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28,215 results on '"Yu F."'

1. Axisymmetric Slow Rotation of Coaxial Soft/Porous Spheres

Author

Yu F. Chou and Huan J. Keh

Subjects
rotation of soft spheres, creeping flow, hydrodynamic torque, particle interaction, Organic chemistry, QD241-441
Abstract

The steady low-Reynolds-number rotation of a chain of coaxial soft spheres (each with an impermeable hard core covered by a permeable porous layer) about the axis in a viscous fluid is analyzed. The particles may be unequally spaced, and may differ in the permeability and inner and outer radii of the porous surface layer as well as angular velocity. By using a method of boundary collocation, the Stokes and Brinkman equations for the external fluid flow and flow within the surface layers, respectively, are solved semi-analytically. The particle interaction effect increases as the relative gap thickness between adjacent particles or their permeability decreases, which can be significant as the gap thickness approaches zero. A particle’s hydrodynamic torque is reduced (its rotation is enhanced) when other particles rotate in the same direction at equivalent or greater angular velocities, but increases (its rotation is hindered) when other particles rotate in the opposite direction at arbitrary angular velocities. For particles with different radii or permeabilities, the particle interaction has a greater effect on smaller or more permeable particles than on larger or less permeable particles. For the rotation of three particles, the presence of the third particle can significantly affect the hydrodynamic torques acting on the other two particles. For the rotation of numerous particles, shielding effects between particles can be substantial. When the permeability of porous layers is low, relative fluid motion is barely felt by the hard cores of the soft particles. The insights gained from this analysis on the effects of interactions among rotating soft particles may be of great importance in many physicochemical applications of colloidal suspensions.

Published
2024
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2. Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deployment

Author

Wu, Jiaqi, Chen, Simin, Wang, Zehua, Chen, Wei, Tian, Zijian, Yu, F. Richard, and Leung, Victor C. M.

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence
Abstract

As the volume of image data grows, data-oriented cloud computing in Internet of Video Things (IoVT) systems encounters latency issues. Task-oriented edge computing addresses this by shifting data analysis to the edge. However, limited computational power of edge devices poses challenges for executing visual tasks. Existing methods struggle to balance high model performance with low resource consumption; lightweight neural networks often underperform, while device-specific models designed by Neural Architecture Search (NAS) fail to adapt to heterogeneous devices. For these issues, we propose a novel co-design framework to optimize neural network architecture and deployment strategies during inference for high-throughput. Specifically, it implements a dynamic model structure based on re-parameterization, coupled with a Roofline-based model partitioning strategy to enhance the computational performance of edge devices. We also employ a multi-objective co-optimization approach to balance throughput and accuracy. Additionally, we derive mathematical consistency and convergence of partitioned models. Experimental results demonstrate significant improvements in throughput (12.05\% on MNIST, 18.83\% on ImageNet) and superior classification accuracy compared to baseline algorithms. Our method consistently achieves stable performance across different devices, underscoring its adaptability. Simulated experiments further confirm its efficacy in high-accuracy, real-time detection for small objects in IoVT systems.

Published
2024

3. A Simple System for Differentiation of Functional Intestinal Stem Cell-like Cells from Bone Marrow Mesenchymal Stem Cells

Author

Lei Ye, Lei X. Sun, Min H. Wu, Jin Wang, Xin Ding, Hui Shi, Sheng L. Lu, Lin Wu, Juan Wei, Liang Li, and Yu F. Wang

Subjects
Therapeutics. Pharmacology, RM1-950
Abstract

Disruption of normal barrier function is a fundamental factor in the pathogenesis of inflammatory bowel disease, and intestinal stem cell (ISC) transplantation may be an optional treatment for patients. However, it is complicated and inefficient to isolate ISCs from the intestine, which hampers its wide application in clinic. We developed a two-step protocol in which mesenchymal stem cells (MSCs) were first induced into Sox17- or Foxa2-positive definitive endoderm cells by activin A treatment and then into Lgr5-positive ISC-like cells by miR-17 and FGF2 treatment. Furthermore, these Lgr5-positive cells could differentiate into enterocyte-like cells following induction with EGF. The results from an in vivo experiment showed that the MSC-derived Lgr5-positive cells were able to protect against dextran sulfate sodium-induced colitis. Taken together, our work might provide a new source of autologous ISCs. Keywords: mesenchymal stem cells, differentiation, intestinal stem cells

Published
2018
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4. A Strategy Transfer and Decision Support Approach for Epidemic Control in Experience Shortage Scenarios

Author

Xiao, X., Chen, P., Cao, X., Liu, K., Deng, L., Zhao, D., Chen, Z., Deng, Q., Yu, F., and Zhang, H.

