange ◽  
Good Agreement

AbstractInvestigation ofδ18O of leaf water may improve our understanding of the evapotranspiration partitioning and material exchange between the inside and outside of leaves. In this study,δ18O of bulk leaf water (δL,b) was estimated by both isotopic–steady–state (ISS) and non–steady–state (NSS) assumptions considering the Péclet effect. Specifically, we carefully modified kinetic fractionation coefficients (αk). The results showed that the Péclet effect is required to predictδL,b. On the diel time scale, both NSS assumption + Péclet effect (NSS + P) and ISS assumption + Péclet effect (ISS + P) using modifiedαk(αk–modified) forδL,bshowed a good agreement with observedδL,b(p> 0.05). When using previously proposedαk, however, both NSS + P and ISS + P were not reliable estimators ofδL,b(p< 0.05). On a longer time scale (days), estimates of daily meanδL,bfrom ISS + P outperformed the estimates from NSS + P when using the sameαkvalues. Also, the employment ofαk–modifiedimproved model performance in predicting daily meanδL,bcompared to the use of previously proposedαk. Clearly, special care must be taken concerningαkwhen using isotopic models to estimateδL,b.HighlightFor hourly and daily mean data sets, the employment of modified kinetic fractionation coefficients significantly improved model performance forδ18O of bulk leaf water.

Gas Turbine Analytics Using Archival Data Sets

2015 ◽  
Author(s):  
Chad M. Holcomb ◽  
Robert R. Bitmead
Keyword(s):  
Steady State ◽  
System Identification ◽  
Gas Turbine ◽  
Transient Behavior ◽  
Archival Data ◽  
Data Sets ◽  
Input Output ◽  
Identification Methods ◽  
Traditional System ◽  
Subspace System Identification

Transient behavior of machinery is becoming increasingly recognized as a major factor in predicting life of components and exposing degradation or faults that are not observable from steady state measurements. The methods developed here are directed to trawling archival data records to reconstruct a sufficiently informative experiment in lieu of dedicated testing. The central novel observation is the modification to subspace system identification methods to permit their application to multiple concatenated, but non-contiguous data sets, which jointly can be sufficiently rich for identification while individual records are not. This is a break from traditional system identification, where one uses a single contiguous synchronous input-output record.

scholarly journals ShareLoc – an open platform for sharing localization microscopy data

2021 ◽  
Author(s):  
Jiachuan Bai ◽  
Wei Ouyang ◽  
Manish Kumar Singh ◽  
Christophe Leterrier ◽  
Paul Barthelemy ◽  
...  
Keyword(s):  
Single Molecule ◽  
Super Resolution ◽  
Data Sets ◽  
Localization Microscopy ◽  
Open Platform ◽  
Machine Learning Methods ◽  
Microscopy Data ◽  
Analytical Tools ◽  
Existing Data ◽  
Single Molecule Localization Microscopy

Novel insights and more powerful analytical tools can emerge from the reanalysis of existing data sets, especially via machine learning methods. Despite the widespread use of single molecule localization microscopy (SMLM) for super-resolution bioimaging, the underlying data are often not publicly accessible. We developed ShareLoc (https://shareloc.xyz), an open platform designed to enable sharing, easy visualization and reanalysis of SMLM data. We discuss its features and show how data sharing can improve the performance and robustness of SMLM image reconstruction by deep learning.

Sign in / Sign up

Export Citation Format

Share Document