Glass Model Research Articles

A memristive circuit for self-organized network topology formation based on guided axon growth

Circuit implementations of neuronal networks so far have been focusing on synaptic weight changes as network growth principles. Besides these weight changes, however, it is also useful to incorporate additional network growth principles such as guided axon growth and pruning. These allow for dynamical signal delays and a higher degree of self-organization, and can thus lead to novel circuit design principles. In this work we develop an ideal, bio-inspired electrical circuit mimicking growth and pruning controlled by guidance cues. The circuit is based on memristively coupled neuronal oscillators. As coupling element, we use memsensors consisting of a general sensor, two gradient sensors, and two memristors. The oscillators and memsensors are arranged in a grid structure, where oscillators and memsensors realize nodes and edges, respectively. This allows for arbitrary 2D growth scenarios with axon growth controlled by guidance cues. Simulation results show that the circuit successfully mimics a biological example in which two neurons initially grow towards two target neurons, where undesired connections are pruned later on.

Fluctuations of the free energy in p-spin SK models on two scales

20 years ago, Bovier, Kurkova, and Löwe (Ann Probab 30(2):605–651, 2002) proved a central limit theorem (CLT) for the fluctuations of the free energy in the p-spin version of the Sherrington–Kirkpatrick model of spin glasses at high temperatures. In this paper we improve their results in two ways. First, we extend the range of temperatures to cover the entire regime where the quenched and annealed free energies are known to coincide. Second, we identify the main source of the fluctuations as a purely coupling dependent term, and we show a further CLT for the deviation of the free energy around this random object.

In vitro evaluation of flow diverter performance using a human fibrinogen-based flow model.

Fibrin deposition represents a key step in aneurysm occlusion, promoting endothelization of implants and connective tissue organization as part of the aneurysm-healing mechanism. In this study, the authors introduce a novel in vitro testing platform for flow diverters based on human fibrinogen. A flow diverter was deployed in 4 different glass models. The glass models had the same internal parent artery (4 mm) and aneurysm (8 mm) diameters with varying parent artery angulations (paraophthalmic, sidewall, bifurcation, and slightly curved models). The neck size and area were 4 mm and 25 mm2, respectively. Human fibrinogen (330 mg/dl) was circulated within the glass models at varying flow rates (0, 3, 4, and 5 ml/sec) with or without heparin, calcium chloride, and thrombin for as long as 6 hours or until complete fibrin coverage of the flow diverter's neck was achieved. Aneurysm neck coverage was defined as macroscopic fibrin deposition occluding the flow diverters' pores. Flow characteristics after flow diverter deployment were assessed with computational fluid dynamics analysis. The effects of flow rates, heparin, calcium chloride, and thrombin on fibrin deposition rates were tested using 1-way ANOVA and the Tukey test. A total of 84 replicates were performed. Human fibrin did not accumulate on the flow diverter stents under static conditions. The fibrin deposition rate on the aneurysm neck was significantly greater with the 5 ml/sec flow rate as compared to 3 ml/sec for all models. The paraophthalmic model had the highest inflow velocity of 48.7 cm/sec. The bifurcation model had the highest maximum shear stress (SS) and maximum normalized shear stress values at the device cells at 843.3 dyne/cm2 and 35.1 SS/SSinflow, respectively. The fibrin deposition rates of the paraophthalmic and bifurcation models were significantly higher than those of sidewall and slightly curved models for all additive or flow rate comparisons (p = 0.001 for all comparisons). The incorporation of thrombin significantly increased the fibrin deposition rates across all models (p = 0.001 for all models). Rates of fibrin deposition varied widely across different configurations and additive conditions in this novel in vitro model system. Fibrin accumulation started at the aneurysm inflow zone where flow velocity and shear stress were the highest. The primary factors influencing fibrin deposition included flow velocities, shear stress, and the addition of thrombin at a physiological concentration. Further research is needed to test the clinical utility of fibrinogen-based models for patient-specific aneurysms.

Security Interpretations and Elaborations on Systems Engineering Principles

AbstractINCOSE's Systems Engineering Vision 2035 includes thirty‐one mentions of security as part of the vision, including security to become as foundational a perspective to system design as performance and safety. INCOSE's Systems Engineering Principles technical product published a “first set of systems principles” (Watson, et al., 2022). This paper examines interpretations of these principles for security as captured in the vision and suggests modifications and possible additional principles to see security more integrated into the systems engineering process.

