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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 | Process optimization for microfluidic preparation of liposomes using food-grade components | This study explores the potential for optimizing a sustainable manufacturing process that maintains the essential characteristics of conventional liposomes using food-grade solvents and components. The focus was comparing the physicochemical, morphological, and interfacial properties of liposomes produced with these food-grade ingredients to those made by conventional methods. It was found that there was no significant difference in particle size (195.87 +/- 1.40 nm) and zeta -potential (-45.13 +/- 0.65 mV) between liposomes made from food-grade and conventional materials. The manufacturing process for liposomes, utilizing food-grade solvents and components, was optimized through the application of Plackett-Burman design and response surface methodology. This approach helped identify key parameters (soy lecithin, beta -sitosterol, W/O ratio) and their optimal values (3.17 g, 0.25 g, 1:2.59). These findings suggest that it is possible to enhance the use of liposomes as an effective and safe delivery system in the food industry, adhering to the strict guidelines set by regulatory agencies. | Hong, Sung-Chul; Hong, Chi Rac; Kim, Minsoo; Kang, Yue Jai; Jung, Young Hoon; Park, Kyung-Min; Choi, Jaeyoung; Chang, Pahn-Shick | Kunsan Natl Univ, Dept Food Sci & Biotechnol, Gunsan 54150, South Korea; Seoul Natl Univ Sci & Technol, Dept Food Sci & Technol, Seoul 01811, South Korea; Natl Inst Math Sci, Div Fundamental Res Publ Agenda, Res Team Transmiss Dynam Infect Dis, Daejeon 34047, South Korea; Kunsan Natl Univ, Dept Aquat Life Med, Gunsan 54150, South Korea; Kyungpook Natl Univ, Sch Food Sci & Biotechnol, Daegu 41566, South Korea; Wonkwang Univ, Dept Food Sci & Biotechnol, Iksan 54538, South Korea; Kyung Hee Univ, Dept Oriental Med Biotechnol, Yongin 17104, South Korea; Seoul Natl Univ, Dept Agr Biotechnol, Seoul 08826, South Korea; Seoul Natl Univ, Ctr Food & Bioconvergence, Seoul 08826, South Korea; Seoul Natl Univ, Ctr Agr Microorganism & Enzyme, Seoul 08826, South Korea; Seoul Natl Univ, Res Inst Agr & Life Sci, Seoul 08826, South Korea | Jung, Young/F-1703-2013; PARK, KYUNG/B-9342-2012; Hong, Sung-Chul/ABA-5643-2021; kang, yue/GYA-2003-2022; Choi, Jaeyoung/T-5932-2019 | 58612005000; 56391558700; 59000552400; 34872393600; 55550063700; 56358951700; 57199098501; 35749476600 | jaeyoung.choi@khu.ac.kr;pschang@snu.ac.kr; | FOOD CHEMISTRY | FOOD CHEM | 0308-8146 | 1873-7072 | 451 | SCIE | CHEMISTRY, APPLIED;FOOD SCIENCE & TECHNOLOGY;NUTRITION & DIETETICS | 2024 | 9.8 | 3.1 | 0.34 | 2025-05-07 | 1 | 1 | Liposome; Microfluidizer; Food-grade component; Process optimization; Plackett -Burman design; Response surface methodology | LOADED LIPOSOMES; BIOAVAILABILITY; EMULSIONS; ENCAPSULATION; STABILITY; AGENTS | Food-grade component; Liposome; Microfluidizer; Plackett–Burman design; Process optimization; Response surface methodology | Glycine max; Lecithins; Liposomes; Microfluidics; Particle Size; Sitosterols; Design; Liposomes; Particle size; Physicochemical properties; Process control; Surface properties; food ingredient; liposome; phosphatidylcholine; sitosterol; gamma-sitosterol; phosphatidylcholine; sitosterol derivative; Essential characteristic; Food grade; Food-grade component; Manufacturing process; Microfluidizers; Physicochemical property; Plackett -burman design; Process optimisation; Response-surface methodology; Sustainable manufacturing; Article; cell culture; cell viability; central composite design; controlled study; cytotoxicity; dispersity; HT-29 cell line; human; human cell; manufacturing; microfluidics; MTT assay; particle size; photon correlation spectroscopy; process optimization; refraction index; response surface method; transmission electron microscopy; viscosity; zeta potential; chemistry; devices; microfluidics; particle size; soybean; Optimization | English | 2024 | 2024-09-01 | 10.1016/j.foodchem.2024.139437 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | Meeting Abstract | Reverting radioiodine avidity and enhancing treatment effect using engineered macrophage derived extracellular vesicles in radioiodine refractory thyroid cancers | Gangadaran, Prakash; Rajendran, Ramya; Oh, Ji Min; Ahn, Byeong-Cheol; Jeong, Shin Young; Lee, Sang-Woo; Hong, Chae Moon | Kyungpook Natl Univ, Daegu, South Korea | Lee, Sangwoo/MVV-2859-2025; Gangadaran, Prakash/AAV-3102-2021; Rajendran, Ramya/AAV-6338-2021 | JOURNAL OF NUCLEAR MEDICINE | J NUCL MED | 0161-5505 | 1535-5667 | 65 | SCIE | RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING | 2024 | 9.1 | 3.1 | 0 | English | 2024 | 2024-06-01 | 바로가기 | 바로가기 | ||||||||||||||||
| ○ | Article | Test of lepton flavor universality in B± → K± μ⁺μ⁻ and B± → K± e⁺ e⁻ decays in proton-proton collisions at √s=13 TeV | A test of lepton flavor universality in B-+/- -> K +/- mu(+) mu(-) and B-+/- -> (K)+/- e(+) e(-) decays, as well as a measurement of differential and integrated branching fractions of a nonresonant B-+/- -> K-+/- mu(+)mu(-) decay are presented. The analysis is made possible by a dedicated data set of proton-proton collisions at root s = 13 TeV recorded in 2018, by the CMS experiment at the LHC, using a special high-rate data stream designed for collecting about 10 billion unbiased b hadron decays. The ratio of the branching fractions B(B-+/- -> K-+/- mu(+) mu(-)) to B(B-+/- -> K-+/- e(+) e(-)) is determined from the measured double ratio R(K) of these decays to the respective branching fractions of the B-+/- -> J/psi K-+/- with J/psi -> mu(+)mu(-) and e(+) e(-) decays, which allow for significant cancellation of systematic uncertainties. The ratio R(K) is measured in the range 1.1 K-+/- mu(+) mu(-)) = (12.42 +/- 0.68) x 10(-8), is consistent with the present world-average value and has a comparable precision. | Hayrapetyan, A.; Tumasyan, A.; Adam, W.; Andrejkovic, J. W.; Bergauer, T.; Chatterjee, S.; Damanakis, K.; Dragicevic, M.; Hussain, P. S.; Jeitler, M.; Krammer, N.; Li, A.; Liko, D.; Mikulec, I.; Schieck, J.; Schoefbeck, R.; Schwarz, D.; Sonawane, M.; Templ, S.; Waltenberger, W.; Wulz, C. -E; Darwish, M. R.; Janssen, T.; Van Mechelen, P.; Bols, E. S.; D'Hondt, J.; Dansana, S.; De Moor, A.; Delcourt, M.; El Faham, H.; Lowette, S.; Makarenko, I.; Muller, D.; Sahasransu, A. R.; Tavernier, S.; Tytgat, M.; Van Onsem, G. P.; Van Putte, S.; Vannerom, D.; Clerbaux, B.; Das, A. K.; De Lentdecker, G.; Favart, L.; Gianneios, P.; Hohov, D.; Jaramillo, J.; Khalilzadeh, A.; Lee, K.; Mahdavikhorrami, M.; Malara, A.; Paredes, S.; Postiau, N.; Thomas, L.; Vanden Bemden, M.; Vander Velde, C.; Vanlaer, P.; De Coen, M.; Dobur, D.; Hong, Y.; Knolle, J.; Lambrecht, L.; Mestdach, G.; Amarilo, K. Mota; Rendon, C.; Samalan, A.; Skovpen, K.; Van den Bossche, N.; van der Linden, J.; Wezenbeek, L.; Benecke, A.; Bethani, A.; Bruno, G.; Caputo, C.; Delaere, C.; Donertas, I. S.; Giammanco, A.; Jaffel, K.; Jain, Sa; Lemaitre, V.; Lidrych, J.; Mastrapasqua, P.; Mondal, K.; Tran, T. T.; Wertz, S.; Alves, G. A.; Coelho, E.; Hensel, C.; Menezes De Oliveira, T.; Moraes, A.; Rebello Teles, P.; Soeiro, M.; 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.; Fonseca De Souza, S.; Gomes De Souza, R.; Martins, J.