News and Events

Thumbnail of A Solstice Moon
Rising opposite the setting Sun, June's Full Moon occurred within about 28 hours of the solstice. The Moon stays close to the Sun's path along the ecliptic plane and so while the solstice Sun climbed high in daytime skies, June's Full Moon remained low that night as seen from northern latitudes. In fact, the Full Moon hugs the horizon in this June 21 rooftop night sky view from Bursa, Turkey, constructed from exposures made every 10 minutes between moonrise and moonset. In 2024 the Moon also reached a major lunar standstill, an extreme in the monthly north-south range of moonrise and moonset caused by the precession of the Moon's orbit over an 18.6 year cycle. As a result, this June solstice Full Moon was at its southernmost moonrise and moonset along the horizon.
Mount Timpanogos with sky above
Check current conditions and historical weather data at the ESC.
Image for Nanoparticle Drug Delivery Using Magnetism
Dr. Karine Chesnel awarded Interdisciplinary Research Origination Grant
Image for Sommerfeldts Called as Mission Leaders
Professor Scott and Lisa Sommerfeldt in Missouri Independence Mission
Image for Adam Fennimore's Insights for Students
Alumni Adam Fennimore shares career insights for current students

Selected Publications

Thumbnail of figure from publication
By Tracianne B. Neilsen, Bethany Wu, and Corey E. Dobbs (et al.)
Abstract:

Applications of supervised machine learning to ocean acoustics is often limited by the lack of labeled measured data. To overcome this, synthetic data can be used for training. This paper explores the potential for unsupervised learning to provide labels for measured data. Specifically, a comparison is made between seabed classification from supervised learning and labels inferred from unsupervised learning. Both networks are trained on synthetic ship noise spectrograms. Six CNN-based supervised learning methods were trained using synthetic data labeled by seabed class. The trained networks were applied to 69 measured spectrograms from the Seabed Characterization Experiment 2017. The results show a distinct preference for seabeds with softer top layer (water-sediment sound speed ratios less than one). The unsupervised ML method, k-means clustering, is applied to same synthetic dataset, and the resulting clusters are evaluated based on the characteristics of the synthetic data samples placed into each cluster. The measured ship noise spectrograms are then passed through the trained clustering model, and the characteristics of the assigned clusters are evaluated. Of the 69 measured data samples, 70% are placed in clusters showing a distinct preference for seabed classes similar to those obtained from the CNN-based classifiers. Other measured data samples are placed in clusters that contain synthetic data samples from short ranges. This work illustrates the potential for using clustering to assign preliminary labels to unlabeled data.

Thumbnail of figure from publication
By Katrina Pedersen, Mark K. Transtrum, and Kent L. Gee (et al.)
Abstract:

Modeling environmental sound levels over continental scales is difficult due to the variety of geospatial environments. Moreover, current continental-scale models depend upon machine learning and therefore face additional challenges due to limited acoustic training data. In previous work, an ensemble of machine learning models was used to predict environmental sound levels in the contiguous United States using a training set composed of 51 geospatial layers (downselected from 120) and acoustic data from 496 geographic sites from Pedersen, Transtrum, Gee, Lympany, James, and Salton [JASA Express Lett. 1(12), 122401 (2021)]. In this paper, the downselection process, which is based on factors such as data quality and inter-feature correlations, is described in further detail. To investigate additional dimensionality reduction, four different feature selection methods are applied to the 51 layers. Leave-one-out median absolute deviation cross-validation errors suggest that the number of geospatial features can be reduced to 15 without significant degradation of the model's predictive error. However, ensemble predictions demonstrate that feature selection results are sensitive to variations in details of the problem formulation and, therefore, should elicit some skepticism. These results suggest that more sophisticated dimensionality reduction techniques are necessary for problems with limited training data and different training and testing distributions.

