A modified finescale parameterization for turbulent mixing in the western equatorial Pacific

Finescale parameterizations are of great importance to explore the turbulent mixing in the open ocean due to the difficulty of microstructure measurements. Studies based on finescale parameterizations have greatly aided our knowledge of the turbulent mixing in the open ocean. In this study, we introduce a modified finescale parameterization (MMG) based on shear/strain variance ratio Rω and compare it with three existing parameterizations, namely the MacKinnon–Gregg (MG) parameterization, the Gregg–Henyey–Polzin (GHP) parameterization based on shear and strain variances, and the GHP parameterization based on strain variance. The result indicates that the prediction of MG parameterization is the best, followed by the MMG parameterization, then the shear&strain-based GHP parameterization, and finally the strain-based GHP parameterization. The strain-based GHP parameterization is less effective than the shear&strain-based GHP parameterization, which is mainly due to its excessive dependence on stratification. The predictions of the strain-based MMG parameterization can be comparable to that of the MG parameterization and better than that of the shear&strain-based GHP parameterization. Most importantly, MMG parameterization is even effective over rough topography where the GHP parameterization fails. This modified MMG parameterization with prescribed Rω can be applied to extensive CTD data. It would be a useful tool for researchers to explore the turbulent mixing in the open ocean.

Characterization of Viscoelastic Behavior of Ripe Deseeded Tamarind Subjected to Uniaxial Compressive Loading

The creep behavior a rheological property of tamarind (Tamarandus indica L.) was studied to characterize the effect of compressive stress and time on volumetric reduction in ripe deseeded tamarind and creep curve developed using Kelvin model. Five different compressive stresses 222.95, 445.90, 668.86, 891.81 and 1114.77 N/m2 were used and deformation was observed at different time intervals 0+, 5, 10, 20, 30, 45, 60, 90, 120, 180, 240, 300 and 360 minutes. Creep curve were plotted to demonstrate the volumetric strain variance for various time intervals. The slope of curve is sharp at the beginning and then with the increase in duration of loading the slope of curve flattened down which shows that the rate of change of volumetric strain for a given sample at a given stress is large at the beginning and with increase in the time, the rate of change becomes less and less. The volumetric strain with respect to variation of loading is maximum in case of maximum stress that was 1114.77 N/m2.

Autometa: Automated extraction of microbial genomes from individual shotgun metagenomes

MotivationShotgun metagenomics is a powerful, high-resolution technique enabling the study of microbial communities in situ. However, species-level resolution is only achieved after a process of “binning” where contigs predicted to originate from the same genome are clustered. Such culture-independent sequencing frequently unearths novel microbes, and so various methods have been devised for reference-free binning. Existing methods, however, suffer from: (1) reliance on human pattern recognition, which is inherently unscalable; (2) requirement for multiple co-assembled metagenomes, which degrades assembly quality due to strain variance; and (3) assumption of prior host genome removal not feasible for non-model hosts. We therefore devised a fully-automated pipeline, termed “Autometa,” to address these issues. Results: Autometa implements a method for taxonomic partitioning of contigs based on predicted protein homology, and this was shown to vastly improve binning in host-associated and complex metagenomes. Autometa’s method of automated clustering, based on Barnes-Hut Stochastic Neighbor Embedding (BH-tSNE) and DBSCAN, was shown to be highly scalable, outperforming other binning pipelines in complex simulated datasets.Availability and implementationAutometa is freely available at https://bitbucket.org/jasonckwan/autometa and as a docker image at https://hub.docker.com/r/jasonkwan/autometa under the GNU Affero General Public License 3 (AGPL 3)[email protected] informationSupplementary data are available attached to this article at https://biorxiv.org

Adaptive mesh refinement for elastic modulus reconstruction in elastography

Meshes play a crucial role in determining the accuracy of the elastic modulus reconstruction in the elastography when the finite element method is employed. In this article, we propose an adaptive mesh refinement strategy which can ensure the coincidence of the meshes with the shape of the inclusions in the observed tissue. This strategy is based on the intensity distribution of the strain image where the variance of the strain distribution in each element of the meshes is used to measure the homogeneity of the element, that is, the larger the strain variance is the more inhomogeneous the element will be and hence more detailed information will be included in this element. For more accurate reconstruction of such detailed information, mesh refinement procedure is implemented in such elements. Besides, two refinement steps are employed for the reconstruction to improve the fitness of the reconstructed image and the observed tissue. Simulation results show that the two-stage adaptive mesh refinement algorithm performs well without needing any prior information about the internal geometric shape in tissue. Not only Young’s moduli of models but also shapes of the inclusions can be reconstructed perfectly and quickly with our proposed method.

Energy Exchange between the Mesoscale Oceanic Eddies and Wind-Forced Near-Inertial Oscillations

In this study, the energy exchange between mesoscale eddies and wind-forced near-inertial oscillations (NIOs) is theoretically analyzed using a slab mixed layer model modified by including the geostrophic flow. In the presence of strain, there is a permanent energy transfer from mesoscale eddies to NIOs forced by isotropic wind stress. The energy transfer efficiency, that is, the ratio of the energy transfer rate to the near-inertial wind work, is proportional to , where S2 is the total strain variance, is the effective Coriolis frequency, and ζ is the relative vorticity. The theories derived from the modified slab mixed layer model are verified by the realistic numerical simulation obtained from a coupled regional climate model (CRCM) configured over the North Pacific. Pronounced energy transfer from mesoscale eddies to wind-forced NIOs is localized in the Kuroshio Extension region associated with both strong near-inertial wind work and strain variance. The energy transfer efficiency in anticyclonic eddies is about twice the value in cyclonic eddies in the Kuroshio Extension region because of the influence of ζ on feff, which may contribute to shaping the dominance of cyclonic eddies than anticyclonic eddies in that region.

The Impact of Observed Variations in the Shear-to-Strain Ratio of Internal Waves on Inferred Turbulent Diffusivities

The most comprehensive studies of the spatial and temporal scales of diffusivity rely on internal wave parameterizations that require knowledge of finescale shear and strain. Studies lacking either shear or strain measurements have to assume a constant ratio between shear and strain (Rω). Data from 14 moorings collected during five field programs are examined to determine the spatial and temporal patterns in Rω and the influence of these patterns on parameterized diffusivity. Time-mean Rω ranges from 1 to 10, with changes of order 10 observed over a broad range of scales. Temporal variability in Rω is observed at daily, weekly, and monthly scales. Observed changes in Rω could produce a 2–3 times change in parameterized diffusivity. Vertical profiles of Rω, Eshear, and Estrain (shear or strain variance relative to Garret–Munk) reveal that both local topographic properties and wind variability impact the internal wave field. Time series of Rω from each mooring have strong correlations to either shear or strain, often only at a specific range of vertical wavenumbers. Sites fall into two categories, in which Rω variability is dominated by either shear or strain. Linear fits to the dominant property (i.e., shear or strain) can be used to estimate a time series of Rω that has an RMS error that is 30% less than the RMS error from assuming Rω = 3. Shear and strain level vary in concert, as predicted by the Garret–Munk model, at high Eshear values. However, at Eshear < 5, strain variations are 3 times weaker than shear.