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Pinheiro, J. P.; Santoro, A.; Sznajder, A.; Thiel, M.; Vilela Pereira, A.; Bernardes, C. A.; Calligaris, L.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Orzari, B.; Padula, Sandra S.; Aleksandrov, A.; Antchev, G.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Petrov, A.; Shumka, E.; Keshri, S.; Thakur, S.; Cheng, T.; Javaid, T.; Yuan, L.; Hu, Z.; Liu, J.; Yi, K.; Chen, G. M.; Chen, H. S.; Chen, M.; Iemmi, F.; Jiang, C. H.; Kapoor, A.; Liao, H.; Liu, Z. -A; Sharma, R.; Song, J. N.; Tao, J.; Wang, C.; Wang, J.; Wang, Z.; Zhang, H.; Agapitos, A.; Ban, Y.; Levin, A.; Li, C.; Li, Q.; Mao, Y.; Qian, S. J.; Sun, X.; Wang, D.; Yang, H.; Zhang, L.; Zhou, C.; You, Z.; Lu, N.; Bauer, G.; Gao, X.; Leggat, D.; Okawa, H.; Lin, Z.; Lu, C.; Xiao, M.; Avila, C.; Barbosa Trujillo, D. A.; Cabrera, A.; Florez, C.; Fraga, J.; Reyes Vega, J. A.; Mejia Guisao, J.; Ramirez, F.; Rodriguez, M.; Ruiz Alvarez, J. D.; Giljanovic, D.; Godinovic, N.; Lelas, D.; Sculac, A.; Kovac, M.; Sculac, T.; Bargassa, P.; Brigljevic, V.; Chitroda, B. K.; Ferencek, D.; Mishra, S.; Starodumov, A.; Susa, T.; Attikis, A.; Christoforou, K.; Konstantinou, S.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Saka, H.; Stepennov, A.; Finger, M.; Finger, M., Jr.; Kveton, A.; Ayala, E.; Carrera Jarrin, E.; Abdelalim, A. A.; Salama, E.; Lotfy, A.; Mahmoud, M. A.; Ehataht, K.; Kadastik, M.; Lange, T.; Nandan, S.; Nielsen, C.; Pata, J.; Raidal, M.; Tani, L.; Veelken, C.; Kirschenmann, H.; Osterberg, K.; Voutilainen, M.; Bharthuar, S.; Brucken, E.; Garcia, F.; Kallonen, K. T. S.; Kinnunen, R.; Lampen, T.; Lassila-Perini, K.; Lehti, S.; Linden, T.; Martikainen, L.; Myllymaki, M.; Rantanen, M. M.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Luukka, P.; Petrow, H.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Gras, P.; de Monchenault, G. Hamel; Lohezic, V.; Malcles, J.; Rander, J.; Rosowsky, A.; Sahin, M. O.; Savoy-Navarro, A.; Simkina, P.; Titov, M.; Tornago, M.; Barrera, C. Baldenegro; Beaudette, F.; Perraguin, A. Buchot; Busson, P.; Cappati, A.; Charlot, C.; Chiusi, M.; Damas, F.; Davignon, O.; De Wit, A.; Alves, B. A. Fontana Santos; Ghosh, S.; Gilbert, A.; de Cassagnac, R. Granier; Hakimi, A.; Harikrishnan, B.; Kalipoliti, L.; Liu, G.; Motta, J.; Nguyen, M.; Ochando, C.; Portales, L.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Tarabini, A.; Vernazza, E.; Zabi, A.; Zghiche, A.; Agram, J. -L; Andrea, J.; Apparu, D.; Bloch, D.; Brom, J. -M; Chabert, E. C.; Collard, C.; Falke, S.; Goerlach, U.; Grimault, C.; Haeberle, R.; Le Bihan, A. -C; Meena, M.; Saha, G.; Sessini, M. A.; Van Hove, P.; Beauceron, S.; Blancon, B.; Boudoul, G.; Chanon, N.; Choi, J.; Contardo, D.; Depasse, P.; Dozen, C.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Greenberg, C.; Grenier, G.; Ille, B.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Perries, S.; Purohit, A.; Vander Donckt, M.; Verdier, P.; Xiao, J.; Chokheli, D.; Lomidze, I.; Tsamalaidze, Z.; Botta, V.; Feld, L.; Klein, K.; Lipinski, M.; Meuser, D.; Pauls, A.; Roewert, N.; Teroerde, M.; Diekmann, S.; Dodonova, A.; Eich, N.; Eliseev, D.; Engelke, F.; Erdmann, J.; Erdmann, M.; Fackeldey, P.; Fischer, B.; Hebbeker, T.; Hoepfner, K.; Ivone, F.; Jung, A.; Lee, M. Y.; Mastrolorenzo, L.; Mausolf, F.; Merschmeyer, M.; Meyer, A.; Mukherjee, S.; Noll, D.; Nowotny, F.; Pozdnyakov, A.; Rath, Y.; Redjeb, W.; Rehm, F.; Reithler, H.; Sarkar, U.; Sarkisovi, V.; Schmidt, A.; Sharma, A.; Spah, J. L.; Stein, A.; De Araujo, F. Torres Da Silva; Vigilante, L.; Wiedenbeck, S.; Zaleski, S.; Dziwok, C.; Fluegge, G.; Ahmad, W. Haj; Kress, T.; Nowack, A.; Pooth, O.; Stahl, A.; Ziemons, T.; Zotz, A.; Petersen, H. Aarup; Martin, M. Aldaya; Alimena, J.; Amoroso, S.; An, Y.; Baxter, S.; Bayatmakou, M.; Gonzalez, H. Becerril; Behnke, O.; Belvedere, A.; Bhattacharya, S.; Blekman, F.; Borras, K.; Campbell, A.; Cardini, A.; Cheng, C.; Colombina, F.; Rodriguez, S. Consuegra; Silva, G. Correia; De Silva, M.; Eckerlin, G.; Eckstein, D.; Banos, L. I. Estevez; Filatov, O.; Gallo, E.; Geiser, A.; Giraldi, A.; Greau, G.; Guglielmi, V.; Guthoff, M.; Hinzmann, A.; Jafari, A.; Jeppe, L.; Jomhari, N. Z.; Kaech, B.; Kasemann, M.; Kleinwort, C.; Kogler, R.; Komm, M.; Kruecker, D.; Lange, W.; Pernia, D. Leyva; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I-A; Morentin, M. Mendizabal; Meyer, A. B.; Milella, G.; Mussgiller, A.; Nair, L. P.; Nuernberg, A.; Otarid, Y.; Park, J.; Adan, D. Perez; Ranken, E.; Raspereza, A.; Lopes, B. Ribeiro; Ruebenach, J.; Saggio, A.; Scham, M.; Schnake, S.; Schuetze, P.; Schwanenberger, C.; Selivanova, D.; Sharko, K.; Shchedrolosiev, M.; Ricardo, R. E. Sosa; Stafford, D.; Vazzoler, F.; Barroso, A. Ventura; Walsh, R.; Wang, Q.; Wen, Y.; Wichmann, K.; Wiens, L.; Wissing, C.; Yang, Y.; Santos, A. Zimermmane Castro; Albrecht, A.; Albrecht, S.; Antonello, M.; Bein, S.; Benato, L.; Bollweg, S.; Bonanomi, M.; Connor, P.; Eich, M.; El Morabit, K.; Fischer, Y.; Froehlich, A.; Garbers, C.; Garutti, E.; Grohsjean, A.; Hajheidari, M.; Haller, J.; Jabusch, H. R.; Kasieczka, G.; Keicher, P.; Klanner, R.; Korcari, W.; Kramer, T.; Kutzner, V.; Labe, F.; Lange, J.; Lobanov, A.; Matthies, C.; Mehta, A.; Moureaux, L.; Mrowietz, M.; Nigamova, A.; Nissan, Y.; Paasch, A.; Rodriguez, K. J. Pena; Quadfasel, T.; Raciti, B.; Rieger, M.; Savoiu, D.; Schindler, J.; Schleper, P.; Schroeder, M.; Schwandt, J.; Sommerhalder, M.; Stadie, H.; Steinbrueck, G.; Tews, A.; Wolf, M.; Brommer, S.; Burkart, M.; Butz, E.; Chwalek, T.; Dierlamm, A.; Droll, A.; Faltermann, N.; Giffels, M.; Gottmann, A.; Hartmann, F.; Hofsaess, R.; Horzela, M.; Husemann, U.; Kieseler, J.; Klute, M.; Koppenhoefer, R.; Lawhorn, J. M.; Link, M.; Lintuluoto, A.; Maier, S.; Mitra, S.; Mormile, M.; Mueller, Th; Neukum, M.; Oh, M.; Presilla, M.; Quast, G.; Rabbertz, K.; Regnery, B.; Shadskiy, N.; Shvetsov, I.; Simonis, H. J.; Toms, M.; Trevisani, N.; Ulrich, R.; Von Cube, R. F.; Wassmer, M.; Wieland, S.; Wittig, F.; Wolf, R.; Zuo, X.; Anagnostou, G.; Daskalakis, G.; Kyriakis, A.; Papadopoulos, A.; Stakia, A.; Kontaxakis, P.; Melachroinos, G.; Panagiotou, A.; Papavergou, I.; Paraskevas, I.; Saoulidou, N.; Theofilatos, K.; Tziaferi, E.; Vellidis, K.; Zisopoulos, I.; Bakas, G.; Chatzistavrou, T.; Karapostoli, G.; Kousouris, K.; Papakrivopoulos, I.; Siamarkou, E.; Tsipolitis, G.; Zacharopoulou, A.; Adamidis, K.; Bestintzanos, I.; Evangelou, I.; Foudas, C.; Kamtsikis, C.; Katsoulis, P.; Kokkas, P.; Kioseoglou, P. G. Kosmoglou; Manthos, N.; Papadopoulos, I.; Strologas, J.; Bartok, M.; Hajdu, C.; Horvath, D.; Marton, K.; Sikler, F.; Veszpremi, V.; Csanad, M.; Farkas, K.; Gadallah, M. M. A.; Kadlecsik, A.; Major, P.; Mandal, K.; Pasztor, G.; Radl, A. J.; Veres, G. I.; Raics, P.; Ujvari, B.; Zilizi, G.; Bencze, G.; Czellar, S.; Molnar, J.; Szillasi, Z.; Csorgo, T.; Nemes, F.; Novak, T.; Babbar, J.