Active nematic fluids confined in narrow channels are known to generate spontaneous flows when the activity is sufficiently intense. Recently, it was demonstrated [R. Green, J. Toner, and V. Vitelli, Phys. Rev. Fluids 2, 104201 (2017)] that if the molecular anchoring at the channel walls is conflicting, i.e., perpendicular on one plate and parallel on the other, flows are initiated even in the zero activity limit. An analytical laminar velocity profile for this specific configuration was derived within a simplified nematohydrodynamic model in which the nematic order parameter is a fixed-magnitude unit vector n. The solution holds in a regime where the flow does not perturb the nematic order imposed by the walls. In this study, we explore systematically active flows in this confined geometry with a more general theoretical model that uses a second-rank tensor order parameter Q to express both the magnitude and orientation of the nematic phase. The Q-model allows for the presence of defects and biaxial, in addition to uniaxial, molecular arrangements. Our aim is to provide a unified picture, beyond the limiting regime explored previously, to serve as a guide for potential microfluidic applications that exploit the coupling between the orientational order of the molecules and the velocity field to finely control the flow and overcome the intrinsic difficulties of directing and pumping fluids at the microscale. We reveal how the nematic-flow coupling is not only dependent on geometrical constraints, but is also highly sensitive to material and flow parameters. We specifically stress the key role played by the activity and the flow aligning parameter, and we show that solutions mostly depend on two dimensionless parameters. We find that for large values of the activity parameter, the flow is suppressed for contractile particles while it is either sustained or suppressed for extensile particles depending on whether they tend to align or tumble when subject to shear. We explain these distinct behaviors by an argument based on the results of the stability analysis applied to two simpler configurations: active flows confined between parallel plates with either orthogonal or perpendicular alignment at both walls. We show that the analytical laminar solution derived for the n model in the low activity limit is found also in the Q model, both analytically and numerically. This result is valid for both contractile and extensile particles and for a flow-tumbling as well as aligning nematics. We remark that this velocity profile can be derived for generic boundary conditions. To stress the more general nature of the Q model, we conclude by providing a numerical example of a biaxial three-dimensional thresholdless active flow for which we show that biaxiality is especially relevant for a weakly first-order isotropic-nematic phase transition.

We investigate the collective transport properties of microscopic magnetic rollers that propel close to a surface due to a circularly polarized, rotating magnetic field. The applied field exerts a torque to the particles, which induces a net rolling motion close to a surface. The collective dynamics of the particles result from the balance between magnetic dipolar interactions and hydrodynamic ones. We show that, when hydrodynamics dominate, i.e. for high particle spinning, the collective mean velocity linearly increases with the particle density. In this regime we analyse the clustering kinetics, and find that hydrodynamic interactions between the anisotropic, elongated particles, induce preferential cluster growth along a direction perpendicular to the driving one, leading to dynamic clusters that easily break and reform during propulsion.

We study a liquid-gas front propagation in a modulated Hele-Shaw cell by means of multiphase computational fluid mechanics based on the three-dimensional Navier-Stokes equations. In the simulations an obstacle that partially fills the gap is placed at the center of the cell, and the liquid-gas interface is driven at a constant velocity. We study the morphological differences between imbibition and drainage for a wide range of capillary numbers, and explore how the wetting properties of the constriction affect the amount of liquid that remains trapped in the draining process. We observe increasing remaining volumes with increasing capillary number and decreasing contact angle. The present CFD implementation for a single mesa defect provides insight into a wide number of practical applications.

Magnetic rotors energized by external fields represent a promising platform for investigation of complex dynamics and self-organization in fluid media. The intricate balance between magnetic and hydrodynamic interactions drives rotor's dynamics, and promotes novel self-assembled states. Non-invasive nature of actuation of particles by external fields suggests their applications as microscale mixers and cargo carriers.

