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6,516 results on '"Curtis, E. A."'

1. Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

Author

Aamir, M., Acar, B., Adamov, G., Adams, T., Adloff, C., Afanasiev, S., Agrawal, C., Ahmad, A., Ahmed, H. A., Akbar, S., Akchurin, N., Akgul, B., Akgun, B., Akpinar, R. O., Aktas, E., AlKadhim, A., Alexakhin, V., Alimena, J., Alison, J., Alpana, A., Alshehri, W., Dominguez, P. Alvarez, Alyari, M., Amendola, C., Amir, R. B., Andersen, S. B., Andreev, Y., Antoszczuk, P. D., Aras, U., Ardila, L., Aspell, P., Avila, M., Awad, I., Aydilek, O., Azimi, Z., Pretel, A. Aznar, Bach, O. A., Bainbridge, R., Bakshi, A., Bam, B., Banerjee, S., Barney, D., Bayraktar, O., Beaudette, F., Beaujean, F., Becheva, E., Behera, P. K., Belloni, A., Bergauer, T., Besancon, M., Bylund, O. Bessidskaia, Bhatt, L., Bhowmil, D., Blekman, F., Blinov, P., Bloch, P., Bodek, A., Boger, a., Bonnemaison, A., Bouyjou, F., Brennan, L., Brondolin, E., Brusamolino, A., Bubanja, I., Perraguin, A. Buchot, Bunin, P., Misura, A. Burazin, Butler-nalin, A., Cakir, A., Callier, S., Campbell, S., Canderan, K., Cankocak, K., Cappati, A., Caregari, S., Carron, S., Carty, C., Cauchois, A., Ceard, L., Cerci, S., Chang, P. J., Chatterjee, R. M., Chatterjee, S., Chattopadhyay, P., Chatzistavrou, T., Chaudhary, M. S., Chauhan, A., Chen, J. A., Chen, J., Chen, Y., Cheng, K., Cheung, H., Chhikara, J., Chiron, A., Chiusi, M., Chokheli, D., Chudasama, R., Clement, E., Mendez, S. Coco, Coko, D., Coskun, K., Couderc, F., Crossman, B., Cui, Z., Cuisset, T., Cummings, G., Curtis, E. M., D'Alfonso, M., D-hler-ball, J., Dadazhanova, O., Damgov, J., Das, I., DasGupta, S., Dauncey, P., Mendes, A. David Tinoco, Davies, G., Davignon, O., DeLa, P. deBarbaroC., DeSilva, M., DeWit, A., Debbins, P., Defranchis, M. M., Delagnes, E., Devouge, P., Dewangan, C., DiGuglielmo, G., Diehl, L., Dilsiz, K., Dincer, G. G., Dittmann, J., Dragicevic, M., Du, D., Dubinchik, B., Dugad, S., Dulucq, F., Dumanoglu, I., Duran, B., Dutta, S., Dutta, V., Dychkant, A., Dünser, M., Edberg, T., Ehle, I. T., Berni, A. El, Elias, F., Eno, S. C., Erdogan, E. N., Erkmen, B., Ershov, Y., Ertorer, E. Y., Extier, S., Eychenne, L., Fedar, Y. E., Fedi, G., De Almeida, J. P. Figueiredo De De Sá Sousa, Alves, B. A. Fontana Santos Santos, Frahm, E., Francis, K., Freeman, J., French, T., Gaede, F., Gandhi, P. K., Ganjour, S., Garcia-Bellido, A., Gastaldi, F., Gazi, L., Gecse, Z., Gerwig, H., Gevin, O., Ghosh, S., Gill, K., Gleyzer, S., Godinovic, N., Goek, M., Goettlicher, P., Goff, R., Golunov, A., Gonultas, B., Martínez, J. D. González, Gorbounov, N., Gouskos, L., Gray, A., Gray, L., Grieco, C., Groenroos, S., Groner, D., Gruber, A., Grummer, A., Grönroos, S., Guilloux, F., Guler, Y., Gungordu, A. D., Guo, J., Guo, K., Guler, E. Gurpinar, Gutti, H. K., Guvenli, A. A., Gülmez, E., Hacisahinoglu, B., Halkin, Y., Machado, G. Hamilton Ilha, Hare, H. S., Hatakeyama, K., Heering, A. H., Hegde, V., Heintz, U., Hinton, N., Hinzmann, A., Hirschauer, J., Hitlin, D., Hos, İ., Hou, B., Hou, X., Howard, A., Howe, C., Hsieh, H., Hsu, T., Hua, H., Hummer, F., Imran, M., Incandela, J., Iren, E., Isildak, B., Jackson, P. S., Jackson, W. J., Jain, S., Jana, P., Jaroslavceva, J., Jena, S., Jige, A., Jordano, P. P., Joshi, U., Kaadze, K., Kafizov, A., Kalipoliti, L., Tharayil, A. Kallil, Kaluzinska, O., Kamble, S., Kaminskiy, A., Kanemura, M., Kanso, H., Kao, Y., Kapic, A., Kapsiak, C., Karjavine, V., Karmakar, S., Karneyeu, A., Kaya, M., Topaksu, A. Kayis, Kaynak, B., Kazhykarim, Y., Khan, F. A., Khudiakov, A., Kieseler, J., Kim, R. S., Klijnsma, T., Kloiber, E. G., Klute, M., Kocak, Z., Kodali, K. R., Koetz, K., Kolberg, T., Kolcu, O. B., Komaragiri, J. R., Komm, M., Kopsalis, I., Krause, H. A., Krawczyk, M. A., Vinayakam, T. R. Krishnaswamy, Kristiansen, K., Kristic, A., Krohn, M., Kronheim, B., Krüger, K., Kudtarkar, C., Kulis, S., Kumar, M., Kumar, N., Kumar, S., Verma, R. Kumar, Kunori, S., Kunts, A., Kuo, C., Kurenkov, A., Kuryatkov, V., Kyre, S., Ladenson, J., Lamichhane, K., Landsberg, G., Langford, J., Laudrain, A., Laughlin, R., Lawhorn, J., Dortz, O. Le, Lee, S. W., Lektauers, A., Lelas, D., Leon, M., Levchuk, L., Li, A. J., Li, J., Li, Y., Liang, Z., Liao, H., Lin, K., Lin, W., Lin, Z., Lincoln, D., Linssen, L., Litomin, A., Liu, G., Liu, Y., Lobanov, A., Lohezic, V., Loiseau, T., Lu, C., Lu, R., Lu, S. Y., Lukens, P., Mackenzie, M., Magnan, A., Magniette, F., Mahjoub, A., Mahon, D., Majumder, G., Makarenko, V., Malakhov, A., Malgeri, L., Mallios, S., Mandloi, C., Mankel, A., Mannelli, M., Mans, J., Mantilla, C., Martinez, G., Massa, C., Masterson, P., Matthewman, M., Matveev, V., Mayekar, S., Mazlov, I., Mehta, A., Mestvirishvili, A., Miao, Y., Milella, G., Mirza, I. R., Mitra, P., Moccia, S., Mohanty, G. B., Monti, F., Moortgat, F., Murthy, S., Music, J., Musienko, Y., Nabili, S., Nayak, S., Nelson, J. W., Nema, A., Neutelings, I., Niedziela, J., Nikitenko, A., Noonan, D., Noy, M., Nurdan, K., Obraztsov, S., Ochando, C., Ogul, H., Olsson, J., Onel, Y., Ozkorucuklu, S., Paganis, E., Palit, P., Pan, R., Pandey, S., Pantaleo, F., Papageorgakis, C., Paramesvaran, S., Paranjpe, M. M., Parolia, S., Parsons, A. G., Parygin, P., Paulini, M., Paus, C., Peñaló, K., Pedro, K., Pekic, V., Peltola, T., Peng, B., Perego, A., Perini, D., Petrilli, A., Pham, H., Pierre-Emile, T., Podem, S. K., Popov, V., Portales, L., Potok, O., Pradeep, P. B., Pramanik, R., Prosper, H., Prvan, M., Qasim, S. R., Qu, H., Quast, T., Trivino, A. Quiroga, Rabour, L., Raicevic, N., Rajpoot, H., Rao, M. A., Rapacz, K., Redjeb, W., Reinecke, M., Revering, M., Roberts, A., Rohlf, J., Rosado, P., Rose, A., Rothman, S., Rout, P. K., Rovere, M., Rumerio, P., Rusack, R., Rygaard, L., Ryjov, V., Sadivnycha, S., Sahin, M. Ö., Sakarya, U., Salerno, R., Saradhy, R., Saraf, M., Sarbandi, K., Sarkisla, M. A., Satyshev, I., Saud, N., Sauvan, J., Schindler, G., Schmidt, A., Schmidt, I., Schmitt, M. H., Sculac, A., Sculac, T., Sedelnikov, A., Seez, C., Sefkow, F., Selivanova, D., Selvaggi, M., Sergeychik, V., Sert, H., Shahid, M., Sharma, P., Sharma, R., Sharma, S., Shelake, M., Shenai, A., Shih, C. W., Shinde, R., Shmygol, D., Shukla, R., Sicking, E., Silva, P., Simsek, C., Simsek, E., Sirasva, B. K., Sirois, Y., Song, S., Song, Y., Soudais, G., Sriram, S., StJacques, R. R., StahlLeiton, A. G., Steen, A., Stein, J., Strait, J., Strobbe, N., Su, X., Sukhov, E., Suleiman, A., Cerci, D. Sunar, Suryadevara, P., Swain, K., Syal, C., Tali, B., Tanay, K., Tang, W., Tanvir, A., Tao, J., Tarabini, A., Tatli, T., Taylor, R., Taysi, Z. C., Teafoe, G., Tee, C. Z., Terrill, W., Thienpont, D., Thomas, R., Titov, M., Todd, C., Todd, E., Toms, M., Tosun, A., Troska, J., Tsai, L., Tsamalaidze, Z., Tsionou, D., Tsipolitis, G., Tsirigoti, M., Tu, R., Polat, S. N. Tural, Undleeb, S., Usai, E., Uslan, E., Ustinov, V., Vernazza, E., Viahin, O., Viazlo, O., Vichoudis, P., Vijay, A., Virdee, T., Voirin, E., Vojinovic, M., Voytishin, N., Vámi, T. Á., Wade, A., Walter, D., Wang, C., Wang, F., Wang, J., Wang, K., Wang, X., Wang, Y., Wang, Z., Wanlin, E., Wayne, M., Wetzel, J., Whitbeck, A., Wickwire, R., Wilmot, D., Wilson, J., Wu, H., Xiao, M., Yang, J., Yazici, B., Ye, Y., Yetkin, T., Yi, R., Yohay, R., Yu, T., Yuan, C., Yuan, X., Yuksel, O., YushmanoV, I., Yusuff, I., Zabi, A., Zareckis, D., Zarubin, A., Zehetner, P., Zghiche, A., Zhang, C., Zhang, D., Zhang, H., Zhang, J., Zhang, Z., Zhao, X., Zhong, J., Zhou, Y., and Zorbilmez, Ç.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Physics - Data Analysis, Statistics and Probability
Abstract