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chaudhary, G.; Chauhan, S.; Dhingra, N.; Kaur, A.; Kaur, A.; Kaur, H.; Kaur, M.; Kumar, S.; Sandeep, K.; Sheokand, T.; Singh, J. B.; Singla, A.; Ahmed, A.; Bhardwaj, A.; Chhetri, A.; Choudhary, B. C.; Kumar, A.; Kumar, A.; Naimuddin, M.; Ranjan, K.; Saumya, S.; Baradia, S.; Barman, S.; Bhattacharya, S.; Dutta, S.; Dutta, S.; Sarkar, S.; Ameen, M. M.; Behera, P. K.; Behera, S. C.; Chatterjee, S.; Jana, P.; Kalbhor, P.; Komaragiri, J. R.; Kumar, D.; Panwar, L.; Pujahari, P. R.; Saha, N. R.; Sharma, A.; Sikdar, A. K.; Verma, S.; Dugad, S.; Kumar, M.; Mohanty, G. B.; Suryadevara, P.; Bala, A.; Banerjee, S.; Chatterjee, R. M.; Dewanjee, R. K.; Guchait, M.; Jain, Sh; Jaiswal, A.; Karmakar, S.; Kumar, S.; Majumder, G.; Mazumdar, K.; Parolia, S.; Thachayath, A.; Bahinipati, S.; Kar, C.; Maity, D.; Mal, P.; Mishra, T.; Bindhu, V. K. Muraleedharan Nair; Naskar, K.; Nayak, A.; Sadangi, P.; Saha, P.; Swain, S. K.; Varghese, S.; Vats, D.; Acharya, S.; Alpana, A.; Dube, S.; Gomber, B.; Kansal, B.; Laha, A.; Sahu, B.; Sharma, S.; Vaish, K. Y.; Bakhshiansohi, H.; Khazaie, E.; Zeinali, M.; Chenarani, S.; Etesami, S. M.; Khakzad, M.; Najafabadi, M. Mohammadi; Grunewald, M.; Abbrescia, M.; Aly, R.; Colaleo, A.; Creanza, D.; D'Anzi, B.; De Filippis, N.; De Palma, M.; Di Florio, A.; Elmetenawee, W.; Fiore, L.; Iaselli, G.; Louka, M.; Maggi, G.; Maggi, M.; Margjeka, I.; Mastrapasqua, V.; My, S.; Nuzzo, S.; Pellecchia, A.; Pompili, A.; Pugliese, G.; Radogna, R.; Ramirez-Sanchez, G.; Ramos, D.; Ranieri, A.; Silvestris, L.; Simone, F. M.; Sozbilir, U.; Stamerra, A.; Venditti, R.; Verwilligen, P.; Zaza, A.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Borgonovi, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Cuffiani, M.; Diotalevi, T.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Giommi, L.; Grandi, C.; Guiducci, L.; Lo Meo, S.; Lunerti, L.; Marcellini, S.; Masetti, G.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Costa, S.; Di Mattia, A.; Potenza, R.; Tricomi, A.; Tuve, C.; Assiouras, P.; Barbagli, G.; Bardelli, G.; Camaiani, B.; Cassese, A.; Ceccarelli, R.; Ciulli, V.; Cassese, A.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Kello, T.; Latino, G.; Lenzi, P.; Lizzo, M.; Meschini, M.; Paoletti, S.; Papanastassiou, A.; Sguazzoni, G.; Viliani, L.; Benussi, L.; Bianco, S.; Meola, S.; Piccolo, D.; Chatagnon, P.; Ferro, F.; Robutti, E.; Tosi, S.; Benaglia, A.; Boldrini, G.; Brivio, F.; Cetorelli, F.; De Guio, F.; Dinardo, M. E.; Dini, P.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Guzzi, L.; Lucchini, M. T.; Malberti, M.; Malvezzi, S.; Massironi, A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pinolini, B. S.; Ragazzi, S.; de Fatis, T. Tabarelli; Zuolo, D.; Buontempo, S.; Cagnotta, A.; Carnevali, F.; Cavallo, N.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Paolucci, P.; Rossi, B.; Sciacca, C.; Ardino, R.; Azzi, P.; Bacchetta, N.; Bortignon, P.; Bragagnolo, A.; Carlin, R.; Checchia, P.; Dorigo, T.; Gasparini, F.; Gasparini, U.; Lusiani, E.; Margoni, M.; Marini, F.; Meneguzzo, A. T.; Migliorini, M.; Montecassiano, F.; Pazzini, J.; Ronchese, P.; Rossin, R.; Simonetto, F.; Strong, G.; Tosi, M.; Triossi, A.; Ventura, S.; Yarar, H.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Abu Zeid, S.; Aime, C.; Braghieri, A.; Calzaferri, S.; Fiorina, D.; Montagna, P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Ajmal, S.; Bilei, G. M.; Ciangottini, D.; Fano, L.; Magherini, M.; Mantovani, G.; Mariani, V.; Menichelli, M.; Moscatelli, F.; Rossi, A.; Santocchia, A.; Spiga, D.; Tedeschi, T.; Asenov, P.; Azzurri, P.; Bagliesi, G.; Bhattacharya, R.; Bianchini, L.; Boccali, T.; Bossini, E.; Bruschini, D.; Castaldi, R.; Ciocci, M. A.; Cipriani, M.; D'Amante, V.; Dell'Orso, R.; Donato, S.; Giassi, A.; Ligabue, F.; Figueiredo, D. Matos; Messineo, A.; Musich, M.; Palla, F.; Rizzi, A.; Rolandi, G.; Chowdhury, S. Roy; Sarkar, T.; Scribano, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Turini, N.; Venturi, A.; Verdini, P. G.; Barria, P.; Campana, M.; Cavallari, F.; Mendez, L. Cunqueiro; Del Re, D.; Di Marco, E.; Diemoz, M.; Errico, F.; Longo, E.; Meridiani, P.; Mijuskovic, J.; Organtini, G.; Pandolfi, F.; Paramatti, R.; Quaranta, C.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Bellora, A.; Biino, C.; Borca, C.; Cartiglia, N.; Costa, M.; Covarelli, R.; Demaria, N.; Finco, L.; Grippo, M.; Kiani, B.; Legger, F.; Luongo, F.; Mariotti, C.; Markovic, L.; Maselli, S.; Mecca, A.; Migliore, E.; Monteno, M.; Mulargia, R.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Ruspa, M.; Siviero, F.; Sola, V.; Solano, A.; Staiano, A.; Tarricone, C.; Trocino, D.; Umoret, G.; Vlasov, E.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; De Leo, K.; Della Ricca, G.; Dogra, S.; Hong, J.; Huh, C.; Kim, B.; Kim, D. H.; Kim, J.; Lee, H.; Lee, S. W.; Moon, C. S.; Oh, Y. D.; Ryu, M. S.; Sekmen, S.; Yang, Y. C.; Kim, M. S.; Bak, G.; Gwak, P.; Kim, H.; Moon, D. 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Mora Herrera, Clemencia/AAD-6466-2021; Kadastik, Mario/B-7559-2008; Hill, Christopher/B-5371-2012; Salvini, Paola/G-1670-2018; Doroba, krzysztof/AAA-3419-2021 | REPORTS ON PROGRESS IN PHYSICS | REP PROG PHYS | 0034-4885 | 1361-6633 | 87 | 7 | SCIE | PHYSICS, MULTIDISCIPLINARY | 2024 | 20.7 | 3.1 | 4 | CMS; B physics; lepton flavor universality; B meson; b to sll transitions | MODEL | English | 2024 | 2024-07 | 10.1088/1361-6633/ad4e65 | 바로가기 | 바로가기 | 바로가기 | ||||||||||
| ○ | ○ | Article | Truncated predictive tracking control design for semi-Markovian jump systems with time-varying input delays | A state tracking control problem for a class of semi-Markovian jump systems (SMJSs) with input delay and disturbances is addressed in this study. In particular, an improved -equivalentinput -disturbance estimator approach (IEIDEA)-based truncated predictive controller is designed to synchronously compensate the effect of unknown external disturbances and time -varying delay. Specifically, by making use of IEIDEA, the unknown disturbances are estimated with high precision and incorporated into the control input channel, which eases the way to achieve the desired tracking performances. Specifically, the state predictor satisfies the delay -free state -space equation and is used in controller design along with prediction. In accordance with linear matrix inequality framework and Lyapunov stability theory, a set of adequate conditions are established to guarantee the state tracking performance of SMJSs. Finally, the numerical examples with simulation results are provided to validate the efficacy and practicability of the established control technique. | Harshavarthini, S.; Lee, S. M. | Vellore Inst Technol, Sch Adv Sci, Div Math, Chennai 600127, India; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | Shanmugam, Harshavarthini/AAK-3178-2021; Lee, Sangmoon/C-4502-2018 | 57204646660; 59510733500 | moony@knu.ac.kr; | APPLIED MATHEMATICS AND COMPUTATION | APPL MATH COMPUT | 0096-3003 | 1873-5649 | 474 | SCIE | MATHEMATICS, APPLIED | 2024 | 3.4 | 3.1 | 2.48 | 2025-05-07 | 4 | 4 | Semi-Markovian jump systems; Disturbance estimator approach; Input time-varying delay; Tracking control design | LINEAR-SYSTEMS; FEEDBACK | Disturbance estimator approach; Input time-varying delay; Semi-Markovian jump systems; Tracking control design | Controllers; Equations of state; Markov processes; Navigation; Numerical methods; Time delay; Time varying control systems; Control design; Disturbance estimator; Disturbance estimator approach; Input time-varying delay; Markovian jump systems; Semi-markovian jump system; State tracking; Time-varying delay; Tracking control design; Tracking controls; Linear matrix inequalities | English | 2024 | 2024-08-01 | 10.1016/j.amc.2024.128686 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | α1-COP modulates plasmodesmata function through sphingolipid enzyme regulation | Callose, a beta-1,3-glucan plant cell wall polymer, regulates symplasmic channel size