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Article ; Online: Precise Measurement of the D_{s}^{+} Lifetime at Belle II.

Adachi, I / Aggarwal, L / Aihara, H / Akopov, N / Aloisio, A / Anh Ky, N / Asner, D M / Atmacan, H / Aushev, T / Aushev, V / Aversano, M / Babu, V / Bae, H / Bahinipati, S / Bambade, P / Banerjee, Sw / Barrett, M / Baudot, J / Bauer, M /

Baur, A / Beaubien, A / Becker, J / Behera, P K / Bennett, J V / Bernlochner, F U / Bertacchi, V / Bertemes, M / Bertholet, E / Bessner, M / Bettarini, S / Bhuyan, B / Bianchi, F / Bilka, T / Biswas, D / Bodrov, D / Bondar, A / Bozek, A / Bračko, M / Branchini, P / Briere, R A / Browder, T E / Budano, A / Bussino, S / Campajola, M / Cao, L / Casarosa, G / Cecchi, C / Cerasoli, J / Chang, M-C / Chang, P / Cheema, P / Chekelian, V / Cheon, B G / Chilikin, K / Chirapatpimol, K / Cho, H-E / Cho, K / Choi, S-K / Choudhury, S / Cochran, J / Corona, L / Das, S / Dattola, F / De La Motte, S A / de Marino, G / De Nardo, G / De Nuccio, M / De Pietro, G / de Sangro, R / Destefanis, M / Dey, S / Dhamija, R / Di Canto, A / Di Capua, F / Dingfelder, J / Doležal, Z / Domínguez Jiménez, I / Dong, T V / Dorigo, M / Dort, K / Dreyer, S / Dubey, S / Dujany, G / Ecker, P / Epifanov, D / Feichtinger, P / Ferlewicz, D / Finck, C / Finocchiaro, G / Fodor, A / Forti, F / Frey, A / Fulsom, B G / Gabrielli, A / Ganiev, E / Garcia-Hernandez, M / Garmash, A / Gaudino, G / Gaur, V / Gaz, A / Gellrich, A / Ghevondyan, G / Ghosh, D / Ghumaryan, H / Giakoustidis, G / Giordano, R / Giri, A / Glazov, A / Gobbo, B / Godang, R / Gogota, O / Goldenzweig, P / Gradl, W / Graziani, E / Greenwald, D / Gruberová, Z / Gu, T / Guan, Y / Gudkova, K / Han, Y / Hayasaka, K / Hayashii, H / Hazra, S / Hearty, C / Heredia de la Cruz, I / Hershenhorn, A / Higuchi, T / Hill, E C / Hoek, M / Hohmann, M / Hsu, C-L / Humair, T / Iijima, T / Inami, K / Ipsita, N / Ishikawa, A / Ito, S / Itoh, R / Iwasaki, M / Jackson, P / Jacobs, W W / Jaffe, D E / Jang, E-J / Ji, Q P / Jia, S / Jin, Y / Junkerkalefeld, H / Kaliyar, A B / Kandra, J / Karyan, G / Kawasaki, T / Keil, F / Ketter, C / Kiesling, C / Kim, C-H / Kim, D Y / Kim, K-H / Kim, Y-K / Kindo, H / Kinoshita, K / Kodyš, P / Koga, T / Kohani, S / Kojima, K / Korobov, A / Korpar, S / Kowalewski, R / Kraetzschmar, T M G / Križan, P / Krokovny, P / Kuhr, T / Kumar, J / Kumar, M / Kumar, R / Kumara, K / Kuzmin, A / Kwon, Y-J / Lacaprara, S / Lai, Y-T / Lam, T / Lange, J S / Laurenza, M / Leboucher, R / Le Diberder, F R / Leitl, P / Levit, D / Lewis, P M / Li, L K / Libby, J / Liu, Q Y / Liu, Z Q / Liventsev, D / Longo, S / Lueck, T / Lyu, C / Ma, Y / Maggiora, M / Maharana, S P / Maiti, R / Maity, S / Manfredi, R / Manoni, E / Mantovano, M / Marcantonio, D / Marcello, S / Marinas, C / Martellini, C / Martini, A / Martinov, T / Massaccesi, L / Masuda, M / Matsuda, T / Matsuoka, K / Matvienko, D / Maurya, S K / McKenna, J A / Mehta, R / Meier, F / Merola, M / Metzner, F / Milesi, M / Miller, C / Mirra, M / Miyabayashi, K / Mohanty, G B / Molina-Gonzalez, N / Mondal, S / Moneta, S / Moser, H-G / Mrvar, M / Mussa, R / Nakamura, I / Nakazawa, Y / Narimani Charan, A / Naruki, M / Natkaniec, Z / Natochii, A / Nayak, L / Nazaryan, G / Nisar, N K / Nishida, S / Ono, H / Otani, F / Oxford, E R / Pakhlov, P / Pakhlova, G / Paladino, A / Panta, A / Paoloni, E / Pardi, S / Passeri, A / Patra, S / Paul, S / Pedlar, T K / Peruzzi, I / Peschke, R / Pestotnik, R / Pham, F / Piccolo, M / Piilonen, L E / Podobnik, T / Pokharel, S / Praz, C / Prell, S / Prencipe, E / Prim, M T / Purwar, H / Rados, P / Raeuber, G / Raiz, S / Reif, M / Reiter, S / Remnev, M / Ripp-Baudot, I / Rizzo, G / Roney, J M / Rostomyan, A / Rout, N / Russo, G / Sandilya, S / Sangal, A / Santelj, L / Sato, Y / Savinov, V / Scavino, B / Schmitt, C / Schwanda, C / Schwartz, A J / Seino, Y / Selce, A / Senyo, K / Serrano, J / Sevior, M E / Sfienti, C / Shan, W / Shi, X D / Shillington, T / Shiu, J-G / Shtol, D / Sibidanov, A / Simon, F / Sobie, R J / Sobotzik, M / Soffer, A / Sokolov, A / Solovieva, E / Spataro, S / Spruck, B / Starič, M / Stavroulakis, P / Stottler, Z S / Stroili, R / Sumihama, M / Svidras, H / Takahashi, M / Takizawa, M / Tamponi, U / Tanida, K / Tenchini, F / Tittel, O / Tonelli, D / Torassa, E / Trabelsi, K / Tsaklidis, I / Unger, K / Unno, Y / Uno, K / Uno, S / Urquijo, P / Ushiroda, Y / Vahsen, S E / van Tonder, R / Varvell, K E / Veronesi, M / Vismaya, V S / Vitale, L / Volpe, R / Wach, B / Wallner, S / Wang, E / Wang, M-Z / Wang, X L / Wang, Z / Warburton, A / Watanabe, M / Wessel, C / Won, E / Xu, X P / Yabsley, B D / Yamada, S / Yan, W / Yang, S B / Yoshihara, K / Yuan, C Z / Yusa, Y / Zhang, Y / Zhilich, V / Zhou, J S / Zhou, Q D / Zhukova, V I / Žlebčík, R

