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1. The EMC Effect of Tritium and Helium-3 from the JLab MARATHON Experiment

Author

Abrams, D., Albataineh, H., Aljawrneh, B. S., Alsalmi, S., Androic, D., Aniol, K., Armstrong, W., Arrington, J., Atac, H., Averett, T., Gayoso, C. Ayerbe, Bai, X., Bane, J., Barcus, S., Beck, A., Bellini, V., Bhatt, H., Bhetuwal, D., Biswas, D., Blyth, D., Boeglin, W., Bulumulla, D., Butler, J., Camsonne, A., Carmignotto, M., Castellanos, J., Chen, J. -P., Cloët, I. C., Cohen, E. O., Covrig, S., Craycraft, K., Cruz-Torres, R., Dongwi, B., Duran, B., Dutta, D., Fomin, N., Fuchey, E., Gal, C., Gautam, T. N., Gilad, S., Gnanvo, K., Gogami, T., Gomez, J., Gu, C., Habarakada, A., Hague, T., Hansen, J. -O., Hattawy, M., Hauenstein, F., Higinbotham, D. W., Holt, R. J., Hughes, E. W., Hyde, C., Ibrahim, H., Jian, S., Joosten, S., Karki, A., Karki, B., Katramatou, A. T., Keith, C., Keppel, C., Khachatryan, M., Khachatryan, V., Khanal, A., Kievsky, A., King, D., King, P. M., Korover, I., Kulagin, S. A., Kumar, K. S., Kutz, T., Lashley-Colthirst, N., Li, S., Li, W., Liu, H., Liuti, S., Liyanage, N., Markowitz, P., McClellan, R. E., Meekins, D., Beck, S. Mey-Tal, Meziani, Z. -E., Michaels, R., Mihovilovic, M., Nelyubin, V., Nguyen, D., Nuruzzaman, Nycz, M., Obrecht, R., Olson, M., Owen, V. F., Pace, E., Pandey, B., Pandey, V., Paolone, M., Papadopoulou, A., Park, S., Paul, S., Petratos, G. G., Petti, R., Piasetzky, E., Pomatsalyuk, R., Premathilake, S., Puckett, A. J. R., Punjabi, V., Ransome, R. D., Rashad, M. N. H., Reimer, P. E., Riordan, S., Roche, J., Salmè, G., Santiesteban, N., Sawatzky, B., Scopetta, S., Schmidt, A., Schmookler, B., Segal, J., Segarra, E. P., Shahinyan, A., Širca, S., Sparveris, N., Su, T., Suleiman, R., Szumila-Vance, H., Tadepalli, A. S., Tang, L., Tireman, W., Tortorici, F., Urciuoli, G. M., Wojtsekhowski, B., Wood, S., Ye, Z. H., Ye, Z. Y., and Zhang, J.

Subjects
Nuclear Experiment
Abstract

Measurements of the EMC effect in the tritium and helium-3 mirror nuclei are reported. The data were obtained by the MARATHON Jefferson Lab experiment, which performed deep inelastic electron scattering from deuterium and the three-body nuclei, using a cryogenic gas target system and the High Resolution Spectrometers of the Hall A Facility of the Lab. The data cover the Bjorken $x$ range from 0.20 to 0.83, corresponding to a squared four-momentum transfer $Q^2$ range from 2.7 to $11.9\gevsq$, and to an invariant mass $W$ of the final hadronic state greater than 1.84 GeV/${\it c}^2$. The tritium EMC effect measurement is the first of its kind. The MARATHON experimental results are compared to results from previous measurements by DESY-HERMES and JLab-Hall C experiments, as well as with few-body theoretical predictions., Comment: arXiv admin note: text overlap with arXiv:2104.05850

Published
2024

2. LEGO: QEC Decoding System Architecture for Dynamic Circuits

Author

Wu, Yue, Liyanage, Namitha, and Zhong, Lin

Subjects
Quantum Physics, Electrical Engineering and Systems Science - Systems and Control
Abstract

Quantum error correction (QEC) is a critical component of FTQC; the QEC decoder is an important part of Classical Computing for Quantum or C4Q. Recent years have seen fast development in real-time QEC decoders. Existing efforts to build real-time decoders have yet to achieve a critical milestone: decoding dynamic logical circuits with error-corrected readout and feed forward. Achieving this requires significant engineering effort to adapt and reconfigure the decoders during runtime, depending on the branching of the logical circuit. We present a QEC decoder architecture called LEGO, with the ambitious goal of supporting dynamic logical operations. LEGO employs a novel abstraction called the decoding block to describe the decoding problem of a dynamic logical circuit. Moreover, decoding blocks can be combined with three other ideas to improve the efficiency, accuracy and latency of the decoder. First, they provide data and task parallelisms when combined with fusion-based decoding. Second, they can exploit the pipeline parallelism inside multi-stage decoders. Finally, they serve as basic units of work for computational resource management. Using decoding blocks, LEGO can be easily reconfigured to support all QEC settings and to easily accommodate innovations in three interdependent fields: code, logical operations and qubit hardware. In contrast, existing decoders are highly specialized to a specific QEC setting, which leads to redundant research and engineering efforts, slows down innovation, and further fragments the nascent quantum computing industry.

Published
2024

3. Energy Dissipation in Hilbert Envelopes on Motion Waveforms Detected in Vibrating Systems: An Axiomatic Approach

Author

Peters, James F. and Liyanage, Tharaka U.

Subjects
Physics - General Physics, 74H80, 76F20, 93A05
Abstract

This paper introduces an axiomatic approach in the theory of energy dissipation in Hilbert envelopes on waveforms emanating from various vibrating systems. A Hilbert envelope is a curve tangent to peak points on a motion waveform. The basic approach is to compare non-modulated vs. modulated waveforms in measuring energy loss during the vibratory motion $m(t)$ at time $t$ of moving object such as a walker, runner or biker recorded in a video. Modulation of $m(t)$ is achieved by using Mersenne primes to adjust the frequency $\omega$ of the Euler exponential in $m(t)e^{\pm j2\pi \omega t}{\rm d}t$. Expediture of energy $E_{m(t)}$ by a system is measured in terms of the area bounded by the motion $m(t)$ waveform at time $t$., Comment: 12 pages, 6 figures

Published
2024

4. New Measurements of the Deuteron to Proton F2 Structure Function Ratio

Author

Biswas, Debaditya, Gonzalez, Fernando Araiza, Henry, William, Karki, Abishek, Morean, Casey, Nadeeshani, Sooriyaarachchilage, Sun, Abel, Abrams, Daniel, Ahmed, Zafar, Aljawrneh, Bashar, Alsalmi, Sheren, Ambrose, George, Armstrong, Whitney, Asaturyan, Arshak, Assumin-Gyimah, Kofi, Gayoso, Carlos Ayerbe, Bandari, Anashe, Basnet, Samip, Berdnikov, Vladimir, Bhatt, Hem, Bhetuwal, Deepak, Boeglin, Werner, Bosted, Peter, Brash, Edward, Bukhari, Masroor, Chen, Haoyu, Chen, Jian-Ping, Chen, Mingyu, Christy, Michael Eric, Dusa, Silviu Covrig, Craycraft, Kayla, Danagoulian, Samuel, Day, Donal, Diefenthaler, Markus, Dlamini, Mongi, Dunne, James, Duran, Burcu, Dutta, Dipangkar, Ent, Rolf, Evans, Rory, Fenker, Howard, Fomin, Nadia, Fuchey, Eric, Gaskell, David, Gautam, Thir Narayan, Hansen, Jens-Ole, Hauenstein, Florian, Hernandez, A., Horn, Tanja, Huber, Garth, Jones, Mark, Joosten, Sylvester, Kabir, Md Latiful, Keppel, Cynthia, Khanal, Achyut, King, Paul, Kinney, Edward, Kohl, Michael, Lashley-Colthirst, Nathaniel, Li, Shujie, Li, Wenliang, Liyanage, Anusha Habarakada, Mack, David, Malace, Simona, Markowitz, Pete, Matter, John, Meekins, David, Michaels, Robert, Mkrtchyan, Arthur, Mkrtchyan, Hamlet, Moore, Zae, Nazeer, S. J., Nanda, Shirsendu, Niculescu, Gabriel, Niculescu, Maria, Nguyen, Huong, Nuruzzaman, Nuruzzaman, Pandey, Bishnu, Park, Sanghwa, Pooser, Eric, Puckett, Andrew, Rehfuss, Melanie, Reinhold, Joerg, Sawatzky, Bradley, Smith, G., Szumila-Vance, Holly, Tadepalli, Arun, Tadevosyan, Vardan, Trotta, Richard, Wood, Stephen, Yero, Carlos, and Zhang, Jinlong

Subjects
High Energy Physics - Experiment
Abstract

Nucleon structure functions, as measured in lepton-nucleon scattering, have historically provided a critical observable in the study of partonic dynamics within the nucleon. However, at very large parton momenta it is both experimentally and theoretically challenging to extract parton distributions due to the probable onset of non-perturbative contributions and the unavailability of high precision data at critical kinematics. Extraction of the neutron structure and the d-quark distribution have been further challenging due to the necessity of applying nuclear corrections when utilizing scattering data from a deuteron target to extract free neutron structure. However, a program of experiments has been carried out recently at the energy-upgraded Jefferson Lab electron accelerator aimed at significantly reducing the nuclear correction uncertainties on the d-quark distribution function at large partonic momentum. This allows leveraging the vast body of deuterium data covering a large kinematic range to be utilized for d-quark parton distribution function extraction. We present new data from experiment E12-10-002 carried out in Jefferson Lab Hall C on the deuteron to proton cross-section ratio at large BJorken-x. These results significantly improve the precision of existing data, and provide a first look at the expected impact on quark distributions extracted from global parton distribution function fits.

Published
2024

5. Pion electroproduction measurements in the nucleon resonance region

Author

Li, R., Sparveris, N., Atac, H., Jones, M. K., Paolone, M., Akbar, Z., Ali, M., Gayoso, C. Ayerbe, Berdnikov, V., Biswas, D., Boer, M., Camsonne, A., Chen, J. -P., Diefenthaler, M., Duran, B., Dutta, D., Gaskell, D., Hansen, O., Hauenstein, F., Heinrich, N., Henry, W., Horn, T., Huber, G. M., Jia, S., Joosten, S., Karki, A., Kay, S. J. D., Kumar, V., Li, X., Li, W. B., Liyanage, A. H., Mack, D., Malace, S., Markowitz, P., McCaughan, M., Meziani, Z. -E., Mkrtchyan, H., Morean, C., Muhoza, M., Narayan, A., Pasquini, B., Rehfuss, M., Sawatzky, B., Smith, G. R., Smith, A., Trotta, R., Yero, C., Zheng, X., and Zhou, J.

Subjects
Nuclear Experiment, Nuclear Theory
Abstract

We report new pion electroproduction measurements in the $\Delta(1232)$ resonance, utilizing the SHMS - HMS magnetic spectrometers of Hall C at Jefferson Lab. The data focus on a region that exhibits a strong and rapidly changing interplay of the mesonic cloud and quark-gluon dynamics in the nucleon. The results are in reasonable agreement with models that employ pion cloud effects and chiral effective field theory calculations, but at the same time they suggest that an improvement is required to the theoretical calculations and provide valuable input that will allow their refinements. The data illustrate the potential of the magnetic spectrometers setup in Hall C towards the study the $\Delta(1232)$ resonance. These first reported results will be followed by a series of measurements in Hall C, that will expand the studies of the $\Delta(1232)$ resonance offering a high precision insight within a wide kinematic range from low to high momentum transfers.