at plasmodesmata (PD) and plays a crucial role in a variety of plant processes. However, elucidating the molecular mechanism of PD callose homeostasis is limited. We screened and identified an Arabidopsis mutant plant with excessive callose deposition at PD and found that the mutated gene was alpha 1-COP, a member of the coat protein I (COPI) coatomer complex. We report that loss of function of alpha 1-COP elevates the callose accumulation at PD by affecting subcellular protein localization of callose degradation enzyme PdBG2. This process is linked to the functions of ERH1, an inositol phosphoryl ceramide synthase, and glucosylceramide synthase through physical interactions with the alpha 1-COP protein. Additionally, the loss of function of alpha 1-COP alters the subcellular localization of ERH1 and GCS proteins, resulting in a reduction of GlcCers and GlcHCers molecules, which are key sphingolipid (SL) species for lipid raft formation. Our findings suggest that alpha 1-COP protein, together with SL modifiers controlling lipid raft compositions, regulates the subcellular localization of GPI-anchored PDBG2 proteins, and hence the callose turnover at PD and symplasmic movement of biomolecules. Our findings provide the first key clue to link the COPI-mediated intracellular trafficking pathway to the callose-mediated intercellular signaling pathway through PD. | Iswanto, Arya Bagus Boedi; Vu, Minh Huy; Shon, Jong Cheol; Kumar, Ritesh; Wu, Shuwei; Kang, Hobin; Kim, Da-Ran; Son, Geon Hui; Kim, Woe Yoen; Kwak, Youn-Sig; Liu, Kwang Hyeon; Kim, Sang Hee; Kim, Jae-Yean | Gyeongsang Natl Univ, Plant Mol Biol & Biotechnol Res Ctr, BK21 FOUR Program, Div Appl Life Sci, Jinju 52828, South Korea; Kyungpook Natl Univ, Coll Pharm, Daegu 702701, South Korea; Kyungpook Natl Univ, Res Inst Pharmaceut Sci, Daegu 702701, South Korea; Gyeongsang Natl Univ, Dept Plant Med, Jinju 52828, South Korea; Gyeongsang Natl Univ, Div Life Sci, Jinju 52828, South Korea; Univ Minnesota, Dept Agron & Plant Genet, St Paul, MN USA | Nguyen, Thanh Hai/HLG-9900-2023 | 57189037439; 57215006315; 56010668800; 56214793100; 56120768100; 57223102398; 56677035200; 54788411300; 7405813205; 26638804500; 55768214700; 57196226259; 37106939800 | sangheekim@gnu.ac.kr;kimjy@gnu.ac.kr; | JOURNAL OF INTEGRATIVE PLANT BIOLOGY | J INTEGR PLANT BIOL | 1672-9072 | 1744-7909 | 66 | 8 | SCIE | BIOCHEMISTRY & MOLECULAR BIOLOGY;PLANT SCIENCES | 2024 | 9.3 | 3.1 | 0 | 2025-05-07 | 0 | 0 | callose; coatomer proteins; membrane-bound vesicle; plasmodesmata; sphingolipid enzymes | ALPHA-COP; ENDOPLASMIC-RETICULUM; CALLOSE SYNTHASE; GOLGI TRANSPORT; COATED VESICLES; PLANT; PROTEINS; RECOGNITION; DISTINCT; BETA-1,3-GLUCANASES | callose; coatomer proteins; membrane-bound vesicle; plasmodesmata; sphingolipid enzymes | Arabidopsis; Arabidopsis Proteins; Glucans; Glucosyltransferases; Plasmodesmata; Sphingolipids; Arabidopsis protein; callose; glucan; glucosyltransferase; sphingolipid; enzyme activity; homeostasis; lipid; membrane; molecular analysis; protein; Arabidopsis; genetics; metabolism; plasmodesma | English | 2024 | 2024-08 | 10.1111/jipb.13711 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |
| ○ | ○ | Article | A novel structural adaptive Caputo fractional order derivative multivariate grey model and its application in China's energy production and consumption prediction | With the deepening of economic globalization and the intensification of global warming, all countries are faced with the challenges of low-carbon transition and continuous growth of energy demand. Therefore, precise forecasting of future energy development patterns is critical for our government to optimize its energy structure. Based on this, by introducing Caputo fractional order derivative, power exponential term, linear correction term, and stochastic perturbation term, a novel structural adaptive nonlinear multivariate grey prediction model constructed using Caputo fractional order derivatives is presented. To increase the adaptability of the model, the Grey Wolf Optimization (GWO) technique is used to optimize the model's adaptive parameters. To evaluate the model's validity, seven current grey prediction models are compared to the CFNGMC(p, n) model using three real-world examples of electricity production, energy processing and conversion efficiency, and energy consumption per capita. Experimental findings suggest that the CFNGMC(p, n) is highly predictive and adaptable. Furthermore, Monte Carlo simulation and probability density analysis are used to evaluate the robustness of the CFNGMC(p, n), further confirming its superiority. It demonstrates that the proposed model is an effective way to anticipate energy data in China. | Wang, Yong; Yang, Zhongsen; Luo, Yongxian; Yang, Rui; Sun, Lang; Sapnken, Flavian Emmanuel; Narayanan, Govindasami | Southwest Petr Univ, Sch Sci, Chengdu 610500, Sichuan, Peoples R China; Univ Douala, Univ Inst Technol, Lab Technol & Appl Sci, POB 8698, Douala, Cameroon; Kyungpook Natl Univ, Sch Elect & Elect Engn, Daegu 41566, South Korea | 55733941200; 57807238600; 57807546500; 58591692200; 58492502000; 57193689653; 59146568100 | ywangsc@qq.com; | ENERGY | ENERGY | 0360-5442 | 1873-6785 | 312 | SCIE | ENERGY & FUELS;THERMODYNAMICS | 2024 | 9.4 | 3.2 | 2.52 | 2025-05-07 | 8 | 9 | Grey model; Caputo fractional order derivatives; Grey wolf optimization; Monte-carlo simulation; Probability density analysis; Energy production and consumption | TENSILE-STRENGTH; BERNOULLI MODEL | Caputo fractional order derivatives; Energy production and consumption; Grey model; Grey Wolf Optimization; Monte-Carlo simulation; Probability density analysis | China; Caputo fractional order derivatives; Energy productions; Energy-consumption; Gray Model; Gray wolf optimization; Gray wolves; Monte Carlo's simulation; Optimisations; Probability densities; Probability density analyze; Production and consumption; electricity generation; electricity industry; globalization; government; probability; simulation; Prediction models | English | 2024 | 2024-12-15 | 10.1016/j.energy.2024.133622 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | A study on 5-cycle fuel economy prediction model of electric vehicles using numerical simulation | This paper is a study on 5-cycle fuel economy prediction model of electric vehicles using numerical simulation. It aims to develop a prediction model for the energy efficiency of electric vehicles and compare it with the results of chassis dynamometer tests. Driving tests were conducted on a chassis dynamometer, which included various test cycles of the 5-cycle test. Using MATLAB Simulink, a vehicle dynamics analysis model for electric vehicles was constructed, and analytical research was conducted focusing on light-duty electric vehicles. By comparing and analyzing the experimental data obtained from the chassis dynamometer with the data calculated through simulation, it is possible to verify the accuracy of the electric vehicle energy efficiency prediction model. And the reliability of the simulation model was secured by comparing the experimental data obtained through chassis dynamometer test with the simulation results of the developed electric vehicle energy efficiency prediction model. There is good agreement between the experimental and simulation results. In most areas, the error rate remains below 3 %, indicating that the simulation model closely follows