Physical review letters

2023 Volume 131, Issue 17, Page(s) 171803

Abstract: We measure the lifetime of the D_{s}^{+} meson using a data sample of 207 fb^{-1} collected ... determined by fitting the decay-time distribution of a sample of 116×10^{3} D_{s}^{+}→ϕπ^{+} decays ... Our result is τ_{D_{s}^{+}}=(499.5±1.7±0.9) fs, where the first uncertainty is statistical and the second is ...

Abstract	We measure the lifetime of the D_{s}^{+} meson using a data sample of 207 fb^{-1} collected by the Belle II experiment running at the SuperKEKB asymmetric-energy e^{+}e^{-} collider. The lifetime is determined by fitting the decay-time distribution of a sample of 116×10^{3} D_{s}^{+}→ϕπ^{+} decays. Our result is τ_{D_{s}^{+}}=(499.5±1.7±0.9) fs, where the first uncertainty is statistical and the second is systematic. This result is significantly more precise than previous measurements.
Language	English
Publishing date	2023-11-13
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.131.171803
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Article ; Online: Measurement of CP Violation in B^{0}→K_{S}^{0}π^{0} Decays at Belle II.

Adachi, I / Adamczyk, K / Aggarwal, L / Ahmed, H / Aihara, H / Akopov, N / Aloisio, A / Anh Ky, N / Asner, D M / Atmacan, H / Aushev, T / Aushev, V / Aversano, M / Babu, V / Bae, H / Bahinipati, S / Bambade, P / Banerjee, Sw / Barrett, M /

