Cross-species amplification of Clupeidae microsatellite DNA markers in common kilka, Clupeonella cultriventris from the Caspian Sea

Common kilka Clupeonella cultriventris (Nordmann, 1840) is a brackish water and small pelagic fish species and is one of the most abundant fishes that live gregariously in the Caspian Sea. A total of 60 specimens of adult common kilka were sampled from two seasons. Fifteen pairs of microsatellites previously developed for A. sapidissima, C. pallasi, C. harengus, and S. pilchardus were tested for cross-species amplification on the common kilka. In this study, only five primer pairs were used successfully. Analyses revealed that the average of alleles per locus was 14.4. The average observed and expected heterozygosity was 0.153 and 0.888, respectively. All loci significantly deviated from H–W equilibrium. These results together with significant Rst. values for genotypic differences support the existence of different genetic populations along the Caspian Sea coast (Guilan Province)

New hybrid CPU-GPU solver for CFD-DEM simulation of fluidized bed

Modeling is an alternative to experiment to explore more in multiphase flows. Various modeling approaches have been developed and used from 1D models in the macro-scale to multidimensional models in the micro scale. Well-known modeling approaches for fluidization systems are TFM and CFD-DEM, both have found many practical applications in fluidization systems. The TFM considers both fluid and particulate phase as interpenetrating continua. In contrast, the CFD-DEM considers the fluid as a continuous fluid in the meso-scale (cell-scale) and the solid as discrete particles in the micro-scale. The translational and rotational motions of individual particles are described by applying Newton’s and Euler’s second laws of motion, respectively. Since the first introduction of CFD-DEM technique by Tsuji et al. (1) and Hoomans et al. (2), different aspects of this modeling approach have been being enhanced and developed. Nowadays, this modeling approach has found many applications in different engineering fields specially fluidization (3). One of the main limitations of this modeling approach is its high computational demand which makes the parallelization necessary in order to model larger systems with more details. A CFD-DEM code comprises of three computational parts: CFD, DEM and coupling. The CFD part can be efficiently parallelized using space decomposition method on the distributed-memory platform like MPI, while the DEM part, due to its low granularity, is better to be parallelized using loop-level parallelization on the shared-memory platform like CUDA. We used a combination of both platforms to speed-up the CFD-DEM code. Figure 1 shows the data transfer between different parts of the code and the platforms that are used for their implementation. As it can be seen, the CFD and coupling parts are parallelized using MPI and executed on multiple CPUs and the DEM part is parallelized using CUDA and executed on a GPU. To solve the Navier-Stokes equations, we used the open-source CFD package, OpenFOAM®, while the code for coupling and DEM calculations were developed internally. The main goal of this programing style was to benefit from the maximum computational power of CPU and GPU in a single PC equipped with a CUDA-capable GPU. This code was successfully utilized for a fluidization system containing 100,000 spherical particles with the mean size of 2200 micrometers and density of 1500 kg/m3. Particles were placed in a cylinder with inner diameter of 0.14 m and height of 1 m. Number of fluid cells in the simulation was 7,400. The superficial gas velocity was 2 m/s. The code was executed on one CPU core of an Intel® core™-i7 processor (3.6 GHz) and an NVIDIA GeForce® GTX 660 Ti GPU. The simulation was continued for 1 second and the execution time was about 1.5 hr. Snapshots of this simulation are shown in Figure 2. These snapshots show the contour of gas velocity field and particles which are colored based on their velocity. This code is in its very first stages of developments and needs optimizations in both coupling and DEM parts to gain more execution speed. Please click Additional Files below to see the full abstract

Effects of viscous dissipation on miscible thermo-viscous fingering instability in porous media

The thermo-viscous fingering instability associated with miscible displacement through a porous medium is studied numerically, motivated by applications in upstream oil industries especially enhanced oil recovery (EOR) via wells using hot water flooding and steam flooding. The main innovative aspect of this study is the inclusion of the effects of viscous dissipation on thermal viscous fingering instability. An Arrhenius equation of state is employed for describing the dependency of viscosity on temperature. The normalized conservation equations are solved with the finite element computational fluid dynamics code, COMSOL (Version 5) in which glycerol is considered as the solute and water as the solvent and the two-phase Darcy model employed (which couples the study Darcy flow equation with the time-dependent convection-diffusion equation for the concentration). The progress of finger patterns is studied using concentration and temperature contours, transversely averaged profiles, mixing length and sweep efficiency. The sweep efficiency is a property widely used in industry to characterize how effective is displacement and it can be defined as the ratio of the volume of displaced fluid to the total volume of available fluid in a porous medium in the displacement process. The effects of Lewis number, Brinkman number and thermal lag coefficient on this instability are examined in detail. The results indicate that increasing viscous dissipation generates significant enhancement in the temperature and a marked reduction in viscosity especially in the displaced fluid (high viscous phase). Therefore, the mobility ratio is reduced, and the flow becomes more stable in the presence of viscous dissipation

A novel phenomenological model for dynamic behavior of magnetorheological elastomers in tension-compression mode

