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1. 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

2. 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

3. 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

4. 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

5. 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

6. 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
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7. Metabolic Syndrome and Diabetes Risk Among Young Adult Students in the Health Sciences from Kathmandu, Nepal

Author: Sapkota M, Timilsina A, Shakya M, Thapa TB, Shrestha S, Pokhrel S, Devkota N, and Pardhe BD
Subjects: metabolic syndrome, diabetes risk, young adults, nepal, Medicine (General), R5-920
Abstract: Manisha Sapkota,1,* Alaska Timilsina,1,* Mudita Shakya,1 Tika Bahadur Thapa,1 Sneha Shrestha,1 Sushant Pokhrel,1 Nishchal Devkota,2 Bashu Dev Pardhe1 1Department of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal; 2Department of Public Health, Central Institute of Science and Technology, Baneshwor, Nepal*These authors contributed equally to this workCorrespondence: Bashu Dev PardheDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu 15201, NepalTel +977-01-4030781Email pardhebashu@gmail.comBackground: The widespread dissemination of unhealthy dietary habits, childhood-teenage obesity, and sedentary lifestyle in young adults has paved the way for public health burden metabolic syndrome and early onset of type 2 diabetes mellitus. The aim of this study was to assess the prevalence and risk factors for metabolic syndrome and diabetes among young adult students.Methods: This cross-sectional study was conducted among students of age group (18 to 25 years) studying at Manmohan Memorial Institute of Health Sciences and Central Institute of Science and Technology. The diabetes risk score of each individual was calculated by the Finnish Diabetes Risk Score (FINDRISC tool). Independent risk factors for diabetes and metabolic syndrome were measured by multivariable logistic regression analysis. The p-value of < 0.05 was considered statistically significant in this study.Results: A total of 825 students were recruited and 739 (89.6%) students completed the study with all the fulfilled criteria. The metabolic syndrome (Harmonized Joint Scientific Statement (HJSS) criteria) was present in 7.1%, and the most prevalent defining component was low HDL-C (78%); 74.8% of students were under low risk, 22.18% were at slightly elevated risk, 2.02% were at moderate risk, and 1.01% were at high risk of diabetes. The cardiometabolic risk factors like BMI, TC, and LDL-C were higher at a significant level (p< 0.001) with an increased diabetes risk score. Independent lifestyle risk factor for metabolic syndrome was current smoking (AOR, 4.49, 95% CI 1.38– 14.62) whereas, an independent lifestyle risk factor for diabetes was low adherence to physical exercise (AOR, 4.81, 95% CI, 2.90– 7.99).Conclusion: Metabolic syndrome is present, although in low numbers in young adults putting them at risk to develop diabetes in the near future. Early assessment of metabolic syndrome and diabetes risk in young may provide insights for preventive and control plans for risk population.Keywords: metabolic syndrome, diabetes risk, young adults, Nepal
Published: 2020

8. Self-Care Adherence And Barriers To Good Glycaemic Control In Nepalese Type 2 Diabetes Mellitus Patients: A Hospital-Based Cross-Sectional Study

Author: Pokhrel S, Shrestha S, Timilsina A, Sapkota M, Bhatt MP, and Pardhe BD
Subjects: Type 2 diabetes mellitus, HbA1c, lifestyle variables, risk factors, Medicine (General), R5-920
Abstract: Sushant Pokhrel, Sneha Shrestha, Alaska Timilsina, Manisha Sapkota, Mahendra Prasad Bhatt, Bashu Dev Pardhe Department of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, NepalCorrespondence: Bashu Dev PardheDepartment of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, P.O.Box No. 15201, Kathmandu, NepalTel +977 1 4030781Email bashudev.pardhe@mmihs.edu.npPurpose: The patient believes in adherence to medication rather than to self-care adherence and lifestyle changes for the management of diabetes. This study was carried out to establish the association of self-care adherence and their barriers in poor glycemic control in our diabetic population.Patients and methods: This cross-sectional study was conducted among 480 already diagnosed diabetes outpatients attended in our two hospitals. Glycaemic control was defined by levels of HbA1c. Socio-demographic data, lifestyle variables and anthropometric measurements were recorded using a standard questionnaire. Fasting blood glucose, HbA1c and lipid profiles were estimated using the manufacturer’s guideline. Student’s t-test and one-way ANOVA were used for comparison between different groups and the correlation was established by Spearman correlation. Risk factors associated with poor glycaemic control were verified by logistic regression analysis.Results: The mean HbA1c of the study population was 7.4±1.3% and 65.4% had poor glycaemic control with mean 8.0±1.1%. Higher HbA1c levels were significantly associated with duration of diabetes, a number of drugs used, patient–physician relationship and knowledge about diabetes. The poor glycaemic control was significantly associated with low adherence of following the meal plan, regular medication and regular exercising (p
Published: 2019

