When Companies Don’t Make the Ad: A Multi-Method Inquiry into the Differential Effectiveness of Consumer-Generated Advertising

This four-part multi-method investigation into the under-researched yet increasingly prevalent phenomenon of consumer-generated advertising (CGA) confirms a performance advantage over traditional advertising and suggests a rationale for this differential. CGAs benefit from heightened consumer engagement and increased trustworthiness. CGAs also garner perceived quality advantages that are linked to consumers lowering their expectations and using different evaluation criteria to judge the ad. The ad creator—a personalized, identifiable and relatable entity in the case of CGAs— plays a central role in anchoring and shaping ad reactions. The “consumer-made” characteristic—the fact that CGAs are not made by companies but by independent people—is powerful and stands strong in the face of commercial motives, and presents paradigmatic implications for advertising practice and research

The World as an Interface: Exploring the Ethical Challenges of the Emerging Metaverse

Mixed reality is emerging as the next phase of personal computing. Once Apple Glass is released augmented and mixed reality will go mainstream and the impact on our behaviour will be as dramatic as when the iPhone was released. In parallel, what used to be 2D webpages are becoming 3D worlds, collectively forming a meta universe of virtual or mixed reality domains -the ‘Metaverse’. Mixed reality is precisely where the best affordances of the digital and analogue worlds should work together to create entirely new interactive learning, social and economic opportunities. In this paper we reflect on how the physical world will itself become an interface making reality even more machine-readable, click-able, and searchable. We further propose how society will need to ensure that the appropriate boundary management is in place to allow us as co-creators of the metaverse to protect our ethical rights of privacy, integrity, and autonomy

Nanostickers for cells : a model study using cell-nanoparticle hybrid aggregates

We present direct evidence that nanoparticles (NPs) can stick together cells that are inherently non-adhesive. Using cadherin-depleted S180 murine cells lines, which exhibit very low cell-cell adhesion, we show that NPs can assemble dispersed single cells into large cohesive aggregates. The dynamics of aggregation, which is controlled by diffusion and collision, can be described as a second-order kinetic law characterized by a rate of collision that depends on the size, concentration, and surface chemistry of the NPs. We model the cell-cell adhesion induced by the "nanostickers'' using a three-state dynamical model, where the NPs are free, adsorbed on the cell membrane or internalized by the cells. We define a "sticking efficiency parameter'' to compare NPs and look for the most efficient type of NP. We find that 20 nm carboxylated polystyrene NPs are more efficient nanostickers than 20 nm silica NPs which were reported to induce fast wound healing and to glue soft tissues. Nanostickers, by increasing the cohesion of tissues and tumors, may have important applications for tissue engineering and cancer treatment.Peer reviewe

Choisir Paris : les grandes donations aux musées de la Ville de Paris

La Ville de Paris est l’un des premiers collectionneurs de France. Ses quatorze musées, réunis depuis 2013 au sein de l’établissement public Paris Musées, conservent une part importante de ce patrimoine. Nées de l’intérêt porté par la Ville à sa propre mémoire et à sa vie artistique, ces collections sont aussi le fruit du rapport passionné que de nombreux amateurs et collectionneurs ont entretenu avec la capitale, qu’ils ont choisie pour conserver leurs trésors patiemment assemblés. Ce « choix de Paris » répond à des motifs qui, pour divers qu’ils soient, font sens et écrivent une manière d’histoire de l’art. Hommage aux donateurs, le colloque dont sont issus ces actes s’est donné pour objectif de mieux faire connaître cette histoire, d’éclairer la genèse des collections des musées de la Ville de Paris et de témoigner de l’actualité de la recherche sur les grandes donations qui les ont enrichis. Ces essais témoignent aussi du souhait de Paris Musées de renforcer la recherche au sein de ses différentes activités

Water relations of evergreen and drought-deciduous trees along a seasonally dry tropical forest chronosequence

