Faculty Publications

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https://hdl.handle.net/1911/75173

This collection includes faculty journal articles deposited per Rice's Open Access Policy and additional faculty work. Items found in this collection can also be found in the authors' departmental faculty publication collections.

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The role of stress and fluid saturation on the acoustic response of fractured rock
(Frontiers Media S.A., 2023) Lisabeth, Harrison P.; Ajo-Franklin, Jonathan
Standard rock physics models are formulated to describe the behavior of porous sedimentary reservoirs, with clean sandstones being the archetypal system; however, many situations demand geophysical monitoring of rocks with significantly different structures, such as low porosity, fractured reservoirs. Conventional models also suggest that these “stiff” reservoirs can be challenging to monitor seismically due to small fluid substitution effects, but the presence of fractures leads to stress dependence which may be leveraged for remote monitoring purposes. Using samples from the Duperow Formation (dolostone) obtained from the Danielson test well in Kevin Dome, MT, we conducted ultrasonic and multi-scale structural (profilometry, synchrotron micro-tomography, pressure sensitive film) measurements on naturally fractured core in order to characterize the effects of fluid substitution and effective stress on the acoustic response of fractured reservoir rock with a focus in particular on the textural and seismic characteristics of natural fractures. We find that changes in effective stress can yield changes in velocity of up to 20% and changes in attenuation up to 200%. Measured fluid substitution effects are resolvable, but stress effects dominate. These measurements provide insight into the physical processes controlling acoustic response of fractured rocks in general and can also be used to inform monitoring efforts in fractured reservoirs.
A scientific machine learning framework to understand flash graphene synthesis
(Royal Society of Chemistry, 2023) Sattari, Kianoosh; Eddy, Lucas; Beckham, Jacob L.; Wyss, Kevin M.; Byfield, Richard; Qian, Long; Tour, James M.; Lin, Jian; NanoCarbon Center; Welch Institute for Advanced Materials
Flash Joule heating (FJH) is a far-from-equilibrium (FFE) processing method for converting low-value carbon-based materials to flash graphene (FG). Despite its promises in scalability and performance, attempts to explore the reaction mechanism have been limited due to the complexities involved in the FFE process. Data-driven machine learning (ML) models effectively account for the complexities, but the model training requires a considerable amount of experimental data. To tackle this challenge, we constructed a scientific ML (SML) framework trained by using both direct processing variables and indirect, physics-informed variables to predict the FG yield. The indirect variables include current-derived features (final current, maximum current, and charge density) predicted from the proxy ML models and reaction temperatures simulated from multi-physics modeling. With the combined indirect features, the final ML model achieves an average R2 score of 0.81 ± 0.05 and an average RMSE of 12.1% ± 2.0% in predicting the FG yield, which is significantly higher than the model trained without them (R2 of 0.73 ± 0.05 and an RMSE of 14.3% ± 2.0%). Feature importance analysis validates the key roles of these indirect features in determining the reaction outcome. These results illustrate the promise of this SML to elucidate FFE material synthesis outcomes, thus paving a new avenue to processing other datasets from the materials systems involving the same or different FFE processes.
Cell behaviors underlying Myxococcus xanthus aggregate dispersal
(American Society for Microbiology, 2023) Murphy, Patrick; Comstock, Jessica; Khan, Trosporsha; Zhang, Jiangguo; Welch, Roy; Igoshin, Oleg A.; Center for Theoretical Physical Biology
The soil bacterium Myxococcus xanthus is a model organism with a set of diverse behaviors. These behaviors include the starvation-induced multicellular development program, in which cells move collectively to assemble multicellular aggregates. After initial aggregates have formed, some will disperse, with smaller aggregates having a higher chance of dispersal. Initial aggregation is driven by two changes in cell behavior: cells slow down inside of aggregates and bias their motion by reversing direction less frequently when moving toward aggregates. However, the cell behaviors that drive dispersal are unknown. Here, we use fluorescent microscopy to quantify changes in cell behavior after initial aggregates have formed. We observe that after initial aggregate formation, cells adjust the bias in reversal timings by initiating reversals more rapidly when approaching unstable aggregates. Using agent-based modeling, we then show dispersal is predominantly generated by this change in bias, which is strong enough to overcome slowdown inside aggregates. Notably, the change in reversal bias is correlated with the nearest aggregate size, connecting cellular activity to previously observed correlations between aggregate size and fate. To determine if this connection is consistent across strains, we analyze a second M. xanthus strain with reduced levels of dispersal. We find that far fewer cells near smaller aggregates modified their bias. This implies that aggregate dispersal is under genetic control, providing a foundation for further investigations into the role it plays in the life cycle of M. xanthus.