the experimental results from the chassis dynamometer. Based on these results, it is expected that the developed simulation model can be utilized for measuring the energy efficiency of electric vehicles. | Song, Jingeun; Cha, Junepyo; Choi, Mingi | Kyungpook Natl Univ, Sch Automot Engn, Sangju 37224, South Korea; Korea Natl Univ Transportat, Dept Automot Engn, Chungju 27469, Choongcheongboo, South Korea; Hanyang Cyber Univ, Sch Mech & Automot Engn, Seoul 04763, South Korea | Song, Jingeun/MTG-2604-2025 | 56714139600; 36237962800; 55800531800 | mgchoi@hycu.ac.kr; | ENERGY | ENERGY | 0360-5442 | 1873-6785 | 309 | SCIE | ENERGY & FUELS;THERMODYNAMICS | 2024 | 9.4 | 3.2 | 0 | 2025-05-07 | 0 | 0 | Electric vehicles; 5-Cycle test mode; Fuel economy; Numerical simulation; State of charge | 5-Cycle test mode; Electric vehicles; Fuel economy; Numerical simulation; State of charge | State of charge; 5-cycle test mode; Chassis dynamometer tests; Chassis dynamometers; Cycle tests; Efficiency predictions; Energy; Prediction modelling; Simulation model; States of charges; Vehicle energy; electric vehicle; energy efficiency; model test; numerical method; prediction; simulation; Prediction models | English | 2024 | 2024-11-15 | 10.1016/j.energy.2024.133189 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Advances in nanofluids for tubular heat exchangers: Thermal performance, environmental effects, economics and outlook | Heat transfer deterioration in thermal systems significantly limits the efficiency and practicality of these systems. This review explores state-of-the-art studies on the use of nanofluids (NFs) in various tubular heat exchangers (HEXs), addressing their influence on overcoming the limitations. It discusses the fundamentals of HEXs and NFs, including design criteria, heat transfer mechanisms and thermal transport properties. This work compiles effective thermal conductivity and viscosity correlations under diverse conditions and evaluates NF performance in reactor, flat and helical coiled tube, twisted tube, U-tube and finned tube-based HEXs. Results revealed substantial improvements in system efficiency, with SiC-MWCNT/water NFs achieving 99.9 % absorbance in solar collectors and Ag-rGO/water and Ag-ZnO/silicon oil NFs enhancing efficiency by 210 % and 240 %, respectively. Water-alumina NFs increased convective heat transfer rates and friction factors in flat tube HEXs by 123.6 % and 210 %, respectively. Helical coil exchangers exhibited a pressure drop of 47.35 % with MWCNT/ water NFs and a 69.62 % rise in heat transfer coefficient with polyaniline-water NFs. This review suggests that optimising HEX efficiency depends on the strategic use of NFs and finned-tube designs. It also highlights the significance of selecting suitable source materials for NFs, the corresponding health risks, disposal and waste management. Economic viability depends on using optimal flow parameters, including temperature, concentration of nanoparticles, system compactness and installation and running costs. Finally, this review concludes with insights into existing challenges and prospects in thermohydraulic, environmental and economic aspects, pointing to future developments in engineered fluids and their commercial applications. | Rehman, Tauseef-ur; Park, Cheol Woo | Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea | Rehman, Tauseef-ur/AAE-3086-2022 | 57159403400; 7408416474 | metauseef16@gmail.com;chwoopark@knu.ac.kr; | ENERGY | ENERGY | 0360-5442 | 1873-6785 | 308 | SCIE | ENERGY & FUELS;THERMODYNAMICS | 2024 | 9.4 | 3.2 | 1.26 | 2025-05-07 | 5 | 7 | Heat transfer coefficient; Heat transfer enhancement; Nanofluids; Pressure drop; Environmental effect; Cost analysis | TUBE SOLAR COLLECTOR; HYBRID NANO-ADDITIVES; TRANSFER ENHANCEMENT; ETHYLENE-GLYCOL; CAR RADIATOR; RHEOLOGICAL BEHAVIOR; DYNAMIC VISCOSITY; MAGNETIC-FIELD; PRESSURE-DROP; PARTICLE-SIZE | Cost analysis; Environmental effect; Heat transfer coefficient; Heat transfer enhancement; Nanofluids; Pressure drop | Health risks; Waste disposal; Cost analysis; Finned tube; Heat transfer co-efficients; Heat transfer deterioration; Heat Transfer enhancement; MWCNT's; Nanofluids; Thermal Performance; Tubular heat exchangers; Water nanofluids; cost analysis; environmental economics; environmental effect; heat transfer; nanoparticle; performance assessment; pressure drop; thermal conductivity; thermal power | English | 2024 | 2024-11-01 | 10.1016/j.energy.2024.132732 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Analysis of fuel economy reduction factors of hybrid electric vehicles in winter using on-road driving data | The reduction in driving range during winter is one of the major disadvantages of battery electric vehicles and hybrid electric vehicles. On-road driving tests showed that the fuel efficiency was 23.1 km/L at an ambient temperature of 20 degrees C, but it dropped to 20 km/L at 0 degrees C under the same driving conditions. Therefore, this study analyzed the effect of road load and battery internal resistance on fuel economy reduction during winter. The road load and battery internal resistance for various temperatures were extracted from on-road driving data using intuitive and simple methods. The results showed that the road load was the major factor that reduced the fuel economy of hybrid electric vehicles in winter, whereas the effect of battery internal resistance on fuel economy reduction was negligible. As the ambient temperature decreased from 20 degrees C to 0 degrees C, the energy loss due to road load increased by 2.1 kWh, while the energy loss due to battery internal resistance only increased by 0.0345 kWh. Although this study focused on hybrid vehicles, the methodology used can also be applied to battery electric vehicles. | Choi, Mingi; Cha, Junepyo; Song, Jingeun | Hanyang Cyber Univ, Sch Mech & Automot Engn, Seoul 04763, South Korea; Korea Natl Univ Transportat, Dept Automot Engn, Chungju 27469, South Korea; Kyungpook Natl Univ, Sch Automot Engn, Sangju 37224, South Korea | ; Song, Jingeun/MTG-2604-2025 | 55800531800; 36237962800; 56714139600 | mgchoi@hycu.ac.kr;chaj@ut.ac.kr;sjg@knu.ac.kr; | ENERGY | ENERGY | 0360-5442 | 1873-6785 | 289 | SCIE | ENERGY & FUELS;THERMODYNAMICS | 2024 | 9.4 | 3.2 | 2.2 | 2025-05-07 | 6 | 7 | Fuel economy; On -road driving test; Road load; Battery internal resistance; Energy efficiency; Energy loss | CO2 EMISSIONS; TEMPERATURE | Battery internal resistance; Energy efficiency; Energy loss; Fuel economy; On-road driving test; Road load | Electric losses; Energy efficiency; Hybrid vehicles; Roads and streets; Secondary batteries; % reductions; Battery internal resistance; Battery-electric vehicles; Driving range; Driving test; Internal resistance; On-road driving; On-road driving test; Reduction factor; Road loads; alternative energy; electric vehicle; energy efficiency; fuel consumption; hybrid; road; winter; Fuel economy | English | 2024 | 2024-02-15 | 10.1016/j.energy.2023.129977 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Comprehensive analysis of waste heat recovery and thermal energy storage integration in air conditioning systems | The proposed work aims to address the challenge of effectively recovering and storing wasted heat in air conditioning (AC) systems, which is crucial for improving energy efficiency and system stability. This study focuses on the comprehensive analysis of a Waste