Melodic contour supersedes short-term statistical learning in expressive accentuation.

Sensory systems are permanently bombarded with complex stimuli. Cognitive processing of such complex stimuli may be facilitated by accentuation of important elements. In the case of music listening, alteration of some surface features -such as volume and duration- may facilitate the cognitive processing of otherwise high-level information, such as melody and harmony.

Stochastic block hypergraph model.

The stochastic block model is widely used to generate graphs with a community structure, but no simple alternative currently exists for hypergraphs, in which more than two nodes can be connected together through a hyperedge. We discuss here such a hypergraph generalization, based on the clustering connection probability P_{ij} between nodes of communities i and j, and that uses an explicit and modulable hyperedge formation process. We focus on the standard case where P_{ij}=pδ_{ij}+q(1-δ_{ij}) when 0≤q≤p (δ_{ij} is the Kronecker symbol).

Quantifying metadata relevance to network block structure using description length.

Network analysis is often enriched by including an examination of node metadata. In the context of understanding the mesoscale of networks it is often assumed that node groups based on metadata and node groups based on connectivity patterns are intrinsically linked. This assumption is increasingly being challenged, whereby metadata might be entirely unrelated to structure or, similarly, multiple sets of metadata might be relevant to the structure of a network in different ways.

Biological invasions and epidemics with nonlocal diffusion along a line.

The goal of this work is to understand and quantify how a line with nonlocal diffusion given by an integral enhances a reaction-diffusion process occurring in the surrounding plane. This is part of a long term programme where we aim at modelling, in a mathematically rigorous way, the effect of transportation networks on the speed of biological invasions or propagation of epidemics. We prove the existence of a global propagation speed and characterise in terms of the parameters of the system the situations where such a speed is boosted by the presence of the line.

Symmetry breaking in optimal transport networks.

Engineering multilayer networks that efficiently connect sets of points in space is a crucial task in all practical applications that concern the transport of people or the delivery of goods. Unfortunately, our current theoretical understanding of the shape of such optimal transport networks is quite limited. Not much is known about how the topology of the optimal network changes as a function of its size, the relative efficiency of its layers, and the cost of switching between layers.

Modelling the optimization of world-class 400 m and 1,500 m running performances using high-resolution data.

The 400 m and 1,500 m are track events that rely on different but important contributions from both the aerobic and anaerobic energy systems. The purpose of this study is to model men's and women's 400 m and 1,500 m championship performances to gain a deeper understanding of the key mechanical and physiological factors affecting running speed and bend running using high-resolution data from live competition (10 Hz). To investigate World-class athletes' instantaneous speeds, propulsive forces and aerobic and anaerobic energy, we model and simulate the performances of the men's and women's European Athletics 400 m champions, Matthew Hudson-Smith and Femke Bol, as well as the men's European Athletics 1,500 m champion, Jakob Ingebrigtsen, and the women's European Athletics U23 1,500 m champion, Gaia Sabbatini.

Structure of road networks and the shape of the macroscopic fundamental diagram.

The macroscopic fundamental diagram (MFD) is a large-scale description of the traffic in an urban area and relates the average car flow to the average car density. This MFD has been observed empirically in several cities but how its properties are related to the structure of the road network has remained unclear so far. The MFD displays in general a maximum flow q^{*} for an optimal car density k^{*} which are crucial quantities for practical applications.

The role of complexity for digital twins of cities.

We argue that theories and methods drawn from complexity science are urgently needed to guide the development and use of digital twins for cities. The theoretical framework from complexity science takes into account both the short-term and the long-term dynamics of cities and their interactions. This is the foundation for a new approach that treats cities not as large machines or logistic systems but as mutually interwoven self-organizing phenomena, which evolve, to an extent, like living systems.

Generative models for two-ground-truth partitions in networks.

A myriad of approaches have been proposed to characterize the mesoscale structure of networks most often as a partition based on patterns variously called communities, blocks, or clusters. Clearly, distinct methods designed to detect different types of patterns may provide a variety of answers' to the networks mesoscale structure. Yet even multiple runs of a given method can sometimes yield diverse and conflicting results, producing entire landscapes of partitions which potentially include multiple (locally optimal) mesoscale explanations of the network.

Stochastic equations and cities.

Stochastic equations constitute a major ingredient in many branches of science, from physics to biology and engineering. Not surprisingly, they appear in many quantitative studies of complex systems. In particular, this type of equation is useful for understanding the dynamics of urban population.

Functional architecture of M1 cells encoding movement direction.

In this paper we propose a neurogeometrical model of the behaviour of cells of the arm area of the primary motor cortex (M1). We will mathematically express as a fiber bundle the hypercolumnar organization of this cortical area, first modelled by Georgopoulos (Georgopoulos et al., 1982; Georgopoulos, 2015).

Scenarios for a post-COVID-19 world airline network.

