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Music and speech are encountered daily and are unique to human beings. Both are transformed by the auditory pathway from an initial acoustical encoding to higher level cognition. Studies of cortex have revealed distinct brain responses to music and speech, but differences may emerge in the cortex or may be inherited from different subcortical encoding. In the first part of this study, we derived the human auditory brainstem response (ABR), a measure of subcortical encoding, to recorded music and speech using two analysis methods. The first method, described previously and acoustically based, yielded very different ABRs between the two sound classes. The second method, however, developed here and based on a physiological model of the auditory periphery, gave highly correlated responses to music and speech. We determined the superiority of the second method through several metrics, suggesting there is no appreciable impact of stimulus class (i.e., music vs speech) on the way stimulus acoustics are encoded subcortically. In this study’s second part, we considered the cortex. Our new analysis method resulted in cortical music and speech responses becoming more similar but with remaining differences. The subcortical and cortical results taken together suggest that there is evidence for stimulus-class dependent processing of music and speech at the cortical but not subcortical level. 

Abstract Non‐native plant pests and pathogens threaten biodiversity, ecosystem function, food security, and economic livelihoods. As new invasive populations establish, often as an unintended consequence of international trade, they can become additional sources of introductions, accelerating global spread through bridgehead effects. While the study of non‐native pest spread has used computational models to provide insights into drivers and dynamics of biological invasions and inform management, efforts have focused on local or regional scales and are challenged by complex transmission networks arising from bridgehead population establishment. This paper presents a flexible spatiotemporal stochastic network model called PoPS (Pest or Pathogen Spread) Global that couples international trade networks with core drivers of biological invasions—climate suitability, host availability, and propagule pressure—quantified through open, globally available databases to forecast the spread of non‐native plant pests. The modular design of the framework makes it adaptable for various pests capable of dispersing via human‐mediated pathways, supports proactive responses to emerging pests when limited data are available, and enables forecasts at different spatial and temporal resolutions. We demonstrate the framework using a case study of the invasive planthopper spotted lanternfly (Lycorma delicatula). The model was calibrated with historical, known spotted lanternfly introductions to identify potential bridgehead populations that may contribute to global spread. This global view of phytosanitary pandemics provides crucial information for anticipating biological invasions, quantifying transport pathways risk levels, and allocating resources to safeguard plant health, agriculture, and natural resources. 

In the context of the life cycle and evolution of active galactic nuclei (AGNs), environment plays a key role. In particular, the over-dense environments of galaxy groups, where dynamical interactions and bulk motions have significant impact, offer an excellent but under-explored window into the life cycles of AGNs and the processes that shape the evolution of relativistic plasma. Pilot survey observations with the Australian Square Kilometre Array Pathfinder (ASKAP) Evolutionary Map of the Universe (EMU) survey have recovered diffuse emission associated with the nearby (z = 0.0228) galaxy group HCG15, which was revealed to be strongly linearly polarised. We studied the properties of this emission in unprecedented detail to settle questions about its nature and its relation to the group-member galaxies. We performed a multi-frequency spectropolarimetric study of HCG15, incorporating our ASKAP EMU observations as well as new data from MeerKAT, the LOw-Frequency ARray (LOFAR), Giant Metrewave Radio Telescope (GMRT), and Karl G. Jansky Very Large Array (VLA), along with X-ray data fromXMM-Newtonand optical spectra from Himalayan Chandra Telescope (HCT). Our study confirms that the diffuse structure represents remnant emission from historic AGN activity that is likely to be associated with HCG15-D, some 80 − 86 Myr ago (based on an ageing analysis). We detected significant highly linearly-polarised emission from a diffuse ‘ridge-like’ structure with a highly ordered magnetic field. Our analysis suggests that this emission is generated by the draping of magnetic field lines in the intra-group medium (IGrM). Subsequent investigations with simulations would further improve our understanding of this phenomenon. We confirm that HCG15-C is a group-member galaxy. Finally, we report the detection of thermal emission associated with a background cluster at a redshift ofz ≈ 0.87 projected onto the IGrM of HCG15, which matches the position and redshift of the recent Sunyaev-Zel’dovich (SZ) detection of ACT-CL J0207.8+0209. 

Abstract Models that are both spatially and temporally dynamic are needed to forecast where and when non-native pests and pathogens are likely to spread, to provide advance information for natural resource managers. The potential US range of the invasive spotted lanternfly (SLF, Lycorma delicatula ) has been modeled, but until now, when it could reach the West Coast’s multi-billion-dollar fruit industry has been unknown. We used process-based modeling to forecast the spread of SLF assuming no treatments to control populations occur. We found that SLF has a low probability of first reaching the grape-producing counties of California by 2027 and a high probability by 2033. Our study demonstrates the importance of spatio-temporal modeling for predicting the spread of invasive species to serve as an early alert for growers and other decision makers to prepare for impending risks of SLF invasion. It also provides a baseline for comparing future control options. 

Addressing “wicked” problems like urban stormwater management necessitates building shared understanding among diverse stakeholders with the influence to enact solutions cooperatively. Fuzzy cognitive maps (FCMs) are participatory modeling tools that enable diverse stakeholders to articulate the components of a socio-environmental system (SES) and describe their interactions. However, the spatial scale of an FCM is rarely explicitly considered, despite the influence of spatial scale on SES. We developed a technique to couple FCMs with spatially explicit survey data to connect stakeholder conceptualization of urban stormwater management at a regional scale with specific stormwater problems they identified. We used geospatial data and flooding simulation models to quantitatively evaluate stakeholders’ descriptions of location-specific problems. We found that stakeholders used a wide variety of language to describe variables in their FCMs and that government and academic stakeholders used significantly different suites of variables. We also found that regional FCM did not downscale well to concerns at finer spatial scales; variables and causal relationships important at location-specific scales were often different or missing from the regional FCM. This study demonstrates the spatial framing of stormwater problems influences the perceived range of possible problems, barriers, and solutions through spatial cognitive filtering of the system’s boundaries.