Lack of privileged access to awareness for rewarding social scenes in Autism Spectrum Disorder

Reduced social motivation is hypothesised to underlie social behavioural symptoms of Autism Spectrum Disorder (ASD). The extent to which rewarding social stimuli are granted privileged access to awareness in ASD is currently unknown. We use continuous flash suppression to investigate whether individuals with and without ASD show privileged access to awareness for social over nonsocial rewarding scenes that are closely matched for stimulus features. Strong evidence for a privileged access to awareness for rewarding social over nonsocial scenes was observed in neurotypical adults. No such privileged access was seen in ASD individuals, and moderate support for the null model was noted. These results suggest that the purported deficits in social motivation in ASD may extend to early processing mechanisms

Reduced fire severity offers near-term buffer to climate-driven declines in conifer resilience across the western United States

Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration. © 2023 the Author(s)

A decision support framework for proactive maintenance of water and wastewater systems

Proactive maintenance of assets is a much sought after goal in the water and wastewater industry, where substantial savings could be made by identifying impending failures in pumps and other essential components of the system. A detailed analysis of the operational behaviour of the monitored assets can be used as the foundation to generate estimations on the likelihood of a failure or malfunction in a particular component based on knowledge of previous behavioural patterns. Preventative maintenance or component replacement can then be optimally scheduled based on need, as opposed to traditional reactive maintenance strategies. In most current condition monitoring software, an alarm is normally raised once a fault has occurred, therefore often requiring immediate action. On the other hand, combining the condition monitoring and fault log data that is normally acquired with expert knowledge of the meaning and causes of faults embedded in the software allows predictive maintenance to be implemented. The paper reports on a number of advanced machine learning techniques that have been applied to operational data acquired over a significant period of water pump operation. Results from a representative site within Scottish Water's water network will be presented that demonstrate the application of such software techniques can indeed surface changes in parameters, for example flow and pump power drawn, forming the basis to infer the state of components and the onset of changes in the health of the asset