Changing of the excess conductivity near the irreversibility temperature of the top seeded YBa2Cu3O7−x

A top seeded YBa2Cu3O7-x (YBCO) superconductor was grown using a bulk Nd123 seed crystal. Orientation peaks directed in the c-axis were observed from the X-ray diffraction measurement for the Y123 sample, indicating single crystal behavior. Magneto-resistivity measurements were carried out as a function of temperature under applied magnetic fields up to 4 T. The superconducting transition temperature (Tc) of the sample was obtained to be approximately 93 K and the excess conductivity curve was obtained experimentally from the resistivity measurement at zero magnetic field. The critical exponents were found to be λsfw = 2.26 ± 0.25, λ3D = 0.47 ± 0.03 and λ2D = 0.82 ± 0.07 for the short wave fluctuation (SWF) region and the mean field region characterized by 3D and 2D fluctuations, respectively. The crossover temperature determined from the crossover from 2D to 3D regime was found to be 96.37 K. The irreversible temperatures determined from the magneto-resistivity measurements and the irreversibility field line of the sample was obtained using the giant flux creep (gfc) model. The sample exhibits a behavior consistent with the gfc and the vortex glass model according to the n parameter calculated from the resistivity temperature measurements. The width enlarges with the applied magnetic field and was found to be approximately 4 K at 4 T for the Y123 sample. The sample was in the 3D regime below 96.37 K, while the sample was in the 2D regime between 96.37 K and 101.35 K. On the other hand, the reversible region was confined between 93.95 K and 93.33 K at 0 T. It was observed that 3D fluctuations are dominant in the reversible region, whereas 2D fluctuations are dominant in the irreversible region.

Bibliometric Analysis on Metacognition and Self-Regulation Using Biblioshiny Software

This study aims to conduct a systematic review of Metacognition and Self-Regulation [MSR], with a focus on current trends and contributions. Initial analysis involves Elsevier's Scopus database spanning from 1988 to 2023, with refined search parameters including source type, language, and document type. Later, bibliometric analysis was conducted using Biblioshiny software, exploring various factors derived from the Scopus core collection database [N=428] on the search title MSR. The results highlight trending topics such as cognition, engineering design, memory, and engineering education. Notably, the most prevalent co-occurrence network involves metacognition, student, and self-regulated learning. Analysis of the most influential authors, affiliated institutes, citation analysis, and source production was discussed. The objective of this paper is to assist researchers and scholars in understanding and analyzing contemporary trends in MSR, as well as suggesting further empirical research to explore additional principles related to metacognition and self-regulated learning.

Bethe M-layer construction on the Ising model

In statistical physics, one of the standard methods to study second order phase transitions is the renormalization group that usually leads to an expansion around the corresponding fully connected solution. Unfortunately, often in disordered models, some important finite dimensional second-order phase transitions are qualitatively different or absent in the corresponding fully connected model: in such cases the standard expansion fails. Recently, a new method, the M-layer one, has been introduced that performs an expansion around a different soluble mean field model: the Bethe lattice one. This new method has been already used to compute the upper critical dimension DU of different disordered systems such as the Random Field Ising model or the Spin glass model with field. If then one wants to go beyond and construct an expansion around DU to understand how critical quantities get renormalized, the actual computation of all the numerical factors is needed. This next step has still not been performed, being technically more involved. In this paper we perform this computation for the ferromagnetic Ising model without quenched disorder, in finite dimensions: we show that, at one-loop order inside the M-layer approach, we recover the continuum quartic field theory and we are able to identify the coupling constant g and the other parameters of the theory, as a function of macroscopic and microscopic details of the model such as the lattice spacing, the physical lattice dimension and the temperature. This is a fundamental step that will help in applying in the future the same techniques to more complicated systems, for which the standard field theoretical approach is impracticable.

Additive patterns in near-infrared diffuse reflectance spectra: Implications for product formulation and analysis

In this study, we investigated the additive patterns observed in near-infrared (NIR) diffuse reflectance spectra within the context of food and pharmaceutical product formulation. Employing the Kubelka–Munk theory, we examined the linear correlation between spectra and concentration in polymer materials and tobacco powder samples. Our findings confirm the principle of spectral additivity in diffuse reflectance spectra, demonstrating a linear relationship when the sample scattering coefficient remains constant. Moreover, our results validate the feasibility of substituting actual mixed spectra with NIR additive spectra in tobacco leaf systems. This approach can potentially enhance formulation design, thereby improving efficiency and accuracy while expanding the scope and combination of formulation materials. Furthermore, this study offers a rapid, information-rich, and environmentally friendly alternative to traditional methods, with significant implications for the future of product formulation.

