Marine species reproduce and compete while being advected by turbulent flows. It is largely unknown, both theoretically and experimentally, how population dynamics and genetics are changed by the presence of fluid flows. Discrete agent-based simulations in continuous space allow for accurate treatment of advection and number fluctuations, but can be computationally expensive for even modest organism densities. In this report, we propose an algorithm to overcome some of these challenges. We first provide a thorough validation of the algorithm in one and two dimensions without flow. Next, we focus on the case of weakly compressible flows in two dimensions. This models organisms such as phytoplankton living at a specific depth in the three-dimensional, incompressible ocean experiencing upwelling and/or downwelling events. We show that organisms born at sources in a two-dimensional time-independent flow experience an increase in fixation probability.

The dynamics of inertial particles in Rayleigh-Benard convection, where both particles and fluid exhibit thermal expansion, is studied using direct numerical simulations (DNS) in the soft-turbulence regime. We consider the effect of particles with a thermal expansion coefficient larger than that of the fluid, causing particles to become lighter than the fluid near the hot bottom plate and heavier than the fluid near the cold top plate. Because of the opposite directions of the net Archimedes' force on particles and fluid, particles deposited at the plate now experience a relative force towards the bulk. The characteristic time for this motion towards the bulk to happen, quantified as the time particles spend inside the thermal boundary layers (BLs) at the plates, is shown to depend on the thermal response time, tau T. In particular, the residence time is constant for small thermal response times, tau T less than or similar to 1, and increasing with tau T for larger thermal response times, tau T greater than or similar to 1. Also, the thermal BL residence time is increasing with decreasing K. A one-dimensional (1D) model is developed, where particles experience thermal inertia and their motion is purely dependent on the buoyancy force. Although the values do not match one-to-one, this highly simplified 1D model does predict a regime of a constant thermal BL residence time for smaller thermal response times and a regime of increasing residence time with tau T for larger response times, thus explaining the trends in the DNS data well.

In Rayleigh-Bénard convection (RBC) for fluids with Prandtl number Pr1, rotation beyond a critical (small) rotation rate is known to cause a sudden enhancement of heat transfer, which can be explained by a change in the character of the boundary layer (BL) dynamics near the top and bottom plates of the convection cell. Namely, with increasing rotation rate, the BL signature suddenly changes from Prandtl-Blasius type to Ekman type. The transition from a constant heat transfer to an almost linearly increasing heat transfer with increasing rotation rate is known to be sharp and the critical Rossby number Roc occurs typically in the range 2.3Roc2.9 (for Rayleigh number Ra=1.3×109, Pr=6.7, and a convection cell with aspect ratio ?=DH=1, with D the diameter and H the height of the cell). The explanation of the sharp transition in the heat transfer points to the change in the dominant flow structure. At 1/Ro1/Roc (slow rotation), the well-known large-scale circulation (LSC) is found: a single domain-filling convection roll made up of many individual thermal plumes. At 1/Ro1/Roc (rapid rotation), the LSC vanishes and is replaced with a collection of swirling plumes that align with the rotation axis. In this paper, by numerically studying Lagrangian acceleration statistics, related to the small-scale properties of the flow structures, we reveal that this transition between these different dominant flow structures happens at a second critical Rossby number, Roc2?2.25 (different from Roc1?2.7 for the sharp transition in the Nusselt number Nu; both values for the parameter settings of our present numerical study). When statistical data of Lagrangian tracers near the top plate are collected, it is found that the root-mean-square values and the kurtosis of the horizontal acceleration of these tracers show a sudden increase at Roc2. To better understand the nature of this transition we compute joint statistics of the Lagrangian velocity and acceleration of fluid particles and vertical vorticity near the top plate. It is found that for Ro2.25 there is hardly any correlation between the vertical vorticity and extreme acceleration events of fluid particles. For Ro2.25, however, vortical regions are much more prominent and extreme horizontal acceleration events are now correlated to large values of positive (cyclonic) vorticity. This suggests that the observed sudden transition in the acceleration statistics is related to thermal plumes with cyclonic vorticity developing in the Ekman BL and subsequently becoming mature and entering the bulk of the flow for Ro2.25.