9. 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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10. 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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11. 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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12. 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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13. 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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14. 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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15. 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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16. Impact of agroforestry intervention on carbon stock and soil quality in mid-hills of Nepal

Author: Menuka Maharjan, Santosh Ayer, Sachin Timilsina, Pramod Ghimire, Sandesh Bhatta, Neeru Thapa, Yajna Prasad Timilsina, Soni Lama, Vijay Kumar Yadav, and Chukwuebuka Christopher Okolo
Subjects: Silvo-horto-agro system, Farmyard manure, Vermi-compost, Soil quality index (SQI), Geology, QE1-996.5
Abstract: Traditionally, planting trees on agricultural land including livestock is a very common practice in the mid-hills of Nepal. Trees on farms fulfill the demand for fuel wood/timber including fodder used to feed the livestock. Animal urine/dung is used as a bio-fertilizer that increases soil fertility. However, very few studies have been conducted on assessing carbon (C) stock and soil quality in agroforestry systems. This study was carried out to estimate the C stock and soil quality in agroforestry and agricultural land in the Kaski district of Nepal. Silvo-horto-agro system and agricultural land were selected from Site 1 (900–1000 m and west) and Site 2 (700–800 m and west). Total C stock was higher in the agroforestry at Site 1 (98.57 t ha−1) than agroforestry at Site 2 (64.73 t ha−1). Soil organic C, pH, and available potassium were higher in agroforestry than agriculture sites. Total nitrogen was higher in agroforestry than agriculture at Site 1. Available phosphorus was higher in agriculture than agroforestry at Site 1. Soil quality index (SQI) was good (0.8) and fair (0.6) in agroforestry and agriculture at Site 1. SQI was fair (0.6) in agroforestry and poor (0.5) in agriculture at Site 2. Altogether, the application of farmyard manure and vermi-compost including the higher vegetation density contributes to enhancing the soil quality in agroforestry systems. Further research on C stock including various soil quality indices is necessary under various kinds of agroforestry systems for a better understanding of their contribution towards climate change mitigation.
Published: 2024
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17. 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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18. $\textit{e-Uber}$: 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

19. 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, v1 is version submitted to 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

20. 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
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21. 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

22. 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

23. Antenatal depression among pregnant mothers in Afghanistan: A cross-sectional study

Author: Shararah Sarem, Ahmad Neyazi, Abdul Qadim Mohammadi, Mehrab Neyazi, Mozhgan Ahamdi, Nosaibah Razaqi, Sadaf Wali, Shashank Timilsina, Hamida Faizi, and Mark D. Griffiths
Subjects: Depression, Prenatal, Pregnant, Women, Afghan, Gynecology and obstetrics, RG1-991
Abstract: Abstract Background Approximately one in five pregnant women experience antenatal depression globally. The purpose of the present study was to estimate the prevalence of antenatal depression and explore its relationship between various demographic variables, recent sexual engagement, and recent adverse life events among pregnant Afghan women. Methods A cross-sectional survey study was carried out between January, 2023 and April 2023 among 460 women aged 15–45 years who were recruited using convenience sampling from Herat province (Afghanistan). Logistic regression models were utilized to explore the relationship between antenatal depression and socio-demographic characteristics among the participants. Results The prevalence of antenatal depression symptoms was 78.5%. Multiple regression analysis indicated that antenatal depression was significantly associated with (i) being aged 30–45 years (AOR: 4.216, 95% CI: 1.868–9.515, p = .001), (ii) being of low economic status (AOR:2.102, 95% CI: 1.051–4.202, p = .036), (iii) not being employed (AOR: 2.445, 95% CI:1.189–5.025, p = .015), (iv) not having had sex during the past seven days (AOR: 2.335, 95% CI: 1.427–3.822, p = .001), and (v) not experiencing a traumatic event during the past month (AOR:0.263, 95% CI: 0.139–0.495, p
Published: 2024
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24. 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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25. 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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26. 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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27. Correction: 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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28. 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

29. Understanding the Knowledge, Attitude, Practice and Intention regarding Abortion among Federal and Provincial Policymakers

