A multi-state dynamical process underpins mechano-adaptation in the bacterial flagellar motor

Adaptation is a defining feature of living systems. The bacterial flagellar motor adapts to changes in external mechanical environment by adding or removing torque-generating stator units. However, the molecular mechanism for mechanosensitive motor remodeling remains unclear. Here, we induced stator disassembly using electrorotation, followed by the time-dependent assembly of the individual stator units into the motor. From these experiments, we extracted detailed statistics of the dwell times underlying the stochastic dynamics of stator unit binding and unbinding. The dwell time distribution contains multiple timescales, indicating the existence of multiple stator unit states. Based on these results, we propose a minimal model with four stator unit states – two bound states with different unbinding rates, a diffusive unbound state, and a recently described transiently detached state. Our minimal model quantitatively explains multiple features of the experimental data and allows us to determine the transition rates between all four states. Our experiments and modeling point towards an emergent picture for mechano-adaptive remodeling of the bacterial flagellar motor in which torque generated by bound stator units controls their effective unbinding rate by modulating the transition between the two bound states. Furthermore, the binding rate of stator units with the motor has a non-monotonic dependence on the number of bound units, likely due to two counter-acting effects of motor’s rotation on the binding process.

Automated detection and analysis of surface calving waves with a terrestrial radar interferometer at the front of Eqip Sermia, Greenland

Glacier calving is a key dynamical process of the Greenland Ice Sheet and a major driver of its increasing mass loss. Calving waves, generated by the sudden detachment of ice from the glacier terminus, can reach tens of meters in height and provide very valuable insights into quantifying calving activity. In this study, we present a new method for the detection of source location, timing, and magnitude of calving waves using a terrestrial radar interferometer. This method was applied to 11 500 1 min interval acquisitions from Eqip Sermia, West Greenland, in July 2018. Over 7 d, more than 2000 calving waves were detected, including waves generated by submarine calving, which are difficult to observe with other methods. Quantitative assessment with a wave power index (WPI) yields a higher wave activity (+49 %) and higher temporally cumulated WPI (+34 %) in deep water than under shallow conditions. Subglacial meltwater plumes, occurring 2.3 times more often in the deep sector, increase WPI and the number of waves by a factor of 1.8 and 1.3, respectively, in the deep and shallow sector. We therefore explain the higher calving activity in the deep sector by a combination of more frequent meltwater plumes and more efficient calving enhancement linked with better connections to warm deep ocean water.

Exact solvability and two-frequency Rabi oscillation in cavity-QED setup with moving emitter

In this paper, we investigate the energy spectrum and coherent dynamical process in a cavity-QED setup with a moving emitter, which is subject to a harmonic potential. We find that the vibration of the emitter will induce the effective Kerr and optomechanical interactions. With the assistance of Bogliubov operators approach, we obtain the energy spectrum of the system exactly. Furthermore, we show that the dynamics of the system exhibit a two-frequency Rabi oscillation behavior. We explain such behavior by optomechanical interaction induced quantum transition between emitter-cavity dressed states. We hope that the interaction between cavity mode and moving emitter will provide a versatile platform to explore more exotic effects and potential applications in cavity-QED scenario.

Investigations of Sizes and Dynamical Motions of Solar Photospheric Granules by a Novel Granular Segmenting Algorithm

Granules observed in the solar photosphere are believed to be convective and turbulent, but the physical picture of the granular dynamical process remains unclear. Here we performed an investigation of granular dynamical motions of full length scales based on data obtained by the 1 m New Vacuum Solar Telescope and the 1.6 m Goode Solar Telescope. We developed a new granule segmenting method, which can detect both small faint and large bright granules. A large number of granules were detected, and two critical sizes, 265 and 1420 km, were found to separate the granules into three length ranges. The granules with sizes above 1420 km follow Gaussian distribution, and demonstrate flat in flatness function, which shows that they are non-intermittent and thus are dominated by convective motions. Small granules with sizes between 265 and 1420 km are fitted by a combination of power-law function and Gauss function, and exhibit nonlinearity in flatness function, which reveals that they are in the mixing motions of convection and turbulence. Mini granules with sizes below 265 km follow the power-law distribution and demonstrate linearity in flatness function, indicating that they are intermittent and strongly turbulent. These results suggest that a cascade process occurs: large granules break down due to convective instability, which transports energy into small ones; then turbulence is induced and grows, which competes with convection and further causes the small granules to continuously split. Eventually, the motions in even smaller scales enter in a turbulence-dominated regime.

