Search

Your search keyword '"Emmert A"' showing total 5,217 results
Start Over Author "Emmert A" Publication Year Range Last 10 years

Refine your results

5,217 results on '"Emmert A"'

1. Flying through Moving Gates without Full State Estimation

Author

Römer, Ralf, Emmert, Tim, and Schoellig, Angela P.

Subjects
Computer Science - Robotics
Abstract

Autonomous drone racing requires powerful perception, planning, and control and has become a benchmark and test field for autonomous, agile flight. Existing work usually assumes static race tracks with known maps, which enables offline planning of time-optimal trajectories, performing localization to the gates to reduce the drift in visual-inertial odometry (VIO) for state estimation or training learning-based methods for the particular race track and operating environment. In contrast, many real-world tasks like disaster response or delivery need to be performed in unknown and dynamic environments. To close this gap and make drone racing more robust against unseen environments and moving gates, we propose a control algorithm that does not require a race track map or VIO and uses only monocular measurements of the line of sight (LOS) to the gates. For this purpose, we adopt the law of proportional navigation (PN) to accurately fly through the gates despite gate motions or wind. We formulate the PN-informed vision-based control problem for drone racing as a constrained optimization problem and derive a closed-form optimal solution. We demonstrate through extensive simulations and real-world experiments that our method can navigate through moving gates at high speeds while being robust to different gate movements, model errors, wind, and delays., Comment: 7 pages, 6 figures

Published
2024

2. Hyperspectral Image Reconstruction for Predicting Chick Embryo Mortality Towards Advancing Egg and Hatchery Industry

Author

Ahmed, Md. Toukir, Ahmed, Md Wadud, Monjur, Ocean, Emmert, Jason Lee, Chowdhary, Girish, and Kamruzzaman, Mohammed

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

As the demand for food surges and the agricultural sector undergoes a transformative shift towards sustainability and efficiency, the need for precise and proactive measures to ensure the health and welfare of livestock becomes paramount. In the context of the broader agricultural landscape outlined, the application of Hyperspectral Imaging (HSI) takes on profound significance. HSI has emerged as a cutting-edge, non-destructive technique for fast and accurate egg quality analysis, including the detection of chick embryo mortality. However, the high cost and operational complexity compared to conventional RGB imaging are significant bottlenecks in the widespread adoption of HSI technology. To overcome these hurdles and unlock the full potential of HSI, a promising solution is hyperspectral image reconstruction from standard RGB images. This study aims to reconstruct hyperspectral images from RGB images for non-destructive early prediction of chick embryo mortality. Firstly, the performance of different image reconstruction algorithms, such as HRNET, MST++, Restormer, and EDSR were compared to reconstruct the hyperspectral images of the eggs in the early incubation period. Later, the reconstructed spectra were used to differentiate live from dead chick-producing eggs using the XGBoost and Random Forest classification methods. Among the reconstruction methods, HRNET showed impressive reconstruction performance with MRAE of 0.0955, RMSE of 0.0159, and PSNR of 36.79 dB. This study motivated that harnessing imaging technology integrated with smart sensors and data analytics has the potential to improve automation, enhance biosecurity, and optimize resource management towards sustainable agriculture 4.0., Comment: Under review

Published
2024
Full Text
View/download PDF

3. A Nonhydrostatic Mass-Conserving Dynamical Core for Deep Atmospheres of Variable Composition

Author

Kelly, James F., Alves, Felipe A. V. de Bragança, Eckermann, Stephen D., Giraldo, Francis X., Reinecke, P. Alex, and Emmert, John T.

Subjects
Physics - Atmospheric and Oceanic Physics
Abstract

This paper develops and tests a deep-atmosphere, nonhydrostatic dynamical core (DyCore) targeted towards ground-thermosphere atmospheric prediction using the spectral element method (SEM) with Implicit-Explicit (IMEX) and Horizontally Explicit Vertically Implicit (HEVI) time-integration. Two versions of the DyCore are presented and tested, each based on a different formulation of the specific internal energy and continuity equations, which, unlike standard potential temperature formulations, are valid for variable composition atmospheres. The first version, which uses a product-rule (PR) forms of the continuity and specific internal energy equation, contains an additional pressure dilation term and does not conserve mass. The second version, which does not use the product-rule (no-PR) in the continuity and specific internal energy, contains two terms to represent pressure dilation and conserves mass to machine precision regardless of time truncation error. The pressure gradient and gravitational forces in the momentum balance equation are reformulated to reduce numerical errors at high altitudes. These new equation sets were implemented in two SEM-based atmospheric models: the Nonhydrostatic Unified Model of the Atmosphere (NUMA) and the Navy Environmental Prediction sysTem Using a Nonhydrostatic Engine (NEPTUNE). Numerical results using both a deep-atmosphere and shallow-atmosphere baroclinic instability, a balanced zonal flow, and a high-altitude orographic gravity wave verify the fidelity of the dynamics at low and high altitudes and for constant and variable composition atmospheres. These results are compared to existing deep-atmosphere dynamical cores and a Fourier-ray code, indicating that the proposed discretized equation sets are viable DyCore candidates for next-generation ground-to-thermosphere atmospheric models., Comment: 37 pages, 14 figures, preprint

Published
2024

6. The Artificial Neural Twin -- Process Optimization and Continual Learning in Distributed Process Chains

Author

Emmert, Johannes, Mendez, Ronald, Dastjerdi, Houman Mirzaalian, Syben, Christopher, and Maier, Andreas

Subjects
Computer Science - Machine Learning, I.2.11, J.2, F.2.2
Abstract

Industrial process optimization and control is crucial to increase economic and ecologic efficiency. However, data sovereignty, differing goals, or the required expert knowledge for implementation impede holistic implementation. Further, the increasing use of data-driven AI-methods in process models and industrial sensory often requires regular fine-tuning to accommodate distribution drifts. We propose the Artificial Neural Twin, which combines concepts from model predictive control, deep learning, and sensor networks to address these issues. Our approach introduces differentiable data fusion to estimate the state of distributed process steps and their dependence on input data. By treating the interconnected process steps as a quasi neural-network, we can backpropagate loss gradients for process optimization or model fine-tuning to process parameters or AI models respectively. The concept is demonstrated on a virtual machine park simulated in Unity, consisting of bulk material processes in plastic recycling., Comment: 20 pages, 11 figures

Published
2024
Full Text
View/download PDF

7. THz spectroscopy on amino acids

Author

Emmert, Sebastian, Lunkenheimer, Peter, and Loidl, Alois

Subjects
Condensed Matter - Materials Science
Abstract

We present a detailed study on the temperature-dependent THz spectra of the polycrystalline amino acids L-serine and L-cysteine for wave numbers from 20 to 120 cm-1 and temperatures from 4 to 300 K. Even though the structure of these two amino acids is very similar, with a sulfur atom in the side chain of cysteine instead of an oxygen atom in serine, the excitation spectra are drastically different. Obviously, the vibrational dynamics strongly depend on the ability of cysteine to form sulfur-hydrogen bonds. In addition, cysteine undergoes an order-disorder type phase transition close to 80 K, with accompanying anomalies in our THz results. On increasing temperatures, well-defined vibrational excitations, exhibit significant shifts in eigenfrequencies with concomitant line-broadening yielding partly overlapping modes. Interestingly, several modes completely lose all their dipolar strength and are unobservable at ambient conditions. Comparing the recent results with published work utilizing THz, Raman, and neutron-scattering techniques, as well as with ab-initio simulations, we aim at a consistent analysis of the results ascribing certain eigenfrequencies to distinct collective lattice modes. We document that THz spectra can be used to fine-tune parameters of model calculations and as a fingerprint property of certain amino acids. In addition, we analyzed the temperature-dependent heat capacity of both compounds and detected strong excess heat capacities at low temperatures compared to the canonical Debye behavior of crystalline solids, indicating soft excitations and a strongly enhanced phonon-density of states at low frequencies., Comment: 31 pages, 8 figures, 70 references

Published
2023

10. Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study

Author

Hinchliffe, Chloe, Rehman, Rana Zia Ur, Pinaud, Clemence, Branco, Diogo, Jackson, Dan, Ahmaniemi, Teemu, Guerreiro, Tiago, Chatterjee, Meenakshi, Manyakov, Nikolay V., Pandis, Ioannis, Davies, Kristen, Macrae, Victoria, Aufenberg, Svenja, Paulides, Emma, Hildesheim, Hanna, Kudelka, Jennifer, Emmert, Kirsten, Van Gassen, Geert, Rochester, Lynn, van der Woude, C. Janneke, Reilmann, Ralf, Maetzler, Walter, Ng, Wan-Fai, and Del Din, Silvia

Published
2024
Full Text
View/download PDF

16. Quality-assured treatment in certified cancer center networks in upper Franconia, Germany: a population-centered retrospective cohort analysis based on data of the Bavarian cancer registry

Author

Martin Emmert, Ingrid Gorodiscan, Andrea Thater, Doris Buchner, Alexander Kiani, Jacqueline Müller-Nordhorn, and Stefan Rohrbacher

Subjects
Cancer treatment, Certified cancer center, Patient-centered care, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Cancer is the second most common cause of death in Germany, and treatment in certified cancer networks is recommended to ensure high-quality care. This study sought to (1) determine the percentage of all primary tumors that might potentially have been treated in certified cancer networks and (2) assess the development and current state of quality-assured cancer care for all cancer patients from a locally defined region in Upper Franconia, Germany. Methods This study was a population-centered retrospective cohort analysis based on data from the Bavarian Cancer Registry (2017–2023). First, we determined all potentially available cancer network certifications and calculated the percentage of cancer care that could potentially have been conducted in certified cancer networks. Second, we considered the certification status of the involved healthcare providers and analyzed whether or not cancer care was actually carried out in certified cancer networks. Results Overall, 90.1% (62,119/68,973) of all primary tumors, from a total of 63,372 patients, might potentially have been treated in certified cancer networks. The percentage of patients actually receiving care in certified cancer center networks was 40.7% for initial diagnosis, 59.0% for surgery, 53.2% for chemotherapy, and 50.7% for radiotherapy; the weighted mean was 50.3%. The results thus ranged between 46.9% (2023) and 52.8% (2022). The highest proportions of patients who received quality-assured treatment in certified cancer center networks were determined for breast cancer (79.5%), colon cancer (73.1%), and lymphoma (60.1%); in contrast, the lowest results were shown for lung cancer (2.7%), anal cancer (0.0%), and mesothelioma (0.0%). Female patients as well as younger patients were significantly more likely to receive care in certified care networks compared with their counterparts. In addition, we did not find a clear trend whether patients in different tumor stages were more or less likely to receive care in certified care networks. Conclusions We found meaningful differences in the proportion of patients who received quality-assured treatment in certified cancer center networks. Following this, patients should receive comprehensive information about receiving care in certified cancer center networks and consider longer travel distances, especially for those cancer types without locally available certified cancer networks.