Competition between biological species in marine environments is affected by the motion of the surrounding fluid. An effective 2D compressibility can arise, for example, from the convergence and divergence of water masses at the depth at which passively traveling photosynthetic organisms are restricted to live. In this report, we seek to quantitatively study genetics under flow. To this end, we couple an off-lattice agent-based simulation of two populations in 1D to a weakly compressible velocity field--first a sine wave and then a shell model of turbulence. We find for both cases that even in a regime where the overall population structure is approximately unaltered, the flow can significantly diminish the effect of a selective advantage on fixation probabilities. We understand this effect in terms of the enhanced survival of organisms born at sources in the flow and the influence of Fisher genetic waves.

The selective entrapment of mutually annihilating species within a phase-changing carrier fluid is explored by both analytical and numerical means. The model takes full account of the dynamic heterogeneity which arises as a result of the coupling between hydrodynamic transport, dynamic phase-transitions and chemical reactions between the participating species, in the presence of a selective droplet interface. Special attention is paid to the dynamic symmetry breaking between the mass of the two species entrapped within the expanding droplet as a function of time. It is found that selective sources are much more effective symmetry breakers than selective diffusion. The present study may be of interest for a broad variety of advection-diffusion-reaction phenomena with selective fluid interfaces, including the problem of electroweak baryogenesis.

Recent numerical analyses to optimize the design of microfluidic devices for more effective entrapment or segregation of surrogate circulating tumor cells (CTCs) from healthy cells have been reported in the literature without concurrently accommodating the non-Newtonian nature of the body fluid and the non-uniform geometric shapes of the CTCs. Through a series of two-dimensional proof-of-concept simulations with increased levels of complexity (e.g., number of particles, inline obstacles), we investigated the validity of the assumptions of the Newtonian fluid behavior for pseudoplastic fluids and the circular particle shape for different-shaped particles (DSPs) in the context of microfluidics-facilitated shape-based segregation of particles. Simulations with a single DSP revealed that even in the absence of internal geometric complexities of a microfluidics channel, the aforementioned assumptions led to 0.11-0.21W (W is the channel length) errors in lateral displacements of DSPs, up to 3-20% errors in their velocities, and 3-5% errors in their travel times. When these assumptions were applied in simulations involving multiple DSPs in inertial microfluidics with inline obstacles, errors in the lateral displacements of DSPs were as high as 0.78W and in their travel times up to 23% , which led to different (un)symmetric flow and segregation patterns of DSPs. Thus, the fluid type and particle shape should be included in numerical models and experiments to assess the performance of microfluidics for targeted cell (e.g., CTCs) harvesting.

We present an analytical derivation of the transport coefficients of a relativistic gas in (2 + 1) dimensions for both Chapman-Enskog (CE) asymptotics and Grad's expansion methods. We further develop a systematic calibration method, connecting the relaxation time of relativistic kinetic theory to the transport parameters of the associated dissipative hydrodynamic equations. Comparison of our analytical results and numerical simulations shows that the CE method correctly captures dissipative effects, while Grad's method does not, in agreement with previous analyses performed in the (3 + 1)-dimensional case. These results provide a solid basis for accurately calibrated computational studies of relativistic dissipative flows.

Motility behavior of an engineered chemosensory particle (ECP) in fluidic environments is driven by its responses to chemical stimuli. One of the challenges to understanding such behaviors lies in tracking changes in chemical signal gradients of chemoattractants and ECP-fluid dynamics as the fluid is continuously disturbed by ECP motion. To address this challenge, we introduce a new multiscale numerical model to simulate chemotactic swimming of an ECP in confined fluidic environments by accounting for motility-induced disturbances in spatiotemporal chemoattractant distributions. The model accommodates advective-diffusive transport of unmixed chemoattractants, ECP-fluid hydrodynamics at the ECP-fluid interface, and spatiotemporal disturbances in the chemoattractant concentrations due to particle motion. Demonstrative simulations are presented with an ECP, mimicking Escherichia coli (E. coli) chemotaxis, released into initially quiescent fluids with different source configurations of the chemoattractants N-methyl-L-aspartate and L-serine. Simulations demonstrate that initial distributions and temporal evolution of chemoattractants and their release modes (instantaneous vs. continuous, point source vs. distributed) dictate time histories of chemotactic motility of an ECP. Chemotactic motility is shown to be largely determined by spatiotemporal variation in chemoattractant concentration gradients due to transient disturbances imposed by ECP-fluid hydrodynamics, an observation not captured in previous numerical studies that relied on static chemoattractant concentration fields.