Baudot, J / Bauer, M / Baur, A / Beaubien, A / Becker, J / Behera, P K / Bennett, J V / Bertacchi, V / Bertemes, M / Bertholet, E / Bessner, M / Bettarini, S / Bhuyan, B / Bianchi, F / Bilka, T / Biswas, D / Bodrov, D / Bondar, A / Borah, J / Bozek, A / Bračko, M / Branchini, P / Briere, R A / Browder, T E / Budano, A / Bussino, S / Campajola, M / Cao, L / Casarosa, G / Cecchi, C / Cerasoli, J / Chang, P / Cheaib, R / Cheema, P / Chekelian, V / Chen, C / Cheon, B G / Chilikin, K / Chirapatpimol, K / Cho, H-E / Cho, K / Cho, S-J / Choi, S-K / Choudhury, S / Cochran, J / Corona, L / Cremaldi, L M / Das, S / Dattola, F / De La Cruz-Burelo, E / De La Motte, S A / de Marino, G / De Nuccio, M / De Pietro, G / de Sangro, R / Destefanis, M / De Yta-Hernandez, A / Dhamija, R / Di Canto, A / Di Capua, F / Dingfelder, J / Doležal, Z / Domínguez Jiménez, I / Dong, T V / Dorigo, M / Dort, K / Dreyer, S / Dubey, S / Dujany, G / Ecker, P / Eliachevitch, M / Feichtinger, P / Ferber, T / Ferlewicz, D / Fillinger, T / Finck, C / Finocchiaro, G / Fodor, A / Forti, F / Fulsom, B G / Gabrielli, A / Ganiev, E / Garcia-Hernandez, M / Garg, R / Garmash, A / Gaudino, G / Gaur, V / Gaz, A / Gellrich, A / Ghosh, D / Giakoustidis, G / Giordano, R / Giri, A / Glazov, A / Gobbo, B / Godang, R / Goldenzweig, P / Gradl, W / Grammatico, T / Granderath, S / Graziani, E / Greenwald, D / Gruberová, Z / Gu, T / Guan, Y / Gudkova, K / Halder, S / Han, Y / Hara, K / Hara, T / Hayasaka, K / Hayashii, H / Hazra, S / Hearty, C / Hedges, M T / Heredia de la Cruz, I / Hernández Villanueva, M / Hershenhorn, A / Higuchi, T / Hill, E C / Hoek, M / Hohmann, M / Hsu, C-L / Humair, T / Iijima, T / Inami, K / Ipsita, N / Ishikawa, A / Ito, S / Itoh, R / Iwasaki, M / Jackson, P / Jacobs, W W / Jang, E-J / Ji, Q P / Jia, S / Jin, Y / Johnson, A / Joo, K K / Junkerkalefeld, H / Kaleta, M / Kaliyar, A B / Kandra, J / Kang, K H / Kang, S / Kar, S / Karyan, G / Kawasaki, T / Keil, F / Ketter, C / Kiesling, C / Kim, C-H / Kim, D Y / Kim, K-H / Kim, Y-K / Kindo, H / Kodyš, P / Koga, T / Kohani, S / Kojima, K / Korobov, A / Korpar, S / Kovalenko, E / Kowalewski, R / Kraetzschmar, T M G / Križan, P / Krokovny, P / Kuhr, T / Kumar, J / Kumar, M / Kumara, K / Kunigo, T / Kuzmin, A / Kwon, Y-J / Lacaprara, S / Lai, Y-T / Lam, T / Lange, J S / Laurenza, M / Leboucher, R / Le Diberder, F R / Leitl, P / Levit, D / Li, C / Li, L K / Libby, J / Liu, Q Y / Liu, Z Q / Liventsev, D / Longo, S / Lueck, T / Luo, T / Lyu, C / Ma, Y / Maggiora, M / Maharana, S P / Maiti, R / Maity, S / Mancinelli, G / Manfredi, R / Manoni, E / Mantovano, M / Marcantonio, D / Marcello, S / Marinas, C / Martel, L / Martellini, C / Martinov, T / Massaccesi, L / Masuda, M / Matsuda, T / Matsuoka, K / Matvienko, D / Maurya, S K / McKenna, J A / Mehta, R / Meier, F / Merola, M / Metzner, F / Milesi, M / Miller, C / Mirra, M / Miyabayashi, K / Mizuk, R / Mohanty, G B / Molina-Gonzalez, N / Mondal, S / Moneta, S / Moser, H-G / Mrvar, M / Mussa, R / Nakamura, I / Nakazawa, Y / Narimani Charan, A / Naruki, M / Natochii, A / Nayak, L / Nayak, M / Nazaryan, G / Nisar, N K / Nishida, S / Ono, H / Onuki, Y / Oskin, P / Pakhlov, P / Pakhlova, G / Paladino, A / Paoloni, E / Pardi, S / Parham, K / Park, H / Park, S-H / Passeri, A / Patra, S / Paul, S / Pedlar, T K / Peschke, R / Pestotnik, R / Pham, F / Piccolo, M / Piilonen, L E / Podesta-Lerma, P L M / Podobnik, T / Pokharel, S / Praz, C / Prell, S / Prencipe, E / Prim, M T / Purwar, H / Rad, N / Rados, P / Raeuber, G / Raiz, S / Reif, M / Reiter, S / Remnev, M / Ripp-Baudot, I / Rizzo, G / Robertson, S H / Roehrken, M / Roney, J M / Rostomyan, A / Rout, N / Russo, G / Sahoo, D / Sandilya, S / Sangal, A / Santelj, L / Sato, Y / Savinov, V / Scavino, B / Schmitt, C / Schwanda, C / Schwartz, A J / Seino, Y / Selce, A / Senyo, K / Serrano, J / Sevior, M E / Sfienti, C / Shan, W / Sharma, C / Shi, X D / Shillington, T / Shiu, J-G / Shtol, D / Sibidanov, A / Simon, F / Singh, J B / Skorupa, J / Sobie, R J / Sobotzik, M / Soffer, A / Sokolov, A / Solovieva, E / Spataro, S / Spruck, B / Starič, M / Stavroulakis, P / Stefkova, S / Stottler, Z S / Stroili, R / Sumihama, M / Sumisawa, K / Sutcliffe, W / Svidras, H / Takahashi, M / Takizawa, M / Tamponi, U / Tanaka, S / Tanida, K / Tenchini, F / Thaller, A / Tittel, O / Tiwary, R / Tonelli, D / Torassa, E / Trabelsi, K / Tsaklidis, I / Uchida, M / Ueda, I / Uglov, T / Unger, K / Unno, Y / Uno, K / Uno, S / Urquijo, P / Ushiroda, Y / Vahsen, S E / van Tonder, R / Varner, G S / Varvell, K E / Vinokurova, A / Vismaya, V S / Vitale, L / Wach, B / Wakai, M / Wakeling, H M / Wallner, S / Wang, E / Wang, M-Z / Wang, Z / Warburton, A / Watanabe, M / Watanuki, S / Welsch, M / Wessel, C / Won, E / Xu, X P / Yabsley, B D / Yamada, S / Yan, W / Yang, S B / Yin, J H / Yoshihara, K / Yuan, C Z / Yusa, Y / Zani, L / Zhang, Y / Zhilich, V / Zhou, Q D / Zhukova, V I