Recent experiments have shown that the spontaneous activity of developing dissociated neuronal cultures can be described as a process of highly inhomogeneous nucleation and front propagation due to the localization of noise activity, i.e., noise focusing. However, the basic understanding of the mechanisms of noise build-up leading to the nucleation remains an open fundamental problem. Here we present a minimal dynamical model called stochastic quorum percolation that can account for the observed phenomena, while providing a robust theoretical framework. The model reproduces the first- and second-order phase transitions of bursting dynamics and neuronal avalanches, respectively, and captures the profound effect metric correlations in the network topology can have on the dynamics. The application of our results to other systems such as in the propagation of infectious diseases and of rumors is discussed.

Neuroimaging studies of intellectual disability (ID) have been published over the last three decades, but the findings are often inconsistent, and therefore, the neural correlates of ID remain elusive. This article aims to study the different publications in task-functional magnetic resonance imaging (fMRI) and different ID populations to make a qualitative and quantitative analysis on this field.

Museums and cultural institutions are increasingly striving to respond to the interests and needs of the society that hosts them. This means, apart from other actions, that these institutions must be involved in the health and wellbeing of society, and the creation of cultural activities aimed at people with cognitive impairment, a group of individuals that is growing worldwide due to the aging of society and the increasing prevalence of dementia. The involved sectors are aware of the potential and benefits of activities for this population, even though there is much research to be conducted. To date, no systematic review has focused on the benefits of cultural activities for cognitively impaired people. This study aimed to explore the benefits of different modalities of cultural activities with evidence from 145 studies from various databases, which met the inclusion criteria. Significant improvements in general cognition, quality of life (QoL), emotional wellbeing, socialization, and communication were generally reported after interventions, with a reduction in depression symptoms. There was not enough evidence to prove memory, language, or daily functioning improvements attributable to cultural interventions. There were no significant reductions reported in apathy, sadness, agitation, or anxiety.

In Alzheimer’s disease, two fundamental aspects become important for caregivers: ambiguity and ambivalence. Thus, anticipatory grief is considered an active psychological process that is very different from the mere anticipation of death. The present study aims to determine which characteristics of family caregivers of people with dementia, such as age, gender, educational level, relationship with the person with dementia, years with dementia or years as a caregiver, are related to the presence of anticipatory grief. A cross-sectional design was employed. The sample consisted of a total of 129 subjects who cared for a family member with dementia. A sociodemographic data sheet and a battery of tests measure the presence of anticipatory grief, caregiver burden and/or psychopathology. The results obtained allowed us to confirm some of the hypotheses regarding the anticipatory grief construct, the importance of the care time factor, in years and per day, as well as the relevance of the previous demographic and psychopathological profile (being female, spouse function and possible depressive symptomatology). Likewise, from the prediction analyzes performed, it seems that these variables can predict anticipatory grief. These results propose interesting opportunities to formulate care proposals to professionals and family caregivers in relation to care tasks and caregiver skills

Emerging evidence suggests that an effective or functional connectivity network does not use a static process over time but incorporates dynamic connectivity that shows changes in neuronal activity patterns. Using structural equation models (SEMs), we estimated a dynamic component of the effective network through the effects (recursive and nonrecursive) between regions of interest (ROIs), taking into account the lag 1 effect. The aim of the paper was to find the best structural equation model (SEM) to represent dynamic effective connectivity in people with Down syndrome (DS) in comparison with healthy controls. Twenty-two people with DS were registered in a functional magnetic resonance imaging (fMRI) resting-state paradigm for a period of six minutes. In addition, 22 controls, matched by age and sex, were analyzed with the same statistical approach. In both groups, we found the best global model, which included 6 ROIs within the default mode network (DMN). Connectivity patterns appeared to be different in both groups, and networks in people with DS showed more complexity and had more significant effects than networks in control participants. However, both groups had synchronous and dynamic effects associated with ROIs 3 and 4 related to the upper parietal areas in both brain hemispheres as axes of association and functional integration. It is evident that the correct classification of these groups, especially in cognitive competence, is a good initial step to propose a biomarker in network complexity studies.