Published
2024
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6. LIGO Detector Characterization in the first half of the fourth Observing run

Author

Soni, S., Berger, B. K., Davis, D., Renzo, F. Di., Effler, A., Ferreira, T. A., Glanzer, J., Goetz, E., González, G., Helmling-Cornell, A., Hughey, B., Huxford, R., Mannix, B., Mo, G., Nandi, D., Neunzert, A., Nichols, S., Pham, K., Renzini, A. I., Schofield, R. M. S., Stuver, A, Trevor, M., Álvarez-López, S., Beda, R., Berry, C. P. L., Bhuiyan, S., Bruntz, R., Christensen, N., Blagg, L., Chan, M., Charlton, P., Connolly, G., Dhatri, R., Ding, J., Garg, V., Holley-Bockelmann, K., Hourihane, S., Jani, K., Janssens, K., Jarov, S., Knee, A. M., Lattal, A., Lecoeuche, Y., Littenberg, T., Liyanage, A., Lott, B., Macas, R., Malakar, D., McGowan, K., McIver, J., Millhouse, M., Nuttall, L., Nykamp, D., Ota, I., Rawcliffe, C., Scully, B., Tasson, J., Tejera, A., Thiele, S., Udall, R., Winborn, C., Yarbrough, Z., Zhang, Z., Abbott, R., Abouelfettouh, I., Adhikari, R. X., Ananyeva, A., Appert, S., Arai, K., Aritomi, N., Aston, S. M., Ball, M., Ballmer, S. W., Barker, D., Barsotti, L., Betzwieser, J., Billingsley, G., Biscans, S., Bode, N., Bonilla, E., Bossilkov, V., Branch, A., Brooks, A. F., Brown, D. D., Bryant, J., Cahillane, C., Cao, H., Capote, E., Clara, F., Collins, J., Compton, C. M., Cottingham, R., Coyne, D. C., Crouch, R., Csizmazia, J., Cullen, T. J., Dartez, L. P., Demos, N., Dohmen, E., Driggers, J. C., Dwyer, S. E., Ejlli, A., Etzel, T., Evans, M., Feicht, J., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fulda, P., Fyffe, M., Ganapathy, D., Gateley, B., Giaime, J. A., Giardina, K. D., Goetz, R., Goodwin-Jones, A. W., Gras, S., Gray, C., Griffith, D., Grote, H., Guidry, T., Hall, E. D., Hanks, J., Hanson, J., Heintze, M. C., Holland, N. A., Hoyland, D., Huang, H. Y., Inoue, Y., James, A. L., Jennings, A., Jia, W., Karat, S., Karki, S., Kasprzack, M., Kawabe, K., Kijbunchoo, N., King, P. J., Kissel, J. S., Komori, K., Kontos, A., Kumar, Rahul, Kuns, K., Landry, M., Lantz, B., Laxen, M., Lee, K., Lesovsky, M., Llamas, F., Lormand, M., Loughlin, H. A., MacInnis, M., Makarem, C. N., Mansell, G. L., Martin, R. M., Mason, K., Matichard, F., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McRae, T., Mera, F., Merilh, E. L., Meylahn, F., Mittleman, R., Moraru, D., Moreno, G., Mullavey, A., Nakano, M., Nelson, T. J. N., Notte, J., Oberling, J., O'Hanlon, T., Osthelder, C., Ottaway, D. J., Overmier, H., Parker, W., Pele, A., Pham, H., Pirello, M., Quetschke, V., Ramirez, K. E., Reyes, J., Richardson, J. W., Robinson, M., Rollins, J. G., Romel, C. L., Romie, J. H., Ross, M. P., Ryan, K., Sadecki, T., Sanchez, A., Sanchez, E. J., Sanchez, L. E., Savage, R. L., Schaetzl, D., Schiworski, M. G., Schnabel, R., Schwartz, E., Sellers, D., Shaffer, T., Short, R. W., Sigg, D., Slagmolen, B. J. J., Soike, C., Srivastava, V., Sun, L., Tanner, D. B., Thomas, M., Thomas, P., Thorne, K. A., Torrie, C. I., Traylor, G., Ubhi, A. S., Vajente, G., Vanosky, J., Vecchio, A., Veitch, P. J., Vibhute, A. M., von Reis, E. R. G., Warner, J., Weaver, B., Weiss, R., Whittle, C., Willke, B., Wipf, C. C., Xu, V. A., Yamamoto, H., Zhang, L., and Zucker, M. E.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, General Relativity and Quantum Cosmology
Abstract

Progress in gravitational-wave astronomy depends upon having sensitive detectors with good data quality. Since the end of the LIGO-Virgo-KAGRA third Observing run in March 2020, detector-characterization efforts have lead to increased sensitivity of the detectors, swifter validation of gravitational-wave candidates and improved tools used for data-quality products. In this article, we discuss these efforts in detail and their impact on our ability to detect and study gravitational-waves. These include the multiple instrumental investigations that led to reduction in transient noise, along with the work to improve software tools used to examine the detectors data-quality. We end with a brief discussion on the role and requirements of detector characterization as the sensitivity of our detectors further improves in the future Observing runs., Comment: 35 pages, 18 figures

Published
2024

7. SoK: Identifying Limitations and Bridging Gaps of Cybersecurity Capability Maturity Models (CCMMs)

Author

Liyanage, Lasini, Arachchilage, Nalin Asanka Gamagedara, and Russello, Giovanni

Subjects
Computer Science - Cryptography and Security
Abstract

In the rapidly evolving digital landscape, where organisations are increasingly vulnerable to cybersecurity threats, Cybersecurity Capability Maturity Models (CCMMs) emerge as pivotal tools in enhancing organisational cybersecurity posture. CCMMs provide a structured framework to guide organisations in assessing their current cybersecurity capabilities, identifying critical gaps, and prioritising improvements. However, the full potential of CCMMs is often not realised due to inherent limitations within the models and challenges encountered during their implementation and adoption processes. These limitations and challenges can significantly hamper the efficacy of CCMMs in improving cybersecurity. As a result, organisations remain vulnerable to cyber threats as they may fail to identify and address critical security gaps, implement necessary improvements or allocate resources effectively. To address these limitations and challenges, conducting a thorough investigation into existing models is essential. Therefore, we conducted a Systematic Literature Review (SLR) analysing 43 publications to identify existing CCMMs, their limitations, and the challenges organisations face when implementing and adopting them. By understanding these barriers, we aim to explore avenues for enhancing the efficacy of CCMMs, ensuring they more effectively meet the cybersecurity needs of organisational entities.

Published
2024

8. Inhibition of lysine acetyltransferase KAT6 in ER+HER2- metastatic breast cancer: a phase 1 trial.

Author

Mukohara, Toru, Park, Yeon, Sommerhalder, David, Yonemori, Kan, Hamilton, Erika, Kim, Sung-Bae, Kim, Jee, Iwata, Hiroji, Yamashita, Toshinari, Layman, Rachel, Mita, Monica, Clay, Timothy, Chae, Yee, Oakman, Catherine, Yan, Fengting, Kim, Gun, Im, Seock-Ah, Lindeman, Geoffrey, Rugo, Hope, Liyanage, Marlon, Saul, Michelle, Le Corre, Christophe, Skoura, Athanasia, Liu, Li, Li, Meng, and LoRusso, Patricia

Subjects
Humans, Female, Breast Neoplasms, Histone Acetyltransferases, Middle Aged, Receptor, ErbB-2, Receptors, Estrogen, Fulvestrant, Aged, Adult, Neoplasm Metastasis, Antineoplastic Combined Chemotherapy Protocols
Abstract

Inhibition of histone lysine acetyltransferases (KATs) KAT6A and KAT6B has shown antitumor activity in estrogen receptor-positive (ER+) breast cancer preclinical models. PF-07248144 is a selective catalytic inhibitor of KAT6A and KAT6B. In the present study, we report the safety, pharmacokinetics (PK), pharmacodynamics, efficacy and biomarker results from the first-in-human, phase 1 dose escalation and dose expansion study (n = 107) of PF-07248144 monotherapy and fulvestrant combination in heavily pretreated ER+ human epidermal growth factor receptor-negative (HER2-) metastatic breast cancer (mBC). The primary objectives of assessing the safety and tolerability and determining the recommended dose for expansion of PF-07248144, as monotherapy and in combination with fulvestrant, were met. Secondary endpoints included characterization of PK and evaluation of antitumor activity, including objective response rate (ORR) and progression-free survival (PFS). Common treatment-related adverse events (any grade; grades 3-4) included dysgeusia (83.2%, 0%), neutropenia (59.8%, 35.5%) and anemia (48.6%, 13.1%). Exposure was approximately dose proportional. Antitumor activity was observed as monotherapy. For the PF-07248144-fulvestrant combination (n = 43), the ORR (95% confidence interval (CI)) was 30.2% (95% CI = 17.2-46.1%) and the median PFS was 10.7 (5.3-not evaluable) months. PF-07248144 demonstrated a tolerable safety profile and durable antitumor activity in heavily pretreated ER+HER2- mBC. These findings establish KAT6A and KAT6B as druggable cancer targets, provide clinical proof of concept and reveal a potential avenue to treat mBC. clinicaltrial.gov registration: NCT04606446 .

Published
2024

9. LiverUSRecon: Automatic 3D Reconstruction and Volumetry of the Liver with a Few Partial Ultrasound Scans

Author

Sivayogaraj, Kaushalya, Guruge, Sahan T., Liyanage, Udari, Udupihille, Jeevani, Jayasinghe, Saroj, Fernando, Gerard, Rodrigo, Ranga, and Liyanaarachchi, M. Rukshani

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

3D reconstruction of the liver for volumetry is important for qualitative analysis and disease diagnosis. Liver volumetry using ultrasound (US) scans, although advantageous due to less acquisition time and safety, is challenging due to the inherent noisiness in US scans, blurry boundaries, and partial liver visibility. We address these challenges by using the segmentation masks of a few incomplete sagittal-plane US scans of the liver in conjunction with a statistical shape model (SSM) built using a set of CT scans of the liver. We compute the shape parameters needed to warp this canonical SSM to fit the US scans through a parametric regression network. The resulting 3D liver reconstruction is accurate and leads to automatic liver volume calculation. We evaluate the accuracy of the estimated liver volumes with respect to CT segmentation volumes using RMSE. Our volume computation is statistically much closer to the volume estimated using CT scans than the volume computed using Childs' method by radiologists: p-value of 0.094 (>0.05) says that there is no significant difference between CT segmentation volumes and ours in contrast to Childs' method. We validate our method using investigations (ablation studies) on the US image resolution, the number of CT scans used for SSM, the number of principal components, and the number of input US scans. To the best of our knowledge, this is the first automatic liver volumetry system using a few incomplete US scans given a set of CT scans of livers for SSM., Comment: 10 pages, Accepted to MICCAI 2024

Published
2024

10. Uncovering the origin of interface stress enhancement and compressive-to-tensile stress transition in immiscible nanomultilayers

Author

Hu, Yang, Lorenzin, Giacomo, Yeom, Jeyun, Liyanage, Manura, Curtin, William A., Jeurgens, Lars P. H., Janczak-Rusch, Jolanta, Cancellieri, Claudia, and Turlo, Vladyslav

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

The intrinsic stress in nanomultilayers (NMLs) is typically dominated by interface stress, which is particularly high in immiscible Cu/W NMLs. Here, atomistic simulations with a chemically-accurate neural network potential reveal the role of interfacial intermixing and metastable phase formation on the interface stress levels. These results rationalize an experimentally-reported compressive- to-tensile transition as a function of NML deposition conditions and the extremely high interface stresses under some conditions.

Published
2024

11. ChatGPT as Research Scientist: Probing GPT's Capabilities as a Research Librarian, Research Ethicist, Data Generator and Data Predictor

Author

Lehr, Steven A., Caliskan, Aylin, Liyanage, Suneragiri, and Banaji, Mahzarin R.

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Computers and Society, Computer Science - Information Retrieval, Computer Science - Machine Learning, I.2.7, K.4.0, K.4.1, K.4.2
Abstract

How good a research scientist is ChatGPT? We systematically probed the capabilities of GPT-3.5 and GPT-4 across four central components of the scientific process: as a Research Librarian, Research Ethicist, Data Generator, and Novel Data Predictor, using psychological science as a testing field. In Study 1 (Research Librarian), unlike human researchers, GPT-3.5 and GPT-4 hallucinated, authoritatively generating fictional references 36.0% and 5.4% of the time, respectively, although GPT-4 exhibited an evolving capacity to acknowledge its fictions. In Study 2 (Research Ethicist), GPT-4 (though not GPT-3.5) proved capable of detecting violations like p-hacking in fictional research protocols, correcting 88.6% of blatantly presented issues, and 72.6% of subtly presented issues. In Study 3 (Data Generator), both models consistently replicated patterns of cultural bias previously discovered in large language corpora, indicating that ChatGPT can simulate known results, an antecedent to usefulness for both data generation and skills like hypothesis generation. Contrastingly, in Study 4 (Novel Data Predictor), neither model was successful at predicting new results absent in their training data, and neither appeared to leverage substantially new information when predicting more versus less novel outcomes. Together, these results suggest that GPT is a flawed but rapidly improving librarian, a decent research ethicist already, capable of data generation in simple domains with known characteristics but poor at predicting novel patterns of empirical data to aid future experimentation., Comment: Main article is 14 pages, 1 table. Includes SI Appendix: 26 pages, 12 tables, 2 figures. Total: 40 pages, 13 tables, 2 figures. Under revised review at PNAS

Published
2024

12. Machine learning potential for the Cu-W system

Author

Liyanage, Manura, Turlo, Vladyslav, and Curtin, W. A.