Physical review letters

2023 Volume 131, Issue 11, Page(s) 111803

Abstract: We report a measurement of the CP-violating parameters C and S in B^{0}→K_{S}^{0}π^{0} decays ... decay-time distribution of a sample of 415 signal events. We obtain C=-0.04_{-0.15}^{+0.14}±0.05 and S=0 ...

Abstract	We report a measurement of the CP-violating parameters C and S in B^{0}→K_{S}^{0}π^{0} decays at Belle II using a sample of 387×10^{6} BB[over ¯] events recorded in e^{+}e^{-} collisions at a center-of-mass energy corresponding to the ϒ(4S) resonance. These parameters are determined by fitting the proper decay-time distribution of a sample of 415 signal events. We obtain C=-0.04_{-0.15}^{+0.14}±0.05 and S=0.75_{-0.23}^{+0.20}±0.04, where the first uncertainties are statistical and the second are systematic.
Language	English
Publishing date	2023-09-29
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.131.111803
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Influence of biochar produced from negative pressure-induced carbonization on transformation of potentially toxic metal(loid)s concerning plant physiological characteristics in industrially contaminated soil.

Cheema, Ayesha Imtiyaz / Liu, Guijian / Yousaf, Balal / Ashraf, Aniqa / Lu, Muyuan / Irshad, Samina / Pikon, Krzysztof / Mujtaba Munir, Mehr Ahmed / Rashid, Muhammad Saqib

Journal of environmental management

2023 Volume 347, Page(s) 119018

Abstract: ... 0.05) positive by confining the translocation and movement of metal(loid)s to the aerial part ... FTIR) further provided a more detailed understanding of the metal(loid)s and biochar complexation ... transfer of metal(loid)s by influencing their mobility and availability in the soil-plant system. ...

Abstract	Soil contamination and its subsequent impact on the food chain is a pressing challenge in the present day. The application of biochar has demonstrated a significant and positive effect on soil health, thereby enhancing plant growth and development. However, the application of biochar (BC) produced from negative pressure-induced carbonization to mitigate metal(loid) contamination is a new strategy that has been studied in current research. Results depicted that the application of biochar derived from the negative pressure carbonization (vacuum-assisted biochar (VBC) has a significant (p ≤ 0.05) positive impact on plant growth and physiological characteristics by influencing immobilization and speciation of metal(loid) in the soil system. Moreover, the interactive effect of VBC on physiological characteristics (photosynthesis, gas exchange, and chlorophyll contents) and antioxidant activities of maize (Zea mays L.) was significantly (p ≤ 0.05) positive by confining the translocation and movement of metal(loid)s to the aerial part of the maize plant. X-ray diffraction (XRD) provided information on the structural and chemical changes induced by the VBC-500 °C explaining metal(loid) adsorption onto mineral surfaces and complexation that can affect their mobility, availability, and toxicity in the contaminated soil. Fourier transform infrared spectroscopy (FTIR) further provided a more detailed understanding of the metal(loid)s and biochar complexation mechanisms influenced by VBC-based functional groups -OH, C-Hn, -COOH, CO, C-O-C, CC, C-O, C-H, OH, and C-C in the binding process. These results suggest that the application of biochar prepared at 500 °C under negative pressure-induced carbonization conditions to the soil is the most efficient way to reduce the uptake and transfer of metal(loid)s by influencing their mobility and availability in the soil-plant system.
MeSH term(s)	Soil Pollutants/analysis ; Charcoal/chemistry ; Metals/analysis ; Soil/chemistry ; Zea mays
Chemical Substances	biochar ; Soil Pollutants ; Charcoal (16291-96-6) ; Metals ; Soil
Language	English
Publishing date	2023-09-23
Publishing country	England
Document type	Journal Article
ZDB-ID	184882-3
ISSN	1095-8630 ; 0301-4797
ISSN (online)	1095-8630
ISSN	0301-4797
DOI	10.1016/j.jenvman.2023.119018
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Observation of e^{+}e^{-}→ωχ_{bJ}(1P) and Search for X_{b}→ωϒ(1S) at sqrt[s] near 10.75 GeV.