Subjects
Computer Science - Machine Learning, Physics - Physics and Society, Statistics - Applications
Abstract

Epidemic outbreaks can cause critical health concerns and severe global economic crises. For countries or regions with new infectious disease outbreaks, it is essential to generate preventive strategies by learning lessons from others with similar risk profiles. A Strategy Transfer and Decision Support Approach (STDSA) is proposed based on the profile similarity evaluation. There are four steps in this method: (1) The similarity evaluation indicators are determined from three dimensions, i.e., the Basis of National Epidemic Prevention & Control, Social Resilience, and Infection Situation. (2) The data related to the indicators are collected and preprocessed. (3) The first round of screening on the preprocessed dataset is conducted through an improved collaborative filtering algorithm to calculate the preliminary similarity result from the perspective of the infection situation. (4) Finally, the K-Means model is used for the second round of screening to obtain the final similarity values. The approach will be applied to decision-making support in the context of COVID-19. Our results demonstrate that the recommendations generated by the STDSA model are more accurate and aligned better with the actual situation than those produced by pure K-means models. This study will provide new insights into preventing and controlling epidemics in regions that lack experience., Comment: 20 pages, 9 figures

Published
2024

5. Observation of Seven Astrophysical Tau Neutrino Candidates with IceCube

Author

IceCube Collaboration, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Braun, J., Brinson, B., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Classen, L., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Feigl, N., Fiedlschuster, S., Fienberg, A. T., Fischer, L., Fox, D., Franckowiak, A., Fritz, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Gonzalez, J. G., Goswami, S., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Helbing, K., Hellrung, J., Henningsen, F., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Q. R., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oehler, M., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Pankova, D. V., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Renzi, G., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwefer, G., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Sharma, A., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Ty, B., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wen, A. Y., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Willey, N., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, F., Yu, S., Zhang, Z., Zhelnin, P., Zilberman, P., and Zimmerman, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, High Energy Physics - Experiment
Abstract

We report on a measurement of astrophysical tau neutrinos with 9.7 years of IceCube data. Using convolutional neural networks trained on images derived from simulated events, seven candidate $\nu_\tau$ events were found with visible energies ranging from roughly 20 TeV to 1 PeV and a median expected parent $\nu_\tau$ energy of about 200 TeV. Considering backgrounds from astrophysical and atmospheric neutrinos, and muons from $\pi^\pm/K^\pm$ decays in atmospheric air showers, we obtain a total estimated background of about 0.5 events, dominated by non-$\nu_\tau$ astrophysical neutrinos. Thus, we rule out the absence of astrophysical $\nu_\tau$ at the $5\sigma$ level. The measured astrophysical $\nu_\tau$ flux is consistent with expectations based on previously published IceCube astrophysical neutrino flux measurements and neutrino oscillations., Comment: Accepted for publication in Physical Review Letters. This version includes full author list metadata

Published
2024
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17. CoRaiS: Lightweight Real-Time Scheduler for Multi-Edge Cooperative Computing

Author

Hu, Yujiao, Jia, Qingmin, Chen, Jinchao, Yao, Yuan, Pan, Yan, Xie, Renchao, and Yu, F. Richard

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence
Abstract

Multi-edge cooperative computing that combines constrained resources of multiple edges into a powerful resource pool has the potential to deliver great benefits, such as a tremendous computing power, improved response time, more diversified services. However, the mass heterogeneous resources composition and lack of scheduling strategies make the modeling and cooperating of multi-edge computing system particularly complicated. This paper first proposes a system-level state evaluation model to shield the complex hardware configurations and redefine the different service capabilities at heterogeneous edges. Secondly, an integer linear programming model is designed to cater for optimally dispatching the distributed arriving requests. Finally, a learning-based lightweight real-time scheduler, CoRaiS, is proposed. CoRaiS embeds the real-time states of multi-edge system and requests information, and combines the embeddings with a policy network to schedule the requests, so that the response time of all requests can be minimized. Evaluation results verify that CoRaiS can make a high-quality scheduling decision in real time, and can be generalized to other multi-edge computing system, regardless of system scales. Characteristic validation also demonstrates that CoRaiS successfully learns to balance loads, perceive real-time state and recognize heterogeneity while scheduling., Comment: Accepted by IEEE Internet of Things Journal

Published
2024

18. Empowering Computing and Networks Convergence System with Distributed Cooperative Routing

Author

Hu, Yujiao, Jia, Qingmin, Shen, Meng, Xie, Renchao, Huang, Tao, and Yu, F. Richard

Subjects
Computer Science - Networking and Internet Architecture, Computer Science - Artificial Intelligence
Abstract

The emergence of intelligent applications and recent advances in the fields of computing and networks are driving the development of computing and networks convergence (CNC) system. However, existing researches failed to achieve comprehensive scheduling optimization of computing and network resources. This shortfall results in some requirements of computing requests unable to be guaranteed in an end-to-end service pattern, negatively impacting the development of CNC systems. In this article, we propose a distributed cooperative routing framework for the CNC system to ensure the deadline requirements and minimize the computation cost of requests. The framework includes trading plane, management plane, control plane and forwarding plane. The cross-plane cooperative end-to-end routing schemes consider both computation efficiency of heterogeneous servers and the network congestion degrees while making routing plan, thereby determining where to execute requests and corresponding routing paths. Simulations results substantiates the performance of our routing schemes in scheduling computing requests in the CNC system., Comment: Submit to IEEE Network

