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1. Domain-Factored Untrained Deep Prior for Spectrum Cartography

Author: Timilsina, Subash, Shrestha, Sagar, Cheng, Lei, and Fu, Xiao
Subjects: Electrical Engineering and Systems Science - Signal Processing
Abstract: Spectrum cartography (SC) focuses on estimating the radio power propagation map of multiple emitters across space and frequency using limited sensor measurements. Recent advances in SC have shown that leveraging learned deep generative models (DGMs) as structural constraints yields state-of-the-art performance. By harnessing the expressive power of neural networks, these structural "priors" capture intricate patterns in radio maps. However, training DGMs requires substantial data, which is not always available, and distribution shifts between training and testing data can further degrade performance. To address these challenges, this work proposes using untrained neural networks (UNNs) for SC. UNNs, commonly applied in vision tasks to represent complex data without training, encode structural information of data in neural architectures. In our approach, a custom-designed UNN represents radio maps under a spatio-spectral domain factorization model, leveraging physical characteristics to reduce sample complexity of SC. Experiments show that the method achieves performance comparable to learned DGM-based SC, without requiring training data., Comment: 6 pages 6 figures
Published: 2025

2. Identifiable Shared Component Analysis of Unpaired Multimodal Mixtures

Author: Timilsina, Subash, Shrestha, Sagar, and Fu, Xiao
Subjects: Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning
Abstract: A core task in multi-modal learning is to integrate information from multiple feature spaces (e.g., text and audio), offering modality-invariant essential representations of data. Recent research showed that, classical tools such as {\it canonical correlation analysis} (CCA) provably identify the shared components up to minor ambiguities, when samples in each modality are generated from a linear mixture of shared and private components. Such identifiability results were obtained under the condition that the cross-modality samples are aligned/paired according to their shared information. This work takes a step further, investigating shared component identifiability from multi-modal linear mixtures where cross-modality samples are unaligned. A distribution divergence minimization-based loss is proposed, under which a suite of sufficient conditions ensuring identifiability of the shared components are derived. Our conditions are based on cross-modality distribution discrepancy characterization and density-preserving transform removal, which are much milder than existing studies relying on independent component analysis. More relaxed conditions are also provided via adding reasonable structural constraints, motivated by available side information in various applications. The identifiability claims are thoroughly validated using synthetic and real-world data.
Published: 2024

3. Measurement of elliptic flow of J$/\psi$ in $\sqrt{s_{_{NN}}}=200$ GeV Au$+$Au collisions at forward rapidity

Author: PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Aidala, C., Ajitanand, N. N., Akiba, Y., Alfred, M., Antsupov, S., Aoki, K., Apadula, N., Asano, H., Ayuso, C., Azmoun, B., Babintsev, V., Bai, M., Bandara, N. S., Bannier, B., Bannikov, E., Barish, K. N., Bathe, S., Bazilevsky, A., Beaumier, M., Beckman, S., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Boer, M., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Butler, C., Campbell, S., Roman, V. Canoa, Chen, C. -H., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Chujo, T., Citron, Z., Connors, M., Corliss, R., Csanád, M., Csörgő, T., Liu, L. D., Danley, T. W., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dion, A., Diss, P. B., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Dumancic, M., Durham, J. M., Durum, A., Elder, T., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gallus, P., Gal, C., Garg, P., Ge, H., Giordano, F., Glenn, A., Goto, Y., Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Hemmick, T. K., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imai, K., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Ito, Y., Ivanishchev, D., Jacak, B., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Jorjadze, V., Jouan, D., Jumper, D. S., Kanda, S., Kang, J. H., Kapukchyan, D., Karthas, S., Kawall, D., Kazantsev, A. V., Key, J. A., Khachatryan, V., Khanzadeev, A., Kimelman, B., Kim, C., Kim, D. J., Kim, E. -J., Kim, G. W., Kim, M., Kim, M. H., Kincses, D., Kistenev, E., Kitamura, R., Klatsky, J., Kleinjan, D., Kline, P., Koblesky, T., Komkov, B., Kotov, D., Kovacs, L., Kudo, S., Kurita, K., Kurosawa, M., Kwon, Y., Lajoie, J. G., Lallow, E. O., Lebedev, A., Lee, S., Lee, S. H., Leitch, M. J., Leung, Y. H., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Lökös, S., Loomis, D. A., Lynch, D., Majoros, T., Makdisi, Y. I., Makek, M., Malaev, M., Manion, A., Manko, V. I., Mannel, E., Masuda, H., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Meles, A., Mendoza, M., Mignerey, A. C., Mihalik, D. E., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mohanty, A. K., Montuenga, P., Moon, T., Morrison, D. P., Morrow, S. I., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakano, K., Nattrass, C., Netrakanti, P. K., Niida, T., Nishimura, S., Nouicer, R., Novitzky, N., Novotny, R., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Peng, J. -C., Peng, W., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pinson, R., Pisani, R. P., Potekhin, M., Pun, A., Purschke, M. L., Rak, J., Ramson, B. J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rolnick, S. D., Rosati, M., Rowan, Z., Rubin, J. G., Runchey, J., Sahlmueller, B., Saito, N., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, K., Sato, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seidl, R., Seleznev, A., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stepanov, M., Stoll, S. P., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Syed, S., Sziklai, J., Takeda, A., Taketani, A., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Vazquez-Carson, S., Velkovska, J., Virius, M., Vrba, V., Wang, X. R., Wang, Z., Watanabe, Y., Watanabe, Y. S., Wei, F., White, A. S., Wong, C. P., Woody, C. L., Wysocki, M., Xia, B., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yanovich, A., Yin, P., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., Zhou, S., and Zou, L.
Subjects: Nuclear Experiment
Abstract: We report the first measurement of the azimuthal anisotropy of J$/\psi$ at forward rapidity ($1.2<|\eta|<2.2$) in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV at the Relativistic Heavy Ion Collider. The data were collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The second Fourier coefficient ($v_2$) of the azimuthal distribution of $J/\psi$ is determined as a function of the transverse momentum ($p_T$) using the event-plane method. The measurements were performed for several selections of collision centrality: 0\%--50\%, 10\%--60\%, and 10\%-40\%. We find that in all cases the values of $v_2(p_T)$, which quantify the elliptic flow of J$/\psi$, are consistent with zero. The results are consistent with measurements at midrapidity, indicating no significant elliptic flow of the J$/\psi$ within the quark-gluon-plasma medium at collision energies of $\sqrt{s_{_{NN}}}=200$ GeV., Comment: 369 authors from 72 institutions, 12 pages, 7 figures, 5 tables. v1 is version submitted to Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2024

4. Measurements at forward rapidity of elliptic flow of charged hadrons and open-heavy-flavor muons in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV

Author: PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Aidala, C., Ajitanand, N. N., Akiba, Y., Alfred, M., Antsupov, S., Aoki, K., Apadula, N., Asano, H., Ayuso, C., Azmoun, B., Babintsev, V., Bai, M., Bandara, N. S., Bannier, B., Bannikov, E., Barish, K. N., Bathe, S., Bazilevsky, A., Beaumier, M., Beckman, S., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Boer, M., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Butler, C., Campbell, S., Roman, V. Canoa, Chen, C. -H., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Chujo, T., Citron, Z., Connors, M., Corliss, R., Csanád, M., Csörgő, T., Liu, L. D., Danley, T. W., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dion, A., Diss, P. B., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Dumancic, M., Durham, J. M., Durum, A., Elder, T., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gallus, P., Gal, C., Garg, P., Ge, H., Giordano, F., Glenn, A., Goto, Y., Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Hemmick, T. K., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imai, K., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Ito, Y., Ivanishchev, D., Jacak, B., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Jorjadze, V., Jouan, D., Jumper, D. S., Kanda, S., Kang, J. H., Kapukchyan, D., Karthas, S., Kawall, D., Kazantsev, A. V., Key, J. A., Khachatryan, V., Khanzadeev, A., Kimelman, B., Kim, C., Kim, D. J., Kim, E. -J., Kim, G. W., Kim, M., Kim, M. H., Kincses, D., Kistenev, E., Kitamura, R., Klatsky, J., Kleinjan, D., Kline, P., Koblesky, T., Komkov, B., Kotov, D., Kovacs, L., Kudo, S., Kurita, K., Kurosawa, M., Kwon, Y., Lajoie, J. G., Lallow, E. O., Lebedev, A., Lee, S., Lee, S. H., Leitch, M. J., Leung, Y. H., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Lökös, S., Loomis, D. A., Lynch, D., Majoros, T., Makdisi, Y. I., Makek, M., Malaev, M., Manion, A., Manko, V. I., Mannel, E., Masuda, H., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Meles, A., Mendoza, M., Mignerey, A. C., Mihalik, D. E., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mohanty, A. K., Montuenga, P., Moon, T., Morrison, D. P., Morrow, S. I., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakano, K., Nattrass, C., Netrakanti, P. K., Niida, T., Nishimura, S., Nouicer, R., Novitzky, N., Novotny, R., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Peng, J. -C., Peng, W., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pinson, R., Pisani, R. P., Potekhin, M., Pun, A., Purschke, M. L., Rak, J., Ramson, B. J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rolnick, S. D., Rosati, M., Rowan, Z., Rubin, J. G., Runchey, J., Sahlmueller, B., Saito, N., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, K., Sato, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seidl, R., Seleznev, A., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stepanov, M., Stoll, S. P., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Syed, S., Sziklai, J., Takeda, A., Taketani, A., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Vazquez-Carson, S., Velkovska, J., Virius, M., Vrba, V., Wang, X. R., Wang, Z., Watanabe, Y., Watanabe, Y. S., Wei, F., White, A. S., Wong, C. P., Woody, C. L., Wysocki, M., Xia, B., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yanovich, A., Yin, P., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., Zhou, S., and Zou, L.
Subjects: Nuclear Experiment
Abstract: We present the first forward-rapidity measurements of elliptic anisotropy of open-heavy-flavor muons at the BNL Relativistic Heavy Ion Collider. The measurements are based on data samples of Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV collected by the PHENIX experiment in 2014 and 2016 with integrated luminosity of 14.5~nb$^{-1}$. The measurements are performed in the pseudorapidity range $1.2<|\eta|<2$ and cover transverse momenta $1
Published: 2024

5. Multiplicity dependent $J/\psi$ and $\psi(2S)$ production at forward and backward rapidity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV

Author: PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Aidala, C., Akiba, Y., Alfred, M., Andrieux, V., Antsupov, S., Apadula, N., Asano, H., Azmoun, B., Babintsev, V., Bandara, N. S., Bannikov, E., Barish, K. N., Bathe, S., Bazilevsky, A., Beaumier, M., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Campbell, S., Cervantes, R., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Citron, Z., Connors, M., Corliss, R., Cronin, N., Csanád, M., Csörgő, T., Danley, T. W., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dion, A., Dixit, D., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gallus, P., Gal, C., Garg, P., Ge, H., Giordano, F., Goto, Y., Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Guragain, H., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Hasegawa, S., Haseler, T. O. S., Hemmick, T. K., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imai, K., Inaba, M., Iordanova, A., Isenhower, D., Ivanishchev, D., Jacak, B., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Jouan, D., Jumper, D. S., Kang, J. H., Kapukchyan, D., Karthas, S., Kawall, D., Kazantsev, A. V., Khachatryan, V., Khanzadeev, A., Kim, C., Kim, E. -J., Kim, M., Kincses, D., Kistenev, E., Klatsky, J., Kline, P., Koblesky, T., Kotov, D., Kovacs, L., Kudo, S., Kurita, K., Kwon, Y., Lajoie, J. G., Lebedev, A., Lee, S., Leitch, M. J., Leung, Y. H., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Lökös, S., Loomis, D. A., Lovasz, K., Lynch, D., Majoros, T., Makdisi, Y. I., Makek, M., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Mendoza, M., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Montuenga, P., Moon, T., Morrison, D. P., Mulilo, B., Murakami, T., Murata, J., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakano, K., Nattrass, C., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pisani, R. P., Potekhin, M., Purschke, M. L., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rolnick, S. D., Rosati, M., Rowan, Z., Safonov, A. S., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seidl, R., Seleznev, A., Sen, A., Seto, R., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stoll, S. P., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Wang, X. R., Watanabe, Y. S., Woody, C. L., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., and Zou, L.
Subjects: High Energy Physics - Experiment
Abstract: The $J/\psi$ and $\psi(2S)$ charmonium states, composed of $c\bar{c}$ quark pairs and known since the 1970s, are widely believed to serve as ideal probes to test quantum chromodynamics in high-energy hadronic interactions. However, there is not yet a complete understanding of the charmonium-production mechanism. Recent measurements of $J/\psi$ production as a function of event charged-particle multiplicity at the collision energies of both the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) show enhanced $J/\psi$ production yields with increasing multiplicity. One potential explanation for this type of dependence is multiparton interactions (MPI). We carry out the first measurements of self-normalized $J/\psi$ yields and the $\psi(2S)$ to $J/\psi$ ratio at both forward and backward rapidities as a function of self-normalized charged-particle multiplicity in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV. In addition, detailed {\sc pythia} studies tuned to RHIC energies were performed to investigate the MPI impacts. We find that the PHENIX data at RHIC are consistent with recent LHC measurements and can only be described by {\sc pythia} calculations that include MPI effects. The forward and backward $\psi(2S)$ to $J/\psi$ ratio, which serves as a unique and powerful approach to study final-state effects on charmonium production, is found to be less dependent on the charged-particle multiplicity., Comment: 301 authors from 69 institutions, 8 pages, 3 figures. v1 is version submitted to Physical Review D Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2024

6. Measurement of inclusive jet cross section and substructure in $p$$+$$p$ collisions at $\sqrt{s_{_{NN}}}=200$ GeV

Author: PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Aidala, C., Ajitanand, N. N., Akiba, Y., Akimoto, R., Alexander, J., Alfred, M., Andrieux, V., Antsupov, S., Aoki, K., Apadula, N., Asano, H., Atomssa, E. T., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Bai, X., Bandara, N. S., Bannier, B., Bannikov, E., Barish, K. N., Bathe, S., Baublis, V., Baumann, C., Baumgart, S., Bazilevsky, A., Beaumier, M., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Black, D., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Buesching, H., Bumazhnov, V., Butsyk, S., Campbell, S., Cervantes, R., Chen, C. -H., Chen, D., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choi, S., Christiansen, P., Chujo, T., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Corliss, R., Cronin, N., Crossette, N., Csanád, M., Csörgő, T., D'Orazio, L., Danley, T. W., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Ding, L., Dion, A., Dixit, D., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukao, Y., Fukuda, Y., Fusayasu, T., Gainey, K., Gallus, P., Gal, C., Garg, P., Garishvili, A., Garishvili, I., Ge, H., Giordano, F., Glenn, A., Gong, X., Gonin, M., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Guragain, H., Gu, Y., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Hayano, R., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Ichihara, T., Ikeda, Y., Imai, K., Imazu, Y., Inaba, M., Iordanova, A., Isenhower, D., Isinhue, A., Ivanishchev, D., Jeon, S. J., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kamin, J., Kanda, S., Kang, B. H., Kang, J. H., Kang, J. S., Kapukchyan, D., Kapustinsky, J., Karthas, S., Kawall, D., Kazantsev, A. V., Key, J. A., Khachatryan, V., Khandai, P. K., Khanzadeev, A., Kijima, K. M., Kim, C., Kim, D. J., Kim, E. -J., Kim, M., Kim, Y. -J., Kim, Y. K., Kincses, D., Kistenev, E., Klatsky, J., Kleinjan, D., Kline, P., Koblesky, T., Kofarago, M., Komkov, B., Koster, J., Kotchetkov, D., Kotov, D., Kovacs, L., Krizek, F., Kudo, S., Kurita, K., Kurosawa, M., Kwon, Y., Lai, Y. S., Lajoie, J. G., Lebedev, A., Lee, D. M., Lee, G. H., Lee, J., Lee, K. B., Lee, K. S., Lee, S., Lee, S. H., Leitch, M. J., Leitgab, M., Leung, Y. H., Lewis, B., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Lokos, S., Loomis, D. A., Lovasz, K., Lynch, D., Maguire, C. F., Majoros, T., Makdisi, Y. I., Makek, M., Manion, A., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Meles, A., Mendoza, M., Meredith, B., Miake, Y., Mibe, T., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mohanty, A. K., Mohapatra, S., Montuenga, P., Moon, T., Morrison, D. P., Moskowitz, M., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagae, T., Nagai, K., Nagamiya, S., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakamiya, Y., Nakamura, K. R., Nakamura, T., Nakano, K., Nattrass, C., Netrakanti, P. K., Nihashi, M., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oide, H., Okada, K., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, I. H., Park, J. S., Park, S., Park, S. K., Patel, L., Patel, M., Pate, S. F., Peng, J. -C., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pisani, R. P., Potekhin, M., Purschke, M. L., Qu, H., Rak, J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richardson, E., Richford, D., Rinn, T., Riveli, N., Roach, D., Rolnick, S. D., Rosati, M., Rowan, Z., Ryu, M. S., Safonov, A. S., Sahlmueller, B., Saito, N., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sawada, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seele, J., Seidl, R., Sekiguchi, Y., Seleznev, A., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shaver, A., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Skolnik, M., Slunečka, M., Smith, K. L., Snowball, M., Solano, S., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Steinberg, P., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Stone, M. R., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takahara, A., Taketani, A., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tennant, E., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Torii, H., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Vargyas, M., Vazquez-Zambrano, E., Veicht, A., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, D., Watanabe, K., Watanabe, Y., Watanabe, Y. S., Wei, F., Whitaker, S., Wolin, S., Woody, C. L., Wysocki, M., Xia, B., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yokkaichi, S., Yoon, I., Yoo, J. H., Younus, I., You, Z., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., Zhou, S., and Zou, L.
Subjects: High Energy Physics - Experiment, Nuclear Experiment
Abstract: The jet cross-section and jet-substructure observables in $p$$+$$p$ collisions at $\sqrt{s}=200$ GeV were measured by the PHENIX Collaboration at the Relativistic Heavy Ion Collider (RHIC). Jets are reconstructed from charged-particle tracks and electromagnetic-calorimeter clusters using the anti-$k_{t}$ algorithm with a jet radius $R=0.3$ for jets with transverse momentum within $8.0
Published: 2024

7. Jet modification via $\pi^0$-hadron correlations in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV

Author: PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Afanasiev, S., Aidala, C., Ajitanand, N. N., Akiba, Y., Al-Bataineh, H., Alexander, J., Alfred, M., Aoki, K., Apadula, N., Aphecetche, L., Asai, J., Asano, H., Atomssa, E. T., Averbeck, R., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Baksay, G., Baksay, L., Baldisseri, A., Bandara, N. S., Bannier, B., Barish, K. N., Barnes, P. D., Bassalleck, B., Basye, A. T., Bathe, S., Batsouli, S., Baublis, V., Baumann, C., Bazilevsky, A., Beaumier, M., Beckman, S., Belikov, S., Belmont, R., Bennett, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Bickley, A. A., Blankenship, B., Blau, D. S., Boissevain, J. G., Bok, J. S., Borel, H., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Buesching, H., Bumazhnov, V., Bunce, G., Butsyk, S., Camacho, C. M., Campbell, S., Chang, B. S., Chang, W. C., Charvet, J. L., Chen, C. -H., Chen, D., Chernichenko, S., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choudhury, R. K., Chujo, T., Chung, P., Churyn, A., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Constantin, P., Corliss, R., Csanád, M., Csörgő, T., d'Enterria, D., Dahms, T., Dairaku, S., Danley, T. W., Das, K., Datta, A., Daugherity, M. S., David, G., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dietzsch, O., Dion, A., Diss, P. B., Donadelli, M., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Dubey, A. K., Durham, J. M., Durum, A., Dutta, D., Dzhordzhadze, V., Efremenko, Y. V., Ellinghaus, F., En'yo, H., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Fraenkel, Z., Frantz, J. E., Franz, A., Frawley, A. D., Fujiwara, K., Fukao, Y., Fusayasu, T., Gallus, P., Gal, C., Garg, P., Garishvili, I., Ge, H., Giordano, F., Glenn, A., Gong, H., Gonin, M., Gosset, J., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guo, T., Gustafsson, H. -Å., Hachiya, T., Henni, A. Hadj, Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, R., Han, S. Y., Hartouni, E. P., Haruna, K., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Haslum, E., Hayano, R., Heffner, M., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hodges, A., Hohlmann, M., Hollis, R. S., Holzmann, W., Homma, K., Hong, B., Horaguchi, T., Hornback, D., Hoshino, T., Hotvedt, N., Huang, J., Ichihara, T., Ichimiya, R., Iinuma, H., Ikeda, Y., Imai, K., Imrek, J., Inaba, M., Iordanova, A., Isenhower, D., Ishihara, M., Isobe, T., Issah, M., Isupov, A., Ivanishchev, D., Jacak, B. V., Jezghani, M., Jiang, X., Jin, J., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kajihara, F., Kametani, S., Kamihara, N., Kamin, J., Kanda, S., Kang, J. H., Kapustinsky, J., Kawall, D., Kazantsev, A. V., Kempel, T., Key, J. A., Khachatryan, V., Khanzadeev, A., Kijima, K. M., Kikuchi, J., Kimelman, B., Kim, B. I., Kim, C., Kim, D. H., Kim, D. J., Kim, E., Kim, E. -J., Kim, G. W., Kim, M., Kim, S. H., Kinney, E., Kiriluk, K., Kiss, Á., Kistenev, E., Kitamura, R., Klatsky, J., Klay, J., Klein-Boesing, C., Kleinjan, D., Kline, P., Koblesky, T., Kochenda, L., Komkov, B., Konno, M., Koster, J., Kotov, D., Kovacs, L., Kozlov, A., Kravitz, A., Král, A., Kunde, G. J., Kurgyis, B., Kurita, K., Kurosawa, M., Kweon, M. J., Kwon, Y., Kyle, G. S., Lai, Y. S., Lajoie, J. G., Layton, D., Lebedev, A., Lee, D. M., Lee, K. B., Lee, S., Lee, S. H., Lee, T., Leitch, M. J., Leite, M. A. L., Lenzi, B., Liebing, P., Lim, S. H., Litvinenko, A., Liu, H., Liu, M. X., Liška, T., Li, X., Lokos, S., Loomis, D. A., Love, B., Lynch, D., Maguire, C. F., Makdisi, Y. I., Makek, M., Malakhov, A., Malik, M. D., Manion, A., Manko, V. I., Mannel, E., Mao, Y., Masui, H., Matathias, F., Mašek, L., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Means, N., Meles, A., Mendoza, M., Meredith, B., Miake, Y., Mignerey, A. C., Mikeš, P., Miki, K., Milov, A., Mishra, D. K., Mishra, M., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Miyasaka, S., Mizuno, S., Mohanty, A. K., Montuenga, P., Moon, T., Morino, Y., Morreale, A., Morrison, D. P., Moukhanova, T. V., Mukhopadhyay, D., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagamiya, S., Nagashima, K., Nagle, J. L., Naglis, M., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakamiya, Y., Nakamura, T., Nakano, K., Nattrass, C., Netrakanti, P. K., Newby, J., Nguyen, M., Niida, T., Nishimura, S., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Oda, S. X., Ogilvie, C. A., Okada, K., Oka, M., Onuki, Y., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ouchida, M., Ozawa, K., Pak, R., Palounek, A. P. T., Pantuev, V., Papavassiliou, V., Park, J., Park, J. S., Park, S., Park, W. J., Patel, M., Pate, S. F., Pei, H., Peng, J. -C., Pereira, H., Perepelitsa, D. V., Perera, G. D. N., Peresedov, V., Peressounko, D. Yu., Perry, J., Petti, R., Pinkenburg, C., Pinson, R., Pisani, R. P., Potekhin, M., Purschke, M. L., Purwar, A. K., Qu, H., Rakotozafindrabe, A., Rak, J., Ramson, B. J., Ravinovich, I., Read, K. F., Rembeczki, S., Reygers, K., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Roach, D., Roche, G., Rolnick, S. D., Rosati, M., Rosendahl, S. S. E., Rosnet, P., Rowan, Z., Rubin, J. G., Rukoyatkin, P., Ružička, P., Rykov, V. L., Sahlmueller, B., Saito, N., Sakaguchi, T., Sakai, S., Sakashita, K., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sato, T., Sawada, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seele, J., Seidl, R., Semenov, A. Yu., Semenov, V., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shein, I., Shibata, T. -A., Shigaki, K., Shimomura, M., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Silvestre, C., Sim, K. S., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soldatov, A., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Staley, F., Stankus, P. W., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Sugitate, T., Suire, C., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takagui, E. M., Taketani, A., Tanabe, R., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarján, P., Themann, H., Thomas, T. L., Tieulent, R., Timilsina, A., Todoroki, T., Togawa, M., Toia, A., Tomita, Y., Tomášek, L., Tomášek, M., Torii, H., Towell, C. L., Towell, R., Towell, R. S., Tram, V-N., Tserruya, I., Tsuchimoto, Y., Ujvari, B., Vale, C., Valle, H., van Hecke, H. W., Veicht, A., Velkovska, J., Vinogradov, A. A., Virius, M., Vrba, V., Vznuzdaev, E., Vértesi, R., Wang, X. R., Watanabe, Y., Watanabe, Y. S., Wei, F., Wessels, J., White, A. S., White, S. N., Winter, D., Wong, C. P., Woody, C. L., Wysocki, M., Xia, B., Xie, W., Xue, L., Yalcin, S., Yamaguchi, Y. L., Yamaura, K., Yang, R., Yanovich, A., Ying, J., Yokkaichi, S., Yoon, I., Yoo, J. H., Young, G. R., Younus, I., Yushmanov, I. E., Yu, H., Zajc, W. A., Zaudtke, O., Zelenski, A., Zhang, C., Zhou, S., Zolin, L., and Zou, L.
Subjects: Nuclear Experiment
Abstract: High-momentum two-particle correlations are a useful tool for studying jet-quenching effects in the quark-gluon plasma. Angular correlations between neutral-pion triggers and charged hadrons with transverse momenta in the range 4--12~GeV/$c$ and 0.5--7~GeV/$c$, respectively, have been measured by the PHENIX experiment in 2014 for Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$~GeV. Suppression is observed in the yield of high-momentum jet fragments opposite the trigger particle, which indicates jet suppression stemming from in-medium partonic energy loss, while enhancement is observed for low-momentum particles. The ratio and differences between the yield in Au$+$Au collisions and $p$$+$$p$ collisions, $I_{AA}$ and $\Delta_{AA}$, as a function of the trigger-hadron azimuthal separation, $\Delta\phi$, are measured for the first time at the Relativistic Heavy Ion Collider. These results better quantify how the yield of low-$p_T$ associated hadrons is enhanced at wide angle, which is crucial for studying energy loss as well as medium-response effects., Comment: 535 authors from 84 institutions, 12 pages, 8 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2024
Full Text: View/download PDF

