I’ve noticed that every year certain professors are distinguished with either the Leonard Ledvina Outstanding Teaching Award or the Donald B. King Distinguished Scholar Award. I feel sure that King and Ledvina were fascinating men – can you tell us more?

Abbot Pennings answers questions about Donald B. King and Leonard Ledvina, archived from the SNC website

Extremely loud & incredibly far: observing radio bright AGN into the cosmic dawn

In this thesis new methodologies are developed for the detection and systematic study of radio sources in the early universe. This allows us to gain a deeper understanding of the formation and evolution of galaxies, the activity of supermassive black holes, and the final phase transition of our universe: the epoch of reionization. Using the Low Frequency Array (LOFAR) telescope, this thesis systematically investigates the low radio frequency properties of quasars, the brightest non-variable objects in our cosmos, in the first billion years after the Big Bang. Through the discovery of new radio quasars in the early universe and subsequent studies, this thesis shows the diversity within the quasar population and highlights the importance of multi-wavelength observations for our comprehension of the formation and evolution of active supermassive black holes and their impact on the surrounding environment.Large scale structure and cosmolog

Induction of immunoglobulin A as a therapeutic intervention in allergic asthma

Allergic asthma is a chronic inflammatory disorder of the airways in response to inhaled allergens and is characterized by airway inflammation, bronchial hyperresponsiveness and a variable degree of airflow obstruction, leading to episodes of wheezing, coughing and breathlessness. In addition, structural changes (‘airway remodeling’) in the airway including subepithelial and airway wall fibrosis, goblet cell hyperplasia/metaplasia, smooth muscle thickening and increased vascularity are observed. In susceptible individuals, repeated exposure to harmless environmental allergens like house-dust mites (HDMs), molds, plant pollen and animal dander can lead to sensitization and development of a chronic immune response consisting of an effector cascade leading to immediate and late-phase reactions to allergens and subsequent characteristic clinical symptoms

Polygon Intersection-over-Union Loss for Viewpoint-Agnostic Monocular 3D Vehicle Detection

Monocular 3D object detection is a challenging task because depth information is difficult to obtain from 2D images. A subset of viewpoint-agnostic monocular 3D detection methods also do not explicitly leverage scene homography or geometry during training, meaning that a model trained thusly can detect objects in images from arbitrary viewpoints. Such works predict the projections of the 3D bounding boxes on the image plane to estimate the location of the 3D boxes, but these projections are not rectangular so the calculation of IoU between these projected polygons is not straightforward. This work proposes an efficient, fully differentiable algorithm for the calculation of IoU between two convex polygons, which can be utilized to compute the IoU between two 3D bounding box footprints viewed from an arbitrary angle. We test the performance of the proposed polygon IoU loss (PIoU loss) on three state-of-the-art viewpoint-agnostic 3D detection models. Experiments demonstrate that the proposed PIoU loss converges faster than L1 loss and that in 3D detection models, a combination of PIoU loss and L1 loss gives better results than L1 loss alone (+1.64% AP70 for MonoCon on cars, +0.18% AP70 for RTM3D on cars, and +0.83%/+2.46% AP50/AP25 for MonoRCNN on cyclists)

Water vapour total columns from SCIAMACHY spectra in the 2.36 μm window

The potential of the shortwave infrared channel of the atmospheric spectrometer SCIAMACHY on Envisat to provide accurate measurements of total atmospheric water vapour columns is explored. It is shown that good quality results can be obtained for cloud free scenes above the continents using the Iterative Maximum Likelihood Method. In addition to the standard cloud filter employed in this method, further cloud screening is obtained by comparing simultaneously retrieved methane columns with values expected from models. A novel method is used to correct for the scattering effects introduced in the spectra by the ice layer on the detector window. The retrieved water vapour total vertical columns for the period 2003–2007 are compared with spatially and temporally collocated values from the European Centre for Mid-Range Weather Forecast (ECMWF) data. The observed differences for individual measurements have standard deviations not higher than 0.3 g/cm^2 and an absolute mean value smaller than 0.01 g/cm^2 with some regional excursions. The use of recently published spectroscopic data for water vapour led to a significant improvement in the agreement of the retrieved water vapour total columns and the values derived from ECMWF data. This analysis thus supports the superior quality of the new spectroscopic information using atmospheric data

The Interstate-24 3D Dataset: a new benchmark for 3D multi-camera vehicle tracking

This work presents a novel video dataset recorded from overlapping highway traffic cameras along an urban interstate, enabling multi-camera 3D object tracking in a traffic monitoring context. Data is released from 3 scenes containing video from at least 16 cameras each, totaling 57 minutes in length. 877,000 3D bounding boxes and corresponding object tracklets are fully and accurately annotated for each camera field of view and are combined into a spatially and temporally continuous set of vehicle trajectories for each scene. Lastly, existing algorithms are combined to benchmark a number of 3D multi-camera tracking pipelines on the dataset, with results indicating that the dataset is challenging due to the difficulty of matching objects traveling at high speeds across cameras and heavy object occlusion, potentially for hundreds of frames, during congested traffic. This work aims to enable the development of accurate and automatic vehicle trajectory extraction algorithms, which will play a vital role in understanding impacts of autonomous vehicle technologies on the safety and efficiency of traffic

Virtual trajectories for I-24 MOTION: data and tools

This article introduces a new virtual trajectory dataset derived from the I-24 MOTION INCEPTION v1.0.0 dataset to address challenges in analyzing large but noisy trajectory datasets. Building on the concept of virtual trajectories, we provide a Python implementation to generate virtual trajectories from large raw datasets that are typically challenging to process due to their size. We demonstrate the practical utility of these trajectories in assessing speed variability and travel times across different lanes within the INCEPTION dataset. The virtual trajectory dataset opens future research on traffic waves and their impact on energy