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This paper aims to review the radical role of AI and deep learning in various functional areas of the business, such as marketing, finance, operations, human resources and customer service. Thus, based on the overview of the latest research and practices focusing on AI technologies in different industries, the possibilities of improving organizational efficiency by personalized AI for making decisions based on big data and personalizing clients' interactions with organizations are presented and discussed. Several operational issues, ethical concerns, and regulatory concerns have also been discussed in the review of the literature. Moreover, it covers material applications in the healthcare sector, the retail and manufacturing industry, agriculture and farming, and finance before considering possible future developments and themes for further investigation. Drawing from this revolutionary ethnographic review, organizations aiming to implement strategic and responsible optimization benefit from detailed guides., Comment: 8 pages

Liquid crystals are known for their optical birefringence, a property that gives rise to intricate patterns and colors when viewed in a microscope between crossed polarisers. Resulting images are rich in geometric patterns and serve as valuable fingerprints of the liquid crystal's intrinsic properties. By using machine learning techniques, it is possible to extract from the images information about, e.g., liquid crystal elastic constants, the scalar order parameter, local orientation of the director, etc. Machine learning can also be employed to identify phase transitions and classify different liquid crystalline phases and topological defects. In addition to well studied singular defects such as point or line disclinations, liquid crystals can also host non-singular solitonic defects such as skyrmions, hopfions, and torons. The solitons, with their localised and stable configurations, offer an alternative view into material properties and behaviour of liquid crystals. In this study, we demonstrate that the optical signatures of skyrmions can be utilised effectively in machine learning to predict important system parameters. Our method focuses specifically on the skyrmion-localised regions, reducing significantly the computational cost. By training convolutional neural networks on simulated polarised optical microscopy images of liquid crystal skyrmions, we showcase the ability of trained networks to accurately predict several selected parameters such as the free energy, cholesteric pitch, and strength of applied electric fields. This study highlights the importance of localized topologically arrested order parameter configurations for materials characterisation research empowered by state-of-the-art data science methods, and may pave the way for the development of advanced skyrmion-based applications.

Solitons in liquid crystals are spatially localised stable configuration of the liquid crystal orientational order parameter that exhibit emergent particle-like properties such as mutual interaction, translational motion and reconfigurable self-asembling behaviour in oscillating electric fields. Understanding solitons' out-of-equilibrium interactions remains a significant challenge. In this study, we present a minimalist model capable to address this challenge. We derive analytically elastic multipole interaction potentials between two solitons assuming two dimensional LC configurations. We determine the soliton's elastic dipole and quadrupole moments based on the equilibrium director textures obtained as minimizers of the Frank-Oseen free energy functional. Incorporating the time dependence of the soliton's multipole moments in response to electric field oscillations, we carry out particle-based simulations that demonstrate the formation of soliton chains and two dimensional clusters by varying the amplitude and/or the frequency of the electric field, in agreement with experiments. The presented formalism may serve as a benchmark model for future theoretical developments incorporating, e.g. higher order elastic multipoles or/and many body interactions.

The Yang-Mills-Chern-Simons theory in three-dimensional Minkowski space-time is studied in a gauge-fixing scheme which interpolates between the covariant gauge and light-cone gauge, the interpolating gauge-fixing. The ultraviolet finiteness of the theory is proved via the Becchi-Rouet-Stora (BRS) algebraic renormalization procedure, which allows us to demonstrate the vanishing of all $\beta$-functions and all anomalous dimensions to all orders in perturbation theory., Comment: 6 pages

This paper aims at introducing a methodology to compute stable coupled state-space models for dynamic substructuring applications by introducing two novel approaches targeted to accomplish this task: a) a procedure to impose Newtons's second law without relying on the use of undamped RCMs (residual compensation modes) and b) a novel approach to impose stability on unstable coupled state-space models. The enforcement of stability is performed by dividing the unstable model into two different models, one composed by the stable poles (stable model) and the other composed by the unstable ones (unstable model). Then, the poles of the unstable state-space model are forced to be stable, leading to the computation of a stabilized state-space model. Afterwards, to make sure that the Frequency Response Functions (FRFs) of the stabilized model well match the FRFs of the unstable model, the Least-Squares Frequency Domain (LSFD) method is exploited to update the modal parameters of the stabilized model composed by the pairs of complex conjugate poles. The validity of the proposed methodologies is presented and discussed by exploiting experimental data. Indeed, by exploiting the FRFs of a real system, accurate state-space models respecting Newton's second law are computed. Then, decoupling and coupling operations are performed with the identified state-space models, no matter the models resultant from the decoupling/coupling operations are unstable. Stability is then imposed on the computed unstable coupled model by following the approach proposed in this paper. The methodology proved to work well on these data. Moreover, the paper also shows that the coupled state-space models obtained using this methodology are suitable to be exploited in time-domain analyses and simulations.