Stable reconstruction of simple Riemannian manifolds from unknown interior sources
(IOP Publishing Ltd, 2023) Hoop, Maarten V. de; Ilmavirta, Joonas; Lassas, Matti; Saksala, Teemu
Consider the geometric inverse problem: there is a set of delta-sources in spacetime that emit waves travelling at unit speed. If we know all the arrival times at the boundary cylinder of the spacetime, can we reconstruct the space, a Riemannian manifold with boundary? With a finite set of sources we can only hope to get an approximate reconstruction, and we indeed provide a discrete metric approximation to the manifold with explicit data-driven error bounds when the manifold is simple. This is the geometrization of a seismological inverse problem where we measure the arrival times on the surface of waves from an unknown number of unknown interior microseismic events at unknown times. The closeness of two metric spaces with a marked boundary is measured by a labeled Gromov–Hausdorff distance. If measurements are done for infinite time and spatially dense sources, our construction produces the true Riemannian manifold and the finite-time approximations converge to it in the metric sense
Bridging physical intuition and hardware efficiency for correlated electronic states: the local unitary cluster Jastrow ansatz for electronic structure
(Royal Society of Chemistry, 2023) Motta, Mario; Sung, Kevin J.; Whaley, K. Birgitta; Head-Gordon, Martin; Shee, James
A prominent goal in quantum chemistry is to solve the molecular electronic structure problem for ground state energy with high accuracy. While classical quantum chemistry is a relatively mature field, the accurate and scalable prediction of strongly correlated states found, e.g., in bond breaking and polynuclear transition metal compounds remains an open problem. Within the context of a variational quantum eigensolver, we propose a new family of ansatzes which provides a more physically appropriate description of strongly correlated electrons than a unitary coupled cluster with single and double excitations (qUCCSD), with vastly reduced quantum resource requirements. Specifically, we present a set of local approximations to the unitary cluster Jastrow wavefunction motivated by Hubbard physics. As in the case of qUCCSD, exactly computing the energy scales factorially with system size on classical computers but polynomially on quantum devices. The local unitary cluster Jastrow ansatz removes the need for SWAP gates, can be tailored to arbitrary qubit topologies (e.g., square, hex, and heavy-hex), and is well-suited to take advantage of continuous sets of quantum gates recently realized on superconducting devices with tunable couplers. The proposed family of ansatzes demonstrates that hardware efficiency and physical transparency are not mutually exclusive; indeed, chemical and physical intuition regarding electron correlation can illuminate a useful path towards hardware-friendly quantum circuits.
Denoising Non-Stationary Signals via Dynamic Multivariate Complex Wavelet Thresholding
(MDPI, 2023) Raath, Kim C.; Ensor, Katherine B.; Crivello, Alena; Scott, David W.
Over the past few years, we have seen an increased need to analyze the dynamically changing behaviors of economic and financial time series. These needs have led to significant demand for methods that denoise non-stationary time series across time and for specific investment horizons (scales) and localized windows (blocks) of time. Wavelets have long been known to decompose non-stationary time series into their different components or scale pieces. Recent methods satisfying this demand first decompose the non-stationary time series using wavelet techniques and then apply a thresholding method to separate and capture the signal and noise components of the series. Traditionally, wavelet thresholding methods rely on the discrete wavelet transform (DWT), which is a static thresholding technique that may not capture the time series of the estimated variance in the additive noise process. We introduce a novel continuous wavelet transform (CWT) dynamically optimized multivariate thresholding method (WaveL2E). Applying this method, we are simultaneously able to separate and capture the signal and noise components while estimating the dynamic noise variance. Our method shows improved results when compared to well-known methods, especially for high-frequency signal-rich time series, typically observed in finance.
