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Probing the CP nature of the top–Higgs Yukawa coupling in tt¯H and tH events with H→bb¯ decays using the ATLAS detector at the LHC

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 849卷

作者： Aad, G. Abbott, B. Abbott, D.C. Abed Abud, A. Abeling, K. Abhayasinghe, D.K. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Achkar, B. Adam, L. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Adelman, J. Adiguzel, A. Adorni, S. Adye, T. Affolder, A.A. Afik, Y. Agapopoulou, C. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ai, X. Aielli, G. Aizenberg, I. Akatsuka, S. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Alconada Verzini, M.J. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, A. Alfonsi, F. Alhroob, M. Ali, B. Ali, S. Aliev, M. Alimonti, G. Allaire, C. Allbrooke, B.M.M. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alunno Camelia, E. Alvarez Estevez, M. Alviggi, M.G. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amoroso, S. Amos, K.R. Amrouche, C.S. Ananiev, V. Anastopoulos, C. Andari, N. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Anelli, C.R. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Aranzabal, N. Araujo Ferraz, V. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Armbruster, A.J. Armstrong, A. Arnaez, O. Arnold, H. Arrubarrena Tame, Z.P. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Asimakopoulou, E.M. Asquith, L. Assahsah, J. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Austrup, V.A. Avner, G. Avolio, G. Ayoub, M.K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahrasemani, H. Bailey, A.J. Bailey, V.R. Baines, J.T. Bakalis, C. Baker, O.K. Bakker, P.J. Bakos, E. Bakshi Gupta, D. Balaji, S. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene CPPM Aix-Marseille Université CNRS IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States Department of Physics University of Massachusetts Amherst MA United States CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Physics Department Brookhaven National Laboratory Upton NY United States Mohammed VI Polytechnic University Ben Guerir Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne IL United States Departamento de Física Pontificia Universidad Católica de Chile Santiago Chile INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom Institut für Physik Universität Mainz Mainz Germany LAPP Univ. Savoie Mont Blanc CNRS IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics University of Toronto Toronto ON Canada Department of Physics Brandeis University Waltham MA United States Department of Physics Northern Illinois University DeKalb IL United States Istanbul University Dept. of Physics Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA United States IJCLab Université Paris-Saclay CNRS IN2P3 Orsay 91405 France Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia

The CP properties of the coupling between the Higgs boson and the top quark are investigated using 139 fb−1 of proton–proton collision data recorded by the ATLAS experiment at the LHC at a centre-of-mass energy of s=...

The CP properties of the coupling between the Higgs boson and the top quark are investigated using 139 fb⁻¹ of proton–proton collision data recorded by the ATLAS experiment at the LHC at a centre-of-mass energy of s=13 TeV. The CP structure of the top quark–Higgs boson Yukawa coupling is probed in events with a Higgs boson decaying into a pair of b-quarks and produced in association with either a pair of top quarks, tt¯H, or a single top quark, tH. Events containing one or two electrons or muons are used for the measurement. Multivariate techniques are used to select regions enriched in tt¯H and tH events, where dedicated CP-sensitive observables are exploited. In an extension of the Standard Model (SM) with a CP-odd admixture in the top–Higgs Yukawa coupling, the mixing angle between CP-even and CP-odd couplings is measured to be α=11−73^∘ ^{∘+52^∘}, compatible with the SM prediction corresponding to α=0.

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Search for the Zγ decay mode of new high-mass resonances in pp collisions at s=13 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 848卷

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The s=13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb⁻¹. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV. © 2023 The Author(s)

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Classification of Major Depressive Disorder Using Vertex-Wise Brain Sulcal Depth, Curvature, and Thickness with a Deep and a Shallow Learning Model

