Recent experiments on crosslinked gels quenched from solvent-rich to solvent-poor conditions show solvent-rich domains embedded in a gel-rich matrix. These domains coarsen and then undergo kinetic arrest at micron scales for hours, before macroscopic drainage to equilibrium over even longer times. Motivated by these observations, we develop a minimal model that couples capillarity-driven Darcy permeation to the viscoelastic-to-elastic crossover of the polymer network. In the viscoelastic regime, the Young--Laplace traction at curved solvent--gel interfaces generates a pressure gradient in the solvent pores of the gel that drives solvent flow and coarsening. In the elastic regime, the same interfacial traction is balanced by elastic stress. This force balance eliminates pressure gradients in the solvent-filled pores of the gel, removing the Darcy driving force and arresting coarsening. Using the kinetic criterion $t(λ_{\rm arrest}) \sim τ_{\rm el}$, we predict stiffness-dependent coarsening and arrest laws. For melt-like, polymer-rich gels, $λ(t)\sim G^{-1/2} t^{1/4}$ and $λ_{\rm arrest}\sim G^{-1/2}$. For low polymer fractions where the mesh size controls transport, $λ(t)\sim G^{-1
The equilibrium behavior of binary mixtures can be understood through the competition of energy scales, which classifies their corresponding phase diagrams into distinct topological regimes (Types I-IV). However, in many soft-matter mixtures, strong competing interactions and kinetic barriers often promote dynamical arrest, disrupting the formation of equilibrium and metastable states, and thus rendering conventional phase diagrams incomplete. Here we extend the description and classification of binary systems inside regions of thermodynamical instability. Specifically, we discuss how the interplay between two kind of instabilities and kinetic arrest generates a variety of amorphous states driven by different underlying mechanisms. For strong cross-attraction, for example, dynamical arrest suppresses demixing, whereas in competitive regimes, a mixture may display either condensation-driven or demixing-induced arrested states. The crossover between these regimes can be described by a structural order parameter $χ$, providing a unified non-equilibrium description that reconciles theoretical predictions with experimentally observed arrested states.
We investigate Coulomb spin liquids in classical spin-3/2 ice and show that the enlarged on-site Hilbert space gives rise to a qualitatively new class of such phases. Beyond the conventional magnetic monopoles of spin-1/2 ice, the system hosts additional low-energy crystal-field excitations, whose interplay with monopoles significantly modifies both equilibrium and non-equilibrium properties. Following a thermal quench, we find a pronounced dynamical arrest manifested in an exponentially long-lived {athermal} plateau in spin autocorrelations. This constitutes a rare example of dynamical arrest in a short-range interacting, disorder-free system. We demonstrate that the arrested dynamics originate from novel composite excitation structures unique to spin-3/2 ice and from kinetically constrained relaxation pathways that require activated processes. Our results establish higher-spin ice as a fertile platform for realising unconventional Coulomb spin liquids and dynamical arrest without quenched disorder.
We report a phenomenological theory for the kinetic arrest (KA) of a first-order phase transition, taking the Mott metal-insulator transition in $V_2O_3$ as a test case. By defining a order parameter $φ$ related to the monoclinic distortion of the high temperature metallic and mapping its Time-Dependent Ginzburg-Landau (TDGL) dynamics onto a disorder-influenced Imry-Wortis landscape, we derive a universal transcendental condition for the mechanism of the kinetic arrest. We demonstrate that epitaxial substrate-induced clamping in (001)-oriented $V_2O_3$ thin films elevates the elastic activation barriers, trapping the high-symmetry corundum phase down to 4.2~K. This structural suppression of the insulating state robustly explains the observed hysteretic $V$-$I$ switching a hallmark of memristive behaviour. Our work identifies a "Mott-Glass" as a structurally arrested non-equilibrium state in the strained thin-film of V$_2$O$_3$. Our work provides a predictive framework for engineering strain-tuned neuromorphic synapses.