Author: Madhabi Bajracharya, Nisha Gyawali, Tejaswee Bhattarai, Shipra Joshi, Jivan Devkota, Bishnu Devkota, Jayashree Rai, Samasti Tandukar, Amit Timilsina, and Deeb Shrestha Dangol
Subjects: Public aspects of medicine, RA1-1270
Abstract: Background: For more than two decades abortion is legalized in Nepal, recognizing unsafe abortion as one of the leading but preventable cause of maternal morbidity and mortality. To safeguard safe abortion as women’s rights, several policies, guidelines, training manuals have been developed along with training human resources and increasing access to abortion services across Nepal. However, access to safe abortion services remains a challenge. Hence, to unravel the possible reasons behind these challenges, this study explored the knowledge, attitudes, practices and intentions of policymakers of Nepal towards abortion. Methods: Mixed methodology was used incorporating self-administered questionnaire for quantitative data collection and semi-structured interview guidelines to interview twenty local leaders from federal and provincial level, identified through purposive sampling. The ethical approval was taken from Nepal Health Research Council prior to data collection. After transcription and translation to English, Dedoose application was used for qualitative thematic analysis while the quantitative data was analysed using SPSS version. Results: 70% understand that international health and human rights frameworks support abortion. Also, a majority (85%) believe that policies limiting abortion access create negative attitudes toward abortion. All the participants mentioned that they possess a good knowledge of safe abortion services. Majority of the participants had good attitude, confident in advocating, and had positive intention towards safe abortion services. However, existing socio-cultural barriers, lack of awareness, legal barriers and maintaining privacy were identified challenges to seek safe abortion and related services. Conclusions: Despite strong positive intentions, policy implementation gaps and lack of accountability have resulted in poor awareness, access, and acceptability of abortion related services. Further budget allocation, safe abortion prioritization, continuous advocacy, integration of abortion in preservice curriculum and community engagement and awareness will bridge these gaps – to ensure equitable access to quality services including women and girls from marginalized community and adolescents. Keywords: Intention; knowledge; policy gaps; policymakers; safe abortion.
Published: 2024
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30. Status of Abortion-Related Stigma in Nepal using Stigmatizing Attitudes, Beliefs, and Actions Scale

Author: Jagadishwor Ghimire, Bibek Kumar Lal, Suresh Mehata, Nisha Kumari Joshi, Amit Timilsina, Kritee Lamichhane, Parash Prasad Phuyal, Bhogendra Raj Dotel, Manish Gautam, Sanju Maharjan, and Sujan Karki
Subjects: Public aspects of medicine, RA1-1270
Abstract: Background: Despite substantial improvements in the accessibility of safe abortion services nationwide, a noticeable underutilization of these services persists, primarily attributable to the presence of social stigma. This stigma leads to discrimination, abuse, and poor healthcare. This study aims to understand and address abortion stigma among Nepali women of reproductive age. Methods: This cross-sectional study involved 2286 women of reproductive age across Nepal. SABAS was used to measure abortion stigma, which includes 18 questions. Quantitative data was collected through face-to-face interviews using structured questionnaires on kobo collect. Stata 15.0 software was used for data analysis. Results: The mean SABAS score was 46.5 out of 90, indicating moderate abortion stigma in Nepal. Negative stereotypes and beliefs about abortion were more prevalent, with over 80% believing a woman's health deteriorates after abortion. Discrimination tendencies were lower, with less than 10% endorsing teasing, pointing fingers, or disgrace. Fear of contagion was also relatively low, with less than 20% agreeing that women who had abortions made others ill. Factors such as age, caste/ethnicity, education, marital status, wealth, and provinces were associated with varying levels of stigma, and women of higher age group, Madhesh, Dalit, Muslim, lower education levels, widowed, poor, Madhes province were linked to higher stigma scores. The study found that stigma levels varied among different groups. Conclusions: The stigma level on abortion is higher in upper age group, Madheshi, Dalit, Muslim, lower education levels, widowed, poor, Madhesh province women in Nepal. Similarly, the negative stereotype and discrimination and exclusion is also high while the fear of contagion is low among Nepalese women and girls. Keywords: Abortion-related stigma; attitudes; Nepal.
Published: 2024
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31. Clinical Study of Cutaneous Manifestations in Neonates in A Tertiary Care Center in Eastern Nepal: A Descriptive Cross-sectional Study