Thickness-Dependent Terahertz Permittivity of Epitaxially Grown PbTe Thin Films
(MDPI, 2023) Kawahala, Nicolas M.; Matos, Daniel A.; Rappl, Paulo H. O.; Abramof, Eduardo; Baydin, Andrey; Kono, Junichiro; Hernandez, Felix G. G.; Smalley-Curl Institute
The exceptional thermoelectric properties of PbTe are believed to be associated with the incipient ferroelectricity of this material, which is caused by strong electron–phonon coupling that connects phononic and electronic dynamics. Here, we have used terahertz time-domain spectroscopy measurements to generate complex permittivity spectra for a set of epitaxially grown PbTe thin films with thicknesses between 100 nm and 500 nm at temperatures from 10 K to 300 K. Using a Drude–Lorentz model, we retrieved the physical parameters of both the phononic and electronic contributions to the THz permittivity. We observed a strong decrease, or softening, of the transverse optical phonon mode frequency with decreasing temperature, determining a thickness-independent negative ferroelectric-transition critical temperature, while we found a thickness-dependent anharmonic phonon decay lifetime. The electronic contribution to the permittivity was larger in thinner films, and both the carrier density and mobility increased with decreasing temperature in all films. Finally, we detected a thickness-dependent longitudinal optical phonon mode frequency, indicating the presence of plasmon–phonon coupling.
Supervised convex clustering
(Wiley, 2023) Wang, Minjie; Yao, Tianyi; Allen, Genevera I.
Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming up with meaningful interpretations of the estimated clusters has often been challenging precisely due to their unsupervised nature. Meanwhile, in many real-world scenarios, there are some noisy supervising auxiliary variables, for instance, subjective diagnostic opinions, that are related to the observed heterogeneity of the unlabeled data. By leveraging information from both supervising auxiliary variables and unlabeled data, we seek to uncover more scientifically interpretable group structures that may be hidden by completely unsupervised analyses. In this work, we propose and develop a new statistical pattern discovery method named supervised convex clustering (SCC) that borrows strength from both information sources and guides towards finding more interpretable patterns via a joint convex fusion penalty. We develop several extensions of SCC to integrate different types of supervising auxiliary variables, to adjust for additional covariates, and to find biclusters. We demonstrate the practical advantages of SCC through simulations and a case study on Alzheimer's disease genomics. Specifically, we discover new candidate genes as well as new subtypes of Alzheimer's disease that can potentially lead to better understanding of the underlying genetic mechanisms responsible for the observed heterogeneity of cognitive decline in older adults.
Consecutive Shifts: A Repeated Measure Study to Evaluate Stress, Biomarkers, Social Support, and Fatigue in Medical/Surgical Nurses
(MDPI, 2023) Cockerham, Mona; Kang, Duck-Hee; Beier, Margaret E.
Nurses report that they are required to work during their scheduled breaks and generally experience extended work times and heavy workloads due to staffing shortages. This study aimed to examine changes in personal, work-related, and overall stress, as well as biological responses and fatigue experienced by nurses during three consecutive 12 h workdays (i.e., the typical “three-twelves” schedule). We also considered the moderating effects of social resources. This prospective study of 81 medical/surgical nurses who completed questionnaires and provided saliva samples at four designated intervals (i.e., pre-shift and post-shift on workdays 1 and 3). Fatigue reported by night shift nurses increased significantly over three consecutive workdays (p = 0.001). Day shift nurses said they encountered more social support than those on the night shift (p = 0.05). Social support moderated the relationship between work-related stress at baseline and reported fatigue on day 3.
Nanobomb optical coherence elastography in multilayered phantoms
(Optica Publishing Group, 2023) Hatami, Maryam; Nevozhay, Dmitry; Singh, Manmohan; Schill, Alexander; Boerner, Paul; Aglyamov, Salavat; Sokolov, Konstantin; Larin, Kirill V.
Many tissues are composed of layered structures, and a better understanding of the changes in the layered tissue biomechanics can enable advanced guidance and monitoring of therapy. The advent of elastography using longitudinally propagating shear waves (LSWs) has created the prospect of a high-resolution assessment of depth-dependent tissue elasticity. Laser activation of liquid-to-gas phase transition of dye-loaded perfluorocarbon (PFC) nanodroplets (a.k.a., nanobombs) can produce highly localized LSWs. This study aims to leverage the potential of photoactivation of nanobombs to incudce LSWs with very high-frequency content in wave-based optical coherence elastography (OCE) to estimate the elasticity gradient with high resolution. In this work, we used multilayered tissue-mimicking phantoms to demonstrate that highly localized nanobomb (NB)-induced LSWs can discriminate depth-wise tissue elasticity gradients. The results show that the NB-induced LSWs rapidly change speed when transitioning between layers with different mechanical properties, resulting in an elasticity resolution of ∼65 µm. These results show promise for characterizing the elasticity of multilayer tissue with a fine resolution.
