Rice University Research Repository
The Rice Research Repository (R-3) provides access to research produced at Rice University, including theses and dissertations, journal articles, research center publications, datasets, and academic journals. Managed by Fondren Library, R-3 is indexed by Google and Google Scholar, follows best practices for preservation, and provides DOIs to facilitate citation. Woodson Research Center collections, including Rice Images and Documents and the Task Force on Slavery, Segregation, and Racial Injustice, have moved here.
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Deep Learning-Based Subsurface Damage Localization Using Full-Field Surface Strains
(MDPI, 2023) Pal, Ashish; Meng, Wei; Nagarajaiah, Satish
Structures in their service life are often damaged as a result of aging or extreme events such as earthquakes or storms. It is essential to detect damage in a timely fashion to ensure the safe operation of the structure. If left unchecked, subsurface damage (SSD) can cause significant internal damage and may result in premature structural failure. In this study, a Convolutional Neural Network (CNN) has been developed for SSD detection using surface strain measurements. The adopted network architecture is capable of pixel-level image segmentation, that is, it classifies each location of strain measurement as damaged or undamaged. The CNN which is fed full-field strain measurements as an input image of size 256 × 256 projects the SSD onto an output image of the same size. The data for network training is generated by numerical simulation of aluminum bars with different damage scenarios, including single damage and double damage cases at a random location, direction, length, and thickness. The trained network achieves an Intersection over Union (IoU) score of 0.790 for the validation set and 0.794 for the testing set. To check the applicability of the trained network on materials other than aluminum, testing is performed on a numerically generated steel dataset. The IoU score is 0.793, the same as the aluminum dataset, affirming the network’s capability to apply to materials exhibiting a similar stress–strain relationship. To check the generalization potential of the network, it is tested on triple damage cases; the IoU score is found to be 0.764, suggesting that the network works well for unseen damage patterns as well. The network was also found to provide accurate predictions for real experimental data obtained from Strain Sensing Smart Skin (S4). This proves the efficacy of the network to work in real-life scenarios utilizing the full potential of the novel full-field strain sensing methods such as S4. The performance of the proposed network affirms that it can be used as a non-destructive testing method for subsurface crack detection and localization.
The VLT MUSE NFM view of outflows and externally photoevaporating discs near the orion bar★
(Oxford University Press, 2023) Haworth, Thomas J; Reiter, Megan; O’Dell, C Robert; Zeidler, Peter; Berne, Olivier; Manara, Carlo F; Ballabio, Giulia; Kim, Jinyoung S; Bally, John; Goicoechea, Javier R; Aru, Mari-Liis; Gupta, Aashish; Miotello, Anna
We present Very Large Telescope/Multi-Unit Spectroscopic Explorer Narrow Field Mode observations of a pair of disc-bearing young stellar objects towards the Orion Bar: 203–504 and 203–506. Both of these discs are subject to external photoevaporation, where winds are launched from their outer regions due to environmental irradiation. Intriguingly, despite having projected separation from one another of only 1.65 arcsec(660 au at 400 pc), 203–504 has a classic teardrop shaped ‘proplyd’ morphology pointing towards θ2 Ori A (indicating irradiation by the EUV of that star, rather than $\rm \theta ^1$ Ori C) but 203–506 has no ionization front, indicating it is not irradiated by stellar EUV at all. However, 203–506 does show [C i] 8727 Å and [O i] 6300 Å in emission, indicating irradiation by stellar FUV. This explicitly demonstrates the importance of FUV irradiation in driving mass loss from discs. We conclude that shielding of 203–506 from EUV is most likely due to its position on the observers side of an ionized layer lying in the foreground of the Huygens Region. We demonstrate that the outflow HH 519, previously thought to be emanating from 203–504 is actually an irradiated cloud edge and identify a new compact outflow from that object approximately along our line of sight with a velocity ∼130 km s−1.
