Parallel Direct Solution of the Covariance-Localized Ensemble Square Root Kalman Filter Equations with Matrix Functions

[EN] Recently, the serial approach to solving the square root ensemble Kalman filter (ESRF) equations in the presence of covariance localization was found to depend on the order of observations. As shown previously, correctly updating the localized posterior covariance in serial requires additional effort and computational expense. A recent work by Steward et al. details an all-at-once direct method to solve the ESRF equations in parallel. This method uses the eigenvectors and eigenvalues of the forward observation covariance matrix to solve the difficult portion of the ESRF equations. The remaining assimilation is easily parallelized, and the analysis does not depend on the order of observations. While this allows for long localization lengths that would render local analysis methods inefficient, in theory, an eigenpair-based method scales as the cube number of observations, making it infeasible for large numbers of observations. In this work, we extend this method to use the theory of matrix functions to avoid eigenpair computations. The Arnoldi process is used to evaluate the covariance-localized ESRF equations on the reduced-order Krylov subspace basis. This method is shown to converge quickly and apparently regains a linear scaling with the number of observations. The method scales similarly to the widely used serial approach of Anderson and Collins in wall time but not in memory usage. To improve the memory usage issue, this method potentially can be used without an explicit matrix. In addition, hybrid ensemble and climatological covariances can be incorporated.This research was partially funded by the NOAA Hurricane Forecast Improvement Project Award NA14NWS4680022. This work was partially supported by Agencia Estatal de Investigacion (AEI) under Grant TIN2016-75985-P, which includes European Commission ERDF funds. Alejandro Lamas Davina was supported by the Spanish Ministry of Education, Culture and Sport through a grant with reference FPU13-06655. The fourth author's work was in part carried out under the auspices of CIMAS, a joint institute of the University of Miami and NOAA, Cooperative Agreement NA15OAR4320064. The authors acknowledge the NOAA Research and Development High Performance Computing Program for providing computing and storage resources that have contributed to the research results reported within this paper (http://rdhpcs.noaa.gov). We thank Jeff Anderson, Shu-Chih Yang, and three anonymous reviewers for their helpful comments and contributions. We also thank Hui Christophersen for providing technical assistance.Steward, JL.; Roman, JE.; Lamas Daviña, A.; Aksoy, A. (2018). Parallel Direct Solution of the Covariance-Localized Ensemble Square Root Kalman Filter Equations with Matrix Functions. Monthly Weather Review. 146(9):2819-2836. https://doi.org/10.1175/MWR-D-18-0022.1S28192836146

Cooperative spontaneous emission in nonuniform media

The subject of this paper is modification of cooperative spontaneous emission by a nonuniform medium, with nonuniform distributions of electromagnetic field. A brief analyzis is presented and it is postulated, that if spontaneous emission from an atom is strongly suppressed, cooperative emission with another atom may be a preferred emission channel and counteract the suppression.Comment: The final publication is available at http://www.epj.or

Lensfree optofluidic plasmonic sensor for real-time and label-free monitoring of molecular binding events over a wide field-of-view

We demonstrate a high-throughput biosensing device that utilizes microfluidics based plasmonic microarrays incorporated with dual-color on-chip imaging toward real-time and label-free monitoring of biomolecular interactions over a wide field-of-view of >20 mm^2. Weighing 40 grams with 8.8 cm in height, this biosensor utilizes an opto-electronic imager chip to record the diffraction patterns of plasmonic nanoapertures embedded within microfluidic channels, enabling real-time analyte exchange. This plasmonic chip is simultaneously illuminated by two different light-emitting-diodes that are spectrally located at the right and left sides of the plasmonic resonance mode, yielding two different diffraction patterns for each nanoaperture array. Refractive index changes of the medium surrounding the near-field of the nanostructures, e.g., due to molecular binding events, induce a frequency shift in the plasmonic modes of the nanoaperture array, causing a signal enhancement in one of the diffraction patterns while suppressing the other. Based on ratiometric analysis of these diffraction images acquired at the detector-array, we demonstrate the proof-of-concept of this biosensor by monitoring in real-time biomolecular interactions of protein A/G with immunoglobulin G (IgG) antibody. For high-throughput on-chip fabrication of these biosensors, we also introduce a deep ultra-violet lithography technique to simultaneously pattern thousands of plasmonic arrays in a cost-effective manner

Field-portable optofluidic plasmonic biosensor for wide-field and label-free monitoring of molecular interactions

We demonstrate a field-portable optofluidic plasmonic sensing device, weighing 40 g and 7.5 cm in height, which merges plasmonic microarrays with dual-wavelength lensfree on-chip imaging for real-time monitoring of protein binding kinetics

Animal Models for Limbal Stem Cell Deficiency: A Critical Narrative Literature Review

