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| WoS | SCOPUS | Document Type | Document Title | Abstract | Authors | Affiliation | ResearcherID (WoS) | AuthorsID (SCOPUS) | Author Email(s) | Journal Name | JCR Abbreviation | ISSN | eISSN | Volume | Issue | WoS Edition | WoS Category | JCR Year | IF | JCR (%) | FWCI | FWCI Update Date | WoS Citation | SCOPUS Citation | Keywords (WoS) | KeywordsPlus (WoS) | Keywords (SCOPUS) | KeywordsPlus (SCOPUS) | Language | Publication Stage | Publication Year | Publication Date | DOI | JCR Link | DOI Link | WOS Link | SCOPUS Link |
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| ○ | ○ | Article | Double-pion electroproduction off protons in deuterium: Quasifree cross sections and final-state interactions | The single-differential and fully integrated cross sections for quasifree pi(+) pi(-) electroproduction off protons bound in deuterium have been extracted for the first time. The experimental data were collected at Jefferson Laboratory with the CLAS detector. The measurements were performed in the kinematic region of the invariant mass W from 1.3 to 1.825 GeV and the photon virtuality Q(2) from 0.4 to 1.0 GeV2. Sufficient experimental statistics allowed for narrow binning in all kinematic variables, while maintaining a small statistical uncertainty. The extracted cross sections were compared with the corresponding cross sections off free protons, which allowed us to obtain an estimate of the contribution from events in which interactions between the final-state hadrons and the spectator neutron took place. | Skorodumina, Iu. A.; Fedotov, G. V.; Gothe, R. W.; Achenbach, P.; Akbar, Z.; Alvarado, J. S.; Amaryan, M. J.; Armstrong, Whitney R.; Atac, H.; Avakian, H.; Gayoso, C. Ayerbe; Baashen, L.; Baltzell, N. A.; Barion, L.; Battaglieri, M.; Benkel, B.; Benmokhtar, Fatiha; Bianconi, A.; Biselli, A. S.; Boiarinov, S.; Bossu, F.; Brinkmann, K. -Th.; Briscoe, W. J.; Brooks, W. K.; Bulumulla, D.; Burkert, V. D.; Capobianco, R.; Carman, D. S.; Chatagnon, P.; Chetry, T.; Ciullo, G.; Cole, P. L.; Contalbrigo, M.; Costantini, G.; D'Angelo, A.; Dashyan, N.; De Vita, R.; Deur, A.; Diehl, S.; Djalali, C.; Dupre, R.; Egiyan, H.; El Alaoui, A.; El Fassi, L.; Eugenio, P.; Filippi, A.; Fogler, C.; Gavalian, G.; Gilfoyle, G. P.; Girod, F. X.; Golubenko, A. A.; Gosta, G.; Griffioen, K. A.; Hafidi, K.; Hakobyan, H.; Hattawy, M.; Hayward, T. B.; Heddle, D.; Hobart, A.; Holtrop, M.; Hung, Yu-Chun; Ilieva, Y.; Ireland, D. G.; Isupov, E. L.; Jo, H. S.; Joo, K.; Joosten, S.; Keller, D.; Khanal, A.; Khandaker, M.; Kim, A.; Kim, W.; Klein, F. J.; Klimenko, V.; Kripko, A.; Kubarovsky, V.; Lanza, L.; Lee, S.; Lenisa, P.; Livingston, K.; MacGregor, I. J. D.; Marchand, D.; Mascagna, V.; McKinnon, B.; Migliorati, S.; Mineeva, T.; Mirazita, M.; Mokeev, V.; Camacho, C. Munoz; Nadel-Turonski, P.; Naidoo, P.; Neupane, K.; Niccolai, S.; Osipenko, M.; Ouillon, M.; Pandey, P.; Pappalardo, L. L.; Paremuzyan, R.; Pasyuk, E.; Paul, S. J.; Phelps, W.; Pilleux, N.; Pokhrel, M.; Poudel, J.; Prok, Y.; Raue, B. A.; Reed, Trevor; Richards, J.; Ripani, M.; Ritman, J.; Rossi, P.; Salgado, C.; Schadmand, S.; Schmidt, A.; Schumacher, R. A.; Sharabian, Y. G.; Shirokov, E. V.; Shrestha, U.; Sparveris, N.; Spreafico, M.; Strauch, S.; Trotta, N.; Tyson, R.; Ungaro, M.; Vallarino, S.; Venturelli, L.; Voskanyan, H.; Voutier, E.; Watts, D. P.; Wei, X.; Williams, R.; Wishart, R.; Wood, M. H.; Yurov, M.; Zachariou, N.; Zhao, Z. W.; Ziegler, V. | Argonne Natl Lab, Argonne, IL 60439 USA; Arizona State Univ, Tempe, AZ 85287 USA; Canisius Coll, Buffalo, NY 14208 USA; Carnegie Mellon Univ, Pittsburgh, PA 15213 USA; Catholic Univ Amer, Washington, DC 20064 USA; Christopher Newport Univ, Newport News, VA 23606 USA; Coll William & Mary, Williamsburg, VA 23187 USA; Duke Univ, Durham, NC 27708 USA; Duquesne Univ, Pittsburgh, PA 15282 USA; Fairfield Univ, Fairfield, CT 06824 USA; Florida Int Univ, Miami, FL 33199 USA; Florida State Univ, Tallahassee, FL 32306 USA; George Washington Univ, Washington, DC 20052 USA; GSI Helmholtzzentrum Schwerionenforsch GmbH, D-64291 Darmstadt, Germany; INFN, Sez Ferrara, I-44100 Ferrara, Italy; INFN, Lab Nazl Frascati, I-00044 Frascati, Italy; INFN, Sez Genova, I-16146 Genoa, Italy; INFN, Sez Pavia, I-27100 Pavia, Italy; INFN, Sez Roma Tor Vergata, I-00133 Rome, Italy; INFN, Sez Torino, I-10125 Turin, Italy; Univ Paris Saclay, IRFU, CEA, F-91191 Gif Sur Yvette, France; Kyungpook Natl Univ, Daegu 41566, South Korea; Lamar Univ, Beaumont, TX 77710 USA; Mississippi State Univ, Mississippi State, MS 39762 USA; Kurchatov Inst, Natl Res Ctr, BP Konstantinov Petersburg Nucl Phys Inst, St Petersburg 188300, Russia; Norfolk State Univ, Norfolk, VA 23504 USA; Ohio Univ, Athens, OH 45701 USA; Old Dominion Univ, Norfolk, VA 23529 USA; Univ Giessen, Phys Inst 2, D-35392 Giessen, Germany; Rensselaer Polytech Inst, Troy, NY 12180 USA; Ruhr Univ Bochum, D-44801 Bochum, Germany; Lomonosov Moscow State Univ, Skobeltsyn Inst Nucl Phys, Moscow 119234, Russia; Temple Univ, Philadelphia, PA 19122 USA; Thomas Jefferson Natl Accelerator Facil, Newport News, VA 23606 USA; Univ Brescia, I-25123 Brescia, Italy; Univ Calif Riverside, Riverside, CA 92521 USA; Univ Connecticut, Storrs, CT 06269 USA; Univ Ferrara, I-44121 Ferrara, Italy; Univ Glasgow, Glasgow G12 8QQ, Scotland; Univ New Hampshire, Durham, NH 03824 USA; Univ Paris Saclay, CNRS, IN2P3, IJCLab, F-91405 Orsay, France; Univ Richmond, Richmond, VA 23173 USA; Univ Roma Tor Vergata, I-00133 Rome, Italy; Univ South Carolina, Columbia, SC 29208 USA; Uni Tecn Federico Santa Maria, Casilla 110-5, Valparaiso, Chile; Univ Virginia, Charlottesville, VA 22901 USA; Univ York, York YO10 5DD, England; Yerevan Phys Inst, Yerevan 375036, Armenia | Baashen, Lamya/KRP-2733-2024; Lee, Sangbaek/MVV-9130-2025; Filippi, Alessandra/JHU-4272-2023; Jo, Hyon-Suk/HGC-7070-2022; Mineeva, Taisiya/MDT-1592-2025; Sparveris, Nikolaos/C-4751-2008; Wood, Mary/AAW-7514-2021; Joosten, Sylvester/HZL-4182-2023; McKinnon, Bryan/J-2928-2018; Holtrop, Maurik/A-9017-2010; Brooks, William/C-8636-2013; Mascagna, Valerio/HLQ-1103-2023; Khanal, Aaditya/ABI-5610-2020; Zhao, Zhi-Wen/HZI-5398-2023; Osipenko, Mikhail/N-8292-2015; Bianconi, Antonio/J-3997-2013; Pappalardo, Luciano/AAB-2380-2021; Costantini, Giulio/F-3829-2018; Alaoui, Ahmed/B-4638-2015; D'Angelo, Annalisa/A-2439-2012; Bozzi, Giuseppe/H-7283-2017; POUDEL, JIWAN/KQU-6557-2024; Tyson, Richard/LRC-4125-2024; Isupov, Evgeny/J-2976-2012; Battaglieri, Marco/I-6262-2018; Ireland, David/E-8618-2010; Schumacher, Reinhard/K-6455-2013; Burkert, Volker/AAF-7395-2020; Hyde, Charles/W-9190-2018; Deur, Alexandre/H-9778-2019; Achenbach, Patrick/AAB-4394-2020; Pokhrel, Madhusudhan/LGY-9951-2024; Adikaram, Dasuni/D-1539-2016; Lanza, Lucilla/E-6479-2017; MacGregor, Ian/D-4072-2011; Zachariou, Nicholas/R-8360-2018 | 55834228500; 57215092344; 7102183142; 7004424420; 57220423310; 57211254204; 35277104000; 57221249616; 57210826461; 7006613415; 15755099700; 57215197650; 35226938500; 23033257000; 7004520678; 57605743600; 57218527298; 7102358422; 35227021700; 35277071300; 35725064700; 7007041327; 56550149800; 35400106000; 57218357843; 7004440244; 57221140443; 7005853901; 57202987431; 57189889203; 6603765308; 35227101500; 7003468594; 57221147612; 55828029600; 6507987909; 59345445900; 6604025441; 57217562965; 35374416600; 35069234100; 35227171500; 26535686800; 14041647600; 57215091978; 8695796100; 57210218314; 35227304900; 6603686320; 35227280900; 57210932456; 56711891800; 57217000308; 34570410000; 57208726428; 56115055200; 57206656408; 7003821864; 57214681432; 7005060869; 58515451800; 35227424100; 7006927902; 35227460400; 35227429400; 57202638465; 23034837300; 57216594895; 57208691543; 13405022500; 36604596000; 35227558900; 57251793200; 57204052333; 57205462419; 6701392158; 56047689500; 58375580000; 56273696800; 9278396500; 7006040977; 7004889588; 22135531000; 35227669300; 57224626542; 26023453000; 35227656900; 7004546205; 12244632700; 6603294089; 57214093211; 57212715831; 35227746500; 6701825145; 57250707600; 57226647977; 7004207376; 36085149700; 35227791700; 57208699533; 56362788600; 57385323900; 57814422500; 57200602864; 35227871000; 7004527121; 57219768156; 57733236300; 7003515879; 6701495633; 58092074700; 35228024200; 57208791396; 57198983235; 7201653195; 35227996900; 15030349100; 57213706614; 6507906118; 57221112096; 7004321986; 57733253800; 57222078258; 35228099400; 57223798916; 22136651400; 6504161736; 6603350317; 7201539565; 13204321200; 58422408300; 57222271505; 57201559118; 16029849600; 36836386600; 57216598335; 59819934500 | PHYSICAL REVIEW C | PHYS REV C | 2469-9985 | 2469-9993 | 109 | 6 | SCIE | PHYSICS, NUCLEAR | 2024 | 3.4 | 29.5 | 0 | 2025-05-07 | 0 | 0 | PHOTOPRODUCTION; CLAS; RESONANCES; NUCLEI; GAMMA | English | 2024 | 2024-06-17 | 10.1103/physrevc.109.065205 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||||