Oxytocin (OXT; hereafter OT) and arginine vasopressin or vasotocin (AVP or VT; hereafter VT) are neurotransmitter ligands that function through specific receptors to control diverse functions1,2. Here we performed genomic analyses on 35 species that span all major vertebrate lineages, including newly generated high-contiguity assemblies from the Vertebrate Genomes Project3,4. Our findings support the claim5 that OT (also known as OXT) and VT (also known as AVP) are adjacent paralogous genes that have resulted from a local duplication, which we infer was through DNA transposable elements near the origin of vertebrates and in which VT retained more of the parental sequence. We identified six major oxytocin–vasotocin receptors among vertebrates. We propose that all six of these receptors arose from a single receptor that was shared with the common ancestor of invertebrates, through a combination of whole-genome and large segmental duplications. We propose a universal nomenclature based on evolutionary relationships for the genes that encode these receptors, in which the genes are given the same orthologous names across vertebrates and paralogous names relative to each other. This nomenclature avoids confusion due to differential naming in the pre-genomic era and incomplete genome assemblies, furthers our understanding of the evolution of these genes, aids in the translation of findings across species and serves as a model for other gene families.

Background: Studies on complexity indicators in the field of functional connectivity derived from resting-state fMRI (rs-fMRI) in Down syndrome (DS) samples and their possible relationship with cognitive functioning variables are rare. We analyze how some complexity indicators estimated in the subareas that constitute the default mode network (DMN) might be predictors of the neuropsychological outcomes evaluating Intelligence Quotient (IQ) and cognitive performance in persons with DS. Methods: Twenty-two DS people were assessed with the Kaufman Brief Test of Intelligence (KBIT) and Frontal Assessment Battery (FAB) tests, and fMRI signals were recorded in a resting state over a six-minute period. In addition, 22 controls, matched by age and sex, were evaluated with the same rs-fMRI procedure. Results: There was a significant difference in complexity indicators between groups: the control group showed less complexity than the DS group. Moreover, the DS group showed more variance in the complexity indicator distributions than the control group. In the DS group, significant and negative relationships were found between some of the complexity indicators in some of the DMN networks and the cognitive performance scores. Conclusions: The DS group is characterized by more complex DMN networks and exhibits an inverse relationship between complexity and cognitive performance based on the negative parameter estimates.

Computer simulations of experimentally comparable system sizes in soft matter often require considerable elapsed times. The use of many cores can reduce the needed time, ideally proportionally to the number of processors. In this paper a parallel computational method using coarray Fortran is implemented and tested for large systems of purely block copolymer melts, as well as block copolymer nanocomposites. A satisfactory strong scaling is shown up to 512 cores while a weak scaling with a drop in performance is achieved up to 4096 cores. The scaling of the parallel cell dynamic simulations scheme displays no drawbacks over MPI and provides an example of the simplicity of the coarray approach. The code has been tested on several architectures and compilers. The hybrid block copolymer/nanoparticle algorithm can achieve previously unavailable system sizes.

Down syndrome (DS) is a chromosomal disorder that causes intellectual disability. Few studies have been conducted on functional connectivity using resting-state fMRI (functional magnetic resonance imaging) signals or more specifically, on the relevant structure and density of the default mode network (DMN). Although data on this issue have been reported in adult DS individuals (age: >45 years), the DMN properties in young DS individuals have not been studied. The aim of this study was to describe the density and structure of the DMN network from fMRI signals in young DS (age: <36 years).

The presence of missing data and small sample sizes are very common in social and health sciences. Concurrently to present a methodology to solve the small sample size and missing data, we aim to present a definition of Cognitive Reserve for people with Down Syndrome. This population has become an appealing focus to study this concept because of the high incidence of dementia. The accidental sample comprised 35 persons with DS (16–35 years). A total of 12 variables were acquired, four of them had missing data. Two types of multiple imputation were made. Confirmatory factor analysis with Bayesian estimations was performed on the final database with non-informative priors. However, to solve the sample size problem, two additional corrections were made: first, we followed the Jiang and Yuan (2017) schema, and second, we made a Jackknife correlation correction. The estimations of the confirmatory factor analysis, as well as the global fit, are adequate. As an applied perspective, the acceptable fit of our model suggests the possibility of operationalizing the latent factor Cognitive Reserve in a simple way to measure it in the Down Syndrome population.

