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13,897 results on '"Warren, D"'

1. Brain age identification from diffusion MRI synergistically predicts neurodegenerative disease

Author

Gao, Chenyu, Kim, Michael E., Ramadass, Karthik, Kanakaraj, Praitayini, Krishnan, Aravind R., Saunders, Adam M., Newlin, Nancy R., Lee, Ho Hin, Yang, Qi, Taylor, Warren D., Boyd, Brian D., Beason-Held, Lori L., Resnick, Susan M., Barnes, Lisa L., Bennett, David A., Van Schaik, Katherine D., Archer, Derek B., Hohman, Timothy J., Jefferson, Angela L., Išgum, Ivana, Moyer, Daniel, Huo, Yuankai, Schilling, Kurt G., Zuo, Lianrui, Bao, Shunxing, Khairi, Nazirah Mohd, Li, Zhiyuan, Davatzikos, Christos, and Landman, Bennett A.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting early detection and implementation of prevention strategies. Diffusion MRI (dMRI) presents an opportunity to build an earlier biomarker for neurodegenerative disease prediction because it captures subtle microstructural changes that precede more perceptible macrostructural changes. However, the coexistence of macro- and micro-structural information in dMRI raises the question of whether current dMRI-based brain age estimation models are leveraging the intended microstructural information or if they inadvertently rely on the macrostructural information. To develop a microstructure-specific brain age, we propose a method for brain age identification from dMRI that mitigates the model's use of macrostructural information by non-rigidly registering all images to a standard template. Imaging data from 13,398 participants across 12 datasets were used for the training and evaluation. We compare our brain age models, trained with and without macrostructural information mitigated, with an architecturally similar T1-weighted (T1w) MRI-based brain age model and two recent, popular, openly available T1w MRI-based brain age models that primarily use macrostructural information. We observe difference between our dMRI-based brain age and T1w MRI-based brain age across stages of neurodegeneration, with dMRI-based brain age being older than T1w MRI-based brain age in participants transitioning from cognitively normal (CN) to mild cognitive impairment (MCI), but younger in participants already diagnosed with Alzheimer's disease (AD). Furthermore, dMRI-based brain age may offer advantages over T1w MRI-based brain age in predicting the transition from CN to MCI up to five years before diagnosis.

Published
2024

2. Strings and membranes from $\mathcal{A}$-theory five brane

Author

Hatsuda, Machiko, Hulík, Ondřej, Linch, William D., Siegel, Warren D., Wang, Di, and Wang, Yu-Ping

Subjects
High Energy Physics - Theory
Abstract

The $\mathcal{A}$-theory takes U-duality symmetry as a guiding principle, with the SL(5) U-duality symmetry being described as the world-volume theory of a 5-brane. Furthermore, by unifying the 6-dimensional world-volume Lorentz symmetry with the SL(5) spacetime symmetry, it extends to SL(6) U-duality symmetry. The SL(5) spacetime vielbein fields and the 5-brane world-volume vielbein fields are mixed under the SL(6) U-duality transformation. We demonstrate that consistent sectionings of the SL(6) $\mathcal{A}$5-brane world-volume Lagrangian yield Lagrangians of the ${\cal T}$-string with O(D,D) T-duality symmetry, the conventional string, the $\mathcal{M}$5-brane with GL(4) duality symmetry, and the non-perturbative M2-brane in supergravity theory. The GL(4) covariant Lagrangian of the $\mathcal{M}$5-brane derived in this manner is a new, perturbatively quantizable theory., Comment: 43 pages, revised introduction

Published
2024

3. Advancing Machine Learning in Industry 4.0: Benchmark Framework for Rare-event Prediction in Chemical Processes

Author

Sudarshan, Vikram and Seider, Warren D.

Subjects
Computer Science - Machine Learning, Computer Science - Computational Engineering, Finance, and Science, Electrical Engineering and Systems Science - Systems and Control
Abstract

Previously, using forward-flux sampling (FFS) and machine learning (ML), we developed multivariate alarm systems to counter rare un-postulated abnormal events. Our alarm systems utilized ML-based predictive models to quantify committer probabilities as functions of key process variables (e.g., temperature, concentrations, and the like), with these data obtained in FFS simulations. Herein, we introduce a novel and comprehensive benchmark framework for rare-event prediction, comparing ML algorithms of varying complexity, including Linear Support-Vector Regressor and k-Nearest Neighbors, to more sophisticated algorithms, such as Random Forests, XGBoost, LightGBM, CatBoost, Dense Neural Networks, and TabNet. This evaluation uses comprehensive performance metrics, such as: $\textit{RMSE}$, model training, testing, hyperparameter tuning and deployment times, and number and efficiency of alarms. These balance model accuracy, computational efficiency, and alarm-system efficiency, identifying optimal ML strategies for predicting abnormal rare events, enabling operators to obtain safer and more reliable plant operations., Comment: This is a preprint for our manuscript to be submitted for publication in Computers and Chemical Engineering Journal. Pages: 22 (including Appendix and References). Figures: 9 (main) + 3 (Appendix). Tables: 3 (main) + 3 (Appendix)