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated., Comment: Prepared for submission to JINST

Published
2024

3. $^{171}$Yb$^+$ optical clock with $2.2\times 10^{-18}$ systematic uncertainty and absolute frequency measurements

Author

Tofful, Alexandra, Baynham, Charles F. A., Curtis, E. Anne, Parsons, Adam O., Robertson, Billy I., Schioppo, Marco, Tunesi, Jacob, Margolis, Helen S., Hendricks, Richard J., Whale, Josh, Thompson, Richard C., and Godun, Rachel M.

Subjects
Physics - Atomic Physics
Abstract

A full evaluation of the uncertainty budget for the ytterbium ion optical clock at the National Physical Laboratory (NPL) was performed on the electric octupole (E3) $^2\mathrm{S}_{1/2}\,\rightarrow\, ^2\mathrm{F}_{7/2}$ transition. The total systematic frequency shift was measured with a fractional standard systematic uncertainty of $2.2\times 10^{-18}$. Furthermore, the absolute frequency of the E3 transition of the $^{171}$Yb$^+$ ion was measured between 2019 and 2023 via a link to International Atomic Time (TAI) and against the local caesium fountain NPL-CsF2. The absolute frequencies were measured with fractional standard uncertainties between $3.7 \times 10^{-16}$ and $1.1 \times 10^{-15}$, and all were in agreement with the 2021 BIPM recommended frequency., Comment: 16 pages, 8 figures, submitted to Metrologia

Published
2024
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6. Analysis of atomic-clock data to constrain variations of fundamental constants

Author

Sherrill, Nathaniel, Parsons, Adam O., Baynham, Charles F. A., Bowden, William, Curtis, E. Anne, Hendricks, Richard, Hill, Ian R., Hobson, Richard, Margolis, Helen S., Robertson, Billy I., Schioppo, Marco, Szymaniec, Krzysztof, Tofful, Alexandra, Tunesi, Jacob, Godun, Rachel M., and Calmet, Xavier

Subjects
Physics - Atomic Physics, High Energy Physics - Phenomenology
Abstract

We present a new framework to study the time variation of fundamental constants in a model-independent way. Model independence implies more free parameters than assumed in previous studies. Using data from atomic clocks based on $^{87}$Sr, $^{171}$Yb$^+$ and $^{133}$Cs, we set bounds on parameters controlling the variation of the fine-structure constant, $\alpha$, and the electron-to-proton mass ratio, $\mu$. We consider variations on timescales ranging from a minute to almost a day. In addition, we use our results to derive some of the tightest limits to date on the parameter space of models of ultralight dark matter and axion-like particles.

Published
2023

9. Estimating the expansion and reduction of agricultural extent in Egypt using Landsat time series

Author

Kelsee H. Bratley and Curtis E. Woodcock

Subjects
Agriculture, Cropland mapping, Change detection, LandTrendr, Time series, Egypt, Physical geography, GB3-5030, Environmental sciences, GE1-350
Abstract

Increasing population and the consequent rise in the demand for food and water resources pose significant challenges for the future of agriculture in Egypt. Rapid large-scale agricultural expansion has occurred in the country to meet the growing demand, but agricultural loss from urban infringement and field abandonment remains prevalent. Documenting the full spectrum of changes within Egypt’s agricultural systems is crucial for developing effective land-use policies that improve food security. Here we map and estimate the areal extent of multiple types of agricultural change in Egypt (i.e., agricultural gain, agricultural abandonment, and agricultural loss from urban growth) by applying the Landsat-based detection of trends in disturbance and recovery (LandTrendr) algorithm, a widely used time series temporal segmentation algorithm. First, we used LandTrendr to identify areas of agricultural gain and loss throughout Egypt from 1987 to 2019. Second, we combined land-cover maps and the LandTrendr results to create a comprehensive land-cover change map. Lastly, we evaluated the accuracy of our findings and estimated per-class areas with quantified uncertainty using high-quality reference data. Our results reveal a notable expansion in Egypt’s agricultural land area. However, this growth is accompanied by the widespread loss of prime agricultural land, a consequence of urban development and agricultural abandonment. This study emphasizes the pressing need for the implementation of sustainable land-use policies in Egypt, particularly as climate change will exacerbate pressures on the agricultural sector in the future.

