Quasi-Majorana modes in the-wave Kitaev chains on a square lattice.

The topological characteristics of the-wave Kitaev chains on a square lattice with nearest-neighbor and next-nearest-neighbor inter-chains hopping and pairing are investigated. Besides gapless exact zero-energy modes, this model exhibits topological gapless phase hosting edge modes, which do not reside strictly at zero energy. However, these modes can be distinguished from the bulk states.

Load-based divergence in the dynamic allostery of two TCRs recognizing the same pMHC.

Increasing evidence suggests that mechanical load on the αβ T-cell receptor (TCR) is crucial for recognizing the antigenic peptide-bound major histocompatibility complex (pMHC) molecule. Our recent all-atom molecular dynamics (MD) simulations revealed that the inter-domain motion of the TCR is responsible for the load-induced catch bond behavior of the TCR-pMHC complex and peptide discrimination (Chang-Gonzalez et al., 2024).

On Self-Similar Converging Shock Waves.

In this paper, we rigorously prove the existence of self-similar converging shock wave solutions for the non-isentropic Euler equations for . These solutions are analytic away from the shock interface before collapse, and the shock wave reaches the origin at the time of collapse. The region behind the shock undergoes a sonic degeneracy, which causes numerous difficulties for smoothness of the flow and the analytic construction of the solution.

The depth of tumor hierarchy and its impact on hypertumor susceptibility.

Cancer cells, despite their shared origin, could be heterogeneous with respect to their stemness, plasticity, self-renewal, and oncogenicity. Recent findings indicate that a small proportion of the cancer cells oligopolize the capacity to produce diverse cancer subtypes and metastasize to other sites. Analogous to the apical hierarchy observed in adult stem cells, such versatile cancer cells were termed cancer stem cells.

Dynamic Programming for Chain Propagator Computation of Branched Block Copolymers in Polymer Field Theory Simulations.

We present an algorithmic approach to optimize chain propagator computations in polymer field theory simulations, including self-consistent field theory (SCFT) calculations and field-theoretic simulations (FTSs). Propagator calculations for branched block copolymers often involve recursive structures and overlapping subproblems, resulting in redundant computations. By employing dynamic programming (DP) and encoding computational dependencies as strings, our method systematically eliminates these redundancies in mixtures of branched polymers.

Ferroelectric Switchable Altermagnetism.

We propose a novel ferroelectric switchable altermagnetism effect: the reversal of ferroelectric polarization is coupled to the switching of altermagnetic spin splitting. We demonstrate the design principles for the ferroelectric altermagnets and the additional symmetry constraints necessary for switching the spin splitting through flipping the electric polarization based on the state-of-the-art spin-group symmetry techniques. We find 22 ferroelectric altermagnets by screening through the 2001 experimental reported magnetic structures in the MAGNDATA database and identify two of them as ferroelectric switchable altermagnets.

UNRES web server: Extensions to nucleic acids, prediction of peptide aggregation, and new types of restrained calculations.

The third version of the UNRES web server is described, in which the range of biological macromolecules treated and calculation types has been extended significantly. DNA and RNA molecules have been added to enable the user to run simulations of their folding/hybridization and dynamics. To increase the accuracy of the simulated proteins models, the restraints on secondary structure have been enhanced to include the probabilities of the coil, extended and helical state, which are taken from the PSIPRED or HHpred raw input and the restraints from multiple bioinformatics models have been added.

Pd-Modified Microneedle Array Sensor Integration with Deep Learning for Predicting Silica Aerogel Properties in Real Time.

The continuous global effort to predict material properties through artificial intelligence has predominantly focused on utilizing material stoichiometry or structures in deep learning models. This study aims to predict material properties using electrochemical impedance data, along with frequency and time parameters, that can be obtained during processing stages. The target material, silica aerogel, is widely recognized for its lightweight structure and excellent insulating properties, which are attributed to its large surface area and pore size.

Evolutionary rewiring of the dynamic network underpinning allosteric epistasis in NS1 of the influenza A virus.

Viral proteins frequently mutate to evade host innate immune responses, yet the impact of these mutations on the molecular energy landscape remains unclear. Epistasis, the intramolecular communications between mutations, often renders the combined mutational effects unpredictable. Nonstructural protein 1 (NS1) is a major virulence factor of the influenza A virus (IAV) that activates host PI3K by binding to its p85β subunit.

Periodically driven thermodynamic systems under vanishingly small viscous drives.

Periodically driven thermodynamic systems support stable nonequilibrium oscillating states with properties drastically different from equilibrium. They exhibit even more exotic features for low viscous drives, which is a regime that is hard to probe due to singular behavior of the underlying Langevin dynamics near vanishing viscosity. We propose a method, based on singular perturbation and Floquet theories, that allows us to obtain oscillating states in this limit.

Organization and Dynamics of Chromosomes.

How long thread-like eukaryotic chromosomes fit tidily in the small volume of the nucleus without significant entanglement is just beginning to be understood, thanks to major advances in experimental techniques. Several polymer models, which reproduce contact maps that measure the probabilities that two loci are in spatial contact, have predicted the 3D structures of interphase chromosomes. Data-driven approaches, using contact maps as input, predict that mitotic helical chromosomes are characterized by a switch in handedness, referred to as perversion.

Bifurcations and multistability in empirical mutualistic networks.

Individual species may experience diverse outcomes, from prosperity to extinction, in an ecological community subject to external and internal variations. Despite the wealth of theoretical results derived from random matrix ensembles, a theoretical framework still remains to be developed to understand species-level dynamical heterogeneity within a given community, hampering real-world ecosystems' theoretical assessment and management. Here, we consider empirical plant-pollinator mutualistic networks, additionally including all-to-all intragroup competition, where species abundance evolves under a Lotka-Volterra-type equation.

