Light-wave dynamic control of magnetism.

The enigmatic interplay between electronic and magnetic phenomena observed in many early experiments and outlined in Maxwell's equations propelled the development of modern electromagnetism1. Today, the fully controlled evolution of the electric field of ultrashort laser pulses enables the direct and ultrafast tuning of the electronic properties of matter, which is the cornerstone of light-wave electronics2-7. By contrast, owing to the lack of first-order interaction between light and spin, the magnetic properties of matter can only be affected indirectly and on much longer timescales, through a sequence of optical excitations and subsequent rearrangement of the spin structure8-16. Here we introduce the regime of ultrafast coherent magnetism and show how the magnetic properties of a ferromagnetic layer stack can be manipulated directly by the electric-field oscillations of light, reducing the magnetic response time to an external stimulus by two orders of magnitude. To track the unfolding dynamics in real time, we develop an attosecond time-resolved magnetic circular dichroism detection scheme, revealing optically induced spin and orbital momentum transfer in synchrony with light-field-driven coherent charge relocation17. In tandem with ab initio quantum dynamical modelling, we show how this mechanism enables the simultaneous control of electronic and magnetic properties that are essential for spintronic functionality. Our study unveils light-field coherent control of spin dynamics and macroscopic magnetic moments in the initial non-dissipative temporal regime and establishes optical frequencies as the speed limit of future coherent spintronic applications, spin transistors and data storage media.

Complexified synchrony.

The Kuramoto model and its generalizations have been broadly employed to characterize and mechanistically understand various collective dynamical phenomena, especially the emergence of synchrony among coupled oscillators. Despite almost five decades of research, many questions remain open, in particular, for finite-size systems. Here, we generalize recent work [Thümler et al., Phys. Rev. Lett. 130, 187201 (2023)] on the finite-size Kuramoto model with its state variables analytically continued to the complex domain and also complexify its system parameters. Intriguingly, systems of two units with purely imaginary coupling do not actively synchronize even for arbitrarily large magnitudes of the coupling strengths, |K|→∞, but exhibit conservative dynamics with asynchronous rotations or librations for all |K|. For generic complex coupling, both traditional phase-locked states and asynchronous states generalize to complex locked states, fixed points off the real subspace that exist even for arbitrarily weak coupling. We analyze a new collective mode of rotations exhibiting finite, yet arbitrarily large rotation numbers. Numerical simulations for large networks indicate a novel form of discontinuous phase transition. We close by pointing to a range of exciting questions for future research.

Synchrony for Weak Coupling in the Complexified Kuramoto Model.

We present the finite-size Kuramoto model analytically continued from real to complex variables and analyze its collective dynamics. For strong coupling, synchrony appears through locked states that constitute attractors, as for the real-variable system. However, synchrony persists in the form of complex locked states for coupling strengths K below the transition K^{(pl)} to classical phase locking. Stable complex locked states indicate a locked subpopulation of zero mean frequency in the real-variable model and their imaginary parts help identifying which units comprise that subpopulation. We uncover a second transition at K^{'}

High-dose methylprednisolone pulse therapy during refractory COVID-19 acute respiratory distress syndrome: a retrospective observational study.

BACKGROUND: Current COVID-19 guidelines recommend the early use of systemic corticoids for COVID-19 acute respiratory distress syndrome (ARDS). It remains unknown if high-dose methylprednisolone pulse therapy (MPT) ameliorates refractory COVID-19 ARDS after many days of mechanical ventilation or rapid deterioration with or without extracorporeal membrane oxygenation (ECMO). METHODS: This is a retrospective observational study. Consecutive patients with COVID-19 ARDS treated with a parenteral high-dose methylprednisolone pulse therapy at the intensive care units (ICU) of two University Hospitals between January 1st 2021 and November 30st 2022 were included. Clinical data collection was at ICU admission, start of MPT, 3-, 10- and 14-days post MPT. RESULTS: Thirty-seven patients (mean age 55 ± 12 years) were included in the study. MPT started at a mean of 17 ± 12 days after mechanical ventilation. Nineteen patients (54%) received ECMO support when commencing MPT. Mean paO2/FiO2 significantly improved 3- (p = 0.034) and 10 days (p = 0.0313) post MPT. The same applied to the necessary FiO2 10 days after MPT (p = 0.0240). There were no serious infectious complications. Twenty-four patients (65%) survived to ICU discharge, including 13 out of 20 (65%) needing ECMO support. CONCLUSIONS: Late administration of high-dose MPT in a critical subset of refractory COVID-19 ARDS patients improved respiratory function and was associated with a higher-than-expected survival of 65%. These data suggest that high-dose MPT may be a viable salvage therapy in refractory COVID-19 ARDS.