Adachi, I / Aggarwal, L / Ahmed, H / Aihara, H / Akopov, N / Aloisio, A / Anh Ky, N / Asner, D M / Aushev, T / Aushev, V / Bae, H / Bambade, P / Banerjee, Sw / Baudot, J / Bauer, M / Beaubien, A / Becker, J / Behera, P K / Bennett, J V /

Bernieri, E / Bernlochner, F U / Bertacchi, V / Bertemes, M / Bertholet, E / Bessner, M / Bettarini, S / Bhuyan, B / Bianchi, F / Bilka, T / Biswas, D / Bodrov, D / Bolz, A / Borah, J / Bozek, A / Bračko, M / Branchini, P / Browder, T E / Budano, A / Bussino, S / Campajola, M / Cao, L / Casarosa, G / Chang, M-C / Cheema, P / Chekelian, V / Chen, Y Q / Chilikin, K / Chirapatpimol, K / Cho, H-E / Cho, K / Cho, S-J / Choi, S-K / Choudhury, S / Cinabro, D / Corona, L / Cunliffe, S / Das, S / Dattola, F / De La Cruz-Burelo, E / De La Motte, S A / De Nardo, G / De Nuccio, M / De Pietro, G / de Sangro, R / Destefanis, M / Dey, S / De Yta-Hernandez, A / Dhamija, R / Di Canto, A / Di Capua, F / Doležal, Z / Domínguez Jiménez, I / Dong, T V / Dorigo, M / Dort, K / Dreyer, S / Dubey, S / Dujany, G / Eliachevitch, M / Feichtinger, P / Ferber, T / Ferlewicz, D / Fillinger, T / Finocchiaro, G / Fodor, A / Forti, F / Fulsom, B G / Ganiev, E / Gaur, V / Gaz, A / Gellrich, A / Ghevondyan, G / Giordano, R / Giri, A / Glazov, A / Gobbo, B / Godang, R / Goldenzweig, P / Granderath, S / Graziani, E / Greenwald, D / Gu, T / Guan, Y / Gudkova, K / Guilliams, J / Hara, T / Hayasaka, K / Hayashii, H / Hazra, S / Hearty, C / Heredia de la Cruz, I / Hernández Villanueva, M / Hershenhorn, A / Higuchi, T / Hill, E C / Hirata, H / Hohmann, M / Hsu, C-L / Iijima, T / Inami, K / Inguglia, G / Ipsita, N / Ishikawa, A / Ito, S / Iwasaki, M / Jackson, P / Jacobs, W W / Jaffe, D E / Jang, E-J / Ji, Q P / Jia, S / Jin, Y / Joo, K K / Junkerkalefeld, H / Kaliyar, A B / Kang, K H / Karl, R / Karyan, G / Ketter, C / Kiesling, C / Kim, C-H / Kim, D Y / Kim, K-H / Kim, Y-K / Kindo, H / Kodyš, P / Koga, T / Kohani, S / Kojima, K / Konno, T / Korobov, A / Korpar, S / Kovalenko, E / Kowalewski, R / Kraetzschmar, T M G / Križan, P / Krokovny, P / Kumar, R / Kumara, K / Kunigo, T / Kuzmin, A / Kwon, Y-J / Lacaprara, S / Lam, T / Lanceri, L / Lange, J S / Laurenza, M / Lautenbach, K / Leboucher, R / Lewis, P M / Li, C / Li, L K / Libby, J / Lieret, K / Liptak, Z / Liu, Q Y / Liventsev, D / Longo, S / Lozar, A / Lueck, T / Lyu, C / Maggiora, M / Maiti, R / Manfredi, R / Manoni, E / Marcello, S / Marinas, C / Martel, L / Martini, A / Martinov, T / Massaccesi, L / Masuda, M / Matsuoka, K / Maurya, S K / McKenna, J A / Merola, M / Metzner, F / Milesi, M / Miller, C / Miyabayashi, K / Mizuk, R / Molina-Gonzalez, N / Moneta, S / Moser, H-G / Mrvar, M / Mussa, R / Nakamura, I / Nakao, M / Nakazawa, Y / Narimani Charan, A / Naruki, M / Natkaniec, Z / Natochii, A / Nayak, L / Nayak, M / Nazaryan, G / Nisar, N K / Ogawa, S / Ono, H / Onuki, Y / Oskin, P / Paladino, A / Panta, A / Paoloni, E / Pardi, S / Park, H / Park, S-H / Paschen, B / Passeri, A / Paul, S / Pedlar, T K / Peruzzi, I / Peschke, R / Pestotnik, R / Piccolo, M / Piilonen, L E / Podesta-Lerma, P L M / Podobnik, T / Pokharel, S / Polat, L / Praz, C / Prell, S / Prencipe, E / Prim, M T / Purwar, H / Rad, N / Raiz, S / Ramirez Morales, A / Reif, M / Reiter, S / Remnev, M / Ripp-Baudot, I / Rizzo, G / Robertson, S H / Roney, J M / Rostomyan, A / Rout, N / Russo, G / Sanders, D A / Sandilya, S / Sangal, A / Santelj, L / Sato, Y / Savinov, V / Scavino, B / Schueler, J / Schwanda, C / Seino, Y / Selce, A / Senyo, K / Serrano, J / Sevior, M E / Sfienti, C / Shen, C P / Shi, X D / Shillington, T / Sibidanov, A / Singh, J B / Skorupa, J / Sobie, R J / Soffer, A / Solovieva, E / Spataro, S / Starič, M / Stefkova, S / Stottler, Z S / Stroili, R / Sue, Y / Sumihama, M / Sumisawa, K / Sutcliffe, W / Suzuki, S Y / Svidras, H / Takizawa, M / Tanida, K / Tanigawa, H / Tenchini, F / Thaller, A / Tiwary, R / Tonelli, D / Torassa, E / Toutounji, N / Trabelsi, K / Uchida, M / Ueda, I / Uematsu, Y / Uglov, T / Unger, K / Unno, Y / Uno, K / Uno, S / Ushiroda, Y / Vahsen, S E / van Tonder, R / Varner, G S / Vinokurova, A / Vitale, L / Vobbilisetti, V / Wakeling, H M / Wang, E / Wang, M-Z / Warburton, A / Watanuki, S / Welsch, M / Wessel, C / Won, E / Xu, X P / Yabsley, B D / Yamada, S / Yan, W / Yang, S B / Ye, H / Yelton, J / Yin, J H / Yook, Y M / Yoshihara, K / Yuan, C Z / Zani, L / Zhang, Y / Zhou, X Y / Zhukova, V I / Žlebčík, R