8. Global drive toward net-zero emissions and sustainability via electric vehicles: an integrative critical review

Author: Timilsina, Raja Rajendra, Zhang, Jingchao, Rahut, Dil B, Patradool, Kaewupsorn, and Sonobe, Tetsushi
Published: 2025
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9. New evidence on the health and employment effects of non-pharmaceutical COVID-19 interventions on workers in the United States

Author: Aksu, Ege, De, Prabal K., and Timilsina, Laxman
Published: 2024
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10. The diversity and nesting preferences of birds along an urban-rural gradient in the Kathmandu Valley, Nepal

Author: Bhusal, Dinesh, Ghimire, Prashant, Low, Matthew, Rosin, Zuzanna M., and Timilsina, Yajna Prasad
Published: 2025
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11. Soil erosion estimation in the Bagmati River basin of Nepal using RUSLE modeling to assess priority areas for conservation

Author: Gelal, Devendra, Timilsina, Sachin, Ayer, Santosh, Bhatta, Kishor Prasad, Manandhar, Bikram, and Maharjan, Menuka
Published: 2024
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12. Maize-soybean intercropping reduces greenhouse gas emissions from the fertilized soil in the North China Plain

Author: Raseduzzaman, Md, Dong, Wenxu, Gaudel, Gokul, Aluoch, Stephen Okoth, Timilsina, Arbindra, Li, Xiaoxin, and Hu, Chunsheng
Published: 2024
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13. Identified charged-hadron production in $p$$+$Al, $^3$He$+$Au, and Cu$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV and in U$+$U collisions at $\sqrt{s_{_{NN}}}=193$ GeV

Author: PHENIX Collaboration, Abdulameer, N. J., Acharya, U., Adare, A., Aidala, C., Ajitanand, N. N., Akiba, Y., Akimoto, R., Alexander, J., Alfred, M., Andrieux, V., Aoki, K., Apadula, N., Asano, H., Atomssa, E. T., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Bai, X., Bandara, N. S., Bannier, B., Barish, K. N., Bathe, S., Baublis, V., Baumann, C., Baumgart, S., Bazilevsky, A., Beaumier, M., Beckman, S., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Black, D., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Boyle, K., Brooks, M. L., Bryslawskyj, J., Buesching, H., Bumazhnov, V., Butsyk, S., Campbell, S., Roman, V. Canoa, Cervantes, R., Chen, C. -H., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choi, S., Christiansen, P., Chujo, T., Cianciolo, V., Citron, Z., Cole, B. A., Connors, M., Corliss, R., Morales, Y. Corrales, Cronin, N., Crossette, N., Csanád, M., Csörgő, T., D'Orazio, L., Danley, T. W., Datta, A., Daugherity, M. S., David, G., Dean, C. T., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Ding, L., Dion, A., Diss, P. B., Dixit, D., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fleuret, F., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukao, Y., Fukuda, Y., Fusayasu, T., Gainey, K., Gallus, P., Gal, C., Garg, P., Garishvili, A., Garishvili, I., Ge, H., Giles, M., Giordano, F., Glenn, A., Gong, X., Gonin, M., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gu, Y., Gunji, T., Guo, T., Guragain, H., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Harvey, M., Hasegawa, S., Haseler, T. O. S., Hashimoto, K., Hayano, R., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Ichihara, T., Ikeda, Y., Imai, K., Imazu, Y., Inaba, M., Iordanova, A., Isenhower, D., Isinhue, A., Ivanishchev, D., Jacak, B. V., Jeon, S. J., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Joo, K. S., Jouan, D., Jumper, D. S., Kamin, J., Kanda, S., Kang, B. H., Kang, J. H., Kang, J. S., Kapukchyan, D., Kapustinsky, J., Karthas, S., Kawall, D., Kazantsev, A. V., Key, J. A., Khachatryan, V., Khandai, P. K., Khanzadeev, A., Khatiwada, A., Kijima, K. M., Kimelman, B., Kim, C., Kim, D. J., Kim, E. -J., Kim, G. W., Kim, M., Kim, T., Kim, Y. -J., Kim, Y. K., Kincses, D., Kingan, A., Kistenev, E., Kitamura, R., Klatsky, J., Kleinjan, D., Kline, P., Koblesky, T., Kofarago, M., Komkov, B., Koster, J., Kotchetkov, D., Kotov, D., Kovacs, L., Krizek, F., Kudo, S., Kurgyis, B., Kurita, K., Kurosawa, M., Kwon, Y., Lai, Y. S., Lajoie, J. G., Larionova, D., Lebedev, A., Lee, D. M., Lee, G. H., Lee, J., Lee, K. B., Lee, K. S., Lee, S., Lee, S. H., Leitch, M. J., Leitgab, M., Leung, Y. H., Lewis, B., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Loomis, D. A., Lovasz, K., Lynch, D., Lökös, S., Maguire, C. F., Majoros, T., Makdisi, Y. I., Makek, M., Manion, A., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Meles, A., Mendoza, M., Meredith, B., Miake, Y., Mibe, T., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mohanty, A. K., Mohapatra, S., Mondal, M. M., Montuenga, P., Moon, T., Morrison, D. P., Moskowitz, M., Moukhanova, T. V., Muhammad, A., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagae, T., Nagai, K., Nagamiya, S., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakamiya, Y., Nakamura, K. R., Nakamura, T., Nakano, K., Nattrass, C., Nelson, S., Netrakanti, P. K., Nihashi, M., Niida, T., Nishimura, S., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oh, J., Oide, H., Okada, K., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pak, R., Pantuev, V., Papavassiliou, V., Park, I. H., Park, J. S., Park, S., Park, S. K., Patel, L., Patel, M., Pate, S. F., Peng, J. -C., Peng, W., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pinson, R., Pisani, R. P., Potekhin, M., Pun, A., Purschke, M. L., Qu, H., Radzevich, P. V., Rak, J., Ramasubramanian, N., Ramson, B. J., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richardson, E., Richford, D., Rinn, T., Riveli, N., Roach, D., Rolnick, S. D., Rosati, M., Rowan, Z., Rubin, J. G., Runchey, J., Ryu, M. S., Safonov, A. S., Sahlmueller, B., Saito, N., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sawada, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seele, J., Seidl, R., Sekiguchi, Y., Sen, A., Seto, R., Sett, P., Sexton, A., Sharma, D., Shaver, A., Shein, I., Shibata, M., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shi, Z., Shoji, K., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, V., Skolnik, M., Slunečka, M., Smith, K. L., Snowball, M., Solano, S., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Steinberg, P., Stenlund, E., Stepanov, M., Ster, A., Stoll, S. P., Stone, M. R., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takahama, R., Takahara, A., Taketani, A., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tennant, E., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Torii, H., Towell, C. L., Towell, R., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Vargyas, M., Vazquez-Zambrano, E., Veicht, A., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Vznuzdaev, E., Vértesi, R., Wang, X. R., Wang, Z., Watanabe, D., Watanabe, K., Watanabe, Y., Watanabe, Y. S., Wei, F., Whitaker, S., White, A. S., Wolin, S., Wong, C. P., Woody, C. L., Wysocki, M., Xia, B., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yokkaichi, S., Yoon, I., Yoo, J. H., Younus, I., You, Z., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., Zhou, S., and Zou, L.
Subjects: Nuclear Experiment
Abstract: The PHENIX experiment has performed a systematic study of identified charged-hadron ($\pi^\pm$, $K^\pm$, $p$, $\bar{p}$) production at midrapidity in $p$$+$Al, $^3$He$+$Au, Cu$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV and U$+$U collisions at $\sqrt{s_{_{NN}}}=193$ GeV. Identified charged-hadron invariant transverse-momentum ($p_T$) and transverse-mass ($m_T$) spectra are presented and interpreted in terms of radially expanding thermalized systems. The particle ratios of $K/\pi$ and $p/\pi$ have been measured in different centrality ranges of large (Cu$+$Au, U$+$U) and small ($p$$+$Al, $^3$He$+$Au) collision systems. The values of $K/\pi$ ratios measured in all considered collision systems were found to be consistent with those measured in $p$$+$$p$ collisions. However the values of $p/\pi$ ratios measured in large collision systems reach the values of $\approx0.6$, which is $\approx2$ times larger than in $p$$+$$p$ collisions. These results can be qualitatively understood in terms of the baryon enhancement expected from hadronization by recombination. Identified charged-hadron nuclear-modification factors ($R_{AB}$) are also presented. Enhancement of proton $R_{AB}$ values over meson $R_{AB}$ values was observed in central $^3$He$+$Au, Cu$+$Au, and U$+$U collisions. The proton $R_{AB}$ values measured in $p$$+$Al collision system were found to be consistent with $R_{AB}$ values of $\phi$, $\pi^\pm$, $K^\pm$, and $\pi^0$ mesons, which may indicate that the size of the system produced in $p$$+$Al collisions is too small for recombination to cause a noticeable increase in proton production., Comment: 480 authors from 78 institutions, 18 pages, 6 tables, 16 figures. v2 is version accepted for publication in Physical Review C. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2023
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14. Association between blood hemoglobin levels, anemia, and body mass index in children and women of Myanmar: findings from a nationally representative health study

