More Like this

1. Semantics for Conditional Literals via the SM Operator

   https://doi.org/10.1007/978-3-031-15707-3_20  

   Hansen, Z.; Lierler, Y. (August 2022, Logic Programming and Nonmonotonic Reasoning)

   Conditional literals are an expressive Answer Set Programming language construct supported by the solver clingo. Their semantics are currently defined by a translation to infinitary propositional logic, however, we develop an alternative characterization with the SM operator which does not rely on grounding. This allows us to reason about the behavior of a broad class of clingo programs/encodings containing conditional literals, without referring to a particular input/instance of an encoding. We formalize the intuition that conditional literals behave as nested implications, and prove the equivalence of our semantics to those implemented by clingo. 

   more » « less
2. Event Trend Aggregation Under Rich Event Matching Semantics

   https://doi.org/10.1145/3299869.3319862  

   Poppe, Olga; Lei, Chuan; Rundensteiner, Elke A.; Maier, David (June 2019, SIGMOD)

   null (Ed.)

   Streaming applications from cluster monitoring to algorithmic trading deploy Kleene queries to detect and aggregate event trends. Rich event matching semantics determine how to compose events into trends. The expressive power of stateof- the-art streaming systems remains limited since they do not support many of these semantics. Worse yet, they suffer from long delays and high memory costs because they maintain aggregates at a fine granularity. To overcome these limitations, our Coarse-Grained Event Trend Aggregation (Cogra) approach supports a rich variety of event matching semantics within one system. Better yet, Cogra incrementally maintains aggregates at the coarsest granularity possible for each of these semantics. In this way, Cogra minimizes the number of aggregates – reducing both time and space complexity. Our experiments demonstrate that Cogra achieves up to six orders of magnitude speed-up and up to seven orders of magnitude memory reduction compared to state-of-the-art approaches. 

   more » « less
3. Arguing Correctness of ASP Programs with Aggregates

   https://doi.org/10.1007/978-3-031-15707-3_15  

   Fandinno, J.; Hansen, Z.; Lierler, Y (August 2022, Arguing Correctness of ASP Programs with Aggregates)

   This paper studies the problem of arguing program correctness for logic programs with aggregates in the context of Answer Set Programming. Cabalar, Fandinno, and Lierler (2020) championed a modular methodology for arguing program correctness. We show how a recently proposed many-sorted semantics for logic programs with aggregates allows us to apply their methodology to this type of program. This is illustrated using well-known encodings for the Graph Coloring and Traveling Salesman problems. In particular, we showcase how this modular approach allows us to reuse the proof of correctness of a Hamiltonian Cycle encoding studied in a previous publication when considering the Traveling Salesman program. 

   more » « less
4. Effects of Phytoplankton Growth Phase on Settling Properties of Marine Aggregates

   https://doi.org/10.3390/jmse7080265  

   Prairie, Jennifer C.; Montgomery, Quinn W.; Proctor, Kyle W.; Ghiorso, Kathryn S. (August 2019, Journal of Marine Science and Engineering)

   Marine snow aggregates often dominate carbon export from the surface layer to the deep ocean. Therefore, understanding the formation and properties of aggregates is essential to the study of the biological pump. Previous studies have observed a relationship between phytoplankton growth phase and the production of transparent exopolymer particles (TEP), the sticky particles secreted by phytoplankton that act as the glue during aggregate formation. In this experimental study, we aim to determine the effect of phytoplankton growth phase on properties related to aggregate settling. Cultures of the diatom Thalassiosira weissflogii were grown to four different growth phases and incubated in rotating cylindrical tanks to form aggregates. Aggregate excess density and delayed settling time through a sharp density gradient were quantified for the aggregates that were formed, and relative TEP concentration was measured for cultures before aggregate formation. Compared to the first growth phase, later phytoplankton growth phases were found to have higher relative TEP concentration and aggregates with lower excess densities and longer delayed settling times. These findings may suggest that, although particle concentrations are higher at later stages of phytoplankton blooms, aggregates may be less dense and sink slower, thus affecting carbon export. 

   more » « less
5. Cell behaviors underlying Myxococcus xanthus aggregate dispersal

   https://doi.org/10.1128/msystems.00425-23  

   Murphy, Patrick; Comstock, Jessica; Khan, Trosporsha; Zhang, Jiangguo; Welch, Roy; Igoshin, Oleg A. (September 2023, mSystems)

   Rodríguez-Verdugo, Alejandra (Ed.)

   ABSTRACT The soil bacteriumMyxococcus xanthusis a model organism with a set of diverse behaviors. These behaviors include the starvation-induced multicellular development program, in which cells move collectively to assemble multicellular aggregates. After initial aggregates have formed, some will disperse, with smaller aggregates having a higher chance of dispersal. Initial aggregation is driven by two changes in cell behavior: cells slow down inside of aggregates and bias their motion by reversing direction less frequently when moving toward aggregates. However, the cell behaviors that drive dispersal are unknown. Here, we use fluorescent microscopy to quantify changes in cell behavior after initial aggregates have formed. We observe that after initial aggregate formation, cells adjust the bias in reversal timings by initiating reversals more rapidly when approaching unstable aggregates. Using agent-based modeling, we then show dispersal is predominantly generated by this change in bias, which is strong enough to overcome slowdown inside aggregates. Notably, the change in reversal bias is correlated with the nearest aggregate size, connecting cellular activity to previously observed correlations between aggregate size and fate. To determine if this connection is consistent across strains, we analyze a secondM. xanthusstrain with reduced levels of dispersal. We find that far fewer cells near smaller aggregates modified their bias. This implies that aggregate dispersal is under genetic control, providing a foundation for further investigations into the role it plays in the life cycle ofM. xanthus. IMPORTANCEUnderstanding the processes behind bacterial biofilm formation, maintenance, and dispersal is essential for addressing their effects on health and ecology. Within these multicellular communities, various cues can trigger differentiation into distinct cell types, allowing cells to adapt to their specific local environment. The soil bacteriumMyxococcus xanthusforms biofilms in response to starvation, marked by cells aggregating into mounds. Some aggregates persist as spore-filled fruiting bodies, while others disperse after initial formation for unknown reasons. Here, we use a combination of cell tracking analysis and computational simulations to identify behaviors at the cellular level that contribute to aggregate dispersal. Our results suggest that cells in aggregates actively determine whether to disperse or persist and undergo a transition to sporulation based on a self-produced cue related to the aggregate size. Identifying these cues is an important step in understanding and potentially manipulating bacterial cell-fate decisions. 

   more » « less