Subjects
Condensed Matter - Materials Science
Abstract

Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix composites and nano-multilayers (NMLs) are finding applications as brazing fillers and shielding material for plasma and radiation. Due to the large lattice mismatch between fcc Cu and bcc W, these systems have complex interfaces that are beyond the scales suitable for ab initio methods, thus motivating the development of chemically accurate interatomic potentials. Here, a neural network potential (NNP) for Cu-W is developed within the Behler-Parrinello framework using a curated training dataset that captures metallurgically-relevant local atomic environments. The Cu-W NNP accurately predicts (i) the metallurgical properties (elasticity, stacking faults, dislocations, thermodynamic behavior) in elemental Cu and W, (ii) energies and structures of Cu-W intermetallics and solid solutions, and (iii) a range of fcc Cu/bcc W interfaces, and exhibits physically-reasonable behavior for solid W/liquid Cu systems. As will be demonstrated in forthcoming work, this near-ab initio-accurate NNP can be applied to understand complex phenomena involving interface-driven processes and properties in Cu-W composites., Comment: Submitted, yet unpublished

Published
2024

13. Inclusive studies of two- and three-nucleon short-range correlations in $^3$H and $^3$He

Author

Li, S., Santiesteban, S. N., Arrington, J., Cruz-Torres, R., Kurbany, L., Abrams, D., Alsalmi, S., Androic, D., Aniol, K., Averett, T., Gayoso, C. Ayerbe, Bane, J., Barcus, S., Barrow, J., Beck, A., Bellini, V., Bhatt, H., Bhetuwal, D., Biswas, D., Bulumulla, D., Camsonne, A., Castellanos, J., Chen, J., Chen, J-P., Chrisman, D., Christy, M. E., Clarke, C., Covrig, S., Craycraft, K., Day, D., Dutta, D., Fuchey, E., Gal, C., Garibaldi, F., Gautam, T. N., Gogami, T., Gomez, J., Guéye, P., Habarakada, A., Hague, T. J., Hansen, J. O., Hauenstein, F., Henry, W., Higinbotham, D. W., Holt, R. J., Hyde, C., Itabashi, K., Kaneta, M., Karki, A., Katramatou, A. T., Keppel, C. E., Khachatryan, M., Khachatryan, V., King, P. M., Korover, I., Kutz, T., Lashley-Colthirst, N., Li, W. B., Liu, H., Liyanage, N., Long, E., Mammei, J., Markowitz, P., McClellan, R. E., Meddi, F., Meekins, D., Beck, S. Mey-Tal, Michaels, R., Mihovilovič, M., Moyer, A., Nagao, S., Nelyubin, V., Nguyen, D., Nycz, M., Olson, M., Ou, L., Owen, V., Palatchi, C., Pandey, B., Papadopoulou, A., Park, S., Paul, S., Petkovic, T., Pomatsalyuk, R., Premathilake, S., Punjabi, V., Ransome, R. D., Reimer, P. E., Reinhold, J., Riordan, S., Roche, J., Rodriguez, V. M., Schmidt, A., Schmookler, B., Segarra, E. P., Shahinyan, A., Širca, S., Slifer, K., Solvignon, P., Su, T., Suleiman, R., Szumila-Vance, H., Tang, L., Tian, Y., Tireman, W., Tortorici, F., Toyama, Y., Uehara, K., Urciuoli, G. M., Votaw, D., Williamson, J., Wojtsekhowski, B., Wood, S., Ye, Z. H., Zhang, J., and Zheng, X.

Subjects
Nuclear Experiment, Nuclear Theory
Abstract

Inclusive electron scattering at carefully chosen kinematics can isolate scattering from short-range correlations (SRCs), produced through hard, short-distance interactions of nucleons in the nucleus. Because the two-nucleon (2N) SRCs arise from the same N-N interaction in all nuclei, the cross section in the SRC-dominated regime is identical up to an overall scaling factor, and the A/2H cross section ratio is constant in this region. This scaling behavior has been used to identify SRC dominance and to map out the contribution of SRCs for a wide range of nuclei. We examine this scaling behavior at lower momentum transfers using new data on $^2$H, $^3$H, and $^3$He which show that the scaling region is larger than in heavy nuclei. Based on the improved scaling, especially for $^3$H/$^3$He, we examine the ratios at kinematics where three-nucleon SRCs may play an important role. The data for the largest initial nucleon momenta are consistent with isolation of scattering from 3N-SRCs, and suggest that the very-highest momentum nucleons in $^3$He have a nearly isospin-independent momentum configuration, or a small enhancement of the proton distribution.

Published
2024

15. Stand-alone and combined effects of protein hydrolysate and humic-like substances derived from waste materials on the growth, physiology and mineral nutrition of tea nursery plants

Author

Raguraj, Sriharan, Kasim, Susilawati, Sanali, Bellana Vithanage Roshika, Senarathne, Thakshala Thilini Kumari, Weerathunga, Saman Kumara, Damayanthi, Maha Makkalage Nalika, Wijesinghe, Senarath Pathiranalage Shyamali Kumari, Amali, Rathnasekara Kuruppu Arachchige, Madushani, Maha Gamage Kusala, and Liyanage, Liyana Rallage Mahesh Chaminda

Published
2024
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21. FPGA-based Distributed Union-Find Decoder for Surface Codes

Author

Liyanage, Namitha, Wu, Yue, Tagare, Siona, and Zhong, Lin

Subjects
Quantum Physics, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

A fault-tolerant quantum computer must decode and correct errors faster than they appear to prevent exponential slowdown due to error correction. The Union-Find (UF) decoder is promising with an average time complexity slightly higher than $O(d^3)$. We report a distributed version of the UF decoder that exploits parallel computing resources for further speedup. Using an FPGA-based implementation, we empirically show that this distributed UF decoder has a sublinear average time complexity with regard to $d$, given $O(d^3)$ parallel computing resources. The decoding time per measurement round decreases as $d$ increases, the first time for a quantum error decoder. The implementation employs a scalable architecture called Helios that organizes parallel computing resources into a hybrid tree-grid structure. Using a Xilinx VCU129 FPGA, we successfully implement $d$ up to 21 with an average decoding time of 11.5 ns per measurement round under 0.1\% phenomenological noise, and 23.7 ns for $d=17$ under equivalent circuit-level noise. This performance is significantly faster than any existing decoder implementation. Furthermore, we show that Helios can optimize for resource efficiency by decoding $d=51$ on a Xilinx VCU129 FPGA with an average latency of 544ns per measurement round., Comment: The article extends the work in arXiv:2301.08419, which also appeared in https://ieeexplore.ieee.org/document/10313800

Published
2024
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22. Photon-triggered jets as probes of multi-stage jet modification

Author

Sirimanna, C., Tachibana, Y., Angerami, A., Arora, R., Bass, S. A., Cao, S., Chen, Y., Du, L., Ehlers, R., Elfner, H., Fan, W., Fries, R. J., Gale, C., He, Y., Heinz, U., Jacak, B. V., Jacobs, P. M., Jeon, S., Ji, Y., Kasper, L., Kordell II, M., Kumar, A., Kunnawalkam-Elayavalli, R., Latessa, J., Lee, S., Lee, Y. -J., Liyanage, D., Luzum, M., Mak, S., Majumder, A., Mankolli, A., Martin, C., Mehryar, H., Mengel, T., Mulligan, J., Nattrass, C., Paquet, J. -F., Parker, C., Putschke, J. H., Roch, H., Roland, G., Schenke, B., Schwiebert, L., Sengupta, A., Shen, C., Soeder, D., Soltz, R. A., Soudi, I., Strickland, M., Velkovska, J., Vujanovic, G., Wang, X. -N., and Zhao, W.

Subjects
Nuclear Theory, High Energy Physics - Phenomenology
Abstract

Prompt photons are created in the early stages of heavy ion collisions and traverse the QGP medium without any interaction. Therefore, photon-triggered jets can be used to study the jet quenching in the QGP medium. In this work, photon-triggered jets are studied through different jet and jet substructure observables for different collision systems and energies using the JETSCAPE framework. Since the multistage evolution used in the JETSCAPE framework is adequate to describe a wide range of experimental observables simultaneously using the same parameter tune, we use the same parameters tuned for jet and leading hadron studies. The same isolation criteria used in the experimental analysis are used to identify prompt photons for better comparison. For the first time, high-accuracy JETSCAPE results are compared with multi-energy LHC and RHIC measurements to better understand the deviations observed in prior studies. This study highlights the importance of multistage evolution for the simultaneous description of experimental observables through different collision systems and energies using a single parameter tune., Comment: 4 pages, 5 figures. Proceedings of Quark Matter 2023 - XXXth International Conference on Ultra-relativistic Nucleus-Nucleus Collisions, Houston, TX, 3-9 September 2023

Published
2024

23. Measuring jet quenching with a Bayesian inference analysis of hadron and jet data by JETSCAPE

Author

Ehlers, R., Angerami, A., Arora, R., Bass, S. A., Cao, S., Chen, Y., Du, L., Elfner, H., Fan, W., Fries, R. J., Gale, C., He, Y., Heinz, U., Jacak, B. V., Jacobs, P. M., Jeon, S., Ji, Y., Kasper, L., Kordell II, M., Kumar, A., Kunnawalkam-Elayavalli, R., Latessa, J., Lee, S., Lee, Y. -J., Liyanage, D., Luzum, M., Mak, S., Majumder, A., Mankolli, A., Martin, C., Mehryar, H., Mengel, T., Mulligan, J., Nattrass, C., Paquet, J. -F., Parker, C., Putschke, J. H., Roch, H., Roland, G., Schenke, B., Schwiebert, L., Sengupta, A., Shen, C., Sirimanna, C., Soeder, D., Soltz, R. A., Soudi, I., Strickland, M., Tachibana, Y., Velkovska, J., Vujanovic, G., Wang, X. -N., and Zhao, W.

Subjects
High Energy Physics - Phenomenology, Nuclear Experiment, Nuclear Theory
Abstract

The JETSCAPE Collaboration reports the first multi-messenger study of the QGP jet transport parameter $\hat{q}$ using Bayesian inference, incorporating all available hadron and jet inclusive yield and jet substructure data from RHIC and the LHC. The theoretical model utilizes virtuality-dependent in-medium partonic energy loss coupled to a detailed dynamical model of QGP evolution. Tension is observed when constraining $\hat{q}$ for different kinematic cuts of the inclusive hadron data. The addition of substructure data is shown to improve the constraint on $\hat{q}$, without inducing tension with the constraint due to inclusive observables. These studies provide new insight into the mechanisms of jet interactions in matter, and point to next steps in the field for comprehensive understanding of jet quenching as a probe of the QGP., Comment: 4 pages, 2 figures. Proceedings of Quark Matter 2023 - XXXth International Conference on Ultra-relativistic Nucleus-Nucleus Collisions, Houston, TX, 3-9 September 2023

Published
2024

24. New metric improving Bayesian calibration of a multistage approach studying hadron and inclusive jet suppression

Author

Fan, W, Vujanovic, G, Bass, SA, Angerami, A, Arora, R, Cao, S, Chen, Y, Dai, T, Du, L, Ehlers, R, Elfner, H, Fries, RJ, Gale, C, He, Y, Heffernan, M, Heinz, U, Jacak, BV, Jacobs, PM, Jeon, S, Ji, Y, Kasper, L, Kordell, M, Kumar, A, Latessa, J, Lee, Y-J, Lemmon, R, Liyanage, D, Lopez, A, Luzum, M, Majumder, A, Mak, S, Mankolli, A, Martin, C, Mehryar, H, Mengel, T, Mulligan, J, Nattrass, C, Norman, J, Paquet, J-F, Parker, C, Putschke, JH, Roland, G, Schenke, B, Schwiebert, L, Sengupta, A, Shen, C, Sirimanna, C, Soeder, D, Soltz, RA, Soudi, I, Strickland, M, Tachibana, Y, Velkovska, J, Wang, X-N, and Zhao, W

Subjects
Particle and High Energy Physics, Physical Sciences, Nuclear and plasma physics
Abstract

We study parton energy-momentum exchange with the quark gluon plasma (QGP) within a multistage approach composed of in-medium Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution at high virtuality, and (linearized) Boltzmann transport formalism at lower virtuality. This multistage simulation is then calibrated in comparison with high-pT charged hadrons, D mesons, and the inclusive jet nuclear modification factors, using Bayesian model-to-data comparison, to extract the virtuality-dependent transverse momentum broadening transport coefficient q. To facilitate this undertaking, we develop a quantitative metric for validating the Bayesian workflow, which is used to analyze the sensitivity of various model parameters to individual observables. The usefulness of this new metric in improving Bayesian model emulation is shown to be highly beneficial for future such analyses.