Joint embedding of biological networks for cross-species functional alignment
(Oxford University Press, 2023) Li, Lechuan; Dannenfelser, Ruth; Zhu, Yu; Hejduk, Nathaniel; Segarra, Santiago; Yao, Vicky
Model organisms are widely used to better understand the molecular causes of human disease. While sequence similarity greatly aids this cross-species transfer, sequence similarity does not imply functional similarity, and thus, several current approaches incorporate protein–protein interactions to help map findings between species. Existing transfer methods either formulate the alignment problem as a matching problem which pits network features against known orthology, or more recently, as a joint embedding problem.We propose a novel state-of-the-art joint embedding solution: Embeddings to Network Alignment (ETNA). ETNA generates individual network embeddings based on network topological structure and then uses a Natural Language Processing-inspired cross-training approach to align the two embeddings using sequence-based orthologs. The final embedding preserves both within and between species gene functional relationships, and we demonstrate that it captures both pairwise and group functional relevance. In addition, ETNA’s embeddings can be used to transfer genetic interactions across species and identify phenotypic alignments, laying the groundwork for potential opportunities for drug repurposing and translational studies.https://github.com/ylaboratory/ETNA
Real-time, deep-learning aided lensless microscope
(Optica Publishing Group, 2023) Wu, Jimin; Boominathan, Vivek; Veeraraghavan, Ashok; Robinson, Jacob T.
Traditional miniaturized fluorescence microscopes are critical tools for modern biology. Invariably, they struggle to simultaneously image with a high spatial resolution and a large field of view (FOV). Lensless microscopes offer a solution to this limitation. However, real-time visualization of samples is not possible with lensless imaging, as image reconstruction can take minutes to complete. This poses a challenge for usability, as real-time visualization is a crucial feature that assists users in identifying and locating the imaging target. The issue is particularly pronounced in lensless microscopes that operate at close imaging distances. Imaging at close distances requires shift-varying deconvolution to account for the variation of the point spread function (PSF) across the FOV. Here, we present a lensless microscope that achieves real-time image reconstruction by eliminating the use of an iterative reconstruction algorithm. The neural network-based reconstruction method we show here, achieves more than 10000 times increase in reconstruction speed compared to iterative reconstruction. The increased reconstruction speed allows us to visualize the results of our lensless microscope at more than 25 frames per second (fps), while achieving better than 7 µm resolution over a FOV of 10 mm2. This ability to reconstruct and visualize samples in real-time empowers a more user-friendly interaction with lensless microscopes. The users are able to use these microscopes much like they currently do with conventional microscopes.
Minmers are a generalization of minimizers that enable unbiased local Jaccard estimation
(Oxford University Press, 2023) Kille, Bryce; Garrison, Erik; Treangen, Todd J; Phillippy, Adam M
The Jaccard similarity on k-mer sets has shown to be a convenient proxy for sequence identity. By avoiding expensive base-level alignments and comparing reduced sequence representations, tools such as MashMap can scale to massive numbers of pairwise comparisons while still providing useful similarity estimates. However, due to their reliance on minimizer winnowing, previous versions of MashMap were shown to be biased and inconsistent estimators of Jaccard similarity. This directly impacts downstream tools that rely on the accuracy of these estimates.To address this, we propose the minmer winnowing scheme, which generalizes the minimizer scheme by use of a rolling minhash with multiple sampled k-mers per window. We show both theoretically and empirically that minmers yield an unbiased estimator of local Jaccard similarity, and we implement this scheme in an updated version of MashMap. The minmer-based implementation is over 10 times faster than the minimizer-based version under the default ANI threshold, making it well-suited for large-scale comparative genomics applications.MashMap3 is available at https://github.com/marbl/MashMap.
Regulation of Syntaxin3B-Mediated Membrane Fusion by T14, Munc18, and Complexin
(MDPI, 2023) Nishad, Rajkishor; Betancourt-Solis, Miguel; Dey, Himani; Heidelberger, Ruth; McNew, James A.
Retinal neurons that form ribbon-style synapses operate over a wide dynamic range, continuously relaying visual information to their downstream targets. The remarkable signaling abilities of these neurons are supported by specialized presynaptic machinery, one component of which is syntaxin3B. Syntaxin3B is an essential t-SNARE protein of photoreceptors and bipolar cells that is required for neurotransmitter release. It has a light-regulated phosphorylation site in its N-terminal domain at T14 that has been proposed to modulate membrane fusion. However, a direct test of the latter has been lacking. Using a well-controlled in vitro fusion assay, we found that a phosphomimetic T14 syntaxin3B mutation leads to a small but significant enhancement of SNARE-mediated membrane fusion following the formation of the t-SNARE complex. While the addition of Munc18a had only a minimal effect on membrane fusion mediated by SNARE complexes containing wild-type syntaxin3B, a more significant enhancement was observed in the presence of Munc18a when the SNARE complexes contained a syntaxin3B T14 phosphomimetic mutant. Finally, we showed that the retinal-specific complexins (Cpx III and Cpx IV) inhibited membrane fusion mediated by syntaxin3B-containing SNARE complexes in a dose-dependent manner. Collectively, our results establish that membrane fusion mediated by syntaxin3B-containing SNARE complexes is regulated by the T14 residue of syntaxin3B, Munc18a, and Cpxs III and IV.