Author: Acharya, Shiva Raj, Timilsina, Diwash, and Acharya, Sabitri
Published: 2024
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15. Antenatal depression among pregnant mothers in Afghanistan: A cross-sectional study

Author: Sarem, Shararah, Neyazi, Ahmad, Mohammadi, Abdul Qadim, Neyazi, Mehrab, Ahamdi, Mozhgan, Razaqi, Nosaibah, Wali, Sadaf, Timilsina, Shashank, Faizi, Hamida, and Griffiths, Mark D.
Published: 2024
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16. Enhancing food and nutrition security in Himalayan foothills with neglected and underutilized millets

Author: Raja Rajendra Timilsina, Hari Prashad Joshi, and Dil Bahadur Rahut
Subjects: Food security, Nutrition security, Himalayan foothills, Millet potential, Climate-resilient crops, Sustainable agriculture, Medicine, Science
Abstract: Abstract Global food production predominantly depends on a limited number of cereal crops; however, numerous other crops have the potential to support the nutrition and economy of many local communities in developing countries. The different crop species characterized as having relatively low perceived economic importance or agricultural significance are known as underutilized crops. Millet is one of the underutilized crops with significant potential to address nutrient and hunger-related challenges in many developing countries like Nepal due to its versatility and climate resilience. Little is known about the determinants of adoption, cultural importance, and nutritional benefits of millet. Therefore, this study uses data from 1988 to 2019 and examines trends in millet production and its climate resilience, employing the Dynamic Ordinary Least Square Method. Results indicate that fertilizer use, cultivated area, and rural population significantly impact millet production in Nepal, while mean temperature has a negative but insignificant effect. The findings suggest that climate change does not significantly impact millet production. Millet is well adapted to challenging environments and offers superior nutritional value, suggesting that integration of millet into modern agriculture could be a valuable tool for creating a more sustainable, equitable, resilient, and healthy agrifood system that benefits both people and the planet. This research provides valuable insights for policymakers to enhance underutilized crops such as millet and implement strategies to integrate them into central agrifood systems. It also has a more considerable socio-economic impact on local communities.
Published: 2025
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17. Cereal-legume intercropping enhances the quality of feedstock for lignocellulosic bioethanol production by reducing the carbon: nitrogen ratio

Author: Md Raseduzzaman, Gokul Gaudel, Stephen Okoth Aluoch, and Arbindra Timilsina
Subjects: Second-generation bioethanol, Lignocellulosic biomass, C/N ratio, Clover-grass, Undersown legume, Cereal-legume intercropping, Agriculture (General), S1-972, Environmental sciences, GE1-350
Abstract: Abstract Bioethanol production from cereal straw is a sustainable alternative to meet the current energy demand, but its low nitrogen (N) content and high carbon to nitrogen (C/N) ratio are problematic during bioethanol processing. Intercropping cereals with legumes may increase the N content and reduce the C/N ratio in the harvested straw biomass. In order to investigate the combined production of food, feed, and suitable feedstock (low C/N ratio) for lignocellulosic bioethanol production, a field experiment on cereal-legume intercropping was carried out in southern Sweden. In the experiment, autumn-sown cereals (wheat, triticale, and rye) were grown as monocrops with two different N fertilization levels (60 and 120 kg N ha−1) or intercropped with autumn-sown or spring-sown (undersown) clover-grass, autumn-sown or spring-sown (undersown) alfalfa, or autumn-sown faba bean. Total grain dry matter yield, cereal grain protein content, straw dry matter yield, and straw biomass C/N ratio were estimated. The results showed that the intercrops produced more straw biomass and had a lower C/N ratio, but produced less grain, than cereal monocrops. Among the cereals, rye showed significantly higher grain and straw yields, but lower grain protein content, in all treatments. Among the intercrop treatments, cereal with spring-sown clover-grass produced higher grain and straw yields and had a significantly lower C/N ratio (38:1) than the other treatments. Thus, cereal with spring-sown (undersown) clover-grass is a promising cropping system for lignocellulosic bioethanol production.
Published: 2025
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18. Interspecies Expression of an EF-HAND CALCIUM-BINDING PROTEIN in Xanthomonas perforans Leads to Reduced Virulence and Decreased Immune Evasion in Tomato Plants

Author: Shaheen Bibi, Gerald V. Minsavage, J. Figueiredo, Sujan Timilsina, Kayla Margin, Juliana Quay, Hannah Bendure, Elizabeth Ryerson, Cliff Calloway, Jacob Andring, Aastha Subedi, Robert McKenna, Paul Gulig, Erica M. Goss, Jason C. Hurlbert, and Jeffrey B. Jones
Subjects: calcium, hypersensitivity, tomato, type III secretion system (TTSS), Xanthomonas, Microbiology, QR1-502, Botany, QK1-989
Abstract: Many phytopathogenic bacteria require a type III secretion system (TTSS) to activate effector-triggered immunity (ETI). We identified a calcium-binding protein, EfhXXfa, in the citrus pathogen Xanthomonas citri subsp. aurantifolii that does not require a TTSS to activate reactive oxygen species (ROS) and elicit a hypersensitive reaction (HR) in tomato leaves following infection. Purified, recombinant EfhXXfa was shown to bind two moles of calcium per mole of protein, whereas mutation of the first of two EF-hands did not bind calcium. EfhXXfa expression was determined to be inducible in hrp-inducing medium. Additionally, growth of X. perforans transconjugants with and without the efhXXfa gene in hrp-inducing medium differed in intracellular calcium concentration; the transconjugant without efhXXfa yielded higher cell pellet masses and higher increased intracellular calcium concentrations relative to cells expressing EfhXXfa. An EfhXXfa homolog, EfhXXe, present in the pepper pathogen X. euvesicatoria, triggered ROS production and an HR in tomato leaves when expressed in the tomato pathogen X. perforans and is a host-limiting factor. Interestingly, all tested X. perforans and X. euvesicatoria strains pathogenic on tomato contain a stop codon immediately upstream of the first EF-hand domain in the efhXXe gene, whereas most X. euvesicatoria strains pathogenic on pepper do not. [Figure: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Published: 2024
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19. Ecological impact and community perception of Phoenix acaulis (Roxb.) management in Shorea robusta (Garten. f.) forest of Udayapur district, Nepal

Author: Santosh Ayer, Kishor Prasad Bhatta, Sachin Timilsina, Renuka Khamcha, Janak Airee, Prakash Chaudhary, Yajna Timilsina, Sagar Bhatta, and Hari Adhikari
Subjects: Environmental attitudes, Forest inventory, Forest management, Impact assessment, Species interaction, Understory vegetation, Forestry, SD1-669.5, Plant ecology, QK900-989
Abstract: Phoenix acaulis (Roxb.), a common understory shrub in Nepal's Chure region, has remained largely understudied until now. Therefore, this study aims to examine the ecological impact of P. acaulis on Shorea robusta (Gaertn. f.) forest properties and to explore associated community perceptions in S. robusta forest of Udayapur district, Nepal. Stratified random sampling was adopted for this study where P. acaulis density (high, low and absent) was considered as basis of stratification. Altogether, 45 rectangular plots of 10 m x 10 m area (15 each category) were established for regeneration survey and soil sample collection (up to 30 cm). Soil quality index (SQI) method was used for soil quality assessment using indicators on the basis of prior studies conducted in Nepal. Using random sampling, a total of 52 households from the community forest user group were interviewed to gather their insights on the perceived effects of P. acaulis and its management. Highest S. robusta seedling and sapling density was observed in P. acaulis absent area (1132 ± 9.65 ha⁻¹ and 60 ± 0.63 ha⁻¹) where lowest in P. acaulis dense area (548 ± 7.4 ha⁻¹ and 4 ± 0.2 ha⁻¹). Similarly, higher SQI was in areas with high P. acaulis density (0.49) followed by low (0.45) and absent area (0.39). Most respondents advocated for removing P. acaulis from the forest, highlighting significant concerns among stakeholders. Our study suggests a positive impact P. acaulis on soil quality but indicates a negative impact on S. robusta regeneration. Therefore, further research to explore management strategies that balance the positive impact on soil quality with the observed negative influence on regeneration in P. acaulis presence areas is recommended.
Published: 2024
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20. Selective Inhibition of mTORC1 Signaling Supports the Development and Maintenance of Pluripotency.

Author: Kim, Jin, Villa-Diaz, Luis, Saunders, Thomas, Saul, Ruiz, Timilsina, Suraj, Liu, Fei, Mishina, Yuji, and Krebsbach, Paul
Subjects: 4E-BP1, S6, S6K, human pluripotent stem cells, inner cell mass, pluripotency-related transcription factors, Humans, Animals, Mice, Signal Transduction, Blastocyst, Sirolimus, Phosphorylation, Mechanistic Target of Rapamycin Complex 1
Abstract: Insight into the molecular mechanisms governing the development and maintenance of pluripotency is important for understanding early development and the use of stem cells in regenerative medicine. We demonstrate the selective inhibition of mTORC1 signaling is important for developing the inner cell mass (ICM) and the self-renewal of human embryonic stem cells. S6K suppressed the expression and function of pluripotency-related transcription factors (PTFs) OCT4, SOX2, and KLF4 through phosphorylation and ubiquitin proteasome-mediated protein degradation, indicating that S6K inhibition is required for pluripotency. PTFs inhibited mTOR signaling. The phosphorylation of S6 was decreased in PTF-positive cells of the ICM in embryos. Activation of mTORC1 signaling blocked ICM formation and the selective inhibition of S6K by rapamycin increased the ICM size in mouse blastocysts. Thus, selective inhibition of mTORC1 signaling supports the development and maintenance of pluripotency.
Published: 2024

21. Towards making EIA more human-centric: Demonstration in Nepal of a values crystallization approach to capture local shared values for scoping use

Author: Pazhoor, Shehanas, Pandey, Swastik, Palmer, David A., Timilsina, Biraj, Huang, Yanyan, Zhang, Yangcheng, Gaire, Bikas, Timilsina, Bikram, Marasini, Rajesh, and Harder, Marie K.
Published: 2025
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22. Hypertension, depression, and health-related quality of life among hospitalized patients in Afghanistan

Author: Neyazi, Ahmad, Mohammadi, Abdul Qadim, Neyazi, Mehrab, Timilsina, Shashank, Padhi, Bijaya Kumar, and Griffiths, Mark D.
Published: 2024
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23. Phylodynamic Insights into Global Emergence and Diversification of the Tomato Pathogen Xanthomonas hortorum pv. gardneri