Published
2024

19. Pioneering Deterministic Scheduling and Network Structure Optimization for Time-Critical Computing Tasks in Industrial IoT

Author

Hu, Yujiao, Zhu, Yining, Zhang, Huayu, Pan, Yan, Jia, Qingmin, Xie, Renchao, Yang, Gang, and Yu, F. Richard

Subjects
Computer Science - Networking and Internet Architecture
Abstract

The Industrial Internet of Things (IIoT) has become a critical technology to accelerate the process of digital and intelligent transformation of industries. As the cooperative relationship between smart devices in IIoT becomes more complex, getting deterministic responses of IIoT periodic time-critical computing tasks becomes a crucial and nontrivial problem. However, few current works in cloud/edge/fog computing focus on this problem. This paper is a pioneer to explore the deterministic scheduling and network structural optimization problems for IIoT periodic time-critical computing tasks. We first formulate the two problems and derive theorems to help quickly identify computation and network resource sharing conflicts. Based on this, we propose a deterministic scheduling algorithm, \textit{IIoTBroker}, which realizes deterministic response for each IIoT task by optimizing the fine-grained computation and network resources allocations, and a network optimization algorithm, \textit{IIoTDeployer}, providing a cost-effective structural upgrade solution for existing IIoT networks. Our methods are illustrated to be cost-friendly, scalable, and deterministic response guaranteed with low computation cost from our simulation results., Comment: Under Review

Published
2024

20. Labile assembly of a tardigrade protein induces biostasis.

Author

Sanchez-Martinez, S, Nguyen, K, Biswas, S, Nicholson, V, Romanyuk, A, Ramirez, J, Kc, S, Akter, A, Childs, C, Meese, E, Usher, E, Ginell, G, Yu, F, Gollub, E, Malferrari, M, Francia, F, Venturoli, G, Martin, E, Caporaletti, F, Giubertoni, G, Woutersen, S, Sukenik, S, Woolfson, D, Holehouse, A, and Boothby, T

Subjects
anhydrobiosis, biomolecular condensation, desiccation tolerance, filament formation, gelation, intrinsically disordered protein, osmotic stress, tardigrade, Animals, Desiccation, Tardigrada, Intrinsically Disordered Proteins, Gels
Abstract

Tardigrades are microscopic animals that survive desiccation by inducing biostasis. To survive drying tardigrades rely on intrinsically disordered CAHS proteins, which also function to prevent perturbations induced by drying in vitro and in heterologous systems. CAHS proteins have been shown to form gels both in vitro and in vivo, which has been speculated to be linked to their protective capacity. However, the sequence features and mechanisms underlying gel formation and the necessity of gelation for protection have not been demonstrated. Here we report a mechanism of fibrillization and gelation for CAHS D similar to that of intermediate filament assembly. We show that in vitro, gelation restricts molecular motion, immobilizing and protecting labile material from the harmful effects of drying. In vivo, we observe that CAHS D forms fibrillar networks during osmotic stress. Fibrillar networking of CAHS D improves survival of osmotically shocked cells. We observe two emergent properties associated with fibrillization; (i) prevention of cell volume change and (ii) reduction of metabolic activity during osmotic shock. We find that there is no significant correlation between maintenance of cell volume and survival, while there is a significant correlation between reduced metabolism and survival. Importantly, CAHS Ds fibrillar network formation is reversible and metabolic rates return to control levels after CAHS fibers are resolved. This work provides insights into how tardigrades induce reversible biostasis through the self-assembly of labile CAHS gels.

Published
2024

21. A new light at the end of the tunnel: fiber gas discharge lasers

Author

Love, A. L., Bateman, S. A., Belardi, W., Yu, F., Knight, J. C., Coutts, D. W., Webb, C. E., and Wadsworth, W. J.

Subjects
Physics - Optics
Abstract

Optical fibers have emerged as a transformative platform for building better and more robust solid state lasers. However, the wavelengths available to these lasers are limited. Using hollow core optical fibers allows us to add gases as new potential gain media for fiber lasers, and also liberates the gas laser from the limits normally imposed by diffraction. To demonstrate the new technology, we present a fiber laser at 3500 nm wavelength, using an antiresonant guiding hollow core optical fiber containing neutral xenon atoms pumped by an afterglow discharge of a helium-xenon mixture within a fiber of over 1 m in length. Laser action is confirmed through observation of polarization dependence, mode pulling and mode beating. Our results unlock a new breed of flexible fiber lasers operating at a plethora of wavelengths, many previous unavailable., Comment: 10 pages

Published
2023

22. Joint User Association, Interference Cancellation and Power Control for Multi-IRS Assisted UAV Communications

Author

Ning, Zhaolong, Hu, Hao, Wang, Xiaojie, Wu, Qingqing, Yuen, Chau, Yu, F. Richard, and Zhang, Yan

Subjects
Computer Science - Information Theory, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Signal Processing
Abstract

Intelligent reflecting surface (IRS)-assisted unmanned aerial vehicle (UAV) communications are expected to alleviate the load of ground base stations in a cost-effective way. Existing studies mainly focus on the deployment and resource allocation of a single IRS instead of multiple IRSs, whereas it is extremely challenging for joint multi-IRS multi-user association in UAV communications with constrained reflecting resources and dynamic scenarios. To address the aforementioned challenges, we propose a new optimization algorithm for joint IRS-user association, trajectory optimization of UAVs, successive interference cancellation (SIC) decoding order scheduling and power allocation to maximize system energy efficiency. We first propose an inverse soft-Q learning-based algorithm to optimize multi-IRS multi-user association. Then, SCA and Dinkelbach-based algorithm are leveraged to optimize UAV trajectory followed by the optimization of SIC decoding order scheduling and power allocation. Finally, theoretical analysis and performance results show significant advantages of the designed algorithm in convergence rate and energy efficiency.

Published
2023

23. Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Review

Author

Hu, Yujiao, Jia, Qingmin, Yao, Yuao, Lee, Yong, Lee, Mengjie, Wang, Chenyi, Zhou, Xiaomao, Xie, Renchao, and Yu, F. Richard

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computers and Society
Abstract

The fiercely competitive business environment and increasingly personalized customization needs are driving the digital transformation and upgrading of the manufacturing industry. IIoT intelligence, which can provide innovative and efficient solutions for various aspects of the manufacturing value chain, illuminates the path of transformation for the manufacturing industry. It's time to provide a systematic vision of IIoT intelligence. However, existing surveys often focus on specific areas of IIoT intelligence, leading researchers and readers to have biases in their understanding of IIoT intelligence, that is, believing that research in one direction is the most important for the development of IIoT intelligence, while ignoring contributions from other directions. Therefore, this paper provides a comprehensive overview of IIoT intelligence. We first conduct an in-depth analysis of the inevitability of manufacturing transformation and study the successful experiences from the practices of Chinese enterprises. Then we give our definition of IIoT intelligence and demonstrate the value of IIoT intelligence for industries in fucntions, operations, deployments, and application. Afterwards, we propose a hierarchical development architecture for IIoT intelligence, which consists of five layers. The practical values of technical upgrades at each layer are illustrated by a close look on lighthouse factories. Following that, we identify seven kinds of technologies that accelerate the transformation of manufacturing, and clarify their contributions. The ethical implications and environmental impacts of adopting IIoT intelligence in manufacturing are analyzed as well. Finally, we explore the open challenges and development trends from four aspects to inspire future researches., Comment: Accepted by IoTJ

Published
2023
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24. Influence of Water on the Structure and Dielectric Properties of the Microcrystalline and Nano-Cellulose

Author

Kostiantyn M. Kovalov, Olexander M. Alekseev, Maxim M. Lazarenko, Yu F. Zabashta, Yurii E. Grabovskii, and Sergii Yu Tkachov

Subjects
Microcrystalline cellulose, Relaxation, X-ray, Dielectric permittivity, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

Abstract Influence of water in the different states on a structure and dielectric properties of microcrystalline cellulose were studied by of X-ray, thermogravimetry, and dielectric spectroscopy. At research of microcrystalline cellulose (MCC) with different content of water, it is shown that the molecules of water are located in the macropores of MCC and in multimolecular hydrated layers. It is shown that at the increase of concentration of water in a hydrated shell, the reorganization of molecules of cellulose in the surface of crystallites takes place, and as a result, their transversal size and crystallinity increase. It is shown that during the concentration of water, more than 13% in a continuous hydrated shell of crystallites appears. Temperature dependences of actual and imaginary parts of complex dielectric permittivity were studied in the interval of temperatures [−180 ÷ 120] °C on frequencies of f = 5, 10, 20, and 50 kHz. A low-temperature relaxation process and high-temperature transition were observed. Low-temperature relaxation process which is related to transition of surface methylol groups of molecules of cellulose conformation from tg to tt is shifted toward low temperatures at the increase of concentration of water in microcrystalline cellulose.

Published
2017
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29. Three-Arm Spectrometer Scan-3 on Nuclotron Internal Targets

Author

Afanas’yev, S. V., Anisimov, Yu. S., Baskov, V. A., Dryablov, D. K., Dubinchik, B. V., Gmutsa, Sh., Kliman, Ya., Kolesnikov, R. Yu., Krechetov, Yu. F., Kutinova, O. V., Kuznetsov, A. S., L’vov, A. I., Malakhov, A. I., Mateushek, V., Polyanskii, V. V., Sakulin, D. G., Sidorin, S. S., Smirnov, V. A., Sukhov, E. V., Ustinov, V. V., Vartik, V., and Vocal, S.