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Making good decisions requires updating beliefs according to new evidence. This is a dynamical process that is prone to biases: in some cases, beliefs become entrenched and resistant to new evidence (leading to primacy effects), while in other cases, beliefs fade over time and rely primarily on later evidence (leading to recency effects). How and why either type of bias dominates in a given context is an important open question. Here, we study this question in classic perceptual decision-making tasks, where, puzzlingly, previous empirical studies differ in the kinds of biases they observe, ranging from primacy to recency, despite seemingly equivalent tasks. We present a new model, based on hierarchical approximate inference and derived from normative principles, that not only explains both primacy and recency effects in existing studies, but also predicts how the type of bias should depend on the statistics of stimuli in a given task. We verify this prediction in a novel visual discrimination task with human observers, finding that each observer’s temporal bias changed as the result of changing the key stimulus statistics identified by our model. The key dynamic that leads to a primacy bias in our model is an overweighting of new sensory information that agrees with the observer’s existing belief—a type of ‘confirmation bias’. By fitting an extended drift-diffusion model to our data we rule out an alternative explanation for primacy effects due to bounded integration. Taken together, our results resolve a major discrepancy among existing perceptual decision-making studies, and suggest that a key source of bias in human decision-making is approximate hierarchical inference.

The Dynamics of Coupled Oscillators

<p>The subject is introduced by considering the treatment of oscillators in Mathematics from the simple Poincar´e oscillator, a single variable dynamical process defined on a circle, to the oscillatory dynamics of systems of differential equations. Some models of real oscillator systems are considered. Noise processes are included in the dynamics of the system. Coupling between oscillators is investigated both in terms of analytical systems and as coupled oscillator models. It is seen that driven oscillators can be used as a model of 2 coupled oscillators in 2 and 3 dimensions due to the dependence of the dynamics on the phase difference of the oscillators. This means that the dynamics are easily able to be modelled by a 1D or 2D map. The analysis of N coupled oscillator systems is also described. The human cardiovascular system is studied as an example of a coupled oscillator system. The heart oscillator system is described by a system of delay differential equations and the dynamics characterised. The mechanics of the coupling with the respiration is described. In particular the model of the heart oscillator includes the baroreceptor reflex with time delay whereby the aortic fluid pressure influences the heart rate and the peripheral resistance. Respiration is modelled as forcing the heart oscillator system. Locking zones caused by respiratory sinus arrhythmia (RSA), the synchronisation of the heart with respiration, are found by plotting the rotation number against respiration frequency. These are seen to be relatively narrow for typical physiological parameters and only occur for low ratios of heart rate to respiration frequency. Plots of the diastolic pressure and heart interval in terms of respiration phase parameterised by respiration frequency illustrate the dynamics of synchronisation in the human cardiovascular system.</p>

The Dynamics of Coupled Oscillators

<p>The subject is introduced by considering the treatment of oscillators in Mathematics from the simple Poincar´e oscillator, a single variable dynamical process defined on a circle, to the oscillatory dynamics of systems of differential equations. Some models of real oscillator systems are considered. Noise processes are included in the dynamics of the system. Coupling between oscillators is investigated both in terms of analytical systems and as coupled oscillator models. It is seen that driven oscillators can be used as a model of 2 coupled oscillators in 2 and 3 dimensions due to the dependence of the dynamics on the phase difference of the oscillators. This means that the dynamics are easily able to be modelled by a 1D or 2D map. The analysis of N coupled oscillator systems is also described. The human cardiovascular system is studied as an example of a coupled oscillator system. The heart oscillator system is described by a system of delay differential equations and the dynamics characterised. The mechanics of the coupling with the respiration is described. In particular the model of the heart oscillator includes the baroreceptor reflex with time delay whereby the aortic fluid pressure influences the heart rate and the peripheral resistance. Respiration is modelled as forcing the heart oscillator system. Locking zones caused by respiratory sinus arrhythmia (RSA), the synchronisation of the heart with respiration, are found by plotting the rotation number against respiration frequency. These are seen to be relatively narrow for typical physiological parameters and only occur for low ratios of heart rate to respiration frequency. Plots of the diastolic pressure and heart interval in terms of respiration phase parameterised by respiration frequency illustrate the dynamics of synchronisation in the human cardiovascular system.</p>

