Improving collisional growth in Lagrangian cloud models: development and verification of a new splitting algorithm

In many explicit microphysics cloud models the description of turbulent mixing of droplet size distributions (DSDs) treats them as conservative quantities, which leads to changes in DSDs for adiabatic profiles of liquid water. A new approach representing turbulent diffusion of DSD in Eulerian and Lagrangian cloud models is proposed. The approach is an extension of the classical K‐theory (used for calculation of turbulent fluxes) to the mixing of non‐conservative quantities. The proposed approach takes into account the growth/evaporation of drops as well as nucleation/denucleation in the course of the turbulent mixing. Implementation of the method is illustrated by the analysis of mixing between several different pairs of adjacent Lagrangian parcels: two cloudy parcels, a cloudy parcel with a drop‐free one, and two drop‐free parcels. The initial values of DSD and other parameters of the parcels are taken from simulations of stratocumulus clouds using the Lagrangian trajectory ensemble model. It is shown that taking into account the non‐conservativity of DSD makes the rate and the results of mixing strongly dependent on the mutual locations of the parcels. The effects of mixing increase with the deviation of the vertical profile of liquid water content (LWC) from the adiabatic one. If the upper parcel contains a larger LWC, the effect of mixing on the DSD is significantly weaker than for lower LWC in the upper parcel. The mixing near cloud base and cloud top is more intense. The standard method underestimates the rate of mixing near cloud top and overestimates it near cloud base.The proposed approach can serve as an efficient tool for investigating the role of mixing in Eulerian and Lagrangian models of stratocumulus and cumulus clouds. Copyright © 2010 Royal Meteorological Society

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We have previously shown by freeze-fracture electron microscopy that serum from infection-immune syphilitic rabbits aggregates the low-density membrane-spanning Treponema pallidum rare outer membrane proteins (TROMPs). The purpose of this study was to determine if a relationship could be demonstrated between acquired immunity in experimental rabbit syphilis, serum complement-dependent treponemicidal antibody, and antibody directed against TROMPs as measured by the aggregation of TROMP particles. Three groups of T. pallidum-infected rabbits were treated curatively with penicillin at 9 days, 30 days, and 6 months postinfection to generate various degrees of immunity to challenge reinfection. Sera from rabbits completely susceptible to localized and disseminated reinfection possessed a low titer of treponemicidal antibody (</=1:1 in killing >/=50% of a treponemal suspension) and showed a correspondingly low level of TROMP aggregation (16.5% of the total number of outer membrane particles counted) similar to normal serum controls (13. 4%); the number of particles within these aggregates never exceeded three. Sera from partially immune rabbits, which were susceptible to local reinfection but had no evidence of dissemination, showed an increase in the titer of treponemicidal antibody (1:16) compared to the completely susceptible group (</=1:1). Although no significant increase was observed in the total number of TROMP particles aggregated (18.9%) compared to the number in controls (13.4%), approximately 15% of these aggregates did exhibit a significant increase in the number of particles per aggregate (4 to 5 particles) compared to controls (</=3 particles), indicating a measurable increase in anti-TROMP antibody. Finally, sera from rabbits completely immune to both local and disseminated reinfection possessed both high titers of treponemicidal antibody (1:128) and significant aggregation of TROMP (88.6%); approximately 50% of these aggregates contained four to six particles. The results indicate that complete immunity in experimental rabbit syphilis correlates with antibody that kills T. pallidum and aggregates TROMPs, suggesting that TROMPs are molecules which contribute to the development of acquired immunity.

The direct gamma dose rates due to a stationary Gaussian plume of radionuclides in the atmosphere have been calculated using different models [Lagrangian dose model (LDM), Gaussian plume model (GPM), and uniform cloud model (UCM)], and the results are compared.The atmospheric parameters (used in the Lagrangian model) like mean and fluctuating wind components, etc., were obtained from the published field data on a neutral atmosphere. In the LDM, a continuous release of radionuclides into the atmosphere was simulated by liberating a large number of Lagrangian particles, whose trajectories were tracked for various hours in a three-dimensional computational domain. A point isotropic source formula was used for calculating the direct gamma dose contribution from all Lagrangian particles constituting the plume. Each particle represented a point source of radioactivity, whose strength was calculated from the known release rate and was subsequently allowed to decay as a function of time.The comparison of the LDM results with the GPM indicated that both models predict comparable results in a homogeneous atmosphere. The LDM is, however, more versatile, as it can incorporate variation in meteorological data in space and time (of course when available). The UCM also compared well for ground releases; however, it cannot be used for elevated releases and short downwind distances. The purpose of this work was to test the LDM for simulating the transport, dispersion, and decay of a radionuclide plume. The LDM shall later be used for complex topographic and meteorological conditions, where the GPM is not suitable.