Published
2024
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44. A Survey of Adversarial CAPTCHAs on its History, Classification and Generation

Author

Xu, Zisheng, Yan, Qiao, Yu, F. Richard, and Leung, Victor C. M.

Subjects
Computer Science - Cryptography and Security, Computer Science - Artificial Intelligence
Abstract

Completely Automated Public Turing test to tell Computers and Humans Apart, short for CAPTCHA, is an essential and relatively easy way to defend against malicious attacks implemented by bots. The security and usability trade-off limits the use of massive geometric transformations to interfere deep model recognition and deep models even outperformed humans in complex CAPTCHAs. The discovery of adversarial examples provides an ideal solution to the security and usability trade-off by integrating adversarial examples and CAPTCHAs to generate adversarial CAPTCHAs that can fool the deep models. In this paper, we extend the definition of adversarial CAPTCHAs and propose a classification method for adversarial CAPTCHAs. Then we systematically review some commonly used methods to generate adversarial examples and methods that are successfully used to generate adversarial CAPTCHAs. Also, we analyze some defense methods that can be used to defend adversarial CAPTCHAs, indicating potential threats to adversarial CAPTCHAs. Finally, we discuss some possible future research directions for adversarial CAPTCHAs at the end of this paper., Comment: Submitted to ACM Computing Surveys (Under Review)

Published
2023

45. Data-driven Modeling of a Coronal Magnetic Flux Rope: from Birth to Death

Author

Guo, J. H., Ni, Y. W., Guo, Y., Xia, C., Schmieder, B., Poedts, S., Zhong, Z., Zhou, Y. H., Yu, F., and Chen, P. F.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Physics - Space Physics
Abstract

Magnetic flux ropes are a bundle of twisted magnetic field lines produced by internal electric currents, which are responsible for solar eruptions and are the major drivers of geomagnetic storms. As such, it is crucial to develop a numerical model that can capture the entire evolution of a flux rope, from its birth to death, in order to predict whether adverse space weather events might occur or not. In this paper, we develop a data-driven modeling that combines a time-dependent magneto-frictional approach with a thermodynamic magnetohydrodynamic model. Our numerical modeling successfully reproduces the formation and confined eruption of an observed flux rope, and unveils the physical details behind the observations. Regarding the long-term evolution of the active region, our simulation results indicate that the flux cancellation due to collisional shearing plays a critical role in the formation of the flux rope, corresponding to a substantial increase in magnetic free energy and helicity. Regarding the eruption stage, the deformation of the flux rope during its eruption can cause an increase in the downward tension force, which suppresses it from further rising. This finding may shed light on why some torus-unstable flux ropes lead to failed eruptions after large-angle rotations. Moreover, we find that twisted fluxes can accumulate during the confined eruptions, which would breed the subsequent eruptive flares., Comment: 30 pages, 10 figures, Accepted for ApJ

Published
2023

47. Beyond Reality: The Pivotal Role of Generative AI in the Metaverse

Author

Chamola, Vinay, Bansal, Gaurang, Das, Tridib Kumar, Hassija, Vikas, Reddy, Naga Siva Sai, Wang, Jiacheng, Zeadally, Sherali, Hussain, Amir, Yu, F. Richard, Guizani, Mohsen, and Niyato, Dusit

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Artificial Intelligence
Abstract

Imagine stepping into a virtual world that's as rich, dynamic, and interactive as our physical one. This is the promise of the Metaverse, and it's being brought to life by the transformative power of Generative Artificial Intelligence (AI). This paper offers a comprehensive exploration of how generative AI technologies are shaping the Metaverse, transforming it into a dynamic, immersive, and interactive virtual world. We delve into the applications of text generation models like ChatGPT and GPT-3, which are enhancing conversational interfaces with AI-generated characters. We explore the role of image generation models such as DALL-E and MidJourney in creating visually stunning and diverse content. We also examine the potential of 3D model generation technologies like Point-E and Lumirithmic in creating realistic virtual objects that enrich the Metaverse experience. But the journey doesn't stop there. We also address the challenges and ethical considerations of implementing these technologies in the Metaverse, offering insights into the balance between user control and AI automation. This paper is not just a study, but a guide to the future of the Metaverse, offering readers a roadmap to harnessing the power of generative AI in creating immersive virtual worlds., Comment: 8 pages, 4 figures