| ○ | ○ | Article | Dynamical model of J/ψ photoproduction on the nucleon | A dynamical model based on a phenomenological charm quark -nucleon ( c - N ) potential v cN and the Pomeronexchange mechanism is constructed to investigate the J /1' photoproduction on the nucleon from threshold to invariant mass W = 300 GeV. The J /1' - N potential, V J /1' N ( r ), is constructed by folding v cN into the wave function 0 J /1' ( cc ) of J /1' within a constituent quark model (CQM) of Segovia et al. [Int. J. Mod. Phys. E 22 , 1330026 (2013)]. A photoproduction amplitude is also generated by v cN by a cc -loop integration over the gamma -> cc vertex function and 0 J /1' ( cc ). No commonly used vector meson dominance assumption is used to define this photoproduction amplitude which is needed to describe the data near the threshold. The c - N potential v c N ( r ) is parameterized in a form such that the predicted V J /1' N ( r ) at large distances has the same Yukawa potential form extracted from a lattice QCD (LQCD) calculation of Kawanai and Sasaki, [Phys. Rev. D 82 , 091501(R) (2010)]. The parameters of v cN are determined by fitting the total cross-section data of Jefferson Laboratory (JLab) by performing calculations that include J /1' - N final -state interactions (FSI). The resulting differential cross sections d cr / dt are found in good agreements with the data. It is shown that the FSI effects dominate the cross section in the very near -threshold region, allowing for sensitive testing of the predicted J /1' - N scattering amplitudes. By imposing the constraints of J /1' - N potential extracted from the LQCD calculation of Kawanai and Sasaki, [Phys. Rev. D 82 , 091501(R) (2010)], we have obtained three J /1' - N potentials which fit the JLab data equally well. The resulting J /1' - N scattering lengths are in the range of a = [ - 0 . 05 , - 0 . 25] fm. With the determined v c N ( r ) and the wave functions generated from the same CQM, the constructed model is used to predict the cross sections of photoproduction of q c (1 S ) and 1' (2 S ) mesons for future experimental tests. | Sakinah, S.; Lee, T. -S. H.; Choi, H. M. | Kyungpook Natl Univ, Dept Phys, Daegu 41566, South Korea; Argonne Natl Lab, Phys Div, Argonne, IL 60439 USA | ; Ahmad, Sharifah Sakinah/AAV-9230-2021 | 57220754597; 8745480200; 7404339783 | ssakinahf@knu.ac.kr;tshlee@anl.gov;homyoung@knu.ac.kr; | PHYSICAL REVIEW C | PHYS REV C | 2469-9985 | 2469-9993 | 109 | 6 | SCIE | PHYSICS, NUCLEAR | 2024 | 3.4 | 29.5 | 0 | 2025-05-07 | 2 | 1 | SHORT-DISTANCE ANALYSIS; HEAVY-QUARK SYSTEMS; MESON PRODUCTION; QCD; SCATTERING; EXCHANGE; GAMMA; PI | English | 2024 | 2024-06-13 | 10.1103/physrevc.109.065204 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Measurements of low-energy nuclear recoil quenching factors for Na and I recoils in the NaI(Tl) scintillator | Elastic scattering off nuclei in target detectors, involving interactions with dark matter and coherent elastic neutrino nuclear recoil (CEvNS), results in the deposition of low energy within the nuclei, dissipating rapidly through a combination of heat and ionization. The primary energy loss mechanism for nuclear recoil is heat, leading to consistently smaller measurable scintillation signals compared to electron recoils of the same energy. The nuclear recoil quenching factor (QF), representing the ratio of scintillation light yield produced by nuclear recoil to that of electron recoil at the same energy, is a critical parameter for understanding dark matter and neutrino interactions with nuclei. The low energy QF of NaI(Tl) crystals, commonly employed in dark matter searches and CEvNS measurements, is of substantial importance. Previous low energy QF measurements were constrained by contamination from photomultiplier tube (PMT)-induced noise, resulting in an observed light yield of approximately 15 photoelectrons per keVee (kilo-electron-volt electron-equivalent energy) and nuclear recoil energy above 5 keVnr (kilo-electron-volt nuclear recoil energy). Through enhanced crystal encapsulation, an increased light yield of around 26 photoelectrons per keVee is achieved. This improvement enables the measurement of the nuclear recoil QF for sodium nuclei at an energy of 3.8 +/- 0.6 keVnr with a QF of 11.2 +/- 1.7%. Furthermore, a re-evaluation of previously reported QF results is conducted, incorporating enhancements in low energy events based on waveform simulation. The outcomes are generally consistent with various recent QF measurements for sodium and iodine. | Lee, S. H.; Joo, H. W.; Kim, H. J.; Kim, K. W.; Kim, S. K.; Kim, Y. D.; Ko, Y. J.; Lee, H. S.; Lee, J. Y.; Park, H. S.; Yoon, Y. S. | Korea Univ Sci & Technol UST, Daejeon 34113, South Korea; Inst Basic Sci IBS, Ctr Underground Phys, Daejeon 34126, South Korea; Seoul Natl Univ, Dept Phys & Astron, Seoul 08826, South Korea; Kyungpook Natl Univ, Dept Phys Educ, Daegu 41566, South Korea; Korea Res Inst Stand & Sci, Daejeon 34113, South Korea | Lee, Sang-Jun/A-3892-2015; Lee, Seunghyun/AAS-8066-2021; Lee, Hyun Woo/AAH-8473-2020; Lee, Jooyoung/HTN-0335-2023; Kim, Dong/C-1533-2011; Kim, Hong Joo/AAE-1178-2022; Ko, Young/AEI-0838-2022; Lee, Hyun Su/G-3392-2014 | 57257129200; 56375205700; 59051568100; 57209988432; 57200876753; 7410207253; 56030036300; 56113238600; 57204797944; 57216599536; 35243798200 | kwkim@ibs.re.kr;hyunsulee@ibs.re.kr; | PHYSICAL REVIEW C | PHYS REV C | 2469-9985 | 2469-9993 | 110 | 1 | SCIE | PHYSICS, NUCLEAR | 2024 | 3.4 | 29.5 | 1.62 | 2025-05-07 | 3 | 5 | English | 2024 | 2024-07-10 | 10.1103/physrevc.110.014614 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||||
| ○ | Article | Molecular detection and phylogenetic analysis of six bee viruses from Varroa destructor in Korea | In the beekeeping industry, the control of Varroa destructor and viruses is a crucial factor in maintaining the health of the western honey bee Apis mellifera L. Recently, in Korea, beekeepers suffered for high colony losses during the overwintering, and the presence of V. destructor and viruses has been considered an important factor for honey bee health. In this study, we investigated the presence of six honey bee viruses [deformed wing virus (DWV), sacbrood virus (SBV), Kashmir bee virus (KBV), Israeli acute paralysis virus (IAPV), chronic bee paralysis virus (CBPV), and black queen cell virus (BQCV)] in V. destructor in Korea. V. destructor was collected from 46 apiaries in nine provinces in Korea, and viruses were detected using reverse transcription–polymerase chain reaction. DWV was most predominantly detected at 87% of apiaries, followed by IAPV, SBV, KBV, BQCV, and CBPV that were detected in 65.2%, 17.4%, 13%, 8.7%, and 6.5% of apiaries in Korea. Phylogenetic analysis revealed that five viruses (IAPV, SBV, BQCV, and CBPV) were grouped into clades of viruses originating from China, Russia, and Australia, but KBV showed no distinct clades of countries. This study confirmed the presence of various types of bee viruses in V. destructor in Korea, indicating that domestic honey bees are exposed to multiple viruses via V. destructor. © 2024 International Bee Research Association. | Moon, KyungHwan; Cho, Susie; Lee, Joonhee; Lee, Si Hyeock; Seong, Keon Mook; Kim, Young Ho | Department of Vector Entomology, Kyungpook National University, Sangju, South Korea; Department of Agricultural Biotechnology, Seoul National University, Seoul, South Korea; Department of Agricultural Biotechnology, Seoul National University, Seoul, South Korea; Department of Agricultural Biotechnology, Seoul National University, Seoul, South Korea, Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul, South Korea; Department of Applied Biology, Chungnam National University, Daejeon, South Korea; Department of Vector Entomology, Kyungpook National University, Sangju, South Korea, Research Institute of Invertebrate Vector, Kyungpook National University, Sangju, South Korea | 57202874378; 57215506355; 57562565200; 34872664900; 59672065600; 58516491300 | yhkim05@knu.ac.kr; | Journal of Apicultural Research | J APICULT RES | 0021-8839 | 2078-6913 | SCIE | ENTOMOLOGY | 2024 | 1.8 | 29.5 | 0 | 2025-05-07 | 0 | honey bee; phylogenetic analysis; RNA viruses; Varroa destructor; virus distribution | English | Article in press | 2024 | 10.1080/00218839.2024.2411769 | 바로가기 | 바로가기 | 바로가기 | ||||||||||