Heat Recovery (WHR) system integrated with Thermal Energy Storage (TES) tanks. A lumped-dynamic thermal model was developed and validated against literature data to accurately simulate the system's performance. Through a detailed parametric study, the research explores how factors like WHR effectiveness, TES type, PCM type, and TES volume influence the system. The results demonstrate that recovering and storing wasted heat from AC systems significantly enhances operational stability and performance. Notably, increasing WHR effectiveness from 0.55 to 0.85 extends the duration of constant thermal power recovery and also results in higher recovered water temperatures with reduced water pump energy consumption. Furthermore, latent heat storage (PCM tank) extends the duration of stable thermal power recovery by over 61 % compared to sensible storage. Using PCM RT 44HC is more effective for WHR in AC units compared to RT 50 and RT 54HC. Finally, it was shown that increasing PCM tank volume from 2 to 4 m3 improves the duration of constant thermal power recovery by up to 52 % while stabilizing the recovered water temperature. | Lamrani, Bilal; El Marbet, Safae; Rehman, Tauseef-ur; Kousksou, Tarik | Univ Mohammed V Rabat, Fac Sci, Lab MANAPSE, BP 1014 RP, Rabat, Morocco; Univ Pau & Pays Adour, SIAME, E2S, Pau, France; Kyungpook Natl Univ, Sch Mech Engn, Daegu 41566, South Korea | LAMRANI, Bilal/IQS-2711-2023; Rehman, Tauseef-ur/AAE-3086-2022 | 57203242590; 59166958800; 57159403400; 12759352100 | b.lamrani@um5r.ac.ma;tarik.kousksou@univ-pau.fr; | ENERGY CONVERSION AND MANAGEMENT-X | ENERG CONVERS MAN-X | 2590-1745 | 24 | ESCI | ENERGY & FUELS;MECHANICS;THERMODYNAMICS | 2024 | 7.6 | 3.2 | 1.18 | 2025-05-07 | 6 | 7 | Waste heat recovery; Hot water production; Air conditioning; PCM; Thermal energy storage; Dynamic modeling | REFRIGERATION | Air conditioning; Dynamic modeling; Hot water production; PCM; Thermal energy storage; Waste heat recovery | Air conditioning; Hot water distribution systems; Waste heat utilization; Comprehensive analysis; Conditioning systems; Dynamics models; Energy; Hot-water production; Power recovery; Thermal energy storage; Thermal power; Waste-heat recovery; Water temperatures; Latent heat | English | 2024 | 2024-10 | 10.1016/j.ecmx.2024.100708 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Design of high-performance binary carbonate/hydroxide Ni-based supercapacitors for photo-storage systems | Silicon solar cells were used to convert solar energy into electrical energy, and a supercapacitor was designed to store this energy. To maximize the surface area of the electrodes, a three-dimensional Ni foam substrate was employed, onto which Ni-based compounds were deposited to enhance the electrochemical performance of the electrodes. Specifically, to address the conductivity reduction problem that arises when using only Ni ions, we introduced transition metal ions such as Mn, Co, Cu, Fe, and Zn to create binary compounds as electrode material. These binary metal compounds provided high electronic conductivity, structural stability, and reversible capacity, thereby optimizing the performance of the supercapacitor. As a result, the optimized NiCo(CO3)(OH)2 electrode demonstrated high capacity and excellent cycle stability, exhibiting an energy density of 35.5 Wh kg-1 and a power density of 2555.6 W kg-1 as an asymmetric supercapacitor device. Furthermore, when this device was combined directly with silicon solar cells, it achieved a storage efficiency of 63 % and an overall efficiency of 5.17 % under an illumination intensity of 10 mW cm-2. These findings suggest the potential for commercializing high-performance self-charging energy storage devices and contribute significantly to the advancement of energy storage technology. | Lee, Damin; Keppetipola, Nilanka M.; Kim, Dong Hwan; Roh, Jong Wook; Cojocaru, Ludmila; Toupance, Thierry; Kim, Jeongmin | Div Nanotechnol, DGIST, 333 Techno Jungang daero, Daegu 42988, South Korea; Kyungpook Natl Univ, Reg Leading Res Ctr Smart Energy Syst, Daegu 41566, South Korea; Univ Bordeaux, CNRS, Bordeaux INP, ISM,Grp Chim Mol & Mat C2M, 351 Cours Liberat, F-33405 Talence, France; Coll France, Chim Solide & Energie CSE, UMR 8260, F-75231 Paris, France; Komaba Inst Sci KIS, Grad Sch Arts & Sci, Komaba 4-6-1, Tokyo 1538904, Japan | ; TOUPANCE, Thierry/O-3368-2018; Cojocaru, Ludmila/HKV-3402-2023 | 57194601076; 57221673990; 57195540717; 25638796100; 36500685000; 6701783693; 57203325094 | damin91@knu.ac.kr;jkim@dgist.ac.kr; | ENERGY | ENERGY | 0360-5442 | 1873-6785 | 313 | SCIE | ENERGY & FUELS;THERMODYNAMICS | 2024 | 9.4 | 3.2 | 1.26 | 2025-05-07 | 4 | 4 | Binary-transition metal; Carbonate hydroxide; Hydrothermal method; Faradaic capacitors; Supercapacitors; Photo-storage | LAYERED DOUBLE HYDROXIDES; TEMPLATE-FREE SYNTHESIS; ELECTRODE MATERIALS; CUCO2O4 NANOSHEETS; 3D GRAPHENE; CO3O4; NANOPARTICLES; NANOFLAKES; SPHERES; SHELL | Binary-transition metal; Carbonate hydroxide; Faradaic capacitors; Hydrothermal method; Photo-storage; Supercapacitors | Cobalt compounds; Iron compounds; Manganese compounds; Nickel compounds; Binary-transition metal; Carbonate hydroxide; Cell-be; Cell/B.E; Energy; Faradaic capacitor; Hydrothermal methods; Performance; Photo-storage; Storage systems; carbonate; electrical conductivity; electrode; energy storage; silicon; substrate; surface area; transition element; Capacitor storage | English | 2024 | 2024-12-30 | 10.1016/j.energy.2024.133593 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||
| ○ | ○ | Article | Effect of direct-acting antivirals on disease burden of hepatitis C virus infection in South Korea in 2007-2021: a nationwide, multicentre, retrospective cohort study | Background It is unclear whether direct-acting antivirals (DAAs) treatment improves the disease burden in hepatitis C virus (HCV) infection. This study aimed to investigate the effect of DAA treatment on the reduction of disease burden in patients with HCV infection using individual participant data. Methods This nationwide multicentre retrospective cohort study recruited patients with HCV infection from 29 tertiary institutions in South Korea. The data collection was done from medical records in each institution. The study included the untreated patients and the DAAs-treated patients and excluded those with a history of interferon -based treatments. Disease burden was the primary outcome, as represented by disability -adjusted life years (DALYs). Improvement in fi brosis after DAA treatment was assessed using APRI, FIB -4 index, and liver stiffness (LS) as assessed by transient elastography. Clinical outcomes were hepatocellular carcinoma (HCC), decompensation, and mortality. Findings Between January 1, 2007, and February 17, 2022, data from 11,725 patients with HCV infection, 8464 (72%) of whom were treated with DAAs, were analysed. DAA treatment signi fi cantly improved APRI- (median 0.64 [interquartile range (IQR), 0.35 - 1.31] - 0.33 [0.23 - 0.52], p < 0.0001), FIB -4(median 2.42 [IQR, 1.48 - 4.40] - 1.93 [1.31 - 2.97], p < 0.0001), and liver LS -based fi brosis (median 7.4 [IQR, 5.3 - 12.3] - 6.2 [4.6 - 10.2] kPa, p < 0.0001). During the median follow-up period of 27.5 months (IQR, 10.6 - 52.4), 469 patients died (4.0%), 586 (5.0%) developed HCC, and 580 (4.9%) developed decompensation. The APRI-based DALY estimate was signi fi cantly lower in the DAA group