The airline industry was severely hit by the COVID-19 crisis with an average demand decrease of about 64 % (IATA, April 2020), which triggered already several bankruptcies of airline companies all over the world. While the robustness of the world airline network (WAN) was mostly studied as a homogeneous network, we introduce a new tool for analyzing the impact of a company failure: the "airline company network" where two airlines are connected if they share at least one route segment. Using this tool, we observe that the failure of companies well connected with others has the largest impact on the connectivity of the WAN.

Evolution of road infrastructure in large urban areas.

Most cities in the United States and around the world were organized around car traffic. In particular, large structures such as urban freeways or ring roads were built for reducing car traffic congestion. With the evolution of public transportation and working conditions, the future of these structures and the organization of large urban areas is uncertain.

Class of models for random hypergraphs.

Despite the recently exhibited importance of higher-order interactions for various processes, few flexible (null) models are available. In particular, most studies on hypergraphs focus on a small set of theoretical models. Here, we introduce a class of models for random hypergraphs which displays a similar level of flexibility of complex network models and where the main ingredient is the probability that a node belongs to a hyperedge.

Association between location of out-of-hospital cardiac arrest, on-scene socioeconomic status, and accessibility to public automated defibrillators in two large metropolitan areas in Canada and France.

Aim: To compare walking access times to automated external defibrillators (AEDs) between area-level quintiles of socioeconomic status (SES) in out-of-hospital cardiac arrest (OHCA) cases occurring in 2 major urban regions of Canada and France.

Methods: This was an international, multicenter, retrospective cohort study of adult, non-traumatic OHCA cases in the metropolitan Vancouver (Canada) and Rhône County (France) regions that occurred between 2014 and 2018. We calculated area-level SES for each case, using quintiles of country-specific scores (Q5 = most deprived).

Spatial structure of city population growth.

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas.

Evidence That Nine Autistic Women Out of Ten Have Been Victims of Sexual Violence.

Background: Research indicates that sexual violence affects about 30% of women in the general population and between two to three times as much for autistic women.

Materials And Methods: We investigated prevalence of sexual abuse, autistic traits and a range of symptoms, using an online survey addressed to the women of the French autistic community ( = 225). We assessed victimization through an open question and through a specific questionnaire, derived from the Sexual Experiences Survey-Short Form Victimization.

Local impacts on road networks and access to critical locations during extreme floods.

Floods affected more than 2 billion people worldwide from 1998 to 2017 and their occurrence is expected to increase due to climate warming, population growth and rapid urbanization. Recent approaches for understanding the resilience of transportation networks when facing floods mostly use the framework of percolation but we show here on a realistic high-resolution flood simulation that it is inadequate. Indeed, the giant connected component is not relevant and instead, we propose to partition the road network in terms of accessibility of local towns and define new measures that characterize the impact of the flooding event.

Draw me Science: Multi-level and multi-scale reconstruction of knowledge dynamics with phylomemies.

Unlabelled: In 1751, Jean le Rond d'Alembert had a dream: "to make a genealogical or encyclopedic tree which will gather the various branches of knowledge together under a single point of view and will serve to indicate their origin and their relationships to one another". In this paper, we address the question identifying the branches of science by taking advantage of the massive digitization of scientific production. In the framework of complex systems studies, we first formalize the notion of level and scale of knowledge dynamics.

Perceived Usefulness of Telerehabilitation of Musculoskeletal Disorders: A Belgium-France Pilot Study during Second Wave of COVID-19 Pandemic.

Background: COVID-19 has affected the practice of physiotherapy, and telerehabilitation (TR) may be seen as an alternative model of care if it is accepted by patients and physiotherapists. This study investigates the perceived usefulness of TR and the intention to use it among physiotherapists and patients from Belgium and France concerned with musculoskeletal disorders (MSDs) during the pandemic period.

Methods: An online questionnaire based on the technology-acceptance model was designed.

Categorical Perception: A Groundwork for Deep Learning.

Classification is one of the major tasks that deep learning is successfully tackling. Categorization is also a fundamental cognitive ability. A well-known perceptual consequence of categorization in humans and other animals, categorical perception, is notably characterized by a within-category compression and a between-category separation: two items, close in input space, are perceived closer if they belong to the same category than if they belong to different categories.

Confidence-Controlled Hebbian Learning Efficiently Extracts Category Membership From Stimuli Encoded in View of a Categorization Task.

In experiments on perceptual decision making, individuals learn a categorization task through trial-and-error protocols. We explore the capacity of a decision-making attractor network to learn a categorization task through reward-based, Hebbian-type modifications of the weights incoming from the stimulus encoding layer. For the latter, we assume a standard layer of a large number of stimulus-specific neurons.

Pace and motor control optimization for a runner.

We present a model which encompasses pace optimization and motor control effort for a runner on a fixed distance. We see that for long races, the long term behaviour is well approximated by a turnpike problem, that allows to define an approximate optimal velocity. We provide numerical simulations quite consistent with this approximation which leads to a simplified problem.