Published
2024
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11. Bridging the literacy gap for surgical consents: an AI-human expert collaborative approach

Author

Rohaid Ali, Ian D. Connolly, Oliver Y. Tang, Fatima N. Mirza, Benjamin Johnston, Hael F. Abdulrazeq, Rachel K. Lim, Paul F. Galamaga, Tiffany J. Libby, Neel R. Sodha, Michael W. Groff, Ziya L. Gokaslan, Albert E. Telfeian, John H. Shin, Wael F. Asaad, James Zou, and Curtis E. Doberstein

Subjects
Computer applications to medicine. Medical informatics, R858-859.7
Abstract

Abstract Despite the importance of informed consent in healthcare, the readability and specificity of consent forms often impede patients’ comprehension. This study investigates the use of GPT-4 to simplify surgical consent forms and introduces an AI-human expert collaborative approach to validate content appropriateness. Consent forms from multiple institutions were assessed for readability and simplified using GPT-4, with pre- and post-simplification readability metrics compared using nonparametric tests. Independent reviews by medical authors and a malpractice defense attorney were conducted. Finally, GPT-4’s potential for generating de novo procedure-specific consent forms was assessed, with forms evaluated using a validated 8-item rubric and expert subspecialty surgeon review. Analysis of 15 academic medical centers’ consent forms revealed significant reductions in average reading time, word rarity, and passive sentence frequency (all P

Published
2024
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12. Measuring the stability of fundamental constants with a network of clocks

Author

Barontini, G., Blackburn, L., Boyer, V., Butuc-Mayer, F., Calmet, X., Lopez-Urrutia, J. R. Crespo, Curtis, E. A., Darquie, B., Dunningham, J., Fitch, N. J., Forgan, E. M., Georgiou, K., Gill, P., Godun, R. M., Goldwin, J., Guarrera, V., Harwood, A. C., Hill, I. R., Hendricks, R. J., Jeong, M., Johnson, M. Y. H., Keller, M., Sajith, L. P. Kozhiparambil, Kuipers, F., Margolis, H. S., Mayo, C., Newman, P., Parsons, A. O., Prokhorov, L., Robertson, B. I., Rodewald, J., Safronova, M. S., Sauer, B. E., Schioppo, M., Sherrill, N., Stadnik, Y. V., Szymaniec, K., Tarbutt, M. R., Thompson, R. C., Tofful, A., Tunesi, J., Vecchio, A., Wang, Y., and Worm, S.

Subjects
High Energy Physics - Phenomenology, Astrophysics - Cosmology and Nongalactic Astrophysics, General Relativity and Quantum Cosmology, High Energy Physics - Experiment, Physics - Atomic Physics
Abstract

The detection of variations of fundamental constants of the Standard Model would provide us with compelling evidence of new physics, and could lift the veil on the nature of dark matter and dark energy. In this work, we discuss how a network of atomic and molecular clocks can be used to look for such variations with unprecedented sensitivity over a wide range of time scales. This is precisely the goal of the recently launched QSNET project: A network of clocks for measuring the stability of fundamental constants. QSNET will include state-of-the-art atomic clocks, but will also develop next-generation molecular and highly charged ion clocks with enhanced sensitivity to variations of fundamental constants. We describe the technological and scientific aims of QSNET and evaluate its expected performance. We show that in the range of parameters probed by QSNET, either we will discover new physics, or we will impose new constraints on violations of fundamental symmetries and a range of theories beyond the Standard Model, including dark matter and dark energy models.

Published
2021
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14. Identification of hemodynamically stable patients with acute pulmonary embolism at high risk for death: external validation of different models