Creation of complex composites from Metal-Organic Frameworks with pure metal nanoparticles under electronic irradiation

Metal-organic frameworks (MOFs) are unique materials with high porosity and flexibility utilized widely in chemistry and physics. However, they could be used as initial materials for creation new types of composites with nanoparticles. The creation of NPs inside MOFs crystals is related with different types of outer stimuli (temperature, light, and electron irradiation). Here we report about a new approach of the creation complex composites from MOFs’ crystals using the electron irradiation of the transmission electron microscope (TEM) as a highly precise method for the growing of different types of Ni and Cu nanoparticles and discuss about the dynamical process of NPs growth using the classical kinetic theory.

The Robustness of Interdependent Directed Networks With Intra-layer Angular Correlations

The robustness of interdependent networks is a frontier topic in current network science. A line of studies has so far been investigated in the perspective of correlated structures on robustness, such as degree correlations and geometric correlations in interdependent networks, in-out degree correlations in interdependent directed networks, and so on. Advances in network geometry point that hyperbolic properties are also hidden in directed structures, but few studies link those features to the dynamical process in interdependent directed networks. In this paper, we discuss the impact of intra-layer angular correlations on robustness from the perspective of embedding interdependent directed networks into hyperbolic space. We find that the robustness declines as increasing intra-layer angular correlations under targeted attacks. Interdependent directed networks without intra-layer angular correlations are always robust than those with intra-layer angular correlations. Moreover, empirical networks also support our findings: the significant intra-layer angular correlations are hidden in real interdependent directed networks and contribute to the prediction of robustness. Our work sheds light that the impact of intra-layer angular correlations should be attention, although in-out degree correlations play a positive role in robustness. In particular, it provides an early warning indicator by which the system decoded the intrinsic rules for designing efficient and robust interacting directed networks.

Exploring the “Dark Matter” of Social Interaction: Systematic Review of a Decade of Research in Spontaneous Interpersonal Coordination

Interpersonal coordination is a research topic that has attracted considerable attention this last decade both due to a theoretical shift from intra-individual to inter-individual processes and due to the development of new methods for recording and analyzing movements in ecological settings. Encompassing spatiotemporal behavioral matching, interpersonal coordination is considered as “social glue” due to its capacity to foster social bonding. However, the mechanisms underlying this effect are still unclear and recent findings suggest a complex picture. Goal-oriented joint action and spontaneous coordination are often conflated, making it difficult to disentangle the role of joint commitment from unconscious mutual attunement. Consequently, the goals of the present article are twofold: (1) to illustrate the rapid expansion of interpersonal coordination as a research topic and (2) to conduct a systematic review of spontaneous interpersonal coordination, summarizing its latest developments and current challenges this last decade. By applying Rapid Automatic Keyword Extraction and Latent Dirichlet Allocation algorithms, keywords were extracted from PubMed and Scopus databases revealing the large diversity of research topics associated with spontaneous interpersonal coordination. Using the same databases and the keywords “behavioral matching,” “interactional synchrony,” and “interpersonal coordination,” 1,213 articles were identified, extracted, and screened following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. A total of 19 articles were selected using the following inclusion criteria: (1) dynamic and spontaneous interactions between two unacquainted individuals (2) kinematic analyses, and (3) non-clinical and non-expert adult populations. The results of this systematic review stress the proliferation of various definitions and experimental paradigms that study perceptual and/or social influences on the emergence of spontaneous interpersonal coordination. As methods and indices used to quantify interpersonal coordination differ from one study to another, it becomes difficult to establish a coherent picture. This review highlights the need to reconsider interpersonal coordination not as the pinnacle of social interactions but as a complex dynamical process that requires cautious interpretation. An interdisciplinary approach is necessary for building bridges across scattered research fields through opening a dialogue between different theoretical frameworks and consequently provides a more ecological and holistic understanding of human social cognition.