Published
2024
Full Text
View/download PDF

17. The solenoidal large intensity device (SoLID) for JLab 12 GeV

Author

Arrington, J, Benesch, J, Camsonne, A, Caylor, J, Chen, J-P, Dusa, S Covrig, Emmert, A, Evans, G, Gao, H, Hansen, J-O, Huber, GM, Joosten, S, Khachatryan, V, Liyanage, N, Meziani, Z-E, Nycz, M, Peng, C, Paolone, M, Seay, W, Souder, PA, Sparveris, N, Spiesberger, H, Tian, Y, Voutier, E, Xie, J, Xiong, W, Ye, Z-Y, Ye, Z, Zhang, J, Zhao, Z-W, Zheng, X, and Collaboration, For the Jefferson Lab SoLID

Subjects
Nuclear and Plasma Physics, Particle and High Energy Physics, Synchrotrons and Accelerators, Physical Sciences, quantum chromodynamics, 3D imaging, transverse momentum distributions, parity violation deep inelastic scattering, standard model, proton gluonic gravitational form factors, J/& psi, electro- and photoproduction, Atomic, Molecular, Nuclear, Particle and Plasma Physics, Nuclear & Particles Physics, Nuclear and plasma physics, Particle and high energy physics
Abstract

The solenoidal large intensity device (SoLID) is a new experimental apparatus planned for Hall A at the Thomas Jefferson National Accelerator Facility (JLab). SoLID will combine large angular and momentum acceptance with the capability to handle very high data rates at high luminosity. With a slate of approved high-impact physics experiments, SoLID will push JLab to a new limit at the QCD intensity frontier that will exploit the full potential of its 12 GeV electron beam. In this paper, we present an overview of the rich physics program that can be realized with SoLID, which encompasses the tomography of the nucleon in 3D momentum space from semi-inclusive deep inelastic scattering, expanding the phase space in the search for new physics and novel hadronic effects in parity-violating DIS, a precision measurement of J/ψ production at threshold that probes the gluon field and its contribution to the proton mass, tomography of the nucleon in combined coordinate and momentum space with deep exclusive reactions, and more. To meet the challenging requirements, the design of SoLID described here takes full advantage of recent progress in detector, data acquisition and computing technologies. In addition, we outline potential experiments beyond the currently approved program and discuss the physics that could be explored should upgrades of CEBAF become a reality in the future.

Published
2023

19. Strong Interaction Physics at the Luminosity Frontier with 22 GeV Electrons at Jefferson Lab

Author

Accardi, A., Achenbach, P., Adhikari, D., Afanasev, A., Akondi, C. S., Akopov, N., Albaladejo, M., Albataineh, H., Albrecht, M., Almeida-Zamora, B., Amaryan, M., Androić, D., Armstrong, W., Armstrong, D. S., Arratia, M., Arrington, J., Asaturyan, A., Austregesilo, A., Avagyan, H., Averett, T., Gayoso, C. Ayerbe, Bacchetta, A., Balantekin, A. B., Baltzell, N., Barion, L., Barry, P. C., Bashir, A., Battaglieri, M., Bellini, V., Belov, I., Benhar, O., Benkel, B., Benmokhtar, F, Bentz, W., Bertone, V., Bhatt, H., Bianconi, A., Bibrzycki, L., Bijker, R., Binosi, D., Biswas, D., Boër, M., Boeglin, W., Bogacz, S. A., Boglione, M., Bondí, M., Boos, E. E., Bosted, P., Bozzi, G., Brash, E. J., Briceño, R. A., Brindza, P. D., Briscoe, W. J., Brodsky, S. J, Brooks, W. K., Burkert, V. D., Camsonne, A., Cao, T., Cardman, L. S., Carman, D. S., Carpinelli, M, Cates, G. D., Caylor, J., Celentano, A., Celiberto, F. G., Cerutti, M., Chang, Lei, Chatagnon, P., Chen, C., Chen, J-P, Chetry, T., Christopher, A., Christy, E., Chudakov, E., Cisbani, E., Cloët, I. C., Cobos-Martinez, J. J., Cohen, E. O., Colangelo, P., Cole, P. L., Constantinou, M., Contalbrigo, M., Costantini, G., Cosyn, W., Cotton, C., Courtoy, A., Dusa, S. Covrig, Crede, V., Cui, Z. -F., D'Angelo, A., Döring, M., Dalton, M. M., Danilkin, I., Davydov, M., Day, D., De Fazio, F., De Napoli, M., De Vita, R., Dean, D. J., Defurne, M., Deur, A., Devkota, B., Dhital, S., Di Nezza, P., Diefenthaler, M., Diehl, S., Dilks, C., Ding, M., Djalali, C., Dobbs, S., Dupré, R., Dutta, D., Edwards, R. G., Egiyan, H., Ehinger, L., Eichmann, G., Elaasar, M., Elouadrhiri, L., Alaoui, A. El, Fassi, L. El, Emmert, A., Engelhardt, M., Ent, R., Ernst, D. J, Eugenio, P., Evans, G., Fanelli, C., Fegan, S., Fernández-Ramírez, C., Fernandez, L. A., Fernando, I. P., Filippi, A., Fischer, C. S., Fogler, C., Fomin, N., Frankfurt, L., Frederico, T., Freese, A., Fu, Y., Gamberg, L., Gan, L., Gao, F., Garcia-Tecocoatzi, H., Gaskell, D., Gasparian, A., Gates, K, Gavalian, G., Ghoshal, P. K., Giachino, A., Giacosa, F., Giannuzzi, F., Gilfoyle, G. -P., Girod, F-X, Glazier, D. I., Gleason, C., Godfrey, S., Goity, J. L., Golubenko, A. A., Gonzàlez-Solís, S., Gothe, R. W., Gotra, Y., Griffioen, K., Grocholski, O., Grube, B., Guèye, P., Guo, F. -K., Guo, Y., Guo, L., Hague, T. J., Hammoud, N., Hansen, J. -O., Hattawy, M., Hauenstein, F., Hayward, T., Heddle, D., Heinrich, N., Hen, O., Higinbotham, D. W., Higuera-Angulo, I. M., Blin, A. N. Hiller, Hobart, A., Hobbs, T., Holmberg, D. E, Horn, T., Hoyer, P., Huber, G. M., Hurck, P., Hutauruk, P. T. P., Ilieva, Y., Illari, I., Ireland, D. G, Isupov, E. L., Italiano, A., Jaegle, I., Jarvis, N. S., Jenkins, DJ, Jeschonnek, S., Ji, C-R., Jo, H. S., Jones, M., Jones, R. T., Jones, D. C., Joo, K., Junaid, M., Kageya, T., Kalantarians, N., Karki, A., Karyan, G., Katramatou, A. T., Kay, S. J. D, Kazimi, R., Keith, C. D., Keppel, C., Kerbizi, A., Khachatryan, V., Khanal, A., Khandaker, M., Kim, A., Kinney, E. R., Kohl, M., Kotzinian, A., Kriesten, B. T., Kubarovsky, V., Kubis, B., Kuhn, S. E., Kumar, V., Kutz, T., Leali, M., Lebed, R. F., Lenisa, P., Leskovec, L., Li, S., Li, X., Liao, J., Lin, H. -W., Liu, L., Liuti, S., Liyanage, N., Lu, Y., MacGregor, I. J. D., Mack, D. J., Maiani, L, Mamo, K. A., Mandaglio, G., Mariani, C., Markowitz, P., Marukyan, H., Mascagna, V., Mathieu, V., Maxwell, J., Mazouz, M., McCaughan, M., McKeown, R. D., McKinnon, B., Meekins, D., Melnitchouk, W., Metz, A., Meyer, C. A., Meziani, Z. -E., Mezrag, C., Michaels, R., Miller, G. A., Mineeva, T., Miramontes, A. S., Mirazita, M., Mizutani, K., Mkrtchyan, H., Mkrtchyan, A., Moffit, B., Mohanmurthy, P., Mokeev, V. I., Monaghan, P., Montaña, G., Montgomery, R., Moretti, A., Chàvez, J. M. Morgado, Mosel, U., Movsisyan, A., Musico, P., Nadeeshani, S. A, Nadolsky, P. M., Nakamura, S. X., Nazeer, J., Nefediev, A. V., Neupane, K., Nguyen, D., Niccolai, S., Niculescu, I., Niculescu, G., Nocera, E. R., Nycz, M., Olness, F. I., Ortega, P. G., Osipenko, M., Pace, E., Pandey, B, Pandey, P., Papandreou, Z., Papavassiliou, J., Pappalardo, L. L., Paredes-Torres, G., Paremuzyan, R., Park, S., Parsamyan, B., Paschke, K. D., Pasquini, B., Passemar, E., Pasyuk, E., Patel, T., Paudel, C., Paul, S. J., Peng, J-C., Pentchev, L., Perrino, R., Perry, R. J., Peters, K., Petratos, G. G., Phelps, W., Piasetzky, E., Pilloni, A., Pire, B., Pitonyak, D., Pitt, M. L., Polosa, A. D., Pospelov, M., Postuma, A. C., Poudel, J., Preet, L., Prelovsek, S., Price, J. W., Prokudin, A., Puckett, A. J. R., Pybus, J. R., Qin, S. -X., Qiu, J. -W., Radici, M., Rashidi, H., Rathnayake, A. D, Raue, B. A., Reed, T., Reimer, P. E., Reinhold, J., Richard, J. -M., Rinaldi, M., Ringer, F., Ripani, M., Ritman, J., West, J. Rittenhouse, Rivero-Acosta, A., Roberts, C. D., Rodas, A., Rodini, S., Rodríguez-Quintero, J., Rogers, T. C., Rojo, J., Rossi, P., Rossi, G. C., Salmè, G., Santiesteban, S. N., Santopinto, E., Sargsian, M., Sato, N., Schadmand, S., Schmidt, A., Schmidt, S. M, Schnell, G., Schumacher, R. A., Schweitzer, P., Scimemi, I., Scott, K. C, Seay, D. A, Segovia, J., Semenov-Tian-Shansky, K., Seryi, A., Sharda, A. S, Shepherd, M. R., Shirokov, E. V., Shrestha, S., Shrestha, U., Shvedunov, V. I., Signori, A., Slifer, K. J., Smith, W. A., Somov, A., Souder, P., Sparveris, N., Spizzo, F., Spreafico, M., Stepanyan, S., Stevens, J. R., Strakovsky, I. I., Strauch, S., Strikman, M., Su, S., Sumner, B. C. L., Sun, E., Suresh, M., Sutera, C., Swanson, E. S., Szczepaniak, A. P, Sznajder, P., Szumila-Vance, H., Szymanowski, L., Tadepalli, A. -S., Tadevosyan, V., Tamang, B., Tarasov, V. V., Thiel, A., Tong, X. -B., Tyson, R., Ungaro, M., Urciuoli, G. M., Usman, A., Valcarce, A., Vallarino, S., Vaquera-Araujo, C. A., Venturelli, L., Vera, F., Vladimirov, A., Vossen, A., Wagner, J., Wei, X., Weinstein, L. B., Weiss, C., Williams, R., Winney, D., Wojtsekhowski, B., Wood, M. H., Xiao, T., Xu, S. -S., Ye, Z., Yero, C., Yuan, C. -P., Yurov, M., Zachariou, N., Zhang, Z., Zhao, Z. W., Zhao, Y., Zheng, X., Zhou, X., Ziegler, V., Zihlmann, B., de Paula, W, and de Téramond, G. F.

