Exact regularized point particle method for multi-phase flows in the two-way coupling regime

Particulate flows have been largely studied under the simplifying assumptions of one-way coupling regime where the disperse phase do not react-back on the carrier fluid. In the context of turbulent flows, many non trivial phenomena such as small scales particles clustering or preferential spatial accumulation have been explained and understood. A more complete view of multiphase flows can be gained calling into play two-way coupling effects, i.e. by accounting for the inter-phase momentum exchange between the carrier and the suspended phase, certainly relevant at increasing mass loading. In such regime, partially investigated in the past by the so-called Particle In Cell (PIC) method, much is still to be learned about the dynamics of the disperse phase and the ensuing alteration of the carrier flow. In this paper we present a new methodology rigorously designed to capture the inter-phase momentum exchange for particles smaller than the smallest hydrodynamical scale, e.g. the Kolmogorov scale in a turbulent flow. In fact, the momentum coupling mechanism exploits the unsteady Stokes flow around a small rigid sphere where the transient disturbance produced by each particle is evaluated in a closed form. The particles are described as lumped, point masses which would lead to the appearance of singularities. A rigorous regularization procedure is conceived to extract the physically relevant interactions between particles and fluid which avoids any "ah hoc" assumption. The approach is suited for high efficiency implementation on massively parallel machines since the transient disturbance produced by the particles is strongly localized in space around the actual particle position. As will be shown, hundred thousands particles can therefore be handled at an affordable computational cost as demonstrated by a preliminary application to a particle laden turbulent shear flow.Comment: Submitted to Journal of Fluid Mechanics, 56 pages, 15 figure

Integrating Learning into a BDI Agent for Environments with Changing Dynamics

We propose a framework that adds learning for improving plan selection in the popular BDI agent programming paradigm. In contrast with previous proposals, the approach given here is able to scale up well with the complexity of the agent's plan library. Technically, we develop a novel confidence measure which allows the agent to adjust its reliance on the learning dynamically, facilitating in principle infinitely many (re)learning phases. We demonstrate the benefits of the approach in an example controller for energy management

A combined genome-wide approach identifies a new potential candidate marker associated with the coat color sidedness in cattle

Coat color is one of the most important phenotypic features in livestock breeds. Cinisara is a local cattle breed generally of uniform black color which occasionally presents a particular phenotype, with animals typically display a white band along their spine, from the head to the tail, and on the ventral line (color sidedness). Therefore, this breed provides an ideal model to study the genetic components underlying phenotypic variation in coat color. A total of 63 animals, ten with sidedness phenotype and 53 with uniform black color were genotyped with Illumina Bovine 50 K. The comparison among genome-wide association study and FST analysis revealed a single nucleotide polymorphism (SNP), ARS-BFGL-NGS-55928, significantly associated with the trait. Only one gene (PLK2)was annotated near the associated SNP in a window of ±200 kb. The protein encoded by this gene is a member of the polo-like kinases, the same family of several known coat-color candidate genes. Based on the reported results, we draw the possible conclusion that the identified marker is potentially associated with the coat color sidedness in Cinisara. The local breeds with their genetic variability represent an important resource and model to study the genetic basis affecting peculiar traits. Future studies would be particularly relevant to refine these results and to better understand the genetic basis for this phenotype

Lagrangian supersaturation fluctuations at the cloud edge

Evaporation of cloud droplets accelerates when turbulence mixes dry air into the cloud, affecting droplet-size distributions in atmospheric clouds, combustion sprays, and jets of exhaled droplets. The challenge is to model local correlations between droplet numbers, sizes, and supersaturation, which determine supersaturation fluctuations along droplet paths (Lagrangian fluctuations). We derived a statistical model that accounts for these correlations. Its predictions are in quantitative agreement with results of direct numerical simulations, and it explains the key mechanisms at play.Comment: 6 pages, 3 figures, supplemental materia

Role of large-scale advection and small-scale turbulence on vertical migration of gyrotactic swimmers

In this work, we use direct-numerical-simulation-based Eulerian-Lagrangian simulations to investigate the dynamics of small gyrotactic swimmers in free-surface turbulence. We consider open-channel flow turbulence in which bottom-heavy swimmers are dispersed. Swimmers are characterized by different vertical stability, so that some realign to swim upward with a characteristic time smaller than the Kolmogorov timescale, while others possess a reorientation time longer than the Kolmogorov timescale. We cover one order of magnitude in the flow Reynolds number and two orders of magnitude in the stability number, which is a measure of bottom heaviness. We observe that large-scale advection dominates vertical motion when the stability number, scaled on the local Kolmogorov timescale of the flow, is larger than unity: This condition is associated to enhanced migration toward the surface, particularly at low Reynolds number, when swimmers can rise through surface renewal motions that originate directly from the bottom boundary turbulent bursts. Conversely, small-scale effects become more important when the Kolmogorov-based stability number is below unity: Under this condition, migration toward the surface is hindered, particularly at high Reynolds, when bottom-boundary bursts are less effective in bringing bulk fluid to the surface. In an effort to provide scaling arguments to improve predictions of models for motile microorganisms in turbulent water bodies, we demonstrate that a Kolmogorov-based stability number around unity represents a threshold beyond which swimmer capability to reach the free surface and form clusters saturates