Published
2023

48. The IceCube-Gen2 Collaboration -- Contributions to the 38th International Cosmic Ray Conference (ICRC2023)

Author

IceCube-Gen2, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Audehm, J., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Bishop, A., Blaufuss, E., Blot, S., Bohmer, M., Bontempo, F., Book, J. Y., Borowka, J., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Bouma, S., Bourbeau, E., Braun, J., Brinson, B., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Cataldo, M., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Clark, R., Classen, L., Coleman, A., Collin, G. H., Conrad, J. M., Cowen, D. F., Dasgupta, B., Dave, P., Deaconu, C., De Clercq, C., De Kockere, S., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evans, J. J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Flaggs, B., Fox, D., Franckowiak, A., Fritz, A., Fujii, T., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Gernhaeuser, R., Ghadimi, A., Giri, P., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Goswami, S., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Guevel, D., Günther, C., Gutjahr, P., Haack, C., Azim, T. Haji, Hallgren, A., Halliday, R., Hallmann, S., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haugen, J., Haungs, A., Heinen, D., Helbing, K., Hellrung, J., Hendricks, B., Henningsen, F., Henrichs, J., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hignight, J., Hill, C., Hill, G. C., Hoffman, K. D., Hoffmann, B., Holzapfel, K., Hori, S., Hoshina, K., Hou, W., Huber, T., Huege, T., Hughes, K., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kalekin, O., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katori, T., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kobayashi, T., Kochocki, A., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krauss, C. B., Kravchenko, I., Krishnamoorthi, J., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Q. R., Liubarska, M., Lohan, M., Lohfink, E., LoSecco, J., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Lyu, Y., Madsen, J., Mahn, K. B. M., Makino, Y., Mancina, S., Mandalia, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Meyers, Z., Micallef, J., Mikhailova, M., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Narayan, A., Naumann, U., Necker, J., Negi, A., Nelles, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Nozdrina, A., Oberla, E., Pollmann, A. Obertacke, O'Dell, V., Oehler, M., Oeyen, B., Olivas, A., Ørsøe, R., Osborn, J., O'Sullivan, E., Papp, L., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Petersen, T. C., Peterson, J., Philippen, S., Pieper, S., Pinfold, J. L., Pizzuto, A., Plaisier, I., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Pyras, L., Rack-Helleis, J., Rameez, M., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Renzi, G., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Riegel, M., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rott, C., Ruhe, T., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Sandstrom, P., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwefer, G., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shaevitz, M. H., Shah, R., Sharma, A., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smith, D., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Southall, D., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stoffels, J., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Taketa, A., Tanaka, H. K. M., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Torres, J., Toscano, S., Tosi, D., Trettin, A., Tsunesada, Y., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Ty, B., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veberic, D., Veitch-Michaelis, J., Venugopal, M., Verpoest, S., Vieregg, A., Vijai, A., Walck, C., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Welling, C., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Willey, N., Williams, D. R., Wissel, S., Witthaus, L., Wolf, A., Wolf, M., Wörner, G., Wrede, G., Wren, S., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, F., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., Zierke, S., and Zimmerman, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

IceCube-Gen2 is a planned next-generation neutrino observatory at the South Pole that builds upon the successful design of IceCube. Integrating two complementary detection technologies for neutrinos, optical and radio Cherenkov emission, in combination with a surface array for cosmic ray air shower detection, IceCube-Gen2 will cover a broad neutrino energy range from MeV to EeV. This index of contributions to the 38th International Cosmic Ray Conference in Nagoya, Japan (July 26 - August 3, 2023) describes research and development efforts for IceCube-Gen2. Included are summaries of the design, status, and sensitivity of the IceCube-Gen2 optical, surface, and radio components; performance studies of next-generation optical sensors detecting optical Cherenkov radiation from cosmic ray and neutrino events; reconstruction techniques of radio and optical events in terms of energy, direction, and neutrino flavor; and sensitivity studies of astrophysical neutrino flavors, diffuse neutrino fluxes, and cosmic ray anisotropies. Contributions related to IceCube and the scheduled IceCube Upgrade are available in a separate collection., Comment: To access the list of contributions, please follow the "HTML" link. Links to individual contributions will fill in as authors upload their material