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

This document presents the initial scientific case for upgrading the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab (JLab) to 22 GeV. It is the result of a community effort, incorporating insights from a series of workshops conducted between March 2022 and April 2023. With a track record of over 25 years in delivering the world's most intense and precise multi-GeV electron beams, CEBAF's potential for a higher energy upgrade presents a unique opportunity for an innovative nuclear physics program, which seamlessly integrates a rich historical background with a promising future. The proposed physics program encompass a diverse range of investigations centered around the nonperturbative dynamics inherent in hadron structure and the exploration of strongly interacting systems. It builds upon the exceptional capabilities of CEBAF in high-luminosity operations, the availability of existing or planned Hall equipment, and recent advancements in accelerator technology. The proposed program cover various scientific topics, including Hadron Spectroscopy, Partonic Structure and Spin, Hadronization and Transverse Momentum, Spatial Structure, Mechanical Properties, Form Factors and Emergent Hadron Mass, Hadron-Quark Transition, and Nuclear Dynamics at Extreme Conditions, as well as QCD Confinement and Fundamental Symmetries. Each topic highlights the key measurements achievable at a 22 GeV CEBAF accelerator. Furthermore, this document outlines the significant physics outcomes and unique aspects of these programs that distinguish them from other existing or planned facilities. In summary, this document provides an exciting rationale for the energy upgrade of CEBAF to 22 GeV, outlining the transformative scientific potential that lies within reach, and the remarkable opportunities it offers for advancing our understanding of hadron physics and related fundamental phenomena., Comment: Updates to the list of authors; Preprint number changed from theory to experiment; Updates to sections 4 and 6, including additional figures

Published
2023

20. Gotcha! I Know What You are Doing on the FPGA Cloud: Fingerprinting Co-Located Cloud FPGA Accelerators via Measuring Communication Links

Author

Fang, Chongzhou, Miao, Ning, Wang, Han, Zhou, Jiacheng, Sheaves, Tyler, Emmert, John M., Sasan, Avesta, and Homayoun, Houman

Subjects
Computer Science - Cryptography and Security
Abstract

In recent decades, due to the emerging requirements of computation acceleration, cloud FPGAs have become popular in public clouds. Major cloud service providers, e.g. AWS and Microsoft Azure have provided FPGA computing resources in their infrastructure and have enabled users to design and deploy their own accelerators on these FPGAs. Multi-tenancy FPGAs, where multiple users can share the same FPGA fabric with certain types of isolation to improve resource efficiency, have already been proved feasible. However, this also raises security concerns. Various types of side-channel attacks targeting multi-tenancy FPGAs have been proposed and validated. The awareness of security vulnerabilities in the cloud has motivated cloud providers to take action to enhance the security of their cloud environments. In FPGA security research papers, researchers always perform attacks under the assumption that attackers successfully co-locate with victims and are aware of the existence of victims on the same FPGA board. However, the way to reach this point, i.e., how attackers secretly obtain information regarding accelerators on the same fabric, is constantly ignored despite the fact that it is non-trivial and important for attackers. In this paper, we present a novel fingerprinting attack to gain the types of co-located FPGA accelerators. We utilize a seemingly non-malicious benchmark accelerator to sniff the communication link and collect performance traces of the FPGA-host communication link. By analyzing these traces, we are able to achieve high classification accuracy for fingerprinting co-located accelerators, which proves that attackers can use our method to perform cloud FPGA accelerator fingerprinting with a high success rate. As far as we know, this is the first paper targeting multi-tenant FPGA accelerator fingerprinting with the communication side-channel., Comment: To be published in ACM CCS 2023

Published
2023
Full Text
View/download PDF

21. Understanding Physics-Informed Neural Networks: Techniques, Applications, Trends, and Challenges

Author

Amer Farea, Olli Yli-Harja, and Frank Emmert-Streib

Subjects
physics-informed neural networks, data-driven modeling, neural network architectures, inverse problems, ordinary differential equations, partial differential equations, Electronic computers. Computer science, QA75.5-76.95
Abstract

Physics-informed neural networks (PINNs) represent a significant advancement at the intersection of machine learning and physical sciences, offering a powerful framework for solving complex problems governed by physical laws. This survey provides a comprehensive review of the current state of research on PINNs, highlighting their unique methodologies, applications, challenges, and future directions. We begin by introducing the fundamental concepts underlying neural networks and the motivation for integrating physics-based constraints. We then explore various PINN architectures and techniques for incorporating physical laws into neural network training, including approaches to solving partial differential equations (PDEs) and ordinary differential equations (ODEs). Additionally, we discuss the primary challenges faced in developing and applying PINNs, such as computational complexity, data scarcity, and the integration of complex physical laws. Finally, we identify promising future research directions. Overall, this survey seeks to provide a foundational understanding of PINNs within this rapidly evolving field.

Published
2024
Full Text
View/download PDF

22. A systematic mapping of public health master’s and structured doctoral programs in Germany

Author

Hanna Saturska, Katrina Kufer, Sara Pedron, Gesa Meyer, Karl Emmert-Fees, Michael Laxy, and Anna-Janina Stephan

Subjects
Public health, Education, Curricula, Doctoral program, Master’s program, MPH programs, Special aspects of education, LC8-6691, Medicine
Abstract

Abstract Background Well-trained public health professionals are key to addressing both global and local public health challenges of the twenty-first century. Though availability of programs has increased, the population health science (PHS) and public health (PH) higher education landscape in Germany remains scattered. To date, no comprehensive overview of programs exists. Objectives This study aimed to map PHS and PH master’s and structured doctoral programs in Germany, including selected program characteristics, curricula and target competencies. Methods We conducted a systematic mapping of PHS and PH programs in Germany following a prospectively registered protocol ( https://doi.org/10.17605/OSF.IO/KTCBA ). Relevant master’s and doctoral programs were identified by two study authors independently searching a comprehensive higher education database, which was, for doctoral programs, supplemented with a google search. For PHS programs, general characteristics were mapped and for the subset of PH programs, in-depth characteristics were extracted. Results Overall, 75 master’s and 18 structured doctoral PHS programs were included. Of these, 23 master’s and 8 doctoral programs focused specifically on PH. The majority of PHS master’s programs awarded a Master of Science degree (55 out of 75 programs). The PH master’s program curricula offered various courses, allowing for different specializations. Courses on topics like public health, epidemiology, health systems (research) and research methods were common for the majority of the master’s programs, while courses on physical activity, behavioral science, nutrition, and mental health were offered less frequently. Structured PH doctoral programs were mainly offered by medical faculties (6 out of 8 programs) and awarded a doctorate of philosophy (Ph.D.) (6 out of 8 programs). PH doctoral programs were very heterogeneous regarding curricula, entry, and publication requirements. There was a broad geographical distribution of programs across Germany, with educational clusters in Munich, Berlin, Bielefeld and Düsseldorf. Conclusion Germany offers a diverse landscape of PHS and PH master’s programs, but only few structured doctoral programs. The variety of mandatory courses and competencies in these programs reflect Germany’s higher education system’s answer to the evolving demands of the PH sector. This review may aid in advancing PH education both in Germany and globally.