Author: Anil Timilsina, Nisha Keshary Bhatta, and Nidhi Shah
Subjects: maternal age, newborn, physiological, skin manifestations, Medicine (General), R5-920
Abstract: Introduction: In the neonatal period, a variety of cutaneous symptoms are frequent. To minimize unneeded therapy and to reduce parents' stress, it's important to distinguish between transient and pathological newborn dermatoses. The purpose of this study is to describe the clinical pattern of cutaneous lesions in neonates. Methods: In this cross-sectional descriptive(IRC/1885/020) study , we enrolled 512 neonates born and admitted in maternal child health care ward and Post Natal ward of a tertiary health care cener irrespective of cutaneous manifestations. Convenience sampling technique was used. They were examined till their stay in hospital and followed up weekly via telephone for development of dermatological manifestations. Results: Out of 512 neonates examined, 415 (81.05%) of neonate had at least one cutaneous manifestation.393 (94.69%) had physiological skin lesions, 22 (5.31%) had pathological skin lesions. The most common physiological skin manifestations were sebaceous gland hyperplasia, mongolian spot, ETN, milia and epstein pearl. The pathological cutaneous manifestations though least common comprised of cradle cap, napkin dermatitis and bacterial infections. Most of the lesions were present within 24 hours of birth and many of them were physiological transient lesion. Conclusions: In conclusion, our study highlights the high prevalence of cutaneous manifestations in neonates, with the majority being physiological in nature. Medical personnel must be well versed in the skin changes of neonates which will further help prevent unnecessary treatment and identify life threatening situations that require additional attention.
Published: 2024
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32. An advanced meta metrics-based approach to assess an appropriate optimization method for Wind/PV/Battery based hybrid AC-DC microgrid

Author: Behnaz Papari, Laxman Timilsina, Ali Moghassemi, Asif Ahmed Khan, Ali Arsalan, Gokhan Ozkan, and Christopher S. Edrington
Subjects: Microgrids, DC Loads, Distributed Generations, Energy Storage Devices, Uncertainty, Optimization, Electrical engineering. Electronics. Nuclear engineering, TK1-9971
Abstract: This paper discusses the growing influence of renewable energy and distributed generation, emphasizing the need for smart control systems to maximize benefits and optimize network performance. However, the absence of a standardized evaluation framework makes it challenging to compare different control systems effectively, especially in large-scale hybrid networks with both AC and DC components. While hybrid energy systems show promise for greener and more reliable power networks, they introduce complexity to control methods. Researchers are exploring innovative approaches, including linear and nonlinear techniques, to leverage renewable energy sources effectively in hybrid grids. The paper provides an overview of heuristic evolutionary optimization methods for microgrids (AC, DC, and hybrid AC-DC), highlighting promising techniques such as Crow Search Algorithm, Modified Crow Search Algorithm, Particle Swarm Optimization, and Genetic Algorithms. Comparative analysis suggests that the Modified Crow Search Algorithm performs best across various evaluation criteria, indicating its potential for optimizing microgrids effectively.
Published: 2024
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33. Explaining customer churn prediction in telecom industry using tabular machine learning models

Author: Sumana Sharma Poudel, Suresh Pokharel, and Mohan Timilsina
Subjects: Customer churn, Explainable model, Global explainable, Local explainable, Telecommunication, Cybernetics, Q300-390, Electronic computers. Computer science, QA75.5-76.95
Abstract: The study addresses customer churn, a major issue in service-oriented sectors like telecommunications, where it refers to the discontinuation of subscriptions. The research emphasizes the importance of recognizing customer satisfaction for retaining clients, focusing specifically on early churn prediction as a key strategy. Previous approaches mainly used generalized classification techniques for churn prediction but often neglected the aspect of interpretability, vital for decision-making. This study introduces explainer models to address this gap, providing both local and global explanations of churn predictions. Various classification models, including the standout Gradient Boosting Machine (GBM), were used alongside visualization techniques like Shapley Additive Explanations plots and scatter plots for enhanced interpretability. The GBM model demonstrated superior performance with an 81% accuracy rate. A Wilcoxon signed rank test confirmed GBM’s effectiveness over other models, with the p-value indicating significant performance differences. The study concludes that GBM is notably better for churn prediction, and the employed visualization techniques effectively elucidate key churn factors in the telecommunications sector.
Published: 2024
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34. Effect of the irregular shelterwood system on soil organic carbon stock and soil quality of Shorea robusta Gaertn. f. forest in Nepal

Author: Anil Poudel, Santosh Ayer, Rajeev Joshi, Jeetendra Gautam, Sachin Timilsina, Keshav Khadka, Kishor Prasad Bhatta, and Menuka Maharjan
Subjects: Irregular shelterwood system, Soil properties, Soil quality index, Forest management, Science (General), Q1-390, Social sciences (General), H1-99
Abstract: The effective management of forests relies on the crucial role played bysilvicultural systems. However there exist a significant knowledge gap regarding impact of these systems in Nepalese forests. Therefore, this research was conducted to assess the effects of the forest management activities under irregular shelterwood system on soil organic carbon (SOC) stock and the overall soil quality of Sal (Shorea robusta Gaertn. f.) forests in Terai region of Nepal. Stratified random sampling method with 1.67 % sampling intensity was adopted in this study where management of stands was used as basis of strata. A total of 30 composite soil samples (15 each from managed and unmanaged forest stands) were collected from a depth of 0–30 cm, taken from the four corners and the center of each plot. Soil quality index (SQI) method was used for soil quality assessment using indicators on the basis of prior studies conducted in Nepal. Our study found significant difference in soil parameters except organic carbon, pH, silt, and clay among the managed and unmanaged forest stands (p
Published: 2024
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35. 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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36. 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

