High-statistics modeling of complex pedestrian avoidance scenarios

Quantitatively modeling the trajectories and behavior of pedestrians walking in crowds is an outstanding fundamental challenge deeply connected with the physics of flowing active matter, from a scientific point of view, and having societal applications entailing individual safety and comfort, from an application perspective. In this contribution, we review a pedestrian dynamics modeling approach, previously proposed by the authors, aimed at reproducing some of the statistical features of pedestrian motion. Comparing with high-statistics pedestrian dynamics measurements collected in real-life conditions (from hundreds of thousands to millions of trajectories), we modeled quantitatively the statistical features of the undisturbed motion (i.e. in absence of interactions with other pedestrians) as well as the avoidance dynamics triggered by a pedestrian incoming in the opposite direction. This was accomplished through (coupled) Langevin equations with potentials including multiple preferred velocity states and preferred paths. In this chapter we review this model, discussing some of its limitations, in view of its extension toward a more complex case: the avoidance dynamics of a single pedestrian walking through a crowd that is moving in the opposite direction. We analyze some of the challenges connected to this case and present extensions to the model capable of reproducing some features of the motion

Immunohistochemical study of subepidermal connective of molluscan integument

Sections of integument from gastropod, bivalve and cephalopod species were studied immunohistochemically to determine reactivity to antibody against the type I-like collagen from Sepia cartilage and antibodies against components of the extracellular matrix (ECM) of vertebrate connective tissue: type I, III, IV, V, and VI collagens, laminin, nidogen and heparan sulphate. All samples exhibited similar reactivities to the antibodies, although differences in the intensity and localization of the immunostaining were found that were clearly correlated with between-species differences in integumental ultrastructure. These findings indicate that the composition of the integumental ECM is similar in the three classes of molluscs examined and that several types of collagen are present. However molluscan subepidermal connective tissue differs from the ECM of vertebrate dermis: molluscan integumental ECM contains collagens similar to type I, V and VI collagens but has no type III-similar collagen. Furthermore molecules similar to the type IV collagen, laminin, nidogen and heparan sulphate of vertebrates were present ubiquitously in molluscan basement membrane, confirming the statement that the structure and composition of basement membrane have remained constant throughout the evolution of all animal phyla

Continuous measurements of real-life bidirectional pedestrian flows on a wide walkway

Employing partially overlapping overhead \kinectTMS sensors and automatic pedestrian tracking algorithms we recorded the crowd traffic in a rectilinear section of the main walkway of Eindhoven train station on a 24/7 basis. Beside giving access to the train platforms (it passes underneath the railways), the walkway plays an important connection role in the city. Several crowding scenarios occur during the day, including high- and low-density dynamics in uni- and bi-directional regimes. In this paper we discuss our recording technique and we illustrate preliminary data analyses. Via fundamental diagrams-like representations we report pedestrian velocities and fluxes vs. pedestrian density. Considering the density range $0$ - $1.1\,$ped/m$^2$, we find that at densities lower than $0.8\,$ped/m$^2$ pedestrians in unidirectional flows walk faster than in bidirectional regimes. On the opposite, velocities and fluxes for even bidirectional flows are higher above $0.8\,$ped/m$^2$

Alkylation of isopropanol with ethanol over heterogeneous catalysts

The importance of synthesis of carbon-carbon bonds is reflected by the fact that Nobel Prizes in Chemistry have been given to this area: The Grignard reaction (1912), the Diels-Alder reaction (1950), the Witting reaction (1979), the olefin metathesis Y. Chauvin, R.H. Grubbs and R.R. Schrock (2005), the palladiumcatalyzed cross-coupling reactions to R. F. Heck, A. Suzuki, E. Negishi (2010). For the first time ever alkylation of isopropanol with ethanol was carried out over heterogeneous 0.2-1 wt.% Au and/or 0.02-0.3 wt. %Ni - containing catalysts without any sacrificial agents and/or presence of acidic/base additives. The catalyst containing 0.2 wt.% Au and 0.18 wt.% Ni supported on γ-Al2O3 was found to be the most selective in the cross-coupling route. Total selectivity of coupling products reached up to 70 %, conversion of the both initial alcohols was 50 %. Structural investigations of the Au, Ni - containing catalysts permitted to determine probable active sites peculiarities that provide effective one-pot alkylation of isopropanol with ethanol

