Dataset Information

Heterogeneities in granular dynamics.

ABSTRACT: The absence of Brownian motion in granular media is a source of much complexity, including the prevalence of heterogeneity, whether static or dynamic, within a given system. Such strong heterogeneities can exist as a function of depth in a box of grains; this is the system we study here. First, we present results from three-dimensional, cooperative and stochastic Monte Carlo shaking simulations of spheres on heterogeneous density fluctuations. Next, we juxtapose these with results obtained from a theoretical model of a column of grains under gravity; frustration via competing local fields is included in our model, whereas the effect of gravity is to slow down the dynamics of successively deeper layers. The combined conclusions suggest that the dynamics of a real granular column can be divided into different phases-ballistic, logarithmic, activated, and glassy-as a function of depth. The nature of the ground states and their retrieval (under zero-temperature dynamics) is analyzed; the glassy phase shows clear evidence of its intrinsic ("crystalline") states, which lie below a band of approximately degenerate ground states. In the other three phases, by contrast, the system jams into a state chosen randomly from this upper band of metastable states.

SUBMITTER: Mehta A

PROVIDER: S-EPMC2448822 | biostudies-other | 2008 Jun

REPOSITORIES: biostudies-other

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Heterogeneities in granular dynamics.

Mehta A A Barker G C GC Luck J M JM

Proceedings of the National Academy of Sciences of the United States of America 20080609 24

The absence of Brownian motion in granular media is a source of much complexity, including the prevalence of heterogeneity, whether static or dynamic, within a given system. Such strong heterogeneities can exist as a function of depth in a box of grains; this is the system we study here. First, we present results from three-dimensional, cooperative and stochastic Monte Carlo shaking simulations of spheres on heterogeneous density fluctuations. Next, we juxtapose these with results obtained from ...[more]

PMID: 18541918

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Project description:Aerobic granular sludge (AGS) is based on self-granulated flocs forming mobile biofilms with a gel-like consistence. Bacterial and structural dynamics from flocs to granules were followed in anaerobic-aerobic sequencing batch reactors (SBR) fed with synthetic wastewater, namely a bubble column (BC-SBR) operated under wash-out conditions for fast granulation, and two stirred-tank enrichments of Accumulibacter (PAO-SBR) and Competibacter (GAO-SBR) operated at steady-state. In the BC-SBR, granules formed within 2 weeks by swelling of Zoogloea colonies around flocs, developing subsequently smooth zoogloeal biofilms. However, Zoogloea predominance (37-79%) led to deteriorated nutrient removal during the first months of reactor operation. Upon maturation, improved nitrification (80-100%), nitrogen removal (43-83%), and high but unstable dephosphatation (75-100%) were obtained. Proliferation of dense clusters of nitrifiers, Accumulibacter, and Competibacter from granule cores outwards resulted in heterogeneous bioaggregates, inside which only low abundance Zoogloea (<5%) were detected in biofilm interstices. The presence of different extracellular glycoconjugates detected by fluorescence lectin-binding analysis showed the complex nature of the intracellular matrix of these granules. In the PAO-SBR, granulation occurred within two months with abundant and active Accumulibacter populations (56 ± 10%) that were selected under full anaerobic uptake of volatile fatty acids and that aggregated as dense clusters within heterogeneous granules. Flocs self-granulated in the GAO-SBR after 480 days during a period of over-aeration caused by biofilm growth on the oxygen sensor. Granules were dominated by heterogeneous clusters of Competibacter (37 ± 11%). Zoogloea were never abundant in biomass of both PAO- and GAO-SBRs. This study showed that Zoogloea, Accumulibacter, and Competibacter affiliates can form granules, and that the granulation mechanisms rely on the dominant population involved.

Project description:Introduction Certain behavioral practices, such as wearing masks, practicing social distancing, and accepting vaccines, play a crucial role in impeding the spread of COVID-19 and reducing the severity of symptoms. Opinions regarding whether to observe such behavioral practices evolve over time through interactions via networks that overlap with but are not identical to the physical interaction networks over which the disease progresses. This necessitates the joint study of the dynamics of COVID-19 and opinion evolution. Methods We develop a mathematical model that can be easily adapted to a wide range of behavioral practices and captures in a computationally tractable manner the joint evolution of the disease and relevant opinions in populations of large sizes. Populations of large sizes are typically heterogeneous in that they comprise individuals of different age groups, genders, races, and underlying health conditions. Such groups have different propensities to imbibe severe forms of the disease, different physical contact, and social interaction patterns and rates. These lead to different disease and opinion dynamics in them. Our model is designed to effectively capture such diversities. Results Computations using our model reveal that opinion dynamics have a strong impact on fatality and hospitalization counts and the number of man-days lost due to symptoms both in the regular form of the disease and the extended forms, more commonly known as long COVID. We show that opinion dynamics in certain groups have a disproportionate impact on the overall public health attributes because they have high physical interaction rates, even when they have the lowest propensity to imbibe severe forms of the disease. This identifies a social vulnerability that malactors can utilize to inflict heavy public health damages through opinion campaigns targeting specific segments. Once such vulnerabilities are identified, which we accomplish, adequate precautions may be designed to enhance resilience to such targeted attacks and better protect public health. Discussion By recognizing and understanding the vulnerabilities, appropriate precautions can be developed to enhance resilience against targeted attacks and safeguard public health. Our study underscores the importance of considering opinion evolution alongside disease dynamics, providing insights into the interplay between behavioral practices, opinions, and disease outcomes. We believe that our model is a valuable tool for understanding the joint dynamics of COVID-19 and opinions. We hope that our findings will help to inform public health policy and facilitate evidence-based decision-making for public health interventions.

Dataset Information

Heterogeneities in granular dynamics.

Publications

Heterogeneities in granular dynamics.

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