37. 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

38. Tumor Necrosis Factor Alpha Inhibitors and Cardiovascular Risk in Rheumatoid Arthritis

Author: Luciano, Nicoletta, Barone, Elisa, Timilsina, Suraj, Gershwin, M. Eric, and Selmi, Carlo
Published: 2023
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39. Flood susceptibility assessment using machine learning approach in the Mohana-Khutiya River of Nepal

Author: Menuka Maharjan, Sachin Timilsina, Santosh Ayer, Bikram Singh, Bikram Manandhar, and Amir Sedhain
Subjects: Flood risk assessment, MaxEnt model, Environmental variables, AUC, Land use land cover, Geology, QE1-996.5, Geophysics. Cosmic physics, QC801-809
Abstract: Nepal, known for its challenging topography and fragile geology is confronted with the constant threat of floods leading to substantial socio-economic losses annually. However, the country's efforts in planning and managing flood risks remain insufficient, especially in the vulnerable Mohana-Khutiya River. Therefore, this study focused on the Mohana-Khutiya River and utilizes the Maximum Entropy (MaxEnt) model to comprehensively map flood susceptibility and fill crucial gaps in flood risk assessments. This study employed a combination of 10 geospatial environmental layers and field-based past flood inventory to implement the MaxEnt machine learning model for flood susceptibility modeling. The available past flood data were divided into two sets, with 75% allocated for model construction and the remaining 25% for model validation. This study demonstrated that the proximity of the river had a significant impact (33.1%) on the occurrence of the flood. Surprisingly, the amount of annual precipitation throughout the year exhibited no detectable contribution to the flood event in the study site. About 4.9% area came under the high flood susceptible zone followed by 12.75 % in the moderate zone and 82.34% in the low-risk zone. The model exhibited excellent performance with an Area Under Curve (AUC) value of 0.935 and a low standard deviation of 0.018, indicating accurate predictions and consistent precision. These results highlight the model's reliability and its significance for developing disaster management policy by local government in the study site. Future research should refine the MaxEnt model by including more variables, validating against observed flood events, and exploring integration with other flood modeling approaches.
Published: 2024
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40. Bacterial Mutation During Seasonal Epidemics

Author: Anuj Sharma, Sujan Timilsina, Peter Abrahamian, Gerald V. Minsavage, Jeffrey B. Jones, Gary E. Vallad, and Erica M. Goss
Subjects: bacteria, epidemics, mutation rate, whole-genome sequencing, Xanthomonas perforans, Microbiology, QR1-502, Botany, QK1-989
Abstract: Rapidly evolving bacterial pathogens pose a unique challenge for long-term plant disease management. In this study, we investigated the types and rate of mutations in bacterial populations during seasonal disease epidemics. Two phylogenetically distinct strains of the bacterial spot pathogen, Xanthomonas perforans, were marked, released in tomato fields, and recaptured at several time points during the growing season. Genomic variations in recaptured isolates were identified by comparative analysis of their whole-genome sequences. In total, 180 unique variations (116 substitutions, 57 insertions/deletions, and 7 structural variations) were identified from 300 genomes, resulting in the overall host-associated mutation rate of ∼0.3 to 0.9/genome/week. This result serves as a benchmark for bacterial mutation during epidemics in similar pathosystems. [Graphic: 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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41. Qualitative Analysis of 400 Life Stories from Children and Young People Working in the Worst Forms of Child Labour in Nepal

Author: Bhattarai (B.C.), Kriti, primary, Burns, Danny, additional, Cannon, Mariah, additional, Hacker, Elizabeth, additional, Sharma, Ranjama, additional, Bhujel, Samjhana, additional, Dawadi, Sushmita, additional, Deshar, Lazana, additional, Dhakal, Utram, additional, Ghimire, Raju, additional, Karki, Shanta, additional, K.C., Anita, additional, Lamsal, Pragya, additional, Luitel, Barsha, additional, Malla, Sudhir, additional, Mishra, Nitish, additional, Thapa, Krishna, additional, Timilsina, Amit, additional, Rai, Arun, additional, Rayamajhi, Durlav, additional, Shakya, Angeliya, additional, Sharma, Kushum, additional, Sherpa, Pema, additional, and Shrestha, Kapil, additional
Published: 2024
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42. Measurement of $\phi$-meson production in Cu$+$Au at $\sqrt{s_{_{NN}}}=200$ GeV and U$+$U at $\sqrt{s_{_{NN}}}=193$ GeV

