Characteristic features of self-avoiding active Brownian polymers under linear shear flow.

We present Brownian dynamics simulation results of a flexible linear polymer with excluded-volume interactions under shear flow in the presence of active noise. The active noise strongly affects the polymer's conformational and dynamical properties, such as the stretching in the flow direction and compression in the gradient direction, shear-induced alignment, and shear viscosity. In the asymptotic limit of large activities and shear rates, the power-law scaling exponents of these quantities differ significantly from those of passive polymers.

Driven transport of active particles through arrays of symmetric obstacles.

We numerically examine the driven transport of an overdamped self-propelled particle through a two-dimensional array of circular obstacles. A detailed analysis of transport quantifiers (mobility and diffusivity) has been performed for two types of channels, channel I and channel II, that respectively correspond to the parallel and diagonal drives with respect to the array axis. Our simulation results show that the signatures of pinning actions and depinning processes in the array of obstacles are manifested through excess diffusion peaks or sudden drops in diffusivity, and abrupt jumps in mobility with varying amplitude of the drive.

Electron Transport Properties of Graphene/WS Van Der Waals Heterojunctions.

Van der Waals heterojunctions of two-dimensional atomic crystals are widely used to build functional devices due to their excellent optoelectronic properties, which are attracting more and more attention, and various methods have been developed to study their structure and properties. Here, density functional theory combined with the nonequilibrium Green's function technique has been used to calculate the transport properties of graphene/WS heterojunctions. It is observed that the formation of heterojunctions does not lead to the opening of the Dirac point of graphene.

Neuronal Population Activity in Macaque Visual Cortices Dynamically Changes through Repeated Fixations in Active Free Viewing.

During free viewing, we move our eyes and fixate on objects to recognize the visual scene of our surroundings. To investigate the neural representation of objects in this process, we studied individual and population neuronal activity in three different visual regions of the brains of macaque monkeys (): the primary and secondary visual cortices (V1, V2) and the inferotemporal cortex (IT). We designed a task where the animal freely selected objects in a stimulus image to fixate on while we examined the relationship between spiking activity, the order of fixations, and the fixated objects.

Manipulating the Spin Orientation of Co Atoms Using Monatomic Cu Chains.

Harnessing the spin of single atoms is at the heart of quantum information nanotechnology based on magnetic concepts. By attaching single Co atoms to monatomic Cu chains, we demonstrate the ability to control the spin orientation by the atomic environment. Due to spin-orbit coupling (SOC), the spin is tilted by ≈58° from the surface normal toward the chain as evidenced by inelastic tunneling spectroscopy.

Intrinsic Néel Antiferromagnetic Multimeronic Spin Textures in Ultrathin Films.

Topological antiferromagnetism is a vibrant and captivating research field, generating considerable enthusiasm with the aim of identifying topologically protected magnetic states of key importance in the hybrid realm of topology, magnetism, and spintronics. While topological antiferromagnetic (AFM) solitons bear various advantages with respect to their ferromagnetic cousins, their observation is scarce. Utilizing first-principles simulations, here we predict new chiral particles in the realm of AFM topological magnetism, exchange-frustrated multimeronic spin textures hosted by a Néel magnetic state, arising universally in single Mn layers directly grown on an Ir(111) surface or interfaced with Pd-based films.

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways.

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contextual state. Here, we demonstrate that dendritic N-Methyl-D-Aspartate spikes can, within physiological constraints, implement contextual modulation of feedforward processing. Such neuron-specific modulations exploit prior knowledge, encoded in stable feedforward weights, to achieve transfer learning across contexts.

Controlling the Interlayer Dzyaloshinskii-Moriya Interaction by Electrical Currents.

The recently discovered interlayer Dzyaloshinskii-Moriya interaction (IL-DMI) in multilayers with perpendicular magnetic anisotropy favors canting of spins in the in-plane direction. It could thus stabilize intriguing spin textures such as Hopfions. A key requirement for nucleation is to control the IL-DMI.

Wrapping anisotropic microgel particles in lipid membranes: Effects of particle shape and membrane rigidity.

Cellular engulfment and uptake of macromolecular assemblies or nanoparticles via endocytosis can be associated to both healthy and disease-related biological processes as well as delivery of drug nanoparticles and potential nanotoxicity of pollutants. Depending on the physical and chemical properties of the system, the adsorbed particles may remain at the membrane surface, become wrapped by the membrane, or translocate across the membrane through an endocytosis-like process. In this paper, we address the question of how the wrapping of colloidal particles by lipid membranes can be controlled by the shape of the particles, the particle-membrane adhesion energy, the membrane phase behavior, and the membrane-bending rigidity.

Giant and Tunable Out-of-Plane Spin Polarization of Topological Antimonene.

Topological insulators are bulk insulators with metallic and fully spin-polarized surface states displaying Dirac-like band dispersion. Due to spin-momentum locking, these topological surface states (TSSs) have a predominant in-plane spin polarization in the bulk fundamental gap. Here, we show by spin-resolved photoemission spectroscopy that the TSS of a topological insulator interfaced with an antimonene bilayer exhibits nearly full out-of-plane spin polarization within the substrate gap.

Optical Properties of MoSe Monolayer Implanted with Ultra-Low-Energy Cr Ions.

This paper explores the optical properties of an exfoliated MoSe monolayer implanted with Cr ions, accelerated to 25 eV. Photoluminescence of the implanted MoSe reveals an emission line from Cr-related defects that is present only under weak electron doping. Unlike band-to-band transition, the Cr-introduced emission is characterized by nonzero activation energy, long lifetimes, and weak response to the magnetic field.