Author: Mustafa O. Jibrin, Anuj Sharma, Carla N. Mavian, Sujan Timilsina, Amandeep Kaur, Fernanda Iruegas-Bocardo, Neha Potnis, Gerald V. Minsavage, Teresa A. Coutinho, Tom C. Creswell, Daniel S. Egel, David M. Francis, Misrak Kebede, Sally A. Miller, María J. Montelongo, Ekaterina Nikolaeva, María J. Pianzzola, Olivier Pruvost, Alice M. Quezado-Duval, Gail E. Ruhl, Vou M. Shutt, Elizabeth Maynard, Diego C. Maeso, María I. Siri, Cheryl L. Trueman, Marco Salemi, Gary E. Vallad, Pamela D. Roberts, Jeffrey B. Jones, and Erica M. Goss
Subjects: bacterial plant pathogen, genome evolution, phylodynamics, Microbiology, QR1-502, Botany, QK1-989
Abstract: The emergence of plant pathogens is often associated with waves of unique evolutionary and epidemiological events. Xanthomonas hortorum pv. gardneri is one of the major pathogens causing bacterial spot disease of tomatoes. After its first report in the 1950s, there were no formal reports on this pathogen until the 1990s, despite active global research on the pathogens that cause tomato and pepper bacterial spot disease. Given the recently documented global distribution of X. hortorum pv. gardneri, our objective was to examine genomic diversification associated with its emergence. We sequenced the genomes of X. hortorum pv. gardneri strains collected in eight countries to examine global population structure and pathways of emergence using phylodynamic analysis. We found that strains isolated post-1990 group by region of collection and show minimal impact of recombination on genetic variation. A period of rapid geographic expansion in X. hortorum pv. gardneri is associated with acquisition of a large plasmid conferring copper tolerance by horizontal transfer and coincides with the burgeoning hybrid tomato seed industry through the 1980s. The ancestry of X. hortorum pv. gardneri is consistent with introduction to hybrid tomato seed production and dissemination during the rapid increase in trade of hybrid seeds. [Figure: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Published: 2024
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24. Early Identification and Management of Ulcerative Colitis: A Narrative Review

Author: Dimple V Nandurkar, Manju Chandankhede, Dilip Timilsina, Shweta Borkar, and Nandkishor Bankar
Subjects: colorectal cancer, diagnostic delay, inflammatory bowel disease, Medicine
Abstract: Ulcerative Colitis (UC) is a chronic Inflammatory Bowel Disease (IBD) that affects the inner lining of the colon, imposing a significant burden on healthcare systems worldwide. Symptoms include bloody stools and abdominal pain. The prevalence of UC is increasing, particularly among young adults. The pathogenesis involves immune responses, genetics and environmental factors. Diagnostic delays are common, leading to complications and increased costs. Early diagnosis is crucial for preventing complications. Endoscopy is the primary diagnostic tool. Treatment aims to reduce inflammation and achieve remission. Delayed diagnosis can lead to long-term complications such as Colorectal Cancer (CRC) and bowel stenosis. Prompt recognition and management are essential for minimising the disease burden and optimising care. The present study delves into the complex nature of UC, a chronic IBD, revealing its epidemiology, pathogenesis, diagnostic challenges, treatment strategies, prognosis, complications and the impact of delayed diagnosis on patients’ quality of life. The study highlights the evolving understanding of UC pathogenesis, incorporating immune responses, genetics, environmental factors and biomarkers. It also discusses diagnostic delays due to symptom similarities and the need for increased awareness among healthcare providers and the public. The study also discusses advanced diagnostic methods and therapeutic approaches, including novel drug targets and surgical interventions. It also highlights the negative consequences of delayed diagnosis, including increased morbidity, psychological distress and socioeconomic burden. The study emphasises the need for collaborative efforts to ensure timely and appropriate care for UC patients.
Published: 2024
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25. $\textit{e-Uber}$: A Crowdsourcing Platform for Electric Vehicle-based Ride- and Energy-sharing

Author: Timilsina, Ashutosh and Silvestri, Simone
Subjects: Computer Science - Artificial Intelligence, Computer Science - Computer Science and Game Theory, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Systems and Control
Abstract: The sharing-economy-based business model has recently seen success in the transportation and accommodation sectors with companies like Uber and Airbnb. There is growing interest in applying this model to energy systems, with modalities like peer-to-peer (P2P) Energy Trading, Electric Vehicles (EV)-based Vehicle-to-Grid (V2G), Vehicle-to-Home (V2H), Vehicle-to-Vehicle (V2V), and Battery Swapping Technology (BST). In this work, we exploit the increasing diffusion of EVs to realize a crowdsourcing platform called e-Uber that jointly enables ride-sharing and energy-sharing through V2G and BST. e-Uber exploits spatial crowdsourcing, reinforcement learning, and reverse auction theory. Specifically, the platform uses reinforcement learning to understand the drivers' preferences towards different ride-sharing and energy-sharing tasks. Based on these preferences, a personalized list is recommended to each driver through CMAB-based Algorithm for task Recommendation System (CARS). Drivers bid on their preferred tasks in their list in a reverse auction fashion. Then e-Uber solves the task assignment optimization problem that minimizes cost and guarantees V2G energy requirement. We prove that this problem is NP-hard and introduce a bipartite matching-inspired heuristic, Bipartite Matching-based Winner selection (BMW), that has polynomial time complexity. Results from experiments using real data from NYC taxi trips and energy consumption show that e-Uber performs close to the optimum and finds better solutions compared to a state-of-the-art approach, Comment: Preprint, under review
Published: 2023

26. Disentangling centrality bias and final-state effects in the production of high-$p_T$ $\pi^0$ using direct $\gamma$ in $d$$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV

Author: Abdulameer, N. J., Acharya, U., Aidala, C., Akiba, Y., Alfred, M., Aoki, K., Apadula, N., Ayuso, C., Babintsev, V., Barish, K. N., Bathe, S., Bazilevsky, A., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Boer, M., Bok, J. S., Borisov, V., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Butler, C., Campbell, S., Roman, V. Canoa, Chiu, M., Connors, M., Corliss, R., Morales, Y. Corrales, Csanád, M., Csörgő, T., Liu, L. D., Danley, T. W., Daugherity, M. S., David, G., Dean, C. T., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Dumancic, M., Durham, J. M., Durum, A., Elder, T., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gal, C., Garg, P., Ge, H., Giles, M., Goto, Y., Grau, N., Greene, S. V., Gunji, T., Hachiya, T., Haggerty, J. S., Hahn, K. I., Han, S. Y., Harvey, M., Hasegawa, S., Haseler, T. O. S., Hemmick, T. K., He, X., Hill, K., Hodges, A., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imrek, J., Inaba, M., Isenhower, D., Ito, Y., Ivanishchev, D., Jacak, B. V., Ji, Z., Johnson, B. M., Jorjadze, V., Jouan, D., Jumper, D. S., Kang, J. H., Kapukchyan, D., Karthas, S., Kazantsev, A. V., Khachatryan, V., Khanzadeev, A., Khatiwada, A., Kim, C., Kim, D. J., Kim, E. -J., Kim, M., Kim, M. H., Kim, T., Kincses, D., Kingan, A., Kistenev, E., Koblesky, T., Kotov, D., Kovacs, L., Kudo, S., Kurgyis, B., Kurita, K., Lajoie, J. G., Lallow, E. O., Larionova, D., Lebedev, A., Lee, S. H., Leitch, M. J., Leung, Y. H., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Loomis, D. A., Lynch, D., Lökös, S., Majoros, T., Makek, M., Malaev, M., Manko, V. I., Mannel, E., Masuda, H., McCumber, M., McGlinchey, D., Mignerey, A. C., Mihalik, D. E., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Mondal, M. M., Moon, T., Morrison, D. P., Morrow, S. I., Muhammad, A., Mulilo, B., Murakami, T., Murata, J., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakagomi, H., Nakano, K., Nattrass, C., Nelson, S., Nouicer, R., Novitzky, N., Novotny, R., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oh, J., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ozawa, K., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Peng, W., Perepelitsa, D. V., Perera, G. D. N., PerezLara, C. E., Petti, R., Phipps, M., Pinkenburg, C., Potekhin, M., Pun, A., Purschke, M. L., Radzevich, P. V., Ramasubramanian, N., Read, K. F., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rosati, M., Rowan, Z., Runchey, J., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, K., Sato, S., Schaefer, B., Schmoll, B. K., Seidl, R., Sen, A., Seto, R., Sexton, A., Sharma, D., Shein, I., Shibata, M., Shibata, T. -A., Shigaki, K., Shimomura, M., Shi, Z., Silva, C. L., Silvermyr, D., Slunečka, M., Smith, K. L., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stoll, S. P., Sugitate, T., Sukhanov, A., Sun, Z., Syed, S., Takahama, R., Takeda, A., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Vazquez-Carson, S., Velkovska, J., Virius, M., Vrba, V., Wang, X. R., Wang, Z., Watanabe, Y., Wong, C. P., Xu, C., Xu, Q., Yamaguchi, Y. L., Yanovich, A., Yin, P., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., and Zou, L.
Subjects: Nuclear Experiment
Abstract: PHENIX presents a simultaneous measurement of the production of direct $\gamma$ and $\pi^0$ in $d$$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV over a $p_T$ range of 7.5 to 18 GeV/$c$ for different event samples selected by event activity, i.e. charged-particle multiplicity detected at forward rapidity. Direct-photon yields are used to empirically estimate the contribution of hard-scattering processes in the different event samples. Using this estimate, the average nuclear-modification factor $R_{d\rm Au,EXP}^{\gamma^{\rm dir}}$ is $0.925{\pm}0.023({\rm stat}){\pm}0.15^{\rm (scale)}$, consistent with unity for minimum-bias (MB) $d$$+$Au events. For event classes with moderate event activity, $R_{d\rm Au,EXP}^{\gamma^{\rm dir}}$ is consistent with the MB value within 5\% uncertainty. These results confirm that the previously observed enhancement of high-$p_T$ $\pi^0$ production found in small-system collisions with low event activity is a result of a bias in interpreting event activity within the Glauber framework. In contrast, for the top 5\% of events with the highest event activity, $R_{d\rm Au,EXP}^{\gamma^{\rm dir}}$ is suppressed by 20\% relative to the MB value with a significance of $4.5\sigma$, which may be due to final-state effects., Comment: 279 authors from 69 institutions, 8 pages, 3 figures, v2 is version accepted for publication in Physical Review Letters. HEPdata tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2023
Full Text: View/download PDF

27. Transverse single-spin asymmetry of charged hadrons at forward and backward rapidity in polarized $p$+$p$, $p$+Al, and $p$+Au collisions at $\sqrt{s_{NN}}=200$ GeV}