Author: Abdulameer, N. J., Acharya, U., Aidala, C., Ajitanand, N. N., Akiba, Y., Akimoto, R., Alexander, J., Alfred, M., Alibordi, M., Aoki, K., Apadula, N., Asano, H., Atomssa, E. T., Awes, T. C., Azmoun, B., Babintsev, V., Bai, M., Bai, X., Bannier, B., 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., Roman, V. Canoa, Chen, C. -H., Chiu, M., Chi, C. Y., Choi, I. J., Choi, J. B., Choi, S., Christiansen, P., Chujo, T., Cianciolo, V., Cole, B. A., Connors, M., Corliss, R., Morales, Y. Corrales, Cronin, N., Crossette, N., Csanád, M., Csörgő, T., D'Orazio, L., Datta, A., Daugherity, M. S., David, G., Dean, C. T., Dehmelt, K., Denisov, A., Deshpande, A., Desmond, E. J., Ding, L., Doomra, V., Do, J. H., Drapier, O., Drees, A., Drees, K. A., Durham, J. M., Durum, A., Engelmore, T., Enokizono, A., Esha, R., Eyser, K. O., Fadem, B., Fan, W., 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., Fusayasu, T., Gainey, K., Gal, C., Garg, P., Garishvili, A., Garishvili, I., Giles, M., Giordano, F., Glenn, A., Gong, X., Gonin, M., Goto, Y., de Cassagnac, R. Granier, Grau, N., Greene, S. V., Perdekamp, M. Grosse, Gunji, T., Guragain, H., Gu, Y., Hachiya, T., Haggerty, J. S., Hahn, K. I., Hamagaki, H., Hanks, J., Harvey, M., Hasegawa, S., Hashimoto, K., Hayano, R., Hemmick, T. K., Hester, T., He, X., Hill, J. C., Hodges, A., Hollis, R. S., Homma, K., Hong, B., Hoshino, T., 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., Kapustinsky, J., Kawall, D., Kazantsev, A. V., Key, J. A., Khachatryan, V., Khandai, P. K., Khanzadeev, A., Khatiwada, A., Kijima, K. M., Kim, C., Kim, D. J., Kim, E. -J., Kim, T., Kim, Y. -J., Kim, Y. K., Kincses, D., Kingan, A., Kistenev, E., Klatsky, J., Kleinjan, D., Kline, P., Koblesky, T., Kofarago, M., Komkov, B., Koster, J., Kotchetkov, D., Kotov, D., Kovacs, L., Krizek, F., 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. H., Leitch, M. J., Leitgab, M., Lewis, B., Lewis, N. A., Lim, S. H., Liu, M. X., Li, X., Loomis, D. A., 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., Miyasaka, S., Mizuno, S., Mohanty, A. K., Mohapatra, S., Mondal, M. M., Moon, T., Morrison, D. P., Moskowitz, M., Moukhanova, T. V., Mulilo, B., Murakami, T., Murata, J., Mwai, A., Nagae, T., Nagamiya, S., Nagle, J. L., Nagy, M. I., Nakagawa, I., Nakamiya, Y., Nakamura, K. R., Nakamura, T., Nakano, K., Nattrass, C., Nelson, S., Netrakanti, P. K., Nihashi, M., Niida, T., Nouicer, R., Novitzky, N., Novák, T., Nukazuka, G., Nyanin, A. S., O'Brien, E., Ogilvie, C. A., Oh, J., Oide, H., Okada, K., Orosz, M., Osborn, J. D., Oskarsson, A., 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., Pinkenburg, C., Pisani, R. P., Potekhin, M., Pun, A., Purschke, M. L., Qu, H., Radzevich, P. V., Rak, J., Ramasubramanian, N., Ravinovich, I., Read, K. F., Reynolds, D., Riabov, V., Riabov, Y., Richardson, E., Richford, D., Riveli, N., Roach, D., Rolnick, S. D., Rosati, M., Runchey, J., Ryu, M. S., Sahlmueller, B., Saito, N., Sakaguchi, T., Sako, H., Samsonov, V., Sarsour, M., Sato, S., Sawada, S., Sedgwick, K., Seele, J., Seidl, R., Sekiguchi, Y., Sen, A., Seto, R., Sett, P., Sharma, D., Shaver, A., Shein, I., Shi, Z., Shibata, M., Shibata, T. -A., Shigaki, K., Shimomura, M., 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., 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., Sun, J., Sun, Z., Takahama, R., Takahara, A., Taketani, A., Tanaka, Y., Tanida, K., Tannenbaum, M. J., Tarafdar, S., Taranenko, A., Tennant, E., Timilsina, A., Todoroki, T., Tomášek, M., Torii, H., 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., Vznuzdaev, E., Vértesi, R., Wang, X. R., Wang, Z., Watanabe, D., Watanabe, K., Watanabe, Y., Watanabe, Y. S., Wei, F., Whitaker, S., Wolin, S., Wong, C. P., Woody, C. L., Wysocki, M., Xia, B., Yamaguchi, Y. L., Yanovich, A., Yokkaichi, S., Yoon, I., Younus, I., You, Z., Yushmanov, I. E., Zajc, W. A., Zelenski, A., Zhou, S., and Zou, L.
Subjects: Nuclear Experiment
Abstract: The PHENIX experiment reports systematic measurements at the Relativistic Heavy Ion Collider of $\phi$-meson production in asymmetric Cu$+$Au collisions at $\sqrt{s_{_{NN}}}$=200 GeV and in U$+$U collisions at $\sqrt{s_{_{NN}}}$=193 GeV. Measurements were performed via the $\phi\rightarrow K^{+}K^{-}$ decay channel at midrapidity $|\eta|<0.35$. Features of $\phi$-meson production measured in Cu$+$Cu, Cu$+$Au, Au$+$Au, and U$+$U collisions were found to not depend on the collision geometry, which was expected because the yields are averaged over the azimuthal angle and follow the expected scaling with nuclear-overlap size. The elliptic flow of the $\phi$ meson in Cu$+$Au, Au$+$Au, and U$+$U collisions scales with second-order-participant eccentricity and the length scale of the nuclear-overlap region (estimated with the number of participating nucleons). At moderate $p_T$, $\phi$-meson production measured in Cu$+$Au and U$+$U collisions is consistent with coalescence-model predictions, whereas at high $p_T$ the production is in agreement with expectations for in-medium energy loss of parent partons prior to their fragmentation. The elliptic flow for $\phi$ mesons measured in Cu$+$Au and U$+$U collisions is well described by a (2+1)D viscous-hydrodynamic model with specific-shear viscosity $\eta/s=1/4\pi$., Comment: 412 authors from 76 institutions, 16 pages, 12 figures, 9 tables, 2012 data. v2 is version accepted for publication by Physical Review C. HEPdata 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: 2022
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43. Gymnosperms of Nepal: Diversity, Distribution, Economic Importance, and Future Perspectives