Despite extensive theoretical treatment of short- to long-crack transitions, direct experimental quantification of how elastic and plastic energy contributions evolve at the crack tip during arrest has remained absent. In this study, we present an in situ investigation of crack propagation in cold-worked AA-5052 using high-resolution scanning electron microscopy digital image correlation (SEM-DIC) and electron backscatter diffraction (EBSD). By reconstructing local crack-tip fields from measured displacement data, we extract mode I and II stress intensity factors and both elastic and elastoplastic energy release rates (ΔJE and ΔJp). The results show that microstructure-sensitive cracks propagate in a mixed-mode manner at low driving force and transition to plasticity-dominated and load-aligned crack, arrested as the crack-tip process zone develops and expands multiple grains. This transition is identified through the divergence of elastic and elastoplastic energy measures (ΔJE >= ΔJP), crack-tip blunting, slip-band emission, and the emergence of localised plastic deformation. These findings demonstrate that crack arrest coincides with a measurable transition in crack-tip energy
The non-equilibrium dynamics of an order parameter confined by an external constraint field are investigated within a spatially extended Belitz-Kirkpatrick-Vojta framework. A generic non-monotonic dissipation peak arises at avoided criticality due to the interplay between macroscopic free-energy flattening and microscopic disorder-induced trapping. Near this regime, suppressed deterministic forces enhance activated trapping, leading to an effective violation of the fluctuation-dissipation theorem and ultimate glassy arrest. At higher fields, the system undergoes a discontinuous phase transition that bypasses this flat free-energy region. These explicit analytical scalings establish a generic mechanism for non-equilibrium arrest in disordered condensed matter systems.
Cardiac arrest is one of the biggest global health problems, and early identification and management are key to enhancing the patient's prognosis. In this paper, we propose a novel framework that combines an EfficientNet-based deep learning model with a digital twin system to improve the early detection and analysis of cardiac arrest. We use compound scaling and EfficientNet to learn the features of cardiovascular images. In parallel, the digital twin creates a realistic and individualized cardiovascular system model of the patient based on data received from the Internet of Things (IoT) devices attached to the patient, which can help in the constant assessment of the patient and the impact of possible treatment plans. As shown by our experiments, the proposed system is highly accurate in its prediction abilities and, at the same time, efficient. Combining highly advanced techniques such as deep learning and digital twin (DT) technology presents the possibility of using an active and individual approach to predicting cardiac disease.
This study examines racial disparities in violent arrest outcomes, challenging conventional methods through a nuanced analysis of Cincinnati Police Department data. Acknowledging the intricate nature of racial disparity, the study categorizes explanations into types of place, types of person, and a combination of both, emphasizing the impact of neighborhood characteristics on crime distribution and police deployment. By introducing alternative scenarios, such as spuriousness, directed policing, and the geo-concentration of racial groups, the study underscores the complexity of racial disparity calculations. Employing a case study approach, the analysis of violent arrest outcomes reveals approximately 40 percent of the observed variation attributed to neighborhood-level characteristics, with concentrated disadvantage neutralizing the influence of race on arrest rates. Contrary to expectations, the study challenges the notion of unintentional racism, suggesting that neighborhood factors play a more significant role than the racial composition in explaining arrests. Policymakers are urged to focus on comprehensive community development initiatives addressing socioeconomic inequalities
Aim: Approximately six million people suffer cardiac arrests worldwide per year with very low survival rates (<1%). Thus, the aim of this study is to estimate the probability of a poor outcome after cardiac arrest. Accurate outcome predictions avoid removing care too soon for patients with potentially good outcomes or continuing care for patients with likely poor outcomes. Method: The method is based on dynamical systems embedding theorems that show that a reconstructed phase space (RPS) topologically equivalent to an underlying system can be constructed from measured signals. Here the underlying system is the human brain after a cardiac arrest, and the signals are the EEG channels. We model the RPS with a Gaussian mixture model (GMM) and ensemble the output of the RPS-GMM with clinical data via XGBoost. Results: As team Blue and Gold in the Predicting Neurological Recovery from Coma After Cardiac Arrest: The George B. Moody PhysioNet Challenge 2023, our RPS-GMM-XGBoost method obtained a test set competition score of 0.426 and rank of 24/36.
We develop a dissipation-based framework for earthquake rupture on homogeneous faults that explicitly separates the onset of unstable slip from the conditions required for self-sustained rupture propagation. This distinction explains the coexistence of self-arresting earthquakes and run-away ruptures (subshear and supershear events) observed in numerical simulations and empirical studies. We identify two distinct characteristic fault sizes: a nucleation radius controlling the instability of slip, and in general a larger propagation radius controlling whether an unstable rupture can be energetically sustained. Ruptures initiated above the nucleation scale but below the propagation scale spontaneously arrest. We further derive the Gutenberg-Richter law for self-arresting earthquakes by linking rupture physics to the fractal geometry of faulting. Finally, we interpret run-away ruptures as extreme events generated by an amplifying mechanism, consistent with the dragon-king concept. These results provide a unified physical basis for earthquake initiation, arrest, and seismicity statistics.