Published
2024
Full Text
View/download PDF

23. The implications of policy modeling assumptions for the projected impact of sugar-sweetened beverage taxation on body weight and type 2 diabetes in Germany

Author

Karl M. F. Emmert-Fees, Andreea Felea, Matthias Staudigel, Jaithri Ananthapavan, and Michael Laxy

Subjects
Sugar-sweetened beverages, Health taxation, Simulation modeling, Structural uncertainty, Health policy, Obesity, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Evaluating sugar-sweetened beverage (SSB) taxation often relies on simulation models. We assess how assumptions about the response to SSB taxation affect the projected body weight change and subsequent health and economic impacts related to type 2 diabetes mellitus (T2DM) using Germany as an example. Methods In the main analysis, we estimated changes in energy intake by age and sex under a 20% value-added tax on SSBs in Germany using marginal price elasticities (PE) and applied an energy equilibrium model to predict body weight changes. We then quantified the impact of several assumption modifications: SSB own-PE adjusted for consumption (M1)/based on alternative meta-analysis (M2); SSB consumption adjusted for underreporting (M3); substitution via marginal (M4a) or adjusted (M4b) cross-PE/as % of calorie change (M4c). We also assessed scenarios with alternative tax rates of 10% (S1) or 30% (S2) and including fruit juice (S3). We calculated overweight and obesity rates per modification and scenario. We simulated the impact on T2DM, associated healthcare costs, and disability-adjusted life years (DALYs) over the lifetime of the 2011 German adult population with a Markov model. Data included official demographics, national surveys, and meta-analyses. Results A 20% value-added tax in Germany could reduce the number of men and women with obesity by 210,800 [138,800; 294,100] and 80,800 [45,100; 123,300], respectively. Over the population’s lifetime, this would lead to modest T2DM-related health and economic impacts (76,700 DALYs [42,500; 120,600] averted; €2.37 billion [1.33; 3.71] costs saved). Policy impacts varied highly across modifications (all in DALYs averted): (M1) 94,800 [51,500; 150,700]; (M2) 164,200 [99,500; 243,500]; (M3) 52,600 [22,500; 91,100]; (M4a) -18,100 [-111,500; 68,300]; (M4b) 25,800 [-31,400; 81,500]; (M4c) 46,700 [25,300; 77,200]. The variability in policy impact related to modifications was similar to the variability between alternative policy scenarios (all in DALYs averted): (S1) 26,400 [9,300; 47,600]; (S2) 126,200 [73,600; 194,500]; (S3) 342,200 [234,200; 430,400]. Conclusions Predicted body weight reductions under SSB taxation are sensitive to assumptions by researchers often needed due to data limitations. Because this variability propagates to estimates of health and economic impacts, the resulting structural uncertainty should be considered when using results in decision-making.

Published
2024
Full Text
View/download PDF

24. Strong interaction physics at the luminosity frontier with 22 GeV electrons at Jefferson Lab

Author

Accardi, A., Achenbach, P., Adhikari, D., Afanasev, A., Akondi, C. S., Akopov, N., Albaladejo, M., Albataineh, H., Albrecht, M., Almeida-Zamora, B., Amaryan, M., Androić, D., Armstrong, W., Armstrong, D. S., Arratia, M., Arrington, J., Asaturyan, A., Austregesilo, A., Avakian, H., Averett, T., Gayoso, C. Ayerbe, Bacchetta, A., Balantekin, A. B., Baltzell, N., Barion, L., Barry, P. C., Bashir, A., Battaglieri, M., Bellini, V., Belov, I., Benhar, O., Benkel, B., Benmokhtar, F., Bentz, W., Bertone, V., Bhatt, H., Bianconi, A., Bibrzycki, L., Bijker, R., Binosi, D., Biswas, D., Boër, M., Boeglin, W., Bogacz, S. A., Boglione, M., Bondí, M., Boos, E. E., Bosted, P., Bozzi, G., Brash, E. J., Briceño, R. A., Brindza, P. D., Briscoe, W. J., Brodsky, S. J., Brooks, W. K., Burkert, V. D., Camsonne, A., Cao, T., Cardman, L. S., Carman, D. S., Carpinelli, M., Cates, G. D., Caylor, J., Celentano, A., Celiberto, F. G., Cerutti, M., Chang, L., Chatagnon, P., Chen, C., Chen, J.-P., Chetry, T., Christopher, A., Christy, E., Chudakov, E., Cisbani, E., Cloët, I. C., Cobos-Martinez, J. J., Cohen, E. O., Colangelo, P., Cole, P. L., Constantinou, M., Contalbrigo, M., Costantini, G., Cosyn, W., Cotton, C., Courtoy, A., Dusa, S. Covrig, Crede, V., Cui, Z.-F., D’Angelo, A., Döring, M., Dalton, M. M., Danilkin, I., Davydov, M., Day, D., De Fazio, F., De Napoli, M., De Vita, R., Dean, D. J., Defurne, M., de Paula, W., de Téramond, G. F., Deur, A., Devkota, B., Dhital, S., Di Nezza, P., Diefenthaler, M., Diehl, S., Dilks, C., Ding, M., Djalali, C., Dobbs, S., Dupré, R., Dutta, D., Edwards, R. G., Egiyan, H., Ehinger, L., Eichmann, G., Elaasar, M., Elouadrhiri, L., Alaoui, A. El, Fassi, L. El, Emmert, A., Engelhardt, M., Ent, R., Ernst, D. J., Eugenio, P., Evans, G., Fanelli, C., Fegan, S., Fernández-Ramírez, C., Fernandez, L. A., Fernando, I. P., Filippi, A., Fischer, C. S., Fogler, C., Fomin, N., Frankfurt, L., Frederico, T., Freese, A., Fu, Y., Gamberg, L., Gan, L., Gao, F., Garcia-Tecocoatzi, H., Gaskell, D., Gasparian, A., Gates, K., Gavalian, G., Ghoshal, P. K., Giachino, A., Giacosa, F., Giannuzzi, F., Gilfoyle, G.-P., Girod, F.-X., Glazier, D. I., Gleason, C., Godfrey, S., Goity, J. L., Golubenko, A. A., Gonzàlez-Solís, S., Gothe, R. W., Gotra, Y., Griffioen, K., Grocholski, O., Grube, B., Guèye, P., Guo, F.-K., Guo, Y., Guo, L., Hague, T. J., Hammoud, N., Hansen, J.-O., Hattawy, M., Hauenstein, F., Hayward, T., Heddle, D., Heinrich, N., Hen, O., Higinbotham, D. W., Higuera-Angulo, I. M., Hiller Blin, A. N., Hobart, A., Hobbs, T., Holmberg, D. E., Horn, T., Hoyer, P., Huber, G. M., Hurck, P., Hutauruk, P. T. P., Ilieva, Y., Illari, I., Ireland, D. G., Isupov, E. L., Italiano, A., Jaegle, I., Jarvis, N. S., Jenkins, D. J., Jeschonnek, S., Ji, C.-R., Jo, H. S., Jones, M., Jones, R. T., Jones, D. C., Joo, K., Junaid, M., Kageya, T., Kalantarians, N., Karki, A., Karyan, G., Katramatou, A. T., Kay, S. J. D., Kazimi, R., Keith, C. D., Keppel, C., Kerbizi, A., Khachatryan, V., Khanal, A., Khandaker, M., Kim, A., Kinney, E. R., Kohl, M., Kotzinian, A., Kriesten, B. T., Kubarovsky, V., Kubis, B., Kuhn, S. E., Kumar, V., Kutz, T., Leali, M., Lebed, R. F., Lenisa, P., Leskovec, L., Li, S., Li, X., Liao, J., Lin, H.-W., Liu, L., Liuti, S., Liyanage, N., Lu, Y., MacGregor, I. J. D., Mack, D. J., Maiani, L., Mamo, K. A., Mandaglio, G., Mariani, C., Markowitz, P., Marukyan, H., Mascagna, V., Mathieu, V., Maxwell, J., Mazouz, M., McCaughan, M., McKeown, R. D., McKinnon, B., Meekins, D., Melnitchouk, W., Metz, A., Meyer, C. A., Meziani, Z.-E., Mezrag, C., Michaels, R., Miller, G. A., Mineeva, T., Miramontes, A. S., Mirazita, M., Mizutani, K., Mkrtchyan, A., Mkrtchyan, H., Moffit, B., Mohanmurthy, P., Mokeev, V. I., Monaghan, P., Montaña, G., Montgomery, R., Moretti, A., Chàvez, J. M. Morgado, Mosel, U., Movsisyan, A., Musico, P., Nadeeshani, S. A., Nadolsky, P. M., Nakamura, S. X., Nazeer, J., Nefediev, A. V., Neupane, K., Nguyen, D., Niccolai, S., Niculescu, I., Niculescu, G., Nocera, E. R., Nycz, M., Olness, F. I., Ortega, P. G., Osipenko, M., Pace, E., Pandey, B., Pandey, P., Papandreou, Z., Papavassiliou, J., Pappalardo, L. L., Paredes-Torres, G., Paremuzyan, R., Park, S., Parsamyan, B., Paschke, K. D., Pasquini, B., Passemar, E., Pasyuk, E., Patel, T., Paudel, C., Paul, S. J., Peng, J.-C., Pentchev, L., Perrino, R., Perry, R. J., Peters, K., Petratos, G. G., Phelps, W., Piasetzky, E., Pilloni, A., Pire, B., Pitonyak, D., Pitt, M. L., Polosa, A. D., Pospelov, M., Postuma, A. C., Poudel, J., Preet, L., Prelovsek, S., Price, J. W., Prokudin, A., Puckett, A. J. R., Pybus, J. R., Qin, S.-X., Qiu, J.-W., Radici, M., Rashidi, H., Rathnayake, A. D., Raue, B. A., Reed, T., Reimer, P. E., Reinhold, J., Richard, J.-M., Rinaldi, M., Ringer, F., Ripani, M., Ritman, J., West, J. Rittenhouse, Rivero-Acosta, A., Roberts, C. D., Rodas, A., Rodini, S., Rodríguez-Quintero, J., Rogers, T. C., Rojo, J., Rossi, P., Rossi, G. C., Salmè, G., Santiesteban, S. N., Santopinto, E., Sargsian, M., Sato, N., Schadmand, S., Schmidt, A., Schmidt, S. M., Schnell, G., Schumacher, R. A., Schweitzer, P., Scimemi, I., Scott, K. C., Seay, D. A., Segovia, J., Semenov-Tian-Shansky, K., Seryi, A., Sharda, A. S., Shepherd, M. R., Shirokov, E. V., Shrestha, S., Shrestha, U., Shvedunov, V. I., Signori, A., Slifer, K. J., Smith, W. A., Somov, A., Souder, P., Sparveris, N., Spizzo, F., Spreafico, M., Stepanyan, S., Stevens, J. R., Strakovsky, I. I., Strauch, S., Strikman, M., Su, S., Sumner, B. C. L., Sun, E., Suresh, M., Sutera, C., Swanson, E. S., Szczepaniak, A. P., Sznajder, P., Szumila-Vance, H., Szymanowski, L., Tadepalli, A.-S., Tadevosyan, V., Tamang, B., Tarasov, V. V., Thiel, A., Tong, X.-B., Tyson, R., Ungaro, M., Urciuoli, G. M., Usman, A., Valcarce, A., Vallarino, S., Vaquera-Araujo, C. A., Venturelli, L., Vera, F., Vladimirov, A., Vossen, A., Wagner, J., Wei, X., Weinstein, L. B., Weiss, C., Williams, R., Winney, D., Wojtsekhowski, B., Wood, M. H., Xiao, T., Xu, S.-S., Ye, Z., Yero, C., Yuan, C.-P., Yurov, M., Zachariou, N., Zhang, Z., Zhao, Y., Zhao, Z. W., Zheng, X., Zhou, X., Ziegler, V., and Zihlmann, B.