Author: Abdulameer, N. J., Acharya, U., Aidala, C., Akiba, Y., Alfred, M., Andrieux, V., Apadula, N., Asano, H., Azmoun, B., Babintsev, V., Bandara, N. S., Barish, K. N., Bathe, S., Bazilevsky, A., Beaumier, M., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Campbell, S., Roman, V. Canoa, Cervantes, R., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Citron, Z., Connors, M., Corliss, R., Morales, Y. Corrales, Cronin, N., Csanád, M., Csörgő, T., Danley, T. W., Daugherity, M. S., David, G., Dean, C. T., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dion, A., Dixit, D., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gallus, P., Gal, C., Garg, P., Ge, H., Giles, M., Giordano, F., Goto, Y., Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guragain, H., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Harvey, M., Hasegawa, S., Haseler, T. O. S., Hemmick, T. K., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imai, K., Inaba, M., Iordanova, A., Isenhower, D., Ivanishchev, D., Jacak, B. V., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Jouan, D., Jumper, D. S., Kang, J. H., Kapukchyan, D., Karthas, S., Kawall, D., Kazantsev, A. V., Khachatryan, V., Khanzadeev, A., Khatiwada, A., Kim, C., Kim, E. -J., Kim, M., Kim, T., Kincses, D., Kingan, A., Kistenev, E., Klatsky, J., Kline, P., Koblesky, T., Kotov, D., Kovacs, L., Kudo, S., Kurgyis, B., Kurita, K., Kwon, Y., Lajoie, J. G., Larionova, D., Lebedev, A., Lee, S., Lee, S. H., Leitch, M. J., Leung, Y. H., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Loomis, D. A., Lovasz, K., Lynch, D., Lökös, S., Majoros, T., Makdisi, Y. I., Makek, M., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Mendoza, M., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mondal, M. M., Montuenga, P., Moon, T., Morrison, D. P., Muhammad, A., Mulilo, B., Murakami, T., Murata, J., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakano, K., Nattrass, C., Nelson, S., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oh, J., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Peng, W., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pisani, R. P., Potekhin, M., Pun, A., Purschke, M. L., Radzevich, P. V., Ramasubramanian, N., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rolnick, S. D., Rosati, M., Rowan, Z., Runchey, J., Safonov, A. S., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seidl, R., Sen, A., Seto, R., Sexton, A., Sharma, D., Shein, I., Shibata, M., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shi, Z., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stoll, S. P., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takahama, R., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Wang, X. R., Wang, Z., Watanabe, Y. S., Wong, C. P., Woody, C. L., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., and Zou, L.
Subjects: High Energy Physics - Experiment
Abstract: Reported here are transverse single-spin asymmetries ($A_{N}$) in the production of charged hadrons as a function of transverse momentum ($p_T$) and Feynman-$x$ ($x_F$) in polarized $p^{\uparrow}$+$p$, $p^{\uparrow}$+Al, and $p^{\uparrow}$+Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV. The measurements have been performed at forward and backward rapidity ($1.4<|\eta|<2.4$) over the range of $1.50$) in $p^{\uparrow}$+$p$ collisions, whereas the $p^{\uparrow}$+Al and $p^{\uparrow}$+Au results show smaller asymmetries. This finding provides new opportunities to investigate the origin of transverse single-spin asymmetries and a tool to study nuclear effects in $p$+$A$ collisions., Comment: 322 authors from 70 institutions, 13 pages, 9 figures, 13 tables, one appendix, 2015 data. v2 is version accepted for publication in Phys. Rev. D. HEPData tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2023
Full Text: View/download PDF

28. Transverse single-spin asymmetry of midrapidity $\pi^{0}$ and $\eta$ mesons in $p$+Au and $p$+Al collisions at $\sqrt{s_{_{NN}}}=$ 200 GeV

Author: Abdulameer, N. J., Acharya, U., Aidala, C., Akiba, Y., Alfred, M., Andrieux, V., Apadula, N., Asano, H., Azmoun, B., Babintsev, V., Bandara, N. S., Barish, K. N., Bathe, S., Bazilevsky, A., Beaumier, M., Belmont, R., Berdnikov, A., Berdnikov, Y., Bichon, L., Blankenship, B., Blau, D. S., Bok, J. S., Borisov, V., Brooks, M. L., Bryslawskyj, J., Bumazhnov, V., Campbell, S., Roman, V. Canoa, Cervantes, R., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Citron, Z., Connors, M., Corliss, R., Morales, Y. Corrales, Cronin, N., Csanád, M., Csörgő, T., Danley, T. W., Daugherity, M. S., David, G., Dean, C. T., DeBlasio, K., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Dion, A., Dixit, D., Doomra, V., Do, J. H., Drees, A., Drees, K. A., Durham, J. M., Durum, A., En'yo, H., Enokizono, A., Esha, R., Fadem, B., Fan, W., Feege, N., Fields, D. E., Finger, Jr., M., Finger, M., Firak, D., Fitzgerald, D., Fokin, S. L., Frantz, J. E., Franz, A., Frawley, A. D., Fukuda, Y., Gallus, P., Gal, C., Garg, P., Ge, H., Giles, M., Giordano, F., Goto, Y., Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guragain, H., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hamilton, H. F., Hanks, J., Han, S. Y., Harvey, M., Hasegawa, S., Haseler, T. O. S., Hemmick, T. K., He, X., Hill, J. C., Hill, K., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., Hotvedt, N., Huang, J., Imai, K., Inaba, M., Iordanova, A., Isenhower, D., Ivanishchev, D., Jacak, B. V., Jezghani, M., Jiang, X., Ji, Z., Johnson, B. M., Jouan, D., Jumper, D. S., Kang, J. H., Kapukchyan, D., Karthas, S., Kawall, D., Kazantsev, A. V., Khachatryan, V., Khanzadeev, A., Khatiwada, A., Kim, C., Kim, E. -J., Kim, M., Kim, T., Kincses, D., Kingan, A., Kistenev, E., Klatsky, J., Kline, P., Koblesky, T., Kotov, D., Kovacs, L., Kudo, S., Kurgyis, B., Kurita, K., Kwon, Y., Lajoie, J. G., Larionova, D., Lebedev, A., Lee, S., Lee, S. H., Leitch, M. J., Leung, Y. H., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loggins, V. -R., Loomis, D. A., Lovasz, K., Lynch, D., Lökös, S., Majoros, T., Makdisi, Y. I., Makek, M., Manko, V. I., Mannel, E., McCumber, M., McGaughey, P. L., McGlinchey, D., McKinney, C., Mendoza, M., Mignerey, A. C., Milov, A., Mishra, D. K., Mitchell, J. T., Mitrankova, M., Mitrankov, Iu., Mitsuka, G., Miyasaka, S., Mizuno, S., Mondal, M. M., Montuenga, P., Moon, T., Morrison, D. P., Muhammad, A., Mulilo, B., Murakami, T., Murata, J., Nagai, K., Nagashima, K., Nagashima, T., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakano, K., Nattrass, C., Nelson, S., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oh, J., Koop, J. D. Orjuela, Orosz, M., Osborn, J. D., Oskarsson, A., Ottino, G. J., Ozawa, K., Pantuev, V., Papavassiliou, V., Park, J. S., Park, S., Patel, M., Pate, S. F., Peng, W., Perepelitsa, D. V., Perera, G. D. N., Peressounko, D. Yu., PerezLara, C. E., Perry, J., Petti, R., Phipps, M., Pinkenburg, C., Pisani, R. P., Potekhin, M., Pun, A., Purschke, M. L., Radzevich, P. V., Ramasubramanian, N., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richford, D., Rinn, T., Rolnick, S. D., Rosati, M., Rowan, Z., Runchey, J., Safonov, A. S., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Schaefer, B., Schmoll, B. K., Sedgwick, K., Seidl, R., Sen, A., Seto, R., Sexton, A., Sharma, D., Shein, I., Shibata, M., Shibata, T. -A., Shigaki, K., Shimomura, M., Shioya, T., Shi, Z., Shukla, P., Sickles, A., Silva, C. L., Silvermyr, D., Singh, B. K., Singh, C. P., Singh, V., Slunečka, M., Smith, K. L., Snowball, M., Soltz, R. A., Sondheim, W. E., Sorensen, S. P., Sourikova, I. V., Stankus, P. W., Stoll, S. P., Sugitate, T., Sukhanov, A., Sumita, T., Sun, J., Sun, Z., Sziklai, J., Takahama, R., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tarnai, G., Tieulent, R., Timilsina, A., Todoroki, T., Tomášek, M., Towell, C. L., Towell, R. S., Tserruya, I., Ueda, Y., Ujvari, B., van Hecke, H. W., Velkovska, J., Virius, M., Vrba, V., Vukman, N., Wang, X. R., Wang, Z., Watanabe, Y. S., Wong, C. P., Woody, C. L., Xue, L., Xu, C., Xu, Q., Yalcin, S., Yamaguchi, Y. L., Yamamoto, H., Yanovich, A., Yoon, I., Yoo, J. H., Yushmanov, I. E., Yu, H., Zajc, W. A., Zelenski, A., and Zou, L.
Subjects: High Energy Physics - Experiment
Abstract: Presented are the first measurements of the transverse single-spin asymmetries ($A_N$) for neutral pions and eta mesons in $p$+Au and $p$+Al collisions at $\sqrt{s_{_{NN}}}=200$ GeV in the pseudorapidity range $|\eta|<$0.35 with the PHENIX detector at the Relativistic Heavy Ion Collider. The asymmetries are consistent with zero, similar to those for midrapidity neutral pions and eta mesons produced in $p$+$p$ collisions. These measurements show no evidence of additional effects that could potentially arise from the more complex partonic environment present in proton-nucleus collisions., Comment: 322 authors from 70 institutions, 8 pages, 2 figures, 1 table, 2015 data. v2 is version accepted for publication in Phys. Rev. D. HEPData tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.html
Published: 2023

29. Quantized Radio Map Estimation Using Tensor and Deep Generative Models

Author: Timilsina, Subash, Shrestha, Sagar, and Fu, Xiao
Subjects: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning
Abstract: Spectrum cartography (SC), also known as radio map estimation (RME), aims at crafting multi-domain (e.g., frequency and space) radio power propagation maps from limited sensor measurements. While early methods often lacked theoretical support, recent works have demonstrated that radio maps can be provably recovered using low-dimensional models -- such as the block-term tensor decomposition (BTD) model and certain deep generative models (DGMs) -- of the high-dimensional multi-domain radio signals. However, these existing provable SC approaches assume that sensors send real-valued (full-resolution) measurements to the fusion center, which is unrealistic. This work puts forth a quantized SC framework that generalizes the BTD and DGM-based SC to scenarios where heavily quantized sensor measurements are used. A maximum likelihood estimation (MLE)-based SC framework under a Gaussian quantizer is proposed. Recoverability of the radio map using the MLE criterion are characterized under realistic conditions, e.g., imperfect radio map modeling and noisy measurements. Simulations and real-data experiments are used to showcase the effectiveness of the proposed approach., Comment: 16 pages, 9 figures
Published: 2023

30. Developing affordable and efficient heating devices for enhanced live cell imaging in confocal microscopy

Author: Abhishesh Bajracharya, Sampada Timilsina, Ruofan Cao, Qingrui Jiang, Berry A. Dickey, Anupa Wasti, Jing Xi, Magdalena Weingartner, Scott R. Baerson, Gregg W. Roman, Yiwei Han, and Yongjian Qiu
Subjects: cost-effective, low-maintenance, confocal microscopy, live cell imaging, heat stress, heat shock protein, Plant culture, SB1-1110
Abstract: Temperature control is crucial for live cell imaging, particularly in studies involving plant responses to high ambient temperatures and thermal stress. This study presents the design, development, and testing of two cost-effective heating devices tailored for confocal microscopy applications: an aluminum heat plate and a wireless mini-heater. The aluminum heat plate, engineered to integrate seamlessly with the standard 160 mm × 110 mm microscope stage, supports temperatures up to 36°C, suitable for studies in the range of non-stressful warm temperatures (e.g., 25-27°C for Arabidopsis thaliana) and moderate heat stress (e.g., 30-36°C for A. thaliana). We also developed a wireless mini-heater that offers rapid, precise heating directly at the sample slide, with a temperature increase rate over 30 times faster than the heat plate. The wireless heater effectively maintained target temperatures up to 50°C, ideal for investigating severe heat stress and heat shock responses in plants. Both devices performed well in controlled studies, including the real-time analysis of heat shock protein accumulation and stress granule formation in A. thaliana. Our designs are effective and affordable, with total construction costs lower than $300. This accessibility makes them particularly valuable for small laboratories with limited funding. Future improvements could include enhanced heat uniformity, humidity control to mitigate evaporation, and more robust thermal management to minimize focus drift during extended imaging sessions. These modifications would further solidify the utility of our heating devices in live cell imaging, offering researchers reliable, budget-friendly tools for exploring plant thermal biology.
Published: 2025
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31. Dual‐Modal Sensing Skin Adaptive to Daylight, Darkness, and Ultraviolet Light for Simultaneous Full‐Field Deformation Measurement and Mechanoluminescence Responses