some studies have reported controversial results when comparing the gastrointestinal transit between diabetic and healthy individuals. Therefore, we compared the gastrointestinal transit of radiopaque particles between diabetic and non-diabetic healthy individuals. abdominal radiographies were performed for 45 type 2 diabetes mellitus patients and 35 healthy individuals (gender and age similar for both groups) at 24 and 72 h after they ingested radiopaque particles. The mean number of particles in the colon was compared for both groups. The data were expressed as mean and standard deviation values. at 24 h, the total number of particles in the colon did not differ significantly for the diabetic and non-diabetic individuals. At 72 hours, the distribution in the diabetic and non-diabetic individuals was as follows: right colon, 0.44 ± 0.88 and 0.26 ± 0.7, respectively (p = 0.8); left colon, 2.6 ± 4.2 and 0.49 ± 1.3 (p < 0.003); and rectosigmoid colon, 2.65 ± 3.8 and 0.80 ± 1.5 (p < 0.005).The mean number of radiopaque particles in the entire colon was 5.7 ± 7.1 and 1.5 ± 2.7 for diabetic and non-diabetic individuals, respectively (p < 0.001). the number of radiopaque particles in the colon did not significantly differ for the diabetic and non-diabetic individuals at 24 h after ingestion but was significantly greater in diabetic individuals at 72 h after ingestion. At 72 h, the mean number of radiopaque particles in the left and rectosigmoid colon were significantly higher in the diabetics than in the non-diabetic individuals.

The paper presents the results of examination of particulate matter emission from the Diesel engine FPT 1.3 MJT simultaneously fuelled with diesel oil and natural gas CNG. The basic premise for engine adaptation was the addition of a small amount of CNG to reduce exhaust gas opacity and particulate matter emission. At this assumption, diesel oil remained the basic fuel, with contribution amounting to 0,70-0,85 of total energy delivered to the engine. The dual fuel engine was examined using an original controller installed in the Diesel engine FPT 1.3 MJT which controlled the diesel fuel dose. The dose of the injected natural gas was controlled by changing the opening time of gas injectors at constant pressure in the gas collector. The examined issues included the exhaust gas opacity, and the total number and fractional distribution of the emitted particles. The measurements were performed at twenty selected measuring points corresponding to the New European Driving Cycle (NEDC) test. The performed tests have demonstrated a positive effect of gas addition on exhaust gas opacity and particulate matter emission. Depending on test conditions, the exhaust gas opacity was reduced by 10÷92%, and the total number of particles by 30÷40%. The performed tests have revealed that a small addition of gas can reduce the load of the DPF filter, extend its lifetime, and increase engine reliability. Longer time intervals between successive DPF filter regenerations improve ecological properties of the engine.

In recent years, the enhanced sensing and computation capabilities of Internet-of-Things (IoT) devices have opened the doors to several mobile crowdsensing applications. In mobile crowdsensing, a model owner announces a sensing task following which interested workers collect the required data. However, in some cases, a model owner may have insufficient data samples to build an effective machine learning model. To this end, we propose a federated learning (FL)-based privacy-preserving approach to facilitate collaborative machine learning among multiple model owners in mobile crowdsensing. Our system model allows collaborative machine learning without compromising data privacy given that only the model parameters instead of the raw data are exchanged within the federation. However, there are two main challenges of incentive mismatches between workers and model owners, as well as among model owners. For the former, we leverage on the self-revealing mechanism in the contract theory under information asymmetry. For the latter, to ensure the stability of a federation through preventing free-riding attacks, we use the coalitional game theory approach that rewards model owners based on their marginal contributions. Considering the inherent hierarchical structure of the involved entities, we propose a hierarchical incentive mechanism framework. Using the backward induction, we first solve the contract formulation and then proceed to solve the coalitional game with the merge and split algorithm. The numerical results validate the performance efficiency of our proposed hierarchical incentive mechanism design, in terms of incentive compatibility of our contract design and fair payoffs of model owners in stable federation formation.