| ○ | ○ | Article | Nocturnal behavior and dietary specialization of Vespa binghami (Hymenoptera: Vespidae) in South Korea | This study comprehensively explored the ecological roles, behaviors, and adaptive strategies of the enigmatic nocturnal hornet species Vespa binghami du Buysson, 1905 (Hymenoptera: Vespidae), in South Korea. Using time-series analysis, we identified the hornet's peak activity to be between 23:00 and 00:00, consistent with its dietary preference for species of the order Lepidoptera as identified through cytochrome c oxidase I metabarcoding. Metabarcoding revealed a specialized diet that predominantly consists of moths belonging to the family Noctuidae, suggesting a co-evolutionary predator-prey relationship. However, our sample size was limited; therefore, this observation should be considered preliminary. Our findings also provide evidence of opportunistic predation on bees, indicating adaptive flexibility in foraging behavior. Spatiotemporal analysis showed that the hornets exhibited peak activity during late summer and that they are mainly found at elevations between 100 m and 400 m. Despite their adaptability, sightings are regionally limited within South Korea. Observations indicated that the hornets prefer nesting in tree cavities, which have architectural features uniquely adapted to their nocturnal lifestyle. Taken together, these findings offer a multidimensional understanding of the nocturnal behaviors, specialized adaptations, and ecological significance of V. binghami. Moreover, they highlight the need for further multidisciplinary research to fully elucidate the role of this hornet in its ecosystem and its potential as a bioindicator of environmental stability and habitat quality. | Do, Yuno; Choi, Moon Bo | Kongju Natl Univ, Dept Biol Sci, Gongju, South Korea; Kyungpook Natl Univ, Inst Agr Sci & Technol, Daegu, South Korea | 52163435800; 51863232400 | kosinchoi@hanmail.net; | ANNALS OF THE ENTOMOLOGICAL SOCIETY OF AMERICA | ANN ENTOMOL SOC AM | 0013-8746 | 1938-2901 | 117 | 6 | SCIE | ENTOMOLOGY | 2024 | 1.8 | 29.5 | 0 | 2025-05-07 | 0 | 0 | nocturnal hornet; time-series analysis; cytochrome c oxidase I metabarcoding; ecological adaptation; nesting behavior | ADAPTATIONS; VISION; HORNET | cytochrome c oxidase I metabarcoding; ecological adaptation; nesting behavior; nocturnal hornet; time-series analysis | South Korea; adaptation; cytochrome; dietary intake; habitat quality; nesting behavior; nocturnal activity; predation; specialization; time series analysis; wasp | English | 2024 | 2024-09-11 | 10.1093/aesa/saae024 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Two-particle Bose-Einstein correlations and their Lévy parameters in PbPb collisions at √sNN=5.02 TeV | Two -particle Bose-Einstein momentum correlation functions are studied for charged-hadron pairs in lead -lead collisions at a center -of -mass energy per nucleon pair of .'/sNN = 5.02 TeV. The data sample, containing 4.27 x 109 minimum bias events corresponding to an integrated luminosity of 0.607 nb-1, was collected by the CMS experiment in 2018. The experimental results are discussed in terms of a Levy-type source distribution. The parameters of this distribution are extracted as functions of particle pair average transverse mass and collision centrality. These parameters include the Levy index or shape parameter alpha, the Levy scale parameter R, and the correlation strength parameter lambda. The source shape, characterized by alpha, is found to be neither Cauchy nor Gaussian, implying the need for a full Levy analysis. Similarly to what was previously found for systems characterized by Gaussian source radii, a hydrodynamical scaling is observed for the Levy R parameter. The lambda parameter is studied in terms of the core -halo model. | Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Del Valle, A. Escalante; Hussain, P. S.; Jeitler, M.; Krammer, N.; Lechner, L.; Liko, D.; Mikulec, I.; Paulitsch, P.; Schieck, J.; Schofbeck, R.; Schwarz, D.; Sonawane, M.; Templ, S.; Waltenberger, W.; Wulz, C. -E.; Darwish, M. R.; Janssen, T.; Kello, T.; Sfar, H. Rejeb; Van Mechelen, P.; Bols, E. S.; D'Hondt, J.; De Moor, A.; Delcourt, M.; El Faham, H.; Lowette, S.; Morton, A.; Mueller, D.; Sahasransu, A. R.; Tavernier, S.; Van Doninck, W.; Van Putte, S.; Vannerom, D.; Clerbaux, B.; Dansana, S.; De Lentdecker, G.; Favart, L.; Hohov, D.; Jaramillo, J.; Lee, K.; Mahdavikhorrami, M.; Makarenko, I.; Malara, A.; Paredes, S.; Petre, L.; Postiau, N.; Thomas, L.; Vanden Bemden, M.; Vander Velde, C.; Vanlaer, P.; Dobur, D.; Knolle, J.; Lambrecht, L.; Mestdach, G.; Rendon, C.; Samalan, A.; Skovpen, K.; Tytgat, M.; Van den Bossche, N.; Vermassen, B.; Wezenbeek, L.; Benecke, A.; Bruno, G.; Bury, F.; Caputo, C.; David, P.; Delaere, C.; Donertas, I. S.; Giammanco, A.; Jaffel, K.; Jain, Sa; Lemaitre, V.; Mondal, K.; Taliercio, A.; Tran, T. T.; Vischia, P.; Wertz, S.; Alves, G. A.; Coelho, E.; Hensel, C.; Moraes, A.; Teles, P. Rebello; Alda Junior, W. L.; Alves Gallo Pereira, M.; Barroso Ferreira Filho, M.; Brandao Malbouisson, H.; Carvalho, W.; Chinellato, J.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Dos Santos Sousa, V.; Fonseca De Souza, S.; Martins, J.; Mora Herrera, C.; Mota Amarilo, K.; Mundim, L.; Nogima, H.; Santoro, A.; Silva Do Amaral, S. M.; Sznajder, A.; Thiel, M.; Vilela Pereira, A.; Bernardes, C. A.; Calligaris, L.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Antchev, G.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Ivanov, T.; Litov, L.; Pavlov, B.; Petkov, P.; Petrov, A.; Shumka, E.; Thakur, S.; Cheng, T.; Javaid, T.; Mittal, M.; Yuan, L.; Ahmad, M.; Bauer, G.; Hu, Z.; Lezki, S.; Yi, K.; Chen, G. M.; Chen, H. S.; Chen, M.; Iemmi, F.; Jiang, C. H.; Kapoor, A.; Liao, H.; Liu, Z. -A.; Milosevic, V.; Monti, F.; Sharma, R.; Tao, J.; Thomas-Wilsker, J.; Wang, J.; Zhang, H.; Zhao, J.; Agapitos, A.; An, Y.; Ban, Y.; Levin, A.; Li, C.; Li, Q.; Lyu, X.; Mao, Y.; Qian, S. J.; Sun, X.; Wang, D.; Xiao, J.; Yang, H.; Lu, M.; You, Z.; Lu, N.; Gao, X.; Leggat, D.; Okawa, H.; Zhang, Y.; Lin, Z.; Lu, C.; Xiao, M.; Avila, C.; Trujillo, D. A. Barbosa; Cabrera, A.; Florez, C.; Fraga, J.; Mejia Guisao, J.; Ramirez, F.; Rodriguez, M.; Ruiz Alvarez, J. D.; Giljanovic, D.; Godinovic, N.; Lelas, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Sculac, T.; Brigljevic, V.; Chitroda, B. K.; Ferencek, D.; Mishra, S.; Roguljic, M.; Starodumov, A.; Susa, T.; Attikis, A.; Christoforou, K.; Konstantinou, S.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Saka, H.; Stepennov, A.; Finger, M.; Finger, M., Jr.; Kveton, A.; Ayala, E.; Carrera Jarrin, E.; Abdalla, H.; Assran, Y.; Abdullah Al-Mashad, M.; Mahmoud, M. A.; Bhowmik, S.; Dewanjee, R. 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Fontana; Ghosh, S.; Granier de Cassagnac, R.; Hakimi, A.; Harikrishnan, B.; Liu, G.; Motta, J.; Nguyen, M.; Ochando, C.; Portales, L.; Salerno, R.; Sarkar, U.; Sauvan, J. B.; Sirois, Y.; Tarabini, A.; Vernazza, E.; Zabi, A.; Zghiche, A.; Agram, J. -L.; Andrea, J.; Apparu, D.; Bloch, D.; Bourgatte, G.; Brom, J. -M.; Chabert, E. C.; Collard, C.; Darej, D.; Goerlach, U.; Grimault, C.; Le Bihan, A. -C.; Van Hove, P.; Beauceron, S.; Blancon, B.; Boudoul, G.; Carle, A.; Chanon, N.; Choi, J.; Contardo, D.; Depasse, P.; Dozen, C.