Physical review letters

2023 Volume 130, Issue 9, Page(s) 91902

Abstract: ... energies sqrt[s]=10.701, 10.745, and 10.805 GeV, corresponding to 1.6, 9.8, and 4.7 fb^{-1} of integrated ... s]=10.745 GeV. By combining Belle II data with Belle results at sqrt[s]=10.867 GeV, we find energy ... may differ. Including data at sqrt[s]=10.653 GeV, we also search for the bottomonium equivalent of the X ...

Abstract	We study the processes e^{+}e^{-}→ωχ_{bJ}(1P) (J=0, 1, or 2) using samples at center-of-mass energies sqrt[s]=10.701, 10.745, and 10.805 GeV, corresponding to 1.6, 9.8, and 4.7 fb^{-1} of integrated luminosity, respectively. These data were collected with the Belle II detector during special operations of the SuperKEKB collider above the ϒ(4S) resonance. We report the first observation of ωχ_{bJ}(1P) signals at sqrt[s]=10.745 GeV. By combining Belle II data with Belle results at sqrt[s]=10.867 GeV, we find energy dependencies of the Born cross sections for e^{+}e^{-}→ωχ_{b1,b2}(1P) to be consistent with the shape of the ϒ(10753) state. These data indicate that the internal structures of the ϒ(10753) and ϒ(10860) states may differ. Including data at sqrt[s]=10.653 GeV, we also search for the bottomonium equivalent of the X(3872) state decaying into ωϒ(1S). No significant signal is observed for masses between 10.45 and 10.65 GeV/c^{2}.
Language	English
Publishing date	2023-02-24
Publishing country	United States
Document type	Journal Article
ZDB-ID	208853-8
ISSN	1079-7114 ; 0031-9007
ISSN (online)	1079-7114
ISSN	0031-9007
DOI	10.1103/PhysRevLett.130.091902
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Article ; Online: Weed control through allelopathic crop water extracts and S-metolachlor in cotton

Nadeem Iqbal / Abdul Khaliq / Zahid Ata Cheema

Information Processing in Agriculture, Vol 7, Iss 1, Pp 165-

2020 Volume 172

Abstract: ... extracts (ACWEs) alone and in combination with one third rate of S-metolachlor (717 g a.i. ha−1 ... L ha−1, sorghum + brassica WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, sorghum + sunflower ... WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, sorghum + brassica WE + sunflower WE at 1.5 L ha−1 + S ...