arXiv

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arXiv 2023年

作者： Goya-Maldonado, Roberto Erwin-Grabner, Tracy Zeng, Ling-Li Ching, Christopher R.K. Aleman, Andre Amod, Alyssa R. Basgoze, Zeynep Benedetti, Francesco Besteher, Bianca Brosch, Katharina Bülow, Robin Colle, Romain Connolly, Colm G. Corruble, Emmanuelle Couvy-Duchesne, Baptiste Cullen, Kathryn Dannlowski, Udo Davey, Christopher G. Dols, Annemiek Ernsting, Jan Evans, Jennifer W. Fisch, Lukas Fuentes-Claramonte, Paola Gonul, Ali Saffet Gotlib, Ian H. Grabe, Hans J. Groenewold, Nynke A. Grotegerd, Dominik Hahn, Tim Hamilton, J. Paul Han, Laura K.M. Harrison, Ben J. Ho, Tiffany C. Jahanshad, Neda Jamieson, Alec J. Karuk, Andriana Kircher, Tilo Klimes-Dougan, Bonnie Koopowitz, Sheri-Michelle Lancaster, Thomas Leenings, Ramona Li, Meng Linden, David E.J. MacMaster, Frank P. Mehler, David M.A. Meinert, Susanne Melloni, Elisa Mueller, Bryon A. Mwangi, Benson Nenadić, Igor Ojha, Amar Okamoto, Yasumasa Oudega, Mardien L. Penninx, Brenda W.J.H. Poletti, Sara Pomarol-Clotet, Edith Portella, Maria J. Pozzi, Elena Radua, Joaquim Rodríguez-Cano, Elena Sacchet, Matthew D. Salvador, Raymond Schrantee, Anouk Sim, Kang Soares, Jair C. Solanes, Aleix Stein, Dan J. Stein, Frederike Stolicyn, Aleks Thomopoulos, Sophia I. Toenders, Yara J. Uyar-Demir, Aslihan Vieta, Eduard Vives-Gilabert, Yolanda Völzke, Henry Walter, Martin Whalley, Heather C. Whittle, Sarah Winter, Nils Wittfeld, Katharina Wright, Margaret J. Wu, Mon-Ju Yang, Tony T. Zarate, Carlos Veltman, Dick J. Schmaal, Lianne Thompson, Paul M. Georg-August University Göttingen Germany College of Intelligence Science and Technology National University of Defense Technology Changsha410073 China Imaging Genetics Center Mark & Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine University of Southern California Marina del ReyCA90274 United States Department of Biomedical Sciences of Cells and Systems University Medical Center Groningen University of Groningen Groningen Netherlands Department of Psychiatry & Mental Health Neuroscience Institute University of Cape Town Cape Town South Africa Department of Psychiatry and Behavioral Science University of Minnesota Medical School MinneapolisMN United States Division of Neuroscience IRCCS Scientific Institute Ospedale San Raffaele Milano Italy Department of Psychiatry and Psychotherapy Jena University Hospital Jena Germany Department of Psychiatry and Psychotherapy University of Marburg Rudolf Bultmann Str. 8 Marburg35039 Germany Institute for Radiology and Neuroradiology University Medicine Greifswald Greifswald Germany MOODS Team CESP INSERM U1018 Faculté de Médecine Univ Paris-Saclay Le Kremlin Bicêtre94275 France Service Hospitalo Universitaire de Psychiatrie de Bicêtre Hôpitaux Universitaires Paris-Saclay Assistance Publique-Hôpitaux deParis Hôpital de Bicêtre Le Kremlin BicêtreF-94275 France Department of Biomedical Sciences Florida State University TallahasseeFL United States Sorbonne University Paris Brain Institute - ICM CNRS Inria Inserm AP-HP Hôpital de la Pitié Salpêtrière ParisF-75013 France Institute for Molecular Bioscience the University of Queensland St LuciaQLD Australia Institute for Translational Psychiatry University of Münster Münster Germany Melbourne Neuropsychiatry Centre Department of Psychiatry the University of Melbourne ParkvilleVIC Australia Department of Psychiatry Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam Neuroscience Amsterdam Public Health Research Institute Am

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing 7,012 participants from 30 sites (N=2,772 MDD and N=4,240 HC), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%;SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%;SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible. Future studies are needed to determine whether more sophisticated integration of information from ot

关键词： Support vector machines

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PFC and Fuzzy based PI controller for bidirectional DC/DC converter of Buck mode in HEV 30

PFC and Fuzzy based PI controller for bidirectional DC/DC co...