Published
2024
Full Text
View/download PDF

25. ChatGPT is a promising tool to increase readability of orthopedic research consents

Author

Bissem Gill, John Bonamer, Henry Kuechly, Rajul Gupta, Scottie Emmert, Sarah Kurkowski, Kim Hasselfeld, and Brian Grawe

Subjects
Orthopedic surgery, RD701-811
Abstract

Background/Purpose: Informed consent is a fundamental ethical requirement in medical research, ensuring that participants have a comprehensive understanding of the risks and benefits associated with their participation. Clinical researchers must ensure effective and efficient communication of the implications of participation, but the complexity and length of traditional research consent forms can impede comprehension and create barriers to effective communication between researchers and participants. For this reason, the American Medical Association recommends a 6th grade reading level for all patient-facing medical information. Can the large language model, ChatGPT-3.5, improve readability while simultaneously preserving information necessary for adequate informed consent?. Methods: Nineteen IRB approved Orthopedic surgery research consent forms were entered into ChatGPT with instructions to make the form “readable at a 6th-grade level.” Post ChatGPT consent forms were assessed using commonly used readability metrics. Additionally, a single Orthopedic surgeon who has practiced independently for 15 years assessed the forms for accuracy and retention of imperative informed consent elements. Results: The median differences between pre-ChatGPT and post-ChatGPT were statistically significant for every readability metric (all p

Published
2024
Full Text
View/download PDF

26. Hyperspectral image reconstruction for predicting chick embryo mortality towards advancing egg and hatchery industry

Author

Md. Toukir Ahmed, Md Wadud Ahmed, Ocean Monjur, Jason Lee Emmert, Girish Chowdhary, and Mohammed Kamruzzaman

Subjects
Hyperspectral imaging, Embryo mortality, Agriculture 4.0, Deep learning, Image reconstruction, Classification, Agriculture (General), S1-972, Agricultural industries, HD9000-9495
Abstract

As the demand for food surges and the agricultural sector undergoes a transformative shift towards sustainability and efficiency, the need for precise and proactive measures to ensure the health and welfare of livestock becomes paramount. In the egg and hatchery industry, hyperspectral imaging (HSI) has emerged as a cutting-edge, non-destructive technique for fast and accurate egg quality analysis, including detecting chick embryo mortality. However, the high cost and operational complexity compared to conventional RGB imaging are significant bottlenecks in the widespread adoption of HSI technology. To overcome these hurdles and unlock the full potential of HSI, a promising solution is hyperspectral image reconstruction from standard RGB images. This study aims to reconstruct hyperspectral images from RGB images for non-destructive early prediction of chick embryo mortality. Initially, the performance of different image reconstruction algorithms, such as HRNET, MST++, Restormer, and EDSR were compared to reconstruct the hyperspectral images of the eggs in the early incubation period. Later, the reconstructed spectra were used to differentiate live from dead embryos eggs using the XGBoost and Random Forest classification methods. Among the reconstruction methods, HRNET showed impressive reconstruction performance with MRAE of 0.0955, RMSE of 0.0159, and PSNR of 36.79 dB. This study motivated the idea that harnessing imaging technology integrated with smart sensors and data analytics has the potential to improve automation, enhance biosecurity, and optimize resource management towards sustainable agriculture 4.0.

Published
2024
Full Text
View/download PDF

27. Trends in null hypothesis significance testing: Still going strong

Author

Frank Emmert-Streib

Subjects
Null hypothesis significance testing, Statistical inference, Change-point analysis, Trends, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Null hypothesis significance testing (NHST) is among the most prominent and widely used methods for analyzing data. At the same time, NHST has been criticized since many years because of misuses and misconceptions that can be found extensively in the scholarly literature. Furthermore, in recent years, NHST has been identified as one reason for the replication crisis because many studies place too much emphasis on statistical significance for drawing conclusions. As a response to those problems, calls for actions have been raised, among others by the American Statistical Association (ASA), to rectify these issues, for instance, by modifying or even abandoning NHST. In this paper, we study the reaction of the community on these discussions. Specifically, we conduct a scientometric analysis of bibliographic records to investigate the publication behavior about the usage of NHST. We conduct a trend analysis for the general community, for specific subject areas and for individual journals. Furthermore, we conduct a change-point analysis to investigate if there are continued movements or actual changes. As a result, we find that for the general community NHST is more popular than ever, however, for particular subject-areas and journals there is a clear heterogeneity and no uniform publication behavior is observable.

Published
2024
Full Text
View/download PDF

28. National health and economic impact of a lifestyle program to prevent type 2 diabetes mellitus in Germany: a simulation study

Author

Ping Zhang, Andrea Icks, Michael Laxy, Karl Emmert-Fees, Katherine Ogurtsova, and Charalabos-Markos Dintsios

Subjects
Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

Introduction To examine the long-term health and economic impact of a lifestyle diabetes prevention program in people with high risk of developing type 2 diabetes in Germany.Research design and methods We assessed the lifetime cost-effectiveness of a 2-year pragmatic lifestyle program for preventing type 2 diabetes targeting German adults aged 35–54 and 55–74 years old with hemoglobin A1c (HbA1c) from 6.0% to 6.4%. We used the Centers for Disease Control and Prevention RTI Diabetes Cost-Effectiveness Model to run a simulation on the program effectiveness. We estimated incremental health benefits in quality-adjusted life years (QALYs) and costs using an established simulation model adapted to the German context, from a healthcare system and societal perspective. The cost-effectiveness of the program was measured by incremental cost-effectiveness ratios (ICERs) in cost per QALY. We projected the number of type 2 diabetes cases prevented by participation rate if the program was implemented nationwide.Results The lifestyle program would result to more QALYs and higher costs. The lifetime ICERs were 14 690€ (35–54 years old) and 14 372€ (55–74 years old) from a healthcare system perspective and cost saving (ICER=−3805€) and cost-effective (ICER=4579€), respectively, from a societal perspective. A total of 10 527 diabetes cases would be prevented over lifetime if the program was offered to all eligible people nationwide and 25% of those would participate in the program.Conclusions Implementing the lifestyle intervention for people with HbA1c from 6.0% to 6.4% could be a cost-effective at standard willingness to pay level strategy for type 2 diabetes prevention. The intervention in the younger cohort could be cost saving from a societal perspective. The successful implementation of a lifestyle-based diabetes prevention program could be an important component of a successful National Diabetes Strategy in Germany.

Published
2024
Full Text
View/download PDF

32. Addressing food insecurity and chronic conditions in community health centres: protocol of a quasi-experimental evaluation of Recipe4Health

Author

Rosas, Lisa G, Chen, Steven, Xiao, Lan, Emmert-Aronson, Benjamin O, Chen, Wei-ting, Ng, Elliot, Martinez, Erica, Baiocchi, Mike, Thompson-Lastad, Ariana, Markle, Elizabeth A, and Tester, June

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Public Health, Health Sciences, Diabetes, Obesity, Mental Health, Clinical Trials and Supportive Activities, Clinical Research, Health Services, Behavioral and Social Science, Depression, Patient Safety, Nutrition, Prevention, Prevention of disease and conditions, and promotion of well-being, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, Generic health relevance, Zero Hunger, Good Health and Well Being, Humans, Delivery of Health Care, Food Insecurity, Chronic Disease, Community Health Centers, PRIMARY CARE, PUBLIC HEALTH, NUTRITION & DIETETICS, Clinical Sciences, Public Health and Health Services, Other Medical and Health Sciences, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

IntroductionChronic conditions, such as diabetes, obesity, heart disease and depression, are highly prevalent and frequently co-occur with food insecurity in communities served by community health centres in the USA. Community health centres are increasingly implementing 'Food as Medicine' programmes to address the dual challenge of chronic conditions and food insecurity, yet they have been infrequently evaluated.Methods and analysisThe goal of this quasi-experimental study was to evaluate the effectiveness of Recipe4Health, a 'Food as Medicine' programme. Recipe4Health includes two components: (1) a 'Food Farmacy' that includes 16 weekly deliveries of produce and (2) a 'Behavioural Pharmacy' which is a group medical visit. We will use mixed models to compare pre/post changes among participants who receive the Food Farmacy alone (n=250) and those who receive the Food Farmacy and Behavioural Pharmacy (n=140). The primary outcome, fruit and vegetable consumption, and secondary outcomes (eg, food security status, physical activity, depressive symptoms) will be collected via survey. We will also use electronic health record (EHR) data on laboratory values, prescriptions and healthcare usage. Propensity score matching will be used to compare Recipe4Health participants to a control group of patients in clinics where Recipe4Health has not been implemented for EHR-derived outcomes. Data from surveys, EHR, group visit attendance and produce delivery is linked with a common identifier (medical record number) and then deidentified for analysis with use of an assigned unique study ID. This study will provide important preliminary evidence on the effectiveness of primary care-based strategies to address food insecurity and chronic conditions.Ethics and disseminationThis study was approved by the Stanford University Institutional Review Board (reference protocol ID 57239). Appropriate study result dissemination will be determined in partnership with the Community Advisory Board.