Obscuring digital route-choice information prevents delay-induced congestion.

Although routing applications increasingly affect individual mobility choices, their impact on collective traffic dynamics remains largely unknown. Smart communication technologies provide accurate traffic data for choosing one route over other alternatives; yet, inherent delays undermine the potential usefulness of such information. Here, we introduce and analyze a simple model of collective traffic dynamics, which results from route choice relying on outdated traffic information. We find for sufficiently small information delays that traffic flows are stable against perturbations. However, delays beyond a bifurcation point induce self-organized flow oscillations of increasing amplitude-congestion arises. Providing delayed information averaged over sufficiently long periods of time or, more intriguingly, reducing the number of vehicles adhering to the route recommendations may prevent such delay-induced congestion. We reveal the fundamental mechanisms underlying these phenomena in a minimal two-road model and demonstrate their generality in microscopic, agent-based simulations of a road network system. Our findings provide a way to conceptually understand system-wide traffic dynamics caused by broadly used non-instantaneous routing information and suggest how resulting unintended collective traffic states could be avoided.

Scaling Laws of Collective Ride-Sharing Dynamics.

Ride-sharing services may substantially contribute to future sustainable mobility. Their collective dynamics intricately depend on the topology of the underlying street network, the spatiotemporal demand distribution, and the dispatching algorithm. The efficiency of ride-sharing fleets is thus hard to quantify and compare in a unified way. Here, we derive an efficiency observable from the collective nonlinear dynamics and show that it exhibits a universal scaling law. For any given dispatcher, we find a common scaling that yields data collapse across qualitatively different topologies of model networks and empirical street networks from cities, islands, and rural areas. A mean-field analysis confirms this view and reveals a single scaling parameter that jointly captures the influence of network topology and demand distribution. These results further our conceptual understanding of the collective dynamics of ride-sharing fleets and support the evaluation of ride-sharing services and their transfer to previously unserviced regions or unprecedented demand patterns.

Adhesion-Induced Discontinuous Transitions and Classifying Social Networks.

Transition points mark qualitative changes in the macroscopic properties of large complex systems. Explosive transitions, exhibiting properties of both continuous and discontinuous phase transitions, have recently been uncovered in network growth processes. Real networks not only grow but often also restructure; yet common network restructuring processes, such as small world rewiring, do not exhibit phase transitions. Here, we uncover a class of intrinsically discontinuous transitions emerging in network restructuring processes controlled by adhesion-the preference of a chosen link to remain connected to its end node. Deriving a master equation for the temporal network evolution and working out an analytic solution, we identify genuinely discontinuous transitions in nongrowing networks, separating qualitatively distinct phases with monotonic and with peaked degree distributions. Intriguingly, our analysis of empirical data indicates a separation between the same two forms of degree distributions distinguishing abstract from face-to-face social networks.

Hysteretic Percolation from Locally Optimal Individual Decisions.

The emergence of large-scale connectivity underlies the proper functioning of many networked systems, ranging from social networks and technological infrastructure to global trade networks. Percolation theory characterizes network formation following stochastic local rules, while optimization models of network formation assume a single controlling authority or one global objective function. In socioeconomic networks, however, network formation is often driven by individual, locally optimal decisions. How such decisions impact connectivity is only poorly understood to date. Here, we study how large-scale connectivity emerges from decisions made by rational agents that individually minimize costs for satisfying their demand. We establish that the solution of the resulting nonlinear optimization model is exactly given by the final state of a local percolation process. This allows us to systematically analyze how locally optimal decisions on the microlevel define the structure of networks on the macroscopic scale.