A $r$-role assignment of a simple graph $G$ is an assignment of $r$ distinct roles to the vertices of $G$, such that two vertices with the same role have the same set of roles assigned to related vertices. Furthermore, a specific $r$-role assignment defines a role graph, in which the vertices are the distinct $r$ roles, and there is an edge between two roles whenever there are two related vertices in the graph $G$ that correspond to these roles. We consider complementary prisms, which are graphs formed from the disjoint union of the graph with its respective complement, adding the edges of a perfect matching between their corresponding vertices. In this work, we characterize the complementary prisms that do not admit a $3$-role assignment. We highlight that all of them are complementary prisms of disconnected bipartite graphs. Moreover, using our findings, we show that the problem of deciding whether a complementary prism has a $3$-role assignment can be solved in polynomial time., Comment: 20 pages, 4 figures

The publication of the \emph{Gaia} catalogue and improvements in methods to determine memberships and fundamental parameters of open clusters has led to major advances in recent years. However, important parameters such as the masses of these objects, although being studied mostly in some isolated cases, have not been addressed in large homogeneous samples based on \emph{Gaia} data, taking into account details such as binary fractions. Consequently, relevant aspects such as the existence of mass segregation were not adequately studied. Within this context, in this work, we introduce a new method to determine individual stellar masses, including an estimation for the ones in binary systems. This method allows us to study the mass of open clusters, as well as the mass functions of the binary star populations. We validate the method and its efficiency and characterize uncertainties using a grid of synthetic clusters with predetermined parameters. We highlight the application of the method to the Pleiades cluster, showing that the results obtained agree with the current consensus in the literature as well as recent \emph{Gaia} data. We then applied the procedure to a sample of 773 open clusters with fundamental parameters determined using \emph{Gaia Early Data Release 3 (eDR3)} data, obtaining their masses. Subsequently, we investigated the relation between the masses and other fundamental parameters of the clusters. Among the results, we found no significant evidence that clusters in our sample lose and segregate mass with age., Comment: 26 pages, 17 figures, accepted for publication in Monthly Notices of the Royal Astronomical Society

Identifying the necessary conditions for the onset of rigidity in a gel remains a challenge. It has been suggested that local particle coordination could be used to establish such conditions, but rigid gels occur for various coordination numbers. Combining simulations, oscillatory rheology, and a percolation analysis, for particles where the valence can be controlled, we find that the onset of rigidity coincides with the percolation of particles with three or more bonds, which arises after the connectivity percolation. We show that the rigidity results from an interplay of bonding and non-bonding interactions, providing insight into low-valence colloidal gel rigidity.

The formation of groups of interacting individuals improves performance and fitness in many decentralised systems, from micro-organisms to social insects, from robotic swarms to artificial intelligence algorithms. Often, group formation and high-level coordination in these systems emerge from individuals with limited information-processing capabilities implementing low-level rules of communication to signal to each other. Here, we show that, even in a community of clueless individuals incapable of processing information and communicating, a dynamic environment can coordinate group formation by transiently storing memory of the earlier passage of individuals. Our results identify a new mechanism of indirect coordination via shared memory that is primarily promoted and reinforced by dynamic environmental factors, thus overshadowing the need for any form of explicit signalling between individuals. We expect this pathway to group formation to be relevant for understanding and controlling self-organisation and collective decision making in both living and artificial active matter in real-life environments.

Flare frequency distributions represent a key approach to addressing one of the largest problems in solar and stellar physics: determining the mechanism that counter-intuitively heats coronae to temperatures that are orders of magnitude hotter than the corresponding photospheres. It is widely accepted that the magnetic field is responsible for the heating, but there are two competing mechanisms that could explain it: nanoflares or Alfv\'en waves. To date, neither can be directly observed. Nanoflares are, by definition, extremely small, but their aggregate energy release could represent a substantial heating mechanism, presuming they are sufficiently abundant. One way to test this presumption is via the flare frequency distribution, which describes how often flares of various energies occur. If the slope of the power law fitting the flare frequency distribution is above a critical threshold, $\alpha=2$ as established in prior literature, then there should be a sufficient abundance of nanoflares to explain coronal heating. We performed $>$600 case studies of solar flares, made possible by an unprecedented number of data analysts via three semesters of an undergraduate physics laboratory course. This allowed us to include two crucial, but nontrivial, analysis methods: pre-flare baseline subtraction and computation of the flare energy, which requires determining flare start and stop times. We aggregated the results of these analyses into a statistical study to determine that $\alpha = 1.63 \pm 0.03$. This is below the critical threshold, suggesting that Alfv\'en waves are an important driver of coronal heating., Comment: 1,002 authors, 14 pages, 4 figures, 3 tables, published by The Astrophysical Journal on 2023-05-09, volume 948, page 71