Abstract	Weeds are one of the most important biological constraint to cotton production, and resulting in a yield losses of up to 90%. The evolution of hundreds of resistant weed species, the lack of new herbicide chemistries, and the increase in weed management costs are all making weed management more arduous for the growers. Hence, a field experiment was conducted to investigate the efficacy of allelopathic crop water extracts (ACWEs) alone and in combination with one third rate of S-metolachlor (717 g a.i. ha−1) for effective weed management in cotton. The treatments investigated were; weedy check, sorghum + brassica water extract (WE) at 1.5 L ha−1, sorghum + sunflower WE at 1.5 L ha−1, sorghum + brassica + sunflower WE at 1.5 L ha−1, sorghum + brassica WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, sorghum + sunflower WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, sorghum + brassica WE + sunflower WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, and S-metolachlor at recommended rate of 2.15 kg a.i. ha−1. Results revealed that pre-emergent application of sorghum + brassica water extract (WE) at 1.5 L ha−1 was the best treatment in terms of effective dry biomass reduction (40%) of Trianthema portulacastrum and Cyperus rotundus, and increase in seed cotton yield (12%). The second best treatment was sorghum + sunflower WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i. ha−1 with yield increase of 11% over the weedy control. In comparison, S-metolachlor at recommended rate 2.15 kg a.i. ha−1 recorded only 4% decrease in weeds dry biomass reduction and 8% increase in seed cotton yield. Hence, it can be predicted that binary combination of sorghum and brassica WE at 1.5 L ha−1 or binary combination of sorghum + sunflower WE at 1.5 L ha−1 with one third dose of S-metolachlor (717 g a.i. ha−1) can be used for effective weed management and increase in seed cotton yield. Furthermore, adoption of this technique will also reduce the herbicide application, which is not only beneficial for the ecosystem but, also minimize ...
Keywords	Agriculture (General) ; S1-972 ; Information technology ; T58.5-58.64
Subject code	580
Language	English
Publishing date	2020-03-01T00:00:00Z
Publisher	KeAi Communications Co., Ltd.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Estimating the Global Fatality Rate from COVID-19 Given a Country’s Socio-Economic Characteristics

Szulczuk, Kenneth / Cheema, Muhammad A.

SSRN Electronic Journal ; ISSN 1556-5068

2020

Keywords	covid19
Language	English
Publisher	Elsevier BV
Publishing country	us
Document type	Article ; Online
DOI	10.2139/ssrn.3591551
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Weed control through allelopathic crop water extracts and S-metolachlor in cotton

Iqbal, Nadeem / Khaliq, Abdul / Cheema, Zahid Ata

Information processing in agriculture. 2019 Mar. 27,

2019

Abstract	Weeds are one of the most important biological constraint to cotton production, and resulting in a yield losses of up to 90%. The evolution of hundreds of resistant weed species, the lack of new herbicide chemistries, and the increase in weed management costs are all making weed management more arduous for the growers. Hence, a field experiment was conducted to investigate the efficacy of allelopathic crop water extracts (ACWEs) alone and in combination with one third rate of S-metolachlor (717 g a.i. ha−1) for effective weed management in cotton. The treatments investigated were; weedy check, sorghum + brassica water extract (WE) at 1.5 L ha−1, sorghum + sunflower WE at 1.5 L ha−1, sorghum + brassica + sunflower WE at 1.5 L ha−1, sorghum + brassica WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, sorghum + sunflower WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, sorghum + brassica WE + sunflower WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i.ha−1, and S-metolachlor at recommended rate of 2.15 kg a.i. ha−1. Results revealed that pre-emergent application of sorghum + brassica water extract (WE) at 1.5 L ha−1 was the best treatment in terms of effective dry biomass reduction (40%) of Trianthema portulacastrum and Cyperus rotundus, and increase in seed cotton yield (12%). The second best treatment was sorghum + sunflower WE at 1.5 L ha−1 + S-metolachlor at 717 g a.i. ha−1 with yield increase of 11% over the weedy control. In comparison, S-metolachlor at recommended rate 2.15 kg a.i. ha−1 recorded only 4% decrease in weeds dry biomass reduction and 8% increase in seed cotton yield. Hence, it can be predicted that binary combination of sorghum and brassica WE at 1.5 L ha−1 or binary combination of sorghum + sunflower WE at 1.5 L ha−1 with one third dose of S-metolachlor (717 g a.i. ha−1) can be used for effective weed management and increase in seed cotton yield. Furthermore, adoption of this technique will also reduce the herbicide application, which is not only beneficial for the ecosystem but, also minimize the evolution of herbicide-resistant weed species.
Keywords	Brassica ; Cyperus rotundus ; Helianthus annuus ; Trianthema portulacastrum ; biomass ; cotton ; crop yield ; ecosystems ; field experimentation ; growers ; herbicide-resistant weeds ; metolachlor ; pesticide application ; weed control
Language	English
Dates of publication	2019-0327
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ISSN	2214-3173
DOI	10.1016/j.inpa.2019.03.006
Database	NAL-Catalogue (AGRICOLA)

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Article: Application of deep learning to detect Lamb’s quarters (Chenopodium album L.) in potato fields of Atlantic Canada

Hussain, Nazar / Farooque, Aitazaz A. / Schumann, Arnold W. / Abbas, Farhat / Acharya, Bishnu / McKenzie-Gopsill, Andrew / Barrett, Ryan / Afzaal, Hassan / Zaman, Qamar U. / Cheema, Muhammad J.M.