Ubiquitous lognormal distribution of neuron densities in mammalian cerebral cortex.

Numbers of neurons and their spatial variation are fundamental organizational features of the brain. Despite the large corpus of cytoarchitectonic data available in the literature, the statistical distributions of neuron densities within and across brain areas remain largely uncharacterized. Here, we show that neuron densities are compatible with a lognormal distribution across cortical areas in several mammalian species, and find that this also holds true within cortical areas.

Observation of the orbital Hall effect in a light metal Ti.

The orbital Hall effect refers to the generation of electron orbital angular momentum flow transverse to an external electric field. Contrary to the common belief that the orbital angular momentum is quenched in solids, theoretical studies predict that the orbital Hall effect can be strong and is a fundamental origin of the spin Hall effect in many transition metals. Despite the growing circumstantial evidence, its direct detection remains elusive.

Toward reproducible models of sequence learning: replication and analysis of a modular spiking network with reward-based learning.

To acquire statistical regularities from the world, the brain must reliably process, and learn from, spatio-temporally structured information. Although an increasing number of computational models have attempted to explain how such sequence learning may be implemented in the neural hardware, many remain limited in functionality or lack biophysical plausibility. If we are to harvest the knowledge within these models and arrive at a deeper mechanistic understanding of sequential processing in cortical circuits, it is critical that the models and their findings are accessible, reproducible, and quantitatively comparable.

A refined information processing capacity metric allows an in-depth analysis of memory and nonlinearity trade-offs in neurocomputational systems.

Since dynamical systems are an integral part of many scientific domains and can be inherently computational, analyses that reveal in detail the functions they compute can provide the basis for far-reaching advances in various disciplines. One metric that enables such analysis is the information processing capacity. This method not only provides us with information about the complexity of a system's computations in an interpretable form, but also indicates its different processing modes with different requirements on memory and nonlinearity.

The Electrodegradation Process in PZT Ceramics under Exposure to Cosmic Environmental Conditions.

Long-time electric field action on perovskite piezoelectric ceramic leads to chemical degradation. A new way to accelerate the degradation is the exposure of the ceramic to DC electric fields under a vacuum. A high-quality commercial piezoelectric material based on PbZrTiO is used to study such impacts.

Dynamic shapes of floppy vesicles enclosing active Brownian particles with membrane adhesion.

Recent advances in micro- and nano-technologies allow the construction of complex active systems from biological and synthetic materials. An interesting example is active vesicles, which consist of a membrane enclosing self-propelled particles, and exhibit several features resembling biological cells. We investigate numerically the behavior of active vesicles, where the enclosed self-propelled particles can adhere to the membrane.

Geometry-Induced Spin Filtering in Photoemission Maps from WTe_{2} Surface States.

We demonstrate that an important quantum material WTe_{2} exhibits a new type of geometry-induced spin filtering effect in photoemission, stemming from low symmetry that is responsible for its exotic transport properties. Through the laser-driven spin-polarized angle-resolved photoemission Fermi surface mapping, we showcase highly asymmetric spin textures of electrons photoemitted from the surface states of WTe_{2}. Such asymmetries are not present in the initial state spin textures, which are bound by the time-reversal and crystal lattice mirror plane symmetries.

Inducing Single Spin-Polarized Flat Bands in Monolayer Graphene.

Due to the fundamental and technological implications in driving the appearance of non-trivial, exotic topological spin textures and emerging symmetry-broken phases, flat electronic bands in 2D materials, including graphene, are nowadays a relevant topic in the field of spintronics. Here, via europium doping, single spin-polarized bands are generated in monolayer graphene supported by the Co(0001) surface. The doping is controlled by Eu positioning, allowing for the formation of a -valley localized single spin-polarized low-dispersive parabolic band close to the Fermi energy when Eu is on top, and of a π* flat band with single spin character when Eu is intercalated underneath graphene.

Competition between deformation and free volume quantified by 3D image analysis of red blood cell.

Cells in living organisms are subjected to mechanical strains caused by external forces like overcrowding, resulting in strong deformations that affect cell function. We study the interplay between deformation and crowding of red blood cells (RBCs) in dispersions of nonabsorbing rod-like viruses. We identify a sequence of configurational transitions of RBC doublets, including configurations that can only be induced by long-ranged attraction: highly fluctuating T-shaped and face-to-face configurations at low, and doublets approaching a complete spherical configuration at high, rod concentrations.

RateML: A Code Generation Tool for Brain Network Models.

Whole brain network models are now an established tool in scientific and clinical research, however their use in a larger workflow still adds significant informatics complexity. We propose a tool, RateML, that enables users to generate such models from a succinct declarative description, in which the mathematics of the model are described without specifying how their simulation should be implemented. RateML builds on NeuroML's Low Entropy Model Specification (LEMS), an XML based language for specifying models of dynamical systems, allowing descriptions of neural mass and discretized neural field models, as implemented by the Virtual Brain (TVB) simulator: the end user describes their model's mathematics once and generates and runs code for different languages, targeting both CPUs for fast single simulations and GPUs for parallel ensemble simulations.

Simulations approaching data: cortical slow waves in inferred models of the whole hemisphere of mouse.

The development of novel techniques to record wide-field brain activity enables estimation of data-driven models from thousands of recording channels and hence across large regions of cortex. These in turn improve our understanding of the modulation of brain states and the richness of traveling waves dynamics. Here, we infer data-driven models from high-resolution in-vivo recordings of mouse brain obtained from wide-field calcium imaging.