Published
2024

5. Intravenous and intracranial GD2-CAR T cells for H3K27M+ diffuse midline gliomas

Author

Monje, Michelle, Mahdi, Jasia, Majzner, Robbie, Yeom, Kristen W., Schultz, Liora M., Richards, Rebecca M., Barsan, Valentin, Song, Kun-Wei, Kamens, Jen, Baggott, Christina, Kunicki, Michael, Rietberg, Skyler P., Lim, Alexandria Sung, Reschke, Agnes, Mavroukakis, Sharon, Egeler, Emily, Moon, Jennifer, Patel, Shabnum, Chinnasamy, Harshini, Erickson, Courtney, Jacobs, Ashley, Duh, Allison K., Tunuguntla, Ramya, Klysz, Dorota Danuta, Fowler, Carley, Green, Sean, Beebe, Barbara, Carr, Casey, Fujimoto, Michelle, Brown, Annie Kathleen, Petersen, Ann-Louise G., McIntyre, Catherine, Siddiqui, Aman, Lepori-Bui, Nadia, Villar, Katlin, Pham, Kymhuynh, Bove, Rachel, Musa, Eric, Reynolds, Warren D., Kuo, Adam, Prabhu, Snehit, Rasmussen, Lindsey, Cornell, Timothy T., Partap, Sonia, Fisher, Paul G., Campen, Cynthia J., Grant, Gerald, Prolo, Laura, Ye, Xiaobu, Sahaf, Bita, Davis, Kara L., Feldman, Steven A., Ramakrishna, Sneha, and Mackall, Crystal

Published
2025
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6. Isotropy of cosmic rays beyond $10^{20}$ eV favors their heavy mass composition

Author

Telescope Array Collaboration, Abbasi, R. U., Abe, Y., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Belz, J. W., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibi, R., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Mizuno, K., Murakami, M., Myers, I., Nagataki, S., Nakai, K., Nakamura, T., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Onishi, M., Ohoka, H., Okazaki, N., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Pshirkov, M. S., Remington, J., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Saito, R., Sakaki, N., Sako, T., Sakurai, N., Sato, D., Sato, K., Sato, S., Sekino, K., Shah, P. D., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Urban, F., Warren, D., Wong, T., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., and Zundel, Z.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We report an estimation of the injected mass composition of ultra-high energy cosmic rays (UHECRs) at energies higher than 10 EeV. The composition is inferred from an energy-dependent sky distribution of UHECR events observed by the Telescope Array surface detector by comparing it to the Large Scale Structure of the local Universe. In the case of negligible extra-galactic magnetic fields the results are consistent with a relatively heavy injected composition at E ~ 10 EeV that becomes lighter up to E ~ 100 EeV, while the composition at E > 100 EeV is very heavy. The latter is true even in the presence of highest experimentally allowed extra-galactic magnetic fields, while the composition at lower energies can be light if a strong EGMF is present. The effect of the uncertainty in the galactic magnetic field on these results is subdominant., Comment: 8 pages, 3 figures, accepted for publication in PRL

Published
2024

7. Mass composition of ultra-high energy cosmic rays from distribution of their arrival directions with the Telescope Array

Author

Telescope Array Collaboration, Abbasi, R. U., Abe, Y., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Belz, J. W., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibi, R., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Mizuno, K., Murakami, M., Myers, I., Nagataki, S., Nakai, K., Nakamura, T., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Onishi, M., Ohoka, H., Okazaki, N., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Pshirkov, M. S., Remington, J., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Saito, R., Sakaki, N., Sako, T., Sakurai, N., Sato, D., Sato, K., Sato, S., Sekino, K., Shah, P. D., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Urban, F., Warren, D., Wong, T., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., and Zundel, Z.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We use a new method to estimate the injected mass composition of ultrahigh cosmic rays (UHECRs) at energies higher than 10 EeV. The method is based on comparison of the energy-dependent distribution of cosmic ray arrival directions as measured by the Telescope Array experiment (TA) with that calculated in a given putative model of UHECR under the assumption that sources trace the large-scale structure (LSS) of the Universe. As we report in the companion letter, the TA data show large deflections with respect to the LSS which can be explained, assuming small extra-galactic magnetic fields (EGMF), by an intermediate composition changing to a heavy one (iron) in the highest energy bin. Here we show that these results are robust to uncertainties in UHECR injection spectra, the energy scale of the experiment and galactic magnetic fields (GMF). The assumption of weak EGMF, however, strongly affects this interpretation at all but the highest energies E > 100 EeV, where the remarkable isotropy of the data implies a heavy injected composition even in the case of strong EGMF. This result also holds if UHECR sources are as rare as $2 \times 10^{-5}$ Mpc$^{-3}$, that is the conservative lower limit for the source number density., Comment: 18 pages, 11 figures, accepted for publication in PRD

Published
2024

8. Observation of Declination Dependence in the Cosmic Ray Energy Spectrum

Author

The Telescope Array Collaboration, Abbasi, R. U., Abu-Zayyad, T., Allen, M., Belz, J. W., Bergman, D. R., Buckland, I., Campbell, W., Cheon, B. G., Endo, K., Fedynitch, A., Fujii, T., Fujisue, K., Fujita, K., Fukushima, M., Furlich, G., Gerber, Z., Globus, N., Hanlon, W., Hayashida, N., He, H., Hibino, K., Higuchi, R., Ikeda, D., Ishii, T., Ivanov, D., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kawachi, Y., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kobo, R., Komae, I., Komatsu, K., Komori, K., Koyama, C., Kudenko, M., Kuroiwa, M., Kusumori, Y., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lee, M. J., Lubsandorzhiev, B., Lundquist, J. P., Matsuzawa, A., Matthews, J. A., Matthews, J. N., Mizuno, K., Mori, M., Murakami, M., Nagataki, S., Nakahara, M., Nakamura, T., Nakayama, T., Nakayama, Y., Nonaka, T., Ogio, S., Ohoka, H., Okazaki, N., Onishi, M., Oshima, A., Oshima, H., Ozawa, S., Park, I. H., Park, K. Y., Potts, M., Przybylak, M., Pshirkov, M. S., Remington, J., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Sakaki, N., Sakamoto, R., Sako, T., Sakurai, N., Sakurai, S., Sato, D., Sato, S., Sekino, K., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinozaki, K., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takagi, Y., Takahashi, K., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tomida, T., Troitsky, S., Tsunesada, Y., Udo, S., Urban, F., Vaiman, I. A., Vrábel, M., Warren, D., Yamazaki, K., Zhezher, Y., Zundel, Z., and Zvirzdin, J.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