\ua9 2024, The Author(s). This literature review will provide a critical narrative overview of the highlights and potential pitfalls of the reported animal models for limbal stem cell deficiency (LSCD) and will identify the neglected aspects of this research area. There exists significant heterogeneity in the literature regarding the methodology used to create the model and the predefined duration after the insult when the model is supposedly fully fit for evaluations and/or for testing various therapeutic interventions. The literature is also replete with examples wherein the implementation of a specific model varies significantly across different studies. For example, the concentration of the chemical, as well as its duration and technique of exposure in a chemically induced LSCD model, has a great impact not only on the validity of the model but also on the severity of the complications. Furthermore, while some models induce a full-blown clinical picture of total LSCD, some are hindered by their ability to yield only partial LSCD. Another aspect to consider is the nature of the damage induced by a specific method. As thermal methods cause more stromal scarring, they may be better suited for assessing the anti-fibrotic properties of a particular treatment. On the other hand, since chemical burns cause more neovascularisation, they provide the opportunity to tap into the potential treatments for anti-neovascularisation. The animal species (i.e., rats, mice, rabbits, etc.) is also a crucial factor in the validity of the model and its potential for clinical translation, with each animal having its unique set of advantages and disadvantages. This review will also elaborate on other overlooked aspects, such as the anaesthetic(s) used during experiments, the gender of the animals, care after LSCD induction, and model validation. The review will conclude by providing future perspectives and suggestions for further developments in this rather important area of research

Quantifying uncertainties of permafrost carbon–climate feedbacks

The land surface models JULES (Joint UK Land Environment Simulator, two versions) and ORCHIDEE-MICT (Organizing Carbon and Hydrology in Dynamic Ecosystems), each with a revised representation of permafrost carbon, were coupled to the Integrated Model Of Global Effects of climatic aNomalies (IMOGEN) intermediate-complexity climate and ocean carbon uptake model. IMOGEN calculates atmospheric carbon dioxide (CO2) and local monthly surface climate for a given emission scenario with the land–atmosphere CO2 flux exchange from either JULES or ORCHIDEE-MICT. These simulations include feedbacks associated with permafrost carbon changes in a warming world. Both IMOGEN–JULES and IMOGEN–ORCHIDEE-MICT were forced by historical and three alternative future-CO2-emission scenarios. Those simulations were performed for different climate sensitivities and regional climate change patterns based on 22 different Earth system models (ESMs) used for CMIP3 (phase 3 of the Coupled Model Intercomparison Project), allowing us to explore climate uncertainties in the context of permafrost carbon–climate feedbacks. Three future emission scenarios consistent with three representative concentration pathways were used: RCP2.6, RCP4.5 and RCP8.5. Paired simulations with and without frozen carbon processes were required to quantify the impact of the permafrost carbon feedback on climate change. The additional warming from the permafrost carbon feedback is between 0.2 and 12 % of the change in the global mean temperature (ΔT) by the year 2100 and 0.5 and 17 % of ΔT by 2300, with these ranges reflecting differences in land surface models, climate models and emissions pathway. As a percentage of ΔT, the permafrost carbon feedback has a greater impact on the low-emissions scenario (RCP2.6) than on the higher-emissions scenarios, suggesting that permafrost carbon should be taken into account when evaluating scenarios of heavy mitigation and stabilization. Structural differences between the land surface models (particularly the representation of the soil carbon decomposition) are found to be a larger source of uncertainties than differences in the climate response. Inertia in the permafrost carbon system means that the permafrost carbon response depends on the temporal trajectory of warming as well as the absolute amount of warming. We propose a new policy-relevant metric – the frozen carbon residence time (FCRt) in years – that can be derived from these complex land surface models and used to quantify the permafrost carbon response given any pathway of global temperature change

(E)-Methyl 3-(4-chloro­phen­yl)-2-{2-[(E)-(hy­droxy­imino)­meth­yl]phen­oxy­meth­yl}acrylate

In the title compound, C18H16ClNO4, the dihedral angle between the mean planes through the aromatic rings is 83.8 (8)°. The hy­droxy­ethanimine group is essentially coplanar with the ring to which it is attached [O—N—C—C torsion angle = −177.96 (13)°]. The mol­ecules are linked into centrosymmetric R 2 2(6) dimers via O—H⋯N hydrogen bonds. The crystal packing is further stabilized by C—H⋯O inter­actions

(E)-Methyl 2-({2-eth­oxy-6-[(E)-(hy­droxy­imino)­meth­yl]phen­oxy}meth­yl)-3-phenyl­acrylate

In the title compound, C20H21NO5, the dihedral angle between the mean planes through the two rings is 47.1 (8)°. The enoate group assumes an extended conformation. The hy­droxy­ethanimine group is essentially coplanar with the benzene ring, the largest deviation from the mean plane being 0.061 (1) Å for the O atom. In the crystal, mol­ecules are linked into cyclic centrosymmetric dimers with an R 2 2(6) motif via pairs of O—H⋯N hydrogen bonds. Inter­molecular C—H⋯O hydrogen bonds form a C(8) chain along the b axis. The crystal packing is further stabilized by C—H⋯π inter­actions