Published
2024

25. Novel Measurement of the Neutron Magnetic Form Factor from A=3 Mirror Nuclei

Author

Santiesteban, SN, Li, S, Abrams, D, Alsalmi, S, Androic, D, Aniol, K, Arrington, J, Averett, T, Gayoso, C Ayerbe, Bane, J, Barcus, S, Barrow, J, Beck, A, Bellini, V, Bhatt, H, Bhetuwal, D, Biswas, D, Camsonne, A, Castellanos, J, Chen, J, Chen, J-P, Chrisman, D, Christy, ME, Clarke, C, Covrig, S, Cruz-Torres, R, Day, D, Dutta, D, Fuchey, E, Gal, C, Garibaldi, F, Gautam, TN, Gogami, T, Gomez, J, Guèye, P, Hague, TJ, Hansen, JO, Hauenstein, F, Henry, W, Higinbotham, DW, Holt, RJ, Hyde, C, Itabashi, K, Kaneta, M, Karki, A, Katramatou, AT, Keppel, CE, King, PM, Kurbany, L, Kutz, T, Lashley-Colthirst, N, Li, WB, Liu, H, Liyanage, N, Long, E, Lovato, A, Mammei, J, Markowitz, P, McClellan, RE, Meddi, F, Meekins, D, Michaels, R, Mihovilovič, M, Moyer, A, Nagao, S, Nguyen, D, Nycz, M, Olson, M, Ou, L, Owen, V, Palatchi, C, Pandey, B, Papadopoulou, A, Park, S, Petkovic, T, Premathilake, S, Punjabi, V, Ransome, RD, Reimer, PE, Reinhold, J, Riordan, S, Rocco, N, Rodriguez, VM, Schmidt, A, Schmookler, B, Segarra, EP, Shahinyan, A, Širca, S, Slifer, K, Solvignon, P, Su, T, Suleiman, R, Tang, L, Tian, Y, Tireman, W, Tortorici, F, Toyama, Y, Uehara, K, Urciuoli, GM, and Votaw, D

Subjects
Nuclear and Plasma Physics, Synchrotrons and Accelerators, Physical Sciences, Jefferson Lab Hall A Collaboration, Mathematical Sciences, Engineering, General Physics, Mathematical sciences, Physical sciences
Abstract

The electromagnetic form factors of the proton and neutron encode information on the spatial structure of their charge and magnetization distributions. While measurements of the proton are relatively straightforward, the lack of a free neutron target makes measurements of the neutron's electromagnetic structure more challenging and more sensitive to experimental or model-dependent uncertainties. Various experiments have attempted to extract the neutron form factors from scattering from the neutron in deuterium, with different techniques providing different, and sometimes large, systematic uncertainties. We present results from a novel measurement of the neutron magnetic form factor using quasielastic scattering from the mirror nuclei ^{3}H and ^{3}He, where the nuclear effects are larger than for deuterium but expected to largely cancel in the cross-section ratios. We extracted values of the neutron magnetic form factor for low-to-modest momentum transfer, 0.6

Published
2024

30. 3D Multi-system Bayesian Calibration with Energy Conservation to Study Rapidity-dependent Dynamics of Nuclear Collisions

Author

Mankolli, Andi, Angerami, Aaron, Arora, Ritu, Bass, Steffen, Cao, Shanshan, Chen, Yi, Du, Lipei, Ehlers, Raymond, Elfner, Hannah, Fan, Wenkai, Fries, Rainer J., Gale, Charles, He, Yayun, Heinz, Ulrich, Jacak, Barbara, Jacobs, Peter, Jeon, Sangyong, Ji, Yi, Kasper, Lauren, Kordell II, Michael, Kumar, Amit, Kunnawalkam-Elayavalli, R., Latessa, Joseph, Lee, Sook H., Lee, Yen-Jie, Liyanage, Dananjaya, Luzum, Matt, Majumder, Abhijit, Mak, Simon, Martin, Christal, Mehryar, Haydar, Mengel, Tanner, Mulligan, James, Nattrass, Christine, Paquet, Jean-Francois, Parker, Cameron, Putschke, Joern H., Roland, Gunther, Schenke, Bjoern, Schwiebert, Loren, Sengupta, Arjun, Shen, Chun, Sirimanna, Chathuranga, Soltz, Ron A., Soudi, Ismail, Strickland, Michael, Tachibana, Yasuki, Velkovska, Julia, Vujanovic, Gojko, Wang, Xin-Nian, and Zhao, Wenbin

Subjects
Nuclear Theory, High Energy Physics - Phenomenology, Nuclear Experiment
Abstract

Considerable information about the early-stage dynamics of heavy-ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems -- large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late- time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.

Published
2023

31. Skyrmion-Excited Spin Wave Fractal Network

Author

Tang, Nan, Liyanage, W. L. N. C., Montoya, Sergio A., Patel, Sheena, Quigley, Lizabeth J., Grutter, Alexander J., Fitzsimmons, Michael R., Sinha, Sunil, Borchers, Julie A., Fullerton, Eric E., DeBeer-Schmitt, Lisa, and Gilbert, Dustin A.

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Other Condensed Matter
Abstract

Magnetic skyrmions exhibit unique, technologically relevant pseudo-particle behaviors which arise from their topological protection, including well-defined, three-dimensional dynamic modes that occur at microwave frequencies. During dynamic excitation, spin waves are ejected into the interstitial regions between skyrmions, creating the magnetic equivalent of a turbulent sea. However, since the spin waves in these systems have a well-defined length scale, and the skyrmions are on an ordered lattice, ordered structures from spin wave interference can precipitate from the chaos. This work uses small angle neutron scattering (SANS) to capture the dynamics in hybrid skyrmions and investigate the spin wave structure. Performing simultaneous ferromagnetic resonance and SANS, the diffraction pattern shows a large increase in low-angle scattering intensity which is present only in the resonance condition. This scattering pattern is best fit using a mass fractal model, which suggests the spin waves form a long-range fractal network. The fractal structure is constructed of fundamental units with a size that encodes the spin wave emissions and are constrained by the skyrmion lattice. These results offer critical insights into the nanoscale dynamics of skyrmions, identify a new dynamic spin wave fractal structure, and demonstrates SANS as a unique tool to probe high-speed dynamics.

Published
2023
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32. Extremal Polynomial Norms of Graphs

Author

Bouthat, Ludovick, Chávez, Ángel, Fullerton, Sarah, LaFortune, Matilda, Linarez, Keyron, Liyanage, Nethmin, Son, Justin, and Ting, Tyler

Subjects
Mathematics - Combinatorics
Abstract

Recent work shows that a new family of norms on Hermitian matrices arise by evaluating the even degree complete homogeneous symmetric (CHS) polynomials on the eigenvalues of a Hermitian matrix. The CHS norm of a graph is then defined by evaluating the even degree CHS polynomials on the eigenvalues of the adjacency matrix of a graph. The fact that these norms are defined in terms of eigenvalues (as opposed to singular values) ensures they can distinguish between graphs that other norms cannot. In addition, we prove that the CHS norms are minimized over all connected graphs by the path and maximized over all connected graphs by the complete graph. Finally, we prove that the CHS norms are minimized over all trees by the path and maximized over all trees by the star. Our paper is intended for a wide mathematical audience and we assume no prior knowledge about graphs or symmetric polynomials.

Published
2023

33. Bayesian calibration of viscous anisotropic hydrodynamic (VAH) simulations of heavy-ion collisions

Author

Heinz, Ulrich, Liyanage, Dananjaya, and Gantenberg, Cullen

Subjects
Nuclear Theory, High Energy Physics - Phenomenology, Nuclear Experiment
Abstract

A Bayesian calibration, using experimental data from 2.76 $A$ TeV Pb-Pb collisions at the LHC, of a novel hybrid model is presented in which the usual pre-hydrodynamic and viscous relativistic fluid dynamic (vRFD) stages are replaced by a viscous anisotropic hydrodynamic (VAH) core that smoothly interpolates between the initial expansion-dominated, approximately boost-invariant longitudinally free-streaming and the subsequent collision-dominated (3+1)-dimensional standard vRFD stages. This model yields meaningful constraints for the temperature-dependent specific shear and bulk viscosities, $(\eta/s)(T)$ and $(\zeta/s)(T)$, for temperatures up to about $700$ MeV (i.e. over twice the range that could be explored with earlier models). With its best-fit model parameters the calibrated VAH model makes highly successful predictions for additional $p_T$-dependent observables for which high-quality experimental data are available that were not used for the model calibration., Comment: 4 pages, 3 figures, to appear in the proceedings of Quark Matter 2023 (Houston, TX, 3-9 Sep. 2023) published by EPJC

Published
2023

34. Taweret: a Python package for Bayesian model mixing

Author

Ingles, Kevin, Liyanage, Dananjaya, Semposki, Alexandra C., and Yannotty, John C.

Subjects
Nuclear Theory, Physics - Data Analysis, Statistics and Probability, Statistics - Computation
Abstract

Uncertainty quantification using Bayesian methods is a growing area of research. Bayesian model mixing (BMM) is a recent development which combines the predictions from multiple models such that each model's best qualities are preserved in the final result. Practical tools and analysis suites that facilitate such methods are therefore needed. Taweret introduces BMM to existing Bayesian uncertainty quantification efforts. Currently Taweret contains three individual Bayesian model mixing techniques, each pertaining to a different type of problem structure; we encourage the future inclusion of user-developed mixing methods. Taweret's first use case is in nuclear physics, but the package has been structured such that it should be adaptable to any research engaged in model comparison or model mixing., Comment: 7 pages, 2 figures, submitted to JOSS (Journal of Open Source Software) on 31 October 2023. Comments are welcome!

Published
2023

35. Hybrid Hadronization of Jet Showers from $e^++e^-$ to $A+A$ with JETSCAPE

Author

Parker, Cameron, Angerami, Aaron, Arora, Ritu, Bass, Steffen, Cao, Shanshan, Chen, Yi, Ehlers, Raymond, Elfner, Hannah, Fan, Wenkai, Fries, Rainer J., Gale, Charles, He, Yayun, Heinz, Ulrich, Jacak, Barbara, Jacobs, Peter, Jeon, Sangyong, Ji, Yi, Kasper, Lauren, Kordell II, Michael, Kumar, Amit, Latessa, Joseph, Lee, Yen-Jie, Lemmon, Roy, Liyanage, Dananjaya, Lopez, Arthur, Luzum, Matt, Majumder, Abhijit, Mak, Simon, Mankolli, Andi, Martin, Christal, Mehryar, Haydar, Mengel, Tanner, Mulligan, James, Nattrass, Christine, Norman, Jaime, Paquet, Jean-Francois, Putschke, Joern H., Roland, Gunther, Schenke, Bjoern, Schwiebert, Loren, Sengupta, Arjun, Shen, Chun, Sirimanna, Chathuranga, Soltz, Ron A., Soudi, Ismail, Strickland, Michael, Tachibana, Yasuki, Velkovska, Julia, Vujanovic, Gojko, Wang, Xin-Nian, and Zhao, Wenbin

Subjects
High Energy Physics - Phenomenology, Nuclear Experiment, Nuclear Theory
Abstract

In this talk we review jet production in a large variety of collision systems using the JETSCAPE event generator and Hybrid Hadronization. Hybrid Hadronization combines quark recombination, applicable when distances between partons in phase space are small, and string fragmentation appropriate for dilute parton systems. It can therefore smoothly describe the transition from very dilute parton systems like $e^++e^-$ to full $A+A$ collisions. We test this picture by using JETSCAPE to generate jets in various systems. Comparison to experimental data in $e^++e^-$ and $p+p$ collisions allows for a precise tuning of vacuum baseline parameters in JETSCAPE and Hybrid Hadronization. Proceeding to systems with jets embedded in a medium, we study in-medium hadronization for jet showers. We quantify the effects of an ambient medium, focusing in particular on the dependence on the collective flow and size of the medium. Our results clarify the effects we expect from in-medium hadronization of jets on observables like fragmentation functions, hadron chemistry and jet shape., Comment: 6 pages, 4 figures, Hard Probes 2023 conference, accepted for publication in Proceedings of Science: version 2, references added, typos fixed

