Physical Sciences and Mathematics Commons^™

Extension Of The Local Vibrational Mode Theory To Periodic Systems, Filippo Bodo

Chemistry Theses and Dissertations

Over the years, vibrational spectroscopy was used to gain a deeper understanding of the electronic structure and the chemical bond in both molecular and periodic systems. In this framework, the Local Vibrational Mode Theory (LVMT), as first introduced by Konkoli and Cremer in 1998, provides a unique tool to quantify the strength of a chemical bond, and better interpret the molecular vibrational spectra, thanks to the adiabatic force constants ($k^a$) and the composition of normal modes (CNM). While LVMT was originally developed for molecular systems, its application to periodic solids has remained limited. This thesis presents a complete and systematic …

New Avenues For |Δb=2| Processes Beyond Neutron-Antineutron Oscillations, Arnau Basi Beneito, Svjetlana Fajfer, Alexey A. Petrov

Faculty Publications

We explore baryon-number-violating (|∆B| = 2) processes beyond the well-known neutron-antineutron (n-n̄) oscillations, focusing on the Λ-Λ̄ system. The presence of a strange quark in the Λ baryon introduces a new set of six-quark operators roughly of the form (uds)², which are different from the (udd)² operators responsible for n-n̄ oscillations. Using the Standard Model Effective Field Theory (SMEFT), we classify all dimension-9 operators that cause |∆B| = 2  transitions and study their UV completions mediated by exotic scalar fields with trilinear interactions. We demonstrate that …

Associational Inference With Many Potential Covariates: Bayesian Information Criterion Elastic Net, Farideh Bagherzadeh Khiabani, I-Chan Huang, Jose Miguel Martinez Martinez, Shizue Izumi, Sedigheh Mirzaei, Tiange Zheng, Irina Dinu, Yutaka Yasui

COBRA Preprint Series

Background: An emerging feature in modern biomedical research is collecting and analyzing numerous variables. In the presence of many potential covariates, inference becomes challenging requiring both distinguishing a set of covariates truly associated with an outcome and estimating their corresponding regression coefficients consistently. Traditional statistical inference typically focuses on estimating coefficients assuming a pre-specified set of covariates. Further, advanced machine/statistical learning methods performing both selection and estimation predominantly focus on outcome prediction rather than association inference.

Methods: Motivated by our epidemiological research on long-term childhood cancer survivors, where we aimed to investigate associations between a large pool of longitudinal symptom …

Mgrre_Thinsections_Mgrre-138_36, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-138_45, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_12, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_53, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_57, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_66, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_88, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_89, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-139_58, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_16, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_68, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_73, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-137_11, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-137_25, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-137_64, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-137_68, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-137_89, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-138_2, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-138_13, Mgrre

Thin Sections

No abstract provided.

Data Centers In Mountain West Markets, 2026, Cason Noll, Krish Sharma, Maisoon Faris, Olivia K. Cheche, Caitlin J. Saladino, William E. Brown Jr.

Transportation & Infrastructure

This fact sheet reports on the distribution and geographic concentration of data centers across the Mountain West states of Arizona, Colorado, Nevada, New Mexico and Utah as of March 6th, 2026. Using data from DataCenterMap, this fact sheet examines the number of data centers in each Mountain West state and further analyzes market-level  distribution, defined as cities within each state where data centers are located. The data are used to compare state totals and to rank Mountain West markets from highest to lowest based on the number of data centers operating in that area.

Mgrre_Thinsections_Mgrre-136_13, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_43, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_46, Mgrre

Thin Sections

No abstract provided.

Geo 170 - Earth Science And Society, Yuri Gorohkovich

Open Educational Resources

Syllabus for our new OER course

Mgrre_Thinsections_Mgrre-136_62, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_64, Mgrre

Thin Sections

No abstract provided.

Mgrre_Thinsections_Mgrre-136_78, Mgrre

Thin Sections

No abstract provided.