GOLIAT is an offshore production field that spans from the subsea wells up to a complete process plant installed on a FPSO. Due to the comprehensive instrumentation installed on the plant, it is the perfect case study to test an innovative agent based software architecture able to support production management. The modularity and the scalability provided by the agent based architecture guarantees the applicability of the method to any part of the plant. Each agent is in charge of supervising a specific or a group of equipment and is fed by the real-time data coming from the field. These data are then analysed through Machine Learning and Deep Learning algorithms which are incorporated within the agents. The machine learning algorithms estimate the current state of the equipment and provide a set of KPIs in order to understand both the production efficiency and the health status of the machines. Furthermore, learning from the observations of the state transition paths which happened in the past, the agents are capable of predicting the most likely future state. The latter capability is fundamental to prevent unplanned shutdowns and optimize the maintenance plans. On the basis of the estimated current state, each agent can also provide a list of actions targeted to maximize the efficiency from an "equipment" point of view. The actions coming from all the agents can then be collected and negotiated in order to maximize the production from a "plant" point of view. The negotiating algorithms are implemented in a super-agent that can support a human operator in the day-by-day management tasks of the plant. Even though the negotiating capabilities will be implemented in the future version of the application, the modular nature of the system guarantees an easy integration of the super-agent inside the agent's framework. The paper will present the results of the agent framework in terms of the robustness of state estimation and the correctness of the computed KPIs.

In this paper, we develop a three-dimensional multiple-relaxation-time lattice Boltzmann method (MRT-LBM) based on a set of non-orthogonal basis vectors. Compared with the classical MRT-LBM based on a set of orthogonal basis vectors, the present non-orthogonal MRT-LBM simplifies the transformation between the discrete velocity space and the moment space and exhibits better portability across different lattices. The proposed method is then extended to multiphase flows at large density ratio with tunable surface tension, and its numerical stability and accuracy are well demonstrated by some benchmark cases. Using the proposed method, a practical case of a fuel droplet impacting on a dry surface at high Reynolds and Weber numbers is simulated and the evolution of the spreading film diameter agrees well with the experimental data. Furthermore, another realistic case of a droplet impacting on a super-hydrophobic wall with a cylindrical obstacle is reproduced, which confirms the experimental finding of Liu et al. ["Symmetry breaking in drop bouncing on curved surfaces," Nat. Commun. 6, 10034 (2015)] that the contact time is minimized when the cylinder radius is comparable with the droplet radius.

In this paper, we propose a hybrid lattice Boltzmann method (HLBM) for solving fluid-structure interaction problems. The proposed numerical approach is applied to model the flow induced by a vibrating thin lamina submerged in a viscous quiescent fluid. The hydrodynamic force exerted by the fluid on the solid body is described by means of a complex hydrodynamic function, whose real and imaginary parts are determined via parametric analysis. Numerical results are validated by comparison with those from other numerical as well as experimental works available in the literature. The proposed hybrid approach enhances the capability of lattice Boltzmann methods to solve fluid dynamic problems involving moving geometries.

GPUs are very powerful computing accelerators that are often employed in single-device configuration. However, there is a steadily growing interest in using multiple GPUs in a concurrent way both to overcome the memory limitations of the single device and to further reduce execution times. Until recently, communication among GPUs had been carried out mainly by using networking technologies originally devised for standard CPUs with the CPU playing an active role in the communication. However, new alternatives start to be available in which a moderate number of GPUs are directly connected each other by means of proprietary technologies. We present the results of a set of experiments aimed at assessing the performance of some of these hardware/software platforms using a particularly challenging application as a benchmark. We release its source code to facilitate people interested in reproducing or extending our results.