We report on an observation of the difference between northern and southern skies of the ultrahigh energy cosmic ray energy spectrum with a significance of ${\sim}8\sigma$. We use measurements from the two largest experiments$\unicode{x2014}$the Telescope Array observing the northern hemisphere and the Pierre Auger Observatory viewing the southern hemisphere. Since the comparison of two measurements from different observatories introduces the issue of possible systematic differences between detectors and analyses, we validate the methodology of the comparison by examining the region of the sky where the apertures of the two observatories overlap. Although the spectra differ in this region, we find that there is only a $1.8\sigma$ difference between the spectrum measurements when anisotropic regions are removed and a fiducial cut in the aperture is applied., Comment: 8 pages, 6 figures

Published
2024

11. Better-than-average uniform random variables and Eulerian numbers, or: How many candidates should a voter approve?

Author

Janson, Svante and Smith, Warren D.

Subjects
Mathematics - Probability, Mathematics - Combinatorics, 60C05, 05A15, 91B12
Abstract

Consider $n$ independent random numbers with a uniform distribution on $[0,1]$. The number of them that exceed their mean is shown to have an Eulerian distribution, i.e., it is described by the Eulerian numbers. This is related to, but distinct from, the well known fact that the integer part of the sum of independent random numbers uniform on $[0,1]$ has an Eulerian distribution. One motivation for this problem comes from voting theory., Comment: 11 pages

Published
2024

12. Predicting Age from White Matter Diffusivity with Residual Learning

Author

Gao, Chenyu, Kim, Michael E., Lee, Ho Hin, Yang, Qi, Khairi, Nazirah Mohd, Kanakaraj, Praitayini, Newlin, Nancy R., Archer, Derek B., Jefferson, Angela L., Taylor, Warren D., Boyd, Brian D., Beason-Held, Lori L., Resnick, Susan M., Team, The BIOCARD Study, Huo, Yuankai, Van Schaik, Katherine D., Schilling, Kurt G., Moyer, Daniel, Išgum, Ivana, and Landman, Bennett A.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Neurons and Cognition
Abstract

Imaging findings inconsistent with those expected at specific chronological age ranges may serve as early indicators of neurological disorders and increased mortality risk. Estimation of chronological age, and deviations from expected results, from structural MRI data has become an important task for developing biomarkers that are sensitive to such deviations. Complementary to structural analysis, diffusion tensor imaging (DTI) has proven effective in identifying age-related microstructural changes within the brain white matter, thereby presenting itself as a promising additional modality for brain age prediction. Although early studies have sought to harness DTI's advantages for age estimation, there is no evidence that the success of this prediction is owed to the unique microstructural and diffusivity features that DTI provides, rather than the macrostructural features that are also available in DTI data. Therefore, we seek to develop white-matter-specific age estimation to capture deviations from normal white matter aging. Specifically, we deliberately disregard the macrostructural information when predicting age from DTI scalar images, using two distinct methods. The first method relies on extracting only microstructural features from regions of interest. The second applies 3D residual neural networks (ResNets) to learn features directly from the images, which are non-linearly registered and warped to a template to minimize macrostructural variations. When tested on unseen data, the first method yields mean absolute error (MAE) of 6.11 years for cognitively normal participants and MAE of 6.62 years for cognitively impaired participants, while the second method achieves MAE of 4.69 years for cognitively normal participants and MAE of 4.96 years for cognitively impaired participants. We find that the ResNet model captures subtler, non-macrostructural features for brain age prediction., Comment: SPIE Medical Imaging: Image Processing. San Diego, CA. February 2024 (accepted as poster presentation)

Published
2023
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13. $\mathcal{A}$-theory: A brane world-volume theory with manifest U-duality

Author

Hatsuda, Machiko, Hulík, Ondřej, Linch, William D., Siegel, Warren D., Wang, Di, and Wang, Yu-Ping

Subjects
High Energy Physics - Theory
Abstract

In this paper, the ${\cal A}$-theory, an extension of F-theory, is described as a fully U-duality covariant brane theory. This theory has some distinguishing features not known from world-sheet models. In particular, seen as a sigma model, both world-volume and target space coordinates are specific representations of the same group (the U-duality group). The U-duality group in question is an exceptional group (a split form of the $E_d$ series). The structure of this group allows it to encompass both the T-duality group of string theory as well as the general linear symmetry group of ${\cal M}$-theory. ${\cal A}$-theory is defined by the current algebras in Hamiltonian formalism, or by world-volume actions in Lagrangian formalism. The spacetime coordinates are selfdual gauge fields on the world-volume, requiring the Gauss law constraints tying the world-volume to spacetime. Solving the Gauss law constraints/the Virasoro constraints gives the world-volume/spacetime sectioning from ${\cal A}$-theory to ${\cal T}$-theory/ ${\cal M}$-theory respectively. The ${\cal A}$-theory Lagrangian admits extended symmetry which has not been observed previously in the literature, where the background fields include both the spacetime and the world-volume gravitational fields. We also constructed the four-point amplitude of ${\cal A}$-theory in the low energy limit. The amplitude is written in a way that the U-duality symmetry is manifest, but after solving the section condition, it reduces to the usual four-graviton amplitude. In the previous papers, we have referred to this model as F-theory, however, F-theory initiated by Vafa is now a big branch of string theory as the study of elliptic fibrations, so we refer to these constructions as generalized models of theory for all dimensions with all duality symmetries as ${\cal A}$-theory., Comment: 71 pages, 2 figures