Published
2023

36. Evaluation of walking activity and gait to identify physical and mental fatigue in neurodegenerative and immune disorders: preliminary insights from the IDEA-FAST feasibility study

Author

Chloe Hinchliffe, Rana Zia Ur Rehman, Clemence Pinaud, Diogo Branco, Dan Jackson, Teemu Ahmaniemi, Tiago Guerreiro, Meenakshi Chatterjee, Nikolay V. Manyakov, Ioannis Pandis, Kristen Davies, Victoria Macrae, Svenja Aufenberg, Emma Paulides, Hanna Hildesheim, Jennifer Kudelka, Kirsten Emmert, Geert Van Gassen, Lynn Rochester, C. Janneke van der Woude, Ralf Reilmann, Walter Maetzler, Wan-Fai Ng, Silvia Del Din, and the IDEA-FAST Consortium

Subjects
Real-world gait, Machine learning, Wearable devices, Walking, Fatigue, Digital health, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Abstract Background Many individuals with neurodegenerative (NDD) and immune-mediated inflammatory disorders (IMID) experience debilitating fatigue. Currently, assessments of fatigue rely on patient reported outcomes (PROs), which are subjective and prone to recall biases. Wearable devices, however, provide objective and reliable estimates of gait, an essential component of health, and may present objective evidence of fatigue. This study explored the relationships between gait characteristics derived from an inertial measurement unit (IMU) and patient-reported fatigue in the IDEA-FAST feasibility study. Methods Participants with IMIDs and NDDs (Parkinson's disease (PD), Huntington's disease (HD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary Sjogren’s syndrome (PSS), and inflammatory bowel disease (IBD)) wore a lower-back IMU continuously for up to 10 days at home. Concurrently, participants completed PROs (physical fatigue (PF) and mental fatigue (MF)) up to four times a day. Macro (volume, variability, pattern, and acceleration vector magnitude) and micro (pace, rhythm, variability, asymmetry, and postural control) gait characteristics were extracted from the accelerometer data. The associations of these measures with the PROs were evaluated using a generalised linear mixed-effects model (GLMM) and binary classification with machine learning. Results Data were recorded from 72 participants: PD = 13, HD = 9, RA = 12, SLE = 9, PSS = 14, IBD = 15. For the GLMM, the variability of the non-walking bouts length (in seconds) with PF returned the highest conditional R2, 0.165, and with MF the highest marginal R2, 0.0018. For the machine learning classifiers, the highest accuracy of the current analysis was returned by the micro gait characteristics with an intrasubject cross validation method and MF as 56.90% (precision = 43.9%, recall = 51.4%). Overall, the acceleration vector magnitude, bout length variation, postural control, and gait rhythm were the most interesting characteristics for future analysis. Conclusions Counterintuitively, the outcomes indicate that there is a weak relationship between typical gait measures and abnormal fatigue. However, factors such as the COVID-19 pandemic may have impacted gait behaviours. Therefore, further investigations with a larger cohort are required to fully understand the relationship between gait and abnormal fatigue.

Published
2024
Full Text
View/download PDF

37. Development of an iPSC-derived tissue-resident macrophage-based platform for the in vitro immunocompatibility assessment of human tissue engineered matrices

Author

Nikolaos Poulis, Marcy Martin, Simon P. Hoerstrup, Maximilian Y. Emmert, and Emanuela S. Fioretta

Subjects
Resident tissue macrophages, Induced pluripotent stem cells, iPSC-derived macrophages, Tissue culture, Extracellular matrix, Mass spectroscopy, Medicine, Science
Abstract

Abstract Upon implanting tissue-engineered heart valves (TEHVs), blood-derived macrophages are believed to orchestrate the remodeling process. They initiate the immune response and mediate the remodeling of the TEHV, essential for the valve’s functionality. The exact role of another macrophage type, the tissue-resident macrophages (TRMs), has not been yet elucidated even though they maintain the homeostasis of native tissues. Here, we characterized the response of hTRM-like cells in contact with a human tissue engineered matrix (hTEM). HTEMs comprised intracellular peptides with potentially immunogenic properties in their ECM proteome. Human iPSC-derived macrophages (iMφs) could represent hTRM-like cells in vitro and circumvent the scarcity of human donor material. iMφs were derived and after stimulation they demonstrated polarization towards non-/inflammatory states. Next, they responded with increased IL-6/IL-1β secretion in separate 3/7-day cultures with longer production-time-hTEMs. We demonstrated that iMφs are a potential model for TRM-like cells for the assessment of hTEM immunocompatibility. They adopt distinct pro- and anti-inflammatory phenotypes, and both IL-6 and IL-1β secretion depends on hTEM composition. IL-6 provided the highest sensitivity to measure iMφs pro-inflammatory response. This platform could facilitate the in vitro immunocompatibility assessment of hTEMs and thereby showcase a potential way to achieve safer clinical translation of TEHVs.

Published
2024
Full Text
View/download PDF

38. Towards a spatially resolved, single-ended TDLAS system for characterizing the distribution of gaseous species

Author

C. Hansemann, M. Bonarens, J. Emmert, K. J. Daun, and S. Wagner

Subjects
Medicine, Science
Abstract

Abstract Many applications require diagnostics that can quantify the distribution of chemical gas species and gas temperature along a single line-of-sight, which is challenging in process environments with limited optical access. To this end, we present an approach that combines time-of-flight Light Detection and Ranging (LiDAR) with Tunable Diode Laser Absorption Spectroscopy (TDLAS) to scan individual gas molecular transition lines. This method is applicable in situations where scattering objects are distributed along the beam path, such as solid fuel combustion, or when dealing with multiple gas volumes separated by weakly reflecting windows. The approach is demonstrated through simulation studies and an initial experimental proof of concept for separated gas volumes.

Published
2024
Full Text
View/download PDF

39. Is ChatGPT the way toward artificial general intelligence

Author

Frank Emmert-Streib

Subjects
Artificial general intelligence, Conversational AI, Question-answering system, Natural language processing, Data science, Computational linguistics. Natural language processing, P98-98.5, Electronic computers. Computer science, QA75.5-76.95
Abstract

Abstract The success of the conversational AI system ChatGPT has triggered an avalanche of studies that explore its applications in research and education. There are also high hopes that, in addition to such particular usages, it could lead to artificial general intelligence (AGI) that means to human-level intelligence. Such aspirations, however, need to be grounded by actual scientific means to ensure faithful statements and evaluations of the current situation. The purpose of this article is to put ChatGPT into perspective and to outline a way forward that might instead lead to an artificial special intelligence (ASI), a notion we introduce. The underlying idea of ASI is based on an environment that consists only of text. We will show that this avoids the problem of embodiment of an agent and leads to a system with restricted capabilities compared to AGI. Furthermore, we discuss gated actions as a means of large language models to moderate ethical concerns.

Published
2024
Full Text
View/download PDF

40. The development and internal validation of a multivariable model predicting 6-month mortality for people with opioid use disorder presenting to community drug services in England: a protocol

Author

Emmert Roberts, John Strang, Patrick Horgan, and Brian Eastwood

Subjects
Mortality, Opioid use disorder, Risk prediction, Prognostic modelling, Model development, Internal validation, Medicine (General), R5-920
Abstract

Abstract Background People with opioid use disorder have substantially higher standardised mortality rates compared to the general population; however, lack of clear individual prognostic information presents challenges to prioritise or target interventions within drug treatment services. Previous prognostic models have been developed to estimate the risk of developing opioid use disorder and opioid-related overdose in people routinely prescribed opioids but, to our knowledge, none have been developed to estimate mortality risk in people accessing drug services with opioid use disorder. Initial presentation to drug services is a pragmatic time to evaluate mortality risk given the contemporaneous routine collection of prognostic indicators and as a decision point for appropriate service prioritisation and targeted intervention delivery. This study aims to develop and internally validate a model to estimate 6-month mortality risk for people with opioid use disorder from prognostic indicators recorded at initial assessment in drug services in England. Methods An English national dataset containing records from individuals presenting to drug services between 1 April 2013 and 1 April 2023 (n > 800,000) (the National Drug Treatment Monitoring System (NDTMS)) linked to their lifetime hospitalisation and death records (Hospital Episode Statistics-Office of National Statistics (HES-ONS)). Twelve candidate prognostic indicator variables were identified based on literature review of demographic and clinical features associated with increased mortality for people in treatment for opioid use disorder. Variables will be extracted at initial presentation to drug services with mortality measured at 6 months. Two multivariable Cox regression models will be developed one for 6-month all-cause mortality and one for 6-month drug-related mortality using backward elimination with a fractional polynomial approach for continuous variables. Internal validation will be undertaken using bootstrapping methods. Discrimination of both models will be reported using Harrel’s c and d-statistics. Calibration curves and slopes will be presented comparing expected and observed event rates. Discussion The models developed and internally validated in this study aim to improve clinical assessment of mortality risk for people with opioid use disorder presenting to drug services in England. External validation in different populations will be required to develop the model into a tool to assist future clinical decision-making.