Quantifying transient spreading dynamics on networks.

Spreading phenomena on networks are essential for the collective dynamics of various natural and technological systems, from information spreading in gene regulatory networks to neural circuits and from epidemics to supply networks experiencing perturbations. Still, how local disturbances spread across networks is not yet quantitatively understood. Here, we analyze generic spreading dynamics in deterministic network dynamical systems close to a given operating point. Standard dynamical systems' theory does not explicitly provide measures for arrival times and amplitudes of a transient spreading signal because it focuses on invariant sets, invariant measures, and other quantities less relevant for transient behavior. We here change the perspective and introduce formal expectation values for deterministic dynamics to work out a theory explicitly quantifying when and how strongly a perturbation initiated at one unit of a network impacts any other. The theory provides explicit timing and amplitude information as a function of the relative position of initially perturbed and responding unit as well as depending on the entire network topology.

A universal order parameter for synchrony in networks of limit cycle oscillators.

We analyze the properties of order parameters measuring synchronization and phase locking in complex oscillator networks. First, we review network order parameters previously introduced and reveal several shortcomings: none of the introduced order parameters capture all transitions from incoherence over phase locking to full synchrony for arbitrary, finite networks. We then introduce an alternative, universal order parameter that accurately tracks the degree of partial phase locking and synchronization, adapting the traditional definition to account for the network topology and its influence on the phase coherence of the oscillators. We rigorously prove that this order parameter is strictly monotonously increasing with the coupling strength in the phase locked state, directly reflecting the dynamic stability of the network. Furthermore, it indicates the onset of full phase locking by a diverging slope at the critical coupling strength. The order parameter may find applications across systems where different types of synchrony are possible, including biological networks and power grids.

Synchronizing noisy nonidentical oscillators by transient uncoupling.

Synchronization is the process of achieving identical dynamics among coupled identical units. If the units are different from each other, their dynamics cannot become identical; yet, after transients, there may emerge a functional relationship between them-a phenomenon termed "generalized synchronization." Here, we show that the concept of transient uncoupling, recently introduced for synchronizing identical units, also supports generalized synchronization among nonidentical chaotic units. Generalized synchronization can be achieved by transient uncoupling even when it is impossible by regular coupling. We furthermore demonstrate that transient uncoupling stabilizes synchronization in the presence of common noise. Transient uncoupling works best if the units stay uncoupled whenever the driven orbit visits regions that are locally diverging in its phase space. Thus, to select a favorable uncoupling region, we propose an intuitive method that measures the local divergence at the phase points of the driven unit's trajectory by linearizing the flow and subsequently suppresses the divergence by uncoupling.

Transient Uncoupling Induces Synchronization.

Finding conditions that support synchronization is a fertile and active area of research with applications across multiple disciplines. Here we present and analyze a scheme for synchronizing chaotic dynamical systems by transiently uncoupling them. Specifically, systems coupled only in a fraction of their state space may synchronize even if fully coupled they do not. While for many standard systems coupling strengths need to be bounded to ensure synchrony, transient uncoupling removes this bound and thus enables synchronization in an infinite range of effective coupling strengths. The presented coupling scheme therefore opens up the possibility to induce synchrony in (biological or technical) systems whose parameters are fixed and cannot be modified continuously.

Selective apheresis of C-reactive protein: a new therapeutic option in myocardial infarction?

