Structural Plasticity of the Selectivity Filter in Cation Channels

Ion channels allow for the passage of ions across biological membranes, which is essential for the functioning of a cell. In pore loop channels the selectivity filter (SF) is a conserved sequence that forms a constriction with multiple ion binding sites. It is becoming increasingly clear that there are several conformations and dynamic states of the SF in cation channels. Here we outline specific modes of structural plasticity observed in the SFs of various pore loop channels: disorder, asymmetry, and collapse. We summarize the multiple atomic structures with varying SF conformations as well as asymmetric and more dynamic states that were discovered recently using structural biology, spectroscopic, and computational methods. Overall, we discuss here that structural plasticity within the SF is a key molecular determinant of ion channel gating behavior.

Developmental Changes in Dynamic Functional Connectivity From Childhood Into Adolescence

The longitudinal study of typical neurodevelopment is key for understanding deviations due to specific factors, such as psychopathology. However, research utilizing repeated measurements remains scarce. Resting-state functional magnetic resonance imaging (MRI) studies have traditionally examined connectivity as ‘static’ during the measurement period. In contrast, dynamic approaches offer a more comprehensive representation of functional connectivity by allowing for different connectivity configurations (time varying connectivity) throughout the scanning session. Our objective was to characterize the longitudinal developmental changes in dynamic functional connectivity in a population-based pediatric sample. Resting-state MRI data were acquired at the ages of 10 (range 8-to-12, n = 3,327) and 14 (range 13-to-15, n = 2,404) years old using a single, study-dedicated 3 Tesla scanner. A fully-automated spatially constrained group-independent component analysis (ICA) was applied to decompose multi-subject resting-state data into functionally homogeneous regions. Dynamic functional network connectivity (FNC) between all ICA time courses were computed using a tapered sliding window approach. We used a k-means algorithm to cluster the resulting dynamic FNC windows from each scan session into five dynamic states. We examined age and sex associations using linear mixed-effects models. First, independent from the dynamic states, we found a general increase in the temporal variability of the connections between intrinsic connectivity networks with increasing age. Second, when examining the clusters of dynamic FNC windows, we observed that the time spent in less modularized states, with low intra- and inter-network connectivity, decreased with age. Third, the number of transitions between states also decreased with age. Finally, compared to boys, girls showed a more mature pattern of dynamic brain connectivity, indicated by more time spent in a highly modularized state, less time spent in specific states that are frequently observed at a younger age, and a lower number of transitions between states. This longitudinal population-based study demonstrates age-related maturation in dynamic intrinsic neural activity from childhood into adolescence and offers a meaningful baseline for comparison with deviations from typical development. Given that several behavioral and cognitive processes also show marked changes through childhood and adolescence, dynamic functional connectivity should also be explored as a potential neurobiological determinant of such changes.

Research on Exhaust Emissions in Dynamic Operating States of a Combustion Engine in a Real Driving Emissions Test

The paper describes the method of investigations of exhaust emissions from a combustion engine under operation classified in terms of its dynamic states. In this paper, the engine operating states are determined through the vehicle driving under actual traffic conditions in the RDE (Real Driving Emissions) test. Based on the recorded tracings of the vehicle velocity, the engine states were classified as static for the acceleration of the absolute value lower than the adopted classification limit. Besides, the authors analyzed the engine operating states for the positive as well as negative acceleration. For the adopted engine operating states, zero-dimensional characteristics of the emission intensity for individual exhaust components were determined (average value, coefficient of variation). The influence of the analyzed operating states on the emission of individual exhaust components was assessed. The greatest increase in the intensity of the emission of nitrogen oxides was observed for the positive vehicle acceleration model and the lowest (also for the nitrogen oxides) for the negative vehicle acceleration. On average, the greatest increase in the emission intensity of pollutants and the intensity of particle number occurred for the dynamic states of the engine corresponding to positive acceleration. The conclusions from the performed investigations entitle the authors to propose a greater allowance for the exhaust emission-related criteria in the engine control algorithms.