Author

Becattini, Cecilia, Gulizia, Michele M., Agnelli, Giancarlo, Dentali, Francesco, Di Lenarda, Andrea, Enea, Iolanda, Fabbri, Andrea, Maggioni, Aldo P., Pomero, Fulvio, Ruggeri, Maria Pia, Lucci, Donata, Vedovati, Maria Cristina, Duranti, Michele, Guercini, Francesco, Groff, Paolo, Verso, Melina, Fabbri, Gianna, Savoia, Martina, Baldini, Ester, Mecatti, Barbara Bartolomei, Bianchini, Francesca, Ceseri, Martina, Gonzini, Lucio, Gorini, Marco, Lorimer, Andrea, Orsini, Giampietro, Tricoli, Martina, Cimini, L.A., Becattini, C., Agnelli, G., Cesarini, V., Sanna, M., Pepe, G., Marchetti, C., Roldan, M. Olivan, Lenzi, L., Cozzio, S., Tomio, P., Diamanti, M., Beltrame, A., Glinski, L., Treleani, M., Coppa, A., Vanni, S., Bartalucci, P., Taccone, A., Costacurta, C., Bortolotti, P., Bortolussi, M., De Vecchi, M., Zanardi, F., Greco, I., Cosentini, R., Gerloni, R., Artusi, N., Cominotto, F., Sisto, U.G., Picariello, C., Roncon, L., Maddalozzo, A., Nitti, C., Riccomi, F., Buzzo, M., Bassanelli, G., Savonitto, S., Bianchi, A., Bilato, C., Lobascio, I., Dalla Valle, C., Pomata, D.P., Giostra, F., Tinuper, A.L., Zalunardo, B., Visonà, A., Panzavolta, C., Novelli, A., Bertini, A., Granai, C., Colombo, S., Periti, E., Bonacchini, L., Abrignani, M.G., Casciolo, M.F., D'Amato, A., Scardovi, A.B., Ricci, R., Iosi, S., Fontana, M.C., Marrazzo, A., Borselli, M., Di Fusco, S.A., Colivicchi, F., Enea, I., Triggiani, M., Papa, I., Pasini, G.F., Fioravanti, C., Panarello, S., Raggi, F., Marzolo, M., Cuppini, S., Milan, M., Barchetti, M., De Laura, D., Caldarola, P., Fiorini, R., Rastelli, G., Ameri, P., La Malfa, G., Cinelli, F., Sganzerla, P.C., Ubaldi, S., Sanchez, F.A., Forgione, C., Cuccia, C., Predieri, S., Fusco, S., Mumoli, N., Porta, C., Romei, M., Lucidi, M., Romaniello, A., Volpe, M., Mogni, P., Pizzolato, E., Martino, G.P., Bitti, G., Righini, G., Bandiera, G., Pennacchio, E., Limauro, S., Dachille, A., Ignone, G., Fuscaldo, G.F., De Rosa, F.M., Vazzana, N., Chesi, G., Di Filippo, F., Pierpaoli, L., Corapi, A., Vatrano, M., Angotti, C., Baccetti, F., Harari, S.A., Luisi, F., Daghini, E., De Curtis, E., Lucà, F., Ciancia, F., Blandizzi, S., Lettica, G.V., D'Orazio, S., Cosmi, F., Zaccaroni, S., Silingardi, M., Valeriano, V., Pugliese, F.R., Murgia, A.P., Parpaglia, P. Pinna, Martinelli, L., Caponi, C., Clemente, M.A., Ciccarone, A., Bongarzoni, A., Garagiola, M., Leone, M.C., Veropalumbo, M.R., Sacco, M., Morella, P., Dorigoni, S., Peterlana, D., Di Paola, R., Felis, S., Correale, M., Brunetti, N.D., Petrelli, G., Feliziani, F.T., Mastroiacovo, D., Romualdi, R., Pasin, F., Bonardi, S., Delfino, P., Scifo, C., Savioli, G., Ceresa, I.F., Galeotalanza, M., Benazzi, B., Porzio, M., Rosini, F., Ancona, C., Verrelli, C., Pasini, A. Fratta, Dalle Carbonare, L., Bozza, N., Nacci, F., Scarabelli, M.A., Amico, F., Marchesi, C., Mazzone, A., Di Tommaso, R., Cocco, F., Pezzuto, G., Luciani, A., Zamboni, P., Muriago, M., Del Pesce, L., Lucarini, A.R., Guglielmelli, E., Vannucchi, V., Moroni, F., Fichera, D., Malatino, L., Sgroi, C., Morana, I.M., Cicero, S., La Rosa, D., Mete, F., Gino, M., De Palma, A., Alessandri, M., Maestripieri, V., Battocchio, M., De Santis, M.T., Saladini, F., Corsi, D.C., Macarone Palmieri, N., Pierfranceschi, M. Giorgi, Palmonari, V., Fontanella, L., Airoldi, L., Bonocore, M., Paliani, U., Prat, L. Iogna, Chiecchi, L., Cuonzo, M., Paludo, A., Padula, D., Antonelli, A., Bicchi, M., Tota, G., Ariello, M., Sai, R., Civita, M., Tucci, M., Barbati, G., Conti, M., Cettina, R., Magnani, O., Levato, M., Gessi, V., De Rui, M., Bellizzi, A., Farneti, L., Salomone, P., Mannarini, A., Grifoni, E., Del Ghianda, S., Campodonico, J., De Cesare, N., Mutone, D., Pasoli, P., Meloni, S., Frenda, A., Viola, G., Torromeo, C., Campana, C., Pistone, M.C., Caravita, S., La Creta, C.P., Miscio, F., Loreno, M., Fenu, P., Mazzetti, M., Rossini, D., Brunacci, M., Capuano, A., Tagliamonte, G., Pinelli, M., Ballocca, F., Parca, G., Pasini, S.M., Maragno, M.G., Vecchi, F., Mancinelli, L., Cavalli, A., Di Mare, F., Conficoni, E., Miceli, R., Pecoraro, R., Fonti, C., Pegoraro, S., Piccinni, G.C., Caruso, G., Boriani, G., Lanzillotta, P., Piccolo, P., Calò, L., Stolfo, D., Mangiacapra, S., Marziali, A., Volponi, M.C., Querci, G., Terribile, R., Menabue, M., Fiorentini, A., Musci, R.L., Uras, S., Cicini, M.P., Manetti, S., Francese, G.M., Melchio, R., Scorpiglione, N., Carrara, D., Pani, A., Morisco, C., Rodolico, M., Colombo, Silvia, Vanni, Simone, Abrignani, Maurizio Giuseppe, Scardovi, Angela Beatrice, Marrazzo, Alessandra, Borselli, Matteo, Barchetti, Marco, and Maggioni, Aldo Pietro

