The Role of Dyadic Coordination in Organizing Visual Attention in 5‐Month‐Old Infants

In human infants, the ability to share attention with others is facilitated by increases in attentional selectivity and focus. Differences in early attention have been associated with socio‐cognitive outcomes including language, yet the social mechanisms of attention organization in early infancy have only recently been considered. Here, we examined how social coordination between 5‐month‐old infants and caregivers relate to differences in infant attention, including looking preferences, span, and reactivity to caregivers’ social cues. Using a naturalistic play paradigm, we found that 5‐month‐olds who received a high ratio of sensitive (jointly focused) contingent responses showed strong preferences for objects with which their caregivers were manually engaged. In contrast, infants whose caregivers exhibited high ratios of redirection (attempts to shift focus) showed no preferences for caregivers’ held objects. Such differences have implications for recent models of cognitive development, which rely on early looking preferences for adults’ manually engaged objects as a pathway toward joint attention and word learning. Further, sensitivity and redirectiveness predicted infant attention even in reaction to caregiver responses that were non‐referential (neither sensitive nor redirective). In response to non‐referentials, infants of highly sensitive caregivers oriented less frequently than infants of highly redirective caregivers, who showed increased distractibility. Our results suggest that specific dyadic exchanges predict infant attention differences toward broader social cues, which may have consequences for social‐cognitive outcomes.     

Neighborhood affluence protects against antenatal smoking: Evidence from a spatial multiple membership model

ABSTRACT

A spatial multiple membership model formalizes the effect of neighborhood affluence on antenatal smoking. The data are geocoded New Jersey birth certificate records linked to United States census tract-level data from 1999 to 2007. Neighborhood affluence shows significant spatial autocorrelation and local clustering. Better model fit is observed when incorporating the spatial clustering of neighborhood affluence into multivariate analyses. Relative to the spatial multiple membership model, the multilevel model that ignores spatial clustering produced downwardly biased standard errors; the effective sample size of the key parameter of interest (neighborhood affluence) is also lower. Residents of communities located in high-high affluence clusters likely have better access to health-promoting institutions that regulate antenatal smoking behaviors.     

Urban noise and grey-headed flying-fox vocalisations: evidence of the silentium effect

Urban Ecosystems - We investigated whether urban noise affected communication behavior of grey-headed flying-foxes (Pteropus poliocephalus), a highly vocal, communally roosting megabat species that...     

Stochastic Counterfactual Risk Analysis for the Vulnerability Assessment of Cyber‐Physical Attacks on Electricity Distribution Infrastructure Networks

In December 2015, a cyber‐physical attack took place on the Ukrainian electricity distribution network. This is regarded as one of the first cyber‐physical attacks on electricity infrastructure to have led to a substantial power outage and is illustrative of the increasing vulnerability of Critical National Infrastructure to this type of malicious activity. Few data points, coupled with the rapid emergence of cyber phenomena, has held back the development of resilience analytics of cyber‐physical attacks, relative to many other threats. We propose to overcome data limitations by applying stochastic counterfactual risk analysis as part of a new vulnerability assessment framework. The method is developed in the context of the direct and indirect socioeconomic impacts of a Ukrainian‐style cyber‐physical attack taking place on the electricity distribution network serving London and its surrounding regions. A key finding is that if decision‐makers wish to mitigate major population disruptions, then they must invest resources more‐or‐less equally across all substations, to prevent the scaling of a cyber‐physical attack. However, there are some substations associated with higher economic value due to their support of other Critical National Infrastructures assets, which justifies the allocation of additional cyber security investment to reduce the chance of cascading failure. Further cyber‐physical vulnerability research must address the tradeoffs inherent in a system made up of multiple institutions with different strategic risk mitigation objectives and metrics of value, such as governments, infrastructure operators, and commercial consumers of infrastructure services.