Published
2024
Full Text
View/download PDF

41. The Solenoidal Large Intensity Device (SoLID) for JLab 12 GeV

Author

Arrington, John, Benesch, Jay, Camsonne, Alexandre, Caylor, Jimmy, Chen, Jian-Ping, Dusa, Silviu Covrig, Emmert, Alexander, Evans, George, Gao, Haiyan, Hansen, J. Ole, Huber, Garth M., Joosten, Sylvester, Khachatryan, Vladimir, Liyanage, Nilanga, Meziani, Zein-Eddine, Nycz, Michael, Peng, Chao, Paolone, Michael, Seay, Whit, Souder, Paul A., Sparveris, Nikos, Spiesberger, Hubert, Tian, Ye, Voutier, Eric, Xie, Junqi, Xiong, Weizhi, Ye, Zhenyu, Ye, Zhihong, Zhang, Jixie, Zhao, Zhiwen, and Zheng, Xiaochao

Subjects
Nuclear Experiment, High Energy Physics - Phenomenology, Physics - Instrumentation and Detectors
Abstract

The Solenoidal Large Intensity Device (SoLID) is a new experimental apparatus planned for Hall A at the Thomas Jefferson National Accelerator Facility (JLab). SoLID will combine large angular and momentum acceptance with the capability to handle very high data rates at high luminosity. With a slate of approved high-impact physics experiments, SoLID will push JLab to a new limit at the QCD intensity frontier that will exploit the full potential of its 12 GeV electron beam. In this paper, we present an overview of the rich physics program that can be realized with SoLID, which encompasses the tomography of the nucleon in 3-D momentum space from Semi-Inclusive Deep Inelastic Scattering (SIDIS), expanding the phase space in the search for new physics and novel hadronic effects in parity-violating DIS (PVDIS), a precision measurement of $J/\psi$ production at threshold that probes the gluon field and its contribution to the proton mass, tomography of the nucleon in combined coordinate and momentum space with deep exclusive reactions, and more. To meet the challenging requirements, the design of SoLID described here takes full advantage of recent progress in detector, data acquisition and computing technologies. In addition, we outline potential experiments beyond the currently approved program and discuss the physics that could be explored should upgrades of CEBAF become a reality in the future., Comment: This white paper for the SoLID program at Jefferson Lab was prepared in part as an input to the 2023 NSAC Long Range Planning exercise. To be submitted to J. Phys. G

Published
2022

42. Evaluation of Question Answering Systems: Complexity of judging a natural language

Author

Farea, Amer, Yang, Zhen, Duong, Kien, Perera, Nadeesha, and Emmert-Streib, Frank

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Question answering (QA) systems are among the most important and rapidly developing research topics in natural language processing (NLP). A reason, therefore, is that a QA system allows humans to interact more naturally with a machine, e.g., via a virtual assistant or search engine. In the last decades, many QA systems have been proposed to address the requirements of different question-answering tasks. Furthermore, many error scores have been introduced, e.g., based on n-gram matching, word embeddings, or contextual embeddings to measure the performance of a QA system. This survey attempts to provide a systematic overview of the general framework of QA, QA paradigms, benchmark datasets, and assessment techniques for a quantitative evaluation of QA systems. The latter is particularly important because not only is the construction of a QA system complex but also its evaluation. We hypothesize that a reason, therefore, is that the quantitative formalization of human judgment is an open problem.

Published
2022

43. Design of the ECCE Detector for the Electron Ion Collider

Author

Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Conroy, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupré, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Gwenian, C., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Horn, T., Hoghmrtsyan, A., Hsu, P. -h. J., Huang, J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, X., Liang, Y. T., Lim, S., Lin, C. -H., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Camacho, C. Munoz, Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Orešić, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Papandreou, Z, Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santiesteban, N., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schmidt, N., Schwarz, C., Schwiening, J., Seidl, R., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zhang, J., Zhang, Y., Zhao, Y. X., Zheng, X., and Zhuang, P.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment
Abstract

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been designed to address the full scope of the proposed Electron Ion Collider (EIC) physics program as presented by the National Academy of Science and provide a deeper understanding of the quark-gluon structure of matter. To accomplish this, the ECCE detector offers nearly acceptance and energy coverage along with excellent tracking and particle identification. The ECCE detector was designed to be built within the budget envelope set out by the EIC project while simultaneously managing cost and schedule risks. This detector concept has been selected to be the basis for the EIC project detector., Comment: 34 pages, 30 figures, 9 tables

Published
2022

44. Detector Requirements and Simulation Results for the EIC Exclusive, Diffractive and Tagging Physics Program using the ECCE Detector Concept

Author

Bylinkin, A., Dean, C. T., Fegan, S., Gangadharan, D., Gates, K., Kay, S. J. D., Korover, I., Li, W. B., Li, X., Montgomery, R., Nguyen, D., Penman, G., Pybus, J. R., Santiesteban, N., Trotta, R., Usman, A., Baker, M. D., Frantz, J., Glazier, D. I., Higinbotham, D. W., Horn, T., Huang, J., Huber, G., Reed, R., Roche, J., Schmidt, A., Steinberg, P., Stevens, J., Goto, Y., Camacho, C. Munoz, Murray, M., Papandreou, Z., Zha, W., Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Demarteau, M., Diehl, S., Doshita, N., Dupre, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Finger, M., Finger Jr., M., Friedman, M., Friscic, I., Gardner, S., Geurts, F., Gilman, R., Glimos, E., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Hoballah, M., Hoghmrtsyan, A., Hsu, P. -h. J., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Liang, Y. T., Lim, S., Lin, C. -h., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Mantry, S., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Morrison, D., Movsisyan, A., Mkrtchyan, H., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Oresic, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Pate, S. F., Patel, M., Paus, C., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K. F., Roed, K., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santos, R., Sarsour, M., Schambach, J., Schmidt, N., Schwarz, C., Schwiening, J., Seidl, R., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Stepanov, P., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Tveter, T. S., Umaka, E., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zhang, J. -L., and Zhang, J. -X.

Subjects
Physics - Instrumentation and Detectors, Nuclear Experiment
Abstract

This article presents a collection of simulation studies using the ECCE detector concept in the context of the EIC's exclusive, diffractive, and tagging physics program, which aims to further explore the rich quark-gluon structure of nucleons and nuclei. To successfully execute the program, ECCE proposed to utilize the detecter system close to the beamline to ensure exclusivity and tag ion beam/fragments for a particular reaction of interest. Preliminary studies confirmed the proposed technology and design satisfy the requirements. The projected physics impact results are based on the projected detector performance from the simulation at 10 or 100 fb^-1 of integrated luminosity. Additionally, a few insights on the potential 2nd Interaction Region can (IR) were also documented which could serve as a guidepost for the future development of a second EIC detector.

Published
2022
Full Text
View/download PDF

45. ECCE unpolarized TMD measurements

Author

Seidl, R., Vladimirov, A., Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupré, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Horn, T., Hoghmrtsyan, A., Hsu, P. -h. J., Huang, J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, X., Liang, Y. T., Lim, S., Lin, C. -H., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Camacho, C. Munoz, Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Orešić, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Papandreou, Z, Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santiesteban, N., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schmidt, N., Schwarz, C., Schwiening, J., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zhang, J., Zhang, Y., Zhao, Y. X., Zheng, X., and Zhuang, P.

Subjects
High Energy Physics - Experiment
Abstract

We performed feasibility studies for various measurements that are related to unpolarized TMD distribution and fragmentation functions. The processes studied include semi-inclusive Deep inelastic scattering (SIDIS) where single hadrons (pions and kaons) were detected in addition to the scattered DIS lepton. The single hadron cross sections and multiplicities were extracted as a function of the DIS variables $x$ and $Q^2$, as well as the semi-inclusive variables $z$, which corresponds to the momentum fraction the detected hadron carries relative to the struck parton and $P_T$, which corresponds to the transverse momentum of the detected hadron relative to the virtual photon. The expected statistical precision of such measurements is extrapolated to accumulated luminosities of 10 fb$^{-1}$ and potential systematic uncertainties are approximated given the deviations between true and reconstructed yields., Comment: 12 pages, 9 figures, to be submitted in joint ECCE proposal NIM-A volume

Published
2022
Full Text
View/download PDF

46. ECCE Sensitivity Studies for Single Hadron Transverse Single Spin Asymmetry Measurements

Author

Seidl, R., Vladimirov, A., Pitonyak, D., Prokudin, A., Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupré, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Horn, T., Hoghmrtsyan, A., Hsu, P. -h. J., Huang, J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, X., Liang, Y. T., Lim, S., Lin, C. -H., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Camacho, C. Munoz, Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Orešić, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Papandreou, Z, Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santiesteban, N., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schmidt, N., Schwarz, C., Schwiening, J., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zhang, J., Zhang, Y., Zhao, Y. X., Zheng, X., and Zhuang, P.

Subjects
High Energy Physics - Experiment
Abstract

We performed feasibility studies for various single transverse spin measurements that are related to the Sivers effect, transversity and the tensor charge, and the Collins fragmentation function. The processes studied include semi-inclusive deep inelastic scattering (SIDIS) where single hadrons (pions and kaons) were detected in addition to the scattered DIS lepton. The data were obtained in {\sc pythia}6 and {\sc geant}4 simulated e+p collisions at 18 GeV on 275 GeV, 18 on 100, 10 on 100, and 5 on 41 that use the ECCE detector configuration. Typical DIS kinematics were selected, most notably $Q^2 > 1 $ GeV$^2$, and cover the $x$ range from $10^{-4}$ to $1$. The single spin asymmetries were extracted as a function of $x$ and $Q^2$, as well as the semi-inclusive variables $z$, and $P_T$. They are obtained in azimuthal moments in combinations of the azimuthal angles of the hadron transverse momentum and transverse spin of the nucleon relative to the lepton scattering plane. The initially unpolarized MonteCarlo was re-weighted in the true kinematic variables, hadron types and parton flavors based on global fits of fixed target SIDIS experiments and $e^+e^-$ annihilation data. The expected statistical precision of such measurements is extrapolated to 10 fb$^{-1}$ and potential systematic uncertainties are approximated given the deviations between true and reconstructed yields. The impact on the knowledge of the Sivers functions, transversity and tensor charges, and the Collins function has then been evaluated in the same phenomenological extractions as in the Yellow Report. The impact is found to be comparable to that obtained with the parameterized Yellow Report detector and shows that the ECCE detector configuration can fulfill the physics goals on these quantities., Comment: 22 pages, 22 figures, to be submitted to joint ECCE proposal NIM-A volume

Published
2022
Full Text
View/download PDF

47. Open Heavy Flavor Studies for the ECCE Detector at the Electron Ion Collider

Author

Li, X., Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupré, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Horn, T., Hoghmrtsyan, A., Hsu, P. -h. J., Huang, J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, W. B., Liang, Y. T., Lim, S., Lin, C. -H., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Mantry, S., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Camacho, C. Munoz, Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Orešić, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Papandreou, Z., Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K. F., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santiesteban, N., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schmidt, N., Schwarz, C., Schwiening, J., Seidl, R., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zha, W., Zhang, J. -L., Zhang, J. -X., Zhang, Y., Zhao, Y. -X., Zheng, X., and Zhuang, P.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment
Abstract

The ECCE detector has been recommended as the selected reference detector for the future Electron-Ion Collider (EIC). A series of simulation studies have been carried out to validate the physics feasibility of the ECCE detector. In this paper, detailed studies of heavy flavor hadron and jet reconstruction and physics projections with the ECCE detector performance and different magnet options will be presented. The ECCE detector has enabled precise EIC heavy flavor hadron and jet measurements with a broad kinematic coverage. These proposed heavy flavor measurements will help systematically study the hadronization process in vacuum and nuclear medium especially in the underexplored kinematic region., Comment: Open heavy flavor studies with the EIC reference detector design by the ECCE consortium. 11 pages, 11 figures, to be submitted to the Nuclear Instruments and Methods A

Published
2022

48. Exclusive J/$\psi$ Detection and Physics with ECCE

Author

Li, X., Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupré, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Horn, T., Hoghmrtsyan, A., Hsu, P. -h. J., Huang, J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, W. B., Liang, Y. T., Lim, S., Lin, C. -H., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Mantry, S., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Camacho, C. Munoz, Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Orešić, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Papandreou, Z., Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K. F., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santiesteban, N., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schmidt, N., Schwarz, C., Schwiening, J., Seidl, R., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zha, W., Zhang, J. -L., Zhang, J. -X., Zhang, Y., Zhao, Y. -X., Zheng, X., and Zhuang, P.