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30th Chinese Control and Decision Conference, CCDC 2018

作者： Han, Kai Tao, Jili Ridong, Zhang Huiyu, Zhou School of Information Science and Engineering Ningbo Institute of Technology Zhejiang University Ningbo315100 China Key Lab for IOT and Information Fusion Technology of Zhejiang Information and Control Institute Hangzhou Dianzi University Hangzhou310018 China Department of Informatics University of Leicester LE1 7RH United Kingdom

ISBN: (纸本)9781538612439

It is important to control input and output power of bidirectional DC/DC converter for fuel cell and Ultra-capacitor equipped hybrid energy vehicle. The small signal equivalent model of bidirectional DC/DC converter in the buck mode is first established to obtain its transfer function. And a double loop of voltage and current is designed for the power control of bidirectional DC/DC. The non-minimum state space model is then deduced to initialize the PI controller parameters offline based on the predictive functional control (PFC) and Fuzzy rules are designed to tune the PI controller online. Simulation results of the proposed controller show that the set power can be achieved quickly by comparing with traditional PI controller and PFC based PI controller. © 2018 IEEE.

关键词： Voltage control Tuning Fuzzy control Transfer functions Hybrid electric vehicles Capacitance Process control

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Comparative analyses for plant virus-based cancer immunotherapy drug development

Cell Biomaterials

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Cell Biomaterials 2025年

作者： Anthony O. Omole Hannah S. Newton Edward Cedrone Kimia Nematpour Shaojun Xie Yongmei Zhao Bao Tran Marina A. Dobrovolskaia Nicole F. Steinmetz Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California San Diego La Jolla San Diego CA 92093 USA Shu and K.C. Chien and Peter Farrell Collaboratory University of California San Diego La Jolla San Diego CA 92093 USA Center for Nano-ImmunoEngineering University of California San Diego La Jolla San Diego CA 92093 USA Moores Cancer Center University of California San Diego La Jolla San Diego CA 92093 USA Nanotechnology Characterization Lab Cancer Research Technology Program Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute Frederick MD 21702 USA Sequencing Facility Bioinformatics Group Biomedical Informatics and Data Science Directorate Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute Frederick MD 21702 USA CCR Sequencing Facility Cancer Research Technology Program Frederick National Laboratory for Cancer Research sponsored by the National Cancer Institute Frederick MD 21702 USA Department of Bioengineering University of California San Diego La Jolla San Diego CA 92093 USA Department of Radiology University of California San Diego La Jolla San Diego CA USA Institute for Materials Discovery and Design University of California San Diego La Jolla San Diego CA 92093 USA Center for Engineering in Cancer Institute of Engineering Medicine University of California San Diego La Jolla San Diego CA 92093 USA

Cowpea mosaic virus (CPMV) is a plant virus with potent anti-tumor efficacy. Intratumoral CPMV, but not cowpea chlorotic mottle virus (CCMV), reprograms the tumor microenvironment priming durable, systemic anti-tumor immunity. Here, we performed a side-by-side mechanism of action comparison between CPMV and CCMV. Through immune-multiplexing and trafficking studies we observed that CPMV and CCMV are taken up by innate immune cells at similar rates but are processed differently. While CCMV induces proinflammatory interleukins 22, 23, and 27, CPMV is a strong inducer of type I, II, and III interferons, which contribute to the activation and enhancement of immune cell function. We observed that CPMV RNAs activate Toll-like receptor (TLR) 7 upon delivery—and not CCMV RNAs; CPMV RNAs persist longer within cells compared with CCMV. Taken together, this work identifies determinants for CPMV’s unique mechanism for intratumoral immunotherapy. It also broadens our understanding of the utility of plant viruses for biomedical applications.

关键词： plant viruses intratumoral immunotherapy cowpea mosaic virus cowpea chlorotic mottle virus cancer nanotechnology

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Forecasting intracranial hypertension using multi-scale waveform metrics

arXiv

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arXiv 2019年

作者： Hüser, Matthias Kündig, Adrian Karlen, Walter De Luca, Valeria Jaggi, Martin Biomedical Informatics Group Department of Computer Science ETH Zürich Universitätstrasse 6 Zürich8092 Switzerland Mobile Health Systems Lab Institute of Robotics and Intelligent Systems Department of Health Sciences and Technology ETH Zürich Zürich8008 Switzerland Department of Information Technology and Electrical Engineering ETH Zürich Zürich8092 Switzerland Machine Learning & Optimization Lab EPFL Lausanne1015 Switzerland