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Perries, S.; Torterotot, L.; Vander Donckt, M.; Verdier, P.; Viret, S.; Chokheli, D.; Lomidze, I.; Tsamalaidze, Z.; Botta, V.; Feld, L.; Klein, K.; Lipinski, M.; Meuser, D.; Pauls, A.; Rowert, N.; Teroerde, M.; Diekmann, S.; Dodonova, A.; Eich, N.; Eliseev, D.; Erdmann, M.; Fackeldey, P.; Fasanella, D.; Fischer, B.; Hebbeker, T.; Hoepfner, K.; Ivone, F.; Lee, M. Y.; Mastrolorenzo, L.; Merschmeyer, M.; Meyer, A.; Mondal, S.; Mukherjee, S.; Noll, D.; Novak, A.; Nowotny, F.; Pozdnyakov, A.; Rath, Y.; Redjeb, W.; Rehm, F.; Reithler, H.; Schmidt, A.; Schuler, S. C.; Sharma, A.; Stein, A.; De Araujo, F. Torres Da Silva; Vigilante, L.; Wiedenbeck, S.; Zaleski, S.; Dziwok, C.; Flugge, G.; Ahmad, W. Haj; Hlushchenko, O.; Kress, T.; Nowack, A.; Pooth, O.; Stahl, A.; Ziemons, T.; Zotz, A.; Petersen, H. Aarup; Martin, M. Aldaya; Alimena, J.; Asmuss, P.; Baxter, S.; Bayatmakou, M.; Gonzalez, H. 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Ventura; Walsh, R.; Walter, D.; Wang, Q.; Wen, Y.; Wichmann, K.; Wiens, L.; Wissing, C.; Wuchterl, S.; Yang, Y.; Santos, A. Zimermmane Castro; Albrecht, A.; Albrecht, S.; Antonello, M.; Bein, S.; Benato, L.; Bonanomi, M.; Connor, P.; De Leo, K.; Eich, M.; El Morabit, K.; Feindt, F.; Frohlich, A.; Garbers, C.; Garutti, E.; Hajheidari, M.; Haller, J.; Hinzmann, A.; Jabusch, H. R.; Kasieczka, G.; Keicher, P.; Klanner, R.; Korcari, W.; Kramer, T.; Kutzner, V.; Labe, F.; Lange, J.; Lobanov, A.; Matthies, C.; Mehta, A.; Moureaux, L.; Mrowietz, M.; Nigamova, A.; Nissan, Y.; Paasch, A.; Rodriguez, K. J. Pena; Quadfasel, T.; Rieger, M.; Savoiu, D.; Schindler, J.; Schleper, P.; Schroder, M.; Schwandt, J.; Sommerhalder, M.; Stadie, H.; Steinbruck, G.; Tews, A.; Wolf, M.; Brommer, S.; Burkart, M.; Butz, E.; Chwalek, T.; Dierlamm, A.; Droll, A.; Faltermann, N.; Giffels, M.; Gosewisch, J. 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S.; Sekmen, S.; Yang, Y. C.; Kim, H.; Moon, D. H.; Asilar, E.; Kim, T. J.; Park, J.; Choi, S.; Han, S.; Hong, B.; Lee, K.; Lee, K. S.; Lim, J.; Park, J.; Park, S. K.; Yoo, J.; Goh, J.; Kim, H. S.; Kim, Y.; Lee, S.; Almond, J.; Bhyun, J. H.; Choi, J.; Jeon, S.; Kim, J.; Kim, J. S.; Ko, S.; Kwon, H.; Lee, H.; Lee, S.; Oh, B. H.; Oh, S. B.; Seo, H.; Yang, U. K.; Yoon, I.; Jang, W.; Kang, D. Y.; Kang, Y.; Kim, D.; Kim, S.; Ko, B.; Lee, J. S. H.; Lee, Y.; Merlin, J. A.; Park, I. C.; Roh, Y.; Song, D.; Watson, I. J.; Yang, S.; Ha, S.; Yoo, H. D.; Choi, M.; Kim, M. R.; Lee, H.; Lee, Y.; Yu, I.; Beyrouthy, T.; Maghrbi, Y.; Dreimanis, K.; Pikurs, G.; Potrebko, A.; Seidel, M.; Veckalns, V.; Ambrozas, M.; Antunes De Oliveira, A. Carvalho; Juodagalvis, A.; Rinkevicius, A.; Tamulaitis, G.; Bin Norjoharuddeen, N.; Hoh, S. Y.; Yusuff, I.; Zolkapli, Z.; Benitez, J. F.; Castaneda Hernandez, A.; Encinas Acosta, H. A.; Gallegos Marinez, L. G.; Leon Coello, M.; Murillo Quijada, J. A.; Sehrawat, A.; Valencia Palomo, L.; Ayala, G.; Castilla-Valdez, H.; Heredia-De La Cruz, I.; Lopez-Fernandez, R.; Mondragon Herrera, C. A.; Perez Navarro, D. A.; Sanchez Hernandez, A.; Oropeza Barrera, C.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Bubanja, I.; Mijuskovic, J.; Raicevic, N.; Ahmad, A.; Asghar, M. I.; Awais, A.; Awan, M. I. M.; Gul, M.; Hoorani, H. R.; Khan, W. A.; Avati, V.; Grzanka, L.; Malawski, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Gorski, M.; Kazana, M.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Araujo, M.; Bargassa, P.; Bastos, D.; Boletti, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Niknejad, T.; Pisano, M.; Seixas, J.; Varela, J.; Adzic, P.; Dordevic, M.; Milenovic, P.; Milosevic, J.; Aguilar-Benitez, M.; Alcaraz Maestre, J.; Barrio Luna, M.; Bedoya, Cristina F.; Cepeda, M.; Cerrada, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Fernandez Del Val, D.; Fernandez Ramos, J. P.; Flix, J.; Fouz, M. C.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Leon Holgado, J.; Moran, D.; Perez Dengra, C.; Perez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Redondo, I.; Redondo Ferrero, D. D.; Romero, L.; Sanchez Navas, S.; Sastre, J.; Urda Gomez, L.; Vazquez Escobar, J.; Willmott, C.; de Troconiz, J. 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Univ Visva Bharati, Santini Ketan, W Bengal, India; Univ Hyderabad, Hyderabad, India; Indian Inst Sci IISc, Bangalore, Karnataka, India; Indian Inst Technol IIT, Mumbai, Maharashtra, India; IIT Bhubaneswar, Bhubaneswar, Odisha, India; Inst Phys, Bhubaneswar, India; DESY, Hamburg, Germany; Isfahan Univ Technol, Dept Phys, Esfahan, Iran; Sharif Univ Technol, Tehran, Iran; Univ Sci & Technol Mazandaran, Dept Phys, Behshahr, Iran; Helwan Univ, Cairo, Egypt; Italian Natl Agcy New Technol, Energy & Sustainable Econ Dev, Bologna, Italy; Ctr Siciliano Fis Nucl & Struttura Mat, Catania, Italy; Univ Guglielmo Marconi, Rome, Italy; Univ Napoli Federico II, Scuola Super Merid, Naples, Italy; Fermilab Natl Accelerator Lab, POB 500, Batavia, IL 60510 USA; Univ Napoli Federico II, Naples, Italy; Ain Shams Univ, Cairo, Egypt; CNR, Ist Officina Mat, Perugia, Italy; Riga Tech Univ, Riga, Latvia; Univ Kebangsaan Malaysia, Fac Sci & Technol, Dept Appl Phys, Bangi, Malaysia; Consejo Nacl Ciencia & Technol, Mexico City, DF, Mexico; Univ Paris Saclay, IRFU, CEA, Gif Sur Yvette, France; Univ Belgrade, Fac Phys, Belgrade, Serbia; Eastern Univ, Trincomalee Campus, Nilaveli, Sri Lanka; Univ Pavia, INFN, Sez Pavia, Pavia, Italy; Natl & Kapodistrian Univ Athens, Athens, Greece; Ecole Polytech Fed Lausanne, Lausanne, Switzerland; Univ Zurich, Zurich, Switzerland; Stefan Meyer Inst Subat Phys, Vienna, Austria; CNRS, IN2P3, Lab Annecy le Vieux Phys Particules, Annecy Le Vieux, France; Near East Univ, Res Ctr Expt Hlth Sci, Mersin, Turkiye; Konya Tech Univ, Konya, Turkiye; Izmir Bakircay Univ, Izmir, Turkiye; Adiyaman Univ, Adiyaman, Turkiye; Istanbul Gedik Univ, Istanbul, Turkiye; Necmettin Erbakan Univ, Konya, Turkiye; Bozok Univ Rektorlugu, Yozgat, Turkiye; Marmara Univ, Istanbul, Turkiye; Milli Savunma Univ, Istanbul, Turkiye; Kafkas Univ, Kars, Turkiye; Hacettepe Univ, Ankara, Turkiye; Istanbul Univ Cerrahpasa, Fac Engn, Istanbul, Turkiye; Ozyegin Univ, Istanbul, Turkiye; Vrije Univ Brussel, Brussels, Belgium; Univ Southampton, Sch Phys & Astron, Southampton, Hants, England; Univ Bristol, Bristol, Avon, England; Univ Durham, IPPP, Durham, England; Monash Univ, Fac Sci, Clayton, Vic, Australia; Univ Torino, Turin, Italy; Bethel Univ, St Paul, MN USA; Karamanoglu Mehmetbey Univ, Karaman, Turkiye; CALTECH, Pasadena, CA 91125 USA; US Naval Acad, Annapolis, MD 21402 USA; Univ Florida, Gainesville, FL USA; Bingol Univ, Bingol, Turkiye; Georgian Tech Univ, Tbilisi, Georgia; Sinop Univ, Sinop, Turkiye; Erciyes Univ, Kayseri, Turkiye; Texas A&M Univ Qatar, Doha, Qatar; Kyungpook Natl Univ, Daegu, South Korea; Yerevan Phys Inst, Yerevan, Armenia; Imperial Coll, London, England; Uzbek Acad Sci, Inst Nucl Phys, Tashkent, Uzbekistan | Liu, Zhiquan/P-7976-2017; Di Nardo, Roberto/J-4993-2012; Bouhali, Othmane/JXM-3572-2024; Spagnolo, Paolo/G-3401-2017; Tytgat, Michael/F-3732-2018; Joo, Changwoo/ABI-4034-2020; Benaglia, Andrea/AGF-5495-2022; Aydilek, Orhan/GLV-0592-2022; Cheng, Hok-Chuen/GNP-8341-2022; Kim, Victor/L-1648-2013; Misheva, Mihaela/AEK-6084-2022; Bornheim, Adi/L-2750-2019; 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Roguljic, Matej/NMJ-5801-2025; Marlow, Daniel/C-9132-2014; Mahmoud, Mohammed/AAD-1249-2019; Pásztor, Gabriella/D-9716-2016; Cerri, Olmo/Z-3579-2019; Rossi, Barbara/AAA-3514-2022; Kang, Hyun-Jae/D-6121-2012; Biino, Cristina/AAF-1585-2020; Boimska, Bożena/Z-6088-2019; Escobar, Juan/JLM-3900-2023; QIAN, LIU/S-1353-2019; Calvo Alamillo, Enrique/L-1203-2014; Pedraza Morales, Maria Isabel/ABC-7289-2021; Piperov, Stefan/Q-1980-2017; D'Alessandro, Raffaello/P-4138-2019; Najafabadi, Mojtaba/AAF-7564-2019; Clements, Emma/HSG-3424-2023; Lokos, Sandor/A-4798-2019; Moraes, Arthur/F-6478-2010; Battilana, Carlo/AAA-7345-2020; Dutta, Ipsita/JDW-8207-2023; candelise, vieri/H-2195-2015; Simone, Federica/HDM-3686-2022; Đorđević, Marija/JQV-6386-2023; Teles, Patricia/ABF-9723-2021; Salvatico, Riccardo/JAO-1069-2023; Seidel, Marcus/AAA-4799-2022; Tornago, Marta/NGS-5785-2025; SEVINC