Revealing Topological Barriers against Knot Untying in Thermal and Mechanical Protein Unfolding by Molecular Dynamics Simulations

The knot is one of the most remarkable topological features identified in an increasing number of proteins with important functions. However, little is known about how the knot is formed during protein folding, and untied or maintained in protein unfolding. By means of all-atom molecular dynamics simulation, here we employ methyltransferase YbeA as the knotted protein model to analyze changes of the knotted conformation coupled with protein unfolding under thermal and mechanical denaturing conditions. Our results show that the trefoil knot in YbeA is occasionally untied via knot loosening rather than sliding under enhanced thermal fluctuations. Through correlating protein unfolding with changes in the knot position and size, several aspects of barriers that jointly suppress knot untying are revealed. In particular, protein unfolding is always prior to knot untying and starts preferentially from separation of two α-helices (α1 and α5), which protect the hydrophobic core consisting of β-sheets (β1–β4) from exposure to water. These β-sheets form a loop through which α5 is threaded to form the knot. Hydrophobic and hydrogen bonding interactions inside the core stabilize the loop against loosening. In addition, residues at N-terminal of α5 define a rigid turning to impede α5 from sliding out of the loop. Site mutations are designed to specifically eliminate these barriers, and easier knot untying is achieved under the same denaturing conditions. These results provide new molecular level insights into the folding/unfolding of knotted proteins.

Investigations of regularities in the accumulation of hydrogen-reduced slags in circulation circuits with lead-containing coolants

The paper presents a computational analysis of regularities in the accumulation of slags during the interaction of lead and lead-bismuth coolants with oxygen gas. Oxidation of lead-containing coolants will cause the formation of lead oxide, while the formation of bismuth oxide is unlikely. Dosed supply of oxidizing gas to lead-containing coolants makes it possible to oxidize, selectively, chromium and nickel to their oxides without the slag formation from solid lead oxide. Regularities were studied which are involved in the lead oxide formation during the interaction of lead-containing coolants with oxygen gas. It has been found that, in the process of interacting with oxygen gas, a lead-bismuth alloy is oxidized 1.7 times as intensively as lead, this being explained by the presence of bismuth in the alloy. Bismuth is oxidized more intensively than both lead and the lead-bismuth alloy. The inert gas overpressure during depressurization does not prevent air oxygen from entering the circuit, and the dependence of the nitrogen and oxygen flow into the circuit on the argon flow out of the loop is close to linear regardless of the circuit state (cold, without coolant; heated, without coolant; heated, with circulating coolant). Oxygen is a chemically active impurity and is absorbed by the circuit; it is therefore important to control nitrogen in the gas spaces of the reactor and research plant circuits with lead-containing coolants. This will make it possible to signal, in a timely manner, the ingress of oxygen into the circuit and to take measures required to avoid or reduce the scale of the slag formation from lead oxides.

The Relationship Between Takeover Request Lead Time and Drivers’ Situation Awareness for Freeway Exiting in Conditionally Automated Driving

Conditionally automated vehicles require the out-of-the-loop driver to intervene when the system is unable to handle forthcoming situations, such as freeway exiting. The takeover request (ToR) for exiting a freeway can be scheduled in advance. Upon a ToR, the driver needs to gain situation awareness (SA) and resume manual control. This study examined how the ToR lead time affects driver SA for resuming control and when to send the ToR is most appropriate for freeway exiting. A web-based, supervised experiment was conducted with 31 participants. Each participant experienced 12 levels of ToR lead time (6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 45, and 60 s). The results showed positive effects of longer ToR lead times (16–60 s) on driver SA for resuming control to exit from freeways in comparison to shorter ToR lead times (6–14 s), and the effects level off at 16–30 s.

Evolution of Activation Functions: An Empirical Investigation

The hyper-parameters of a neural network are traditionally designed through a time-consuming process of trial and error that requires substantial expert knowledge. Neural Architecture Search algorithms aim to take the human out of the loop by automatically finding a good set of hyper-parameters for the problem at hand. These algorithms have mostly focused on hyper-parameters such as the architectural configurations of the hidden layers and the connectivity of the hidden neurons, but there has been relatively little work on automating the search for completely new activation functions, which are one of the most crucial hyperparameters to choose. There are some widely used activation functions nowadays that are simple and work well, but nonetheless, there has been some interest in finding better activation functions. The work in the literature has mostly focused on designing new activation functions by hand or choosing from a set of predefined functions while this work presents an evolutionary algorithm to automate the search for completely new activation functions. We compare these new evolved activation functions to other existing and commonly used activation functions. The results are favorable and are obtained from averaging the performance of the activation functions found over 30 runs, with experiments being conducted on 10 different datasets and architectures to ensure the statistical robustness of the study.

Out of the loop? On the radical and the routine in urban big data

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

Mind Wandering Influences EEG Signal in Complex Multimodal Environments

The phenomenon of mind wandering (MW), as a family of experiences related to internally directed cognition, heavily influences vigilance evolution. In particular, humans in teleoperations monitoring partially automated fleet before assuming manual control whenever necessary may see their attention drift due to internal sources; as such, it could play an important role in the emergence of out-of-the-loop (OOTL) situations and associated performance problems. To follow, quantify, and mitigate this phenomenon, electroencephalogram (EEG) systems already demonstrated robust results. As MW creates an attentional decoupling, both ERPs and brain oscillations are impacted. However, the factors influencing these markers in complex environments are still not fully understood. In this paper, we specifically addressed the possibility of gradual emergence of attentional decoupling and the differences created by the sensory modality used to convey targets. Eighteen participants were asked to (1) supervise an automated drone performing an obstacle avoidance task (visual task) and (2) respond to infrequent beeps as fast as possible (auditory task). We measured event-related potentials and alpha waves through EEG. We also added a 40-Hz amplitude modulated brown noise to evoke steady-state auditory response (ASSR). Reported MW episodes were categorized between task-related and task-unrelated episodes. We found that N1 ERP component elicited by beeps had lower amplitude during task-unrelated MW, whereas P3 component had higher amplitude during task-related MW, compared with other attentional states. Focusing on parieto-occipital regions, alpha-wave activity was higher during task-unrelated MW compared with others. These results support the decoupling hypothesis for task-unrelated MW but not task-related MW, highlighting possible variations in the “depth” of decoupling depending on MW episodes. Finally, we found no influence of attentional states on ASSR amplitude. We discuss possible reasons explaining why. Results underline both the ability of EEG to track and study MW in laboratory tasks mimicking ecological environments, as well as the complex influence of perceptual decoupling on operators' behavior and, in particular, EEG measures.