Author: Suman Timilsina, Cheol Woo Jo, Kwang Ho Lee, Kee‐Sun Sohn, and Ji Sik Kim
Subjects: digital image correlation, light‐adaptive skin, mechanoluminescence, structural health monitoring, subsurface crack, Science
Abstract: Abstract Mechanoluminescence (ML) and digital image correlation (DIC) have emerged as promising optical methods to visualize and measure deformation fields. In this study, a dual‐modal sensing skin, called the ML‐DIC skin is introduced, that is capable of emitting ML and facilitating DIC measurements under various lighting conditions, including daylight, night or darkness, and UV irradiation. Four ML‐DIC skins are fabricated with or without carbon nanotubes (CNTs) using a composite powder consisting of SrAl2O4: Eu,Dy (SAO), and acrylic resin, with CNT milling times of 48, 72, and 96 h for three of four skins, respectively. DIC measurements are performed under multiple lighting conditions for measuring photoluminescence, persistence luminescence, and reflection. Uniaxial tension tests demonstrate the superior performance of ML‐DIC skins with CNTs compared with pristine SAO skins, with the skin subjected to 48 h of CNT dispersion exhibiting optimal performance. Further investigations focus on ML emission and DIC measurements near the crack‐tip vicinity of static and propagating cracks as well as on surfaces above subsurface cracks. The integration of ML and DIC techniques offers a versatile approach for comprehensive deformation analysis applicable to diverse environments, with implications for materials science, engineering, and structural health monitoring.
Published: 2025
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32. Are we ready for self-sampling for cervical cancer screening? Insights from service providers and policy makers in Nepal.

Author: Saki Thapa, Amit Timilsina, Bikram Bucha, Swastika Shrestha, Safal Kunwar, Raghu Dhital, and Gillian Holdsworth
Subjects: Public aspects of medicine, RA1-1270
Abstract: Cervical cancer is the leading cancer among women in Nepal, but the country has very low screening rate, with only 8.2% of women being screened. In recent years, a self-sampling kit for testing for the human papillomavirus (HPV) has been developed to allow self-sampling and enable early detection of cervical abnormalities. This kit enables women to collect cervical samples without the need for trained healthcare providers or healthcare facilities. Nevertheless, there has been a notable absence of scientific studies to analyse the feasibility and acceptability of self-sampling for cervical cancer screening in Nepal, particularly from the perspective of various service providers. The qualitative research method used semi-structured in-depth interviews and key informant interviews with healthcare providers, online service providers, and policymakers. These interviews were conducted in person with 20 participants until data saturation was achieved. Thematic analysis was performed where the translated data was coded inductively using NVivo 12. The majority of the participants identified the self-sampling method as an alternative sampling option for detection of cervical abnormalities/cancer in Nepal. Barriers to self-sampling included a low level of knowledge and information, the cost of the self-sampling kit, unclear information regarding self-sampling process and concerns about inaccurate results among women and girls, who are the end users. Similarly, factors such as knowledge and information regarding the self-sampling technique, accessibility of available services and information, and national self-care guidelines and policies for cervical cancer screening were identified as facilitators for self-sampling. It is crucial to have evidence-based discussions, especially regarding the effectiveness of a self-care approach in cervical cancer screening and help create a supportive policy environment for implementing self-care strategies in Nepal. Furthermore, disseminating education and information nationwide through campaigns to raise awareness about self-sampling is essential among beneficiaries for the scaling up of self-sampling for cervical cancer in Nepal.
Published: 2025
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33. Economic and Distributional Impacts of Selected Carbon Pricing Policies for the Arab Republic of Egypt

Author: Timilsina, Govinda R., primary and Sebsibie, Samuel, additional
Published: 2024
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34. Effect of elevation and aspect on carbon stock of bamboo stands (Bambusa nutans subsp. Cupulata) outside the forest area in Eastern Nepal

Author: Santosh Ayer, Sachin Timilsina, Rajeev Joshi, Prakash Chaudhary, Jeetendra Gautam, Menuka Maharjan, Himlal Baral, and Kishor Prasad Bhatta
Subjects: Bamboo stands, Bamboo carbon, Climate change mitigation, Topographical factors, Carbon trade, Forestry, SD1-669.5, Plant ecology, QK900-989
Abstract: Bamboo has emerged as a promising option for climate change mitigation due to its rapid growth, versatility, and renewability. However, in Nepal, there exists a substantial knowledge gap on carbon (C) stock and the influence of aspect and elevation on C stock of bamboo species, particularly in areas outside forests where bamboo is dominant. Therefore, this research was conducted to quantify C stock and aspect-elevation influence on the C stock of Bambusa nutans subsp. cupulata outside the forest area. For this study, three elevation zones (0–400 m, 400–800 m, 800–1200 m) and two aspects (East and West) were considered. A total of 30 square plots having a 100 m2 area were established utilizing purposive sampling due to the scattered distribution of bamboo. Non-destructive methods were applied to measure bamboo culm diameters, while composite soil samples were systematically collected from 30 cm depth using soil augers and core samplers. Clump density (400 ha⁻¹), culm density (42,480 ha⁻¹) and culm diameter (6.82 ± 0.41 cm) were highest at middle elevations (p < 0.05), with no significant difference due to aspect (p > 0.05). The total mean C stock potential of B. nutans was 148.73 ± 3.43 Mg ha⁻¹. Our results indicated a significant difference in C stock among elevation zones, with middle elevation zones (161.77 ± 6.74 Mg ha-1) exhibiting notably higher C stock compared to both lower (150.26 ± 2.69 Mg ha-1) and higher (134.17 ± 4.26 Mg ha-1) elevation zones. Furthermore, East aspect was found to have significantly (p < 0.05) higher soil organic C stock (18.52 ± 1.32 Mg ha-1) compared to West aspect (11.4 ± 1.01 Mg ha-1). Further research is needed to explore other complex environmental interactions with C stock potential for better climate change strategies. Incorporating bamboo C into Nepal's REDD+ initiative can be crucial for optimizing opportunities to earn C credits.
Published: 2024
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35. Development of a standardized monoclonal antibody to the inner lipoyl domain of PDC-E2 as a potential international AMA reference

Author: Zhuye Qin, Fangming Cheng, Mingming Zhang, Ruonan Qian, Hong Chen, Yaqin Zhao, Youtao Zhang, Yaping Dai, Chaochao Tang, Peng Jiang, Xiaoli Hua, Shen Li, Bing Zheng, Pin Yu, Xingjuan Shi, Suraj Timilsina, M. Eric Gershwin, Xiangdong Liu, Chungen Qian, and Fang Qiu
Subjects: Primary biliary cholangitis, AMA, Chimeric antibody, PDC-E2, Inner lipoyl domain, Immunologic diseases. Allergy, RC581-607
Abstract: The detection of antimitochondrial antibodies (AMA) is the specific diagnostic marker for primary biliary cholangitis. Indeed, it is the most specific autoantibody in clinical autoimmunity, with a high titer directed response to the inner lipoyl domain of PDC-E2. The current international reference for AMA detection is based upon sera samples of PBC patients. In rheumatic diseases, i.e. rheumatoid arthritis, great efforts are placed at development of international standards. In this study, we report the development of a monoclonal chimeric IgG1 antibody as a reference for AMA testing. A monoclonal 4G6 antibody was constructed from a murine monoclonal antibody specific for the inner lipoyl domain (ILD) of PDC-E2, by combining the variable region with the constant region of human IgG1. The 4G6 antibody recognizes all AMA epitopes containing the ILD of PDC-E2, including the classical BPO recombinant antigen in all currently available diagnostic methods. The binding affinity of the 4G6 antibody to PDC-E2 and BPO antigen reaches KD value of 7.22 × 10−11 M and 4.55 × 10−11 M, which is sufficient to use as a quantitative reference for all AMA tests. The unlimited availability of the 4G6 antibody makes it a promising candidate for use as an AMA reference or assay calibrator for the international community.
Published: 2024
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36. Current and future habitat suitability modelling of Bambusa teres outside forest areas in Nepal under climate change scenarios

Author: Binay Kharel, Santosh Ayer, Samit Kafle, Sachin Timilsina, Kishor Prasad Bhatta, Jeetendra Gautam, Amul Kumar Acharya, Prakash Lamichhane, and Janak Airee
Subjects: MaxEnt model, Bamboo species, Habitat suitability mapping, Species distribution modelling, Nepal, Forestry, SD1-669.5
Abstract: Bambusa teres Buch.-Ham. ex Munro (syn. Bambusa nutans subsp. capulata Stapleton) is a fast-growing perennial bamboo that has ecological, economic, cultural and climate change mitigation benefits. However, information on its current and future potential distribution outside forest areas across Nepal and the key factors affecting its growth and distribution are little known. We used a total of 298 occurrence points obtained from the National Bamboo Resource Assessment and 23 environmental variables to project the distribution of B. teres throughout its potential range in Nepal. Maximum entropy model (MaxEnt) was utilized for this study. We assessed the performance of the model using a receiver operating characteristic curve and evaluated the relative importance of predictor variables through a Jackknife procedure. The model achieved a high level of performance with an area under the curve value of 0.928. Precipitation of the coldest quarter (bio_19), temperature seasonality (bio_4) and precipitation seasonality (bio_15) were the significant contributing variables for the distribution of B. teres. The most suitable habitat for B. teres, with a suitability index >0.6, covered 9264.6 km2, with large sections in Eastern and Central Nepal. However, under future climate change scenarios, the area of suitable habitat for the species is projected to increase across Nepal. This study serves as a baseline for assessing potential climate change impacts on B. teres and will enable the development of adaptive measures to protect and establish various bamboo populations outside forest areas in Nepal and globally.
Published: 2024
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37. Assessing the Efficacy and Safety of Preemergence Herbicides Applied Alone or in Combination with Superabsorbent Polymer, Soil Binding Agent, and Compost in Tomato (Solanum lycopersicum L.) Plasticulture Production

Author: Ruby Tiwari, Nathan Boyd, Pamela Roberts, Samira Daroub, Nirmal Timilsina, and Ramdas Kanissery
Subjects: crop vigor, crop yield, herbicides, plastic mulch, purple nutsedge, Plant culture, SB1-1110
Abstract: Preemergence herbicide application under plastic mulch is an effective way to manage weeds in tomato (Solanum lycopersicum L.) production. Nonetheless, applying herbicides beneath plastic mulch in raised beds is associated with the inherent risk of crop phytotoxicity. This highlights the need to explore crop-safe methods for herbicide application in plastic mulch beds. The research aimed to evaluate the effectiveness of preemergence herbicides S-metolachlor and flumioxazin at the labeled rate (X) and reduced rate (0.5X, half of the labeled rate) either alone or in combination with a super absorbent polymer, soil binding agent, or compost to determine their ability to control weeds effectively in plastic mulched beds without causing negative effects on tomato crops. Two different experimental trials, trial 1 (Mar–Jun 2021) and trial 2 (Oct 2021–Jan 2022) were performed in the fields in Immokalee, FL, USA. The experimental design was a randomized complete block with five replications. S-metolachlor (X) plus soil binding agent and S-metolachlor (X) plus compost mix suppressed purple nutsedge density by >85% and approximately 68%, respectively, during trial II. Similarly, S-metolachlor (X), S-metolachlor (0.5X) plus super absorbent polymer, S-metolachlor (X) plus super absorbent polymer, S-metolachlor (X) plus soil binding agent, and S-metolachlor (X) plus compost caused reductions in purple nutsedge biomass by >50% compared with that of the nontreated control during trial II. Treatments did not significantly impact tomato crop vigor and chlorophyll contents during trials I and II. Moreover, treatments did not significantly affect tomato crop biomass and yield during both trials. In summary, using preemergence S-metolachlor (X) combined with soil binding agent or compost could be a viable option for suppressing purple nutsedge in plastic mulched tomato beds.
Published: 2024
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38. Impact of agroforestry intervention on carbon stock and soil quality in mid-hills of Nepal