Tension-compression operation in MR elastomers (MREs) offers both the most compact design and superior stiffness in many vertical load-bearing applications, such as MRE bearing isolators in bridges and buildings, suspension systems and engine mounts in cars, and vibration control equipment. It suffers, however, from lack of good computational models to predict device performance, and as a result shear-mode MREs are widely used in the industry, despite their low stiffness and load-bearing capacity. We start with a comprehensive review of modeling of MREs and their dynamic characteristics, showing previous studies have mostly focused on dynamic behavior of MREs in shear mode, though the MRE strength and MR effect are greatly decreased at high strain amplitudes, due to increasing distance between the magnetic particles. Moreover, the characteristic parameters of the current models assume either frequency, or strain, or magnetic field are constant; hence, new model parameters must be recalculated for new loading conditions. This is an experimentally time consuming and computationally expensive task, and no models capture the full dynamic behavior of the MREs at all loading conditions. In this study, we present an experimental setup to test MREs in a coupled tension-compression mode, as well as a novel phenomenological model which fully predicts the stress-strain material behavior as a function of magnetic flux density, loading frequency and strain. We use a training set of experiments to find the experimentally derived model parameters, from which can predict by interpolation the MRE behavior in a relatively large continuous range of frequency, strain and magnetic field. We also challenge the model to make extrapolating predictions and compare to additional experiments outside the training experimental data set with good agreement. Further development of this model would allow design and control of engineering structures equipped with tension-compression MREs and all the advantages they offer.We acknowledge funding from the European Research Council grant EMATTER 280078

A convergent strategy for the pamamycin macrodiolides:Total synthesis of pamamycin-607, pamamycin-593, and pamamycin-621D precursors

International audienc

Comparing Probabilistic Models for Melodic Sequences

Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music features, such as underlying chords and typical melody transitions and dynamics. We assess the models for future prediction and compare their performance to a VMM, which is the current state of the art in melody generation. We show that both models perform significantly better than the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of the music genre significantly better than the VMM.Comment: in Proceedings of the ECML-PKDD 2011. Lecture Notes in Computer Science, vol. 6913, pp. 289-304. Springer (2011

The sensitivity of land emissivity estimates from AMSR-E at C and X bands to surface properties

Microwave observations at low frequencies exhibit more sensitivity to surface and subsurface properties with little interference from the atmosphere. The objective of this study is to develop a global land emissivity product using passive microwave observations from the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) and to investigate its sensitivity to land surface properties. The developed product complements existing land emissivity products from SSM/I and AMSU by adding land emissivity estimates at two lower frequencies, 6.9 and 10.65 GHz (C- and X-band, respectively). Observations at these low frequencies penetrate deeper into the soil layer. Ancillary data used in the analysis, such as surface skin temperature and cloud mask, are obtained from International Satellite Cloud Climatology Project (ISCCP). Atmospheric properties are obtained from the TIROS Operational Vertical Sounder (TOVS) observations to determine the small upwelling and downwelling atmospheric emissions as well as the atmospheric transmission. A sensitivity test confirms the small effect of the atmosphere but shows that skin temperature accuracy can significantly affect emissivity estimates. Retrieved emissivities at C- and X-bands and their polarization differences exhibit similar patterns of variation with changes in land cover type, soil moisture, and vegetation density as seen at SSM/I-like frequencies (Ka and Ku bands). The emissivity maps from AMSR-E at these higher frequencies agree reasonably well with the existing SSM/I-based product. The inherent discrepancy introduced by the difference between SSM/I and AMSR-E frequencies, incidence angles, and calibration has been assessed. Significantly greater standard deviation of estimated emissivities compared to SSM/I land emissivity product was found over desert regions. Large differences between emissivity estimates from ascending and descending overpasses were found at lower frequencies due to the inconsistency between thermal IR skin temperatures and passive microwave brightness temperatures which can originate from below the surface. The mismatch between day and night AMSR-E emissivities is greater than ascending and descending differences of SSM/I emissivity. This is because of unique orbit time of AMSR-E (01:30 a.m./p.m. LT) while other microwave sensors have orbit time of 06:00 to 09:00 (a.m./p.m.). This highlights the importance of considering the penetration depth of the microwave signal and diurnal variability of the temperature in emissivity retrieval. The effect of these factors is greater for AMSR-E observations than SSM/I observations, as AMSR-E observations exhibit a greater difference between day and night measures. This issue must be addressed in future studies to improve the accuracy of the emissivity estimates especially at AMSR-E lower frequencies

Antimicrobial Electrodeposited Silver-Containing Calcium Phosphate Coatings

Biocompatible antimicrobial coatings may enhance the function of many orthopedic implants by combating infection. Hydroxyapatite is a choice mineral for such a coating as it is native to bone and silver would be a possible antimicrobial agent as it is also commonly used in biomedical applications. The aim of the research is to develop a silver-containing calcium phosphate (Ag/Ca-P) coating via electrochemical deposition on titanium substrates as this allows for controlled coating buildup on complex shapes and porous surfaces. Two different deposition approaches are explored: one-step Ag/Ca-P(1) deposition coatings, containing silver ions as microsized silver phosphate particles embedded in the Ca-P matrix; and via a two-step method (Ag/Ca-P(2)) where silver is deposited as metallic silver nanoparticle on the Ca-P coating. The Ag/Ca-P(1) coating displays a bacterial reduction of 76.1 +/- 8.3% via Ag-ion leaching. The Ag/Ca-P(2) coating displays a bacterial reduction of 83.7 +/- 4.5% via contact killing. Interestingly, by preincubation in phosphate-buffered saline solution, bacterial reduction improves to 97.6 +/- 2.7 and 99.7 +/- 0.4% for Ag/Ca-P(1) and Ag/Ca-P(2) coatings, respectively, due to leaching of formed AgClx(x-1)- species. The biocompatibility evaluation indicates that the Ag/Ca-P(1) coating is cytotoxic towards osteoblasts while the Ag/Ca-P(2) coating shows excellent compatibility. The electrochemical deposition of highly bactericidal coatings with excellent biocompatibility will enable us to coat future bone implants even with complex or porous structures