Effects of Homogeneous Doping on Electron-Phonon Coupling in SrTiO.

Bulk n-type SrTiO (STO) has long been known to possess a superconducting ground state at an exceptionally dilute carrier density. This has raised questions about the applicability of the BCS-Eliashberg paradigm with its underlying adiabatic assumption. However, recent experimental reports have set the pairing gap to the critical temperature (Tc) ratio at the BCS value for superconductivity in Nb-doped STO, even though the adiabaticity condition the BCS pairing requires is satisfied over the entire superconducting dome only by the lowest branch of optical phonons.

Elasticity of Swollen and Folded Polyacrylamide Hydrogel Using the MARTINI Coarse-Grained Model.

One of the key advantages of using a hydrogel is its superb control over elasticity obtained through variations of constituent polymer and water. The underlying molecular nature of a hydrogel is a fundamental origin of hydrogel mechanics. In this article, we report a Polyacrylamide (PAAm)-based hydrogel model using the MARTINI coarse-grained (CG) force field.

Biophysical and Structural Features of αβT-Cell Receptor Mechanosensing: A Paradigmatic Shift in Understanding T-Cell Activation.

αβT cells protect vertebrates against many diseases, optimizing surveillance using mechanical force to distinguish between pathophysiologic cellular alterations and normal self-constituents. The multi-subunit αβT-cell receptor (TCR) operates outside of thermal equilibrium, harvesting energy via physical forces generated by T-cell motility and actin-myosin machinery. When a peptide-bound major histocompatibility complex molecule (pMHC) on an antigen presenting cell is ligated, the αβTCR on the T cell leverages force to form a catch bond, prolonging bond lifetime, and enhancing antigen discrimination.

Generalized Langevin equation for a tagged monomer in a Gaussian semiflexible polymer.

In this study, we present a comprehensive analysis of the motion of a tagged monomer within a Gaussian semiflexible polymer model. We carefully derived the generalized Langevin equation (GLE) that governs the motion of a tagged central monomer. This derivation involves integrating out all the other degrees of freedom within the polymer chain, thereby yielding an effective description of the viscoelastic motion of the tagged monomer.

Active motion can be beneficial for target search with resetting in a thermal environment.

Stochastic resetting has recently emerged as an efficient target-searching strategy in various physical and biological systems. The efficiency of this strategy depends on the type of environmental noise, whether it is thermal or telegraphic (active). While the impact of each noise type on a search process has been investigated separately, their combined effects have not been explored.

Data-Efficient Multifidelity Training for High-Fidelity Machine Learning Interatomic Potentials.

Machine learning interatomic potentials (MLIPs) are used to estimate potential energy surfaces (PES) from calculations, providing near-quantum-level accuracy with reduced computational costs. However, the high cost of assembling high-fidelity databases hampers the application of MLIPs to systems that require high chemical accuracy. Utilizing an equivariant graph neural network, we present an MLIP framework that trains on multifidelity databases simultaneously.

Extending Classically Simulatable Bounds of Clifford Circuits with Nonstabilizer States via Framed Wigner Functions.

The Wigner function formalism has played a pivotal role in examining the nonclassical aspects of quantum states and their classical simulatability. Nevertheless, its application in qubit systems faces limitations due to negativity induced by Clifford gates. In this Letter, we propose a novel classical simulation method for qubit Clifford circuits based on the framed Wigner function, an extended form of the Wigner function with an additional phase degree of freedom.

Spatiotemporal characterization of water diffusion anomalies in saline solutions using machine learning force field.

Understanding water behavior in salt solutions remains a notable challenge in computational chemistry. Conventional force fields have shown limitations in accurately representing water's properties across different salt types (chaotropes and kosmotropes) and concentrations, demonstrating the need for better methods. Machine learning force field applications in computational chemistry, especially through deep potential molecular dynamics (DPMD), offer a promising alternative that closely aligns with the accuracy of first-principles methods.

Incorporating Heterogeneous Interactions for Ecological Biodiversity.

Understanding the behaviors of ecological systems is challenging given their multifaceted complexity. To proceed, theoretical models such as Lotka-Volterra dynamics with random interactions have been investigated by the dynamical mean-field theory to provide insights into underlying principles such as how biodiversity and stability depend on the randomness in interaction strength. Yet the fully connected structures assumed in these previous studies are not realistic, as revealed by a vast amount of empirical data.

Unified hierarchical relationship between thermodynamic tradeoff relations.

Recent years have witnessed a surge of discoveries in the studies of thermodynamic inequalities: the thermodynamic uncertainty relation (TUR) and the entropic bound (EB) provide a lower bound on the entropy production (EP) in terms of nonequilibrium currents; the classical speed limit (CSL) expresses the lower bound on the EP using the geometry of probability distributions; the power-efficiency (PE) tradeoff dictates the maximum power achievable for a heat engine given the level of its thermal efficiency. In this study, we show that there exists a unified hierarchical structure encompassing all of these bounds, with the fundamental inequality given by an extension of the TUR (XTUR) that incorporates the most general range of currentlike and state-dependent observables. By selecting more specific observables, the TUR and the EB follow from the XTUR, and the CSL and the PE tradeoff follow from the EB.

Compaction and clustering of a heterogeneous polymer by biomolecular crowding.

Inspired by bacterial chromosome organization, we study the compaction and clustering of a heterogeneous ring polymer in a crowded medium using molecular dynamics simulations. The polymer consists of several large monomers interspersed along the backbone and small intervening monomers. In a crowded medium, the entropy of crowding particles or crowders favors the collapse of chain molecules, such as chromosomes.