Author: Maharjan, Menuka, Ayer, Santosh, Timilsina, Sachin, Ghimire, Pramod, Bhatta, Sandesh, Thapa, Neeru, Timilsina, Yajna Prasad, Lama, Soni, Yadav, Vijay Kumar, and Okolo, Chukwuebuka Christopher
Published: 2024
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39. Machine Learning-Assisted Recurrence Prediction for Early-Stage Non-Small-Cell Lung Cancer Patients

Author: Janik, Adrianna, Torrente, Maria, Costabello, Luca, Calvo, Virginia, Walsh, Brian, Camps, Carlos, Mohamed, Sameh K., Ortega, Ana L., Nováček, Vít, Massutí, Bartomeu, Minervini, Pasquale, Campelo, M. Rosario Garcia, del Barco, Edel, Bosch-Barrera, Joaquim, Menasalvas, Ernestina, Timilsina, Mohan, and Provencio, Mariano
Subjects: Computer Science - Machine Learning, Quantitative Biology - Quantitative Methods
Abstract: Background: Stratifying cancer patients according to risk of relapse can personalize their care. In this work, we provide an answer to the following research question: How to utilize machine learning to estimate probability of relapse in early-stage non-small-cell lung cancer patients? Methods: For predicting relapse in 1,387 early-stage (I-II), non-small-cell lung cancer (NSCLC) patients from the Spanish Lung Cancer Group data (65.7 average age, 24.8% females, 75.2% males) we train tabular and graph machine learning models. We generate automatic explanations for the predictions of such models. For models trained on tabular data, we adopt SHAP local explanations to gauge how each patient feature contributes to the predicted outcome. We explain graph machine learning predictions with an example-based method that highlights influential past patients. Results: Machine learning models trained on tabular data exhibit a 76% accuracy for the Random Forest model at predicting relapse evaluated with a 10-fold cross-validation (model was trained 10 times with different independent sets of patients in test, train and validation sets, the reported metrics are averaged over these 10 test sets). Graph machine learning reaches 68% accuracy over a 200-patient, held-out test set, calibrated on a held-out set of 100 patients. Conclusions: Our results show that machine learning models trained on tabular and graph data can enable objective, personalised and reproducible prediction of relapse and therefore, disease outcome in patients with early-stage NSCLC. With further prospective and multisite validation, and additional radiological and molecular data, this prognostic model could potentially serve as a predictive decision support tool for deciding the use of adjuvant treatments in early-stage lung cancer. Keywords: Non-Small-Cell Lung Cancer, Tumor Recurrence Prediction, Machine Learning
Published: 2022

40. Abstract 4147627: A Pharmacovigilance Study of Bempedoic Acid: Balancing Risks and Benefits

Author: Khadka, Sulochana, Timilsina, Bibek, Matai, Pallavi, Sharma, Seema, Rajak, Kripa, Calderon Barahona, Gabriela, and Oli, Seema
Published: 2024
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41. Abstract 4145352: SGLT2 Inhibitor-Induced Euglycemic Ketoacidosis in a Non-Diabetic Patient with Ischemic Cardiomyopathy

Author: Khadka, Sulochana, Rajak, Kripa, Matai, Pallavi, Timilsina, Bibek, Sharma, Seema, Halder, Anupam, Calderon Martinez, Evelyn, and Jaiswal, Vikash
Published: 2024
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42. A comparative analysis of national water model versions 2.1 and 3.0 reveals advances and challenges in streamflow predictions during storm events

Author: Sujana Timilsina and Paola Passalacqua
Subjects: National Water Model, Streamflow, Forecasting, Performance analysis, Physical geography, GB3-5030, Geology, QE1-996.5
Abstract: Study RegionTexas, United States of America. Study FocusThis study presents a thorough evaluation of the National Water Model (NWM) versions 2.1 and 3.0 using an extensive dataset from 610 USGS gauges across Texas, and provides a detailed comparison of the model performance across the region. New Hydrological InsightsThe National Water Model (NWM), launched by the National Oceanic and Atmospheric Administration (NOAA), represents a significant advancement in hydrological forecasting in the United States. However, the accuracy and reliability of NWM outputs, particularly in specific regions and during extreme events, require comprehensive evaluation. This study evaluates the accuracy and reliability of the NWM’s streamflow predictions in Texas by comparing them to observational data from USGS gauges. We assess the performance of NWM versions 2.1 and 3.0, focusing on both retrospective data and short-range forecasts. NWM version 3.0 achieves a 38.1% improvement in overall predictive accuracy over NWM 2.1, as measured by the Root Mean Square Error (RMSE). It also shows an 87.5% improvement in the Kling–Gupta Efficiency (KGE), reflecting better balance in bias, variability, and correlation; a 172.7% enhancement in streamflow predictive skill, as indicated by the Nash–Sutcliffe Efficiency (NSE); and a 10.6% increase in normalized predictive skill, as measured by the Normalized Nash–Sutcliffe Efficiency (NNSE). However, NWM 3.0 consistently underestimates streamflow and, in some cases, results in negative NSE and KGE values, highlighting difficulties in capturing extreme events. Short-range forecasts with data assimilation outperform retrospective analyses, highlighting the importance of data assimilation methods. Despite these advancements, challenges remain in predicting both the magnitude and timing of peak flow events underscoring the need for further improvements in the model to enhance its reliability.
Published: 2025
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43. NDN-TR70 -- Utilizing NDN-DPDK for Kubernetes Genomics Data Lake

Author: Timilsina, Sankalpa, Presley, Justin, Reddick, David, and Shannigrahi, Susmit
Subjects: Computer Science - Networking and Internet Architecture, Quantitative Biology - Genomics
Abstract: As the growth of genomics samples rapidly expands due to increased access to high resolution DNA sequencing technology, the need for a scalable platform to aggregate dispersed datasets enable easy access to the vast wealth of DNA sequences available is paramount. In this work, we introduce and demonstrate a novel way to use Named Data Networking (NDN) in conjunction with a Kubernetes cluster to design a flexible and scalable genomics Data Lake in the cloud. In addition, the use of the NDN Data Plane Development Kit (DPDK) provides an efficient and accessible distribution of the datasets to researchers anywhere. This report will explain the need to deploy a Data Lake for genomics data, what is necessary to deploy successfully, and detailed instructions to replicate the proposed design. Finally, this technical report outlines future enhancement options for further improvements.
Published: 2022

44. Prospect Theory-inspired Automated P2P Energy Trading with Q-learning-based Dynamic Pricing

Author: Timilsina, Ashutosh and Silvestri, Simone
Subjects: Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract: The widespread adoption of distributed energy resources, and the advent of smart grid technologies, have allowed traditionally passive power system users to become actively involved in energy trading. Recognizing the fact that the traditional centralized grid-driven energy markets offer minimal profitability to these users, recent research has shifted focus towards decentralized peer-to-peer (P2P) energy markets. In these markets, users trade energy with each other, with higher benefits than buying or selling to the grid. However, most researches in P2P energy trading largely overlook the user perception in the trading process, assuming constant availability, participation, and full compliance. As a result, these approaches may result in negative attitudes and reduced engagement over time. In this paper, we design an automated P2P energy market that takes user perception into account. We employ prospect theory to model the user perception and formulate an optimization framework to maximize the buyer's perception while matching demand and production. Given the non-linear and non-convex nature of the optimization problem, we propose Differential Evolution-based Algorithm for Trading Energy called DEbATE. Additionally, we introduce a risk-sensitive Q-learning algorithm, named Pricing mechanism with Q-learning and Risk-sensitivity (PQR), which learns the optimal price for sellers considering their perceived utility. Results based on real traces of energy consumption and production, as well as realistic prospect theory functions, show that our approach achieves a 26% higher perceived value for buyers and generates 7% more reward for sellers, compared to a recent state of the art approach.
Published: 2022

45. Correction to: Enhancing crop yields and farm income through climate‑smart agricultural practices in Eastern India

Author: Tanti, Purna Chandra, Jena, Pradyot Ranjan, Timilsina, Raja Rajendra, and Rahut, Dil Bahadur
Published: 2024
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46. Enhancing crop yields and farm income through climate-smart agricultural practices in Eastern India

Author: Tanti, Purna Chandra, Jena, Pradyot Ranjan, Timilsina, Raja Rajendra, and Rahut, Dil Bahadur
Published: 2024
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47. Primary Biliary Cholangitis

Author: Leung, Patrick S. C., Shao, Tihong, Wang, Li, Tsuneyama, Koichi, Invernizzi, Pietro, Timilsina, Suraj, Gershwin, M. Eric, Shoenfeld, Yehuda, editor, Cervera, Ricard, editor, Espinosa, Gerard, editor, and Gershwin, M. Eric, editor
Published: 2024
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48. Gymnosperms of Nepal: Diversity, Distribution, Economic Importance, and Future Perspectives

Author: Pandey, Bikram, Timilsina, Arbindra, Werger, Marinus J.A., Series Editor, Hobohm, Carsten, Series Editor, Boot, René, Series Editor, Rokaya, Maan Bahadur, editor, and Sigdel, Shalik Ram, editor
Published: 2024
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49. Leaching nickel sulfide tailings with activated carbon in sulfuric acid medium

Author: Mends, Emmanuel Atta, Arthur, Sabinus Essel, Tita, Angela Manka, Hussaini, Shokrullah, Osho, Bankole, Timilsina, Anil, Basyal, Sudarshan, Yang, Yu, and Chu, Pengbo
Published: 2025
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50. Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence

Author: Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, and Dilip Khatiwada
Subjects: Co-pyrolysis, Synergistic effect, Machine learning, Bio-oil, SHAP, Genetic algorithm, Engineering (General). Civil engineering (General), TA1-2040
Abstract: The rapid increase in biomass and plastic waste poses significant environmental challenges. Co-pyrolysis of biomass with plastic wastes offers a promising avenue for sustainable waste management and renewable energy generation. This study covers several novel aspects: First, it investigates the impacts of feedstock composition and operating conditions in pyrolysis (individual feedstock) and co-pyrolysis (biomass and plastic wastes). The study reveals that synergistic effects, specifically improved yields and optimized temperature, exist in the co-pyrolysis of biomass and plastic wastes compared to individual feedstock. Secondly, a suitable blended machine learning predictive model (with Random Forest, Gradient Boosting Regressor, and XGBoost) and robust optimization framework are developed to address model accuracy, non-linear interactions, and uncertainties in pyrolysis such as temperature, heating rate, and biomass-to-plastic ratio. This study predicts the bio-oil yield quantitatively (amount) and qualitatively (composition) with high accuracy (R2 > 0.97). Thirdly, key factors contributing to yield include plastic content (18 %) and biomass type (13 %) have been identified through Gini feature importance and Shapley Additive Explanation (SHAP) analysis. Furthermore, multi-objective optimization techniques reveal the most optimal bio-oil yield under specific conditions, supported by uncertainty analysis, which confines bio-oil yield to a range of 30–50 %. Finally, it also demonstrates a case study to find the optimal bio-oil yield and quality conditions using co-pyrolysis of local resources, i.e., biomass (wood and bagasse) and plastic wastes. The case study suggests optimal conditions like > 50 °C heating rate, 60 % plastic content in a blend of wood and HDPE. This study assists industries and policymakers to assess and understand the viability of co-pyrolysis, optimal design parameters, and process impacts.
Published: 2024
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