than in the untreated group (median 4.55 vs. 5.14 years, p < 0.0001), as was the FIB -4based DALY estimate (median 5.43 [IQR, 3.00 - 6.44] vs. 5.79 [3.85 - 8.07] years, p < 0.0001). The differences between the untreated and DAA groups were greatest in patients aged 40 - 60 years. In multivariable analyses, the DAA group had a signi fi cantly reduced risk of HCC, decompensation, and mortality compared with the untreated group (hazard ratios: 0.41 [95% con fi dence interval (CI), 0.34 - 0.48], 0.31 [95% CI, 0.30 - 0.38], and 0.22 [95% CI, 0.17 - 0.27], respectively; p < 0.0001). Interpretation Our fi ndings suggest that DAA treatment is associated with the improvement of liver -related outcomes and a reduction of liver fi brosis -based disease burden in patients with HCV infection. However, further studies using liver biopsy are needed to clarify the effect of DAA treatment on the reduction in the exact fi brosis -based disease burden beyond noninvasive tests. | Sohn, Won; Park, Soo Young; Lee, Tae Hee; Chon, Young Eun; Kim, In Hee; Lee, Byung-Seok; Yoon, Ki Tae; Jang, Jae Young; Lee, Yu Rim; Yu, Su Jong; Choi, Won-Mook; Kim, Sang Gyune; Jun, Dae Won; Jeong, Joonho; Kim, Ji Hoon; Jang, Eun Sun; Kim, Hwi Young; Cho, Sung Bum; Jang, Byoung Kuk; Park, Jung Gil; Lee, Jin-Woo; Seo, Yeon Seok; Lee, Jung Il; Song, Do Seon; Kim, Moon Young; Yim, Hyung Joon; Sinn, Dong Hyun; Ahn, Sang Hoon; Kim, Young Seok; Jang, Heejoon; Kim, Won; Han, Seungbong; Kim, Seung Up | Sungkyunkwan Univ, Kangbuk Samsung Hosp, Seoul, South Korea; Kyungpook Natl Univ, Kyungpook Natl Univ Hosp, Daegu, South Korea; Konyang Univ, Coll Med, Daejeon, South Korea; CHA Univ, CHA Bundang Med Ctr, Seongnam, South Korea; Chonbuk Natl Univ, Chonbuk Natl Univ Hosp, Med Sch, Jeonju, South Korea; Chungnam Natl Univ, Chungnam Natl Univ Hosp, Sch Med, Daejeon, South Korea; Pusan Natl Univ, Yangsan Hosp, Coll Med, Yangsan, South Korea; Soonchunhyang Univ, Inst Digest Res, Coll Med, Digest Dis Ctr, Seoul, South Korea; Kyungpook Natl Univ, Chilgok Hosp, Daegu, South Korea; Seoul Natl Univ, Liver Res Inst, Coll Med, Seoul, South Korea; Univ Ulsan, Coll Med, Liver Ctr, Asan Med Ctr, Seoul, South Korea; Soonchunhyang Univ, Hosp Bucheon, Coll Med, Bucheon, South Korea; Hanyang Univ, Hanyang Univ Hosp, Coll Med, Seoul, South Korea; Ulsan Univ, Ulsan Univ Hosp, Coll Med, Ulsan, South Korea; Korea Univ, Guro Hosp, Coll Med, Seoul, South Korea; Seoul Natl Univ, Bundang Hosp, Coll Med, Seongnam, South Korea; Ewha Womans Univ, Coll Med, Seoul, South Korea; Chonnam Natl Univ, Chonnam Natl Univ Hosp, Hwasun, South Korea; Keimyung Univ, Sch Med, Daegu, South Korea; Yeungnam Univ, Coll Med, Daegu, South Korea; Inha Univ, Inha Univ Hosp, Sch Med, Incheon, South Korea; Korea Univ, Anam Hosp, Coll Med, Seoul, South Korea; Yonsei Univ, Gangnam Severance Hosp, Coll Med, Seoul, South Korea; Catholic Univ Korea, St Vincents Hosp, Coll Med, Suwon, South Korea; Yonsei Univ, Wonju Coll Med, Wonju, South Korea; Korea Univ, Ansan Hosp, Coll Med, Ansan, South Korea; Sungkyunkwan Univ, Samsung Med Ctr, Sch Med, Seoul, South Korea; Yonsei Univ, Coll Med, Seoul, South Korea; Severance Hosp, Yonsei Liver Ctr, Seoul, South Korea; Seoul Natl Univ, Coll Med, Boramae Med Ctr, Seoul Metropolitan Govt, Seoul, South Korea; Korea Univ, Coll Med, Dept Biostat, Seoul, South Korea; Seoul Natl Univ, Coll Med, Boramae Med Ctr, Dept Internal Med,Seoul Metropolitan Govt, 20 Boramae Ro 5 Gil, Seoul 07061, South Korea; Korea Univ, Coll Med, Dept Biostat, 73 Goryeodae Ro, Seoul 02841, South Korea; Yonsei Univ, Coll Med, Dept Internal Med, 50-1 Yonsei Ro, Seoul 03722, South Korea | Choi, Won-Mook/ABE-2662-2021; Lee, Jeong-Hoon/Q-1055-2018; Jun, Dae Won/O-4529-2017; Ahn, Sang Hoon/AFM-2603-2022; Kim, Jung/L-9791-2019; LEE, JIN/Q-3108-2018; Kim, Ju/AAV-3029-2020; Jeong, Joonho/NIV-1254-2025; Kim, Sun/L-4239-2013; Kim, Sang/AAI-5704-2020; Kim, Joo/X-7562-2019; Kim, Won/H-6940-2019; Sinn, Dong/JAC-4247-2023 | 55998889800; 57191674344; 58567822800; 36089768300; 7404143744; 57203247116; 14820137300; 57221679776; 57194094753; 7405730251; 57203486081; 35278042500; 57226004346; 57217121454; 57328819200; 35102352800; 56493773500; 57216641631; 58849853600; 57216816399; 57216961138; 35234912400; 57856405800; 57217514699; 55545239100; 7005664934; 23493891100; 7401989551; 57207444475; 57197796643; 57049716700; 54885771000; 54933821200 | drwon1@snu.ac.kr;hanseungbong@gmail.com;ksukorea@yuhs.ac; | ECLINICALMEDICINE | ECLINICALMEDICINE | 2589-5370 | 73 | SCIE | MEDICINE, GENERAL & INTERNAL | 2024 | 10 | 3.2 | 3.35 | 2025-05-07 | 5 | 6 | Hepatitis C virus; Direct-acting antiviral; Disease burden; Liver fi brosis | SIMPLE NONINVASIVE INDEX; SIGNIFICANT FIBROSIS; LIVER FIBROSIS; ELASTOGRAPHY; PREDICT | Direct-acting antiviral; Disease burden; Hepatitis C virus; Liver fibrosis | antivirus agent; asunaprevir; daclatasvir; dasabuvir; elbasvir plus grazoprevir; glecaprevir plus pibrentasvir; ledipasvir plus sofosbuvir; ombitasvir; paritaprevir; pibrentasvir; ribavirin; ritonavir; sofosbuvir; alcohol consumption; antiviral activity; Article; bacterial peritonitis; cause of death; cohort analysis; computer assisted tomography; diabetes mellitus; disease burden; disease duration; echography; elastography; female; genotype; hepatectomy; hepatic encephalopathy; hepatitis C; hepatorenal syndrome; hypertension; inflammation; life expectancy; liquid chromatography-mass spectrometry; liver biopsy; liver cell carcinoma; liver cirrhosis; liver fibrosis; liver parenchyma; liver stiffness; liver transplantation; male; medical record; mortality; multicenter study; nuclear magnetic resonance imaging; outcome assessment; prevalence; quality of life; retrospective study; risk assessment; risk factor; sensitivity analysis; South Korea; survival time; sustained virologic response; transient elastography; virus infection | English | 2024 | 2024-07 | 10.1016/j.eclinm.2024.102671 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | Emerging detection of carbon-based gases with multiple bonds by activating Mo=O bonding in Na, Sb-codoped NiMoO4 | Exhausting carbon-based gases from building construction or comfortable household supplies have caused the main pollution gas species for the indoor air environment. Given the variety of indoor activities, many reports have been challenged to find room-temperature operational and harmless materials. Here, we report that the activating Mo--O vibration mode in Na,Sb doped-NiMoO4 micro-sized powder reveals the high response of CO and VOC, occupying multiple bonds at room temperature. We performed Na and Sb doping in the alpha-NiMoO4 crystal structure, such as introducing the Sb in Ni and interstitial doping of Na in around 4 & Aring; of free space in the NiMoO4 crystal structure that manipulates the partial beta-NiMoO4 phase. The Na,Sb-codoped NiMoO4 generates the higher Mo--O vibration mode from FT-IR measurement and enables carbon-based gas detection with 38 responses to CO and nearly 20 responses to VOC under 20 ppm of each analyte gases environment. Furthermore, the n-type gas sensing behavior of Na,Sb doped-NiMoO4 chemiresistor exhibits an immediate sensing response instead of a none-of response than intrinsic or single element doped NiMoO4. These results suggest that Na,Sb codoped-NiMoO4 is the applicable material for emergent warning against carbon-based gas exposure in the indoor environment. In addition, activating