Active fluids display spontaneous turbulent-like flows known as active turbulence. Recent work revealed that these flows have universal features, independent of the material properties and of the presence of topological defects. However, the differences between defect-laden and defect-free active turbulence remain largely unexplored. Here, by means of large-scale numerical simulations, we show that defect-free active nematic turbulence can undergo dynamical arrest. This state is characterized by an emergent network of nematic domain walls that channels coherent streams and suppresses chaotic flows. As the system evolves, the branched wall network produces a large-scale pattern with tree-like topological properties. We find that flow alignment -- the tendency of nematics to reorient under shear -- enhances large-scale chaotic jets in contractile rodlike systems while promoting dynamical arrest in extensile systems. We further show that dynamical arrest persists regardless of whether defects are prohibited by construction or simply fail to form due to a high energy cost of defect cores. Taken together, our findings reveal a striking pattern-formation mechanism, with labyrinths emergi
Many important policy decisions concerning policing hinge on our understanding of how likely various criminal offenses are to result in arrests. Since many crimes are never reported to law enforcement, estimates based on police records alone must be adjusted to account for the likelihood that each crime would have been reported to the police. In this paper, we present a methodological framework for estimating the likelihood of arrest from police data that incorporates estimates of crime reporting rates computed from a victimization survey. We propose a parametric regression-based two-step estimator that (i) estimates the likelihood of crime reporting using logistic regression with survey weights; and then (ii) applies a second regression step to model the likelihood of arrest. Our empirical analysis focuses on racial disparities in arrests for violent crimes (sex offenses, robbery, aggravated and simple assaults) from 2006--2015 police records from the National Incident Based Reporting System (NIBRS), with estimates of crime reporting obtained using 2003--2020 data from the National Crime Victimization Survey (NCVS). We find that, after adjusting for unreported crimes, the likeliho
The Nd0.6Sr0.4MnO3 manganite system exhibits a phase transition from paramagnetic insulating (PMI) to ferromagnetic metallic (FMM) state around its Curie temperature TC = 270 K (bulk). The morphology-driven changes in the kinetically arrested magnetic phases in NSMO thin films with granular and a crossed-nano-rod-type morphology are studied. At low temperatures, the manganite thin films possess a magnetic glassy state arising from the coexistence of the high-temperature PMI phase and the low-temperature FMM phase. The extent of kinetic arrest and its relaxation was studied using the "cooling and heating in unequal field (CHUF)" protocol in magnetic and magneto-transport investigations. The sample with rod morphology showed a large extent of phase coexistence compared to the granular sample. Further, with a field-cooling protocol, time-evolution studies were carried out to understand the relaxation of arrested magnetic phases across these morphologically distinct thin films. The results on the devitrification of the arrested magnetic state are interpreted from the point of view of homogeneous and heterogeneous nucleation of the FM phase in the PM matrix with respect to temperature.
Sudden cardiac arrest is a significant public health concern. Successful treatment of cardiac arrest is extremely time sensitive, and use of an automated external defibrillator (AED) where possible significantly increases the probability of survival. Placement of AEDs in public locations can improve survival by enabling bystanders to treat victims of cardiac arrest prior to the arrival of emergency medical responders. However, since the exact locations of future cardiac arrests cannot be known a priori, AEDs must be placed strategically in public locations to ensure their accessibility in the event of an out-of-hospital cardiac arrest emergency. In this paper, we propose a data-driven optimization model for deploying AEDs in public spaces while accounting for uncertainty in future cardiac arrest locations. Our approach involves discretizing a continuous service area into a large set of scenarios, where the probability of cardiac arrest at each location is itself uncertain. We model uncertainty in the spatial risk of cardiac arrest using a polyhedral uncertainty set that we calibrate using historical cardiac arrest data. We propose a solution technique based on row-and-column genera
Energy cascades lie at the heart of the dynamics of turbulent flows. In a recent study of turbulence in fluids with odd-viscosity [de Wit \textit{et al.}, Nature \textbf{627}, 515 (2024)], the two-dimensionalization of the flow at small scales leads to the arrest of the energy cascade and selection of an intermediate scale, between the forcing and the viscous scales. To investigate the generality of this phenomenon, we study a shell model that is carefully constructed to have three-dimensional turbulent dynamics at small wavenumbers and two-dimensional turbulent dynamics at large wavenumbers. The large scale separation that we can achieve in our shell model allows us to examine clearly the interplay between these dynamics, which leads to an arrest of the energy cascade at a transitional wavenumber and an associated accumulation of energy at the same scale. Such pile-up of energy around the transitional wavenumber is reminiscent of the formation of condensates in two-dimensional turbulence, \textit{but, in contrast, it occurs at intermediate wavenumbers instead of the smallest wavenumber
Crack growth in stress corrosion cracking (SCC) in 7xxx Al alloys is an intermittent process, which generates successive crack arrest markings (CAMs) visible on the fracture surface. It is conjectured that H is generated at the crack tip during crack arrest, which then facilitates crack advancement through hydrogen embrittlement. Here, nanoscale imaging by 4D-scanning-transmission electron microscopy and atom probe tomography show that CAMs are produced by oxidation at the arrested crack tip, matrix precipitates dissolve and solute diffuse towards the growing CAM. Substantial homogenous residual strain remains underneath the fracture surface, indicative of non-localized plastic activity. Our study suggests that H induces crack propagation through decohesion.