Objective: Acute intracranial hypertension is an important risk factor of secondary brain damage after traumatic brain injury. Hypertensive episodes are often diagnosed reactively, leading to late detection and lost time for intervention planning. A pro-active approach that predicts critical events several hours ahead of time could assist in directing attention to patients at risk. Approach: We developed a prediction framework that forecasts onsets of acute intracranial hypertension in the next 8 hours. It jointly uses cerebral auto-regulation indices, spectral energies and morphological pulse metrics to describe the neurological state of the patient. One-minute base windows were compressed by computing signal metrics, and then stored in a multi-scale history, from which physiological features were derived. Main results: Our model predicted events up to 8 hours in advance with alarm recall rates of 90% at a precision of 30.3% in the MIMIC-III waveform database, improving upon two baselines from the literature. We found that features derived from high-frequency waveforms substantially improved the prediction performance over simple statistical summaries of low-frequency time serie1s, and each of the three feature classes contributed to the performance gain. The inclusion of long-term history up to 8 hours was especially important. Significance: Our results highlight the importance of information contained in high-frequency waveforms in the neurological intensive care unit. They could motivate future studies on pre-hypertensive patterns and the design of new alarm algorithms for critical events in the injured brain. Copyright © 2019, The Authors. All rights reserved.

关键词： Morphology

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Automatic system for stitching microscopic images using OpenPano

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AIP Conference Proceedings 2020年第1期2314卷

作者： Imas Sukaesih Sitanggang Auriza Akbar Riries Rulaningtyas Andriyan Bayu Suksmono Kuwat Triyana Dwi Winarni 1Departement of Computer Science IPB University Bogor Indonesia 2Department of Physics Airlangga University Surabaya. Indonesia 3School of Electrical Engineering and Informatics Institute of technology Bandung Bandung Indonesia 4Department of Physics Gadjah Mada University Yogyakarta Indonesia 5Department of Biology Faculty of Science and Technology Airlangga University Surabaya Indonesia

Analyzing pap smear images by manual reading through a microscope is a challenge for doctors especially in distinguishing epithelial cells from inflammatory cells. A computer-based application is required for cervical cancer screening and displaying the results of reading automatically pap smear images using a microscope. This study aims to develop a module for stitching microscopic images including pap smear images which are collected from a microscope. A module for automatically stitching pap smear images is an important component in pap smear images management system. There are three tasks in stitching several pap smear images which were implemented in this study. Those three tasks include 1) feature extraction with scale-invariant feature transform, 2) estimation of homography or affine transformation by random sample consensus and 3) optimization of connection between images with bundle adjustment and blending. We use OpenPano to implement those three tasks. The system has successfully stitched the pap smear images with the feature overlap among the images greater than 10%. The stitched pap smear image has good quality after smoothing using the vertical blending step. In addition, blurry pixels on in some spots disappeared after performing the stitching error. The image quality has been improved after the multiband blending using 16-band and 128-band which shows the significant improvement on the 128-band. The system is expected to assist doctors in pap smear image identification.

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Search for pair-production of vector-like quarks in pp collision events at s=13 TeV with at least one leptonically decaying Z boson and a third-generation quark with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2023年 843卷

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Aly, M. Alviggi, M.G. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arbiol Val, S.J. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assahsah, J. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramonte, M. Bandyopadh Department of Physics University of Adelaide Adelaide Australia Department of Physics University of Alberta Edmonton AB Canada Department of Physics Ankara University Ankara Turkey Istanbul Aydin University Application and Research Center for Advanced Studies Istanbul Turkey Division of Physics TOBB University of Economics and Technology Ankara Turkey LAPP Univ. Savoie Mont Blanc CNRS/IN2P3 Annecy France High Energy Physics Division Argonne National Laboratory Argonne IL United States Department of Physics University of Arizona Tucson AZ United States Department of Physics University of Texas at Arlington Arlington TX United States Physics Department National and Kapodistrian University of Athens Athens Greece Physics Department National Technical University of Athens Zografou Greece Department of Physics University of Texas at Austin Austin TX United States Bahcesehir University Faculty of Engineering and Natural Sciences Istanbul Turkey Istanbul Bilgi University Faculty of Engineering and Natural Sciences Istanbul Turkey Department of Physics Bogazici University Istanbul Turkey Department of Physics Engineering Gaziantep University Gaziantep Turkey Institut de Física d'Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain Institute of High Energy Physics Chinese Academy of Sciences Beijing China Physics Department Tsinghua University Beijing China Department of Physics Nanjing University Nanjing China University of Chinese Academy of Science (UCAS) Beijing China Institute of Physics University of Belgrade Belgrade Serbia Department for Physics and Technology University of Bergen Bergen Norway Physics Division Lawrence Berkeley National Laboratory Berkeley CA United States Institut für Physik Humboldt Universität zu Berlin Berlin Germany Albert Einstein Center for Fundamental Physics Laboratory for High Energy Physics University of Bern Bern Switzerland School of Physics and Astronomy University of