Published
2024
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15. Broad-area-search of new construction using time series analysis of Landsat and Sentinel-2 data

Author

Xiaojing Tang, Madison G. Barrett, Kangjoon Cho, Kelsee H. Bratley, Katelyn Tarrio, Yingtong Zhang, Hanfeng Gu, Peter Rasmussen, Marc Bosch, and Curtis E. Woodcock

Subjects
Landsat, Time series, LSMA, Construction, GEE, Physical geography, GB3-5030, Science
Abstract

New construction activities can alter surface albedo and structure, which then affect surface temperature and roughness, and hence have a significant impact on urban climate. Construction activity is also an important indicator of human development and movement and is of high interest to the intelligence community. A new approach for Broad-Area-Search of New Construction activities (BASC) by combining time series analysis and rule-based filters using Landsat data was developed and tested in five selected cities (Boston, Shanghai, São Paulo, Dubai, and Ho Chi Minh City). The algorithm transforms Landsat images into fractions of a set of four endmembers using Linear Spectral Mixture Analysis (LSMA) and then applies the Continuous Change Detection and Classification (CCDC) algorithm for change detection. A set of rule-based filters and spatial processing was then applied to narrow the search to changes related to construction activities. Overall, BASC reached a recall of 0.83, a precision of 0.58, and an F1-Score of 0.68. Among the five cities, Dubai had the highest recall of 1.0 and the highest F1-score of 0.75, while Boston had the highest precision of 0.63. BASC performed worst in Shanghai with an F1-Score of 0.6, mainly due to it having the lowest recall of 0.62, while São Paulo has the lowest precision of 0.5. Common sources of omission errors include low-density, redevelopment, and small sites, while common commission errors include roofing, land clearing, water level changes, and re-surfacing projects. For comparison, BASC using Sentinel-2 Top-of-Atmosphere (TOA) Reflectance data recorded an overall F1-Score of 0.63, but with higher recall and lower precision. Integration of Sentinel-2 Surface Reflectance and Sentinel-1 SAR data has the potential to further improve the performance of BASC. The new algorithm provided a method for routine monitoring of construction activities over large areas. The result of such monitoring can be used as a baseline to narrow down the candidate targets of construction activities, where very high-resolution imagery can then be requested to perform further examination.

Published
2024
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18. A global land cover training dataset from 1984 to 2020

Author

Radost Stanimirova, Katelyn Tarrio, Konrad Turlej, Kristina McAvoy, Sophia Stonebrook, Kai-Ting Hu, Paulo Arévalo, Eric L. Bullock, Yingtong Zhang, Curtis E. Woodcock, Pontus Olofsson, Zhe Zhu, Christopher P. Barber, Carlos M. Souza, Shijuan Chen, Jonathan A. Wang, Foster Mensah, Marco Calderón-Loor, Michalis Hadjikakou, Brett A. Bryan, Jordan Graesser, Dereje L. Beyene, Brian Mutasha, Sylvester Siame, Abel Siampale, and Mark A. Friedl

Subjects
Science
Abstract

Abstract State-of-the-art cloud computing platforms such as Google Earth Engine (GEE) enable regional-to-global land cover and land cover change mapping with machine learning algorithms. However, collection of high-quality training data, which is necessary for accurate land cover mapping, remains costly and labor-intensive. To address this need, we created a global database of nearly 2 million training units spanning the period from 1984 to 2020 for seven primary and nine secondary land cover classes. Our training data collection approach leveraged GEE and machine learning algorithms to ensure data quality and biogeographic representation. We sampled the spectral-temporal feature space from Landsat imagery to efficiently allocate training data across global ecoregions and incorporated publicly available and collaborator-provided datasets to our database. To reflect the underlying regional class distribution and post-disturbance landscapes, we strategically augmented the database. We used a machine learning-based cross-validation procedure to remove potentially mis-labeled training units. Our training database is relevant for a wide array of studies such as land cover change, agriculture, forestry, hydrology, urban development, among many others.