Han [] have recently introduced a classical stochastic lattice gas model which, in addition to particle conservation, also conserves the particles' dipole moment. Because of its intrinsic nonlinearity this model exhibits unusual macroscopic scaling behaviors, different from those of lattice gases that conserve only the number of particles. Here we investigate some basic relaxation and fluctuation properties of this model at large scales and at long times. These properties crucially depend on whether the total number of particles is infinite or finite. We find similarity solutions, describing relaxation of the dipole-conserving gas (DCG) in several standard settings. A major part of our effort is an extension to this model of the macroscopic fluctuation theory (MFT), previously developed for lattice gases where only the number of particles is conserved. We apply the MFT to the calculation of the variance of nonequilibrium fluctuations of the excess number of particles on the positive semi-axis when starting from an (either deterministic, or random) constant density at t=0. Using the MFT, we also identify the equilibrium Boltzmann-Gibbs distribution for the DCG. Finally, based on these results, we determine the probability distribution of, and the most probable density history leading to, a large deviation in the form of a macroscopic void of a given size in an initially uniform DCG at equilibrium. Published by the American Physical Society 2024

&lt;div class="htmlview paragraph"&gt;This work studies the formation of nucleation mode (NM) particles from a Euro 3 passenger car operating on 280 ppm wt. sulfur fuel, during on-road plume chasing and in the laboratory. The vehicle produced a distinct NM when its speed exceeded 100 km/h in both sampling environments. A higher particle number (up to 8 times) after 4 min at constant speed was measured when this speed was approached from a lower than from a higher speed. The variability in the measurement of NM particles was explained using literature information on sulfur-to-sulfate conversion over a catalyst and, in particular, on the extent and rate of sulfate storage and release mechanisms. All evidence led to the conclusion that storage and release processes take several minutes to conclude after a step-wise change in speed and have significant implications in the total particle number measurements during steady-speed testing. However, their effect was much less important during transients due to the averaging effect of transient operation on aftertreatment condition. Appropriate preconditioning is therefore necessary in each case to reduce measurement variability.&lt;/div&gt; &lt;div class="htmlview paragraph"&gt;Over speed transitions, the solid particle number concentration generally followed the inverse of the air-to-fuel (A/F) ratio. The total particle number concentration also followed the inverse A/F ratio at low speeds (i.e. &amp;lt;100 km/h), when no NM was monitored at either the initial or the terminal speed. At higher speeds though, the total particle number increased both during acceleration and during deceleration. The increase during acceleration was explained due to the increase in the exhaust gas temperature which increased the sulfur-to-sulfate conversion. Over deceleration, the total particle number increase could only be explained by the reduction in the available surface area of solid particles as the A/F increased, which promoted the homogeneous nucleation of sulfate.&lt;/div&gt;

Motivated by nucleation and molecular aggregation in physical, chemical, and biological settings, we present an extension to a thorough analysis of the stochastic self-assembly of a fixed number of identical particles in a finite volume. We study the statistics of times required for maximal clusters to be completed, starting from a pure-monomeric particle configuration. For finite volumes, we extend previous analytical approaches to the case of arbitrary size-dependent aggregation and fragmentation kinetic rates. For larger volumes, we develop a scaling framework to study the first assembly time behavior as a function of the total quantity of particles. We find that the mean time to first completion of a maximum-sized cluster may have a surprisingly weak dependence on the total number of particles. We highlight how higher statistics (variance, distribution) of the first passage time may nevertheless help to infer key parameters, such as the size of the maximum cluster. Finally, we present a framework to quantify formation of macroscopic sized clusters, which are (asymptotically) very unlikely and occur as a large deviation phenomenon from the mean-field limit. We argue that this framework is suitable to describe phase transition phenomena, as inherent infrequent stochastic processes, in contrast to classical nucleation theory.