Due to the limited field of view of the microscopes, acquisitions of macroscopic specimens require many parallel image stacks to cover the whole volume of interest. Overlapping regions are introduced among stacks in order to make it possible automatic alignment by means of a 3D stitching tool. Since state-of-the-art microscopes coupled with chemical clearing procedures can generate 3D images whose size exceeds the Terabyte, parallelization is required to keep stitching time within acceptable limits. In the present paper we discuss how multi-level parallelization reduces the execution times of TeraStitcher, a tool designed to deal with very large images. Two algorithms performing dataset partition for efficient parallelization in a transparent way are presented together with experimental results proving the effectiveness of the approach that achieves a speedup close to 300×, when both coarse- and fine-grained parallelism are exploited. Multi-level parallelization of TeraStitcher led to a significant reduction of processing times with no changes in the user interface, and with no additional effort required for the maintenance of code.

We present three case studies to illustrate a methodology for conducting forensics investigation on Microsoft Skype for Business. The proposed methodology helps to retrieve information on chat and audio communications made by any account who accessed the PC, to retrieve IP addresses and communication routes for all the participants of a call, and to retrieve forensics evidence to identify the end-user devices of a VoIP call by analyzing the CODECs exchanged by the clients during the SIP (Session Initiation Protocol) handshaking phase. This information may help the investigator either to corroborate or to contradict an investigative hypothesis.

This paper introduces a dominance test that allows to determine whether or not a financial institution can be classified as being more systemically important than another in a multivariate framework. The dominance test relies on a new risk measure, the NetCoVaR that is specifically tailored to capture the joint extreme co-movements between institutions belonging to a network. The asymptotic theory for the statistical test is provided under mild regularity conditions concerning the joint distribution of asset returns which is assumed to be elliptically contoured. The proposed risk measure and risk measurement framework is used to analyse the US financial system during the recent Global Financial Crises. In the empirical analysis, the returns are assumed to be Elliptically Stable distributed and the estimation is carried out through the Sparse Multivariate Method of Simulated Quantiles, handling both the lack of an analytic expression for the probability density function and the potential high-dimensionality of the problem.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a limb-viewing infrared Fourier transform spectrometer that operated from 2002 to 2012 onboard the ENVISAT satellite. The analysis of MIPAS measurements allows to study the temporal evolution of numerous species of interest for the study of the ozone in the stratosphere, pollutants and many green-house gases. The objective of the MIPAS Quality Working Group is to improve the quality of the MIPAS products through a fruitful collaboration among spectroscopists, Level 1, Level 2, and validation teams. A large effort has recently led to implement significant improvements in both ESA Level 1 and Level 2 processors, as well as in spectroscopic database and in some absorption cross-sections in order to improve the quality of the products. In addition to the products already present in the V7 dataset (temperature and the VMR of H2O, O3, HNO3, CH4, N2O, NO2, CFC-11, CFC-12, N2O5, ClONO2, HCFC-22, COF2, CF4, HCN and CCl4), the VMR of six additional species (OCS, CH3Cl, HDO, C2H2, C2H6, COCl2) will be provided in V8 dataset. In order to evaluate the impact of the changes in the products before full mission reprocessing, the analysis of the performances of the products of the modified L1 and L2 processors, as well as the auxiliary data, has been performed on a Diagnostic DataSet (DDS). The orbits of the DDS have been chosen in coincidence with correlative measurements for performing also a preliminary assessment of the accuracy of the products and to evaluate possible changes in the drift. With respect to V7 products, main improvements consist in a reduction of the temperature bias in the first part of the mission, a reduction of the discontinuities in CH4 and N2O time series due to daily gain upgrade, a better filtering of clouds and a better handling of horizontal inhomogeneities.The results of the assessment of the quality of MIPAS measurements will be shown, as well as the study of the temporal evolution and variability of all species. We will also investigate the spatial, seasonal, and interannual variations in the distribution of these species.