Published
2023

15. Activation of parkin by a molecular glue

Author

Sauvé, Véronique, Stefan, Eric, Croteau, Nathalie, Goiran, Thomas, Fakih, Rayan, Bansal, Nupur, Hadzipasic, Adelajda, Fang, Jing, Murugan, Paramasivam, Chen, Shimin, Fon, Edward A., Hirst, Warren D., Silvian, Laura F., Trempe, Jean-François, and Gehring, Kalle

Published
2024
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17. Dose-dependent reduction of somatic expansions but not Htt aggregates by di-valent siRNA-mediated silencing of MSH3 in HdhQ111 mice

Author

Driscoll, Rachelle, Hampton, Lucas, Abraham, Neeta A., Larigan, J. Douglas, Joseph, Nadine F., Hernandez-Vega, Juan C., Geisler, Sarah, Yang, Fu-Chia, Deninger, Matthew, Tran, David T., Khatri, Natasha, Godinho, Bruno M. D. C., Kinberger, Garth A., Montagna, Daniel R., Hirst, Warren D., Guardado, Catherine L., Glajch, Kelly E., Arnold, H. Moore, Gallant-Behm, Corrie L., and Weihofen, Andreas

Published
2024
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19. Verifying Quantum Phase Estimation (QPE) using Prove-It

Author

Witzel, Wayne M., Craft, Warren D., Carr, Robert, and Kapur, Deepak

Subjects
Quantum Physics, Computer Science - Logic in Computer Science
Abstract

The general-purpose interactive theorem-proving assistant called Prove-It was used to verify the Quantum Phase Estimation (QPE) algorithm, specifically claims about its outcome probabilities. Prove-It is unique in its ability to express sophisticated mathematical statements, including statements about quantum circuits, integrated firmly within its formal theorem-proving framework. We demonstrate our ability to follow a textbook proof to produce a formally certified proof, highlighting useful automation features to fill in obvious steps and make formal proving nearly as straightforward as informal theorem proving. Finally, we make comparisons with formal theorem-proving in other systems where similar claims about QPE have been proven., Comment: 28 pages, 18 figures, 5 tables. Prove-It theorem-proving results available at http://pyproveit.org/ and Prove-It code available at https://github.com/PyProveIt/Prove-It

Published
2023
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20. The closure relations in optical afterglow of Gamma-Ray Bursts

Author

Dainotti, M. G., Levine, D., Warren, D., Fraija, N., and Sourav, S.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Gamma-ray bursts (GRBs) are extremely high-energy events that can be observed at very high redshift. In addition to gamma rays, they can emit in X-ray, optical, and sometimes radio wavelengths. Here, following the approach in Srinivasaragavan et al. (2020); Dainotti et al. (2021b,c), and Dainotti et al (2022, submitted), we consider 82 GRBs from Dainotti et al. (2022a) that have been observed in optical wavelengths and fitted with a broken power law (BPL). We consider the relations between the spectral and temporal indices (closure relations; CRs) according to the synchrotron forward-shock model evolving in the constant-density interstellar medium (ISM; k = 0) and the stellar Wind environment (k = 2) in both slow- and fast-cooling regimes, where the density profile is defined as n is proportional to r to the power minus k. We find the nu > max nuc, nu m regime is most favored, where nu c and nu m are the cooling and characteristic frequencies, respectively. Finally, we test the 2D Dainotti correlation between the rest-frame end time of the plateau and the luminosity at that time on GRBs that fulfill the most-favored CRs. When we compare the intrinsic scatter sigma int of those 2D correlations to the scatter presented in Dainotti et al. (2020b, 2022a), we see the scatters of our correlations generally agree with the previous values within 1sigma, both before and after correction for selection bias. This new information has helped us to pinpoint subsamples of GRBs with features that could drive the GRB emission mechanism, and eventually allow for GRBs to be used as standard candles, Comment: 18 pages , 6 figures, Accepted in The Astrophysical Journal

Published
2022
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27. Alienation

Author

Hviid Jacobsen, Michael, primary and TenHouten, Warren D., additional

Published
2024
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29. Author Correction: Intravenous and intracranial GD2-CAR T cells for H3K27M+ diffuse midline gliomas

Author

Monje, Michelle, Mahdi, Jasia, Majzner, Robbie, Yeom, Kristen W., Schultz, Liora M., Richards, Rebecca M., Barsan, Valentin, Song, Kun-Wei, Kamens, Jen, Baggott, Christina, Kunicki, Michael, Rietberg, Skyler P., Lim, Alexandria Sung, Reschke, Agnes, Mavroukakis, Sharon, Egeler, Emily, Moon, Jennifer, Patel, Shabnum, Chinnasamy, Harshini, Erickson, Courtney, Jacobs, Ashley, Duh, Allison K., Tunuguntla, Ramya, Klysz, Dorota Danuta, Fowler, Carley, Green, Sean, Beebe, Barbara, Carr, Casey, Fujimoto, Michelle, Brown, Annie Kathleen, Petersen, Ann-Louise G., McIntyre, Catherine, Siddiqui, Aman, Lepori-Bui, Nadia, Villar, Katlin, Pham, Kymhuynh, Bove, Rachel, Musa, Eric, Reynolds, Warren D., Kuo, Adam, Prabhu, Snehit, Rasmussen, Lindsey, Cornell, Timothy T., Partap, Sonia, Fisher, Paul G., Campen, Cynthia J., Grant, Gerald, Prolo, Laura, Ye, Xiaobu, Sahaf, Bita, Davis, Kara L., Feldman, Steven A., Ramakrishna, Sneha, and Mackall, Crystal