Dynamic mechanical response and constitutive model of (Ti37.31Zr22.75Be26.39Al4.55Cu9)94Co6 high-entropy bulk metallic glass

In this work, the mechanical response and fracture characteristics of (Ti37.31Zr22.75Be26.39Al4.55Cu9)94Co6 high-entropy bulk metallic glass (HE-BMG) were investigated in detail over a wide range of strain rates (10−4–105 s−1). The HE-BMG exhibited a negative strain rate sensitivity under uniaxial compression, with the strength showing more significant rate dependence under dynamic conditions. The shear band behavior translated from the dominance of multiple shear bands propagations under quasi-static compression to the rapid propagation of a single shear band to form cracks under dynamic compression. Under dynamic loading, the shearing velocity increased along an arc-shaped displacement path, and the local stress state on the shear fracture surface shifted from compressive-shear to tensile-shear, accompanied by changes in fracture morphologies. The spall strength of HE-BMG decreased as flyer impact speed increased, while the long-term dependence of spall strength on strain rate may be positive. With the increase of impact speed, the main microstructural features of the spalling surface translated from flat regions accompanied by dimples to cup-cone structures. Furthermore, the complete parameters of the Johnson–Holmquist II (JH-2) model for HE-BMG were obtained based on experimental data. Numerical simulations of planar impact, penetration, and hypervelocity impact are in good agreement with experimental results, demonstrating the validity of the JH-2 model parameters. The current work has important guiding value for the application of HE-BMG in space debris protection.

Direct Numerical Analysis of Dynamic Facilitation in Glass-Forming Liquids.

We propose a computational strategy to quantify the temperature evolution of the timescales and length scales over which dynamic facilitation affects the relaxation dynamics of glass-forming liquids at low temperatures, which requires no assumption about the nature of the dynamics. In two glass models, we find that dynamic facilitation depends strongly on temperature, leading to a subdiffusive spreading of relaxation events which we characterize using a temperature-dependent dynamic exponent. We also establish that this temperature evolution represents a major contribution to the increase of the structural relaxation time.

«Тонкие» объекты Эйстейна Линнебо: проблема референции

Introduction. The introduction formulates the problem of abstract objects for the philosophy of mathematics, epistemology, and metaphysics. Special attention is paid to the problem of reference. Theoretical analysis. The first section examines Linnebo’s proposed concept of abstract objects as “thin” i.e., not imposing substantial demands on the world. The second section is devoted to the criteria of identity as a special tool for introducing abstract objects into discourse. Linnebo interprets abstraction principles as a particular kind of identity criteria. They allow fixing reference and ensuring its success. The third section presents metasemantic arguments used by Linnebo to justify the preference for a realistic interpretation of the semantics of singular terms. The fourth section criticizes Linnebo’s proposed mechanism of referential access to abstract “thin” objects. In our view, the metasemantic constraints proposed by Linnebo are insufficient to determine the uniqueness of the referent. An additional principle is necessary. Lewis’s “referential magnetism” can be considered as such, but it threatens the concept of “thin” objects. Conclusion. In conclusion, the strengths of Linnebo’s project are acknowledged. His interpretation better reflects how we actually use language. The importance of Linnebo’s theses and ideas for contemporary philosophy is noted.

Hybrid glass-carbon fiber composites for solar greenhouse dryer trays: a 3D computational analysis

A 3D computational study was conducted to analyze the compressive load response of a glass-carbon hybrid composite. The study varied the volume percentage of glass fibers from 0% to 100% in a composite with an overall fiber volume fraction of 0.5. Compressive instability failure was examined using ABAQUS/CAE 3D finite element micro mechanical models. The analysis assessed the behavior of glass and carbon fiber models independently before evaluating the performance of the hybrid composite.The results revealed that hybrid models exhibited superior performance at specific volume fractions. It was observed that the matrix shear yield strength played a significant role in determining compressive instability failure. Furthermore, the study demonstrated that hybrid composite turnable trays enhanced moisture removal and heat transmission during drying processes. These trays were found to be particularly suitable for outdoor solar greenhouses owing to their high strength-to-weight ratio, mechanical properties, corrosion resistance, and dimensional stability.