The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) is a limb-viewing infrared Fourier transform spectrometer that operated from 2002 to 2012 on board the ENVISAT satellite. The fruitful collaboration among spectroscopists, Level 1, Level 2, and validation teams in the frame of the MIPAS Quality Working Group has recently led to the implementation of significant changes in both ESA Level 1 and Level 2 processors, as well as in the spectroscopic database and in some absorption cross-sections. In addition to the products already present in V7 dataset (temperature and the VMR of H2O, O3, HNO3, CH4, N2O, NO2, CFC-11, CFC-12, N2O5, ClONO2, HCFC-22, COF2, CF4, HCN and CCl4), the VMR of six additional species (OCS, CH3Cl, HDO, C2H2, C2H6, COCl2) will be provided in V8 dataset.Among the new species, methyl chloride (CH3Cl) is of great interest in stratospheric ozone chemistry since it is the most abundant chlorine-containing gas in the troposphere and, in contrast to other relatively long-lived ozone-depleting gases, it has both natural and anthropogenic sources, with the known emission being mainly natural (tropical plants, biomass burning, the ocean, salt marshes and fungi). Since it is not controlled under the Montreal Protocol, its importance is expected to increase in the coming decades as emission controls alter the relative contributions from natural and anthropogenic halogen sources.In this paper we present a preliminary assessment of the quality of the MIPAS CH3Cl data, in terms of precision, accuracy and vertical resolution, and we investigate the spatial and seasonal variations in the distribution of CH3Cl in the upper troposphere/lower stratosphere (UTLS).

We examine the constraints on the Yukawa regime from the nonminimally coupled curvature-matter gravity theory arising from deep underwater ocean experiments. We consider the geophysical experiment of Zumberge et al. [Phys. Rev. Lett. 67, 3051 (1991)] for searching deviations of Newton's inverse square law in ocean. In the context of nonminimally coupled curvature-matter theory of gravity the results of Zumberge et al. can be used to obtain an upper bound both on the strength a and range lambda of the Yukawa potential arising from the nonrelativistic limit of the nonminimally coupled theory. The existence of an upper bound on lambda is related to the presence of an extra force, specific of the nonminimally coupled theory, which depends on lambda and on the gradient of mass density, and has an effect in the ocean because of compressibility of seawater. These results can be achieved after a suitable treatment of the conversion of pressure to depth in the ocean by resorting to the equation of state of seawater and taking into account the effect of the extra force on hydrostatic equilibrium. If the sole Yukawa interaction were present, the experiment would yield only a bound on alpha, while, in the presence of the extra force we find an upper bound on the range: lambda(max )= 57.4 km. In the interval 1 m < lambda < lambda(max) the upper bound on alpha is consistent with the constraint alpha < 0.002 found in [Phys. Rev. Lett. 67, 3051 (1991)].

This paper proposes improving the solve time of a bootstrap algebraic multigrid (AMG) designed previously by the authors. This is achieved by incorporating the information, a set of algebraically smooth vectors, generated by the bootstrap algorithm, in a single hierarchy by using sufficiently large aggregates, and these aggregates are compositions of aggregates already built throughout the bootstrap algorithm. The modified AMG method has good convergence properties and shows significant reduction in both memory and solve time. These savings with respect to the original bootstrap AMG are illustrated on some difficult (for standard AMG) linear systems arising from discretization of scalar and vector function elliptic partial differential equations in both 2D and 3D.

Molecular dynamics (MD) has become one of the most powerful tools of investigation in soft matter. Despite such success, simulations of large molecular environments are mostly run using the approximation of closed systems without the possibility of exchange of matter. Due to the molecular complexity of soft matter systems, an optimal simulation strategy would require the application of concurrent multiscale resolution approaches such that each part of a large system can be considered as an open subsystem at a high resolution embedded in a large coarser reservoir of energy and particles. This paper discusses the current capability and the future perspectives of multiscale adaptive resolution MD methods to satisfy the conceptual principles of open systems and to perform simulations of complex molecular environments in soft matter.