Background and Aims: Ultrafine particle (UFP) numbers show large short-term and small scale variation, making strategies to assess personal exposure to UFP in urban environment potentially very costly. Better insight in the role of local and regional processes, can give rise to methods to estimate UFP using correlated pollutants and regional indicators (Can et al 2011). Methods: UFP and NOx were measured simultaneously in Antwerp (Belgium) at three locations in a single street in Summer 2009, and in four different streets in a 1 km grid in Winter 2010. Different size fractions were compared to traffic counts and meteorological data. Regional contributions to various size fractions were assessed using night time number concentrations and air mass back-trajectory techniques. Results: In-street spatial variability of total particle number was rather low. UFP concentrations in four different streets showed a remarkably similar temporal trend on top of which the local component is added. Total particle number correlated poorly with traffic intensity. Mainly the 20 – 50 nm fractions are correlated with traffic intensity. The morning traffic peak leads to a distinct peak in total particle number, but this is not the case for the afternoon rush hour. Analysis of diurnal UFP concentrations for different size bins shows that both processes of agglomeration and condensation and meteorological conditions explain this decoupling of traffic and total particle number. Elevated total night-time UFP was mainly related to larger size fractions (50 - 100 nm). Higher concentrations of the larger size bins were associated with slow moving air masses. Conclusions: Although short-term variation in UFP number counts at urban traffic locations largely depends on local sources, similar temporal trends result both from regional processes and similar underlying traffic patterns. This study illustrates the potential to extrapolate measured UFP concentrations to similar locations using correlated pollutants and regional indicators.

Recent resultsi¾?[5, 9, 23] prove that edge partitioning approaches also known as vertex-cut outperform vertex partitioningedge-cut approaches for computations on large and skewed graphs like social networks. These vertex-cut approaches generally avoid unbalanced computation due to the power-law degree distribution problem. However, these methods, like evenly random assigningi¾?[23] or greedy assignment strategyi¾?[9], are generic and do not consider any computation pattern for specific graph algorithm. We propose in this paper a vertex-cut partitioning dedicated to random walks algorithms which takes advantage of graph topological properties. It relies on a blocks approach which captures local communities. Our split and merge algorithms allow to achieve load balancing of the workers and to maintain it dynamically. Our experiments illustrate the benefit of our partitioning since it significantly reduce the communication cost when performing random walks-based algorithms compared with existing approaches.

In this paper, cluster splitting and merging algorithms are used for flood assessment using LISS-III (before flood) and SAR (during flood) images. Bayesian Information Criteria (BIC) is used to determine the optimal number of clusters. Keeping this constraint, the cluster centers are generated using the cluster splitting techniques, namely Mean Shift Clustering (MSC), and Niche Genetic Algorithm (NGA). The merging method is used to group the data points into their respective classes, using the cluster centers obtained from the above techniques. These techniques are applied on the LISS-III and SAR image. Further, the resultant images are overlaid to analyze the extent of the flood in individual land classes. A performance comparison of these techniques (MSC and NGA) is presented. From the results obtained, we deduce that the NGA is efficient.

In this paper, we present a flexible partitioning scheme for fractal image compression based on adaptive Delaunay triangulation. Such partition is computed on an initial set of points obtained with a split and merge algorithm in a grey level dependent way. The triangulation is fully flexible and returns a limited number of blocks allowing good compression Ratios Moreover, a vector quantization algorithm is implemented on pixel histograms directly generated from the triangulation. The aim is to reduce the number of comparisons between the two sets of blocks involved in fractal image compression by keeping only the best representative triangles in the domain blocks set. Quality coding results are achieved at rates between 0.06 b/pixel and 0.2 b/pixel for a PSNR between 22 and 25 dB depending on the nature of the original image and on the number of triangles refereed.

In this paper, particles of calcium tungstate as a model compound were prepared by a reverse micelle’s method. The morphology of particles was tuned from rod to spindle-like and spherical by altering the temperature and concentration of reactants. A volume per single particle and a total number of particles were calculated to explain quantitatively the mechanism of influence of reaction conditions on the process. It was found that the reactant concentration had no effect on the number of particles. With increasing temperature or reaction time, the number of particles decreased, whereas the particle volume increased. The bulk water in the micelles seemed actually affect the size of particles.