Published
2023

49. The IceCube Collaboration -- Contributions to the 38th International Cosmic Ray Conference (ICRC2023)

Author

IceCube, Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Braun, J., Brinson, B., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Classen, L., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fritz, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Gonzalez, J. G., Goswami, S., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Helbing, K., Hellrung, J., Henningsen, F., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Q. R., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oehler, M., Oeyen, B., Olivas, A., Ørsøe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. T., Raab, C., Rack-Helleis, J., Rawlins, K., Rechav, Z., Rehman, A., Reichherzer, P., Renzi, G., Resconi, E., Reusch, S., Rhode, W., Riedel, B., Rifaie, A., Roberts, E. J., Robertson, S., Rodan, S., Roellinghoff, G., Rongen, M., Rott, C., Ruhe, T., Ruohan, L., Ryckbosch, D., Safa, I., Saffer, J., Salazar-Gallegos, D., Sampathkumar, P., Herrera, S. E. Sanchez, Sandrock, A., Santander, M., Sarkar, S., Savelberg, J., Savina, P., Schaufel, M., Schieler, H., Schindler, S., Schlickmann, L., Schlüter, B., Schlüter, F., Schmeisser, N., Schmidt, T., Schneider, J., Schröder, F. G., Schumacher, L., Schwefer, G., Sclafani, S., Seckel, D., Seikh, M., Seunarine, S., Shah, R., Sharma, A., Shefali, S., Shimizu, N., Silva, M., Skrzypek, B., Smithers, B., Snihur, R., Soedingrekso, J., Søgaard, A., Soldin, D., Soldin, P., Sommani, G., Spannfellner, C., Spiczak, G. M., Spiering, C., Stamatikos, M., Stanev, T., Stezelberger, T., Stürwald, T., Stuttard, T., Sullivan, G. W., Taboada, I., Ter-Antonyan, S., Thiesmeyer, M., Thompson, W. G., Thwaites, J., Tilav, S., Tollefson, K., Tönnis, C., Toscano, S., Tosi, D., Trettin, A., Tung, C. F., Turcotte, R., Twagirayezu, J. P., Ty, B., Elorrieta, M. A. Unland, Upadhyay, A. K., Upshaw, K., Valtonen-Mattila, N., Vandenbroucke, J., van Eijndhoven, N., Vannerom, D., van Santen, J., Vara, J., Veitch-Michaelis, J., Venugopal, M., Vereecken, M., Verpoest, S., Veske, D., Vijai, A., Walck, C., Weaver, C., Weigel, P., Weindl, A., Weldert, J., Wendt, C., Werthebach, J., Weyrauch, M., Whitehorn, N., Wiebusch, C. H., Willey, N., Williams, D. R., Witthaus, L., Wolf, A., Wolf, M., Wrede, G., Xu, X. W., Yanez, J. P., Yildizci, E., Yoshida, S., Young, R., Yu, F., Yu, S., Yuan, T., Zhang, Z., Zhelnin, P., and Zimmerman, M.

Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The IceCube Observatory at the South Pole has been operating in its full configuration since May 2011 with a duty cycle of about 99%. Its main component consists of a cubic-kilometer array of optical sensors deployed deep in the Glacial ice designed for the detection of high-energy astrophysical neutrinos. A surface array for cosmic ray air shower detection, IceTop, and a denser inner subdetector, DeepCore, significantly enhance the capabilities of the observatory, making it a multipurpose facility. This list of contributions to the 38th International Cosmic Ray Conference in Nagoya, Japan (July 26 - August 3, 2023) summarizes the latest results from IceCube covering a broad set of key questions in physics and astrophysics. The papers in this index are grouped topically to highlight IceCube contributions related to high-energy neutrino and multi-messenger astrophysics, cosmic-ray physics, low-energy neutrino transients such as Galactic supernovae, fundamental physics, detector calibration and event reconstruction, education and public outreach, and research and development for the IceCube Upgrade, a scheduled dense sensor infill complemented by calibration devices. Contributions related to IceCube-Gen2, the future extension of IceCube, are available in a separate collection., Comment: To access the list of contributions, please follow the "HTML" link. Links to individual contributions will fill in as authors upload their material