KAYA, OZLEM/AAE-8069-2020; Tumasyan, Armen/P-3390-2015; Flore, Carlo/HZJ-6377-2023; Aruta, Caterina/NRX-9970-2025; Giammanco, Andrea/O-5017-2019; 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Ozkorucuklu, Suat/AAE-7535-2020; Rout, Prasanna/N-8012-2019; Orlando, Nicola/AAL-1723-2021; Habibullah, Redwan/AAK-9617-2020; Colaleo, Anna/JTS-3830-2023; Bossini, Edoardo/AAA-4972-2020; Doğangün, Oktay/AAC-1579-2022; Sen, S./C-6473-2014; Mignerey, Alice/D-6623-2011; Zhou, Shiyuan/IYJ-7387-2023; Veckalns, Viesturs/AAZ-3105-2020; SIMSEK, Ali Eren/AFO-3050-2022; Bainbridge, Robert/JRW-6150-2023; Aimè, Chiara/GXG-4131-2022; Sarica, Ulascan/JXY-2829-2024; Arcidiacono, Roberta/ABF-3918-2020; Garutti, Erika/NRY-4813-2025; Sznajder, Andre/L-1621-2016; Mishra, Trilochan/A-7947-2010; Ye, Sheng/HGA-5474-2022; Atef, Ashraf/AAC-9697-2021; Organtini, Giovanni/D-3990-2009; Colaleo, Anna/HSG-1637-2023; Dremin, Igor/K-8053-2015; Missiroli, Marino/AAA-9072-2021; Ramos, Juan/AAF-3114-2019; SÖZBİLİR, ÜMİT/AAV-8199-2020; Boos, Eduard/D-9748-2012; Salvini, Pericle/ISU-2651-2023; Ulrich, Ralf/Q-3882-2019; Cadamuro, Luca/AAO-8637-2020; Ford, Taani/IAM-2715-2023; MAESTRE, JUAN/I-5763-2015; Osherson, Marc/LWZ-8687-2024; Bunkowski, Karol/KOD-1567-2024; Puljak, Ivica/D-8917-2017; Barria, Patrizia/AAT-3894-2020; Routray, Hardik/NBX-8249-2025; yagil, avi/I-3278-2018; DAS, ANIL KUMAR/JCF-2235-2023; Lannon, Kevin/HGU-5755-2022; Wittich, Peter/HOH-5761-2023; Ogul, Hasan/S-7951-2016; Ozdemir, Kadri/P-8058-2014; LECOQ, Paul/S-7246-2019; D'Hondt, Jorgen/ABD-7930-2020; Azarkin, Maxim/N-2578-2015; Malakhov, Alexander/D-5702-2016; Bortignon, Pierluigi/AAF-6561-2020; dumanoglu, isa/C-3627-2018; Mussgiller, Andreas/AAF-6933-2019; Dogra, Sunil/B-5330-2013; Quijada, Javier/AAS-4234-2021; Cardini, Andrea/KUF-0984-2024; Liu, Zhibo/A-4568-2018; Zolkapli, Zukhaimira/AAA-4039-2019; SASTRE, JUAN/AAB-2344-2019; Martinez Rivero, Celso/V-6916-2017; Watson, Ian/IAM-9344-2023; Cassese, Antonio/R-1713-2016; Hegeman, Jeroen/HJA-1005-2022; Alves, Gilvan/C-4007-2013; Mrenna, Stephen/KIL-6081-2024; Pieri, Matthew/AGD-4546-2022; Fiorendi, Sara/ABA-3311-2021; Elkafrawy, Tamer/HPF-5873-2023; Kratochwil, Nicolaus/ACR-4384-2022; Focardi, Ettore/E-7376-2012; Bruschini, Davide/MCK-5220-2025; Vala, Martin/HZL-1003-2023; Ivanov, Andrew/A-7982-2013; Sánchez-Rodríguez, Alexander/JLK-9336-2023; Petrucciani, Giovanni/AAM-8482-2020; Bermudez Martinez, Armando/HHN-4625-2022; Pellecchia, Antonello/KZV-0289-2024; KARA, Ozgun/MCY-5689-2025; Amoroso, Simone/AAW-4334-2021; Norjoharuddeen, Nurfikri/S-3109-2018; KAYİS TOPAKSU, Aysel/B-8910-2018; Xie, Si/O-6830-2016; Tsirou, Andromachi/HHC-6869-2022; Chang, Hui/AGD-4270-2022; Shopova, Mariana/HKW-0149-2023; Wang, Yifan/KDO-8319-2024; Kirakosyan, Martin/N-2701-2015; Pompili, Alexis/ISU-8813-2023; Pastrone, Nadia/JRZ-0528-2023; Mondal, Santu/GSE-1742-2022; de Souza Sandro, Fonseca/ABB-8505-2020; Fasanella, Daniele/ABD-9759-2020; Arneodo, Michele/ABF-7197-2020; Gennai, Simone/P-2880-2015; ASILAR, Ece/ABC-4577-2020; Lau, Kok-Tee/AAX-5361-2020; Cavallari, Francesca/AAE-8571-2019; Wimpenny, Stephen/K-8848-2013; Paganoni, Marco/A-4235-2016; Casarsa, Massimo/L-3623-2018; Padula, Sandra/AAE-4304-2020; Marinho, Franciole/N-8101-2014; ciocci, maria/I-2153-2015; Verdini, Piero/J-2839-2012; Hobson, Peter/C-8919-2016; Haddad, Yacine/GRX-5022-2022; Venditti, Rosamaria/I-1030-2014; Kapoor, Aakanksha Rajiv/KAM-5986-2024; Maravin, Yurii/N-9259-2018; Kaveh, Hessamoddin/AAI-7230-2021; Choudhury, Seema/LEM-7962-2024; Fernandez Menendez, Javier/B-6550-2014; Kumar, Saroj/AAU-5615-2021; Cankocak, Kerem/A-1507-2018; Baskakov, Alexey/O-4521-2017; Paramatti, Riccardo/IXW-6363-2023; Ceccarelli, Rudy/JTU-5218-2023; Chen, Shiping/B-7492-2011; Nandan, Saswati/JVY-9235-2024; Moscatelli, Francesco/N-6333-2014; BARRILLON, Stephanie/ABA-6873-2021; Raidal, Martti/F-4436-2012; staiano, amedeo/KVB-8364-2024; Hebbeker, Thomas/L-4073-2013; Li, Chun/KBC-9591-2024; Forthomme, Laurent/AFS-8908-2022; Sculac, Toni/AAE-4141-2019; Khakzad, Mohsen/ABB-1945-2021; Abdallah, Hassan/AEE-4715-2022; Saygin, Kadir/AAX-5235-2021; Radogna, Raffaella/I-1033-2014; Swain, Subrat/IXW-8971-2023; Dallavalle, Gaetano Marco/AFW-4654-2022; Sanchez, Federico/F-5809-2012; Juodagalvis, Andrius/F-6952-2018; wang, long/IZE-1764-2023; Sonnadara, Upul/E-6359-2010; Markina, Anastasia/E-3390-2012; siviero, federico/LXA-5818-2024; Ferreira, Maria/G-6561-2012; Finco, Linda/AAH-3618-2019; Zhou, Lihong/IAP-3933-2023; Nielsen, Christine/KJL-2209-2024; Ramos Lopez, Dayron/LPP-5481-2024; Vilela Pereira, Antonio/L-4142-2016; Camporesi, Tiziano/F-8307-2013; Hall-Wilton, Richard/U-6918-2019; KÖMÜRCÜ, YILDIRAY/AAC-6166-2020; Fouz, Maria Cruz/AAF-1105-2019 | 35222495600; 56217303000; 57222730792; 57204570563; 55470759900; 57350183900; 58189557300; 56272545200; 57219627829; 16019870600; 57194835548; 24767624300; 35227509400; 15825660400; 57209005037; 58771602500; 16246113200; 57217070627; 57223981892; 57217018402; 23010348400; 6601931097; 57208209720; 57226328248; 57215664799; 57210325112; 35228082900; 57204547895; 56251124200; 57386695300; 57189268167; 57226343153; 29767622300; 56496326300; 57219477443; 57202372215; 23072003200; 7007131716; 57210311992; 57193208271; 35227095300; 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58367102900; 55547103616; 55773572500; 37100798100; 57218261101; 58376139500; 58886865200; 56950774000; 57226009167 | PHYSICAL REVIEW C | PHYS REV C | 2469-9985 | 2469-9993 | 109 | 2 | SCIE | PHYSICS, NUCLEAR | 2024 | 3.4 | 29.5 | 3.24 | 2025-05-07 | 7 | 8 | PARTICLE INTERFEROMETRY; ANOMALOUS DIFFUSION; COULOMB CORRECTIONS; MODEL; QCD | English | 2024 | 2024-02-23 | 10.1103/physrevc.109.024914 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||||
| ○ | ○ | Article | Long-term prognosis after decoronation of avulsed teeth with replacement resorption: a report of three cases | The complications of replacement resorption following tooth injury in growing children include infrapositioning of the tooth, tilting of the adjacent teeth, and alveolar ridge deformity. Decoronation is a conservative treatment method that facilitates bone preservation. The current case report focuses on the long-term preservation of alveolar ridge dimension following decoronation in three patients. Decoronation was performed prior to occurrence of the pubertal growth spurt, and the patients' ridge width and vertical apposition were monitored for at least 4 years. Timely intervention and regular monitoring are essential for maximization of the benefits of decoronation, a simple procedure that preserves esthetics and minimizes the need for further treatments. The importance of space management for prosthetic treatment has also been highlighted. The findings of this study show that infrapositioned teeth in growing children can be treated successfully using decoronation. | Han, Ji-Eun; Kim, Gi-Min; Kim, Hyun-Jung; Lee, Jae-Sik | Kyungpook Natl Univ, Sch Dent, Dept Pediat Dent, Daegu 41940, South Korea | 58814459000; 57210885969; 57196215346; 57193887436 | leejs@knu.ac.kr; | JOURNAL OF CLINICAL PEDIATRIC DENTISTRY | J CLIN PEDIATR DENT | 1053-4628 | 1557-5268 | 48 | 1 | SCIE | DENTISTRY, ORAL SURGERY & MEDICINE;PEDIATRICS | 2024 | 2.2 | 29.6 | 0.9 | 2025-05-07 | 1 | 1 | Replacement resorption; Ankylosis-related resorption; Decoronation; Bone maintenance | MAXILLARY CENTRAL INCISORS; TOOTH; REPLANTATION; ADOLESCENTS; MANAGEMENT; ANKYLOSIS; INJURIES; CHILDREN | Ankylosis-related resorption; Bone maintenance; Decoronation; Replacement resorption | Child; Humans; Incisor; Prognosis; Root Resorption; Tooth Ankylosis; Tooth Avulsion; Tooth Crown; case report; child; complication; human; incisor; prognosis; tooth avulsion; tooth disease | English | 2024 | 2024 | 10.22514/jocpd.2024.023 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Myomectomy with ArtiSential fully articulating laparoscopic instruments: A prospective multicenter study | Background ArtiSential, a class of innovative laparoscopic instrument, has been developed to overcome the limitations of conventional laparoscopic surgery by enabling free, 360(degrees)-unrestricted movement of the wrist joint, as in robotic surgery. ObjectiveThe aim of the present