Thumbnail of figure from publication
By Aleksandr V Mosenkov and William Roque (et al.)
Abstract:

We use a 0.7-m telescope in the framework of the Halos and Environments of Nearby Galaxies (HERON) survey to probe low surface brightness (LSB) structures in nearby galaxies. One of our targets, UGC 4599, is usually classified as an early-type galaxy surrounded by a blue ring making it a potential Hoag’s Object analogue. Prior photometric studies of UGC 4599 were focused on its bright core and the blue ring. However, the HERON survey allows us to study its faint extended regions. With an 8-h integration, we detect an extremely faint outer disc with an extrapolated central surface brightness of μ0, d(r) = 25.5 mag arcsec−2 down to 31 mag arcsec−2 and a scale length of 15 kpc. We identify two distinct spiral arms of pitch angle ∼6○ surrounding the ring. The spiral arms are detected out to ∼45 kpc in radius and the faint disc continues to ∼70 kpc. These features are also seen in the GALEX far- and near-ultraviolet bands, in a deep u-band image from the 4.3-m Lowell Discovery Telescope (which reveals inner spiral structure emerging from the core), and in H I. We compare this galaxy to ordinary spiral and elliptical galaxies, giant low surface brightness (GLSB) galaxies, and Hoag’s Object itself using several standard galaxy scaling relations. We conclude that the pseudo-bulge and disc properties of UGC 4599 significantly differ from those of Hoag’s Object and of normal galaxies, pointing toward a GLSB galaxy nature and filamentary accretion of gas to generate its outer disc.

Thumbnail of figure from publication
By R. Steven Turley (et al.)
Abstract:

One of the primary reasons why students leave STEM majors is due to the poor quality of instruction. Teaching practices can be improved through professional development programs; however, several barriers exist. Creating lasting change by overcoming these barriers is the primary objective of the STEM Faculty Institute (STEMFI). STEMFI was designed according to the framework established by Ajzen’s Theory of Planned Behavior. To evaluate its effectiveness, the Classroom Observation Protocol for Undergraduate STEM (COPUS) tool was used before and after an intensive year-long faculty development program and analyzed using copusprofiles.org, a tool that classifies each COPUS report into one of three instructional styles: didactic, interactive lecture, and student-centered. We report the success of our program in changing faculty teaching behaviors and we categorize them into types of reformers. Then, thematically coded post-participation interviews give us clues into the characteristics of each type of reformer. Our results demonstrate that faculty can significantly improve the student-centeredness of their teaching practices in a relatively short time. We also discuss the implications of faculty attitudes for future professional development efforts.

Thumbnail of figure from publication
By Adam D. Kingsley, Andrew Basham, and Brian E. Anderson
Abstract:

Time reversal focusing above an array of resonators creates subwavelength–sized features when compared to wavelengths in free space. Previous work has shown the ability to focus acoustic waves near the resonators with and without time reversal with an array placed coplanar with acoustic sources, principally using direct sound emissions. In this work, a two-dimensional array of resonators is studied with a full three-dimensional aperture of waves in a reverberation chamber and including significant reverberation within the time reversed emissions. The full impulse response is recorded, and the spatial inverse filter is used to produce a focus among the resonators. Additionally, images of complex sources are produced by extending the spatial inverse filter to create focal images, such as dipoles and quadrupoles. Although waves at oblique angles would be expected to degrade the focal quality, it is shown that complex focal images can still be achieved with super resolution fidelity when compared to free space wavelengths.

Thumbnail of figure from publication
Abstract:

Organic–inorganic metal hybrids with their tailorable lattice dimensionality and intrinsic spin-splitting properties are interesting material platforms for spintronic applications. While the spin decoherence process is extensively studied in lead- and tin-based hybrids, these systems generally show short spin decoherence lifetimes, and their correlation with the lattice framework is still not well-understood. Herein, we synthesized magnetic manganese hybrid single crystals of (4-fluorobenzylamine)2MnCl4, ((R)-3-fluoropyrrolidinium)MnCl3, and (pyrrolidinium)2MnCl4, which represent a change in lattice dimensionality from 2D and 1D to 0D, and studied their spin decoherence processes using continuous-wave electron spin resonance spectroscopy. All manganese hybrids exhibit nanosecond-scale spin decoherence time τ2 dominated by the symmetry-directed spin exchange interaction strengths of Mn2+–Mn2+ pairs, which is much longer than lead- and tin-based metal hybrids. In contrast to the similar temperature variation laws of τ2 in 2D and 0D structures, which first increase and gradually drop afterward, the 1D structure presents a monotonous rise of τ2 with the temperatures, indicating the strong correlation of spin decoherence with the lattice rigidity of the inorganic framework. This is also rationalized on the basis that the spin decoherence is governed by the competitive contributions from motional narrowing (prolonging the τ2) and electron–phonon coupling interaction (shortening the τ2), both of which are thermally activated, with the difference that the former is more pronounced in rigid crystalline lattices.