Author: Pandey, Bikram, primary and Timilsina, Arbindra, additional
Published: 2024
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44. MARCH2, a T cell specific factor that restricts HIV-1 infection.

Author: Supawadee Umthong, Uddhav Timilsina, Mary R D'Angelo, Kyle Salka, and Spyridon Stavrou
Subjects: Immunologic diseases. Allergy, RC581-607, Biology (General), QH301-705.5
Abstract: Membrane-associated RING-CH (MARCH) 2 is a member of the MARCH protein family of RING-CH finger E3 ubiquitin ligases that play important roles in regulating the levels of proteins found on the cell surface. MARCH1, 2 and 8 inhibit HIV-1 infection by preventing the incorporation of the envelope glycoproteins into nascent virions. However, a better understanding of the mechanism utilized by MARCH proteins to restrict HIV-1 infection is needed. In this report, we identify an amino acid in human MARCH2, absent in mouse MARCH2, critical for its antiretroviral function. Moreover, we map the domains of human MARCH2 critical for restricting as well as binding to the HIV-1 envelope glycoproteins. In addition, we demonstrate that MARCH2 is present inside nascent virions and reduces particle infectivity by blocking virus entry in a RING-CH-independent manner. Finally, we show that MARCH2 acts as an HIV-1 restriction factor only in primary CD4+ T cells and can prevent cell-to-cell transmission of HIV-1. Our findings reveal important new aspects of the antiviral mechanism utilized by human MARCH2 to restrict HIV-1 that have potential implications to all MARCH proteins with antiviral functions and their viral targets.
Published: 2024
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45. Neural Network-Based Cyber-Threat Detection Strategy in Four Motor-Drive Autonomous Electric Vehicles.

Author: Douglas G. Scruggs, Laxman Timilsina, Behnaz Papari, Ali Arsalan, Grace Muriithi, Gökhan özkan, and Christopher S. Edrington
Published: 2024
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46. Empowering Dataspace 4.0: Unveiling Promise of Decentralized Data-Sharing.

Author: Saeed Hamood Alsamhi, Ammar Hawbani, Santosh Kumar 0006, Mohan Timilsina, Majjed Al-Qatf, Rafiqul Haque, Farhan M. A. Nashwan, Liang Zhao 0004, and Edward Curry
Published: 2024
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47. Textual Pre-Trained Models for Age Screening Across Community Question-Answering.