Abusive leaders affect employees’ emotions and health and produce counterproductive behaviors that cause economic damage to organizations. The literature has focused predominantly on the antecedents of abusive supervision and its negative impact, providing knowledge on mechanisms that link abusive supervision to consequences for subordinates. There has been limited research on the supervisor perspective, on the group level, and on recovery. This review makes three contributions: first, we examine the theoretical approaches used by previous research studies to understand abusive supervision. Second, we analyze the types of mechanisms that explain how and when an abusive supervision process occurs. Third, we identify and discuss applied methodologies and limitations. Based on the preferred reporting items for systematic reviews and meta-analysis guidelines, and transactional well-being process perspective, we analyzed 171 empirical manuscripts and 239 samples between 2010 and July 2020. We identified a growth in abusive supervision research between 2018 and 2020 and found 101 different theories. Most of these theories view abusive supervision from a social, relational, or affective perspective, but seldom from an emotional perspective. We classified four types of mechanisms: simple relations between abusive supervision and antecedent-consequences (12), moderators (47), mediators (26), and a combination of mediators and moderators (86). We found that research has mostly been performed at the employee level or on dyads; studies that analyze the team level are rarely found. We identified two methodological problems: cross-sectional designs, which do not allow the analysis of its causality, and the increased risk of common method variance that may influence the results obtained via single-source data. In conclusion, the theories used have focused on employee perceptions, which have not enabled the broadening of the abusive supervision concept to include the supervisor’s perspective and a recovery-related perspective. Research on how and when abusive supervision occurs analyzed with complex mechanisms using emotional variables and appropriate daily methodologies has been scarce. We propose a theoretical expansion including emotional theories to uncover emotional consequences of abusive supervision and the recovery concept to provide a deeper insight into abusive supervision process. We contend that longitudinal and diary designs that include teams and supervisor levels are necessary.

Based on (overdamped) Stokesian dynamics simulations and video microscopy experiments, we study the non equilibrium dynamics of a sheared colloidal cluster, which is confined to a two-dimensional disk. The experimental system is composed of a mixture of paramagnetic and non magnetic polystyrene particles, which are held in the disk by time shared optical tweezers. The paramagnetic particles are located at the center of the disk and are actuated by an external, rotating magnetic field that induces a magnetic torque. We identify two different steady states by monitoring the mean angular velocities per ring. The first one is characterized by rare slip events, where the inner rings momentarily depin from the outer ring, which is kept static by the set of optical traps. For the second state, we find a bistability of the mean angular velocities, which can be understood from the analysis of the slip events in the particle trajectories. We calculate the particle waiting- and jumping time distributions and estimate a time scale between slips, which is also reflected by a plateau in the mean squared azimuthal displacement. The dynamical transition is further reflected by the components of the stress tensor, revealing a shearthinning behavior as well as shear stress overshoots. Finally, we briefly discuss the observed transition in the context of stochastic thermodynamics and how it may open future directions in this field.

Recommender systems are cognitive computing systems designed to support humans in their decision-making processes through convincing, timely product suggestions. In the field of recommender systems, critique-based recommenders have been widely applied as an effective approach for guiding users through a product space in pursuit of suitable products. To date, no critique-based approach has included an assistant that support users in their search in a pleasant way. In this paper, we describe how we integrate an assistant within a critique-based recommender. We consider the proposed assistant to be cognitive because its reasoning process when recommending products is based on a cognitively-inspired clustering algorithm. The proposal is evaluated by users and compared with a non-assistant approach. The results of this research demonstrate that the integration of a cognitive assistant within the recommender improves the user experience and increases the performance of the recommendation process, i.e., users need fewer cycles to achieve the desired product or service. (C) 2020 Published by Elsevier B.V.