Published
2023

36. An Ensemble Method Based on the Combination of Transformers with Convolutional Neural Networks to Detect Artificially Generated Text

Author

Liyanage, Vijini and Buscaldi, Davide

Subjects
Computer Science - Computation and Language
Abstract

Thanks to the state-of-the-art Large Language Models (LLMs), language generation has reached outstanding levels. These models are capable of generating high quality content, thus making it a challenging task to detect generated text from human-written content. Despite the advantages provided by Natural Language Generation, the inability to distinguish automatically generated text can raise ethical concerns in terms of authenticity. Consequently, it is important to design and develop methodologies to detect artificial content. In our work, we present some classification models constructed by ensembling transformer models such as Sci-BERT, DeBERTa and XLNet, with Convolutional Neural Networks (CNNs). Our experiments demonstrate that the considered ensemble architectures surpass the performance of the individual transformer models for classification. Furthermore, the proposed SciBERT-CNN ensemble model produced an F1-score of 98.36% on the ALTA shared task 2023 data., Comment: In Proceedings of the 21st Annual Workshop of the Australasian Language Technology Association (ALTA 2023)

Published
2023

40. Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

Author

Hayrapetyan, A., Tumasyan, A., Adam, W., Andrejkovic, J. W., Bergauer, T., Chatterjee, S., Damanakis, K., Dragicevic, M., Hussain, P. S., Jeitler, M., Krammer, N., Li, A., Liko, D., Mikulec, I., Schieck, J., Schöfbeck, R., Schwarz, D., Sonawane, M., Templ, S., Waltenberger, W., Wulz, C.-E., Darwish, M. R., Janssen, T., Mechelen, P. Van, Bols, E. S., D’Hondt, J., Dansana, S., De Moor, A., Delcourt, M., Faham, H. El, Lowette, S., Makarenko, I., Müller, D., Sahasransu, A. R., Tavernier, S., Tytgat, M., Onsem, G. P. Van, Putte, S. Van, Vannerom, D., Clerbaux, B., Das, A. K., De Lentdecker, G., Favart, L., Gianneios, P., Hohov, D., Jaramillo, J., Khalilzadeh, A., Khan, F. A., Lee, K., Mahdavikhorrami, M., Malara, A., Paredes, S., Thomas, L., Bemden, M. Vanden, Velde, C. Vander, Vanlaer, P., De Coen, M., Dobur, D., Hong, Y., Knolle, J., Lambrecht, L., Mestdach, G., Amarilo, K. Mota, Rendón, C., Samalan, A., Skovpen, K., Bossche, N. Van Den, Linden, J. van der, Wezenbeek, L., Benecke, A., Bethani, A., Bruno, G., Caputo, C., Delaere, C., Donertas, I. S., Giammanco, A., Jaffel, K., Jain, Sa., Lemaitre, V., Lidrych, J., Mastrapasqua, P., Mondal, K., Tran, T. T., Wertz, S., Alves, G. A., Coelho, E., Hensel, C., De Oliveira, T. Menezes, Moraes, A., Teles, P. Rebello, Soeiro, M., Júnior, W. L. Aldá, Pereira, M. Alves Gallo, Filho, M. Barroso Ferreira, Malbouisson, H. Brandao, Carvalho, W., Chinellato, J., Da Costa, E. M., Da Silveira, G. G., De Jesus Damiao, D., De Souza, S. Fonseca, De Souza, R. Gomes, Martins, J., Herrera, C. Mora, Mundim, L., Nogima, H., Pinheiro, J. P., Santoro, A., Sznajder, A., Thiel, M., Pereira, A. Vilela, Bernardes, C. A., Calligaris, L., Tomei, T. R. Fernandez Perez, Gregores, E. M., Mercadante, P. G., Novaes, S. F., Orzari, B., Padula, Sandra S., Aleksandrov, A., Antchev, G., Hadjiiska, R., Iaydjiev, P., Misheva, M., Shopova, M., Sultanov, G., Dimitrov, A., Litov, L., Pavlov, B., Petkov, P., Petrov, A., Shumka, E., Keshri, S., Thakur, S., Cheng, T., Javaid, T., Yuan, L., Hu, Z., Liu, J., Yi, K., Chen, G. M., Chen, H. S., Chen, M., Iemmi, F., Jiang, C. H., Kapoor, A., Liao, H., Liu, Z.-A., Sharma, R., Song, J. N., Tao, J., Wang, C., Wang, J., Wang, Z., Zhang, H., Agapitos, A., Ban, Y., Levin, A., Li, C., Li, Q., Mao, Y., Qian, S. J., Sun, X., Wang, D., Yang, H., Zhang, L., Zhou, C., You, Z., Lu, N., Bauer, G., Gao, X., Leggat, D., Okawa, H., Lin, Z., Lu, C., Xiao, M., Avila, C., Trujillo, D. A. Barbosa, Cabrera, A., Florez, C., Fraga, J., Vega, J. A. Reyes, Guisao, J. Mejia, Ramirez, F., Rodriguez, M., Alvarez, J. D. Ruiz, Giljanovic, D., Godinovic, N., Lelas, D., Sculac, A., Kovac, M., Sculac, T., Bargassa, P., Brigljevic, V., Chitroda, B. K., Ferencek, D., Mishra, S., Starodumov, A., Susa, T., Attikis, A., Christoforou, K., Konstantinou, S., Mousa, J., Nicolaou, C., Ptochos, F., Razis, P. A., Rykaczewski, H., Saka, H., Stepennov, A., Finger, M., Finger, Jr., M., Kveton, A., Ayala, E., Jarrin, E. Carrera, Abdelalim, A. A., Salama, E., Mahmoud, M. A., Mohammed, Y., Ehataht, K., Kadastik, M., Lange, T., Nandan, S., Nielsen, C., Pata, J., Raidal, M., Tani, L., Veelken, C., Kirschenmann, H., Osterberg, K., Voutilainen, M., Bharthuar, S., Brücken, E., Garcia, F., Kallonen, K. T. S., Kinnunen, R., Lampén, T., Lassila-Perini, K., Lehti, S., Lindén, T., Martikainen, L., Myllymäki, M., Rantanen, M.m., Siikonen, H., Tuominen, E., Tuominiemi, J., Luukka, P., Petrow, H., Besancon, M., Couderc, F., Dejardin, M., Denegri, D., Faure, J. L., Ferri, F., Ganjour, S., Gras, P., de Monchenault, G. Hamel, Lohezic, V., Malcles, J., Rander, J., Rosowsky, A., Sahin, M. Ö., Savoy-Navarro, A., Simkina, P., Titov, M., Tornago, M., Barrera, C. Baldenegro, Beaudette, F., Perraguin, A. Buchot, Busson, P., Cappati, A., Charlot, C., Chiusi, M., Damas, F., Davignon, O., De Wit, A., Alves, B. A. Fontana Santos, Ghosh, S., Gilbert, A., de Cassagnac, R. Granier, Hakimi, A., Harikrishnan, B., Kalipoliti, L., Liu, G., Motta, J., Nguyen, M., Ochando, C., Portales, L., Salerno, R., Sauvan, J. B., Sirois, Y., Tarabini, A., Vernazza, E., Zabi, A., Zghiche, A., Agram, J.-L., Andrea, J., Apparu, D., Bloch, D., Brom, J.-M., Chabert, E. C., Collard, C., Falke, S., Goerlach, U., Grimault, C., Haeberle, R., Bihan, A.-C. Le, Meena, M., Saha, G., Sessini, M. A., Hove, P. Van, Beauceron, S., Blancon, B., Boudoul, G., Chanon, N., Choi, J., Contardo, D., Depasse, P., Dozen, C., Mamouni, H. El, Fay, J., Gascon, S., Gouzevitch, M., Greenberg, C., Grenier, G., Ille, B., Laktineh, I. B., Lethuillier, M., Mirabito, L., Perries, S., Purohit, A., Donckt, M. Vander, Verdier, P., Xiao, J., Bagaturia, I., Lomidze, I., Tsamalaidze, Z., Botta, V., Feld, L., Klein, K., Lipinski, M., Meuser, D., Pauls, A., Röwert, N., Teroerde, M., Diekmann, S., Dodonova, A., Eich, N., Eliseev, D., Engelke, F., Erdmann, J., Erdmann, M., Fackeldey, P., Fischer, B., Hebbeker, T., Hoepfner, K., Ivone, F., Jung, A., Lee, M.y., Mausolf, F., Merschmeyer, M., Meyer, A., Mukherjee, S., Noll, D., Nowotny, F., Pozdnyakov, A., Rath, Y., Redjeb, W., Rehm, F., Reithler, H., Sarkar, U., Sarkisovi, V., Schmidt, A., Sharma, A., Spah, J. L., Stein, A., Da Silva De Araujo, F. Torres, Vigilante, L., Wiedenbeck, S., Zaleski, S., Dziwok, C., Flügge, G., Ahmad, W. Haj, Kress, T., Nowack, A., Pooth, O., Stahl, A., Ziemons, T., Zotz, A., Petersen, H. Aarup, Martin, M. Aldaya, Alimena, J., Amoroso, S., An, Y., Baxter, S., Bayatmakou, M., Gonzalez, H. Becerril, Behnke, O., Belvedere, A., Bhattacharya, S., Blekman, F., Borras, K., Campbell, A., Cardini, A., Cheng, C., Colombina, F., Rodríguez, S. Consuegra, Silva, G. Correia, De Silva, M., Eckerlin, G., Eckstein, D., Banos, L. I. Estevez, Filatov, O., Gallo, E., Geiser, A., Giraldi, A., Guglielmi, V., Guthoff, M., Hinzmann, A., Jafari, A., Jeppe, L., Jomhari, N. Z., Kaech, B., Kasemann, M., Kleinwort, C., Kogler, R., Komm, M., Krücker, D., Lange, W., Pernia, D. Leyva, Lipka, K., Lohmann, W., Mankel, R., Melzer-Pellmann, I.-A., Morentin, M. Mendizabal, Meyer, A. B., Milella, G., Mussgiller, A., Nair, L. P., Nürnberg, A., Otarid, Y., Park, J., Adán, D. Pérez, Ranken, E., Raspereza, A., Lopes, B. Ribeiro, Rübenach, J., Saggio, A., Scham, M., Schnake, S., Schütze, P., Schwanenberger, C., Selivanova, D., Sharko, K., Shchedrolosiev, M., Ricardo, R. E. Sosa, Stafford, D., Vazzoler, F., Barroso, A. Ventura, Walsh, R., Wang, Q., Wen, Y., Wichmann, K., Wiens, L., Wissing, C., Yang, Y., Santos, A. Zimermmane Castro, Albrecht, A., Albrecht, S., Antonello, M., Bein, S., Benato, L., Bollweg, S., Bonanomi, M., Connor, P., Eich, M., Morabit, K. El, Fischer, Y., Garbers, C., Garutti, E., Grohsjean, A., Haller, J., Jabusch, H. R., Kasieczka, G., Keicher, P., Klanner, R., Korcari, W., Kramer, T., Kutzner, V., Labe, F., Lange, J., Lobanov, A., Matthies, C., Mehta, A., Moureaux, L., Mrowietz, M., Nigamova, A., Nissan, Y., Paasch, A., Rodriguez, K. J. Pena, Quadfasel, T., Raciti, B., Rieger, M., Savoiu, D., Schindler, J., Schleper, P., Schröder, M., Schwandt, J., Sommerhalder, M., Stadie, H., Steinbrück, G., Tews, A., Wolf, M., Brommer, S., Burkart, M., Butz, E., Chwalek, T., Dierlamm, A., Droll, A., Faltermann, N., Giffels, M., Gottmann, A., Hartmann, F., Hofsaess, R., Horzela, M., Husemann, U., Kieseler, J., Klute, M., Koppenhöfer, R., Lawhorn, J. M., Link, M., Lintuluoto, A., Maier, S., Mitra, S., Mormile, M., Müller, Th., Neukum, M., Oh, M., Presilla, M., Quast, G., Rabbertz, K., Regnery, B., Shadskiy, N., Shvetsov, I., Simonis, H. J., Toms, M., Trevisani, N., Cube, R. F. Von, Wassmer, M., Wieland, S., Wittig, F., Wolf, R., Zuo, X., Anagnostou, G., Daskalakis, G., Kyriakis, A., Papadopoulos, A., Stakia, A., Kontaxakis, P., Melachroinos, G., Panagiotou, A., Papavergou, I., Paraskevas, I., Saoulidou, N., Theofilatos, K., Tziaferi, E., Vellidis, K., Zisopoulos, I., Bakas, G., Chatzistavrou, T., Karapostoli, G., Kousouris, K., Papakrivopoulos, I., Siamarkou, E., Tsipolitis, G., Zacharopoulou, A., Adamidis, K., Bestintzanos, I., Evangelou, I., Foudas, C., Kamtsikis, C., Katsoulis, P., Kokkas, P., Kioseoglou, P. G. Kosmoglou, Manthos, N., Papadopoulos, I., Strologas, J., Bartók, M., Hajdu, C., Horvath, D., Márton, K., Sikler, F., Veszpremi, V., Csanád, M., Farkas, K., Gadallah, M. M. A., Kadlecsik, Á., Major, P., Mandal, K., Pásztor, G., Rádl, A. J., Veres, G. I., Raics, P., Ujvari, B., Zilizi, G., Bencze, G., Czellar, S., Molnar, J., Szillasi, Z., Csorgo, T., Nemes, F., Novak, T., Babbar, J., Bansal, S., Beri, S. B., Bhatnagar, V., Chaudhary, G., Chauhan, S., Dhingra, N., Kaur, A., Kaur, A., Kaur, H., Kaur, M., Kumar, S., Sandeep, K., Sheokand, T., Singh, J. B., Singla, A., Ahmed, A., Bhardwaj, A., Chhetri, A., Choudhary, B. C., Kumar, A., Kumar, A., Naimuddin, M., Ranjan, K., Saumya, S., Baradia, S., Barman, S., Bhattacharya, S., Dutta, S., Dutta, S., Sarkar, S., Ameen, M. M., Behera, P. K., Behera, S. C., Chatterjee, S., Jana, P., Kalbhor, P., Komaragiri, J. R., Kumar, D., Pujahari, P. R., Saha, N. R., Sharma, A., Sikdar, A. K., Verma, S., Dugad, S., Kumar, M., Mohanty, G. B., Suryadevara, P., Bala, A., Banerjee, S., Chatterjee, R. M., Dewanjee, R. K., Guchait, M., Jain, Sh., Jaiswal, A., Karmakar, S., Kumar, S., Majumder, G., Mazumdar, K., Parolia, S., Thachayath, A., Bahinipati, S., Kar, C., Maity, D., Mal, P., Mishra, T., Bindhu, V. K. Muraleedharan Nair, Naskar, K., Nayak, A., Sadangi, P., Saha, P., Swain, S. K., Varghese, S., Vats, D., Acharya, S., Alpana, A., Dube, S., Gomber, B., Kansal, B., Laha, A., Sahu, B., Sharma, S., Vaish, K. Y., Bakhshiansohi, H., Khazaie, E., Zeinali, M., Chenarani, S., Etesami, S. M., Khakzad, M., Najafabadi, M. Mohammadi, Grunewald, M., Abbrescia, M., Aly, R., Colaleo, A., Creanza, D., D’Anzi, B., De