BACKGROUND: There is substantial evidence that C-reactive protein (CRP) mediates secondary damage of the myocardium after acute myocardial infarction (AMI). The aim of this animal trial in pigs was to specifically deplete CRP from porcine plasma after AMI and to study possible beneficial effects of the reduced CRP concentration on the infarcted area. METHODS: Ten pigs received balloon catheter-induced myocardial infarction. CRP was depleted from five animals utilizing a new specific CRP-adsorber, five animals served as controls. The area of infarction was analyzed by cardiovascular magnetic resonance imaging on day 1 and day 14 after AMI. Porcine CRP levels were determined by ELISA. RESULTS: CRP-apheresis resulted in a mean reduction of the CRP levels up to 48.3%. The area of infarction was significantly reduced by 30 ± 6% (P = 0.003) within 14 days in the treatment group, whereas it increased by 19 ± 11% (P = 0.260) in the controls. Fourteen days after infarction, the infarcted area revealed compact, transmural scars in the controls, whereas animals receiving CRP-apheresis showed spotted scar morphology. In the interventional group, a significantly higher left ventricular ejection fraction (LVEF) was observed after 14 days as compared to the controls (57.6 ± 2.4% vs. 46.4 ± 2.7%; P = 0.007). CONCLUSIONS: In a pig model for AMI, we observed that selective CRP-apheresis significantly reduces CRP levels and the volume of the infarction zone after AMI. Additionally, it changes the morphology of the scars and preserves cardiac output (LVEF).

Microtransition cascades to percolation.

We report the discovery of a discrete hierarchy of microtransitions occurring in models of continuous and discontinuous percolation. The precursory microtransitions allow us to target almost deterministically the location of the transition point to global connectivity. This extends to the class of intrinsically stochastic processes the possibility to use warning signals anticipating phase transitions in complex systems.

Efficient self-organization of informal public transport networks.

The Global South, encompassing more than 80% of the world population, heavily relies on informal paratransit services with ad-hoc routes. Yet, it remains unclear how efficiently such informal public transport services organize and operate. Here, we analyze and compare the structural efficiency of more than 7000 formal and informal bus service routes in 36 cities across 22 countries globally. Intriguingly, informal transport self-organizes in ways at or above efficiency levels of centralized services. They exhibit fewer detours, more uniform paths, and comparable interconnectivities, all while remaining profitable without the major subsidies common in the Global North. These insights challenge the global perception of informal transport as an inferior alternative to centrally organized services. More generally, analyzing large-scale microscopic transport data and condensing them into informative macroscopic observables may qualitatively improve system understanding and reveal specific options to create more accessible, efficient, and sustainable public transport solutions.

Exponential adoption of battery electric cars.

The adoption of battery electric vehicles (BEVs) may significantly reduce greenhouse gas emissions caused by road transport. However, there is wide disagreement as to how soon battery electric vehicles will play a major role in overall transportation. Focusing on battery electric passenger cars, we analyze BEV adoption across 17 individual countries, Europe, and the World, and consistently find exponential growth trends. Modeling-based estimates of future adoption given past trends suggest system-wide adoption substantially faster than typical economic analyses have proposed so far. For instance, we estimate the majority of passenger cars in Europe to be electric by about 2031. Within regions, the predicted times of mass adoption are largely insensitive to model details. Despite significant differences in current electric fleet sizes across regions, their growth rates consistently indicate fast doubling times of approximately 15 months, hinting at radical economic and infrastructural consequences in the near future.

Retrograde drilling of talar osteochondritis dissecans lesions: a feasibility and accuracy analysis of a novel electromagnetic navigation method versus a standard fluoroscopic method.