Secure Dynamic State Estimation for Cyber Security of AC Microgrids

A timely, accurate, and secure dynamic state estimation is needed for reliable monitoring and efficient control of microgrids. The synchrophasor technology enables system operators to obtain synchronized measurements in real-time and to develop dynamic state estimators for monitoring and control of microgrids. However, in practice, sensor measurements can be corrupted or attacked. In this study, we consider an AC microgrid comprising several synchronous generators and inverter-interface power supplies, and focus on securely estimating the dynamic states of the microgrid from a set of corrupted data. We propose a secure dynamic state estimator which allows the microgrid operator to reconstruct the dynamic states of the microgrid from a set of attacked or corrupted data without any assumption on attacks or corruptions. Finally, we consider an AC microgrid with the same topology as the IEEE 33-bus distribution system, and show that the proposed secure estimation algorithm can accurately reconstruct the attack signals.

Nonlinear Dynamics of Two-State Quantum Dot Lasers under Optical Feedback

A modified rate equation model was presented to theoretically investigate the nonlinear dynamics of solitary two-state quantum dot lasers (TSQDLs) under optical feedback. The simulated results showed that, for a TSQDL biased at a relatively high current, the ground-state (GS) and excited-state (ES) lasing of the TSQDL can be stimulated simultaneously. After introducing optical feedback, both GS lasing and ES lasing can exhibit rich nonlinear dynamic states including steady state (S), period one (P1), period two (P2), multi-period (MP), and chaotic (C) state under different feedback strength and phase offset, respectively, and the dynamic states for the two lasing types are always identical. Furthermore, the influences of the linewidth enhancement factor (LEF) on the nonlinear dynamical state distribution of TSQDLs in the parameter space of feedback strength and phase offset were also analyzed. For a TSQDL with a larger LEF, much more dynamical states can be observed, and the parameter regions for two lasing types operating at chaotic state are widened after introducing optical feedback.

Estimation of Wind Turbine Gearbox Loads for Online Fatigue Monitoring Using Inverse Methods

In this article a novel approach for the estimation of wind turbine gearbox loads with the purpose of online fatigue damage monitoring is presented. The proposed method employs a Digital Twin framework and aims at continuous estimation of the dynamic states based on CMS vibration data and generator torque measurements from SCADA data. With knowledge of the dynamic states local loads at gearbox bearings are easily determined and fatigue models are be applied to track the accumulation of fatigue damage. A case study using simulation measurements from a high-fidelity gearbox model is conducted to evaluate the proposed method. Estimated loads at the considered IMS and HSS bearings show moderate to high correlation (R = 0.50–0.96) to measurements, as lower frequency internal dynamics are not fully captured. The estimated fatigue damage differs by 5–15 % from measurements.

Dynamic Simulation of High-Speed Induction Motor

In the drives of high-speed devices, such as a blood centrifuge, dynamic states also play an important role in terms of the time and quality of the tests performed. The article presents the application of modified equations resulting from the mathematical model of an induction motor to model dynamic phenomena during motor start-up, both with mains supply and with frequency start-up. The applied solution considers the phenomenon of current displacement in the rotor bar and the phenomenon of saturation. The comparison of the obtained results with the experiment shows that the method is sufficiently accurate. The obtained results can also be extended to higher power machines and to modeling other dynamic states.

Selected Properties of High-Frequency Electric Arc Initiators and Stabilisation Oscillators. Part 1. Devices with Free Electric Arc

The article presents selected physical properties of electric arc used in welding engineering as well as discusses differences in requirements concerning ionisers used to initiate and re-initiate electric arc. In addition, the article compares properties of ioniser systems used to stabilise electric arc burning as well as discusses spark gap and semiconductor systems generating high-frequency and high-voltage impulses used to generate spark discharges. The article also discusses the effect of ioniser operation after the modification of static current-voltage characteristics, enabling the modelling of dynamic states of electric arc.

APPLICABILITY OF BRAY-LIEBHAFSKY REACTION FOR CHEMICAL COMPUTING

The first discovered homogeneous oscillatory reaction was the Bray-Liebhafsky (BL) one, described in a paper published exactly 100 years ago. However, the applicability of oscillatory reactions in chemical computing was recently discovered. Here we intend to expose the native computing concept applied to intermittent states of the BL reaction, because we believe that this particular state may have some advantages. For this purpose, numerical simulations will be used based on the known model. Sequences of perturbations will be introduced by adding iodate (IO3-) and hydrogen peroxide (H2O2), separately, as well as in various combinations with one another. It will be shown that dynamic states obtained after perturbations with same species depend very much on the sequence in which these species were used in perturbations. Additionally, it will be shown that obtained dynamic states shift the system from chaotic intermittent dynamic state to different complex periodic states. Hence, the applicability of the BL reaction system in chemical computing was demonstrated.