Published
2023

50. Search for Extended Sources of Neutrino Emission in the Galactic Plane with IceCube

Author

Abbasi, R., Ackermann, M., Adams, J., Agarwalla, S. K., Aguilar, J. A., Ahlers, M., Alameddine, J. M., Amin, N. M., Andeen, K., Anton, G., Argüelles, C., Ashida, Y., Athanasiadou, S., Axani, S. N., Bai, X., V., A. Balagopal, Baricevic, M., Barwick, S. W., Basu, V., Bay, R., Beatty, J. J., Tjus, J. Becker, Beise, J., Bellenghi, C., Benning, C., BenZvi, S., Berley, D., Bernardini, E., Besson, D. Z., Blaufuss, E., Blot, S., Bontempo, F., Book, J. Y., Meneguolo, C. Boscolo, Böser, S., Botner, O., Böttcher, J., Bourbeau, E., Braun, J., Brinson, B., Brostean-Kaiser, J., Burley, R. T., Busse, R. S., Butterfield, D., Campana, M. A., Carloni, K., Carnie-Bronca, E. G., Chattopadhyay, S., Chau, N., Chen, C., Chen, Z., Chirkin, D., Choi, S., Clark, B. A., Classen, L., Coleman, A., Collin, G. H., Connolly, A., Conrad, J. M., Coppin, P., Correa, P., Cowen, D. F., Dave, P., De Clercq, C., DeLaunay, J. J., Delgado, D., Deng, S., Deoskar, K., Desai, A., Desiati, P., de Vries, K. D., de Wasseige, G., DeYoung, T., Diaz, A., Díaz-Vélez, J. C., Dittmer, M., Domi, A., Dujmovic, H., DuVernois, M. A., Ehrhardt, T., Eller, P., Ellinger, E., Mentawi, S. El, Elsässer, D., Engel, R., Erpenbeck, H., Evans, J., Evenson, P. A., Fan, K. L., Fang, K., Farrag, K., Fazely, A. R., Fedynitch, A., Feigl, N., Fiedlschuster, S., Finley, C., Fischer, L., Fox, D., Franckowiak, A., Fritz, A., Fürst, P., Gallagher, J., Ganster, E., Garcia, A., Gerhardt, L., Ghadimi, A., Glaser, C., Glauch, T., Glüsenkamp, T., Goehlke, N., Gonzalez, J. G., Goswami, S., Grant, D., Gray, S. J., Gries, O., Griffin, S., Griswold, S., Groth, K. M., Günther, C., Gutjahr, P., Haack, C., Hallgren, A., Halliday, R., Halve, L., Halzen, F., Hamdaoui, H., Minh, M. Ha, Hanson, K., Hardin, J., Harnisch, A. A., Hatch, P., Haungs, A., Helbing, K., Hellrung, J., Henningsen, F., Heuermann, L., Heyer, N., Hickford, S., Hidvegi, A., Hill, C., Hill, G. C., Hoffman, K. D., Hori, S., Hoshina, K., Hou, W., Huber, T., Hultqvist, K., Hünnefeld, M., Hussain, R., Hymon, K., In, S., Ishihara, A., Jacquart, M., Janik, O., Jansson, M., Japaridze, G. S., Jeong, M., Jin, M., Jones, B. J. P., Kang, D., Kang, W., Kang, X., Kappes, A., Kappesser, D., Kardum, L., Karg, T., Karl, M., Karle, A., Katz, U., Kauer, M., Kelley, J. L., Zathul, A. Khatee, Kheirandish, A., Kiryluk, J., Klein, S. R., Kochocki, A., Koirala, R., Kolanoski, H., Kontrimas, T., Köpke, L., Kopper, C., Koskinen, D. J., Koundal, P., Kovacevich, M., Kowalski, M., Kozynets, T., Krishnamoorthi, J., Kruiswijk, K., Krupczak, E., Kumar, A., Kun, E., Kurahashi, N., Lad, N., Gualda, C. Lagunas, Lamoureux, M., Larson, M. J., Latseva, S., Lauber, F., Lazar, J. P., Lee, J. W., DeHolton, K. Leonard, Leszczyńska, A., Lincetto, M., Liu, Q. R., Liubarska, M., Lohfink, E., Love, C., Mariscal, C. J. Lozano, Lu, L., Lucarelli, F., Luszczak, W., Lyu, Y., Madsen, J., Mahn, K. B. M., Makino, Y., Manao, E., Mancina, S., Sainte, W. Marie, Mariş, I. C., Marka, S., Marka, Z., Marsee, M., Martinez-Soler, I., Maruyama, R., Mayhew, F., McElroy, T., McNally, F., Mead, J. V., Meagher, K., Mechbal, S., Medina, A., Meier, M., Merckx, Y., Merten, L., Micallef, J., Mitchell, J., Montaruli, T., Moore, R. W., Morii, Y., Morse, R., Moulai, M., Mukherjee, T., Naab, R., Nagai, R., Nakos, M., Naumann, U., Necker, J., Negi, A., Neumann, M., Niederhausen, H., Nisa, M. U., Noell, A., Novikov, A., Nowicki, S. C., Pollmann, A. Obertacke, O'Dell, V., Oehler, M., Oeyen, B., Olivas, A., Orsoe, R., Osborn, J., O'Sullivan, E., Pandya, H., Park, N., Parker, G. K., Paudel, E. N., Paul, L., Heros, C. Pérez de los, Peterson, J., Philippen, S., Pizzuto, A., Plum, M., Pontén, A., Popovych, Y., Rodriguez, M. Prado, Pries, B., Procter-Murphy, R., Przybylski, G. 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Subjects
Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Astrophysics of Galaxies, High Energy Physics - Experiment
Abstract

The Galactic plane, harboring a diffuse neutrino flux, is a particularly interesting target to study potential cosmic-ray acceleration sites. Recent gamma-ray observations by HAWC and LHAASO have presented evidence for multiple Galactic sources that exhibit a spatially extended morphology and have energy spectra continuing beyond 100 TeV. A fraction of such emission could be produced by interactions of accelerated hadronic cosmic rays, resulting in an excess of high-energy neutrinos clustered near these regions. Using 10 years of IceCube data comprising track-like events that originate from charged-current muon neutrino interactions, we perform a dedicated search for extended neutrino sources in the Galaxy. We find no evidence for time-integrated neutrino emission from the potential extended sources studied in the Galactic plane. The most significant location, at 2.6$\sigma$ post-trials, is a 1.7$^\circ$ sized region coincident with the unidentified TeV gamma-ray source 3HWC J1951+266. We provide strong constraints on hadronic emission from several regions in the Galaxy., Comment: 13 pages, 4 figures, 5 tables including an appendix. Accepted for publication in Astrophysical Journal

Published
2023
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