Published
2024
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30. Synchrotron Self-Compton Afterglow Closure Relations and Fermi-LAT Detected Gamma-Ray Bursts

Author

Fraija, N., Dainotti, M. G., Ugale, S., Jyoti, D., and Warren, D. C.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Fermi Large Area Telescope (Fermi-LAT) Collaboration reported the Second Gamma-ray Burst Catalog (2FLGC), which comprises a subset of 29 bursts with photon energies above 10 GeV. Although the standard synchrotron forward-shock model has successfully explained the Gamma-ray burst (GRB) afterglow observations, energetic photons higher than 10 GeV from these transient events can hardly be described in this scenario. We present the closure relations (CRs) of synchrotron self-Compton (SSC) afterglow model in the adiabatic and radiative scenario and when the central engine injects continuous energy into the blastwave to study the evolution of the spectral and temporal indexes of those bursts reported in 2FLGC. We consider the SSC afterglow model evolving in stellar-wind and interstellar medium, and the CRs as a function of the radiative parameter, the energy injection index, and the electron spectral index for $1

Published
2022
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31. First High-speed Video Camera Observations of a Lightning Flash Associated with a Downward Terrestrial Gamma-ray Flash

Author

Abbasi, R. U., Saba, M. M. F., Belz, J. W., Krehbiel, P. R., Rison, W., Kieu, N., da Silva, D. R., Rodeheffer, Dan, Stanley, M. A., Remington, J., Mazich, J., LeVon, R., Smout, K., Petrizze, A., Abu-Zayyad, T., Allen, M., Arai, Y., Arimura, R., Barcikowski, E., Bergman, D. R., Blake, S. A., Buckland, I., Cheon, B. G., Chikawa, M., Fujii, T., Fujisue, K., Fujita, K., Fujiwara, R., Fukushima, M., Furlich, G., Globus, N., Gonzalez, R., Hanlon, W., Hayashida, N., He, H., Hibino, K., Higuchi, R., Honda, K., Ikeda, D., Inoue, N., Ishii, T., Ito, H., Ivanov, D., Iwakura, H., Iwasaki, A., Jeong, H. M., Jeong, S., Jui, C. C. H., Kadota, K., Kakimoto, F., Kalashev, O., Kasahara, K., Kasami, S., Kawakami, S., Kawata, K., Kharuk, I., Kido, E., Kim, H. B., Kim, J. H., Kim, S. W., Kimura, Y., Komae, I., Kubota, Y., Kuzmin, V., Kuznetsov, M., Kwon, Y. J., Lee, K. H., Lubsandorzhiev, B., Lundquist, J. P., Matsumiya, H., Matsuyama, T., Matthews, J. N., Mayta, R., Myers, I., Nagataki, S., Nakai, K., Nakamura, R., Nakamura, T., Nakamura, Y., Nakazawa, A., Nishio, E., Nonaka, T., Oda, H., Ogio, S., Ohnishi, M., Ohoka, H., Oku, Y., Okuda, T., Omura, Y., Ono, M., Oshima, A., Ozawa, S., Park, I. H., Potts, M., Pshirkov, M. S., Rodriguez, D. C., Rott, C., Rubtsov, G. I., Ryu, D., Sagawa, H., Sakaki, N., Sako, T., Sakurai, N., Sato, K., Seki, T., Sekino, K., Shah, P. D., Shibasaki, Y., Shibata, N., Shibata, T., Shikita, J., Shimodaira, H., Shin, B. K., Shin, H. S., Shinto, D., Smith, J. D., Sokolsky, P., Stokes, B. T., Stroman, T. A., Takahashi, K., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Udo, S., Uehama, T., Urban, F., Warren, D., Wong, T., Yamamoto, M., Yamazaki, K., Yashiro, K., Yoshida, F., Zhezher, Y., and Zundel, Z.

Subjects
Physics - Atmospheric and Oceanic Physics, Astrophysics - Instrumentation and Methods for Astrophysics, High Energy Physics - Experiment
Abstract

In this paper, we present the first high-speed video observation of a cloud-to-ground lightning flash and its associated downward-directed Terrestrial Gamma-ray Flash (TGF). The optical emission of the event was observed by a high-speed video camera running at 40,000 frames per second in conjunction with the Telescope Array Surface Detector, Lightning Mapping Array, interferometer, electric-field fast antenna, and the National Lightning Detection Network. The cloud-to-ground flash associated with the observed TGF was formed by a fast downward leader followed by a very intense return stroke peak current of -154 kA. The TGF occurred while the downward leader was below cloud base, and even when it was halfway in its propagation to ground. The suite of gamma-ray and lightning instruments, timing resolution, and source proximity offer us detailed information and therefore a unique look at the TGF phenomena.