What Makes Weak Ties Strong?
(Annual Reviews, 2023) Kim, Minjae; Fernandez, Roberto M.
We raise two challenges concerning the validity of arguments underlying Granovetter's strength of weak ties (SWT) thesis: (a) whether weak ties are actually bridges, i.e., they help reach more socially distant actors than strong ties, and (b) whether weak ties transmit information effectively enough so that weak ties’ alleged structural properties make them more useful than strong ties. In the course of reviewing subsequent research that has made progress in addressing these challenges, we identify both potential limits and possibilities for the SWT thesis. We argue for the importance of identifying how actors’ agency—i.e., the way people use their ties—may affect social networks’ value. We conclude by summarizing some outstanding questions that progress on the SWT thesis has generated.
Detecting plumes in mobile air quality monitoring time series with density-based spatial clustering of applications with noise
(Copernicus Publications, 2023) Actkinson, Blake; Griffin, Robert J.
Mobile monitoring is becoming an increasingly popular technique to assess air pollution on fine spatial scales, but methods to determine specific source contributions to measured pollutants are sorely needed. One approach is to isolate plumes from mobile monitoring time series and analyze them separately, but methods that are suitable for large mobile monitoring time series are lacking. Here we discuss a novel method used to detect and isolate plumes from an extensive mobile monitoring data set. The new method relies on density-based spatial clustering of applications with noise (DBSCAN), an unsupervised machine learning technique. The new method systematically runs DBSCAN on mobile monitoring time series by day and identifies a subset of points as anomalies for further analysis. When applied to a mobile monitoring data set collected in Houston, Texas, analyzed anomalies reveal patterns associated with different types of vehicle emission profiles. We observe spatial differences in these patterns and reveal striking disparities by census tract. These results can be used to inform stakeholders of spatial variations in emission profiles not obvious using data from stationary monitors alone.
An unusual oxygen-deficient ichnofauna from the Vaca Muerta Formation: implications for the ichnofacies model
(Scandinavian University Press, 2023) Paz, Maximiliano; Mángano, M. Gabriela; Buatois, Luis A.; Desjardins, Patricio R.; Minisini, Daniel; Tomassini, Federico González; Rodríguez, Maximiliano N.; Pereira, Egberto; Parada, Martin N.
In most oxygen-deficient ancient successions, Chondrites and Zoophycos are typical and recurrent trace fossils that are the last to disappear during deoxygenation events. Here, we report an unusual case of an oxygen-deficient ichnofauna lacking Chondrites and showing scarce Zoophycos, from the Upper Jurassic-Lower Cretaceous Vaca Muerta Formation of Argentina. One outcrop and cores from nine wells were analysed. The succession comprises fine-grained, mixed carbonate-siliciclastic deposits accumulated in marginal-marine, basin, drift, slope, and outer ramp environments. It displays abundant biodeformational structures mostly producing irregular-laminated and massive fabrics in fine to medium mudstone. However, discrete trace fossils can be found within interbedded coarser-grained intervals, namely (in order of decreased ichnogenera abundance), Teichichnus, Alcyonidiopsis, Coprulus, Phycosiphon, Planolites, Lockeia, Thalassinoides, Palaeophycus, Nereites, Crininicaminus, Zoophycos, Diplocraterion, and ?Skolithos. Considering all ichnotaxa, the Vaca Muerta Formation may be seen as hosting a relatively diverse ichnofauna, yet, this is misleading because most occurrences are of low diversity. This atypical ichnofauna may be explained by either a lack of strong seasonality and existence of background food-rich environments, or by salinity variations, precluding the specialized feeding style of the Chondrites and Zoophycos producers. The dominance of feeding trace fossils with spreite (Teichichnus) and the low ichnodiversity suggest that the studied ichnofauna belongs to the Zoophycos Ichnofacies. Keywords Mudstone Chondrites cryptobioturbation Zoophycos Ichnofacies ichnology
A Magnetically Driven Disk Wind in the Inner Disk of PDS 70*
(IOP Publishing Ltd, 2023) Campbell-White, Justyn; Manara, Carlo F.; Benisty, Myriam; Natta, Antonella; Claes, Rik A. B.; Frasca, Antonio; Bae, Jaehan; Facchini, Stefano; Isella, Andrea; Pérez, Laura; Pinilla, Paola; Sicilia-Aguilar, Aurora; Teague, Richard