study was to describe the initial experiences with these devices in myomectomy and to report the surgical outcomes. Methods A total of 77 women undergoing laparoscopic or robotic myomectomy between January 2021 and June 2022 were included in this multicenter prospective study. The ArtiSential instruments used by the surgeons were those chosen according to their respective preferences. The baseline characteristics, surgical outcomes, trocar placement options, and operator survey results were scrutinized. Results The mean age of the patients was 39.9 +/- 6.3, and the mean body mass index (BMI, calculated as weight in kilograms divided by the square of height in meters) was 22.4 +/- 3.4 kg/m(2); 46.8% of the patients underwent robotic surgery, while 53.2% underwent laparoscopic surgery. The number of removed myomas was 3.3 +/- 3.0, the size of the largest myoma was 7.1 +/- 2.3 cm, and the operative time was 130.0 +/- 54.0 min. No transfusions or laparotomy conversions were required. Other than one case of ileus, there were no postoperative complications. In most cases, the instruments were inserted through the umbilicus trocar, and the fenestrated forceps, needle holder, and bipolar fenestrated forceps, in that order, were frequently employed. According to a surgeon survey, 29.9% moderately or strongly agreed that the ArtiSential devices utilized were more convenient than conventional laparoscopic instruments, while only 9.7% moderately or strongly agreed that they were more convenient than robotic instruments. Conclusions Myomectomy as performed with an ArtiSential instrument seems to be feasible and safe. Further studies are necessary in order to comparatively assess the outcomes and potential benefits of ArtiSential, robotic, and conventional laparoscopic myomectomy. | Won, Seyeon; Kim, Kidong; Lee, Keun Ho; Kim, Tae-Joong; Kim, Taehun; Hwang, Jong Ha; Park, Hyun; Kim, Min Kyu; Hong, Dae Gy; Song, Yong Jung; Seong, Seok Ju | CHA Univ, Sch Med, CHA Gangnam Med Ctr, Dept Obstet & Gynecol, Seoul, South Korea; Seoul Natl Univ, Bundang Hosp, Dept Obstet & Gynecol, Seongnam, South Korea; Catholic Univ Korea, Seoul St Marys Hosp, Dept Obstet & Gynecol, Seoul, South Korea; Sungkyunkwan Univ, Samsung Med Ctr, Sch Med, Dept Obstet & Gynecol, Seoul, South Korea; Seoul Natl Univ, Seoul Metropolitan Govt, Boramae Med Ctr, Dept Obstet & Gynecol, Seoul, South Korea; Catholic Kwandong Univ, Int St Marys Hosp, Coll Med, Dept Obstet & Gynecol, Incheon, South Korea; CHA Univ, CHA Bundang Med Ctr, Dept Obstet & Gynecol, Div Gynecol Oncol, Seoul, South Korea; Sungkyunkwan Univ Med, Samsung Changwon Hosp, Dept Obstet & Gynecol, Chang Won, South Korea; Kyungpook Natl Univ, Sch Med, Dept Obstet & Gynecol, Daegu, South Korea; Pusan Natl Univ, Sch Med, Dept Obstet & Gynecol, Yangsan, South Korea | Kim, Min/ACN-6827-2022; Kim, TaeHeon/KIC-2380-2024; kim, nayoung/IWV-4038-2023 | 57212464403; 35740868200; 58305200300; 29767612300; 56575227700; 7403895581; 57039319900; 56053945200; 26656670100; 26028684500; 7006701440 | sjseongcheil@naver.com; | INTERNATIONAL JOURNAL OF GYNECOLOGY & OBSTETRICS | INT J GYNECOL OBSTET | 0020-7292 | 1879-3479 | 166 | 2 | SCIE | OBSTETRICS & GYNECOLOGY | 2024 | 2.4 | 29.6 | 0.92 | 2025-05-07 | 1 | 1 | laparoscopy; robotic surgical procedures; uterine fibroids; uterine myomectomy | laparoscopy; robotic surgical procedures; uterine fibroids; uterine myomectomy | Adult; Equipment Design; Female; Humans; Laparoscopy; Leiomyoma; Middle Aged; Operative Time; Prospective Studies; Robotic Surgical Procedures; Treatment Outcome; Uterine Myomectomy; Uterine Neoplasms; adult; Article; clinical trial; device safety; feasibility study; female; hemostasis; human; laparoscopic myomectomy; major clinical study; multicenter study; operation duration; outcome assessment; postoperative complication; postoperative ileus; prospective study; robot myomectomy; suture technique; uterus myoma; devices; equipment design; laparoscopy; leiomyoma; middle aged; myomectomy; procedures; robot assisted surgery; surgery; treatment outcome; uterus tumor | English | 2024 | 2024-08 | 10.1002/ijgo.15420 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | 6DoF Object Pose and Focal Length Estimation from Single RGB Images in Uncontrolled Environments | Accurate 6DoF (degrees of freedom) pose and focal length estimation are important in extended reality (XR) applications, enabling precise object alignment and projection scaling, thereby enhancing user experiences. This study focuses on improving 6DoF pose estimation using single RGB images of unknown camera metadata. Estimating the 6DoF pose and focal length from an uncontrolled RGB image, obtained from the internet, is challenging because it often lacks crucial metadata. Existing methods such as FocalPose and Focalpose++ have made progress in this domain but still face challenges due to the projection scale ambiguity between the translation of an object along the z-axis (tz) and the camera's focal length. To overcome this, we propose a two-stage strategy that decouples the projection scaling ambiguity in the estimation of z-axis translation and focal length. In the first stage, tz is set arbitrarily, and we predict all the other pose parameters and focal length relative to the fixed tz. In the second stage, we predict the true value of tz while scaling the focal length based on the tz update. The proposed two-stage method reduces projection scale ambiguity in RGB images and improves pose estimation accuracy. The iterative update rules constrained to the first stage and tailored loss functions including Huber loss in the second stage enhance the accuracy in both 6DoF pose and focal length estimation. Experimental results using benchmark datasets show significant improvements in terms of median rotation and translation errors, as well as better projection accuracy compared to the existing state-of-the-art methods. In an evaluation across the Pix3D datasets (chair, sofa, table, and bed), the proposed two-stage method improves projection accuracy by approximately 7.19%. Additionally, the incorporation of Huber loss resulted in a significant reduction in translation and focal length errors by 20.27% and 6.65%, respectively, in comparison to the Focalpose++ method. | Manawadu, Mayura; Park, Soon-Yong | Kyungpook Natl Univ, Grad Sch Elect & Elect Engn, Daegu 41566, South Korea | ; Park, Soon-Yong/HGV-2374-2022 | 58875158200; 7501834063 | mayuramanawadu@knu.ac.kr;sypark@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 17 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 0.38 | 2025-05-07 | 1 | 1 | 6DoF; pose estimation; focal length; uncontrolled RGB images; XR | RECOGNITION | 6DoF; focal length; pose estimation; uncontrolled RGB images; XR | RGB color model; 6dof; Focal lengths; Length estimation; Object pose; Pose-estimation; RGB images; Scalings; Two-stage methods; Uncontroled RGB image; XR; adult; article; benchmarking; camera; chair; controlled study; diagnosis; human; rotation; Image enhancement | English | 2024 | 2024-09 | 10.3390/s24175474 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Compact Ultra-Wideband Wilkinson Power Divider in Parallel Stripline with Modified Isolation Branches | An efficient design method for a compact and ultra-wideband multi-stage Wilkinson power divider in a parallel stripline (PSL) is proposed. To enhance the frequency bandwidth of the proposed power divider while reducing its size, the isolation branch is modified; that is, two capacitors are connected to both sides of a resistor at each isolation branch. For an efficient design process, the PSL power divider is equivalently represented by two microstrip power dividers, and the design equations are derived. Based on the design equations, an in-house algorithm is utilized to optimally determine the design parameters, including the line impedance, resistance, and capacitance of each stage. For example, a three-stage PSL power divider is designed with three lambda/4 transmission lines at a base frequency of 5 GHz. To verify the accuracy of the design procedure, 3D EM simulations and measurements are performed, and the results show good agreement. Compared with the