Whole genome semiconductor based sequencing of farmed European sea bass (Dicentrarchus labrax) Mediterranean genetic stocks using a DNA pooling approach

European sea bass (Dicentrarchus labrax) is an important marine species for commercial and sport fisheries and aquaculture production. Recently, the European sea bass genome has been sequenced and assembled. This resource can open new opportunities to evaluate and monitor variability and identify variants that could contribute to the adaptation to farming conditions. In this work, two DNA pools constructed from cultivated European sea bass were sequenced using a next generation semiconductor sequencing approach based on Ion Proton sequencer. Using the first draft version of the D. labrax genome as reference, sequenced reads obtained a total of about 1.6 million of single nucleotide polymorphisms (SNPs), spread all over the chromosomes. Transition/transversion (Ti/Tv) was equal to 1.28, comparable to what was already reported in Salmon species. A pilot homozygosity analysis across the D. labrax genome using DNA pool sequence datasets indicated that this approach can identify chromosome regions with putative signatures of selection, including genes involved in ion transport and chloride channel functions, amino acid metabolism and circadian clock and related neurological systems. This is the first study that reported genome wide polymorphisms in a fish species obtained with the Ion Proton sequencer. Moreover, this study provided a methodological approach for selective sweep analysis in this species

Sedimentation of elongated non-motile prolate spheroids in homogenous isotropic turbulence

Phytoplankton are the foundation of aquatic food webs. Through photosynthesis, phytoplankton draw down CO2 at magnitudes equivalent to forests and other terrestrial plants and convert it to organic material that is then consumed by other organisms of phytoplankton in higher trophic levels. Mechanisms that affect local concentrations and velocities are of primary significance to many encounter-based processes in the plankton including prey-predator interactions, fertilization and aggregate formation. We report results from simulations of sinking phytoplankton, considered as elongated spheroids, in homogenous isotropic turbulence to answer the question of whether trajectories and velocities of sinking phytoplankton are altered by turbulence. We show in particular that settling spheroids with physical characteristics similar to those of diatoms weakly cluster and preferentially sample regions of down-welling flow, corresponding to an increase of the mean settling speed with respect to the mean settling speed in quiescent fluid. We explain how different parameters can affect the settling speed and what underlying mechanisms might be involved. Interestingly, we observe that the increase in the aspect ratio of the prolate spheroids can affect the clustering and the average settling speed of particles by two mechanisms: first is the effect of aspect ratio on the rotation rate of the particles, which saturates faster than the second mechanism of increasing drag anisotropy

Genome-wide scan for runs of homozygosity identifies potential candidate genes associated with local adaptation in Valle del Belice sheep

Background: Because very large numbers of single nucleotide polymorphisms (SNPs) are now available throughout the genome, they are particularly suitable for the detection of genomic regions where a reduction in heterozygosity has occurred and they offer new opportunities to improve the accuracy of inbreeding (F F) estimates. Runs of homozygosity (ROH) are contiguous lengths of homozygous segments of the genome where the two haplotypes inherited from the parents are identical. Here, we investigated the occurrence and distribution of ROH using a medium-dense SNP panel to characterize autozygosity in 516 Valle del Belice sheep and to identify the genomic regions with high ROH frequencies. Results: We identified 11,629 ROH and all individuals displayed at least one ROH longer than 1 Mb. The mean value of F F estimated from ROH longer than1 Mb was 0.084 \uc2\ub1 0.061. ROH that were shorter than 10 Mb predominated. The highest and lowest coverages of Ovis aries chromosomes (OAR) by ROH were on OAR24 and OAR1, respectively. The number of ROH per chromosome length displayed a specific pattern, with higher values for the first three chromosomes. Both number of ROH and length of the genome covered by ROH varied considerably between animals. Two hundred and thirty-nine SNPs were considered as candidate markers that may be under directional selection and we identified 107 potential candidate genes. Six genomic regions located on six chromosomes, corresponding to ROH islands, are presented as hotspots of autozygosity, which frequently coincided with regions of medium recombination rate. According to the KEGG database, most of these genes were involved in multiple signaling and signal transduction pathways in a wide variety of cellular and biochemical processes. A genome scan revealed the presence of ROH islands in genomic regions that harbor candidate genes for selection in response to environmental stress and which underlie local adaptation. Conclusions: These results suggest that natural selection has, at least partially, a role in shaping the genome of Valle del Belice sheep and that ROH in the ovine genome may help to detect genomic regions involved in the determinism of traits under selection

Applications of Monte Carlo methods to special radiotherapeutic techniques

Monte Carlo (MC) methods are considered one of the most powerful and precise approaches to study and solve medical physics issues. They, indeed, can be applied in all the situations where to use deterministic algorithms is infeasible or impossible. Surprising improvements in computer technology have promoted a wide diffusion of this technique, giving rise to the born of several Monte Carlo codes, such as the GEANT4 toolkit. In this paper we show some of the applications we developed using GEANT4. In particular, the simulation of two different radiotherapy techniques, such as proton/ion therapy and stereotactic radiosurgery will be discussed. In the first case we show the main features of our last public version of the GEANT4 Hadrontherapy program, also discussing the issues related to the nuclear fragmentation. In the second case, we show the procedures followed for the simulation of a Gamma Knife device, in order to validate the Treatment Planning System (TPS) used for the dose computation