Published
2022
Full Text
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33. Search for Spatial Correlations of Neutrinos with Ultra-High-Energy Cosmic Rays

Author

The ANTARES collaboration, Albert, A., Alves, S., André, M., Anghinolfi, M., Ardid, M., Ardid, S., Aubert, J. -J., Aublin, J., Baret, B., Basa, S., Belhorma, B., Bendahman, M., Bertin, V., Biagi, S., Bissinger, M., Boumaaza, J., Bouta, M., Bouwhuis, M. C., Brânzaş, H., Bruijn, R., Brunner, J., Busto, J., Caiffi, B., Calvo, D., Capone, A., Caramete, L., Carr, J., Carretero, V., Celli, S., Chabab, M., Chau, T. N., Moursli, R. Cherkaoui El, Chiarusi, T., Circella, M., Coleiro, A., Coniglione, R., Coyle, P., Creusot, A., Díaz, A. F., Distefano, C., Di Palma, I., Domi, A., Donzaud, C., Dornic, D., Drouhin, D., Eberl, T., van Eeden, T., van Eijk, D., Khayati, N. El, Enzenhöfer, A., Fermani, P., Ferrara, G., Filippini, F., Fusco, L., Gatelet, Y., Gay, P., Glotin, H., Gozzini, R., Ruiz, R. Gracia, Graf, K., Guidi, C., Hallmann, S., van Haren, H., Heijboer, A. J., Hello, Y., Hernández-Rey, J. J., Hößl, J., Hofestädt, J., Huang, F., Illuminati, G., James, C. W., Jisse-Jung, B., de Jong, M., de Jong, P., Kadler, M., Kalekin, O., Katz, U., Khan-Chowdhury, N. R., Kouchner, A., Kreykenbohm, I., Kulikovskiy, V., Lahmann, R., Breton, R. Le, LeStum, S., Lefèvre, D., Leonora, E., Levi, G., Lopez-Coto, D., Loucatos, S., Maderer, L., Manczak, J., Marcelin, M., Margiotta, A., Marinelli, A., Martínez-Mora, J. A., Martino, B., Melis, K., Migliozzi, P., Moussa, A., Muller, R., Nauta, L., Navas, S., Nezri, E., Fearraigh, B. Ó, Păun, A., Păvălaş, G. E., Pellegrino, C., Perrin-Terrin, M., Pestel, V., Piattelli, P., Pieterse, C., Poirè, C., Popa, V., Pradier, T., Randazzo, N., Real, D., Reck, S., Riccobene, G., Romanov, A., Sánchez-Losa, A., Greus, F. Salesa, Samtleben, D. F. E., Sanguineti, M., Sapienza, P., Schnabel, J., Schumann, J., Schüssler, F., Seneca, J., Spurio, M., Stolarczyk, Th., Taiuti, M., Tayalati, Y., Tingay, S. J., Vallage, B., Van Elewyck, V., Versari, F., Viola, S., Vivolo, D., Wilms, J., Zavatarelli, S., Zegarelli, A., Zornoza, J. D., Zúñiga, J., collaboration, The IceCube, Abbasi, R., Ackermann, M., Adams, J., Aguilar, J. A., Ahlers, M., Ahrens, M., Alameddine, J. M., Alispach, C., Alves Jr., A. A., Amin, N. M., Andeen, K., Anderson, T., Anton, G., Argüelles, C., Ashida, Y., Axani, S., Bai, X., V., A. Balagopal, Barbano, A., Barwick, S. W., Bastian, B., Basu, V., Baur, S., Bay, R., Beatty, J. J., Becker, K. -H., Tjus, J. Becker, Bellenghi, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Binder, G., Bindig, D., Blaufuss, E., Blot, S., Boddenberg, M., Bontempo, F., Borowka, J., Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Bradascio, F., Braun, J., Brinson, B., Bron, S., Brostean-Kaiser, J., Browne, S., Burgman, A., Burley, R. T., Busse, R. S., Campana, M. A., Carnie-Bronca, E. G., Chen, C., Chen, Z., Chirkin, D., Choi, K., Clark, B. A., Clark, K., Classen, L., Collin, G. H., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Cross, R., Dappen, C., Dave, P., De Clercq, C., DeLaunay, J. 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A., Takagi, Y., Takahashi, Y., Takamura, M., Takeda, M., Takeishi, R., Taketa, A., Takita, M., Tameda, Y., Tanaka, H., Tanaka, K., Tanaka, M., Tanoue, Y., Thomas, S. B., Thomson, G. B., Tinyakov, P., Tkachev, I., Tokuno, H., Tomida, T., Troitsky, S., Tsuda, R., Tsunesada, Y., Uchihori, Y., Udo, S., Uehama, T., Urban, F., Warren, D., Wong, T., Yamamoto, M., Yamazaki, K., Yashiro, K., Yoshida, F., Yoshioka, Y., Zhezher, Y., and Zundel, Z.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

For several decades, the origin of ultra-high-energy cosmic rays (UHECRs) has been an unsolved question of high-energy astrophysics. One approach for solving this puzzle is to correlate UHECRs with high-energy neutrinos, since neutrinos are a direct probe of hadronic interactions of cosmic rays and are not deflected by magnetic fields. In this paper, we present three different approaches for correlating the arrival directions of neutrinos with the arrival directions of UHECRs. The neutrino data is provided by the IceCube Neutrino Observatory and ANTARES, while the UHECR data with energies above $\sim$50 EeV is provided by the Pierre Auger Observatory and the Telescope Array. All experiments provide increased statistics and improved reconstructions with respect to our previous results reported in 2015. The first analysis uses a high-statistics neutrino sample optimized for point-source searches to search for excesses of neutrinos clustering in the vicinity of UHECR directions. The second analysis searches for an excess of UHECRs in the direction of the highest-energy neutrinos. The third analysis searches for an excess of pairs of UHECRs and highest-energy neutrinos on different angular scales. None of the analyses has found a significant excess, and previously reported over-fluctuations are reduced in significance. Based on these results, we further constrain the neutrino flux spatially correlated with UHECRs., Comment: 39 pages, 7 figures, 4 tables; updated source files including xml authorlist

