The Impact of Familiarity on Visualizations of Spatial Uncertainty

While visualization can support understanding complex phenomena, their effectiveness might vary with the recipient’s familiarity with both the phenomenon and the visualization. The current study contrasted interpretations of simulated hurricane paths using student populations from a high frequency hurricane area versus no local hurricane risk. Non-expert understanding of trajectory predictions was supported via two visualizations: common cones of uncertainty and novel dynamic ensembles. General patterns of performance were similar across the two groups. Participants from the high hurricane risk area did show narrower decision thresholds, in both common and novel visualization formats. More variability was consistently considered possible when viewing the dynamic ensemble displays. Despite greater likelihood of experiences with variability of trajectories outside of forecast paths, greater familiarity tended towards narrower interpretations of the need for evacuations within the variability possible. The results suggest an advantage of dynamic ensembles in grasping uncertainty even in populations familiar with hurricanes.

About Operational Game Scenario Modeling

An original generalizing class of game-theoretic models (operational games or KOSH games) is presented, using which many micro-and macro - economic interactions are naturally modeled. Basic concepts of the theory of operational games and classification of such games, equations of dynamics of operational game interactions, and procedures for modeling scenarios of such interactions are described. Examples of operational games and some practical results of using this theory are given. The possibilities of fundamental and applied development of the considered direction of game-theoretic research are analyzed. The importance of this research is due to the fact that the original idea of the founders of game theory, which is to create an adequate accurate language for describing economic processes, has not been implemented to this day. In this paper, an attempt is made to implement this by accurately defining the concept of “operation” using static games of a well-defined type and considering dynamic ensembles of such static games.

Dynamic Ensembles versus Cones of Uncertainty: Visualizations to Support Understanding of Uncertainty in Hurricane Forecasts

Visualizations attempt to convey the uncertain track of an approaching hurricane. The current experiment contrasted decision characteristics that resulted from observing hurricane paths presented using cones of uncertainty versus a new form of dynamic ensemble. Participants made judgments about whether to evacuate a town at different eccentricities to the central predicted path of a storm. Results showed that dynamic ensembles have different properties to cone displays. Presentations of dynamic ensembles encouraged greater consideration of evacuation at locations further from the most probable path, but that were still at risk. However, dynamic ensembles resulted in lower evacuation rates at the center of the distribution, consistent with a probabilistic sense of the risk but nonetheless a potentially undesirable strategy. In addition, perceptions of the evacuation need with dynamic ensemble presentations were more strongly influenced by the amount of variability than with cones. The implications for use of dynamic ensembles are discussed.

An RNA dynamic ensemble at atomic resolution

Biomolecules do not fold into a single 3D structure but rather form dynamic ensembles of many inter-converting conformations1. Knowledge of dynamic ensembles is key for understanding how biomolecules fold and function, and for rationally manipulating their activities in drug discovery and synthetic biology2–4. However, solving dynamic ensembles of biomolecules at atomic resolution is a major challenge in structural biology because the information required to specify the position of all atoms in thousands of conformations in an ensemble far exceeds the information content of experimental measurements. Here we addressed the data gap and dramatically simplified and accelerated RNA ensemble determination by using structure prediction tools that leverage the growing database of RNA structures to generate a conformational library. Library refinement with NMR residual dipolar couplings enabled determination of an atomic-resolution ensemble for HIV-1 TAR as confirmed by quantum-mechanical calculations of NMR chemical shifts, comparison to a crystal structure of a substate, and through the successful redistribution of the ensemble by design using atomic mutagenesis. The ensemble provides an unprecedented view of how bulge residues cooperatively flip out and undergo sugar repuckering to allow the adjoining helices to stack. The generality of this approach will make determination of atomic-resolution RNA ensembles routine.

Reconfigurable structure and tunable transport in synchronized active spinner materials

Ensembles of actuated colloids are excellent model systems to explore emergent out-of-equilibrium structures, complex collective dynamics, and design rules for the next generation materials. Here, we demonstrate that ferromagnetic microparticles suspended at an air-water interface and energized by an external rotating magnetic field spontaneously form dynamic ensembles of synchronized spinners in a certain range of the excitation field parameters. Each spinner generates strong hydrodynamic flows, and collective interactions of the multiple spinners promote a formation of dynamic lattices. On the basis of experiments and simulations, we reveal structural transitions from liquid to nearly crystalline states in this novel active spinner material and demonstrate that dynamic spinner lattices are reconfigurable, capable of self-healing behavior and that the transport of embedded inert cargo particles can be remotely tuned by the parameters of the external excitation field. Our findings provide insights into the behavior of active spinner materials with reconfigurable structural order and tunable functionalities.

Clustering and Sampling of the c-Met Conformational Space: A Computational Drug Discovery Study

Background: c-Met kinase plays a critical role in a myriad of human cancers, and a massive scientific work was devoted to design more potent inhibitors. Objective: In this study, 16 molecular dynamics simulations of different complexes of potent c-Met inhibitors with U-shaped binding mode were carried out regarding the dynamic ensembles to design novel potent inhibitors. Methods: A cluster analysis was performed, and the most representative frame of each complex was subjected to the structure-based pharmacophore screening. The GOLD docking program investigated the interaction energy and pattern of output hits from the virtual screening. The most promising hits with the highest scoring values that showed critical interactions with c-Met were presented for ADME/Tox analysis. Results: The screening yielded 45,324 hits that all of them were subjected to the docking studies and 10 of them with the highest-scoring values having diverse structures were presented for ADME/Tox analyses. Conclusion: The results indicated that all the hits shared critical Pi-Pi stacked and hydrogen bond interactions with Tyr1230 and Met1160 respectively.