Filippis, N., De Palma, M., Florio, A. Di, Elmetenawee, W., Fiore, L., Iaselli, G., Louka, M., Maggi, G., Maggi, M., Margjeka, I., Mastrapasqua, V., My, S., Nuzzo, S., Pellecchia, A., Pompili, A., Pugliese, G., Radogna, R., Ramirez-Sanchez, G., Ramos, D., Ranieri, A., Silvestris, L., Simone, F. M., Sözbilir, Ü., Stamerra, A., Venditti, R., Verwilligen, P., Zaza, A., Abbiendi, G., Battilana, C., Bonacorsi, D., Borgonovi, L., Campanini, R., Capiluppi, P., Castro, A., Cavallo, F. R., Cuffiani, M., Dallavalle, G. M., Diotalevi, T., Fanfani, A., Fasanella, D., Giacomelli, P., Giommi, L., Grandi, C., Guiducci, L., Meo, S. Lo, Lunerti, L., Marcellini, S., Masetti, G., Navarria, F. L., Perrotta, A., Primavera, F., Rossi, A. M., Rovelli, T., Siroli, G. P., Costa, S., Mattia, A. Di, Potenza, R., Tricomi, A., Tuve, C., Assiouras, P., Barbagli, G., Bardelli, G., Camaiani, B., Cassese, A., Ceccarelli, R., Ciulli, V., Civinini, C., D’Alessandro, R., Focardi, E., Kello, T., Latino, G., Lenzi, P., Lizzo, M., Meschini, M., Paoletti, S., Papanastassiou, A., Sguazzoni, G., Viliani, L., Benussi, L., Bianco, S., Meola, S., Piccolo, D., Chatagnon, P., Ferro, F., Robutti, E., Tosi, S., Benaglia, A., Boldrini, G., Brivio, F., Cetorelli, F., De Guio, F., Dinardo, M. E., Dini, P., Gennai, S., Gerosa, R., Ghezzi, A., Govoni, P., Guzzi, L., Lucchini, M. T., Malberti, M., Malvezzi, S., Massironi, A., Menasce, D., Moroni, L., Paganoni, M., Pedrini, D., Pinolini, B. S., Ragazzi, S., de Fatis, T. Tabarelli, Zuolo, D., Buontempo, S., Cagnotta, A., Carnevali, F., Cavallo, N., Fabozzi, F., Iorio, A. O. M., Lista, L., Paolucci, P., Rossi, B., Sciacca, C., Ardino, R., Azzi, P., Bacchetta, N., Bisello, D., Bortignon, P., Bragagnolo, A., Checchia, P., Dorigo, T., Gasparini, U., Lusiani, E., Margoni, M., Marini, F., Meneguzzo, A. T., Migliorini, M., Passaseo, M., Pazzini, J., Ronchese, P., Rossin, R., Sgaravatto, M., Simonetto, F., Strong, G., Tosi, M., Triossi, A., Ventura, S., Yarar, H., Zanetti, M., Zotto, P., Zucchetta, A., Zumerle, G., Zeid, S. Abu, Aimè, C., Braghieri, A., Calzaferri, S., Fiorina, D., Montagna, P., Re, V., Riccardi, C., Salvini, P., Vai, I., Vitulo, P., Ajmal, S., Bilei, G. M., Ciangottini, D., Fanò, L., Magherini, M., Mantovani, G., Mariani, V., Menichelli, M., Moscatelli, F., Rossi, A., Santocchia, A., Spiga, D., Tedeschi, T., Asenov, P., Azzurri, P., Bagliesi, G., Bhattacharya, R., Bianchini, L., Boccali, T., Bossini, E., Bruschini, D., Castaldi, R., Ciocci, M. A., Cipriani, M., D’Amante, V., Dell’Orso, R., Donato, S., Giassi, A., Ligabue, F., Figueiredo, D. Matos, Messineo, A., Musich, M., Palla, F., Rizzi, A., Rolandi, G., Chowdhury, S. Roy, Sarkar, T., Scribano, A., Spagnolo, P., Tenchini, R., Tonelli, G., Turini, N., Venturi, A., Verdini, P. G., Barria, P., Basile, C., Campana, M., Cavallari, F., Mendez, L. Cunqueiro, Re, D. Del, Marco, E. Di, Diemoz, M., Errico, F., Longo, E., Meridiani, P., Mijuskovic, J., Organtini, G., Pandolfi, F., Paramatti, R., Quaranta, C., Rahatlou, S., Rovelli, C., Santanastasio, F., Soffi, L., Amapane, N., Arcidiacono, R., Argiro, S., Arneodo, M., Bartosik, N., Bellan, R., Bellora, A., Biino, C., Borca, C., Cartiglia, N., Costa, M., Covarelli, R., Demaria, N., Finco, L., Grippo, M., Kiani, B., Legger, F., Luongo, F., Mariotti, C., Markovic, L., Maselli, S., Mecca, A., Migliore, E., Monteno, M., Mulargia, R., Obertino, M. M., Ortona, G., Pacher, L., Pastrone, N., Pelliccioni, M., Ruspa, M., Siviero, F., Sola, V., Solano, A., Staiano, A., Tarricone, C., Trocino, D., Umoret, G., Vlasov, E., Belforte, S., Candelise, V., Casarsa, M., Cossutti, F., De Leo, K., Ricca, G. Della, Dogra, S., Hong, J., Huh, C., Kim, B., Kim, D. H., Kim, J., Lee, H., Lee, S. W., Moon, C. S., Oh, Y. D., Ryu, M. S., Sekmen, S., Yang, Y. C., Kim, M. S., Bak, G., Gwak, P., Kim, H., Moon, D. H., Asilar, E., Kim, D., Kim, T. J., Merlin, J. A., Choi, S., Han, S., Hong, B., Lee, K., Lee, K. S., Lee, S., Park, J., Park, S. K., Yoo, J., Goh, J., Yang, S., Kim, H. S., Kim, Y., Lee, S., Almond, J., Bhyun, J. H., Choi, J., Jun, W., Kim, J., Ko, S., Kwon, H., Lee, H., Lee, J., Lee, J., Oh, B. H., Oh, S. B., Seo, H., Yang, U. K., Yoon, I., Jang, W., Kang, D. Y., Kang, Y., Kim, S., Ko, B., Lee, J. S. H., Lee, Y., Park, I. C., Roh, Y., Watson, I. J., Ha, S., Yoo, H. D., Choi, M., Kim, M. R., Lee, H., Lee, Y., Yu, I., Beyrouthy, T., Maghrbi, Y., Dreimanis, K., Gaile, A., Pikurs, G., Potrebko, A., Seidel, M., Veckalns, V., Strautnieks, N. R., Ambrozas, M., Juodagalvis, A., Rinkevicius, A., Tamulaitis, G., Norjoharuddeen, N. Bin, Yusuff, I., Zolkapli, Z., Benitez, J. F., Hernandez, A. Castaneda, Acosta, H. A. Encinas, Maríñez, L. G. Gallegos, Coello, M. León, Quijada, J. A. Murillo, Sehrawat, A., Palomo, L. Valencia, Ayala, G., Castilla-Valdez, H., Ledesma, H. Crotte, De La Cruz-Burelo, E., La Cruz, I. Heredia-De, Lopez-Fernandez, R., Herrera, C. A. Mondragon, Hernández, A. Sánchez, Barrera, C. Oropeza, García, M. Ramírez, Bautista, I., Pedraza, I., Ibarguen, H. A. Salazar, Estrada, C. Uribe, Bubanja, I., Raicevic, N., Butler, P. H., Ahmad, A., Asghar, M. I., Awais, A., Awan, M. I. M., Hoorani, H. R., Khan, W. A., Avati, V., Grzanka, L., Malawski, M., Bialkowska, H., Bluj, M., Boimska, B., Górski, M., Kazana, M., Szleper, M., Zalewski, P., Bunkowski, K., Doroba, K., Kalinowski, A., Konecki, M., Krolikowski, J., Muhammad, A., Pozniak, K., Zabolotny, W., Araujo, M., Bastos, D., Da Cruz E Silva, C. Beirão, Boletti, A., Bozzo, M., Camporesi, T., Da Molin, G., Faccioli, P., Gallinaro, M., Hollar, J., Leonardo, N., Niknejad, T., Petrilli, A., Pisano, M., Seixas, J., Varela, J., Wulff, J. W., Adzic, P., Milenovic, P., Dordevic, M., Milosevic, J., Rekovic, V., Aguilar-Benitez, M., Maestre, J. Alcaraz, Bedoya, Cristina F., Cepeda, M., Cerrada, M., Colino, N., De La Cruz, B., Peris, A. Delgado, Valle, A. Escalante Del, Val, D. Fernández Del, Ramos, J. P. Fernández, Flix, J., Fouz, M. C., Lopez, O. Gonzalez, Lopez, S. Goy, Hernandez, J. M., Josa, M. I., Moran, D., Perez, C. M. Morcillo, Tobar, Á. Navarro, Dengra, C. Perez, Yzquierdo, A. Pérez-Calero, Pelayo, J. Puerta, Redondo, I., Ferrero, D. D. Redondo, Romero, L., Navas, S. Sánchez, Gómez, L. Urda, Escobar, J. Vazquez, Willmott, C., de Trocóniz, J. F., Gonzalez, B. Alvarez, Cuevas, J., Menendez, J. Fernandez, Folgueras, S., Caballero, I. Gonzalez, Fernández, J. R. González, Cortezon, E. Palencia, Álvarez, C. Ramón, Bouza, V. Rodríguez, Rodríguez, A. Soto, Trapote, A., Villalba, C. Vico, Vischia, P., Bhowmik, S., Fernández, S. Blanco, Cifuentes, J. A. Brochero, Cabrillo, I. J., Calderon, A., Campderros, J. Duarte, Fernandez, M., Gomez, G., García, C. Lasaosa, Rivero, C. Martinez, Arbol, P. Martinez Ruiz del, Matorras, F., Cuevas, P. Matorras, Ramos, E. Navarrete, Gomez, J. Piedra, Scodellaro, L., Vila, I., Garcia, J. M. Vizan, Jayananda, M. K., Kailasapathy, B., Sonnadara, D. U. J., Wickramarathna, D. D. C., Dharmaratna, W. G. D., Liyanage, K., Perera, N., Wickramage, N., Abbaneo, D., Amendola, C., Auffray, E., Auzinger, G., Baechler, J., Barney, D., Martínez, A. Bermúdez, Bianco, M., Bilin, B., Anuar, A. A. Bin, Bocci, A., Botta, C., Brondolin, E., Caillol, C., Cerminara, G., Chernyavskaya, N., d’Enterria, D., Dabrowski, A., David, A., De Roeck, A., Defranchis, M. M., Deile, M., Dobson, M., Forthomme, L., Franzoni, G., Funk, W., Giani, S., Gigi, D., Gill, K., Glege, F., Gouskos, L., Haranko, M., Hegeman, J., Huber, B., Innocente, V., James, T., Janot, P., Laurila, S., Lecoq, P., Leutgeb, E., Lourenço, C., Maier, B., Malgeri, L., Mannelli, M., Marini, A. C., Matthewman, M., Meijers, F., Mersi, S., Meschi, E., Milosevic, V., Monti, F., Moortgat, F., Mulders, M., Neutelings, I., Orfanelli, S., Pantaleo, F., Petrucciani, G., Pfeiffer, A., Pierini, M., Piparo, D., Qu, H., Rabady, D., Gutiérrez, G. Reales, Rovere, M., Sakulin, H., Scarfi, S., Schwick, C., Selvaggi, M., Sharma, A., Shchelina, K., Silva, P., Sphicas, P., Leiton, A. G. Stahl, Steen, A., Summers, S., Treille, D., Tropea, P., Tsirou, A., Walter, D., Wanczyk, J., Wang, J., Wuchterl, S., Zehetner, P., Zejdl, P., Zeuner, W. D., Bevilacqua, T., Caminada, L., Ebrahimi, A., Erdmann, W., Horisberger, R., Ingram, Q., Kaestli, H. C., Kotlinski, D., Lange, C., Missiroli, M., Noehte, L., Rohe, T., Aarrestad, T. K., Androsov, K., Backhaus, M., Calandri, A., Cazzaniga, C., Datta, K., De Cosa, A., Dissertori, G., Dittmar, M., Donegà, M., Eble, F., Galli, M., Gedia, K., Glessgen, F., Grab, C., Hits, D., Lustermann, W., Lyon, A.-M., Manzoni, R. A., Marchegiani, M., Marchese, L., Perez, C. Martin, Mascellani, A., Nessi-Tedaldi, F., Pauss, F., Perovic, V., Pigazzini, S., Reissel, C., Reitenspiess, T., Ristic, B., Riti, F., Seidita, R., Steggemann, J., Valsecchi, D., Wallny, R., Amsler, C., Bärtschi, P., Brzhechko, D., Canelli, M. F., Cormier, K., Heikkilä, J. K., Huwiler, M., Jin, W., Jofrehei, A., Kilminster, B., Leontsinis, S., Liechti, S. P., Macchiolo, A., Meiring, P., Molinatti, U., Reimers, A., Robmann, P., Cruz, S. Sanchez, Senger, M., Stäger, F., Takahashi, Y., Tramontano, R., Adloff, C., Bhowmik, D., Kuo, C. M., Lin, W., Rout, P. K., Tiwari, P. C., Yu, S. S., Ceard, L., Chao, Y., Chen, K. F., Chen, P. s., Chen, Z. g., De Iorio, A., Hou, W.-S., Hsu, T. h., Kao, Y. w., Khurana, R., Kole, G., Li, Y.y., Lu, R.-S., Paganis, E., Su, X.f., Thomas-Wilsker, J., Tsai, L. s., Wu, H. y., Yazgan, E., Asawatangtrakuldee, C., Srimanobhas, N., Wachirapusitanand, V., Agyel, D., Boran, F., Demiroglu, Z. S., Dolek, F., Dumanoglu, I., Eskut, E., Guler, Y., Guler, E. Gurpinar, Isik, C., Kara, O., Topaksu, A. Kayis, Kiminsu, U., Onengut, G., Ozdemir, K., Polatoz, A., Tali, B., Tok, U. G., Turkcapar, S., Uslan, E., Zorbakir, I. S., Yalvac, M., Akgun, B., Atakisi, I. O., Gülmez, E., Kaya, M., Kaya, O., Tekten, S., Cakir, A., Cankocak, K., Komurcu, Y., Sen, S., Aydilek, O., Cerci, S., Epshteyn, V., Hacisahinoglu, B., Hos, I., Kaynak, B., Ozkorucuklu, S., Potok, O., Sert, H., Simsek, C., Zorbilmez, C., Isildak, B., Cerci, D. Sunar, Boyaryntsev, A., Grynyov, B., Levchuk, L., Anthony, D., Brooke, J. J., Bundock, A., Bury, F., Clement, E., Cussans, D., Flacher, H., Glowacki, M., Goldstein, J., Heath, H. F., Kreczko, L., Paramesvaran, S., Robertshaw, L., Nasr-Storey, S. Seif El, Smith, V. J., Stylianou, N., Pass, K. Walkingshaw, White, R., Ball, A. H., Bell, K. W., Belyaev, A., Brew, C., Brown, R. M., Cockerill, D. J. A., Cooke, C., Ellis, K. V., Harder, K., Harper, S., Holmberg, M.-L., Linacre, J., Manolopoulos, K., Newbold, D. M., Olaiya, E., Petyt, D., Reis, T., Salvi, G., Schuh, T., Shepherd-Themistocleous, C. H., Tomalin, I. R., Williams, T., Bainbridge, R., Bloch, P., Brown, C. E., Buchmuller, O., Cacchio, V., Montoya, C. A. Carrillo, Chahal, G. S., Colling, D., Dancu, J. S., Das, I., Dauncey, P., Davies, G., Davies, J., Negra, M. Della, Fayer, S., Fedi, G., Hall, G., Hassanshahi, M. H., Howard, A., Iles, G., Knight, M., Langford, J., Holgado, J. León, Lyons, L., Magnan, A.