A search for the pair-production of vector-like quarks optimized for decays into a Z boson and a third-generation Standard Model quark is presented, using the full Run 2 dataset corresponding to 139fb⁻¹ of pp collisions at s=13TeV, collected in 2015–2018 with the ATLAS detector at the Large Hadron Collider. The targeted final state is characterized by the presence of a Z boson with high transverse momentum, reconstructed from a pair of same-flavour leptons with opposite-sign charges, as well as by the presence of b-tagged jets and high-transverse-momentum large-radius jets reconstructed from calibrated smaller-radius jets. Events with exactly two or at least three leptons are used, which are further categorized by the presence of boosted W, Z, and Higgs bosons and top quarks. The categorization is performed using a neural-network-based boosted object tagger to enhance the sensitivity to signal relative to the background. No significant excess above the background expectation is observed and exclusion limits at 95% confidence level are set on the masses of the vector-like partners T and B of the top and bottom quarks, respectively. The limits depend on the branching ratio configurations and, in the case of 100% branching ratio for T→Zt and 100% branching ratio for B→Zb, this search sets the most stringent limits to date, allowing m_T>1.60TeV and m_B>1.42TeV, respectively. © 2023 The Author(s)

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Retracted: Designing Data Mining Applications with Rough Set Algorithm for Provision of Recommendations in the Selection of Training Topics on Online Learning

Retracted: Designing Data Mining Applications with Rough Set...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer science, Information Systems, and Information technology, WMA-Mathcomtech 2018

作者： Manurung, Hotler Ongko, Erianto Harahap, Astro Julida Hartono, H. Abdullah, Dahlan Erliana, Cut Ita Sriadhi, S. Kusuma Putra, Aditya Halim Perdana Muslim, M. Ahmad, Hamzah Nanuru, Ricardo Freedom Saleh, A.A. Indahingwati, Asmara Kurniawan, Citra Indra Iswara, Ida Bagus Ary Hasibuan, Abdurrozzaq Wuryani, Eni Hadikurniawati, Wiwien Winarno, Edy Department of Informatics Akademi Teknologi Industri Immanuel Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Department of Management STIM Lasharan Jaya Makassar Indonesia Department of Accounting Universitas Muslim Indonesia Makassar Indonesia Universitas Kristen Indonesia Maluku. Ambon Indonesia Statistics Financial and Social Sciences Research Group Indonesia Manajement School of Economics Indonesia STIESIA Surabaya Indonesia Department of Electrical Engineering Sekolah Tinggi Teknik Malang Malang Indonesia Informatics Department STMIK STIKOM Indonesia Faculty of Engineering Universitas Islam Sumatera Utara Medan Indonesia Department of Accounting Universitas Negeri Surabaya Surabaya Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Online Learning is a learning model that utilizes internet network. As one of the institutions providing vocational education, ATI Immanuel is planned to implement online learning for improving the quality of education. help learners in choosing learning topics. The concept of data mining itself is a process of analysis of the database of students learning ATI Immanuel which has been collected and will be obtained patterns of student behavior in learning. The results of the study are expected to help online learning participants in this case ATI Immanuel students so they can choose the best training topics. Data mining applications with this rough set algorithm will be designed using PHP Programming Language and using System Development Life Cycle (SDLC) design method. © Published under licence by IOP Publishing Ltd.