Published
2023
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21. High-Fidelity Bell-State Preparation with $^{40}$Ca$^+$ Optical Qubits

Author

Clark, Craig R., Tinkey, Holly N., Sawyer, Brian C., Meier, Adam M., Burkhardt, Karl A., Seck, Christopher M., Shappert, Christopher M., Guise, Nicholas D., Volin, Curtis E., Fallek, Spencer D., Hayden, Harley T., Rellergert, Wade G., and Brown, Kenton R.

Subjects
Quantum Physics, Physics - Atomic Physics
Abstract

Entanglement generation in trapped-ion systems has relied thus far on two distinct but related geometric phase gate techniques: Molmer-Sorensen and light-shift gates. We recently proposed a variant of the light-shift scheme where the qubit levels are separated by an optical frequency [B. C. Sawyer and K. R. Brown, Phys. Rev. A 103, 022427 (2021)]. Here we report an experimental demonstration of this entangling gate using a pair of $^{40}$Ca$^+$ ions in a cryogenic surface-electrode ion trap and a commercial, high-power, 532 nm Nd:YAG laser. Generating a Bell state in 35 $\mu$s, we directly measure an infidelity of $6(3) \times 10^{-4}$ without subtraction of experimental errors. The 532 nm gate laser wavelength suppresses intrinsic photon scattering error to $\sim 1 \times 10^{-5}$., Comment: 7 pages, 6 figures, should match published version

Published
2021
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22. Child Opportunity Index and Pediatric Intensive Care Outcomes: A Multicenter Retrospective Study in the United States*

Author

McCrory, Michael C., Akande, Manzilat, Slain, Katherine N., Kennedy, Curtis E., Winter, Meredith C., Stottlemyre, Morgan G., Wakeham, Martin K., Barnack, Kyle A., Huang, Jia Xin, Sharma, Meesha, Zurca, Adrian D., Pinto, Neethi P., Dziorny, Adam C., Maddux, Aline B., Garg, Anjali, Woodruff, Alan G., Hartman, Mary E., Timmons, Otwell D., Heidersbach, R. Scott, Cisco, Michael J., Sochet, Anthony A., Wells, Brian J., Halvorson, Elizabeth E., and Saha, Amit K.

Published
2024
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32. Need and vision for global medium-resolution Landsat and Sentinel-2 data products

Author

Radeloff, Volker C., Roy, David P., Wulder, Michael A., Anderson, Martha, Cook, Bruce, Crawford, Christopher J., Friedl, Mark, Gao, Feng, Gorelick, Noel, Hansen, Matthew, Healey, Sean, Hostert, Patrick, Hulley, Glynn, Huntington, Justin L., Johnson, David M., Neigh, Chris, Lyapustin, Alexei, Lymburner, Leo, Pahlevan, Nima, Pekel, Jean-Francois, Scambos, Theodore A., Schaaf, Crystal, Strobl, Peter, Woodcock, Curtis E., Zhang, Hankui K., and Zhu, Zhe

Published
2024
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33. Natural language processing augments comorbidity documentation in neurosurgical inpatient admissions.

Author

Rahul A Sastry, Aayush Setty, David D Liu, Bryan Zheng, Rohaid Ali, Robert J Weil, G Dean Roye, Curtis E Doberstein, Adetokunbo A Oyelese, Tianyi Niu, Ziya L Gokaslan, and Albert E Telfeian

Subjects
Medicine, Science
Abstract

ObjectiveTo establish whether or not a natural language processing technique could identify two common inpatient neurosurgical comorbidities using only text reports of inpatient head imaging.Materials and methodsA training and testing dataset of reports of 979 CT or MRI scans of the brain for patients admitted to the neurosurgery service of a single hospital in June 2021 or to the Emergency Department between July 1-8, 2021, was identified. A variety of machine learning and deep learning algorithms utilizing natural language processing were trained on the training set (84% of the total cohort) and tested on the remaining images. A subset comparison cohort (n = 76) was then assessed to compare output of the best algorithm against real-life inpatient documentation.ResultsFor "brain compression", a random forest classifier outperformed other candidate algorithms with an accuracy of 0.81 and area under the curve of 0.90 in the testing dataset. For "brain edema", a random forest classifier again outperformed other candidate algorithms with an accuracy of 0.92 and AUC of 0.94 in the testing dataset. In the provider comparison dataset, for "brain compression," the random forest algorithm demonstrated better accuracy (0.76 vs 0.70) and sensitivity (0.73 vs 0.43) than provider documentation. For "brain edema," the algorithm again demonstrated better accuracy (0.92 vs 0.84) and AUC (0.45 vs 0.09) than provider documentation.DiscussionA natural language processing-based machine learning algorithm can reliably and reproducibly identify selected common neurosurgical comorbidities from radiology reports.ConclusionThis result may justify the use of machine learning-based decision support to augment provider documentation.