PURPOSE: A novel method using an electromagnetic navigation system (ENS) was developed, and its feasibility and accuracy for retrograde drilling procedures were evaluated and compared with the standard freehand fluoroscopic method in an experimental setting. METHODS: A controlled laboratory study of 16 standard freehand fluoroscopically guided and 16 electromagnetically navigated retrograde drilling procedures was performed on 4 cadaveric human ankle joints. Four artificial cartilage lesions were consecutively set, 2 on the medial and 2 on the lateral talar dome. Drilling accuracy was measured in terms of the distance from the final position of the drill bit to the tip of the probe hook and the distance between the tip of the drill bit and the center of the cartilage lesion on the articular cartilage surface. Intraoperative fluoroscopy exposure times were documented, as were readjustments of drilling directions or complete restarts. All procedures were timed with a stopwatch. RESULTS: Successful retrograde drilling was accomplished in 12 cases with the standard fluoroscopy-guided technique and in all 16 ENS-guided procedures. The overall mean time for the fluoroscopy-guided procedures was 660.00 ± 239.87 seconds and the overall mean time for the ENS method was 308.06 ± 54.03 seconds, providing a mean time benefit of 420.13 seconds. The mean distance from the final position of the drill bit to the tip of the probe hook was 3.25 ± 1.29 mm for the standard method and 2.19 ± 0.54 mm for the ENS method, and the mean distance between the tip of the drill bit and the center of the cartilage lesion on the articular cartilage surface was 2.50 ± 0.97 mm for the standard method and 0.88 ± 0.81 mm for the ENS method. CONCLUSIONS: Compared with the standard fluoroscopic technique, the ENS method used in this study showed higher accuracy and a shorter procedure time and required no X-ray radiation. CLINICAL RELEVANCE: The novel method considerably improves on the standard operating procedure in terms of safety, operation time, and radiation exposure.

Arthroscopically assisted retrograde drilling for osteochondritis dissecans (OCD) lesions of the knee.

PURPOSE: Accurate retrograde drilling for osteochondritis dissecans lesions remains technically challenging. A novel, radiation-free method using an electromagnetic guidance system was developed, and its feasibility and accuracy for retrograde drilling procedures evaluated in an experimental setting. METHODS: Sixteen arthroscopically assisted, electromagnetically guided retrograde drilling procedures were performed in 4 human cadaveric knee joints. Therefore, two artificial cartilage lesions were set consecutively on each condyle. Final drill bit position was documented in two planes using fluoroscopy. Subsequently, drilling accuracy was measured in terms of distance from the final position of the drill bit to the articular cartilage surface (D1), and distance between the tip of the drill bit to the centre of the cartilage lesion on the articular cartilage surface (D2). All procedures were timed using a stopwatch. RESULTS: Successful retrograde drilling was accomplished in all 16 cases. The overall mean time for the retrograde drilling procedures was 361.6 ± 34.7 s. Mean D1 was 2.2 ± 0.5 mm; mean D2 was 0.8 ± 0.7 mm. No complications occurred. CONCLUSIONS: The novel electromagnetic guidance system used in this study showed accurate targeting results, required no radiation, was associated with no complications and demonstrated user-friendliness. LEVEL OF EVIDENCE: II.

Spontaneous symmetry breaking in ride-sharing adoption dynamics.

Symmetry breaking ubiquitously occurs across complex systems, from phase transition in statistical physics to self-organized lane formation in pedestrian dynamics. Here, we uncover spontaneous symmetry breaking in a simple model of ride-sharing adoption. We analyze how collective interactions among ride-sharing users to avoid detours in shared rides give rise to spontaneous symmetry breaking and pattern formation in the adoption dynamics. These dynamics result in bistability of high homogeneous and partial heterogeneous adoption states, potentially limiting the population-wide adoption of ride sharing. Our results provide a framework to understand real-world adoption patterns of ride sharing in complex urban settings and support the (re)design of ride-sharing services and incentives for sustainable shared mobility.

Collective dynamics of capacity-constrained ride-pooling fleets.

Ride-pooling (or ride-sharing) services combine trips of multiple customers along similar routes into a single vehicle. The collective dynamics of the fleet of ride-pooling vehicles fundamentally underlies the efficiency of these services. In simplified models, the common features of these dynamics give rise to scaling laws of the efficiency that are valid across a wide range of street networks and demand settings. However, it is unclear how constraints of the vehicle fleet impact such scaling laws. Here, we map the collective dynamics of capacity-constrained ride-pooling fleets to services with unlimited passenger capacity and identify an effective fleet size of available vehicles as the relevant scaling parameter characterizing the dynamics. Exploiting this mapping, we generalize the scaling laws of ride-pooling efficiency to capacity-constrained fleets. We approximate the scaling function with a queueing theoretical analysis of the dynamics in a minimal model system, thereby enabling mean-field predictions of required fleet sizes in more complex settings. These results may help to transfer insights from existing ride-pooling services to new settings or service locations.