We study the structural and dynamical consequences of damage in spatial neuronal networks. Inspired by real in vitro networks, we construct directed networks embedded in a two-dimensional space and follow biological rules for designing the wiring of the system. As a result, synthetic cultures display strong metric correlations similar to those observed in real experiments. In its turn, neuronal dynamics is incorporated through the Izhikevich model adopting the parameters derived from observation in real cultures. We consider two scenarios for damage, targeted attacks on those neurons with the highest out-degree and random failures. By analyzing the evolution of both the giant connected component and the dynamical patterns of the neurons as nodes are removed, we observe that network activity halts for a removal of 50% of the nodes in targeted attacks, much lower than the 70% node removal required in the case of random failures. Notably, the decrease of neuronal activity is not gradual. Both damage scenarios portray "boosts" of activity just before full silencing that are not present in equivalent random (Erdos-Renyi) graphs. These boosts correspond to small, spatially compact subnetworks that are able to maintain high levels of activity. Since these subnetworks are absent in the equivalent random graphs, we hypothesize that metric correlations facilitate the existence of local circuits sufficiently integrated to maintain activity, shaping an intrinsic mechanism for resilience. Published under license by AIP Publishing.

Author Summary Neuronal circuits exhibit homeostatic plasticity mechanisms to cope with perturbations or damage. A central mechanism is 'synaptic scaling,' a self-organized response in which the strength of neurons' excitatory synapses is adjusted to compensate for activity variations. Here we present experiments in which the excitatory connectivity of in vitro cortical networks is progressively weakened through chemical action. The spontaneous activity and effective connectivity of the whole network is monitored as degradation progresses, and the capacity of the network for broad information communication is quantified through the global efficiency. We observed that the network responded to the perturbation by strengthening the effective connectivity, reaching a hyperefficient state for moderate perturbations. The study proves the importance of 'synaptic scaling' as a driver for functional reorganization and network-wide resilience.

An elusive phenomenon in network neuroscience is the extent of neuronal activity remodeling upon damage. Here, we investigate the action of gradual synaptic blockade on the effective connectivity in cortical networks in vitro. We use two neuronal cultures configurations-one formed by about 130 neuronal aggregates and another one formed by about 600 individual neurons-and monitor their spontaneous activity upon progressive weakening of excitatory connectivity. We report that the effective connectivity in all cultures exhibits a first phase of transient strengthening followed by a second phase of steady deterioration. We quantify these phases by measuring G(EFF), the global efficiency in processing network information. We term hyperefficiency the sudden strengthening of G(EFF) upon network deterioration, which increases by 20-50% depending on culture type. Relying on numerical simulations we reveal the role of synaptic scaling, an activity-dependent mechanism for synaptic plasticity, in counteracting the perturbative action, neatly reproducing the observed hyperefficiency. Our results demonstrate the importance of synaptic scaling as resilience mechanism.

Changes in membrane deformation and compressibility, induced by an external electric field, are investigated using coarse-grained MARTINI force field simulations in a salt-free environment. We observe changes in the area of the membrane above a critical electric field. Below this value, the membrane compressibility modulus is found to decrease monotonically. For higher electric fields, the membrane projected area remains constant while the net interfacial area increases, with the corresponding compressibility moduli, show the opposite behavior. We find that the mechanical parameters, surface tension and bending modulus, of a freely floating membrane in the absence of explicit ions, are unaffected by the presence of the electric field. We believe these results have a bearing on our understanding of the electroformation of uncharged lipids in a salt-free environment.

