Divergent effects of short-term and continuous anthropogenic noise exposure on Western Bluebird parental care behavior.

Sensory environments are rapidly changing due to increased human activity in urban and non-urban areas alike. For instance, natural and anthropogenic sounds can interfere with parent-offspring communication and mask cues reflective of predation risk, resulting in elevated vigilance at the cost of provisioning. Here we present data from two separate studies involving anthropogenic noise and nestling provisioning behavior in Western Bluebirds (): one in response to short-term (1 h) experimental noise playback and a second in the context of nests located along a gradient of exposure to continuous noise.

Deep learning segmentation-based bone removal from computed tomography of the brain improves subdural hematoma detection.

Purpose: Timely identification of intracranial blood products is clinically impactful, however the detection of subdural hematoma (SDH) on non-contrast CT scans of the head (NCCTH) is challenging given interference from the adjacent calvarium. This work explores the utility of a NCCTH bone removal algorithm for improving SDH detection.

Methods: A deep learning segmentation algorithm was designed/trained for bone removal using 100 NCCTH.

Impacts of climate change on food security and resulting perinatal health impacts.

Climate change's impact on global food security is a pressing concern with profound consequences. Climate change disrupts the global food system through a number of mechanisms including extreme weather events, rising food prices, and compromised food quality. In this article, we explore the effect of climate change on food security and the resulting health impacts of poor nutrition on pregnant women and infants in the perinatal period.

Assessing the Performance of Models from the 2022 RSNA Cervical Spine Fracture Detection Competition at a Level I Trauma Center.

Purpose To evaluate the performance of the top models from the RSNA 2022 Cervical Spine Fracture Detection challenge on a clinical test dataset of both noncontrast and contrast-enhanced CT scans acquired at a level I trauma center. Materials and Methods Seven top-performing models in the RSNA 2022 Cervical Spine Fracture Detection challenge were retrospectively evaluated on a clinical test set of 1828 CT scans (from 1829 series: 130 positive for fracture, 1699 negative for fracture; 1308 noncontrast, 521 contrast enhanced) from 1779 patients (mean age, 55.8 years ± 22.