Motivated by recent experimental results that reveal rich collective dynamics of thousands-to-millions of active liquid crystal skyrmions we have developed a coarse grained particle-based model of the dynamics of skyrmions in dilute regime. The basic physical mechanism of the skyrmion motion is related to the non-reciprocal rotational dynamics of the liquid crystal director field when the electric field is turned {\it on} and {\it off}. Guided by fine grained results of the Frank-Oseen continuum approach, we have mapped this non-reciprocal director distortions onto an effective force acting asymmetrically upon switching the electrical field {\it on} or {\it off}. The coarse grained model correctly reproduces the skyrmion dynamics, including the velocity reversal as a function of the frequency of a pulse width modulated driving voltage. We have also obtained approximate analytical expressions for the phenomenological model parameters encoding their dependence upon the cholesteric pitch and the strength of the electric field. This has been achieved by fitting coarse grained skyrmion trajectories to those determined in the framework of the Frank-Oseen model.

We investigate the evolution dynamics of inhomogeneous discrete-time one-dimensional quantum walks displaying long-range correlations in both space and time. The associated quantum coin operators are built to exhibit a random inhomogeneity distribution of long-range correlations embedded in the time evolution protocol through a fractional Brownian motion with spectrum following a power-law behavior, $S(k)\sim 1/k^{\nu}$. The power-law correlated disorder encoded in the phases of the quantum coin is shown to give rise to a wide variety of spreading patterns of the qubit states, from localized to subdiffusive, diffusive, and superdiffusive (including ballistic) behavior, depending on the relative strength of the parameters driving the correlation degree. Dispersion control is then possible in one-dimensional discrete-time quantum walks by suitably tunning the long-range correlation properties assigned to the inhomogeneous quantum coin operator.

Equilibrium gels of colloidal particles can be realized through the introduction of a second species, a linker that mediates the bonds between the colloids. A gel forming binary mixture whose linkers can self-assemble into linear chains while still promoting the aggregation of particles is considered in this work. The particles are patchy particles with $f_C$ patches of type $C$ and the linkers are patchy particles with $2$ patches of type $A$ and $f_B$ patches of type B. The bonds between patches of type $A$ ($AA$ bonds) promote the formation of linear chains of linkers. Two different ways (model A and model B) of bonding the linkers to the particles - or inducing branching - are studied. In model A, there is a competition between chaining and branching, since the bonding between linkers and particles is done through $AC$ bonds only. In model B linkers aggregate to particles through bonds $BC$ only, making chaining and branching independent. The percolation behaviour of these two models is studied in detail, employing a generalized Flory-Stockmayer theory and Monte Carlo simulations. The self-assembly of linkers into chains reduces the fraction of particles needed for percolation to occur (models A and B) and induces percolation when the fraction of particles is high (model B). Percolation by heating and percolation loops in temperature composition diagrams are obtained when the formation of chains is energetically favourable, by increasing the entropic gain of branching (model A). Chaining and branching are found to follow a model dependent relation at percolation, which shows that, for the same composition, longer chains require less branching for percolation to occur.

The study of the interactions of living adherent cells with mechanically stable (visco)elastic materials enables understanding and exploiting physiological phenomena mediated by cell-extracellular communication. However, insight on the interaction of cells and surrounding objects with different stability patterns upon cell contact might unveil cell responses that may be engineered for innovative applications. Here, it is hypothesized that the efficiency of cell attachment, spreading and movement across a free-packed granular bed of microparticles depend on microparticle diameter, raising the possibility of a necessary minimum traction force for the reinforcement of cell-particle bonds, and long-term cell adhesion. The results suggest that microparticles with 14-20 {\mu}m are prone to cell-mediated mobility, holding the potential of inducing early cell detachment, while objects with diameters from 38-85 {\mu}m enable long-lasting cell adhesion and proliferation. An in-silico hybrid particle-based model that addresses time-dependent biological mechanisms of cell adhesion is proposed, providing inspiration for engineering platforms to address healthcare-related challenges.