Published
2022
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41. CD22-directed CAR T-cell therapy for large B-cell lymphomas progressing after CD19-directed CAR T-cell therapy: a dose-finding phase 1 study

Author

Klysz, Dorota Danuta, Gkitsas-Long, Nikolaos, Bacigalupi, Juliana, Iglesias, Maria, Crawford, Emma, Nichols, Linnea, Cunanan, Kristen, Tamaresis, John, Spiegel, Jay Y., Ehlinger, Zachary, Kuo, Adam, Reynolds, Warren D., Arai, Sally, Johnston, Laura, Lowsky, Robert, Meyer, Everett, Negrin, Robert S., Rezvani, Andrew R., Shiraz, Parveen, Sidana, Surbhi, Weng, Wen Kai, Bharadwaj, Sushma, Dahiya, Saurabh, Smith, Melody, Schultz, Liora M., Ramakrishna, Sneha, Davis, Kara L., Tunuguntla, Ramya, Frank, Matthew J, Baird, John H, Kramer, Anne Marijn, Srinagesh, Hrishikesh K, Patel, Shabnum, Brown, Annie Kathleen, Oak, Jean S, Younes, Sheren F, Natkunam, Yasodha, Hamilton, Mark P, Su, Yi-Jiun, Agarwal, Neha, Chinnasamy, Harshini, Egeler, Emily, Mavroukakis, Sharon, Feldman, Steven A, Sahaf, Bita, Mackall, Crystal L, Muffly, Lori, and Miklos, David B

Published
2024
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42. Deciphering pathophysiological mechanisms underlying cystathionine beta-synthase-deficient homocystinuria using targeted metabolomics, liver proteomics, sphingolipidomics and analysis of mitochondrial function

Author

Majtan, Tomas, Olsen, Thomas, Sokolova, Jitka, Krijt, Jakub, Křížková, Michaela, Ida, Tomoaki, Ditrói, Tamás, Hansikova, Hana, Vit, Ondrej, Petrak, Jiri, Kuchař, Ladislav, Kruger, Warren D., Nagy, Péter, Akaike, Takaaki, and Kožich, Viktor

Published
2024
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43. Graph Autoencoders for Embedding Learning in Brain Networks and Major Depressive Disorder Identification

Author

Noman, Fuad, Ting, Chee-Ming, Kang, Hakmook, Phan, Raphael C. -W., Boyd, Brian D., Taylor, Warren D., and Ombao, Hernando

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Brain functional connectivity (FC) reveals biomarkers for identification of various neuropsychiatric disorders. Recent application of deep neural networks (DNNs) to connectome-based classification mostly relies on traditional convolutional neural networks using input connectivity matrices on a regular Euclidean grid. We propose a graph deep learning framework to incorporate the non-Euclidean information about graph structure for classifying functional magnetic resonance imaging (fMRI)-derived brain networks in major depressive disorder (MDD). We design a novel graph autoencoder (GAE) architecture based on the graph convolutional networks (GCNs) to embed the topological structure and node content of large-sized fMRI networks into low-dimensional latent representations. In network construction, we employ the Ledoit-Wolf (LDW) shrinkage method to estimate the high-dimensional FC metrics efficiently from fMRI data. We consider both supervised and unsupervised approaches for the graph embedding learning. The learned embeddings are then used as feature inputs for a deep fully-connected neural network (FCNN) to discriminate MDD from healthy controls. Evaluated on two resting-state fMRI (rs-fMRI) MDD datasets, results show that the proposed GAE-FCNN model significantly outperforms several state-of-the-art methods for brain connectome classification, achieving the best accuracy using the LDW-FC edges as node features. The graph embeddings of fMRI FC networks learned by the GAE also reveal apparent group differences between MDD and HC. Our new framework demonstrates feasibility of learning graph embeddings on brain networks to provide discriminative information for diagnosis of brain disorders.

Published
2021
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44. Closure relations during the plateau emission of Swift GRBs and the fundamental plane

Author

Dainotti, M. G., Lenart, A. Ł., Fraija, N., Nagataki, S., Warren, D. C., De Simone, B., Srinivasaragavan, G., and Mata, A.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

The Neil Gehrels Swift observatory observe Gamma-Ray bursts (GRBs) plateaus in X-rays. We test the reliability of the closure relations through the fireball model when dealing with the GRB plateau emission. We analyze 455 X-ray lightcurves (LCs) collected by \emph{Swift} from 2005 (January) until 2019 (August) for which the redshift is both known and unknown using the phenomenological Willingale 2007 model. Using these fits, we analyze the emission mechanisms and astrophysical environments of these GRBs through the closure relations within the time interval of the plateau emission. Finally, we test the 3D fundamental plane relation (Dainotti relation) which connects the prompt peak luminosity, the time at the end of the plateau (rest-frame), and the luminosity at that time, on the GRBs with redshift, concerning groups determined by the closure relations. This allows us to check if the intrinsic scatter \sigma_{int} of any of these groups is reduced compared to previous literature. The most fulfilled environments for the electron spectral distribution, p>2, are Wind Slow Cooling (SC) and ISM Slow Cooling for cases in which the parameter q, which indicates the flatness of the plateau emission and accounts for the energy injection, is =0 and =0.5, respectively, both in the cases with known and unknown redshifts. We also find that for the sGRBs All ISM Environments with $q=0$ have the smallest \sigma_{int}=0.04 \pm 0.15 in terms of the fundamental plane relation holding a probability of occurring by chance of p=0.005. We have shown that the majority of GRBs presenting the plateau emission fulfil the closure relations, including the energy injection, with a particular preference for the Wind SC environment. The subsample of GRBs that fulfil given relations can be used as possible standard candles and can suggest a way to reduce the intrinsic scatter of these studied relationships., Comment: 44 pages, 23 figures; Accepted to the PASJ to be published soon