Author: Alejandro Figueroa 0001 and Mohan Timilsina
Published: 2024
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48. Emerging Trends and Challenges in Thermal Management of Power Electronic Converters: A State of the Art Review.

Author: S. M. Imrat Rahman, Ali Moghassemi, Ali Arsalan, Laxman Timilsina, Phanikumar Chamarthi, Behnaz Papari, Gökhan özkan, and Christopher S. Edrington
Published: 2024
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49. Perception of Climate Change Vulnerability and its Impact on Sexual and Reproductive Health and Rights in Khutiya and Banganga River Basins

Author: Khusbu Poudel, Sujan Karki, Kritee Lamichhane, Amit Timilsina, Sally Dijkerman, and Jagadishwor Ghimire
Subjects: Public aspects of medicine, RA1-1270
Abstract: Background: Nepal is one of the most vulnerable countries to climate change. The drivers of climate risk include its topography, ecological diversity, climatic variability, natural resource dependency, under-development, and socioeconomic vulnerabilities. Climate change affects women and girls in unique ways. Research conducted in Asia Pacific region highlight negative sexual and reproductive health outcomes from climate change-related stressors such as droughts, floods, and air pollution, factors also linked to decreased SRH services utilization, increased maternal mortality rates, and repercussions on women’s mental health. Methods: This is a mixed methods study conducted in two river basins including household surveys with 384 females ages 18-49, 12 focus group discussions, and 22 key informant interviews. We conducted descriptive and thematic analysis. Results: More than half relied on agriculture for income (66%). Despite one-third being heads of households, land ownership was low (13%). Climate change perceptions included rising temperatures (88%), increased heat wave (70%), drying water source (99%), and delayed monsoons (83%), impacting agriculture and increasing women's workload (61%) due to displacement and male migration. 64% reported disturbances in antenatal and postnatal care visits . Inaccessible healthcare facilities during the rainy season increased maternal mortality risks. Heavy river flooding hindered female community health volunteers access leading to childbirth complications. 82% of women feared being unable to protect their children post-climate events. Moreover, 21% of women faced gender-based violence during or after climate disasters. Conclusions: Our findings suggest clear impacts of climate change on women and the communities. Thus, climate adaptation efforts must be designed to address the unique impacts of the crisis on women and girls, making space for their increased participation and leadership. Keywords: Climate change; gender based violence; malnutrition; migration; sexual and reproductive health and rights.
Published: 2024
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50. Autoantibodes to GP210 are a metric for UDCA responses in primary biliary cholangitis

Author: Chan Wang, Zhuye Qin, Mingming Zhang, Yaping Dai, Luyao Zhang, Wenyan Tian, Yuhua Gong, Sufang Chen, Can Yang, Ping Xu, Xingjuan Shi, Weifeng Zhao, Suraj Timilsina, M. Eric Gershwin, Weichang Chen, Fang Qiu, and Xiangdong Liu
Subjects: gp210, Primary biliary cholangitis, sp100, Quantitation, UDCA, Immunologic diseases. Allergy, RC581-607
Abstract: Objectives: Antibodies to gp210 and sp100 are specific and unique anti-nuclear autoantibodies (ANAs) associated with primary biliary cholangitis (PBC). Importantly the presence of anti-gp210 and anti-sp100 responses is indicative of poor clinical outcomes. However, the utility of measuring titers of these antibodies remains unclear. Materials and methods: Using the in-house purified gp210 (HSA108-C18) and sp100 (amino acid position 296–386), we quantitatively measured serum autoantibodies to gp210 and sp100 using chemiluminescence immunoassay (CLIA) in a very large cohort of 390 patients with PBC, including 259 cases with no prior ursodesoxycholic acid (UDCA) treatment and 131 cases with UDCA treatment. We also analyzed serial changes in anti-gp210 and anti-sp100 levels in 245 sequential samples from 88 patients. Results: In our cross-sectional analysis, we detected anti-gp210 immunoglobulin G (IgG) and anti-sp100 IgG autoantibodies in 129 out of 390 (33.1%) and 80 out of 390 (20.5%) PBC patients, respectively. Multivariate analysis revealed that serum IgG (st.β = 0.35, P = 0.003) and gamma-glutamyltransferase (GGT) (st.β = 0.23, P = 0.042) levels at baseline were independently associated with anti-gp210 concentrations. In serial testing, we observed significant fluctuations in anti-gp210 antibody levels. These fluctuations reflected responsiveness to UDCA therapy, particularly in anti-gp210-positive patients with initially lower concentrations in the stages of disease. Conclusions: Our study reflects that quantitative changes of anti-gp210 antibody are indicative of UDCA responses. There is a great need for newer metrics in PBC and we suggest that a more detailed and longer study of these unique ANAs is warranted.
Published: 2024
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