-M., Malik, S., Mieskolainen, M., Nash, J., Pesaresi, M., Radburn-Smith, B. C., Richards, A., Rose, A., Savva, K., Seez, C., Shukla, R., Tapper, A., Uchida, K., Uttley, G. P., Vage, L. H., Virdee, T., Vojinovic, M., Wardle, N., Winterbottom, D., Coldham, K., Cole, J. E., Khan, A., Kyberd, P., Reid, I. D., Abdullin, S., Brinkerhoff, A., Caraway, B., Dittmann, J., Hatakeyama, K., Hiltbrand, J., McMaster, B., Saunders, M., Sawant, S., Sutantawibul, C., Wilson, J., Bartek, R., Dominguez, A., Escamilla, C. Huerta, Simsek, A. E., Uniyal, R., Hernandez, A. M. Vargas, Bam, B., Chudasama, R., Cooper, S. I., Gleyzer, S. V., Perez, C. U., Rumerio, P., Usai, E., Yi, R., Akpinar, A., Arcaro, D., Cosby, C., Demiragli, Z., Erice, C., Fangmeier, C., Madrazo, C. Fernandez, Fontanesi, E., Gastler, D., Golf, F., Jeon, S., Reed, I., Rohlf, J., Salyer, K., Sperka, D., Spitzbart, D., Suarez, I., Tsatsos, A., Yuan, S., Zecchinelli, A. G., Benelli, G., Coubez, X., Cutts, D., Hadley, M., Heintz, U., Hogan, J. M., Kwon, T., Landsberg, G., Lau, K. T., Li, D., Luo, J., Mondal, S., Narain, M., Pervan, N., Sagir, S., Simpson, F., Stamenkovic, M., Yan, X., Zhang, W., Abbott, S., Bonilla, J., Brainerd, C., Breedon, R., De La Barca Sanchez, M. Calderon, Chertok, M., Citron, M., Conway, J., Cox, P. T., Erbacher, R., Jensen, F., Kukral, O., Mocellin, G., Mulhearn, M., Pellett, D., Wei, W., Yao, Y., Zhang, F., Bachtis, M., Cousins, R., Datta, A., Avila, G. Flores, Hauser, J., Ignatenko, M., Iqbal, M. A., Lam, T., Manca, E., Prado, A. Nunez Del, Saltzberg, D., Valuev, V., Clare, R., Gary, J. W., Gordon, M., Hanson, G., Si, W., Wimpenny, S., Branson, J. G., Cittolin, S., Cooperstein, S., Diaz, D., Duarte, J., Giannini, L., Guiang, J., Kansal, R., Krutelyov, V., Lee, R., Letts, J., Masciovecchio, M., Mokhtar, F., Mukherjee, S., Pieri, M., Quinnan, M., Narayanan, B. V. Sathia, Sharma, V., Tadel, M., Vourliotis, E., Würthwein, F., Xiang, Y., Yagil, A., Barzdukas, A., Brennan, L., Campagnari, C., Incandela, J., Kim, J., Li, A. J., Masterson, P., Mei, H., Richman, J., Sarica, U., Schmitz, R., Setti, F., Sheplock, J., Stuart, D., Vámi, T. Á., Wang, S., Bornheim, A., Cerri, O., Latorre, A., Mao, J., Newman, H. B., Spiropulu, M., Vlimant, J. R., Wang, C., Xie, S., Zhu, R. Y., Alison, J., An, S., Andrews, M. B., Bryant, P., Cremonesi, M., Dutta, V., Ferguson, T., Harilal, A., Liu, C., Mudholkar, T., Murthy, S., Palit, P., Paulini, M., Roberts, A., Sanchez, A., Terrill, W., Cumalat, J. P., Ford, W. T., Hart, A., Hassani, A., Karathanasis, G., MacDonald, E., Manganelli, N., Perloff, A., Savard, C., Schonbeck, N., Stenson, K., Ulmer, K. A., Wagner, S. R., Zipper, N., Alexander, J., Bright-Thonney, S., Chen, X., Cranshaw, D. J., Fan, J., Fan, X., Gadkari, D., Hogan, S., Kotamnives, P., Monroy, J., Oshiro, M., Patterson, J. R., Reichert, J., Reid, M., Ryd, A., Thom, J., Wittich, P., Zou, R., Albrow, M., Alyari, M., Amram, O., Apollinari, G., Apresyan, A., Bauerdick, L. A. T., Berry, D., Berryhill, J., Bhat, P. C., Burkett, K., Butler, J. N., Canepa, A., Cerati, G. B., Cheung, H. W. K., Chlebana, F., Cummings, G., Dickinson, J., Dutta, I., Elvira, V. D., Feng, Y., Freeman, J., Gandrakota, A., Gecse, Z., Gray, L., Green, D., Grummer, A., Grünendahl, S., Guerrero, D., Gutsche, O., Harris, R. M., Heller, R., Herwig, T. C., Hirschauer, J., Horyn, L., Jayatilaka, B., Jindariani, S., Johnson, M., Joshi, U., Klijnsma, T., Klima, B., Kwok, K. H. M., Lammel, S., Lincoln, D., Lipton, R., Liu, T., Madrid, C., Maeshima, K., Mantilla, C., Mason, D., McBride, P., Merkel, P., Mrenna, S., Nahn, S., Ngadiuba, J., Noonan, D., Papadimitriou, V., Pastika, N., Pedro, K., Pena, C., Ravera, F., Hall, A. Reinsvold, Ristori, L., Sexton-Kennedy, E., Smith, N., Soha, A., Spiegel, L., Stoynev, S., Strait, J., Taylor, L., Tkaczyk, S., Tran, N. V., Uplegger, L., Vaandering, E. W., Zoi, I., Aruta, C., Avery, P., Bourilkov, D., Cadamuro, L., Chang, P., Cherepanov, V., Field, R. D., Koenig, E., Kolosova, M., Konigsberg, J., Korytov, A., Matchev, K., Menendez, N., Mitselmakher, G., Mohrman, K., Madhu, A. Muthirakalayil, Rawal, N., Rosenzweig, D., Rosenzweig, S., Wang, J., Adams, T., Kadhim, A. Al, Askew, A., Bower, S., Habibullah, R., Hagopian, V., Hashmi, R., Kim, R. S., Kim, S., Kolberg, T., Martinez, G., Prosper, H., Prova, P. R., Wulansatiti, M., Yohay, R., Zhang, J., Alsufyani, B., Baarmand, M. M., Butalla, S., Elkafrawy, T., Hohlmann, M., Verma, R. Kumar, Rahmani, M., Yanes, E., Adams, M. R., Baty, A., Bennett, C., Cavanaugh, R., Franco, R. Escobar, Evdokimov, O., Gerber, C. E., Hofman, D. J., Lee, J.h., Lemos, D. S., Merrit, A. H., Mills, C., Nanda, S., Oh, G., Ozek, B., Pilipovic, D., Pradhan, R., Roy, T., Rudrabhatla, S., Tonjes, M. B., Varelas, N., Ye, Z., Yoo, J., Alhusseini, M., Blend, D., Dilsiz, K., Emediato, L., Karaman, G., Köseyan, O. K., Merlo, J.-P., Mestvirishvili, A., Nachtman, J., Neogi, O., Ogul, H., Onel, Y., Penzo, A., Snyder, C., Tiras, E., Blumenfeld, B., Corcodilos, L., Davis, J., Gritsan, A. V., Kang, L., Kyriacou, S., Maksimovic, P., Roguljic, M., Roskes, J., Sekhar, S., Swartz, M., Abreu, A., Alcerro, L. F. Alcerro, Anguiano, J., Baringer, P., Bean, A., Flowers, Z., Grove, D., King, J., Krintiras, G., Lazarovits, M., Mahieu, C. Le, Marquez, J., Minafra, N., Murray, M., Nickel, M., Pitt, M., Popescu, S., Rogan, C., Royon, C., Salvatico, R., Sanders, S., Smith, C., Wang, Q., Wilson, G., Allmond, B., Ivanov, A., Kaadze, K., Kalogeropoulos, A., Kim, D., Maravin, Y., Natoli, J., Roy, D., Sorrentino, G., Rebassoo, F., Wright, D., Baden, A., Belloni, A., Chen, Y. M., Eno, S. C., Hadley, N. J., Jabeen, S., Kellogg, R. G., Koeth, T., Lai, Y., Lascio, S., Mignerey, A. C., Nabili, S., Palmer, C., Papageorgakis, C., Paranjpe, M. M., Wang, L., Bendavid, J., Cali, I. A., D’Alfonso, M., Eysermans, J., Freer, C., Gomez-Ceballos, G., Goncharov, M., Grosso, G., Harris, P., Hoang, D., Kovalskyi, D., Krupa, J., Lavezzo, L., Lee, Y.-J., Long, K., Novak, A., Paus, C., Rankin, D., Roland, C., Roland, G., Rothman, S., Stephans, G. S. F., Wang, Z., Wyslouch, B., Yang, T. J., Crossman, B., Joshi, B. M., Kapsiak, C., Krohn, M., Mahon, D., Mans, J., Marzocchi, B., Pandey, S., Revering, M., Rusack, R., Saradhy, R., Schroeder, N., Strobbe, N., Wadud, M. A., Cremaldi, L. M., Bloom, K., Claes, D. R., Haza, G., Hossain, J., Joo, C., Kravchenko, I., Siado, J. E., Tabb, W., Vagnerini, A., Wightman, A., Yan, F., Yu, D., Bandyopadhyay, H., Hay, L., Iashvili, I., Kharchilava, A., Morris, M., Nguyen, D., Rappoccio, S., Sfar, H. Rejeb, Williams, A., Alverson, G., Barberis, E., Dervan, J., Haddad, Y., Han, Y., Krishna, A., Li, J., Lu, M., Madigan, G., Mccarthy, R., Morse, D. M., Nguyen, V., Orimoto, T., Parker, A., Skinnari, L., Wang, B., Wood, D., Bhattacharya, S., Bueghly, J., Chen, Z., Dittmer, S., Hahn, K. A., Liu, Y., Miao, Y., Monk, D. G., Schmitt, M. H., Taliercio, A., Velasco, M., Agarwal, G., Band, R., Bucci, R., Castells, S., Das, A., Goldouzian, R., Hildreth, M., Ho, K. W., Anampa, K. Hurtado, Ivanov, T., Jessop, C., Lannon, K., Lawrence, J., Loukas, N., Lutton, L., Mariano, J., Marinelli, N., Mcalister, I., McCauley, T., Mcgrady, C., Moore, C., Musienko, Y., Nelson, H., Osherson, M., Piccinelli, A., Ruchti, R., Townsend, A., Wan, Y., Wayne, M., Yockey, H., Zarucki, M., Zygala, L., Basnet, A., Bylsma, B., Carrigan, M., Durkin, L. S., Hill, C., Joyce, M., Ornelas, M. Nunez, Wei, K., Winer, B. L., Yates, B. R., Addesa, F. M., Bouchamaoui, H., Das, P., Dezoort, G., Elmer, P., Frankenthal, A., Greenberg, B., Haubrich, N., Kopp, G., Kwan, S., Lange, D., Loeliger, A., Marlow, D., Ojalvo, I., Olsen, J., Shevelev, A., Stickland, D., Tully, C., Malik, S., Bakshi, A. S., Barnes, V. E., Chandra, S., Chawla, R., Das, S., Gu, A., Gutay, L., Jones, M., Jung, A. W., Kondratyev, D., Koshy, A. M., Liu, M., Negro, G., Neumeister, N., Paspalaki, G., Piperov, S., Scheurer, V., Schulte, J. F., Stojanovic, M., Thieman, J., Virdi, A. K., Wang, F., Xie, W., Dolen, J., Parashar, N., Pathak, A., Acosta, D., Carnahan, T., Ecklund, K. M., Manteca, P. J. Fernández, Freed, S., Gardner, P., Geurts, F. J. M., Li, W., Colin, O. Miguel, Padley, B. P., Redjimi, R., Rotter, J., Yigitbasi, E., Zhang, Y., Bodek, A., de Barbaro, P., Demina, R., Dulemba, J. L., Garcia-Bellido, A., Hindrichs, O., Khukhunaishvili, A., Parmar, N., Parygin, P., Popova, E., Taus, R., Goulianos, K., Chiarito, B., Chou, J. P., Gershtein, Y., Halkiadakis, E., Heindl, M., Houghton, C., Jaroslawski, D., Karacheban, O., Laflotte, I., Lath, A., Montalvo, R., Nash, K., Routray, H., Salur, S., Schnetzer, S., Somalwar, S., Stone, R., Thayil, S. A., Thomas, S., Vora, J., Wang, H., Acharya, H., Ally, D., Delannoy, A. G., Fiorendi, S., Higginbotham, S., Holmes, T., Kanuganti, A. R., Karunarathna, N., Lee, L., Nibigira, E., Spanier, S., Aebi, D., Ahmad, M., Bouhali, O., Eusebi, R., Gilmore, J., Huang, T., Kamon, T., Kim, H., Luo, S., Mueller, R., Overton, D., Rathjens, D., Safonov, A., Akchurin, N., Damgov, J., Hegde, V., Hussain, A., Kazhykarim, Y., Lamichhane, K., Lee, S. W., Mankel, A., Peltola, T., Volobouev, I., Whitbeck, A., Appelt, E., Chen, Y., Greene, S., Gurrola, A., Johns, W., Elayavalli, R. Kunnawalkam, Melo, A., Romeo, F., Sheldon, P., Tuo, S., Velkovska, J., Viinikainen, J., Cardwell, B., Cox, B., Hakala, J., Hirosky, R., Ledovskoy, A., Neu, C., Lara, C. E. Perez, Karchin, P. E., Aravind, A., Banerjee, S., Black, K., Bose, T., Dasu, S., De Bruyn, I., Everaerts, P., Galloni, C., He, H., Herndon, M., Herve, A., Koraka, C. K., Lanaro, A., Loveless, R., Sreekala, J. Madhusudanan, Mallampalli, A., Mohammadi, A., Mondal, S., Parida, G., Pétré, L., Pinna, D., Savin, A., Shang, V., Sharma, V., Smith, W. H., Teague, D., Tsoi, H. F., Vetens, W., Warden, A., Afanasiev, S., Andreev, V., Andreev, Yu., Aushev, T., Azarkin, M., Babaev, A., Belyaev, A., Blinov, V., Boos, E., Borshch, V., Budkouski, D., Chadeeva, M., Chekhovsky, V., Chistov, R., Demiyanov, A., Dermenev, A., Dimova, T., Druzhkin, D., Dubinin, M., Dudko, L., Ershov, A., Gavrilov, G., Gavrilov, V., Gninenko, S., Golovtcov, V., Golubev, N., Golutvin, I., Gorbunov, I., Gribushin, A., Ivanov, Y., Kachanov, V., Karjavine, V., Karneyeu, A., Kim, V., Kirakosyan, M., Kirpichnikov, D., Kirsanov, M., Klyukhin, V., Kodolova, O., Korenkov, V., Kozyrev, A., Krasnikov, N., Lanev, A., Levchenko, P., Lychkovskaya, N., Makarenko, V., Malakhov, A., Matveev, V., Murzin, V., Nikitenko, A., Obraztsov, S., Oreshkin, V., Palichik, V., Perelygin, V., Petrushanko, S., Polikarpov, S., Popov, V., Radchenko, O., Savina, M., Savrin, V., Shalaev, V., Shmatov, S., Shulha, S., Skovpen, Y., Slabospitskii, S., Smirnov, V., Snigirev, A., Sosnov, D., Sulimov, V., Tcherniaev, E., Terkulov, A., Teryaev, O., Tlisova, I., Toropin, A., Uvarov, L., Uzunian, A., Vorobyev, A., Voytishin, N., Yuldashev, B. S., Zarubin, A., Zhizhin, I., and Zhokin, A.

