Concept: Complex number
Multi-level fission-fusion societies, characteristic of a number of large brained mammal species including some primates, cetaceans and elephants, are among the most complex and cognitively demanding animal social systems. Many free-ranging populations of these highly social mammals already face severe human disturbance, which is set to accelerate with projected anthropogenic environmental change. Despite this, our understanding of how such disruption affects core aspects of social functioning is still very limited.
The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player’s advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is [Formula: see text]0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player’s advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent [Formula: see text] characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments.
Information routing is one of the main tasks in many complex networks with a communication function. Maps produced by embedding the networks in hyperbolic space can assist this task enabling the implementation of efficient navigation strategies. However, only static maps have been considered so far, while navigation in more realistic situations, where the network structure may vary in time, remains largely unexplored. Here, we analyze the navigability of real networks by using greedy routing in hyperbolic space, where the nodes are subject to a stochastic activation-inactivation dynamics. We find that such dynamics enhances navigability with respect to the static case. Interestingly, there exists an optimal intermediate activation value, which ensures the best trade-off between the increase in the number of successful paths and a limited growth of their length. Contrary to expectations, the enhanced navigability is robust even when the most connected nodes inactivate with very high probability. Finally, our results indicate that some real networks are ultranavigable and remain highly navigable even if the network structure is extremely unsteady. These findings have important implications for the design and evaluation of efficient routing protocols that account for the temporal nature of real complex networks.
Controlling acoustic fields is crucial in diverse applications such as loudspeaker design, ultrasound imaging and therapy or acoustic particle manipulation. The current approaches use fixed lenses or expensive phased arrays. Here, using a process of analogue-to-digital conversion and wavelet decomposition, we develop the notion of quantal meta-surfaces. The quanta here are small, pre-manufactured three-dimensional units-which we call metamaterial bricks-each encoding a specific phase delay. These bricks can be assembled into meta-surfaces to generate any diffraction-limited acoustic field. We apply this methodology to show experimental examples of acoustic focusing, steering and, after stacking single meta-surfaces into layers, the more complex field of an acoustic tractor beam. We demonstrate experimentally single-sided air-borne acoustic levitation using meta-layers at various bit-rates: from a 4-bit uniform to 3-bit non-uniform quantization in phase. This powerful methodology dramatically simplifies the design of acoustic devices and provides a key-step towards realizing spatial sound modulators.
A direct link between Ca(2+) and lipid homeostasis has not been definitively demonstrated. In this study, we show that manipulation of ER Ca(2+) causes the re-distribution of a portion of the intracellular unesterified cholesterol to a pool that is not available to the SCAP-SREBP complex. The SREBP processing pathway in ER Ca(2+) depleted cells remained fully functional and responsive to changes in cellular cholesterol status but differed unexpectedly in basal activity. These findings establish the role of Ca(2+) in determining the reference set-point for controlling cellular lipid homeostasis. We propose that ER Ca(2+) status is an important determinant of the basal sensitivity of the sterol sensing mechanism inherent to the SREBP processing pathway.
During epithelial morphogenesis, a complex comprising the βPIX (PAK-interacting exchange factor β) and class I PAKs (p21-activated kinases) is recruited to adherens junctions. Scrib, the mammalian ortholog of the Drosophila polarity determinant and tumor suppressor Scribble, binds βPIX directly. Scrib is also targeted to adherens junctions by E-cadherin, where Scrib strengthens cadherin-mediated cell-cell adhesion. Although a role for the Scrib-βPIX-PAK signaling complex in promoting membrane protrusion at wound edges has been elucidated, a function for this complex at adherens junctions remains unknown.
There exists several numerical approaches to describe the active contractile behaviour of skeletal muscles. These models range from simple one-dimensional to more advanced three-dimensional ones; especially, three-dimensional models take up the cause of describing complex contraction modes in a realistic way. However, the validation of such concepts is challenging, as the combination of geometry, material and force characteristics is so far not available from the same muscle. To this end, we present in this study a comprehensive data set of the rabbit soleus muscle consisting of the muscles' characteristic force responses (active and passive), its three-dimensional shape during isometric, isotonic and isokinetic contraction experiments including the spatial arrangement of muscle tissue and aponeurosis-tendon complex, and the fascicle orientation throughout the whole muscle at its optimal length. In this way, an extensive data set is available giving insight into the three-dimensional geometry of the rabbit soleus muscle and, further, allowing to validate three-dimensional numerical models.
Here we report development of the galvanostatic Fourier transform electrochemical impedance spectroscopy (FTEIS), which monitors impedance of electrochemical reactions activated by current steps. We first derive relevant relations for potential change upon application of a step current, obtain impedances theoretically from the relations by simulation, and verify them with experimental results. The validity of the galvanostatic FTEIS technique is demonstrated by measuring impedances of a semiconductive silicon wafer using the conventional frequency response analysis (FRA), the potentiostatic FTEIS and the galvanostatic FTEIS methods, and the results are in excellent agreement with each other. This work is significant in that the galvanostatic FTEIS would allow one to record impedance changes during charge-discharge cycles of secondary batteries and fuel cells as well as electrochemically irreversible systems which may produce noise level chronoamperometric currents by potentiostatic techniques.
There is clear evidence across the globe that the clinical complexity of patients presenting to hospital with the syndrome of heart failure is increasing - not only in terms of the presence of concurrent disease states, but with additional socio-demographic risk factors that complicate treatment. Management strategies that treat heart failure as the main determinant of health outcomes ignores the multiple and complex issues that will inevitably erode the efficacy and efficiency of current heart failure management programmes. This complex problem (or conundrum) requires a different way of thinking around the complex interactions that underpin poor outcomes in heart failure. In this context, we present the COordinated NUrse-led inteNsified Disease management for continuity of caRe for mUltiMorbidity in Heart Failure (CONUNDRUM-HF) matrix that may well inform future research and models of care to achieve better health outcomes in this rapidly increasing patient population.
The synaptic properties of cells define the hallmarks of interval timing in a recurrent neural network
- The Journal of neuroscience : the official journal of the Society for Neuroscience
- Published 4 months ago
Extensive research has described two key features of interval timing. The bias property is associated with accuracy and implies that time is overestimated for short intervals and underestimated for long intervals. The scalar property is linked to precision and states that the variability of interval estimates increases as a function of interval duration. The neural mechanisms behind these properties are not well understood. Here we implemented a recurrent neural network that mimics a cortical ensemble and includes cells that show paired-pulse facilitation and slow inhibitory synaptic currents. The network produces interval selective responses and reproduces both bias and scalar properties when a Bayesian decoder reads its activity. Notably, the interval-selectivity, timing accuracy, and precision of the network showed complex changes as a function of the decay time constants of the modeled synaptic properties and the level of background activity of the cells. These findings suggest that physiological values of the time constants for paired-pulse facilitation and GABAb, as well as the internal state of the network, determine the bias and scalar properties of interval timing.Significant StatementTiming is a fundamental element of complex behavior, including music and language. Temporal processing in a wide variety of contexts shows two primary features: time estimates exhibit a shift towards the mean (the bias property) and are more variable for longer intervals (the scalar property). We implemented a recurrent neural network that includes long-lasting synaptic currents, which can not only produce interval selective responses but also follow the bias and scalar properties. Interestingly, only physiological values of the time constants for paired-pulse facilitation and GABAb, as well as intermediate background activity within the network can reproduce the two key features of interval timing.