Published
2024
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34. A global land cover training dataset from 1984 to 2020

Author

Stanimirova, Radost, Tarrio, Katelyn, Turlej, Konrad, McAvoy, Kristina, Stonebrook, Sophia, Hu, Kai-Ting, Arévalo, Paulo, Bullock, Eric L., Zhang, Yingtong, Woodcock, Curtis E., Olofsson, Pontus, Zhu, Zhe, Barber, Christopher P., Souza, Jr., Carlos M., Chen, Shijuan, Wang, Jonathan A., Mensah, Foster, Calderón-Loor, Marco, Hadjikakou, Michalis, Bryan, Brett A., Graesser, Jordan, Beyene, Dereje L., Mutasha, Brian, Siame, Sylvester, Siampale, Abel, and Friedl, Mark A.

Published
2023
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38. Words Matter: A Qualitative Content Analysis of Campus Crime Alerts and Considerations for Best Practices

Author

Wesely, Jennifer K., Brown, Elizabeth R., and Phills, Curtis E.

Abstract

Objective: An impediment to an informed discussion of the impact that campus crime alerts have on college campuses is the dearth of research on the topic. This study explores the composition of campus crime alerts and the ways they convey and (re)produce meanings concerning victimization, perpetration, responsibility, and consent. Methods: This study uses an qualitative content analysis of a sample of 3,702 campus crime alerts from 55 universities in the United States. Results: Three themes (Central Actor, Overgendering, and Gratuitous Content) emerge. When the victim is portrayed as the alert subject using a passive voice and the crime is framed within a gendered, editorialized narrative, the alert focus shifts to the victim's rather than the perpetrator's identity and behaviors. Conclusions: The wording of alerts may compromise the safety of the campus community by reinforcing misguided expectations for behavior and shaping misleading perceptions of risk; considerations for best practices are explored.

Published
2022
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39. Single-ion addressing via trap potential modulation in global optical fields

Author

Seck, Christopher M., Meier, Adam M., Merrill, J. True, Hayden, Harley T., Sawyer, Brian C., Volin, Curtis E., and Brown, Kenton R.

Subjects
Quantum Physics, Physics - Atomic Physics
Abstract

To date, individual addressing of ion qubits has relied primarily on local Rabi or transition frequency differences between ions created via electromagnetic field spatial gradients or via ion transport operations. Alternatively, it is possible to synthesize arbitrary local one-qubit gates by leveraging local phase differences in a global driving field. Here we report individual addressing of $^{40}$Ca$^+$ ions in a two-ion crystal using axial potential modulation in a global gate laser field. We characterize the resulting gate performance via one-qubit randomized benchmarking, applying different random sequences to each co-trapped ion. We identify the primary error sources and compare the results with single-ion experiments to better understand our experimental limitations. These experiments form a foundation for the universal control of two ions, confined in the same potential well, with a single gate laser beam., Comment: 27 pages, 3 figures

Published
2019
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41. Search for transient variations of the fine structure constant and dark matter using fiber-linked optical atomic clocks

Author

Roberts, B. M., Delva, P., Al-Masoudi, A., Amy-Klein, A., Bærentsen, C., Baynham, C. F. A., Benkler, E., Bilicki, S., Bize, S., Bowden, W., Calvert, J., Cambier, V., Cantin, E., Curtis, E. A., Dörscher, S., Favier, M., Frank, F., Gill, P., Godun, R. M., Grosche, G., Guo, C., Hees, A., Hill, I. R., Hobson, R., Huntemann, N., Kronjäger, J., Koke, S., Kuhl, A., Lange, R., Legero, T., Lipphardt, B., Lisdat, C., Lodewyck, J., Lopez, O., Margolis, H. S., Álvarez-Martínez, H., Meynadier, F., Ozimek, F., Peik, E., Pottie, P. -E., Quintin, N., Sanner, C., De Sarlo, L., Schioppo, M., Schwarz, R., Silva, A., Sterr, U., Tamm, Chr., Targat, R. Le, Tuckey, P., Vallet, G., Waterholter, T., Xu, D., and Wolf, P.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, High Energy Physics - Phenomenology, Physics - Atomic Physics
Abstract

We search for transient variations of the fine structure constant using data from a European network of fiber-linked optical atomic clocks. By searching for coherent variations in the recorded clock frequency comparisons across the network, we significantly improve the constraints on transient variations of the fine structure constant. For example, we constrain the variation in alpha to <5*10^-17 for transients of duration 10^3 s. This analysis also presents a possibility to search for dark matter, the mysterious substance hypothesised to explain galaxy dynamics and other astrophysical phenomena that is thought to dominate the matter density of the universe. At the current sensitivity level, we find no evidence for dark matter in the form of topological defects (or, more generally, any macroscopic objects), and we thus place constraints on certain potential couplings between the dark matter and standard model particles, substantially improving upon the existing constraints, particularly for large (>~10^4 km) objects.

Published
2019
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