We present a new first-principles theory of dynamic arrest in colloidal mixtures based on the multi-component self-consistent generalized Langevin equation (SCGLE) theory of colloid dynamics [Phys. Rev. E {\bf 72}, 031107 (2005); ibid {\bf 76}, 039902 (2007)]. We illustrate its application with the description of dynamic arrest in two simple model colloidal mixtures, namely, the hard-sphere and the repulsive Yukawa binary mixtures. Our results include the observation of the two patterns of dynamic arrest, one in which both species become simultaneously arrested, and the other involving the sequential arrest of the two species. The latter case gives rise to mixed states in which one species is arrested while the other species remains mobile. We also derive the ("fixed point") equations for the non-ergodic parameters of the system, which takes the surprisingly simple form of a system of coupled equations for the localization length of the particles of each species. The solution of this system of equations indicates unambiguously which species is arrested (finite localization length) and which species remains ergodic (infinite localization length). As a result, we are able to draw the
Concentrated aqueous solutions of the protein lysozyme undergo a liquid solid transition upon a temperature quench into the unstable spinodal region below a characteristic arrest temperature of Tf=15C. We use video microscopy and ultra-small angle light scattering in order to investigate the arrested structures as a function of initial concentration, quench temperature and rate of the temperature quench. We find that the solid-like samples show all the features of a bicontinuous network that is formed through an arrested spinodal decomposition process. We determine the correlation length Xi and demonstrate that Xi exhibits a temperature dependence that closely follows the critical scaling expected for density fluctuations during the early stages of spinodal decomposition. These findings are in agreement with an arrest scenario based on a state diagram where the arrest or gel line extends far into the unstable region below the spinodal line. Arrest then occurs when during the early stage of spinodal decomposition the volume fraction phi2 of the dense phase intersects the dynamical arrest threshold phi2Glass, upon which phase separation gets pinned into a space-spanning gel network w
Flowing granular materials often abruptly arrest if not driven by sufficient applied stresses. Such abrupt cessation of motion can be economically expensive in industrial materials handling and processing, and is significantly consequential in intermittent geophysical phenomena such as landslides and earthquakes. Using discrete element simulations, we calculate states of steady flow and arrest for granular materials under the conditions of constant applied pressure and shear stress, which are also most relevant in practice. Here the material can dilate or compact, and flow or arrest, in response to the applied stress. Our simulations highlight that under external stress, the intrinsic response of granular materials is characterized by uniquely-defined steady states of flow or arrest, which are highly sensitive to interparticle friction. While the flowing states can be equivalently characterized by volume fraction, coordination number or internal stress ratio, to characterize the states of shear arrest, one needs to also consider the structural anisotropy in the contact network. We highlight the role of dilation in the flow-arrest transition, and discuss our findings in the context
The interplay of phase separation and dynamical arrest can lead to the formation of gels and glasses, which is relevant for such diverse fields as hard and soft condensed matter physics, materials science, food engineering and pharmaceutical industry. Here, the non-equilibrium states as well as the interactions of globular proteins are analyzed. Lysozyme in brine is chosen as a model system with short-range attractions. The metastable gas-liquid binodal and the dynamical arrest line as well as the second virial coefficient $B_2$ have been determined for various solution conditions by cloud-point measurements, optical microscopy, centrifugation experiments and light scattering. If temperature is expressed in terms of $B_2$, the binodals obtained under various conditions fall onto a master curve, as suggested by the extended law of corresponding states. Arrest lines for different salt concentrations overlap within experimental errors, whereas they do not overlap if the temperature axis is replaced by $B_2$. This indicates that the binodals are not sensitive to the details of the potential, but can be described by one integral parameter, i.e. $B_2$, whereas the arrest line appears gov