Stability and chaos in dynamical last passage percolation

Many complex disordered systems in statistical mechanics are characterized by intricate energy landscapes. The ground state, the configuration with lowest energy, lies at the base of the deepest valley. In important examples, such as Gaussian polymers and spin glass models, the landscape has many valleys and the abundance of near-ground states (at the base of valleys) indicates the phenomenon of chaos, under which the ground state alters profoundly when the disorder of the model is slightly perturbed. In this article, we compute the critical exponent that governs the onset of chaos in a dynamic manifestation of a canonical model in the Kardar-Parisi-Zhang [KPZ] universality class, Brownian last passage percolation [LPP]. In this model in its static form, semidiscrete polymers advance through Brownian noise, their energy given by the integral of the white noise encountered along their journey. A ground state is a geodesic, of extremal energy given its endpoints. We perturb Brownian LPP by evolving the disorder under an Ornstein-Uhlenbeck flow. We prove that, for polymers of length n n , a sharp phase transition marking the onset of chaos is witnessed at the critical time n − 1 / 3 n^{-1/3} . Indeed, the overlap between the geodesics at times zero and t > 0 t > 0 that travel a given distance of order n n will be shown to be of order n n when t ≪ n − 1 / 3 t\ll n^{-1/3} ; and to be of smaller order when t ≫ n − 1 / 3 t\gg n^{-1/3} . We expect this exponent to be universal across a wide range of interface models. The present work thus sheds light on the dynamical aspect of the KPZ class; it builds on several recent advances. These include Chatterjee’s harmonic analytic theory [Superconcentration and related topics, Springer, Cham, 2014] of equivalence of superconcentration and chaos in Gaussian spaces; a refined understanding of the static landscape geometry of Brownian LPP developed in the companion paper (see S. Ganguly and A. Hammond [Electron. J. Probab. 28 (2023), 80 pp.]); and, underlying the latter, strong comparison estimates of the geodesic energy profile to Brownian motion (see J. Calvert, A. Hammond, and M. Hegde [Astérisque 441 (2023), pp. v+119]).

Minimum connected dominating set and backbone of a random graph

We study the minimum dominating set problem as a representative combinatorial optimization challenge with a global topological constraint. The requirement that the backbone induced by the vertices of a dominating set should be a connected subgraph makes the problem rather nontrivial to investigate by statistical physics methods. Here, we convert this global connectivity constraint into a set of local vertex constraints and build a spin glass model with only five coarse-grained vertex states. We derive a set of coarse-grained belief-propagation equations and obtain theoretical predictions of the relative sizes of the minimum dominating sets for regular random and Erdös–Rényi random graph ensembles. We also implement an efficient message-passing algorithm to construct close-to-minimum connected dominating sets and backbone subgraphs for single random graph instances. Our theoretical strategy may also be applicable to some other global topological constraints.

Flaw characteristics of architectural glass and long-term strength prediction model

Flaw characteristics of architectural glass and long-term strength prediction model

Biopolymer networks packed with microgels combine strain stiffening and shape programmability

Biomaterials that can be reversibly stiffened and shaped could be useful in broad biomedical applications where form-fitting scaffolds are needed. Here we investigate the combination of strong non-linear elasticity in biopolymer networks with the reconfigurability of packed hydrogel particles within a composite biomaterial. By packing microgels into collagen-1 networks and characterizing their linear and non-linear material properties, we empirically determine a scaling relationship that describes the synergistic dependence of the material's linear elastic shear modulus on the concentration of both components. We perform high-strain rheological tests and find that the materials strain stiffen and also exhibit a form of programmability, where no applied stress is required to maintain stiffened states of deformation after large strains are applied. We demonstrate that this non-linear rheological behavior can be used to shape samples that do not spontaneously relax large-scale bends, holding their deformed shapes for days. Detailed analysis of the frequency-dependent rheology reveals an unexpected connection to the rheology of living cells, where models of soft glasses capture their low-frequency behaviors and polymer elasticity models capture their high-frequency behaviors.