Computers and electronics in agriculture. 2021 Mar., v. 182

2021

Abstract: ... deep convolutional neural networks (DCNNs) for detecting lamb’s quarters (Chenopodium album) in potato ... to collect images of spatially and temporally varied potato plants and lamb’s quarters. The image database ... EfficientNet to classify lamb’s quarters and potato plants. Performance of two frameworks, namely TensorFlow ...

Abstract	Excessive use of herbicides for weed control increases the cost of crop production and can lead to environmental degradation. An intelligent spraying system can apply agrochemicals on an as-needed basis by detecting and selectively targeting the weeds. The objective of this research was to investigate the feasibility of using deep convolutional neural networks (DCNNs) for detecting lamb’s quarters (Chenopodium album) in potato fields. Five potato fields were selected in Prince Edward Island (PEI) and New Brunswick (NB), Canada to collect images of spatially and temporally varied potato plants and lamb’s quarters. The image database included pictures, taken under varying growth stages of potato, outdoor light (clear, cloudy, and partly cloudy), and shadowy conditions. The images were trained for DCNN models, namely GoogLeNet, VGG-16, and EfficientNet to classify lamb’s quarters and potato plants. Performance of two frameworks, namely TensorFlow and PyTorch, were compared in training, testing, and during inferring the DCNNs. Results showed excellent performance of DCNNs in lamb’s quarters and potato plant classification (accuracy > 90%). However, the EfficientNet with PyTorch framework showed a maximum accuracy of (0.92–0.97) for every growth stage of the plants. Inference times of DCNNs were recorded using three graphics processing units (GPUs), namely Nvidia GeForce 930MX, Nvidia GeForce GTX1080 Ti, and Nvidia GeForce GTX1050. All the DCNNs performed better with PyTorch than TensorFlow frameworks. It was concluded that the trained models can be used in automation of the spraying systems for the site-specific application of agrochemicals for weed control in potato fields. Such precision agriculture technologies will ensure economically viable and environmentally safe potato cultivation.
Keywords	Chenopodium album ; agriculture ; agrochemicals ; automation ; crop production ; databases ; developmental stages ; economic sustainability ; electronics ; environmental degradation ; potatoes ; precision agriculture ; weed control ; New Brunswick ; Prince Edward Island
Language	English
Dates of publication	2021-03
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	395514-x
ISSN	0168-1699
ISSN	0168-1699
DOI	10.1016/j.compag.2021.106040
Database	NAL-Catalogue (AGRICOLA)

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Book ; Online: Open Letter on the National Academies of Sciences, Engineering, and Medicine Committee’s A Framework for Equitable Allocation of Vaccine for the Novel Coronavirus

Caunca, Michelle R / Cheema, Haadiya / Weuve, Jennifer / Murray, Eleanor J. / Corps, Epidemiology COVID- Response

2020

Abstract: This is a public comment on behalf of a group of epidemiologists, public health students, and public health practitioners for submission to the National Academies of Sciences, Engineering, and Medicine Committee for A Framework for Equitable Allocation ... ...

Abstract	This is a public comment on behalf of a group of epidemiologists, public health students, and public health practitioners for submission to the National Academies of Sciences, Engineering, and Medicine Committee for A Framework for Equitable Allocation of Vaccine for the Novel Coronavirus. We believe that Equitable Vaccine Distribution is of the utmost importance as the next major step in COVID-19 response. The pandemic has disproportionately affected BIPOC populations by almost every measure--risk of infection, death, and economic toll--due to the structural racism and racial capitalism that underlies all major systems of American culture, including healthcare, public health response, resource allocation, and science communication.
Keywords	covid19
Publisher	Center for Open Science
Publishing country	us
Document type	Book ; Online
DOI	10.31219/osf.io/x87ua
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: McConnell’s sign unveiled

Ivanova Valentyna / Doyle Mark / Yamrozik June / Williams Ronald B / Rayarao Geetha / Shah Moneal / Cheema Tariq / Biederman Robert W

Journal of Cardiovascular Magnetic Resonance, Vol 14, Iss Suppl 1, p P

2012 Volume 88

Keywords	Diseases of the circulatory (Cardiovascular) system ; RC666-701 ; Specialties of internal medicine ; RC581-951 ; Internal medicine ; RC31-1245 ; Medicine ; R ; DOAJ:Cardiovascular ; DOAJ:Medicine (General) ; DOAJ:Health Sciences
Language	English
Publishing date	2012-02-01T00:00:00Z
Publisher	BioMed Central
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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