关键词： Data mining

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Search for the charged-lepton-flavor-violating decay Z→eμ in pp collisions at s=13 TeV with the ATLAS detector

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Physical Review D 2023年第3期108卷 032015-032015页

作者： G. Aad B. Abbott D. C. Abbott A. Abed Abud K. Abeling D. K. Abhayasinghe S. H. Abidi A. Aboulhorma H. Abramowicz H. Abreu Y. Abulaiti A. C. Abusleme Hoffman B. S. Acharya B. Achkar L. Adam C. Adam Bourdarios L. Adamczyk L. Adamek S. V. Addepalli J. Adelman A. Adiguzel S. Adorni T. Adye A. A. Affolder Y. Afik C. Agapopoulou M. N. Agaras J. Agarwala A. Aggarwal C. Agheorghiesei J. A. Aguilar-Saavedra A. Ahmad F. Ahmadov W. S. Ahmed X. Ai G. Aielli I. Aizenberg S. Akatsuka M. Akbiyik T. P. A. Åkesson A. V. Akimov K. Al Khoury G. L. Alberghi J. Albert P. Albicocco M. J. Alconada Verzini S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos A. Alfonsi F. Alfonsi M. Alhroob B. Ali S. Ali M. Aliev G. Alimonti C. Allaire B. M. M. Allbrooke P. P. Allport A. Aloisio F. Alonso C. Alpigiani E. Alunno Camelia M. Alvarez Estevez M. G. Alviggi Y. Amaral Coutinho A. Ambler L. Ambroz C. Amelung D. Amidei S. P. Amor Dos Santos S. Amoroso K. R. Amos C. S. Amrouche V. Ananiev C. Anastopoulos N. Andari T. Andeen J. K. Anders S. Y. Andrean A. Andreazza S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli D. J. A. Antrim F. Anulli M. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella N. Aranzabal V. Araujo Ferraz C. Arcangeletti A. T. H. Arce E. Arena J.-F. Arguin S. Argyropoulos J.-H. Arling A. J. Armbruster A. Armstrong O. Arnaez H. Arnold Z. P. Arrubarrena Tame G. Artoni H. Asada K. Asai S. Asai N. A. Asbah E. M. Asimakopoulou L. Asquith J. Assahsah K. Assamagan R. Astalos R. J. Atkin M. Atkinson N. B. Atlay H. Atmani P. A. Atmasiddha K. Augsten S. Auricchio V. A. Austrup G. Avner G. Avolio M. K. Ayoub G. Azuelos D. Babal H. Bachacou K. Bachas A. Bachiu F. Backman A. Badea P. Bagnaia H. Bahrasemani A. J. Bailey V. R. Bailey J. T. Baines C. Bakalis O. K. Baker P. J. Bakker E. Bakos D. Bakshi Gupta S. Balaji R. Balasubramanian E. M. Baldin P. Balek E. Ballabene F. Balli L. M. Baltes W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay S. Bansal L. Barak E. L. B CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Department of Physics University of Massachusetts Amherst Massachusetts USA CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Physics Department Brookhaven National Laboratory Upton New York USA Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne Illinois USA Departamento de Física Pontificia Universidad Católica de Chile Santiago Chile INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Institut für Physik Universität Mainz Mainz Germany LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics University of Toronto Toronto Ontario Canada Department of Physics Brandeis University Waltham Massachusetts USA Department of Physics Northern Illinois University DeKalb Illinois USA New York University Abu Dhabi Abu Dhabi United Arab Emirates United Arab Emirates University Al Ain United Arab Emirates University of Sharjah Sharjah United Arab Emirates Department of Physics Bogazici University Istanbul Türkiye Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA IJCLab Université Paris-Saclay CNRS/IN2P3 91405 Orsay France Institut de Física d’

A search for the charged-lepton-flavor-violating process Z→eμ is presented, using 139 fb−1 of s=13 TeV pp collision data collected by the ATLAS experiment at the LHC. An excess in the eμ invariant mass spectrum near the Z boson mass would be a striking signature of new physics. No excess is observed, and an upper limit B(Z→eμ)<2.62×10−7 is placed on the branching fraction at 95% confidence level, which is the most stringent limit to date.

关键词： Particle decays Particle phenomena Electrons Leptons Muons W & Z bosons Flavor symmetries Hadron colliders

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