conventional three-stage Wilkinson power divider, the proposed PSL power divider achieves a wider frequency bandwidth of 1.16 to 6.51 GHz (139.5%) and a 23% shorter transmission line length of 207 degrees, while exhibiting an insertion loss of 0.7 to 1.4 dB. | Go, Dong-Jae; Min, Byung-Cheol; Kim, Mun-Ju; Choi, Hyun-Chul; Kim, Kang-Wook | Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | 59171168400; 39161762500; 57478219300; 57193342681; 57204432422 | dongjae.go1@gmail.com;minbc4658@knu.ac.kr;dranswn@knu.ac.kr;hcchoi@ee.knu.ac.kr;kang_kim@ee.knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 11 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 1.15 | 2025-05-07 | 3 | 3 | parallel stripline; power divider/combiner; ultra-wideband; isolation branch; optimization algorithm | DESIGN | isolation branch; optimization algorithm; parallel stripline; power divider/combiner; ultra-wideband | Bandwidth; Electric power transmission; Strip telecommunication lines; Ultra-wideband (UWB); Voltage dividers; Design equation; Efficient designs; Frequency band width; Isolation branch; Optimization algorithms; Parallel stripline; Power divider; Power divider/combiner; Ultrawide band; Wilkinson power dividers; algorithm; article; bandwidth; controlled study; drug development; human; impedance; simulation; Electric lines | English | 2024 | 2024-06 | 10.3390/s24113437 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Crack Detection and Analysis of Concrete Structures Based on Neural Network and Clustering | Concrete is extensively used in the construction of infrastructure such as houses and bridges. However, the appearance of cracks in concrete structures over time can diminish their sealing and load-bearing capability, potentially leading to structural failures and disasters. The timely detection of cracks allows for repairs without the need to replace the entire structure, resulting in cost savings. Currently, manual inspection remains the predominant method for identifying concrete cracks. However, in today's increasingly complex construction environments, subjective errors may arise due to human vision and perception. The purpose of this work is to investigate and design an autonomous convolutional neural network-based concrete detection system that can identify cracks automatically and use that information to calculate the crack proportion. The experiment's findings show that the trained model can classify concrete cracks with an accuracy of 99.9%. Moreover, the clustering technique applied to crack images enables the clear identification of the percentage of cracks, which facilitates the development of concrete damage level detection over time. | Choi, Young; Park, Hee Won; Mi, Yirong; Song, Sujeen | Earth Turbine, 36 Dongdeok Ro 40 Gil, Daegu 41905, South Korea; Kyungpook Natl Univ, Sch Architecture Civil Environm & Energy Engn, 80 Daehak Ro, Daegu 41566, South Korea | 58937691800; 58962435500; 57225181327; 58536583500 | youngch5@naver.com;phoid1@knu.ac.kr;2021320938@knu.ac.kr;songsujeen69@gmail.com; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 6 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 5.36 | 2025-05-07 | 12 | 19 | deep learning; concrete crack detection; Resnet50; k-means clustering | ALGORITHM | concrete crack detection; deep learning; k-means clustering; Resnet50 | Bridges; Concrete buildings; Concrete construction; Concretes; Convolutional neural networks; Damage detection; Deep learning; Failure (mechanical); Fracture mechanics; K-means clustering; concrete; Concrete crack detection; Concrete cracks; Deep learning; K-means++ clustering; Load-bearing capability; Neural clustering; Neural-networks; Resnet50; Structural failure; Structure-based; article; controlled study; convolutional neural network; cost control; deep learning; human; k means clustering; load bearing; nerve cell network; Crack detection | English | 2024 | 2024-03 | 10.3390/s24061725 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Dense Convolutional Neural Network-Based Deep Learning Pipeline for Pre-Identification of Circular Leaf Spot Disease of Diospyros kaki Leaves Using Optical Coherence Tomography | Circular leaf spot (CLS) disease poses a significant threat to persimmon cultivation, leading to substantial harvest reductions. Existing visual and destructive inspection methods suffer from subjectivity, limited accuracy, and considerable time consumption. This study presents an automated pre-identification method of the disease through a deep learning (DL) based pipeline integrated with optical coherence tomography (OCT), thereby addressing the highlighted issues with the existing methods. The investigation yielded promising outcomes by employing transfer learning with pre-trained DL models, specifically DenseNet-121 and VGG-16. The DenseNet-121 model excels in differentiating among three stages of CLS disease (healthy (H), apparently healthy (or healthy-infected (HI)), and infected (I)). The model achieved precision values of 0.7823 for class-H, 0.9005 for class-HI, and 0.7027 for class-I, supported by recall values of 0.8953 for class-HI and 0.8387 for class-I. Moreover, the performance of CLS detection was enhanced by a supplemental quality inspection model utilizing VGG-16, which attained an accuracy of 98.99% in discriminating between low-detail and high-detail images. Moreover, this study employed a combination of LAMP and A-scan for the dataset labeling process, significantly enhancing the accuracy of the models. Overall, this study underscores the potential of DL techniques integrated with OCT to enhance disease identification processes in agricultural settings, particularly in persimmon cultivation, by offering efficient and objective pre-identification of CLS and enabling early intervention and management strategies. | Kalupahana, Deshan; Kahatapitiya, Nipun Shantha; Silva, Bhagya Nathali; Kim, Jeehyun; Jeon, Mansik; Wijenayake, Udaya; Wijesinghe, Ruchire Eranga | Univ Sri Jayewardenepura, Fac Engn, Dept Comp Engn, Nugegoda 10250, Sri Lanka; Sri Lanka Inst Informat Technol, Fac Comp, Dept Informat Technol, Malabe 10115, Sri Lanka; Sri Lanka Inst Informat Technol, Ctr Excellence Informat Elect & Transmiss CIET, Malabe 10115, Sri Lanka; Kyungpook Natl Univ, Coll IT Engn, Sch Elect & Elect Engn, 80 Daehak Ro, Daegu 41566, South Korea; Sri Lanka Inst Informat Technol, Fac Engn, Dept Elect & Elect Engn, Malabe 10115, Sri Lanka | Wijesinghe, Ruchire/K-3797-2016; Kahatapitiya, Nipun Shantha/IYJ-5055-2023; Silva, Bhagya/AAW-1014-2021; Wijenayake, Udaya/AAY-8146-2021 | 59302759700; 58781581100; 57192304387; 7601373350; 24171094000; 55547801900; 56018152300 | deshankalupahana@sjp.ac.lk;egt18538@sjp.ac.lk;nathali.s@sliit.lk;jeehk@knu.ac.kr;msjeon@knu.ac.kr;udayaw@sjp.ac.lk;eranga.w@sliit.lk; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 16 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 1.15 | 2025-05-07 | 1 | 3 | circular leaf spot (CLS) disease; classification; deep learning (DL); disease identification; optical coherence tomography (OCT); transfer learning | CLASSIFICATION | circular leaf spot (CLS) disease; classification; deep learning (DL); disease identification; optical coherence tomography (OCT); transfer learning | Deep Learning; Diospyros; Image Processing, Computer-Assisted; Neural Networks, Computer; Plant Diseases; Plant Leaves; Tomography, Optical Coherence; Deep neural networks; Optical tomography; Circular leaf spot disease; Class I; Coherence tomography; Deep learning; Disease identification; Leaf spot disease; Leaf spots; Optical coherence tomography; Optical-; Transfer learning; artificial neural network; deep learning; Diospyros; image processing; optical coherence tomography; plant disease; plant leaf; procedures; Optical coherence tomography | English | 2024 | 2024-08 | 10.3390/s24165398 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Design of Wideband Flextensional Hydrophone | Flextensional transducers have been widely used as low-frequency projectors, and these characteristics can be used to develop hydrophones with wider receiver bandwidth and higher sensitivity than conventional products in low-frequency ranges. In this work, we designed