Anatomic dissociation of selective and suppressive processes in visual attention

Visual spatial attention is associated with activation in parietal regions as well as with modulation of visual activity in ventral occipital cortex. Within the parietal lobe, localisation of activity has been hampered by variation in individual anatomy. Using fMRI within regions of interest derived from individual functional maps, we examined the response of superior parietal lobule, intraparietal sulcus, and ventral occipital cortex in 11 normal adults as attention was directed to the left and right visual hemifields during bilateral visual stimulation. Activation in ventral occipital cortex was augmented contralateral to the attended hemifield (p < 0.006), while intraparietal activation was augmented ipsilaterally (p < 0.009), and superior parietal lobule showed no modulation of activity as a function of attended hemifield. These findings suggest that spatial enhancement of relevant stimuli in ventral occipital cortex is complemented by an intraparietal response associated with suppression of, or preparation of a reflexive shift of attention towards, irrelevant stimuli. The spatial attention system in superior parietal cortex, in contrast, may be driven to equal degrees by currently attended stimuli and by stimuli that are potential targets of attention

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention

High-statistics pedestrian dynamics on stairways and their probabilistic fundamental diagrams

Staircases play an essential role in crowd dynamics, allowing pedestrians to flow across large multi-level public facilities such as transportation hubs, and office buildings. Achieving a robust understanding of pedestrian behavior in these facilities is a key societal necessity. What makes this an outstanding scientific challenge is the extreme randomness intrinsic to pedestrian behavior. Any quantitative understanding necessarily needs to be probabilistic, including average dynamics and fluctuations. In this work, we analyze data from an unprecedentedly high statistics year-long pedestrian tracking campaign, in which we anonymously collected millions of trajectories across a staircase within Eindhoven train station (NL). Made possible thanks to a state-of-the-art, faster than real-time, computer vision approach hinged on 3D depth imaging, and YOLOv7-based depth localization. We consider both free-stream conditions, i.e. pedestrians walking in undisturbed, and trafficked conditions, uni/bidirectional flows. We report the position vs density, considering the crowd as a 'compressible' physical medium. We show how pedestrians willingly opt to occupy fewer space than available, accepting a certain degree of compressibility. This is a non-trivial physical feature of pedestrian dynamics and we introduce a novel way to quantify this effect. As density increases, pedestrians strive to keep a minimum distance d = 0.6 m from the person in front of them. Finally, we establish first-of-kind fully resolved probabilistic fundamental diagrams, where we model the pedestrian walking velocity as a mixture of a slow and fast-paced component. Notably, averages and modes of velocity distribution turn out to be substantially different. Our results, including probabilistic parametrizations based on few variables, are key towards improved facility design and realistic simulation of pedestrians on staircases

Extreme statistics and extreme events in dynamical models of turbulence

We present a study of the intermittent properties of a shell model of turbulence with statistics of ∼107 eddy turn over time, achieved thanks to an implementation on a large-scale parallel GPU factory. This allows us to quantify the inertial range anomalous scaling properties of the velocity fluctuations up to the 24th-order moment. Through a careful assessment of the statistical and systematic uncertainties, we show that none of the phenomenological and theoretical models previously proposed in the literature to predict the anomalous power-law exponents in the inertial range are in agreement with our high-precision numerical measurements. We find that at asymptotically high-order moments, the anomalous exponents tend toward a linear scaling, suggesting that extreme turbulent events are dominated by one leading singularity. We found that systematic corrections to scaling induced by the infrared and ultraviolet (viscous) cutoffs are the main limitations to precision for low-order moments, while high orders are mainly affected by the finite statistical samples.. The high-fidelity numerical results reported in this work offer an ideal benchmark for the development of future theoretical models of intermittency in dynamical systems for either extreme events (high-order moments) or typical fluctuations (low-order moments). For the latter, we show that we achieve a precision in the determination of the inertial range scaling exponents of the order of one part over ten thousand (fifth significant digit), which may be considered a record for out-of-equilibrium fluid-mechanics systems and models