PDS 70 is so far the only young disk where multiple planets have been detected by direct imaging. The disk has a large cavity when seen at submillimeter and near-infrared wavelengths, which hosts two massive planets. This makes PDS 70 the ideal target to study the physical conditions in a strongly depleted inner disk shaped by two giant planets, and in particular to test whether disk winds can play a significant role in its evolution. Using X-Shooter and HARPS spectra, we detected for the first time the wind-tracing [O i] 6300 Å line, and confirm the low-moderate value of mass-accretion rate in the literature. The [O i] line luminosity is high with respect to the accretion luminosity when compared to a large sample of disks with cavities in nearby star-forming regions. The FWHM and blueshifted peak of the [O i] line suggest an emission in a region very close to the star, favoring a magnetically driven wind as the origin. We also detect wind emission and high variability in the He i 10830 Å line, which is unusual for low accretors. We discuss that, although the cavity of PDS 70 was clearly carved out by the giant planets, the substantial inner-disk wind could also have had a significant contribution to clearing the inner disk.
Fast-rotating Blue Straggler Stars in the Globular Cluster NGC 3201*
(IOP Publishing Ltd, 2023) Billi, Alex; Ferraro, Francesco R.; Mucciarelli, Alessio; Lanzoni, Barbara; Cadelano, Mario; Monaco, Lorenzo; Mateo, Mario; Bailey, John I.; Reiter, Megan; Olszewski, Edward W.
We used high-resolution spectra acquired with the Magellan Telescope to measure radial and rotational velocities of approximately 200 stars in the Galactic globular cluster NGC 3201. The surveyed sample includes blue straggler stars (BSSs) and reference stars in different evolutionary stages (main-sequence turnoff, subgiant, red giant, and asymptotic giant branches). The average radial velocity value (〈V r 〉 = 494.5 ± 0.5 km s−1) confirms a large systemic velocity for this cluster and was used to distinguish 33 residual field interlopers. The final sample of member stars has 67 BSSs and 114 reference stars. Similarly to what is found in other clusters, the totality of the reference stars has negligible rotation (< 20 km s−1), while the BSS rotational velocity distribution shows a long tail extending up to ∼200 km s−1, with 19 BSSs (out of 67) spinning faster than 40 km s−1. This sets the percentage of fast-rotating BSSs to ∼28%. Such a percentage is roughly comparable to that measured in other loose systems (ω Centauri, M4, and M55) and significantly larger than that measured in high-density clusters (as 47 Tucanae, NGC 6397, NGC 6752, and M30). This evidence supports a scenario where recent BSS formation (mainly from the evolution of binary systems) is occurring in low-density environments. We also find that the BSS rotational velocity tends to decrease for decreasing luminosity and surface temperature, similarly to what is observed in main-sequence stars. Hence, further investigations are needed to understand the impact of BSS internal structure on the observed rotational velocities.
Fear of missing out and depressive symptoms during the COVID-19 pandemic
(Wiley, 2023) LeRoy, Angie S.; Lai, Vincent D.; Tsay-Jones, Arya; Fagundes, Christopher P.
During the early stages of the COVID-19 pandemic, governments issued public health safety measures (e.g., “stay-at-home” ordinances), leaving many people “missing out” on integral social aspects of their own lives. The fear of missing out, popularly shortened as, “FoMO,” is a felt sense of unease one experiences when they perceive they may be missing out on rewarding and/or enjoyable experiences. Among 76 participants (ages M = 69.36, SD = 5.34), who were at risk for hospitalization or death if infected with COVID-19, we found that FoMO was associated with depressive symptoms at Time 1, even when controlling for perceived stress, loneliness, and fear of COVID-19. However, FoMO did not predict future depressive symptoms, about 1 week later, when controlling for Time 1 depressive symptoms. These findings provide further evidence that FoMO is associated with depressive symptoms in a short period of time even when accounting for other powerful social factors such as loneliness. Future research should explore the potential causal relationships between FoMO and depression, especially those that may establish temporal precedence.

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