We investigate the outbreak of anomalous quantum wavefunction amplitudes in a one-dimensional tight-binding lattice featuring correlated diagonal disorder. Such rogue-wave-like behavior is fostered by a competition between localization and mobility. The effective correlation length of the disorder is ultimately responsible for bringing the local disorder strength to a minimum, fuelling the occurrence of extreme events of much higher amplitudes, specially when compared to the case of uncorrelated disorder. Our findings are valid for a class of discrete one-dimensional systems and reveal profound aspects of the role of randomness in rogue-wave generation., Comment: 6 pages, 6 figures

We study how discrete-time quantum walks behave under short-range correlated noise. By considering noise as a source of inhomogeneity of quantum gates, we introduce a primitive relaxation in the uncorrelated stochastic noise assumption: binary pair correlations manifesting in the random distribution. Considering different quantum gates, we examined the transport properties for both spatial and temporal noise regimes. For spatial inhomogeneities, we show noise correlations driving quantum walks from the well-known exponentially localized condition to superdiffusive spreading. This scenario displays an exciting performance in which the superdiffusive exponent is almost invariant to the inhomogeneity degree. The time-asymptotic regime and the finite-size scaling also unveil an emergent superdiffusive behavior for quantum walks undergoing temporal noise correlation, replacing the diffusive regime exhibited when noise is random and uncorrelated. However, results report some quantum gates insensitive to correlations, contrasting with the spatial noise scenario. Results and following discussions help us understand the underlying mechanism of superdiffusive quantum walks, including those with deterministic aperiodic inhomogeneities., Comment: 8 pages and 7 figures

The dynamics of a three-state quantum walk with amplitude-dependent phase shifts is investigated. We consider two representative inputs whose linear evolution is known to display either full dispersion of the wave packet or intrinsic localization on the initial position. The nonlinear counterpart presents much more involved dynamics featuring self-trapping, solitonic pulses, radiation, and chaotic-like behavior. We show that nonlinearity leads to a metastable self-trapped wavepacket component that radiates in the long-time regime with the survival probability $\propto t^{-1/2}$. A sudden dynamical transition from such metastable state to the point when the radiation process is triggered is found for a set of parameters., Comment: 5 pages, 5 figures

Active colloids belong to a class of non-equilibrium systems where energy uptake, conversion and dissipation occurs at the level of individual colloidal particles, which can lead to particles self-propelled motion and surprising collective behavior. Examples include coexistence of vapor and liquid-like steady states for active particles with repulsive interactions only, phenomena known as motility induced phase transition. Similarly to motile unicellular organisms, active colloids tend to accumulate at confining surfaces forming dense adsorbed films. In this work, we study the structure and dynamics of aggregates of self-propelled particle near confining solid surfaces, focusing on the effects of the particle anisotropic interactions. We performed Langevin dynamics simulations of two complementary models for active particles: ellipsoidal particles interacting through Gay-Berne potential, and rod-like particles composed of several repulsive Lennard-Jones beads. We observe a non-monotonic behavior of the structure of clusters formed along the confining surface as a function of the particle aspect ratio, with a film spreading when particles are near spherical, compact clusters with hedgehog-like particle orientation for more elongated active particles, and a complex dynamical behavior for intermediate aspect ratio. The stabilization time of cluster formation along the confining surface also displays a non-monotonic dependence on the aspect ratio, with a local minimum at intermediate values. Additionally, we demonstrate that the hedgehog-like aggregates formed by Gay-Berne ellipsoids exhibit higher structural stability as compared to the ones formed by purely repulsive active rods, which are stable due to the particle activity only.

Rogue waves are rapid and unpredictable events of exceptional amplitude reported in various fields, such as oceanography and optics, with much of the interest being targeted towards their physical origins and likelihood of occurrence. Here, we use the all-round framework of discrete-time quantum walks to study the onset of those events due to a random phase modulation, unveiling its long-tailed statistics, distribution profile, and dependence upon the degree of randomness. We find that those rogue waves belong the Gumbel family of extreme value distributions., Comment: The article contains 5 pages and 5 figures

We perform a finite-time scaling analysis over the detrapping point of a three-state quantum walk on the line. The coin operator is parameterized by $\rho$ that controls the wavepacket spreading velocity. The input state prepared at the origin is set as symmetric linear combination of two eigenstates of the coin operator with a characteristic mixing angle $\theta$, one of them being the component that results in full spreading occurring at $\theta_c(\rho)$ for which no fraction of the wavepacket remains trapped near the initial position. We show that relevant quantities such as the survival probability and the participation ratio assume single parameter scaling forms at the vicinity of the detrapping angle $\theta_c$. In particular, we show that the participation ratio grows linearly in time with a logarithmic correction, thus shedding light on previous reports of sublinear behavior.