Published
2021
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45. Calibration and Validation of NOAA-21 Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper Sensor Data Record Data

Author

Banghua Yan, Trevor Beck, Junye Chen, Steven Buckner, Xin Jin, Ding Liang, Sirish Uprety, Jingfeng Huang, Lawrence E. Flynn, Likun Wang, Quanhua Liu, and Warren D. Porter

Subjects
NOAA-21 OMPS, Nadir Mapper (NM), calibration and validation, dark current correction, wavelength registration, intra-orbit wavelength shift correction, Science
Abstract

The Ozone Mapping and Profiler Suites (OMPS) Nadir Mapper (NM) is a grating spectrometer within the OMPS nadir instruments onboard the SNPP, NOAA-20, and NOAA-21 satellites. It is designed to measure Earth radiance and solar irradiance spectra in wavelengths from 300 nm to 380 nm for operational retrievals of the nadir total column ozone. This study presents calibration and validation analysis results for the NOAA-21 OMPS NM SDR data to meet the JPSS scientific requirements. The NOAA-21 OMPS SDR calibration derives updates of several previous OMPS algorithms, including the dark current correction algorithm, one-time wavelength registration from ground to on-orbit, daily intra-orbit wavelength shift correction, and stray light correction. Additionally, this study derives an empirical scale factor to remove 2.2% of systematic biases in solar flux data, which were caused by pre-launch solar calibration errors of the OMPS nadir instruments. The validation of the NOAA-21 OMPS SDR data is conducted using various methods. For example, the 32-day average method and radiative transfer model are employed to estimate inter-sensor radiometric calibration differences from either the SNPP or NOAA-20 data. The quality of the NOAA-21 OMPS NM SDR data is largely consistent with that of the SNPP and NOAA-20 OMPS data, with differences generally within ±2%. This meets the scientific requirements, except for some deviations mainly in the dichroic range between 300 nm and 303 nm. The deep convective cloud target approach is used to monitor the stability of NOAA-21 OMPS reflectance above 330 nm, showing a variation of 0.5% over the observed period. Data from the NOAA-21 VIIRS M1 band are used to estimate OMPS NM data geolocation errors, revealing that along-track errors can reach up to 3 km, while cross-track errors are generally within ±1 km.

Published
2024
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48. Prove-It: A Proof Assistant for Organizing and Verifying General Mathematical Knowledge

Author

Witzel, Wayne M., Craft, Warren D., Carr, Robert D., and Larrañaga, Joaquín E. Madrid

Subjects
Computer Science - Logic in Computer Science, Quantum Physics
Abstract

We introduce Prove-It, a Python-based general-purpose interactive theorem-proving assistant designed with the goal of making formal theorem proving as easy and natural as informal theorem proving (with moderate training). Prove-It uses a highly-flexible Jupyter notebook-based user interface that documents interactions and proof steps using LaTeX. We review Prove-It's highly expressive representation of expressions, judgments, theorems, and proofs; demonstrate the system by constructing a traditional proof-by-contradiction that $\sqrt{2}\notin\mathbb{Q}$; and discuss how the system avoids inconsistencies such as Russell's and Curry's paradoxes. Extensive documentation is provided in the appendices about core elements of the system. Current development and future work includes promising applications to quantum circuit manipulation and quantum algorithm verification., Comment: Updated the links to our pyproveit.org website. 38 pages, 12 figures

Published
2020

49. Integrative geochronology calibrates the Middle and Late Stone Ages of Ethiopia’s Afar Rift

Author

Niespolo, Elizabeth M, WoldeGabriel, Giday, Hart, William K, Renne, Paul R, Sharp, Warren D, Shackley, M Steven, Ambrose, Stanley H, Asfaw, Berhane, Beyene, Yonas, Brasil, Marianne F, Carlson, Joshua P, Sahle, Yonatan, and White, Tim D

Subjects
geochronology, Middle Stone Age, Late Stone Age, Middle Awash, Ethiopia
Abstract

The Halibee member of the Upper Dawaitoli Formation of Ethiopia's Middle Awash study area features a wealth of Middle and Later Stone Age (MSA and LSA) paleoanthropological resources in a succession of Pleistocene sediments. We introduce these artifacts and fossils, and determine their chronostratigraphic placement via a combination of established radioisotopic methods and a recently developed dating method applied to ostrich eggshell (OES). We apply the recently developed 230Th/U burial dating of OES to bridge the temporal gap between radiocarbon (14C) and 40Ar/39Ar ages for the MSA and provide 14C ages to constrain the younger LSA archaeology and fauna to ∼24 to 21.4 ka. Paired 14C and 230Th/U burial ages of OES agree at ∼31 ka for an older LSA locality, validating the newer method, and in turn supporting its application to stratigraphically underlying MSA occurrences previously constrained only by a maximum 40Ar/39Ar age. Associated fauna, flora, and Homo sapiens fossils are thereby now fixed between 106 ± 20 ka and 96.4 ± 1.6 ka (all errors 2σ). Additional 40Ar/39 results on an underlying tuff refine its age to 158.1 ± 11.0 ka, providing a more precise minimum age for MSA lithic artifacts, fauna, and H. sapiens fossils recovered ∼9 m below it. These results demonstrate how chronological control can be obtained in tectonically active and stratigraphically complex settings to precisely calibrate crucial evidence of technological, environmental, and evolutionary changes during the African Middle and Late Pleistocene.

Published
2021

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