Unlearning regularization for Boltzmann machines

Boltzmann machines (BMs) are graphical models with interconnected binary units, employed for the unsupervised modeling of data distributions. When trained on real data, BMs show the tendency to behave like critical systems, displaying a high susceptibility of the model under a small rescaling of the inferred parameters. This behavior is not convenient for the purpose of generating data, because it slows down the sampling process, and induces the model to overfit the training-data. In this study, we introduce a regularization method for BMs to improve the robustness of the model under rescaling of the parameters. The new technique shares formal similarities with the unlearning algorithm, an iterative procedure used to improve memory associativity in Hopfield-like neural networks. We test our unlearning regularization on synthetic data generated by two simple models, the Curie–Weiss ferromagnetic model and the Sherrington–Kirkpatrick spin glass model. We show that it outperforms Lp -norm schemes and discuss the role of parameter initialization. Eventually, the method is applied to learn the activity of real neuronal cells, confirming its efficacy at shifting the inferred model away from criticality and coming out as a powerful candidate for actual scientific implementations.

Excellent energy storage properties in ZrO2 toughened Ba0.55Sr0.45TiO3-based relaxor ferroelectric ceramics via multi-scale synergic regulation

Lead-free ceramic capacitors offer ultrahigh power density and ultrafast discharging rates, making them critical energy storage components for advanced pulsed power systems. However, the greatest obstacle to broader applications remains the relatively low energy storage density. In this study, a relaxor ferroelectric ceramic based on (0.6-x)Ba0.55Sr0.45TiO3-0.4Bi0.5Na0.5TiO3-xSrZrO3 ((0.6-x)BST-0.4BNT-xSZ) is prepared using the tape casting method, resulting in an excellent energy density (Wrec ≈ 10.0 J cm−3) and high energy storage efficiency (η ≈ 91 %). The solid solution of linear dielectrics SrZrO3 synergistically regulates both relaxor properties and breakdown strength. The variation of relaxor property was explored utilizing New Glass model and the multi-polarization model, with confirmation provided by piezoresponse force microscopy. Furthermore, the breakdown strength could be attributed to improvements in electric insulation and the widening of the bandgap. As SrZrO3 content increases, the in-situ emergence of the second phase ZrO2, accompanied by a martensitic transformation, not only improves the fracture toughness of ceramics but also serves to elongate the breakdown path. Encouragingly, x = 0.20 ceramics also achieve excellent temperature stability (−95–125 ℃), frequency stability (1–1000 Hz), cycling reliability (1–106 cycles), and great charging-discharging properties. This multiscale synergic regulation strategy plays a guiding role in the screening of high-performance energy storage dielectric materials.

NoRA: A Tensor Network Ansatz for Volume-Law Entangled Equilibrium States of Highly Connected Hamiltonians

Motivated by the ground state structure of quantum models with all-to-all interactions such as mean-field quantum spin glass models and the Sachdev-Ye-Kitaev (SYK) model, we propose a tensor network architecture which can accomodate volume law entanglement and a large ground state degeneracy. We call this architecture the non-local renormalization ansatz (NoRA) because it can be viewed as a generalization of MERA, DMERA, and branching MERA networks with the constraints of spatial locality removed. We argue that the architecture is potentially expressive enough to capture the entanglement and complexity of the ground space of the SYK model, thus making it a suitable variational ansatz, but we leave a detailed study of SYK to future work. We further explore the architecture in the special case in which the tensors are random Clifford gates. Here the architecture can be viewed as the encoding map of a random stabilizer code. We introduce a family of codes inspired by the SYK model which can be chosen to have constant rate and linear distance at the cost of some high weight stabilizers. We also comment on potential similarities between this code family and the approximate code formed from the SYK ground space.

Elasticity of self-organized frustrated disordered spring networks.

There have been some interesting recent advances in understanding the notion of mechanical disorder in structural glasses and the statistical mechanics of these systems' low-energy excitations. Here we contribute to these advances by studying a minimal model for structural glasses' elasticity in which the degree of mechanical disorder-as characterized by recently introduced dimensionless quantifiers-is readily tunable over a very large range. We comprehensively investigate a number of scaling laws observed for various macro, meso and microscopic elastic properties, and rationalize them using scaling arguments. Interestingly, we demonstrate that the model features the universal quartic glassy vibrational density of states as seen in many atomistic and molecular models of structural glasses formed by cooling a melt. The emergence of this universal glassy spectrum highlights the role of self-organization (toward mechanical equilibrium) in its formation, and elucidates why models featuring structural frustration alone do not feature the same universal glassy spectrum. Finally, we discuss relations to existing work in the context of strain stiffening of elastic networks and of low-energy excitations in structural glasses, in addition to future research directions.