Full-Field Vibration Response Estimation from Sparse Multi-Agent Automatic Mobile Sensors Using Formation Control Algorithm
(MDPI, 2023) Jana, Debasish; Nagarajaiah, Satish
In structural vibration response sensing, mobile sensors offer outstanding benefits as they are not dedicated to a certain structure; they also possess the ability to acquire dense spatial information. Currently, most of the existing literature concerning mobile sensing involves human drivers manually driving through the bridges multiple times. While self-driving automated vehicles could serve for such studies, they might entail substantial costs when applied to structural health monitoring tasks. Therefore, in order to tackle this challenge, we introduce a formation control framework that facilitates automatic multi-agent mobile sensing. Notably, our findings demonstrate that the proposed formation control algorithm can effectively control the behavior of the multi-agent systems for structural response sensing purposes based on user choice. We leverage vibration data collected by these mobile sensors to estimate the full-field vibration response of the structure, utilizing a compressive sensing algorithm in the spatial domain. The task of estimating the full-field response can be represented as a spatiotemporal response matrix completion task, wherein the suite of multi-agent mobile sensors sparsely populates some of the matrix’s elements. Subsequently, we deploy the compressive sensing technique to obtain the dense full-field vibration complete response of the structure and estimate the reconstruction accuracy. Results obtained from two different formations on a simply supported bridge are presented in this paper, and the high level of accuracy in reconstruction underscores the efficacy of our proposed framework. This multi-agent mobile sensing approach showcases the significant potential for automated structural response measurement, directly applicable to health monitoring and resilience assessment objectives.
A Recombinant Protein XBB.1.5 RBD/Alum/CpG Vaccine Elicits High Neutralizing Antibody Titers against Omicron Subvariants of SARS-CoV-2
(MDPI, 2023) Thimmiraju, Syamala Rani; Adhikari, Rakesh; Villar, Maria Jose; Lee, Jungsoon; Liu, Zhuyun; Kundu, Rakhi; Chen, Yi-Lin; Sharma, Suman; Ghei, Karm; Keegan, Brian; Versteeg, Leroy; Gillespie, Portia M.; Ciciriello, Allan; Islam, Nelufa Y.; Poveda, Cristina; Uzcategui, Nestor; Chen, Wen-Hsiang; Kimata, Jason T.; Zhan, Bin; Strych, Ulrich; Bottazzi, Maria Elena; Hotez, Peter J.; Pollet, Jeroen
(1) Background: We previously reported the development of a recombinant protein SARS-CoV-2 vaccine, consisting of the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein, adjuvanted with aluminum hydroxide (alum) and CpG oligonucleotides. In mice and non-human primates, our wild-type (WT) RBD vaccine induced high neutralizing antibody titers against the WT isolate of the virus, and, with partners in India and Indonesia, it was later developed into two closely resembling human vaccines, Corbevax and Indovac. Here, we describe the development and characterization of a next-generation vaccine adapted to the recently emerging XBB variants of SARS-CoV-2. (2) Methods: We conducted preclinical studies in mice using a novel yeast-produced SARS-CoV-2 XBB.1.5 RBD subunit vaccine candidate formulated with alum and CpG. We examined the neutralization profile of sera obtained from mice vaccinated twice intramuscularly at a 21-day interval with the XBB.1.5-based RBD vaccine, against WT, Beta, Delta, BA.4, BQ.1.1, BA.2.75.2, XBB.1.16, XBB.1.5, and EG.5.1 SARS-CoV-2 pseudoviruses. (3) Results: The XBB.1.5 RBD/CpG/alum vaccine elicited a robust antibody response in mice. Furthermore, the serum from vaccinated mice demonstrated potent neutralization against the XBB.1.5 pseudovirus as well as several other Omicron pseudoviruses. However, regardless of the high antibody cross-reactivity with ELISA, the anti-XBB.1.5 RBD antigen serum showed low neutralizing titers against the WT and Delta virus variants. (4) Conclusions: Whereas we observed modest cross-neutralization against Omicron subvariants with the sera from mice vaccinated with the WT RBD/CpG/Alum vaccine or with the BA.4/5-based vaccine, the sera raised against the XBB.1.5 RBD showed robust cross-neutralization. These findings underscore the imminent opportunity for an updated vaccine formulation utilizing the XBB.1.5 RBD antigen.
Women in Legislative Studies: Improving Gender Equality
(Cambridge University Press, 2023) Powell, Eleanor Neff; Schwindt-Bayer, Leslie; Sin, Gisela
Representation of women in the field of legislative politics is remarkably small and the absence of women has wide-ranging ramifications. In Fall 2019, we surveyed 361 women that we identified as studying legislative politics within political science to understand why women’s representation in legislative studies is so low and what we can do about it. We found that many women study legislatures, but they do not always identify as scholars of legislative studies, often do not join the Legislative Studies Section, and tend to prioritize other journals over Legislative Studies Quarterly, the official journal of the section. In this article, we discuss several solutions to the problem of women’s underrepresentation in legislative studies, including the new Women in Legislative Studies initiative.