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2024
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42. Discovery of an embryonically derived bipotent population of endothelial-macrophage progenitor cells in postnatal aorta

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Williamson, Anna E., Liyanage, Sanuri, Hassanshahi, Mohammadhossein, Dona, Malathi S. I., Toledo-Flores, Deborah, Tran, Dang X. A., Dimasi, Catherine, Schwarz, Nisha, Fernando, Sanuja, Salagaras, Thalia, Long, Aaron, Kazenwadel, Jan, Harvey, Natasha L., Drummond, Grant R., Vinh, Antony, Chandrakanthan, Vashe, Misra, Ashish, Neufeld, Zoltan, Tan, Joanne T. M., Martelotto, Luciano, Polo, Jose M., Bonder, Claudine S., Pinto, Alexander R., Sharma, Shiwani, Nicholls, Stephen J., Bursill, Christina A., and Psaltis, Peter J.

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2024
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44. Creation of an international laboratory network towards global microplastics monitoring harmonisation

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Bakir, Adil, McGoran, Alexandra R., Silburn, Briony, Russell, Josie, Nel, Holly, Lusher, Amy L., Amos, Ruth, Shadrack, Ronick S., Arnold, Shareen J., Castillo, Cecy, Urbina, Joaquin F., Barrientos, Eduardo, Sanchez, Henry, Pillay, Keshnee, Human, Lucienne, Swartbooi, Tarryn, Cordova, Muhammad Reza, Sani, Sofia Yuniar, Wijesinghe, T. W. A. Wasantha, Amarathunga, A. A. Deeptha, Gunasekara, Jagath, Somasiri, Sudarshana, Mahatantila, Kushani, Liyanage, Sureka, Müller, Moritz, Hee, Yet Yin, Onda, Deo Florence, Jansar, Khairiatul Mardiana, Shiraz, Zana, Amir, Hana, and Mayes, Andrew G.

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