flextensional hydrophones of all classes, and compared their acoustic receiver performance to select the most suitable class for a low-frequency broadband hydrophone. For this purpose, basic models of the hydrophones were constructed for all classes and the effects of various structural parameters on the acoustic receiver characteristics of the hydrophones were analyzed. Based on the results, the structure of the flextensional hydrophone of each class was designed to have the maximum receiver bandwidth by an optimization technique while maintaining the receiver voltage sensitivity over a certain level. A comparison of the designed performance led to the selection of the class IV flextensional hydrophone as the most promising one with the widest receiver fractional bandwidth and highest sensitivity. | Kim, Gihyeon; Kim, Donghyun; Roh, Yongrae | Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea | 59253817700; 58950709000; 7102361870 | f12gto5800@naver.com;roy4435@naver.com;yryong@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 15 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 0.38 | 2025-05-07 | 2 | 1 | flextensional hydrophone; receiving voltage sensitivity (RVS); low frequency broadband hydrophone | flextensional hydrophone; low frequency broadband hydrophone; receiving voltage sensitivity (RVS) | Bandwidth; Flextensional; Flextensional hydrophone; Flextensional transducers; High sensitivity; Low frequency broadband hydrophone; Lower frequencies; Receiver bandwidths; Receiving voltage sensitivity; Voltage sensitivity; Wide-band; article; bandwidth; controlled study; electric potential; therapy; Hydrophones | English | 2024 | 2024-08 | 10.3390/s24154941 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Detection of Low-Density Foreign Objects in Infant Snacks Using a Continuous-Wave Sub-Terahertz Imaging System for Industrial Applications | Low-density foreign objects (LDFOs) in foods pose significant safety risks to consumers. Existing detection methods, such as metal and X-ray detectors, have limitations in identifying low-density and nonmetallic contaminants. To address these challenges, our research group constructed and optimized a continuous-wave sub-terahertz (THz) imaging system for the real-time, on-site detection of LDFOs in infant snacks. The system was optimized by adjusting the attenuation value from 0 to 9 dB and image processing parameters [White (W), Black (B), and Gamma (G)] from 0 to 100. Its detectability was evaluated across eight LDFOs underneath snacks with scanning at 30 cm/s. The optimal settings for puffed snacks and freeze-dried chips were found to be 3 dB attenuation with W, B, and G values of 100, 50, and 80, respectively, while others required 0 dB attenuation with W, B, and G set to 100, 0, and 100, respectively. Additionally, the moisture content of infant snacks was measured using a modified AOAC-based drying method at 105 degrees C, ensuring the removal of all free moisture. Using these optimized settings, the system successfully detected a housefly and a cockroach underneath puffed snacks and freeze-dried chips. It also detected LDFOs as small as 3 mm in size in a single layer of snacks, including polyurethane, polyvinyl chloride, ethylene-propylene-diene-monomer, and silicone, while in two layers of infant snacks, they were detected up to 7.5 mm. The constructed system can rapidly and effectively detect LDFOs in foods, offering a promising approach to enhance safety in the food industry. | Na, Byeong-Hyeon; Lee, Dae-Ho; Choe, Jaein; Kim, Young-Duk; Park, Mi-Kyung | Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea; Daegu Gyeongbuk Inst Sci & Technol DGIST, ICT Res Inst, Daegu 42988, South Korea | choe, jaein/JMQ-8957-2023; Park, Mi-Kyung/J-9643-2017 | 59425804700; 59636094900; 57226770667; 55955831300; 7404491155 | hyeonbest@knu.ac.kr;dleogh3046@knu.ac.kr;jane100497@naver.com;ydkim@dgist.ac.kr;parkmik@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 22 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 0 | 2025-05-07 | 0 | 0 | sub-terahertz imaging; low-density foreign objects; on-site detection; infant snacks | BODY ASPIRATION; QUALITY | infant snacks; low-density foreign objects; on-site detection; sub-terahertz imaging | Food Contamination; Foreign Bodies; Humans; Infant; Snacks; Terahertz Imaging; Case hardening; Food safety; Freezing; Low temperature drying; Polyvinyl chlorides; Pressure sensors; Remote sensing; Strain hardening; Surface hardening; Temperature sensors; Terahertz wave detectors; Thermography (imaging); Continuous Wave; Foreign object; Infant snack; Low-density foreign object; Lower density; On-site detection; Sub-terahertz; Sub-terahertz imaging; Terahertz imaging; Terahertz imaging systems; diagnostic imaging; fast food; food contamination; foreign body; human; infant; procedures; terahertz imaging; X ray detectors | English | 2024 | 2024-11 | 10.3390/s24227374 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Development of an In-Pipe Inspection Robot for Large-Diameter Water Pipes | This paper describes the development of an in-pipe inspection robot system designed for large-diameter water pipes. The robot is equipped with a Magnetic Flux Leakage (MFL) sensor module. The robot system is intended for pipes with diameters ranging from 900 mm to 1200 mm. The structure of the in-pipe inspection robot consists of the front and rear driving parts, with the inspection module located centrally. The robot is powered by 22 motors, including eight wheels with motors positioned at both the bottom and the top for propulsion. To ensure that the robot's center aligns with that of the pipeline during operation, lifting units have been incorporated. The robot is equipped with cameras and LiDAR sensors at the front and rear to monitor the internal environment of the pipeline. Pipeline inspection is conducted using the MFL inspection modules, and the robot's driving mechanism is designed to execute spiral maneuvers while maintaining contact with the pipeline surface during rotation. The in-pipe inspection robot is configured with wireless communication modules and batteries, allowing for wireless operation. Following its development, the inspection robot underwent driving experiments in actual pipelines to validate its performance. The field test bed used for these experiments is approximately 1 km in length. Results from the driving experiments on the field test bed confirmed the robot's ability to navigate various curvatures and obstacles within the pipeline. It is posited that the use of the developed in-pipe inspection robot can reduce economic costs and enhance the safety of inspectors when examining aging pipes. | Jeon, Kwang-Woo; Jung, Eui-Jung; Bae, Jong-Ho; Park, Sung-Ho; Kim, Jung-Jun; Chung, Goobong; Chung, Hyun-Joon; Yi, Hak | Korea Inst Robot & Technol Convergence, Pohang 37666, South Korea; Kyungpook Natl Univ, Dept Mech Engn, Daegu 41566, South Korea | park, sungho/ABA-4566-2020; Bae, Jong-Ho/V-5237-2019 | 26024764800; 59277261600; 57215318354; 57191670870; 57221333354; 57214343991; 33067490100; 56567311000 | jeonkw@kiro.re.kr;ejjunmg@kiro.re.kr;jongho.bae@kiro.re.kr;psh84@kiro.re.kr;jjkim@kiro.re.kr;goobongc@kiro.re.kr;hjchung@kiro.re.kr;yihak@knu.ac.kr; | SENSORS | SENSORS-BASEL | 1424-8220 | 24 | 11 | SCIE | CHEMISTRY, ANALYTICAL;ENGINEERING, ELECTRICAL & ELECTRONIC;INSTRUMENTS & INSTRUMENTATION | 2024 | 3.5 | 29.7 | 2.3 | 2025-05-07 | 4 | 7 | in-pipe robot design; defect detection; autonomous driving; posture control | autonomous driving; defect detection; in-pipe robot design; posture control | Equipment testing; Machine design; Optical radar; Robots; Water pipelines; Autonomous driving; Defect detection; In-pipe inspection robot; In-pipe robot; In-pipe robot design; Large diameter; Posture control; Robot designs; Robots system; Water pipes; adult; aging; article; biomechanics; body position; camera; female; human experiment; inspector; magnetic field; male; normal human; rotation; safety; sensor; tube; water; wireless communication; young adult; Inspection | English | 2024 | 2024-06 | 10.3390/s24113470 | 바로가기 | 바로가기 | 바로가기 | 바로가기 |
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