Scaffolds and patterned substrates are among the most successful strategies to dictate the connectivity between neurons in culture. Here, we used numerical simulations to investigate the capacity of physical obstacles placed on a flat substrate to shape structural connectivity, and in turn collective dynamics and effective connectivity, in biologically-realistic neuronal networks. We considered mu-sized obstacles placed in mm-sized networks. Three main obstacle shapes were explored, namely crosses, circles and triangles of isosceles profile. They occupied either a small area fraction of the substrate or populated it entirely in a periodic manner. From the point of view of structure, all obstacles promoted short length-scale connections, shifted the in- and out-degree distributions toward lower values, and increased the modularity of the networks. The capacity of obstacles to shape distinct structural traits depended on their density and the ratio between axonal length and substrate diameter. For high densities, different features were triggered depending on obstacle shape, with crosses trapping axons in their vicinity and triangles funneling axons along the reverse direction of their tip. From the point of view of dynamics, obstacles reduced the capacity of networks to spontaneously activate, with triangles in turn strongly dictating the direction of activity propagation. Effective connectivity networks, inferred using transfer entropy, exhibited distinct modular traits, indicating that the presence of obstacles facilitated the formation of local effective microcircuits. Our study illustrates the potential of physical constraints to shape structural blueprints and remodel collective activity, and may guide investigations aimed at mimicking organizational traits of biological neuronal circuits.

This book aims to contribute to the overall, integrated understanding of the processes of language contact and their evolution, be they the result of political or economic (dis)integrations or migrations or for technological reasons. Via an interdisciplinary, holistic approach, it also aims to support the theoretical grounding of a unified, common sociolinguistic paradigm, based on an ecological and complexity perspective. This approach built on the fact that linguistic structures do not live in isolation from their social functions and must be situated in relation to the sub-and supra-systems that determine their existence if we are to understand their fortunes. It is a useful contribution to understanding and promoting the processes of linguistic revitalization in the world, combining at the same time the maintenance and development of diversity while ensuring the intercommunication of human species.

Connectomes are spatially embedded networks whose architecture has been shaped by physical constraints and communication needs throughout evolution. Using a decentralized navigation protocol, we investigate the relationship between the structure of the connectomes of different species and their spatial layout. As a navigation strategy, we use greedy routing where nearest neighbors, in terms of geometric distance, are visited. We measure the fraction of successful greedy paths and their length as compared to shortest paths in the topology of connectomes. In Euclidean space, we find a striking difference between the navigability properties of mammalian and non-mammalian species, which implies the inability of Euclidean distances to fully explain the structural organization of their connectomes. In contrast, we find that hyperbolic space, the effective geometry of complex networks, provides almost perfectly navigable maps of connectomes for all species, meaning that hyperbolic distances are exceptionally congruent with the structure of connectomes. Hyperbolic maps therefore offer a quantitative meaningful representation of connectomes that suggests a new cartography of the brain based on the combination of its connectivity with its effective geometry rather than on its anatomy only. Hyperbolic maps also provide a universal framework to study decentralized communication processes in connectomes of different species and at different scales on an equal footing.

We investigate the directional locking effects that arise when a monolayer of paramagnetic colloidal particles is driven across a triangular lattice of magnetic bubbles. We use an external rotating magnetic field to generate a two-dimensional traveling wave ratchet forcing the transport of particles along a direction that intersects two crystallographic axes of the lattice. We find that, while single particles show no preferred direction, collective effects induce transversal current and directional locking at high density via a spontaneous symmetry breaking. The colloidal current may be polarized via an additional bias field that makes one transport direction energetically preferred.

In this perspective communication, we briefly sketch the current state of computational (bio)material research and discuss possible solutions for the four challenges that have been increasingly identified within this community: (i) the desire to develop a unified framework for testing the consistency of implementation and physical accuracy for newly developed methodologies, (ii) the selection of a standard format that can deal with the diversity of simulation data and at the same time simplifies data storage, data exchange, and data reproduction, (iii) how to deal with the generation, storage, and analysis of massive data, and (iv) the benefits of efficient "core" engines. Expressed viewpoints are the result of discussions between computational stakeholders during a Lorentz center workshop with the prosaic title Workshop on Multi-scale Modeling and are aimed at (i) improving validation, reporting and reproducibility of computational results, (ii) improving data migration between simulation packages and with analysis tools, (iii) popularizing the use of coarse-grained and multi-scale computational tools among non-experts and opening up these modern computational developments to an extended user community.