the electrochemical reaction site of MoO4-2 in NiMoO4 is tailorable by a simple doping process. | Jeong, Si Hoon; Han, Gi Hyeon; Park, Gi Hyun; Jin, Changhyun; Hwang, Jeong Yun; Choi, Myung Sik; Kang, Se Hwang; Baik, Joon Hyun; Lee, Kyu Hyoung; Lee, Seung Yong | Yonsei Univ, Dept Mat Sci & Engn, Seoul 03722, South Korea; Kyungpook Natl Univ, Dept Nano & Adv Mat Sci & Engn, Sangju 37224, South Korea; Inst Adv Engn, Mat Sci & Chem Engn Ctr Ind Convergence Engn Grp, Suwon 17180, Gyeonggi Do, South Korea; Sookmyung Womens Univ, Dept Chem & Biol Engn, Seoul 04310, South Korea | Baik, Joon/C-3053-2008; Choi, Myung-Sik/J-5687-2012; Jin, Changhyun/P-9398-2015 | 58626837500; 57210563813; 58626805000; 35177895100; 57215200308; 57190737942; 59281689100; 7006635146; 35205856800; 57436380000 | khlee2018@yonsei.ac.kr;lsy549@yonsei.ac.kr; | SENSORS AND ACTUATORS REPORTS | SENSOR ACTUATOR REP | 2666-0539 | 8 | ESCI | CHEMISTRY, ANALYTICAL;ELECTROCHEMISTRY;INSTRUMENTS & INSTRUMENTATION;NANOSCIENCE & NANOTECHNOLOGY;BIOTECHNOLOGY & APPLIED MICROBIOLOGY | 2024 | 7.6 | 3.2 | 0 | 2025-05-07 | 0 | 0 | Gas sensor; VOC; Carbon monoxide | METAL-OXIDE NANOSTRUCTURES; TEMPERATURE; SENSORS; VOCS | Carbon monoxide; Gas sensor; NiMoO<sub>4</sub>; VOC | Chemical activation; Chemical sensors; Crystal structure; Doping (additives); Gas adsorption; Gas detectors; Gas sensing electrodes; Gases; Infrared imaging; Molybdenum compounds; Nickel compounds; Sodium; Sodium compounds; Building construction; Carbon-based; Co-doped; Crystals structures; Gas species; Gas-sensors; Household supplies; Multiple bonds; Sb-doped; Vibration modes; Carbon monoxide | English | 2024 | 2024-12 | 10.1016/j.snr.2024.100219 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | |||
| ○ | ○ | Article | H2S gas sensing enhancement of Au-decorated SnO2 nanospheres synthesized using hydrothermal and microwave methods | In this study, non-oriented Au-decorated SnO2 nanospheres (NSs) were synthesized using hydrothermal and microwave methods. The SnO2 spheres ranged from hundreds of nanometers to a microscale. The oxygen vacancy on the surface increased after Au adsorption on the surface of the SnO2 NSs, ultimately showing a synergistic effect with the spillover effect of the existing Au catalyst. Specifically, at 100 degrees C and 200 degrees C, the response to 10 ppm H2S gas improved to 16.14 and 46.81, respectively. These gas sensing effects were approached individually by being divided into two disadvantages (oxygen adsorption and homojunction) and five advantages (oxygen vacancies, spill-over, surface area, H2S + SnO2 reaction, and H2S + O-2 reaction). Based on this reference, we investigated SnO2 NSs of various sizes and functions by adjusting the process variables. | Shin, Jiyeon; Hwang, Jeong Yun; Kim, Changyu; Park, Jimyeong; Roh, Jong Wook; Choi, Sun-Woo; Jin, Changhyun; Choi, Myung Sik | Kyungpook Natl Univ, Sch Adv Sci & Technol Convergence, Sangju 37224, South Korea; Yonsei Univ, Dept Mat Sci & Engn, Seoul 03722, South Korea; Kyungpook Natl Univ, Dept Nano & Adv Mat Sci & Engn, Sangju 37224, South Korea; Kangwon Natl Univ, Dept Mat Sci & Engn, Samcheok 25912, South Korea | Choi, Myung-Sik/J-5687-2012 | 57994575600; 57215200308; 59125659400; 59125311500; 25638796100; 35106725800; 35177895100; 57190737942 | csw0427@kangwon.ac.kr;z8015026@yonsei.ac.kr;ms.choi@knu.ac.kr; | SENSORS AND ACTUATORS REPORTS | SENSOR ACTUATOR REP | 2666-0539 | 8 | ESCI | CHEMISTRY, ANALYTICAL;ELECTROCHEMISTRY;INSTRUMENTS & INSTRUMENTATION;NANOSCIENCE & NANOTECHNOLOGY;BIOTECHNOLOGY & APPLIED MICROBIOLOGY | 2024 | 7.6 | 3.2 | 0.45 | 2025-05-07 | 1 | 1 | Au; Catalyst; H2S; Gas sensor; SnO2 nanosphere | Au; Catalyst; Gas sensor; H<sub>2</sub>S; SnO<sub>2</sub> nanosphere | Gas sensing electrodes; Hydrothermal synthesis; Microwave sensors; Nanoclay; Nanospheres; Au; Gas sensing; Gas-sensors; H 2S; Hydrothermal methods; Microwave methods; SnO 2; SnO2 nanosphere; Synthesised; ]+ catalyst; Chemical sensors | English | 2024 | 2024-12 | 10.1016/j.snr.2024.100246 | 바로가기 | 바로가기 | 바로가기 | 바로가기 | ||||
| ○ | ○ | Article | Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis | A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identification of transglutaminase 2 (TGM2), a recognized biomarker for chronic kidney disease (CKD), in urine specimens, which offers a remarkably sensitive naked-eye detection mechanism. The surface of MIL-101(Fe) was modified with oxalyl chloride, adipoyl chloride, and poly(acrylic) acid (PAA); these not only improved the labeling material stability in a complex matrix but also achieved a systematic control in the detection limit of the TGM2 concentration using our LFA platform. The advanced LFA with the MIL-101(Fe)-PAA label can detect TGM2 concentrations down to 0.012, 0.009, and 0.010 nM in Tris-HCl buffer, urine, and desalted urine, respectively, which are approximately 55-fold lower than those for a conventional AuNP-based LFAs. Aside from rapid TGM2 detection (i.e., within 20 min), the performance of the MIL-101(Fe)-PAA-based LFA on reproducibility [coefficients of variation (CV) < 2.9%] and recovery (95.9-103.2%) along with storage stability within 25 days of observation (CV < 6.0%) shows an acceptable parameter range for quantitative analysis. A sophisticated sensing method grounded in machine learning principles was also developed, specifically aimed at precisely deducing the TGM2 concentration by analyzing immunoreaction sites. More importantly, our developed LFA offers potential for clinical measurement of TGM2 concentration in normal human urine and CKD patients' samples. | Supianto, Mulya; Yoo, Dong Kyu; Hwang, Hagyeong; Oh, Han Bin; Jhung, Sung Hwa; Lee, Hye Jin | Kyungpook Natl Univ, Dept Chem, Daegu 41566, South Korea; Kyungpook Natl Univ, Green Nano Mat Res Ctr, Daegu 41566, South Korea; Sogang Univ, Dept Chem, Seoul 04107, South Korea | ; LEE, HYEJIN/W-1345-2018; Jhung, Sung/AAO-6683-2021; Bin Oh, Han/B-5390-2011; Supianto, Mulya/KIH-9760-2024; Oh, Han Bin/B-5390-2011 | 57304127400; 57201339246; 58937529300; 7402326081; 6701659467; 56569175200 | hyejinlee@knu.ac.kr; | ACS SENSORS | ACS SENSORS | 2379-3694 | 9 | 3 | SCIE | CHEMISTRY, ANALYTICAL;CHEMISTRY, MULTIDISCIPLINARY;NANOSCIENCE & NANOTECHNOLOGY | 2024 | 9.1 | 3.2 | 2.78 | 2025-05-07 | 9 | 10 | lateral flow assay; metal-organic framework; transglutaminase 2; urine sample; naked-eyedetection; machine learning | CHRONIC KIDNEY-DISEASE; TISSUE TRANSGLUTAMINASE; IMMUNOASSAY; NANOCATALYST; STANDARD; POINT | lateral flow assay; machine learning; metal−organic framework; naked-eye detection; transglutaminase 2; urine sample | Colorimetry; Humans; Iron; Metal-Organic Frameworks; Protein Glutamine gamma Glutamyltransferase 2; Renal Insufficiency, Chronic; Reproducibility of Results; Chlorine compounds; Color; Colorimetry; Eye protection; Iron; Iron compounds; Metal-Organic Frameworks; iron; metal organic framework; MIL-101; protein glutamine gamma glutamyltransferase 2; Chronic kidney disease; Coefficients of variations; Detection mechanism; Iron metal; Lateral-flow assays; Machine-learning; Metalorganic frameworks (MOFs); Naked-eye detection; Transglutaminase 2; Urine sample; chronic kidney failure; colorimetry; human; procedures; reproducibility; Machine learning | English | 2024 | 2024-03-12 | 10.1021/acssensors.3c02250 | 바로가기 | 바로가기 | 바로가기 | 바로가기 |
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