Subjects
Nuclear Experiment, Physics - Instrumentation and Detectors
Abstract

Exclusive heavy quarkonium photoproduction is one of the most popular processes in EIC, which has a large cross section and a simple final state. Due to the gluonic nature of the exchange Pomeron, this process can be related to the gluon distributions in the nucleus. The momentum transfer dependence of this process is sensitive to the interaction sites, which provides a powerful tool to probe the spatial distribution of gluons in the nucleus. Recently the problem of the origin of hadron mass has received lots of attention in determining the anomaly contribution $M_{a}$. The trace anomaly is sensitive to the gluon condensate, and exclusive production of quarkonia such as J/$\psi$ and $\Upsilon$ can serve as a sensitive probe to constrain it. In this paper, we present the performance of the ECCE detector for exclusive J/$\psi$ detection and the capability of this process to investigate the above physics opportunities with ECCE., Comment: 11 pages, 14 figures, 1 table

Published
2022
Full Text
View/download PDF

49. Search for $e\to\tau$ Charged Lepton Flavor Violation at the EIC with the ECCE Detector

Author

Zhang, J. -L., Mantry, S., Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Bock, F., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupré, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Horn, T., Hoghmrtsyan, A., Hsu, P. -h. J., Huang, J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lajoie, J., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, W. B., Li, X., Liang, Y. T., Lim, S., Lin, C. -H., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Camacho, C. Munoz, Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Orešić, S., Osborn, J. D., O'Shaughnessy, C., Paganis, S., Papandreou, Z., Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K. F., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santiesteban, N., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schmidt, N., Schwarz, C., Schwiening, J., Seidl, R., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, P. K., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zha, W., Zhang, J. -X., Zhang, Y., Zhao, Y. -X., Zheng, X., and Zhuang, P.

Subjects
High Energy Physics - Phenomenology
Abstract

The recently approved Electron-Ion Collider (EIC) will provide a unique new opportunity for searches of charged lepton flavor violation (CLFV) and other new physics scenarios. In contrast to the $e \leftrightarrow \mu$ CLFV transition for which very stringent limits exist, there is still a relatively large discovery space for the $e \to \tau$ CLFV transition, potentially to be explored by the EIC. With the latest detector design of ECCE (EIC Comprehensive Chromodynamics Experiment) and projected integral luminosity of the EIC, we find the $\tau$-leptons created in the DIS process $ep\to \tau X$ are expected to be identified with high efficiency. A first ECCE simulation study, restricted to the 3-prong $\tau$-decay mode and with limited statistics for the Standard Model backgrounds, estimates that the EIC will be able to improve the current exclusion limit on $e\to \tau$ CLFV by an order of magnitude., Comment: 11 pages, 8 figures, to be submitted to NIM

Published
2022
Full Text
View/download PDF

50. Design and Simulated Performance of Calorimetry Systems for the ECCE Detector at the Electron Ion Collider

Author

Bock, F., Schmidt, N., Wang, P. K., Santiesteban, N., Horn, T., Huang, J., Lajoie, J., Camacho, C. Munoz, Adkins, J. K., Akiba, Y., Albataineh, A., Amaryan, M., Arsene, I. C., Gayoso, C. Ayerbe, Bae, J., Bai, X., Baker, M. D., Bashkanov, M., Bellwied, R., Benmokhtar, F., Berdnikov, V., Bernauer, J. C., Boeglin, W., Borysova, M., Brash, E., Brindza, P., Briscoe, W. J., Brooks, M., Bueltmann, S., Bukhari, M. H. S., Bylinkin, A., Capobianco, R., Chang, W. -C., Cheon, Y., Chen, K., Chen, K. -F., Cheng, K. -Y., Chiu, M., Chujo, T., Citron, Z., Cline, E., Cohen, E., Cormier, T., Morales, Y. Corrales, Cotton, C., Crafts, J., Crawford, C., Creekmore, S., Cuevas, C., Cunningham, J., David, G., Dean, C. T., Demarteau, M., Diehl, S., Doshita, N., Dupre, R., Durham, J. M., Dzhygadlo, R., Ehlers, R., Fassi, L. El, Emmert, A., Ent, R., Fanelli, C., Fatemi, R., Fegan, S., Finger, M., Finger Jr., M., Frantz, J., Friedman, M., Friscic, I., Gangadharan, D., Gardner, S., Gates, K., Geurts, F., Gilman, R., Glazier, D., Glimos, E., Goto, Y., Grau, N., Greene, S. V., Guo, A. Q., Guo, L., Ha, S. K., Haggerty, J., Hayward, T., He, X., Hen, O., Higinbotham, D. W., Hoballah, M., Hoghmrtsyan, A., Hsu, P. -h. J., Huber, G., Hutson, A., Hwang, K. Y., Hyde, C. E., Inaba, M., Iwata, T., Jo, H. S., Joo, K., Kalantarians, N., Kalicy, G., Kawade, K., Kay, S. J. D., Kim, A., Kim, B., Kim, C., Kim, M., Kim, Y., Kistenev, E., Klimenko, V., Ko, S. H., Korover, I., Korsch, W., Krintiras, G., Kuhn, S., Kuo, C. -M., Kutz, T., Lawrence, D., Lebedev, S., Lee, H., Lee, J. S. H., Lee, S. W., Lee, Y. -J., Li, W., Li, W. B., Li, X., Liang, Y. T., Lim, S., Lin, C. -h., Lin, D. X., Liu, K., Liu, M. X., Livingston, K., Liyanage, N., Llope, W. J., Loizides, C., Long, E., Lu, R. -S., Lu, Z., Lynch, W., Mantry, S., Marchand, D., Marcisovsky, M., Markert, C., Markowitz, P., Marukyan, H., McGaughey, P., Mihovilovic, M., Milner, R. G., Milov, A., Miyachi, Y., Mkrtchyan, A., Monaghan, P., Montgomery, R., Morrison, D., Movsisyan, A., Mkrtchyan, H., Murray, M., Nagai, K., Nagle, J., Nakagawa, I., Nattrass, C., Nguyen, D., Niccolai, S., Nouicer, R., Nukazuka, G., Nycz, M., Okorokov, V. A., Oresic, S., Osborn, J. D., Shaughnessy, C. O, Paganis, S., Papandreou, Z., Pate, S. F., Patel, M., Paus, C., Penman, G., Perdekamp, M. G., Perepelitsa, D. V., da Costa, H. Periera, Peters, K., Phelps, W., Piasetzky, E., Pinkenburg, C., Prochazka, I., Protzman, T., Purschke, M. L., Putschke, J., Pybus, J. R., Rajput-Ghoshal, R., Rasson, J., Raue, B., Read, K. F., Røed, K., Reed, R., Reinhold, J., Renner, E. L., Richards, J., Riedl, C., Rinn, T., Roche, J., Roland, G. M., Ron, G., Rosati, M., Royon, C., Ryu, J., Salur, S., Santos, R., Sarsour, M., Schambach, J., Schmidt, A., Schwarz, C., Schwiening, J., Seidl, R., Sickles, A., Simmerling, P., Sirca, S., Sharma, D., Shi, Z., Shibata, T. -A., Shih, C. -W., Shimizu, S., Shrestha, U., Slifer, K., Smith, K., Sokhan, D., Soltz, R., Sondheim, W., Song, J., Strakovsky, I. I., Steinberg, P., Stepanov, P., Stevens, J., Strube, J., Sun, P., Sun, X., Suresh, K., Tadevosyan, V., Tang, W. -C., Araya, S. Tapia, Tarafdar, S., Teodorescu, L., Thomas, D., Timmins, A., Tomasek, L., Trotta, N., Trotta, R., Tveter, T. S., Umaka, E., Usman, A., van Hecke, H. W., Van Hulse, C., Velkovska, J., Voutier, E., Wang, Q., Wang, Y., Watts, D. P., Wickramaarachchi, N., Weinstein, L., Williams, M., Wong, C. -P., Wood, L., Wood, M. H., Woody, C., Wyslouch, B., Xiao, Z., Yamazaki, Y., Yang, Y., Ye, Z., Yoo, H. D., Yurov, M., Zachariou, N., Zajc, W. A., Zha, W., Zhang, J. -L., Zhang, J. -X., Zhang, Y., Zhao, Y. -X., Zheng, X., and Zhuang, P.

Subjects
Physics - Instrumentation and Detectors, High Energy Physics - Experiment, Nuclear Experiment
Abstract

We describe the design and performance the calorimeter systems used in the ECCE detector design to achieve the overall performance specifications cost-effectively with careful consideration of appropriate technical and schedule risks. The calorimeter systems consist of three electromagnetic calorimeters, covering the combined pseudorapdity range from -3.7 to 3.8 and two hadronic calorimeters. Key calorimeter performances which include energy and position resolutions, reconstruction efficiency, and particle identification will be presented., Comment: 19 pages, 22 figures, 5 tables

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results