Seasonally dry tropical forests (SDTF) are characterized by pronounced seasonality in rainfall, and as a result trees in these forests must endure seasonal variation in soil water availability. Furthermore, SDTF on the northern Yucatan Peninsula, Mexico, have a legacy of disturbances, thereby creating a patchy mosaic of different seral stages undergoing secondary succession. We examined the water status of six canopy tree species, representing contrasting leaf phenology (evergreen vs. drought-deciduous) at three seral stages along a fire chronosequence in order to better understand strategies that trees use to overcome seasonal water limitations. The early-seral forest was characterized by high soil water evaporation and low soil moisture, and consequently early-seral trees exhibited lower midday bulk leaf water potentials (ΨL) relative to late-seral trees (−1.01 ± 0.14 and −0.54 ± 0.07 MPa, respectively). Although ΨL did not differ between evergreen and drought-deciduous trees, results from stable isotope analyses indicated different strategies to overcome seasonal water limitations. Differences were especially pronounced in the early-seral stage where evergreen trees had significantly lower xylem water δ18O values relative to drought-deciduous trees (−2.6 ± 0.5 and 0.3 ± 0.6‰, respectively), indicating evergreen species used deeper sources of water. In contrast, drought-deciduous trees showed greater enrichment of foliar 18O (∆18Ol) and 13C, suggesting lower stomatal conductance and greater water-use efficiency. Thus, the rapid development of deep roots appears to be an important strategy enabling evergreen species to overcome seasonal water limitation, whereas, in addition to losing a portion of their leaves, drought-deciduous trees minimize water loss from remaining leaves during the dry season

How Structure Determines Correlations in Neuronal Networks

Networks are becoming a ubiquitous metaphor for the understanding of complex biological systems, spanning the range between molecular signalling pathways, neural networks in the brain, and interacting species in a food web. In many models, we face an intricate interplay between the topology of the network and the dynamics of the system, which is generally very hard to disentangle. A dynamical feature that has been subject of intense research in various fields are correlations between the noisy activity of nodes in a network. We consider a class of systems, where discrete signals are sent along the links of the network. Such systems are of particular relevance in neuroscience, because they provide models for networks of neurons that use action potentials for communication. We study correlations in dynamic networks with arbitrary topology, assuming linear pulse coupling. With our novel approach, we are able to understand in detail how specific structural motifs affect pairwise correlations. Based on a power series decomposition of the covariance matrix, we describe the conditions under which very indirect interactions will have a pronounced effect on correlations and population dynamics. In random networks, we find that indirect interactions may lead to a broad distribution of activation levels with low average but highly variable correlations. This phenomenon is even more pronounced in networks with distance dependent connectivity. In contrast, networks with highly connected hubs or patchy connections often exhibit strong average correlations. Our results are particularly relevant in view of new experimental techniques that enable the parallel recording of spiking activity from a large number of neurons, an appropriate interpretation of which is hampered by the currently limited understanding of structure-dynamics relations in complex networks

Rapid response to the M_w 4.9 earthquake of November 11, 2019 in Le Teil, Lower Rhône Valley, France

On November 11, 2019, a Mw 4.9 earthquake hit the region close to Montelimar (lower Rhône Valley, France), on the eastern margin of the Massif Central close to the external part of the Alps. Occuring in a moderate seismicity area, this earthquake is remarkable for its very shallow focal depth (between 1 and 3 km), its magnitude, and the moderate to large damages it produced in several villages. InSAR interferograms indicated a shallow rupture about 4 km long reaching the surface and the reactivation of the ancient NE-SW La Rouviere normal fault in reverse faulting in agreement with the present-day E-W compressional tectonics. The peculiarity of this earthquake together with a poor coverage of the epicentral region by permanent seismological and geodetic stations triggered the mobilisation of the French post-seismic unit and the broad French scientific community from various institutions, with the deployment of geophysical instruments (seismological and geodesic stations), geological field surveys, and field evaluation of the intensity of the earthquake. Within 7 days after the mainshock, 47 seismological stations were deployed in the epicentral area to improve the Le Teil aftershocks locations relative to the French permanent seismological network (RESIF), monitor the temporal and spatial evolution of microearthquakes close to the fault plane and temporal evolution of the seismic response of 3 damaged historical buildings, and to study suspected site effects and their influence in the distribution of seismic damage. This seismological dataset, completed by data owned by different institutions, was integrated in a homogeneous archive and distributed through FDSN web services by the RESIF data center. This dataset, together with observations of surface rupture evidences, geologic, geodetic and satellite data, will help to unravel the causes and rupture mechanism of this earthquake, and contribute to account in seismic hazard assessment for earthquakes along the major regional Cévenne fault system in a context of present-day compressional tectonics

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP