Author: "Zhong, Z." / Publication Type: Electronic Resources - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Zhong, Z."' showing total 226 results

Start Over Author "Zhong, Z." Publication Type Electronic Resources

226 results on '"Zhong, Z."'

1. Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics.

Author: Zhong, Z, Hou, J, Yao, Z, Dong, L, Liu, F, Yue, J, Wu, T, Zheng, J, Ouyang, G, Yang, C, Song, J, Zhong, Z, Hou, J, Yao, Z, Dong, L, Liu, F, Yue, J, Wu, T, Zheng, J, Ouyang, G, Yang, C, and Song, J
Abstract: Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.
Published: 2024

2. Domain generalization enables general cancer cell annotation in single-cell and spatial transcriptomics.

Author: Zhong, Z, Hou, J, Yao, Z, Dong, L, Liu, F, Yue, J, Wu, T, Zheng, J, Ouyang, G, Yang, C, Song, J, Zhong, Z, Hou, J, Yao, Z, Dong, L, Liu, F, Yue, J, Wu, T, Zheng, J, Ouyang, G, Yang, C, and Song, J
Abstract: Single-cell and spatial transcriptome sequencing, two recently optimized transcriptome sequencing methods, are increasingly used to study cancer and related diseases. Cell annotation, particularly for malignant cell annotation, is essential and crucial for in-depth analyses in these studies. However, current algorithms lack accuracy and generalization, making it difficult to consistently and rapidly infer malignant cells from pan-cancer data. To address this issue, we present Cancer-Finder, a domain generalization-based deep-learning algorithm that can rapidly identify malignant cells in single-cell data with an average accuracy of 95.16%. More importantly, by replacing the single-cell training data with spatial transcriptomic datasets, Cancer-Finder can accurately identify malignant spots on spatial slides. Applying Cancer-Finder to 5 clear cell renal cell carcinoma spatial transcriptomic samples, Cancer-Finder demonstrates a good ability to identify malignant spots and identifies a gene signature consisting of 10 genes that are significantly co-localized and enriched at the tumor-normal interface and have a strong correlation with the prognosis of clear cell renal cell carcinoma patients. In conclusion, Cancer-Finder is an efficient and extensible tool for malignant cell annotation.
Published: 2024

3. Cross-Language Taint Analysis: Generating Caller-Sensitive Native Code Specification for Java

Author: Kan, S, Gao, Y, Zhong, Z, Sui, Y, Kan, S, Gao, Y, Zhong, Z, and Sui, Y
Abstract: Cross-language programming is a common practice within the software development industry, offering developers a multitude of advantages such as expressiveness, interoperability, and cross-platform compatibility, for developing large-scale applications. As an important example, JNI (Java Native Interface) programming is widely used in diverse scenarios where Java interacts with code written in other programming languages, such as C or C++. Conventional static analysis based on a single programming language faces challenges when it comes to tracing the flow of values across multiple modules that are coded in different programming languages. In this paper, we introduce CSS, a new Caller-Sensitive Specification approach designed to enhance the static taint analysis of Java programs employing JNI to interface with C/C++ code. In contrast to conservative specifications, this approach takes into consideration the calling context of the invoked C/C++ functions (or cross-language context), resulting in more precise and concise specifications for the side effects of native code. Furthermore, CSS specifically enhances the capabilities of Java analyzers, enabling them to perform precise static taint analysis across language boundaries into native code. The experimental results show that CSS can accurately summarize value-flow information and enhance the ability of Java monolingual static analyzers for cross-language taint flow tracking.
Published: 2024

4. Nonstandard Errors

Author: MENKVELD, AJ, DREBER, A, HOLZMEISTER, F, HUBER, J, JOHANNESSON, M, KIRCHLER, M, NEUSÜß, S, RAZEN, M, WEITZEL, U, ABAD‐DÍAZ, D, ABUDY, M, MANO, N, MARCHAL, A, MARTINEAU, C, MAZZOLA, F, MELOSO, D, MI, MG, MIHET, R, MOHAN, V, MOINAS, S, ANGEL, JJ, GEMAYEL, R, MOORE, D, MU, L, MURAVYEV, D, MURPHY, D, NESZVEDA, G, NEUMEIER, C, NIELSSON, U, NIMALENDRAN, M, NOLTE, S, NORDEN, LL, GERRITSEN, D, AVETIKIAN, AT, O'NEILL, P, OBAID, K, ØDEGAARD, BA, ÖSTBERG, P, PAGNOTTA, E, PAINTER, M, PALAN, S, PALIT, IJ, PARK, A, GIL‐BAZO, J, PASCUAL, R, BACH, A, PASQUARIELLO, P, PASTOR, L, PATEL, V, PATTON, AJ, PEARSON, ND, PELIZZON, L, PELLI, M, PELSTER, M, GILDER, D, PÉRIGNON, C, PFIFFER, C, BAIDOO, E, PHILIP, R, PLÍHAL, T, PRAKASH, P, PRESS, O, PRODROMOU, T, PROKOPCZUK, M, PUTNINS, T, GLOSTEN, LR, QIAN, Y, RAIZADA, G, RAKOWSKI, D, BAKALLI, G, RANALDO, A, REGIS, L, REITZ, S, RENAULT, T, RENJIE, RW, RENO, R, GOMEZ, T, RIDDIOUGH, SJ, RINNE, K, RINTAMÄKI, P, RIORDAN, R, BAO, L, RITTMANNSBERGER, T, LONGARELA, IR, ROESCH, D, ROGNONE, L, ROSEMAN, B, GORBENKO, A, ROŞU, I, ROY, S, RUDOLF, N, RUSH, SR, RZAYEV, K, BARBON, A, RZEŹNIK, AA, SANFORD, A, SANKARAN, H, SARKAR, A, GRAMMIG, J, SARNO, L, SCAILLET, O, SCHARNOWSKI, S, SCHENK‐HOPPÉ, KR, SCHERTLER, A, SCHNEIDER, M, BASHCHENKO, O, SCHROEDER, F, SCHÜRHOFF, N, SCHUSTER, P, GRÉGOIRE, V, SCHWARZ, MA, SEASHOLES, MS, SEEGER, NJ, SHACHAR, O, SHKILKO, A, SHUI, J, SIKIC, M, BINDRA, PC, SIMION, G, SMALES, LA, GÜÇBILMEZ, U, SÖDERLIND, P, SOJLI, E, SOKOLOV, K, SÖNKSEN, J, SPOKEVICIUTE, L, STEFANOVA, D, SUBRAHMANYAM, MG, SZASZI, B, BJØNNES, GH, TALAVERA, O, ADRIAN, T, TANG, Y, TAYLOR, N, THAM, W, THEISSEN, E, THIMME, J, TONKS, I, TRAN, H, TRAPIN, L, TROLLE, AB, BLACK, JR, HAGSTRÖMER, B, VADUVA, MA, VALENTE, G, VAN NESS, RA, VASQUEZ, A, VEROUSIS, T, VERWIJMEREN, P, VILHELMSSON, A, VILKOV, G, VLADIMIROV, V, VOGEL, S, HAMBUCKERS, J, BLACK, BS, VOIGT, S, WAGNER, W, WALTHER, T, WEISS, P, VAN DER WEL, M, WERNER, IM, WESTERHOLM, PJ, WESTHEIDE, C, WIKA, HC, HAPNES, E, WIPPLINGER, E, BOGOEV, D, WOLF, M, WOLFF, CCP, WOLK, L, WONG, W, WRAMPELMEYER, J, WU, Z, XIA, S, XIU, D, HARRIS, JH, XU, K, XU, C, CORREA, SB, YADAV, PK, YAGÜE, J, YAN, C, YANG, A, YOO, W, YU, W, YU, Y, HARRIS, L, YU, S, YUESHEN, BZ, YUFEROVA, D, BONDARENKO, O, ZAMOJSKI, M, ZAREEI, A, ZEISBERGER, SM, ZHANG, L, ZHANG, SS, ZHANG, X, HARTMANN, S, ZHAO, L, ZHONG, Z, ZHOU, ZI, ZHOU, C, BOS, CS, ZHU, XS, ZOICAN, M, ZWINKELS, R, BOSCH‐ROSA, C, BOURI, E, HASSE, J, BROWNLEES, C, CALAMIA, A, CAO, VN, CAPELLE‐BLANCARD, G, ROMERO, LMC, CAPORIN, M, CARRION, A, CASKURLU, T, CHAKRABARTY, B, CHEN, J, HAUTSCH, N, CHERNOV, M, CHEUNG, W, CHINCARINI, LB, CHORDIA, T, CHOW, S, CLAPHAM, B, COLLIARD, J, COMERTON‐FORDE, C, CURRAN, E, DAO, T, HE, X, DARE, W, DAVIES, RJ, DE BLASIS, R, DE NARD, GF, DECLERCK, F, DEEV, O, DEGRYSE, H, DEKU, SY, DESAGRE, C, VAN DIJK, MA, HEATH, D, DIM, C, DIMPFL, T, DONG, YJ, DRUMMOND, PA, DUDDA, T, DUEVSKI, T, DUMITRESCU, A, DYAKOV, T, DYHRBERG, AH, DZIELIŃSKI, M, AIT‐SAHALIA, Y, EKSI, A, KALAK, IE, ELLEN, ST, EUGSTER, N, EVANS, MDD, FARRELL, M, FELEZ‐VINAS, E, FERRARA, G, FERROUHI, EM, FLORI, A, HEDIGER, S, FLUHARTY‐JAIDEE, JT, FOLEY, SDV, FONG, KYL, FOUCAULT, T, FRANUS, T, FRANZONI, F, FRIJNS, B, FRÖMMEL, M, FU, SM, FÜLLBRUNN, SC, HENDERSHOTT, T, GAN, B, GAO, G, GEHRIG, TP, HIBBERT, AM, HJALMARSSON, E, HOELSCHER, SA, HOFFMANN, P, HOLDEN, CW, HORENSTEIN, AR, HUANG, W, HUANG, D, AKMANSOY, O, HURLIN, C, ILCZUK, K, IVASHCHENKO, A, IYER, SR, JAHANSHAHLOO, H, JALKH, N, JONES, CM, JURKATIS, S, JYLHÄ, P, KAECK, AT, ALCOCK, JT, KAISER, G, KARAM, A, KARMAZIENE, E, KASSNER, B, KAUSTIA, M, KAZAK, E, KEARNEY, F, VAN KERVEL, V, KHAN, SA, KHOMYN, MK, ALEXEEV, V, KLEIN, T, KLEIN, O, KLOS, A, KOETTER, M, KOLOKOLOV, A, KORAJCZYK, RA, KOZHAN, R, KRAHNEN, JP, KUHLE, P, KWAN, A, ALOOSH, A, LAJAUNIE, Q, LAM, FYEC, LAMBERT, M, LANGLOIS, H, LAUSEN, J, LAUTER, T, LEIPPOLD, M, LEVIN, V, LI, Y, LI, H, AMATO, L, LIEW, CY, LINDNER, T, LINTON, O, LIU, J, LIU, A, LLORENTE, G, LOF, M, LOHR, A, LONGSTAFF, F, LOPEZ‐LIRA, A, AMAYA, D, MANKAD, S, MENKVELD, AJ, DREBER, A, HOLZMEISTER, F, HUBER, J, JOHANNESSON, M, KIRCHLER, M, NEUSÜß, S, RAZEN, M, WEITZEL, U, ABAD‐DÍAZ, D, ABUDY, M, MANO, N, MARCHAL, A, MARTINEAU, C, MAZZOLA, F, MELOSO, D, MI, MG, MIHET, R, MOHAN, V, MOINAS, S, ANGEL, JJ, GEMAYEL, R, MOORE, D, MU, L, MURAVYEV, D, MURPHY, D, NESZVEDA, G, NEUMEIER, C, NIELSSON, U, NIMALENDRAN, M, NOLTE, S, NORDEN, LL, GERRITSEN, D, AVETIKIAN, AT, O'NEILL, P, OBAID, K, ØDEGAARD, BA, ÖSTBERG, P, PAGNOTTA, E, PAINTER, M, PALAN, S, PALIT, IJ, PARK, A, GIL‐BAZO, J, PASCUAL, R, BACH, A, PASQUARIELLO, P, PASTOR, L, PATEL, V, PATTON, AJ, PEARSON, ND, PELIZZON, L, PELLI, M, PELSTER, M, GILDER, D, PÉRIGNON, C, PFIFFER, C, BAIDOO, E, PHILIP, R, PLÍHAL, T, PRAKASH, P, PRESS, O, PRODROMOU, T, PROKOPCZUK, M, PUTNINS, T, GLOSTEN, LR, QIAN, Y, RAIZADA, G, RAKOWSKI, D, BAKALLI, G, RANALDO, A, REGIS, L, REITZ, S, RENAULT, T, RENJIE, RW, RENO, R, GOMEZ, T, RIDDIOUGH, SJ, RINNE, K, RINTAMÄKI, P, RIORDAN, R, BAO, L, RITTMANNSBERGER, T, LONGARELA, IR, ROESCH, D, ROGNONE, L, ROSEMAN, B, GORBENKO, A, ROŞU, I, ROY, S, RUDOLF, N, RUSH, SR, RZAYEV, K, BARBON, A, RZEŹNIK, AA, SANFORD, A, SANKARAN, H, SARKAR, A, GRAMMIG, J, SARNO, L, SCAILLET, O, SCHARNOWSKI, S, SCHENK‐HOPPÉ, KR, SCHERTLER, A, SCHNEIDER, M, BASHCHENKO, O, SCHROEDER, F, SCHÜRHOFF, N, SCHUSTER, P, GRÉGOIRE, V, SCHWARZ, MA, SEASHOLES, MS, SEEGER, NJ, SHACHAR, O, SHKILKO, A, SHUI, J, SIKIC, M, BINDRA, PC, SIMION, G, SMALES, LA, GÜÇBILMEZ, U, SÖDERLIND, P, SOJLI, E, SOKOLOV, K, SÖNKSEN, J, SPOKEVICIUTE, L, STEFANOVA, D, SUBRAHMANYAM, MG, SZASZI, B, BJØNNES, GH, TALAVERA, O, ADRIAN, T, TANG, Y, TAYLOR, N, THAM, W, THEISSEN, E, THIMME, J, TONKS, I, TRAN, H, TRAPIN, L, TROLLE, AB, BLACK, JR, HAGSTRÖMER, B, VADUVA, MA, VALENTE, G, VAN NESS, RA, VASQUEZ, A, VEROUSIS, T, VERWIJMEREN, P, VILHELMSSON, A, VILKOV, G, VLADIMIROV, V, VOGEL, S, HAMBUCKERS, J, BLACK, BS, VOIGT, S, WAGNER, W, WALTHER, T, WEISS, P, VAN DER WEL, M, WERNER, IM, WESTERHOLM, PJ, WESTHEIDE, C, WIKA, HC, HAPNES, E, WIPPLINGER, E, BOGOEV, D, WOLF, M, WOLFF, CCP, WOLK, L, WONG, W, WRAMPELMEYER, J, WU, Z, XIA, S, XIU, D, HARRIS, JH, XU, K, XU, C, CORREA, SB, YADAV, PK, YAGÜE, J, YAN, C, YANG, A, YOO, W, YU, W, YU, Y, HARRIS, L, YU, S, YUESHEN, BZ, YUFEROVA, D, BONDARENKO, O, ZAMOJSKI, M, ZAREEI, A, ZEISBERGER, SM, ZHANG, L, ZHANG, SS, ZHANG, X, HARTMANN, S, ZHAO, L, ZHONG, Z, ZHOU, ZI, ZHOU, C, BOS, CS, ZHU, XS, ZOICAN, M, ZWINKELS, R, BOSCH‐ROSA, C, BOURI, E, HASSE, J, BROWNLEES, C, CALAMIA, A, CAO, VN, CAPELLE‐BLANCARD, G, ROMERO, LMC, CAPORIN, M, CARRION, A, CASKURLU, T, CHAKRABARTY, B, CHEN, J, HAUTSCH, N, CHERNOV, M, CHEUNG, W, CHINCARINI, LB, CHORDIA, T, CHOW, S, CLAPHAM, B, COLLIARD, J, COMERTON‐FORDE, C, CURRAN, E, DAO, T, HE, X, DARE, W, DAVIES, RJ, DE BLASIS, R, DE NARD, GF, DECLERCK, F, DEEV, O, DEGRYSE, H, DEKU, SY, DESAGRE, C, VAN DIJK, MA, HEATH, D, DIM, C, DIMPFL, T, DONG, YJ, DRUMMOND, PA, DUDDA, T, DUEVSKI, T, DUMITRESCU, A, DYAKOV, T, DYHRBERG, AH, DZIELIŃSKI, M, AIT‐SAHALIA, Y, EKSI, A, KALAK, IE, ELLEN, ST, EUGSTER, N, EVANS, MDD, FARRELL, M, FELEZ‐VINAS, E, FERRARA, G, FERROUHI, EM, FLORI, A, HEDIGER, S, FLUHARTY‐JAIDEE, JT, FOLEY, SDV, FONG, KYL, FOUCAULT, T, FRANUS, T, FRANZONI, F, FRIJNS, B, FRÖMMEL, M, FU, SM, FÜLLBRUNN, SC, HENDERSHOTT, T, GAN, B, GAO, G, GEHRIG, TP, HIBBERT, AM, HJALMARSSON, E, HOELSCHER, SA, HOFFMANN, P, HOLDEN, CW, HORENSTEIN, AR, HUANG, W, HUANG, D, AKMANSOY, O, HURLIN, C, ILCZUK, K, IVASHCHENKO, A, IYER, SR, JAHANSHAHLOO, H, JALKH, N, JONES, CM, JURKATIS, S, JYLHÄ, P, KAECK, AT, ALCOCK, JT, KAISER, G, KARAM, A, KARMAZIENE, E, KASSNER, B, KAUSTIA, M, KAZAK, E, KEARNEY, F, VAN KERVEL, V, KHAN, SA, KHOMYN, MK, ALEXEEV, V, KLEIN, T, KLEIN, O, KLOS, A, KOETTER, M, KOLOKOLOV, A, KORAJCZYK, RA, KOZHAN, R, KRAHNEN, JP, KUHLE, P, KWAN, A, ALOOSH, A, LAJAUNIE, Q, LAM, FYEC, LAMBERT, M, LANGLOIS, H, LAUSEN, J, LAUTER, T, LEIPPOLD, M, LEVIN, V, LI, Y, LI, H, AMATO, L, LIEW, CY, LINDNER, T, LINTON, O, LIU, J, LIU, A, LLORENTE, G, LOF, M, LOHR, A, LONGSTAFF, F, LOPEZ‐LIRA, A, AMAYA, D, and MANKAD, S
Abstract: ABSTRACTIn statistics, samples are drawn from a population in a data‐generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence‐generating process (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants.
Published: 2024

5. Non-Standard Errors

Author: Menkveld, AJ, Dreber, A, Holzmeister, F, Huber, J, Johanneson, M, Kirchler, M, Razen, M, Weitzel, U, Abad, D, Abudy, MM, Adrian, T, Gregoire, V, Hagströmer, B, Hambuckers, J, Hapnes, E, Harris, JH, Harris, L, Hartmann, S, Hasse, J-B, Hautsch, N, He, X-ZT, Ait-Sahalia, Y, Heath, D, Hediger, S, Hendershott, TJ, Hibbert, AM, Hjalmarsson, E, Hoelscher, S, Hoffmann, P, Holden, CW, Horenstein, AR, Huang, W, Akmansoy, O, Huang, D, Hurlin, C, Ivashchenko, A, Iyer, SR, Jahanshahloo, H, Jalkh, N, Jones, CM, Jurkatis, S, Jylha, P, Kaeck, A, Alcock, J, Kaiser, G, Karam, A, Karmaziene, E, Kassner, B, Kaustia, M, Kazak, E, Kearney, F, van Kervel, V, Khan, S, Khomyn, M, Alexeev, V, Klein, T, Klein, O, Klos, A, Koetter, M, Krahnen, JP, Kolokolov, A, Korajczyk, RA, Kozhan, R, Kwan, A, Lajaunie, Q, Aloosh, A, Lam, FYEC, Lambert, M, Langlois, H, Lausen, J, Lauter, T, Leippold, M, Levin, V, Li, Y, Li, MH, Liew, CY, Amato, L, Lindner, T, Linton, OB, Liu, J, Liu, A, Llorente-Alvarez, J-G, Lof, M, Lohr, A, Longstaff, FA, Lopez-Lira, A, Mankad, S, Amaya, D, Mano, N, Marchal, A, Martineau, C, Mazzola, F, Meloso, DC, Mihet, R, Mohan, V, Moinas, S, Moore, D, Mu, L, Angel, JJ, Muravyev, D, Murphy, D, Neszveda, G, Neumeier, C, Nielsson, U, Nimalendran, M, Nolte, S, Nordén, LL, O'Neill, P, Obaid, K, Bach, A, Ødegaard, BA, Östberg, P, Painter, M, Palan, S, Palit, I, Park, A, Pascual Gascó, R, Pasquariello, P, Pastor, L, Patel, V, Baidoo, E, Patton, AJ, Pearson, ND, Pelizzon, L, Pelster, M, Pérignon, C, Pfiffer, C, Philip, R, Plíhal, T, Prakash, P, Press, O-A, Bakalli, G, Prodromou, T, Putnins, TJ, Raizada, G, Rakowski, DA, Ranaldo, A, Regis, L, Reitz, S, Renault, T, Wang, R, Renò, R, Barbon, A, Riddiough, S, Rinne, K, Rintamäki, P, Riordan, R, RITTMANNSBERGER, T, Rodríguez Longarela, I, Rösch, D, Rognone, L, Roseman, B, Rosu, I, Bashchenko, O, Roy, S, Rudolf, N, Rush, S, Rzayev, K, Rzeźnik, A, Sanford, A, Sankaran, H, Sarkar, A, Sarno, L, Scaillet, O, Bindra, PC, Scharnowski, S, Schenk-Hoppé, KR, Schertler, A, Schneider, M, Schroeder, F, Schürhoff, N, Schuster, P, Schwarz, MA, Seasholes, MS, Seeger, N, Bjonnes, GH, Shachar, O, Shkilko, A, Shui, J, Sikic, M, Simion, G, Smales, LA, Söderlind, P, Sojli, E, Sokolov, K, Spokeviciute, L, Black, JR, Stefanova, D, Subrahmanyam, MG, Neusüss, S, Szaszi, B, Talavera, O, Tang, Y, Taylor, N, Tham, WW, Theissen, E, Thimme, J, Black, BS, Tonks, I, Tran, H, Trapin, L, Trolle, AB, Vaduva, M, Valente, G, Van Ness, RA, Vasquez, A, Verousis, T, Verwijmeren, P, Bohorquez, S, Vilhelmsson, A, Vilkov, G, Vladimirov, V, Vogel, S, Voigt, S, Wagner, W, Walther, T, Weiss, P, van der Wel, M, Werner, IM, Bondarenko, O, Westerholm, PJ, Westheide, C, Wipplinger, E, Wolf, M, Wolff, CCP, Wolk, L, Wong, WK, Wrampelmeyer, J, Wu, Z-X, Xia, S, Bos, CS, Xiu, D, Xu, K, Xu, C, Yadav, PK, Yagüe, J, Yan, C, Yang, A, Yoo, W, Yu, W, Yu, S, Bosch-Rosa, C, Yueshen, BZ, Yuferova, D, Zamojski, M, Zareei, A, Zeisberger, S, Zhang, S, Zhang, X, Zhong, Z, Zhou, ZI, Zhou, C, Bouri, E, Zhu, X, Zoican, M, Zwinkels, RCJ, Chen, J, Duevski, T, Gao, G, Gemayel, R, Gilder, D, Kuhle, P, Pagnotta, E, Brownlees, CT, Pelli, M, Sönksen, J, Zhang, L, Ilczuk, K, Bogoev, D, Qian, Y, Wika, HC, Yu, Y, Zhao, L, Mi, M, Calamia, A, Bao, L, Cao, VN, Capelle-Blancard, G, Capera, L, Caporin, M, Carrion, A, Caskurlu, T, Chakrabarty, B, Chernov, M, Cheung, WMY, Chincarini, LB, Chordia, T, Chow, SC, Clapham, B, Colliard, J-E, Comerton-Forde, C, Curran, E, Dao, T, Dare, W, Davies, RJ, De Blasis, R, De Nard, G, Declerck, F, Deev, O, Degryse, H, Deku, S, Desagre, C, Van Dijk, MA, Dim, C, Dimpfl, T, Dong, YJ, Drummond, P, Dudda, T, Dumitrescu, A, Dyakov, T, Dyhrberg, AH, Dzieliński, M, Eksi, A, El Kalak, I, ter Ellen, S, Eugster, N, Evans, MDD, Farrell, M, Félez-Viñas, E, Ferrara, G, FERROUHI, EM, Flori, A, Fluharty-Jaidee, J, Foley, S, Fong, KYL, Foucault, T, Franus, T, Franzoni, FA, Frijns, B, Frömmel, M, Fu, S, Füllbrunn, S, Gan, B, Gehrig, T, Gerritsen, D, Gil-Bazo, J, Glosten, LR, Gomez, T, Gorbenko, A, Güçbilmez, U, Grammig, J, Menkveld, AJ, Dreber, A, Holzmeister, F, Huber, J, Johanneson, M, Kirchler, M, Razen, M, Weitzel, U, Abad, D, Abudy, MM, Adrian, T, Gregoire, V, Hagströmer, B, Hambuckers, J, Hapnes, E, Harris, JH, Harris, L, Hartmann, S, Hasse, J-B, Hautsch, N, He, X-ZT, Ait-Sahalia, Y, Heath, D, Hediger, S, Hendershott, TJ, Hibbert, AM, Hjalmarsson, E, Hoelscher, S, Hoffmann, P, Holden, CW, Horenstein, AR, Huang, W, Akmansoy, O, Huang, D, Hurlin, C, Ivashchenko, A, Iyer, SR, Jahanshahloo, H, Jalkh, N, Jones, CM, Jurkatis, S, Jylha, P, Kaeck, A, Alcock, J, Kaiser, G, Karam, A, Karmaziene, E, Kassner, B, Kaustia, M, Kazak, E, Kearney, F, van Kervel, V, Khan, S, Khomyn, M, Alexeev, V, Klein, T, Klein, O, Klos, A, Koetter, M, Krahnen, JP, Kolokolov, A, Korajczyk, RA, Kozhan, R, Kwan, A, Lajaunie, Q, Aloosh, A, Lam, FYEC, Lambert, M, Langlois, H, Lausen, J, Lauter, T, Leippold, M, Levin, V, Li, Y, Li, MH, Liew, CY, Amato, L, Lindner, T, Linton, OB, Liu, J, Liu, A, Llorente-Alvarez, J-G, Lof, M, Lohr, A, Longstaff, FA, Lopez-Lira, A, Mankad, S, Amaya, D, Mano, N, Marchal, A, Martineau, C, Mazzola, F, Meloso, DC, Mihet, R, Mohan, V, Moinas, S, Moore, D, Mu, L, Angel, JJ, Muravyev, D, Murphy, D, Neszveda, G, Neumeier, C, Nielsson, U, Nimalendran, M, Nolte, S, Nordén, LL, O'Neill, P, Obaid, K, Bach, A, Ødegaard, BA, Östberg, P, Painter, M, Palan, S, Palit, I, Park, A, Pascual Gascó, R, Pasquariello, P, Pastor, L, Patel, V, Baidoo, E, Patton, AJ, Pearson, ND, Pelizzon, L, Pelster, M, Pérignon, C, Pfiffer, C, Philip, R, Plíhal, T, Prakash, P, Press, O-A, Bakalli, G, Prodromou, T, Putnins, TJ, Raizada, G, Rakowski, DA, Ranaldo, A, Regis, L, Reitz, S, Renault, T, Wang, R, Renò, R, Barbon, A, Riddiough, S, Rinne, K, Rintamäki, P, Riordan, R, RITTMANNSBERGER, T, Rodríguez Longarela, I, Rösch, D, Rognone, L, Roseman, B, Rosu, I, Bashchenko, O, Roy, S, Rudolf, N, Rush, S, Rzayev, K, Rzeźnik, A, Sanford, A, Sankaran, H, Sarkar, A, Sarno, L, Scaillet, O, Bindra, PC, Scharnowski, S, Schenk-Hoppé, KR, Schertler, A, Schneider, M, Schroeder, F, Schürhoff, N, Schuster, P, Schwarz, MA, Seasholes, MS, Seeger, N, Bjonnes, GH, Shachar, O, Shkilko, A, Shui, J, Sikic, M, Simion, G, Smales, LA, Söderlind, P, Sojli, E, Sokolov, K, Spokeviciute, L, Black, JR, Stefanova, D, Subrahmanyam, MG, Neusüss, S, Szaszi, B, Talavera, O, Tang, Y, Taylor, N, Tham, WW, Theissen, E, Thimme, J, Black, BS, Tonks, I, Tran, H, Trapin, L, Trolle, AB, Vaduva, M, Valente, G, Van Ness, RA, Vasquez, A, Verousis, T, Verwijmeren, P, Bohorquez, S, Vilhelmsson, A, Vilkov, G, Vladimirov, V, Vogel, S, Voigt, S, Wagner, W, Walther, T, Weiss, P, van der Wel, M, Werner, IM, Bondarenko, O, Westerholm, PJ, Westheide, C, Wipplinger, E, Wolf, M, Wolff, CCP, Wolk, L, Wong, WK, Wrampelmeyer, J, Wu, Z-X, Xia, S, Bos, CS, Xiu, D, Xu, K, Xu, C, Yadav, PK, Yagüe, J, Yan, C, Yang, A, Yoo, W, Yu, W, Yu, S, Bosch-Rosa, C, Yueshen, BZ, Yuferova, D, Zamojski, M, Zareei, A, Zeisberger, S, Zhang, S, Zhang, X, Zhong, Z, Zhou, ZI, Zhou, C, Bouri, E, Zhu, X, Zoican, M, Zwinkels, RCJ, Chen, J, Duevski, T, Gao, G, Gemayel, R, Gilder, D, Kuhle, P, Pagnotta, E, Brownlees, CT, Pelli, M, Sönksen, J, Zhang, L, Ilczuk, K, Bogoev, D, Qian, Y, Wika, HC, Yu, Y, Zhao, L, Mi, M, Calamia, A, Bao, L, Cao, VN, Capelle-Blancard, G, Capera, L, Caporin, M, Carrion, A, Caskurlu, T, Chakrabarty, B, Chernov, M, Cheung, WMY, Chincarini, LB, Chordia, T, Chow, SC, Clapham, B, Colliard, J-E, Comerton-Forde, C, Curran, E, Dao, T, Dare, W, Davies, RJ, De Blasis, R, De Nard, G, Declerck, F, Deev, O, Degryse, H, Deku, S, Desagre, C, Van Dijk, MA, Dim, C, Dimpfl, T, Dong, YJ, Drummond, P, Dudda, T, Dumitrescu, A, Dyakov, T, Dyhrberg, AH, Dzieliński, M, Eksi, A, El Kalak, I, ter Ellen, S, Eugster, N, Evans, MDD, Farrell, M, Félez-Viñas, E, Ferrara, G, FERROUHI, EM, Flori, A, Fluharty-Jaidee, J, Foley, S, Fong, KYL, Foucault, T, Franus, T, Franzoni, FA, Frijns, B, Frömmel, M, Fu, S, Füllbrunn, S, Gan, B, Gehrig, T, Gerritsen, D, Gil-Bazo, J, Glosten, LR, Gomez, T, Gorbenko, A, Güçbilmez, U, and Grammig, J
Published: 2024

6. Simultaneous Observation of the Inner and Outer Electron Diffusion Region in Reconnection with Large Guide Field

Author: Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., Russell, C. T., Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., and Russell, C. T.
Abstract: This paper presents a simultaneous observation of the inner and outer electron diffusion region (EDR) at the dayside magnetopause by the magnetospheric multiscale (MMS) spacecraft. The EDR was observed in magnetic reconnection with a large guide field. The inner EDR was characterized by positive J center dot E ' while the outer EDR is manifested by negative J center dot E ' and opposite out-of-plane electric field to that in the inner EDR. One pair of the spacecraft detected the inner EDR while the other pair encountered the outer EDR. Moreover, the two pairs were on the opposite side of the X-line as they observed the bidirectional accelerated electron jets. The fortuitous formation of MMS allows us to estimate the maximum length of the inner EDR as similar to 36 d e and the lower bound of the reconnection rate as 0.142 +/- 0.041. These observations have far-reaching implications for understanding the electron physics in reconnection.
Published: 2023
Full Text: View/download PDF

7. Simultaneous Observation of the Inner and Outer Electron Diffusion Region in Reconnection with Large Guide Field

Author: Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., Russell, C. T., Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., and Russell, C. T.
Abstract: This paper presents a simultaneous observation of the inner and outer electron diffusion region (EDR) at the dayside magnetopause by the magnetospheric multiscale (MMS) spacecraft. The EDR was observed in magnetic reconnection with a large guide field. The inner EDR was characterized by positive J center dot E ' while the outer EDR is manifested by negative J center dot E ' and opposite out-of-plane electric field to that in the inner EDR. One pair of the spacecraft detected the inner EDR while the other pair encountered the outer EDR. Moreover, the two pairs were on the opposite side of the X-line as they observed the bidirectional accelerated electron jets. The fortuitous formation of MMS allows us to estimate the maximum length of the inner EDR as similar to 36 d e and the lower bound of the reconnection rate as 0.142 +/- 0.041. These observations have far-reaching implications for understanding the electron physics in reconnection.
Published: 2023
Full Text: View/download PDF

8. Simultaneous Observation of the Inner and Outer Electron Diffusion Region in Reconnection with Large Guide Field

Author: Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., Russell, C. T., Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., and Russell, C. T.
Abstract: This paper presents a simultaneous observation of the inner and outer electron diffusion region (EDR) at the dayside magnetopause by the magnetospheric multiscale (MMS) spacecraft. The EDR was observed in magnetic reconnection with a large guide field. The inner EDR was characterized by positive J center dot E ' while the outer EDR is manifested by negative J center dot E ' and opposite out-of-plane electric field to that in the inner EDR. One pair of the spacecraft detected the inner EDR while the other pair encountered the outer EDR. Moreover, the two pairs were on the opposite side of the X-line as they observed the bidirectional accelerated electron jets. The fortuitous formation of MMS allows us to estimate the maximum length of the inner EDR as similar to 36 d e and the lower bound of the reconnection rate as 0.142 +/- 0.041. These observations have far-reaching implications for understanding the electron physics in reconnection.
Published: 2023
Full Text: View/download PDF

9. Scalable Compositional Static Taint Analysis for Sensitive Data Tracing on Industrial Micro-Services

Author: Zhong, Z, Liu, J, Wu, D, Di, P, Sui, Y, Liu, AX, Lui, JCS, Zhong, Z, Liu, J, Wu, D, Di, P, Sui, Y, Liu, AX, and Lui, JCS
Abstract: In recent years there has been an increasing demand for sensitive data tracing for industrial microservices these include change of governance data breach detection to data consistency validation As an information tracking technique Taint analysis is widely used to address these demands This paper aims to share our experience in developing a scalable static taint analyzer on sensitive data tracing for large scale industrial microservices Although several taint analyzers have been proposed for Java applications our experiments show that existing approaches are inefficient and or ineffective in terms of low recall precision rates for analyzing large scale industrial microservices Instead we present CFTaint a compositional field based taint analyzer to address the challenges for popular microservices running on industrial Fintech applications CFTaint improves scalability by using a fast compositional function summary which summarizes the data propagation of each function during the on the fly taint analysis CFTaint also uses a novel filed based algorithm to analyze the taint propagation based on specified sensitive fields to reduce false negatives Our field based algorithm maximizes the soundness of our approach even when the taint tracking is performed on an unsound call graph Furthermore we also propose an efficient code transformation method to model the behaviours of the containers which allows our analysis to trace data propagation in a container environment Experiments on numerous production microservices demonstrate the high recall 96 09 rates and precision 93 51 for tracing sensitive data of CFTaint with low time complexity 121 73 seconds
Published: 2023

10. Non-Standard Errors

Author: Menkveld, A.J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, G.U., Abad, D., Abudy, M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., Bach, A., Baidoo, E., Bakalli, G., Barbon, A., Bashchenko, O., Bindra, P.C., Bjonnes, G.H., Black, J., Black, B.S., Bohorquez, S., Bondarenko, O., Bos, C.S., Bosch-Rosa, C., Bouri, E., Brownlees, C.T., Calamia, A., Cao, V.N., Capelle-Blancard, G., Capera, L., Caporin, M., Carrion, A., Caskurlu, T., Chakrabarty, B., Chernov, M., Cheung, W.M., Chincarini, L.B., Chordia, T., Chow, S.C., Clapham, B., Colliard, J.-E., Comerton-Forde, C., Curran, E., Dao, T., Dare, W., Davies, R.J., Blasis, R. De, Nard, G. De, DeClerck, F., Deev, O., Degryse, H., Deku, S., Desagre, C., Dijk, M.A van, Dim, C., Dimpfl, T., Dong, Y., Drummond, P., Dudda, T., Dumitrescu, A., Dyakov, T., Dyhrberg, A.H., Dzieliński, M., Eksi, A., Kalak, I. El, Ellen, S. ter, Eugster, N., Evans, M.D.D., Farrell, M., Félez-Viñas, E., Ferrara, G., Ferrouhi, E.M., Flori, A., Fluharty-Jaidee, J., Foley, S., Fong, K.Y.L., Foucault, T., Franus, T., Franzoni, F.A., Frijns, B., Frömmel, M., Fu, S., Füllbrunn, S.C., Gan, B., Gehrig, T., Gerritsen, D., Gil-Bazo, J., Glosten, L.R., Gomez, T., Gorbenko, A., Güçbilmez, U., Grammig, J., Gregoire, V., Hagströmer, B., Hambuckers, J., Hapnes, E., Harris, J.H., Harris, L., Hartmann, S., Hasse, J.-B., Hautsch, N., He, X., Heath, D., Hediger, S., Hendershott, T., Hibbert, A.M., Hjalmarsson, E., Hoelscher, S.A., Hoffmann, P., Holden, C.W., Horenstein, A.R., Huang, W., Huang, D., Hurlin, C., Ivashchenko, A., Iyer, S.R., Jahanshahloo, H., Jalkh, N., Jones, C.M., Jurkatis, S., Jylha, P., Kaeck, A., Kaiser, G., Karam, A., Karmaziene, E., Kassner, B., Kaustia, M., Kazak, E., Kearney, F., Kervel, V. van, Khan, S., Khomyn, M., Klein, T., Klein, O., Klos, A., Koetter, M., Krahnen, J.P., Kolokolov, A., Korajczyk, R.A., Kozhan, R., Kwan, A., Lajaunie, Q., Lam, F.E.C., Lambert, M., Langlois, H., Lausen, J., Lauter, T., Leippold, M., Levin, V., Li, Y., Li, H., Liew, C.Y., Lindner, T., Linton, O.B., Liu, J., Liu, A., Llorente, G., Lof, M., Lohr, A., Longstaff, F.A., Lopez-Lira, A., Mankad, S., Mano, N., Marchal, A., Martineau, C., Mazzola, F., Meloso, D., Mihet, R., Mohan, V., Moinas, S., Moore, D., Mu, L., Muravyev, D., Murphy, D., Neszveda, G., Neumeier, C., Nielsson, U., Nimalendran, M., Nolte, S., Norden, L.L., O'Neill, P., Obaid, K., Ødegaard, B.A., Östberg, P., Painter, M., Palan, S., Palit, I., Park, A., Pascual, R., Pasquariello, P., Pastor, L., Patel, V., Patton, A.J., Pearson, N.D., Pelizzon, L., Pelster, M., Pérignon, C., Pfiffer, C., Philip, R., Plíhal, T., Prakash, P., Press, O.-A., Prodromou, T., Putniņš, T.J., Raizada, G., Rakowski, D.A., Ranaldo, A., Regis, L., Reitz, S., Renault, T., Renjie, R.W., Renò, R., Riddiough, S., Rinne, K., Rintamäki, P., Riordan, R., Rittmannsberger, T., Rodríguez-Longarela, I., Rösch, D., Rognone, L., Roseman, B., Rosu, I., Roy, S., Rudolf, N., Rush, S., Rzayev, K., Rzeźnik, A., Sanford, A., Sankaran, H., Sarkar, A., Sarno, L., Scaillet, O., Scharnowski, S., Schenk-Hoppé, K.R., Schertler, A., Schneider, M., Schroeder, F., Schürhoff, N., Schuster, P., Schwarz, M.A., Seasholes, M.S., Seeger, N., Shachar, O., Shkilko, A., Shui, J., Sikic, M., Simion, G., Smales, L.A., Söderlind, P., Sojli, E., Sokolov, K., Spokeviciute, L., Stefanova, D., Subrahmanyam, M.G., Neusüss, S., Szaszi, B., Talavera, O., Tang, Y., Taylor, N., Tham, W.W., Theissen, E., Thimme, J., Tonks, I., Tran, H., Trapin, L., Trolle, A.B., Valente, G., Ness, R.A. Van, Vasquez, A., Verousis, T., Verwijmeren, P., Vilhelmsson, A., Vilkov, G., Vladimirov, V., Vogel, S., Voigt, S., Wagner, W., Walther, T., Weiss, P., Wel, M. van der, Werner, I.M., Westerholm, P.J., Westheide, C., Wipplinger, E., Wolf, M., Wolff, C.C.P., Wolk, L., Wong, W.-K., Wrampelmeyer, J., Xia, S., Xiu, D., Xu, K., Xu, C., Yadav, P.K., Yagüe, J., Yan, C., Yang, A., Yoo, W., Yu, W., Yu, S., Yueshen, B.Z., Yuferova, D., Zamojski, M., Zareei, A., Zeisberger, S.M., Zhang, S.S., Zhang, X., Zhong, Z., Zhou, Z.I., Zhou, C., Zhu, X.S., Zoican, M., Zwinkels, R.C.J., Chen, J., Duevski, T., Gao, G., Gemayel, R., Gilder, D. de, Kuhle, P., Pagnotta, E., Pelli, M., Sönksen, J., Zhang, L., Ilczuk, K., Bogoev, D., Qian, Y., Wika, H.C., Yu, Y., Zhao, L., Mi, M., Bao, L., Vaduva, A., Prokopczuk, P., Avetikian, A., Wu, Z.-X., Menkveld, A.J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, G.U., Abad, D., Abudy, M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., Bach, A., Baidoo, E., Bakalli, G., Barbon, A., Bashchenko, O., Bindra, P.C., Bjonnes, G.H., Black, J., Black, B.S., Bohorquez, S., Bondarenko, O., Bos, C.S., Bosch-Rosa, C., Bouri, E., Brownlees, C.T., Calamia, A., Cao, V.N., Capelle-Blancard, G., Capera, L., Caporin, M., Carrion, A., Caskurlu, T., Chakrabarty, B., Chernov, M., Cheung, W.M., Chincarini, L.B., Chordia, T., Chow, S.C., Clapham, B., Colliard, J.-E., Comerton-Forde, C., Curran, E., Dao, T., Dare, W., Davies, R.J., Blasis, R. De, Nard, G. De, DeClerck, F., Deev, O., Degryse, H., Deku, S., Desagre, C., Dijk, M.A van, Dim, C., Dimpfl, T., Dong, Y., Drummond, P., Dudda, T., Dumitrescu, A., Dyakov, T., Dyhrberg, A.H., Dzieliński, M., Eksi, A., Kalak, I. El, Ellen, S. ter, Eugster, N., Evans, M.D.D., Farrell, M., Félez-Viñas, E., Ferrara, G., Ferrouhi, E.M., Flori, A., Fluharty-Jaidee, J., Foley, S., Fong, K.Y.L., Foucault, T., Franus, T., Franzoni, F.A., Frijns, B., Frömmel, M., Fu, S., Füllbrunn, S.C., Gan, B., Gehrig, T., Gerritsen, D., Gil-Bazo, J., Glosten, L.R., Gomez, T., Gorbenko, A., Güçbilmez, U., Grammig, J., Gregoire, V., Hagströmer, B., Hambuckers, J., Hapnes, E., Harris, J.H., Harris, L., Hartmann, S., Hasse, J.-B., Hautsch, N., He, X., Heath, D., Hediger, S., Hendershott, T., Hibbert, A.M., Hjalmarsson, E., Hoelscher, S.A., Hoffmann, P., Holden, C.W., Horenstein, A.R., Huang, W., Huang, D., Hurlin, C., Ivashchenko, A., Iyer, S.R., Jahanshahloo, H., Jalkh, N., Jones, C.M., Jurkatis, S., Jylha, P., Kaeck, A., Kaiser, G., Karam, A., Karmaziene, E., Kassner, B., Kaustia, M., Kazak, E., Kearney, F., Kervel, V. van, Khan, S., Khomyn, M., Klein, T., Klein, O., Klos, A., Koetter, M., Krahnen, J.P., Kolokolov, A., Korajczyk, R.A., Kozhan, R., Kwan, A., Lajaunie, Q., Lam, F.E.C., Lambert, M., Langlois, H., Lausen, J., Lauter, T., Leippold, M., Levin, V., Li, Y., Li, H., Liew, C.Y., Lindner, T., Linton, O.B., Liu, J., Liu, A., Llorente, G., Lof, M., Lohr, A., Longstaff, F.A., Lopez-Lira, A., Mankad, S., Mano, N., Marchal, A., Martineau, C., Mazzola, F., Meloso, D., Mihet, R., Mohan, V., Moinas, S., Moore, D., Mu, L., Muravyev, D., Murphy, D., Neszveda, G., Neumeier, C., Nielsson, U., Nimalendran, M., Nolte, S., Norden, L.L., O'Neill, P., Obaid, K., Ødegaard, B.A., Östberg, P., Painter, M., Palan, S., Palit, I., Park, A., Pascual, R., Pasquariello, P., Pastor, L., Patel, V., Patton, A.J., Pearson, N.D., Pelizzon, L., Pelster, M., Pérignon, C., Pfiffer, C., Philip, R., Plíhal, T., Prakash, P., Press, O.-A., Prodromou, T., Putniņš, T.J., Raizada, G., Rakowski, D.A., Ranaldo, A., Regis, L., Reitz, S., Renault, T., Renjie, R.W., Renò, R., Riddiough, S., Rinne, K., Rintamäki, P., Riordan, R., Rittmannsberger, T., Rodríguez-Longarela, I., Rösch, D., Rognone, L., Roseman, B., Rosu, I., Roy, S., Rudolf, N., Rush, S., Rzayev, K., Rzeźnik, A., Sanford, A., Sankaran, H., Sarkar, A., Sarno, L., Scaillet, O., Scharnowski, S., Schenk-Hoppé, K.R., Schertler, A., Schneider, M., Schroeder, F., Schürhoff, N., Schuster, P., Schwarz, M.A., Seasholes, M.S., Seeger, N., Shachar, O., Shkilko, A., Shui, J., Sikic, M., Simion, G., Smales, L.A., Söderlind, P., Sojli, E., Sokolov, K., Spokeviciute, L., Stefanova, D., Subrahmanyam, M.G., Neusüss, S., Szaszi, B., Talavera, O., Tang, Y., Taylor, N., Tham, W.W., Theissen, E., Thimme, J., Tonks, I., Tran, H., Trapin, L., Trolle, A.B., Valente, G., Ness, R.A. Van, Vasquez, A., Verousis, T., Verwijmeren, P., Vilhelmsson, A., Vilkov, G., Vladimirov, V., Vogel, S., Voigt, S., Wagner, W., Walther, T., Weiss, P., Wel, M. van der, Werner, I.M., Westerholm, P.J., Westheide, C., Wipplinger, E., Wolf, M., Wolff, C.C.P., Wolk, L., Wong, W.-K., Wrampelmeyer, J., Xia, S., Xiu, D., Xu, K., Xu, C., Yadav, P.K., Yagüe, J., Yan, C., Yang, A., Yoo, W., Yu, W., Yu, S., Yueshen, B.Z., Yuferova, D., Zamojski, M., Zareei, A., Zeisberger, S.M., Zhang, S.S., Zhang, X., Zhong, Z., Zhou, Z.I., Zhou, C., Zhu, X.S., Zoican, M., Zwinkels, R.C.J., Chen, J., Duevski, T., Gao, G., Gemayel, R., Gilder, D. de, Kuhle, P., Pagnotta, E., Pelli, M., Sönksen, J., Zhang, L., Ilczuk, K., Bogoev, D., Qian, Y., Wika, H.C., Yu, Y., Zhao, L., Mi, M., Bao, L., Vaduva, A., Prokopczuk, P., Avetikian, A., and Wu, Z.-X.
Abstract: 31 mei 2023, Contains fulltext : 240328.pdf (Author’s version preprint ) (Open Access), In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Published: 2023

11. Observations of Dynamical Flux Ropes and Active Multiple X-Line Reconnection at Earth's Magnetopause

Author: Zhong, Z. H., Lei, G. Y., Zhou, M., Zhang, M., Tang, R. X., Graham, Daniel B., Pang, Y., Deng, X. H., Khotyaintsev, Yuri V., Zhong, Z. H., Lei, G. Y., Zhou, M., Zhang, M., Tang, R. X., Graham, Daniel B., Pang, Y., Deng, X. H., and Khotyaintsev, Yuri V.
Abstract: This paper presents the magnetospheric multiscale (MMS) observations of three flux ropes (FRs) sequentially in a reconnection exhaust at Earth's magnetopause. Three active X-lines, which are responsible for the formation of these FRs, were also detected by MMS, providing strong evidence that the FRs were generated by multiple X-line reconnection. We find that the core field inside the FRs considerably affects the Hall current in the adjacent X-lines. The intense core field of the FRs deflected the electron outflow jet, forming the electron-scale Hall magnetic field on the magnetosheath side. Additionally, an active secondary reconnection was observed at the center of one FR. This secondary reconnection split the FR into two smaller FRs and produced sharp density gradients and intense fluctuations of electric field and current within the FR. These observations advance the understanding of the formation and evolution of FRs during multiple X-line reconnection at magnetopause.
Published: 2023
Full Text: View/download PDF

12. Simultaneous Observation of the Inner and Outer Electron Diffusion Region in Reconnection with Large Guide Field

Author: Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., Russell, C. T., Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., and Russell, C. T.
Abstract: This paper presents a simultaneous observation of the inner and outer electron diffusion region (EDR) at the dayside magnetopause by the magnetospheric multiscale (MMS) spacecraft. The EDR was observed in magnetic reconnection with a large guide field. The inner EDR was characterized by positive J center dot E ' while the outer EDR is manifested by negative J center dot E ' and opposite out-of-plane electric field to that in the inner EDR. One pair of the spacecraft detected the inner EDR while the other pair encountered the outer EDR. Moreover, the two pairs were on the opposite side of the X-line as they observed the bidirectional accelerated electron jets. The fortuitous formation of MMS allows us to estimate the maximum length of the inner EDR as similar to 36 d e and the lower bound of the reconnection rate as 0.142 +/- 0.041. These observations have far-reaching implications for understanding the electron physics in reconnection.
Published: 2023
Full Text: View/download PDF

13. Simultaneous Observation of the Inner and Outer Electron Diffusion Region in Reconnection with Large Guide Field

Author: Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., Russell, C. T., Tian, Z. C., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Gershman, D. J., Khotyaintsev, Yuri V., and Russell, C. T.
Abstract: This paper presents a simultaneous observation of the inner and outer electron diffusion region (EDR) at the dayside magnetopause by the magnetospheric multiscale (MMS) spacecraft. The EDR was observed in magnetic reconnection with a large guide field. The inner EDR was characterized by positive J center dot E ' while the outer EDR is manifested by negative J center dot E ' and opposite out-of-plane electric field to that in the inner EDR. One pair of the spacecraft detected the inner EDR while the other pair encountered the outer EDR. Moreover, the two pairs were on the opposite side of the X-line as they observed the bidirectional accelerated electron jets. The fortuitous formation of MMS allows us to estimate the maximum length of the inner EDR as similar to 36 d e and the lower bound of the reconnection rate as 0.142 +/- 0.041. These observations have far-reaching implications for understanding the electron physics in reconnection.
Published: 2023
Full Text: View/download PDF

14. Plant size, latitude, and phylogeny explain within-population variability in herbivory

Author: Moreira Tomé, Xoaquín [0000-0003-0166-838X], Robinson, M L, Hahn, P G, Inouye, B D, Underwood, N, Whitehead, S R, Abbott, K C, Bruna, E M, Cacho, N I, Dyer, L A, Abdala-Roberts, L, Allen, W J, Lindroth, R L, LoPresti, E F, Losada, M, Louthan, A M, Luizzi, V J, Lynch, S C, Lynn, J S, Lyon, N J, Maia, L F, Maia, R A, Andrade, J F, Mannall, T L, Martin, B S, Massad, T J, McCall, A C, McGurrin, K, Merwin, A C, Mijango-Ramos, Z, Mills, C H, Moles, A T, Moore, C M, Angulo, D F, Moreira Tomé, Xoaquín, Morrison, C R, Moshobane, M C, Muola, A, Nakadai, R, Nakajima, K, Novais, S, Ogbebor, C O, Ohsaki, H, Pan, V S, Anjos, D, Pardikes, N A, Pareja, M, Parthasarathy, N, Pawar, R R, Paynter, Q, Pearse, I S, Penczykowski, R M, Pepi, A A, Pereira, C C, Phartyal, S S, Anstett, D N, Piper, F I, Poveda, K, Pringle, E G, Puy, J, Quijano Gaudes, Laura, Quintero, C, Rasmann, S, Rosche, C, Rosenheim, L Y, Rosenheim, J A, Bagchi, R, Runyon, J B, Sadeh, A, Sakata, Y, Salcido, D M, Salgado-Luarte, C, Santos, B A, Sapir, Y, Sasal, Y, Sato, Y, Sawant, M, Bagchi, S, Schroeder, H, Schumann, I, Segoli, M, Segre, H, Shelef, O, Shinohara, N, Singh, R P, Smith, D S, Sobral, M, Stotz, G C, Barbosa, M, Tack, Ayco J. M., Tayal, M, Tooker, J F, Torrico-Bazoberry, D, Tougeron, K, Trowbridge, A M, Utsumi, S, Uyi, O, Vaca-Uribe, J L, Valtonen, A, Barrett, S, van Dijk, L J A, Vandvik, V, Villellas, J, Waller, L P, Weber, M G, Yamawo, A, Yim, S, Zarnetske, P L, Zehr, L N, Zhong, Z, Baskett, C A, Wetzel, W C, Ben-Simchon, E, Bloodworth, K J, Bronstein, J L, Buckley, Y M, Burghardt, K T, Bustos-Segura, C, Calixto, E S, Carvalho, R L, Castagneyrol, B, Chiuffo, M C, Cinoğlu, D, Cinto Mejía, E, Cock, M C, Cogni, R, Cope, O L, Cornelissen, T, Cortez, D R, Crowder, D W, Dallstream, C, Dáttilo, W, Davis, J K, Dimarco, R D, Dole, H E, Egbon, I N, Eisenring, M, Ejomah, A, Elderd, B D, Endara, M-J, Eubanks, M D, Everingham, S E, Farah, K N, Farias, R P, Fernandes, A P, Fernandes, G W, Ferrante, M, Finn, A, Florjancic, G A, Forister, M L, Fox, Q N, Frago, E, França, F M, Getman-Pickering, A S, Getman-Pickering, Z, Gianoli, E, Gooden, B, Gossner, M M, Greig, K A, Gripenberg, S, Groenteman, R, Grof-Tisza, P, Haack, N, Hahn, L, Haq, S M, Helms, A M, Hennecke, J, Hermann, S L, Holeski, L M, Holm, S, Hutchinson, M C, Jackson, E E, Kagiya, S, Kalske, A, Kalwajtys, M, Karban, R, Kariyat, R, Keasar, T, Kersch-Becker, M F, Kharouba, H M, Kim, T N, Kimuyu, D M, Kluse, J, Koerner, S E, Komatsu, K J, Krishnan, S, Laihonen, M, Lamelas-López, L, LaScaleia, M C, Lecomte, N, Lehn, C R, Li, X, Moreira Tomé, Xoaquín [0000-0003-0166-838X], Robinson, M L, Hahn, P G, Inouye, B D, Underwood, N, Whitehead, S R, Abbott, K C, Bruna, E M, Cacho, N I, Dyer, L A, Abdala-Roberts, L, Allen, W J, Lindroth, R L, LoPresti, E F, Losada, M, Louthan, A M, Luizzi, V J, Lynch, S C, Lynn, J S, Lyon, N J, Maia, L F, Maia, R A, Andrade, J F, Mannall, T L, Martin, B S, Massad, T J, McCall, A C, McGurrin, K, Merwin, A C, Mijango-Ramos, Z, Mills, C H, Moles, A T, Moore, C M, Angulo, D F, Moreira Tomé, Xoaquín, Morrison, C R, Moshobane, M C, Muola, A, Nakadai, R, Nakajima, K, Novais, S, Ogbebor, C O, Ohsaki, H, Pan, V S, Anjos, D, Pardikes, N A, Pareja, M, Parthasarathy, N, Pawar, R R, Paynter, Q, Pearse, I S, Penczykowski, R M, Pepi, A A, Pereira, C C, Phartyal, S S, Anstett, D N, Piper, F I, Poveda, K, Pringle, E G, Puy, J, Quijano Gaudes, Laura, Quintero, C, Rasmann, S, Rosche, C, Rosenheim, L Y, Rosenheim, J A, Bagchi, R, Runyon, J B, Sadeh, A, Sakata, Y, Salcido, D M, Salgado-Luarte, C, Santos, B A, Sapir, Y, Sasal, Y, Sato, Y, Sawant, M, Bagchi, S, Schroeder, H, Schumann, I, Segoli, M, Segre, H, Shelef, O, Shinohara, N, Singh, R P, Smith, D S, Sobral, M, Stotz, G C, Barbosa, M, Tack, Ayco J. M., Tayal, M, Tooker, J F, Torrico-Bazoberry, D, Tougeron, K, Trowbridge, A M, Utsumi, S, Uyi, O, Vaca-Uribe, J L, Valtonen, A, Barrett, S, van Dijk, L J A, Vandvik, V, Villellas, J, Waller, L P, Weber, M G, Yamawo, A, Yim, S, Zarnetske, P L, Zehr, L N, Zhong, Z, Baskett, C A, Wetzel, W C, Ben-Simchon, E, Bloodworth, K J, Bronstein, J L, Buckley, Y M, Burghardt, K T, Bustos-Segura, C, Calixto, E S, Carvalho, R L, Castagneyrol, B, Chiuffo, M C, Cinoğlu, D, Cinto Mejía, E, Cock, M C, Cogni, R, Cope, O L, Cornelissen, T, Cortez, D R, Crowder, D W, Dallstream, C, Dáttilo, W, Davis, J K, Dimarco, R D, Dole, H E, Egbon, I N, Eisenring, M, Ejomah, A, Elderd, B D, Endara, M-J, Eubanks, M D, Everingham, S E, Farah, K N, Farias, R P, Fernandes, A P, Fernandes, G W, Ferrante, M, Finn, A, Florjancic, G A, Forister, M L, Fox, Q N, Frago, E, França, F M, Getman-Pickering, A S, Getman-Pickering, Z, Gianoli, E, Gooden, B, Gossner, M M, Greig, K A, Gripenberg, S, Groenteman, R, Grof-Tisza, P, Haack, N, Hahn, L, Haq, S M, Helms, A M, Hennecke, J, Hermann, S L, Holeski, L M, Holm, S, Hutchinson, M C, Jackson, E E, Kagiya, S, Kalske, A, Kalwajtys, M, Karban, R, Kariyat, R, Keasar, T, Kersch-Becker, M F, Kharouba, H M, Kim, T N, Kimuyu, D M, Kluse, J, Koerner, S E, Komatsu, K J, Krishnan, S, Laihonen, M, Lamelas-López, L, LaScaleia, M C, Lecomte, N, Lehn, C R, and Li, X
Abstract: Interactions between plants and herbivores are central in most ecosystems, but their strength is highly variable. The amount of variability within a system is thought to influence most aspects of plant-herbivore biology, from ecological stability to plant defense evolution. Our understanding of what influences variability, however, is limited by sparse data. We collected standardized surveys of herbivory for 503 plant species at 790 sites across 116° of latitude. With these data, we show that within-population variability in herbivory increases with latitude, decreases with plant size, and is phylogenetically structured. Differences in the magnitude of variability are thus central to how plant-herbivore biology varies across macroscale gradients. We argue that increased focus on interaction variability will advance understanding of patterns of life on Earth.
Published: 2023

15. Data-driven Modeling of a Coronal Magnetic Flux Rope: from Birth to Death

Author: Guo, J. H., Ni, Y. W., Guo, Y., Xia, C., Schmieder, B., Poedts, S., Zhong, Z., Zhou, Y. H., Yu, F., Chen, P. F., Guo, J. H., Ni, Y. W., Guo, Y., Xia, C., Schmieder, B., Poedts, S., Zhong, Z., Zhou, Y. H., Yu, F., and Chen, P. F.
Abstract: Magnetic flux ropes are a bundle of twisted magnetic field lines produced by internal electric currents, which are responsible for solar eruptions and are the major drivers of geomagnetic storms. As such, it is crucial to develop a numerical model that can capture the entire evolution of a flux rope, from its birth to death, in order to predict whether adverse space weather events might occur or not. In this paper, we develop a data-driven modeling that combines a time-dependent magneto-frictional approach with a thermodynamic magnetohydrodynamic model. Our numerical modeling successfully reproduces the formation and confined eruption of an observed flux rope, and unveils the physical details behind the observations. Regarding the long-term evolution of the active region, our simulation results indicate that the flux cancellation due to collisional shearing plays a critical role in the formation of the flux rope, corresponding to a substantial increase in magnetic free energy and helicity. Regarding the eruption stage, the deformation of the flux rope during its eruption can cause an increase in the downward tension force, which suppresses it from further rising. This finding may shed light on why some torus-unstable flux ropes lead to failed eruptions after large-angle rotations. Moreover, we find that twisted fluxes can accumulate during the confined eruptions, which would breed the subsequent eruptive flares., Comment: 30 pages, 10 figures, Accepted for ApJ
Published: 2023

16. Non-Standard Errors

Author: Menkveld, A.J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, G.U., Abad, D., Abudy, M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., Bach, A., Baidoo, E., Bakalli, G., Barbon, A., Bashchenko, O., Bindra, P.C., Bjonnes, G.H., Black, J., Black, B.S., Bohorquez, S., Bondarenko, O., Bos, C.S., Bosch-Rosa, C., Bouri, E., Brownlees, C.T., Calamia, A., Cao, V.N., Capelle-Blancard, G., Capera, L., Caporin, M., Carrion, A., Caskurlu, T., Chakrabarty, B., Chernov, M., Cheung, W.M., Chincarini, L.B., Chordia, T., Chow, S.C., Clapham, B., Colliard, J.-E., Comerton-Forde, C., Curran, E., Dao, T., Dare, W., Davies, R.J., Blasis, R. De, Nard, G. De, DeClerck, F., Deev, O., Degryse, H., Deku, S., Desagre, C., Dijk, M.A van, Dim, C., Dimpfl, T., Dong, Y., Drummond, P., Dudda, T., Dumitrescu, A., Dyakov, T., Dyhrberg, A.H., Dzieliński, M., Eksi, A., Kalak, I. El, Ellen, S. ter, Eugster, N., Evans, M.D.D., Farrell, M., Félez-Viñas, E., Ferrara, G., Ferrouhi, E.M., Flori, A., Fluharty-Jaidee, J., Foley, S., Fong, K.Y.L., Foucault, T., Franus, T., Franzoni, F.A., Frijns, B., Frömmel, M., Fu, S., Füllbrunn, S.C., Gan, B., Gehrig, T., Gerritsen, D., Gil-Bazo, J., Glosten, L.R., Gomez, T., Gorbenko, A., Güçbilmez, U., Grammig, J., Gregoire, V., Hagströmer, B., Hambuckers, J., Hapnes, E., Harris, J.H., Harris, L., Hartmann, S., Hasse, J.-B., Hautsch, N., He, X., Heath, D., Hediger, S., Hendershott, T., Hibbert, A.M., Hjalmarsson, E., Hoelscher, S.A., Hoffmann, P., Holden, C.W., Horenstein, A.R., Huang, W., Huang, D., Hurlin, C., Ivashchenko, A., Iyer, S.R., Jahanshahloo, H., Jalkh, N., Jones, C.M., Jurkatis, S., Jylha, P., Kaeck, A., Kaiser, G., Karam, A., Karmaziene, E., Kassner, B., Kaustia, M., Kazak, E., Kearney, F., Kervel, V. van, Khan, S., Khomyn, M., Klein, T., Klein, O., Klos, A., Koetter, M., Krahnen, J.P., Kolokolov, A., Korajczyk, R.A., Kozhan, R., Kwan, A., Lajaunie, Q., Lam, F.E.C., Lambert, M., Langlois, H., Lausen, J., Lauter, T., Leippold, M., Levin, V., Li, Y., Li, H., Liew, C.Y., Lindner, T., Linton, O.B., Liu, J., Liu, A., Llorente, G., Lof, M., Lohr, A., Longstaff, F.A., Lopez-Lira, A., Mankad, S., Mano, N., Marchal, A., Martineau, C., Mazzola, F., Meloso, D., Mihet, R., Mohan, V., Moinas, S., Moore, D., Mu, L., Muravyev, D., Murphy, D., Neszveda, G., Neumeier, C., Nielsson, U., Nimalendran, M., Nolte, S., Norden, L.L., O'Neill, P., Obaid, K., Ødegaard, B.A., Östberg, P., Painter, M., Palan, S., Palit, I., Park, A., Pascual, R., Pasquariello, P., Pastor, L., Patel, V., Patton, A.J., Pearson, N.D., Pelizzon, L., Pelster, M., Pérignon, C., Pfiffer, C., Philip, R., Plíhal, T., Prakash, P., Press, O.-A., Prodromou, T., Putniņš, T.J., Raizada, G., Rakowski, D.A., Ranaldo, A., Regis, L., Reitz, S., Renault, T., Renjie, R.W., Renò, R., Riddiough, S., Rinne, K., Rintamäki, P., Riordan, R., Rittmannsberger, T., Rodríguez-Longarela, I., Rösch, D., Rognone, L., Roseman, B., Rosu, I., Roy, S., Rudolf, N., Rush, S., Rzayev, K., Rzeźnik, A., Sanford, A., Sankaran, H., Sarkar, A., Sarno, L., Scaillet, O., Scharnowski, S., Schenk-Hoppé, K.R., Schertler, A., Schneider, M., Schroeder, F., Schürhoff, N., Schuster, P., Schwarz, M.A., Seasholes, M.S., Seeger, N., Shachar, O., Shkilko, A., Shui, J., Sikic, M., Simion, G., Smales, L.A., Söderlind, P., Sojli, E., Sokolov, K., Spokeviciute, L., Stefanova, D., Subrahmanyam, M.G., Neusüss, S., Szaszi, B., Talavera, O., Tang, Y., Taylor, N., Tham, W.W., Theissen, E., Thimme, J., Tonks, I., Tran, H., Trapin, L., Trolle, A.B., Valente, G., Ness, R.A. Van, Vasquez, A., Verousis, T., Verwijmeren, P., Vilhelmsson, A., Vilkov, G., Vladimirov, V., Vogel, S., Voigt, S., Wagner, W., Walther, T., Weiss, P., Wel, M. van der, Werner, I.M., Westerholm, P.J., Westheide, C., Wipplinger, E., Wolf, M., Wolff, C.C.P., Wolk, L., Wong, W.-K., Wrampelmeyer, J., Xia, S., Xiu, D., Xu, K., Xu, C., Yadav, P.K., Yagüe, J., Yan, C., Yang, A., Yoo, W., Yu, W., Yu, S., Yueshen, B.Z., Yuferova, D., Zamojski, M., Zareei, A., Zeisberger, S.M., Zhang, S.S., Zhang, X., Zhong, Z., Zhou, Z.I., Zhou, C., Zhu, X.S., Zoican, M., Zwinkels, R.C.J., Chen, J., Duevski, T., Gao, G., Gemayel, R., Gilder, D. de, Kuhle, P., Pagnotta, E., Pelli, M., Sönksen, J., Zhang, L., Ilczuk, K., Bogoev, D., Qian, Y., Wika, H.C., Yu, Y., Zhao, L., Mi, M., Bao, L., Vaduva, A., Prokopczuk, P., Avetikian, A., Wu, Z.-X., Menkveld, A.J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, G.U., Abad, D., Abudy, M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., Bach, A., Baidoo, E., Bakalli, G., Barbon, A., Bashchenko, O., Bindra, P.C., Bjonnes, G.H., Black, J., Black, B.S., Bohorquez, S., Bondarenko, O., Bos, C.S., Bosch-Rosa, C., Bouri, E., Brownlees, C.T., Calamia, A., Cao, V.N., Capelle-Blancard, G., Capera, L., Caporin, M., Carrion, A., Caskurlu, T., Chakrabarty, B., Chernov, M., Cheung, W.M., Chincarini, L.B., Chordia, T., Chow, S.C., Clapham, B., Colliard, J.-E., Comerton-Forde, C., Curran, E., Dao, T., Dare, W., Davies, R.J., Blasis, R. De, Nard, G. De, DeClerck, F., Deev, O., Degryse, H., Deku, S., Desagre, C., Dijk, M.A van, Dim, C., Dimpfl, T., Dong, Y., Drummond, P., Dudda, T., Dumitrescu, A., Dyakov, T., Dyhrberg, A.H., Dzieliński, M., Eksi, A., Kalak, I. El, Ellen, S. ter, Eugster, N., Evans, M.D.D., Farrell, M., Félez-Viñas, E., Ferrara, G., Ferrouhi, E.M., Flori, A., Fluharty-Jaidee, J., Foley, S., Fong, K.Y.L., Foucault, T., Franus, T., Franzoni, F.A., Frijns, B., Frömmel, M., Fu, S., Füllbrunn, S.C., Gan, B., Gehrig, T., Gerritsen, D., Gil-Bazo, J., Glosten, L.R., Gomez, T., Gorbenko, A., Güçbilmez, U., Grammig, J., Gregoire, V., Hagströmer, B., Hambuckers, J., Hapnes, E., Harris, J.H., Harris, L., Hartmann, S., Hasse, J.-B., Hautsch, N., He, X., Heath, D., Hediger, S., Hendershott, T., Hibbert, A.M., Hjalmarsson, E., Hoelscher, S.A., Hoffmann, P., Holden, C.W., Horenstein, A.R., Huang, W., Huang, D., Hurlin, C., Ivashchenko, A., Iyer, S.R., Jahanshahloo, H., Jalkh, N., Jones, C.M., Jurkatis, S., Jylha, P., Kaeck, A., Kaiser, G., Karam, A., Karmaziene, E., Kassner, B., Kaustia, M., Kazak, E., Kearney, F., Kervel, V. van, Khan, S., Khomyn, M., Klein, T., Klein, O., Klos, A., Koetter, M., Krahnen, J.P., Kolokolov, A., Korajczyk, R.A., Kozhan, R., Kwan, A., Lajaunie, Q., Lam, F.E.C., Lambert, M., Langlois, H., Lausen, J., Lauter, T., Leippold, M., Levin, V., Li, Y., Li, H., Liew, C.Y., Lindner, T., Linton, O.B., Liu, J., Liu, A., Llorente, G., Lof, M., Lohr, A., Longstaff, F.A., Lopez-Lira, A., Mankad, S., Mano, N., Marchal, A., Martineau, C., Mazzola, F., Meloso, D., Mihet, R., Mohan, V., Moinas, S., Moore, D., Mu, L., Muravyev, D., Murphy, D., Neszveda, G., Neumeier, C., Nielsson, U., Nimalendran, M., Nolte, S., Norden, L.L., O'Neill, P., Obaid, K., Ødegaard, B.A., Östberg, P., Painter, M., Palan, S., Palit, I., Park, A., Pascual, R., Pasquariello, P., Pastor, L., Patel, V., Patton, A.J., Pearson, N.D., Pelizzon, L., Pelster, M., Pérignon, C., Pfiffer, C., Philip, R., Plíhal, T., Prakash, P., Press, O.-A., Prodromou, T., Putniņš, T.J., Raizada, G., Rakowski, D.A., Ranaldo, A., Regis, L., Reitz, S., Renault, T., Renjie, R.W., Renò, R., Riddiough, S., Rinne, K., Rintamäki, P., Riordan, R., Rittmannsberger, T., Rodríguez-Longarela, I., Rösch, D., Rognone, L., Roseman, B., Rosu, I., Roy, S., Rudolf, N., Rush, S., Rzayev, K., Rzeźnik, A., Sanford, A., Sankaran, H., Sarkar, A., Sarno, L., Scaillet, O., Scharnowski, S., Schenk-Hoppé, K.R., Schertler, A., Schneider, M., Schroeder, F., Schürhoff, N., Schuster, P., Schwarz, M.A., Seasholes, M.S., Seeger, N., Shachar, O., Shkilko, A., Shui, J., Sikic, M., Simion, G., Smales, L.A., Söderlind, P., Sojli, E., Sokolov, K., Spokeviciute, L., Stefanova, D., Subrahmanyam, M.G., Neusüss, S., Szaszi, B., Talavera, O., Tang, Y., Taylor, N., Tham, W.W., Theissen, E., Thimme, J., Tonks, I., Tran, H., Trapin, L., Trolle, A.B., Valente, G., Ness, R.A. Van, Vasquez, A., Verousis, T., Verwijmeren, P., Vilhelmsson, A., Vilkov, G., Vladimirov, V., Vogel, S., Voigt, S., Wagner, W., Walther, T., Weiss, P., Wel, M. van der, Werner, I.M., Westerholm, P.J., Westheide, C., Wipplinger, E., Wolf, M., Wolff, C.C.P., Wolk, L., Wong, W.-K., Wrampelmeyer, J., Xia, S., Xiu, D., Xu, K., Xu, C., Yadav, P.K., Yagüe, J., Yan, C., Yang, A., Yoo, W., Yu, W., Yu, S., Yueshen, B.Z., Yuferova, D., Zamojski, M., Zareei, A., Zeisberger, S.M., Zhang, S.S., Zhang, X., Zhong, Z., Zhou, Z.I., Zhou, C., Zhu, X.S., Zoican, M., Zwinkels, R.C.J., Chen, J., Duevski, T., Gao, G., Gemayel, R., Gilder, D. de, Kuhle, P., Pagnotta, E., Pelli, M., Sönksen, J., Zhang, L., Ilczuk, K., Bogoev, D., Qian, Y., Wika, H.C., Yu, Y., Zhao, L., Mi, M., Bao, L., Vaduva, A., Prokopczuk, P., Avetikian, A., and Wu, Z.-X.
Abstract: Item does not contain fulltext, In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Published: 2022

17. Grow-up of a Filament Channel by Intermittent Small-scale Magnetic Reconnection

Author: Li, H. T., Cheng, X., Guo, J. H., Yan, X. L., Wang, L. F., Zhong, Z., Li, C., Ding, M. D., Li, H. T., Cheng, X., Guo, J. H., Yan, X. L., Wang, L. F., Zhong, Z., Li, C., and Ding, M. D.
Abstract: Filament channel (FC), a plasma volume where the magnetic field is primarily aligned with the polarity inversion line, is believed to be the pre-eruptive configuration of coronal mass ejections. Nevertheless, evidence for how the FC is formed is still elusive. In this paper, we present a detailed study on the build-up of a FC to understand its formation mechanism. The New Vacuum Solar Telescope of Yunnan Observatories and Optical and Near-Infrared Solar Eruption Tracer of Nanjing University, as well as the AIA and HMI on board Solar Dynamics Observatory are used to study the grow-up process of the FC. Furthermore, we reconstruct the non-linear force-free field (NLFFF) of the active region using the regularized Biot-Savart laws (RBSL) and magnetofrictional method to reveal three-dimension (3D) magnetic field properties of the FC. We find that partial filament materials are quickly transferred to longer magnetic field lines formed by small-scale magnetic reconnection, as evidenced by dot-like H{\alpha}/EUV brightenings and subsequent bidirectional outflow jets, as well as untwisting motions. The H{\alpha}/EUV bursts appear repeatedly at the same location and are closely associated with flux cancellation, which occurs between two small-scale opposite polarities and is driven by shearing and converging motions. The 3D NLFFF model reveals that the reconnection takes place in a hyperbolic flux tube that is located above the flux cancellation site and below the FC. The FC is gradually built up toward a twisted flux rope via series of small-scale reconnection events that occur intermittently prior to the eruption., Comment: 10 pages, 7 figures, 1 table. A&A accepted
Published: 2022

18. Evidence for Whistler Waves Propagating Into the Electron Diffusion Region of Collisionless Magnetic Reconnection

Author: Zhong, Z. H., Zhou, M., Graham, Daniel B., Khotyaintsev, Yuri V., Wu, Y. F., Le Contel, O., Li, H. M., Tao, X., Tang, R. X., Deng, X. H., Zhong, Z. H., Zhou, M., Graham, Daniel B., Khotyaintsev, Yuri V., Wu, Y. F., Le Contel, O., Li, H. M., Tao, X., Tang, R. X., and Deng, X. H.
Abstract: Despite a growing number of observations of whistler waves in/around the reconnection diffusion region, the origin of the whistler waves in the diffusion region and their role in reconnection remain elusive. This paper investigates the whistler-mode waves within an electron-scale reconnecting current sheet observed by the Magnetospheric Multiscale mission on 23 December 2016. These whistlers were observed in both the electron diffusion region (EDR) and the immediate inflow region of the electron-scale magnetic reconnection site. The dispersion relation of these whistlers is measured and compared to predictions from linear theory for the first time in these regions. The comparison shows that the field-aligned drifting electron component critically modifies the dispersion relation of whistlers in the EDR due to the Doppler-shift effects. We demonstrate that these whistlers propagated into the EDR from outside rather than locally excited, however, they did not provide sufficiently large anomalous dissipation in this EDR.
Published: 2022
Full Text: View/download PDF

19. Stacked Electron Diffusion Regions and Electron Kelvin-Helmholtz Vortices within the Ion Diffusion Region of Collisionless Magnetic Reconnection

Author: Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., Khotyaintsev, Yu, V, Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., and Khotyaintsev, Yu, V
Abstract: The structure of the electron diffusion region (EDR) is essential for determining how fast the magnetic energy converts to plasma energy during magnetic reconnection. Conventional knowledge of the diffusion region assumes that the EDR is a single layer embedded within the ion diffusion region (IDR). This paper reports the first observation of two EDRs that stack in parallel within an IDR by the Magnetospheric Multiscale mission. The oblique tearing modes can result in these stacked EDRs. Intense electron flow shear in the vicinity of two EDRs induced electron Kelvin-Helmholtz vortices, which subsequently generated kinetic-scale magnetic peak and holes, which may effectively trap electrons. Our analyses show that both the oblique tearing instability and electron Kelvin-Helmholtz instability are important in three-dimensional reconnection since they can control the electron dynamics and structure of the diffusion region through cross-scale coupling.
Published: 2022
Full Text: View/download PDF

20. Stacked Electron Diffusion Regions and Electron Kelvin-Helmholtz Vortices within the Ion Diffusion Region of Collisionless Magnetic Reconnection

Author: Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., Khotyaintsev, Yu, V, Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., and Khotyaintsev, Yu, V
Abstract: The structure of the electron diffusion region (EDR) is essential for determining how fast the magnetic energy converts to plasma energy during magnetic reconnection. Conventional knowledge of the diffusion region assumes that the EDR is a single layer embedded within the ion diffusion region (IDR). This paper reports the first observation of two EDRs that stack in parallel within an IDR by the Magnetospheric Multiscale mission. The oblique tearing modes can result in these stacked EDRs. Intense electron flow shear in the vicinity of two EDRs induced electron Kelvin-Helmholtz vortices, which subsequently generated kinetic-scale magnetic peak and holes, which may effectively trap electrons. Our analyses show that both the oblique tearing instability and electron Kelvin-Helmholtz instability are important in three-dimensional reconnection since they can control the electron dynamics and structure of the diffusion region through cross-scale coupling.
Published: 2022
Full Text: View/download PDF

21. Stacked Electron Diffusion Regions and Electron Kelvin-Helmholtz Vortices within the Ion Diffusion Region of Collisionless Magnetic Reconnection

Author: Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., Khotyaintsev, Yu, V, Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., and Khotyaintsev, Yu, V
Abstract: The structure of the electron diffusion region (EDR) is essential for determining how fast the magnetic energy converts to plasma energy during magnetic reconnection. Conventional knowledge of the diffusion region assumes that the EDR is a single layer embedded within the ion diffusion region (IDR). This paper reports the first observation of two EDRs that stack in parallel within an IDR by the Magnetospheric Multiscale mission. The oblique tearing modes can result in these stacked EDRs. Intense electron flow shear in the vicinity of two EDRs induced electron Kelvin-Helmholtz vortices, which subsequently generated kinetic-scale magnetic peak and holes, which may effectively trap electrons. Our analyses show that both the oblique tearing instability and electron Kelvin-Helmholtz instability are important in three-dimensional reconnection since they can control the electron dynamics and structure of the diffusion region through cross-scale coupling.
Published: 2022
Full Text: View/download PDF

22. Non-Standard Errors

Author: Menkveld, A.J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, G.U., Abad, D., Abudy, M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., Bach, A., Baidoo, E., Bakalli, G., Barbon, A., Bashchenko, O., Bindra, P.C., Bjonnes, G.H., Black, J., Black, B.S., Bohorquez, S., Bondarenko, O., Bos, C.S., Bosch-Rosa, C., Bouri, E., Brownlees, C.T., Calamia, A., Cao, V.N., Capelle-Blancard, G., Capera, L., Caporin, M., Carrion, A., Caskurlu, T., Chakrabarty, B., Chernov, M., Cheung, W.M., Chincarini, L.B., Chordia, T., Chow, S.C., Clapham, B., Colliard, J.-E., Comerton-Forde, C., Curran, E., Dao, T., Dare, W., Davies, R.J., Blasis, R. De, Nard, G. De, DeClerck, F., Deev, O., Degryse, H., Deku, S., Desagre, C., Dijk, M.A van, Dim, C., Dimpfl, T., Dong, Y., Drummond, P., Dudda, T., Dumitrescu, A., Dyakov, T., Dyhrberg, A.H., Dzieliński, M., Eksi, A., Kalak, I. El, Ellen, S. ter, Eugster, N., Evans, M.D.D., Farrell, M., Félez-Viñas, E., Ferrara, G., Ferrouhi, E.M., Flori, A., Fluharty-Jaidee, J., Foley, S., Fong, K.Y.L., Foucault, T., Franus, T., Franzoni, F.A., Frijns, B., Frömmel, M., Fu, S., Füllbrunn, S.C., Gan, B., Gehrig, T., Gerritsen, D., Gil-Bazo, J., Glosten, L.R., Gomez, T., Gorbenko, A., Güçbilmez, U., Grammig, J., Gregoire, V., Hagströmer, B., Hambuckers, J., Hapnes, E., Harris, J.H., Harris, L., Hartmann, S., Hasse, J.-B., Hautsch, N., He, X., Heath, D., Hediger, S., Hendershott, T., Hibbert, A.M., Hjalmarsson, E., Hoelscher, S.A., Hoffmann, P., Holden, C.W., Horenstein, A.R., Huang, W., Huang, D., Hurlin, C., Ivashchenko, A., Iyer, S.R., Jahanshahloo, H., Jalkh, N., Jones, C.M., Jurkatis, S., Jylha, P., Kaeck, A., Kaiser, G., Karam, A., Karmaziene, E., Kassner, B., Kaustia, M., Kazak, E., Kearney, F., Kervel, V. van, Khan, S., Khomyn, M., Klein, T., Klein, O., Klos, A., Koetter, M., Krahnen, J.P., Kolokolov, A., Korajczyk, R.A., Kozhan, R., Kwan, A., Lajaunie, Q., Lam, F.E.C., Lambert, M., Langlois, H., Lausen, J., Lauter, T., Leippold, M., Levin, V., Li, Y., Li, H., Liew, C.Y., Lindner, T., Linton, O.B., Liu, J., Liu, A., Llorente, G., Lof, M., Lohr, A., Longstaff, F.A., Lopez-Lira, A., Mankad, S., Mano, N., Marchal, A., Martineau, C., Mazzola, F., Meloso, D., Mihet, R., Mohan, V., Moinas, S., Moore, D., Mu, L., Muravyev, D., Murphy, D., Neszveda, G., Neumeier, C., Nielsson, U., Nimalendran, M., Nolte, S., Norden, L.L., O'Neill, P., Obaid, K., Ødegaard, B.A., Östberg, P., Painter, M., Palan, S., Palit, I., Park, A., Pascual, R., Pasquariello, P., Pastor, L., Patel, V., Patton, A.J., Pearson, N.D., Pelizzon, L., Pelster, M., Pérignon, C., Pfiffer, C., Philip, R., Plíhal, T., Prakash, P., Press, O.-A., Prodromou, T., Putniņš, T.J., Raizada, G., Rakowski, D.A., Ranaldo, A., Regis, L., Reitz, S., Renault, T., Renjie, R.W., Renò, R., Riddiough, S., Rinne, K., Rintamäki, P., Riordan, R., Rittmannsberger, T., Rodríguez-Longarela, I., Rösch, D., Rognone, L., Roseman, B., Rosu, I., Roy, S., Rudolf, N., Rush, S., Rzayev, K., Rzeźnik, A., Sanford, A., Sankaran, H., Sarkar, A., Sarno, L., Scaillet, O., Scharnowski, S., Schenk-Hoppé, K.R., Schertler, A., Schneider, M., Schroeder, F., Schürhoff, N., Schuster, P., Schwarz, M.A., Seasholes, M.S., Seeger, N., Shachar, O., Shkilko, A., Shui, J., Sikic, M., Simion, G., Smales, L.A., Söderlind, P., Sojli, E., Sokolov, K., Spokeviciute, L., Stefanova, D., Subrahmanyam, M.G., Neusüss, S., Szaszi, B., Talavera, O., Tang, Y., Taylor, N., Tham, W.W., Theissen, E., Thimme, J., Tonks, I., Tran, H., Trapin, L., Trolle, A.B., Valente, G., Ness, R.A. Van, Vasquez, A., Verousis, T., Verwijmeren, P., Vilhelmsson, A., Vilkov, G., Vladimirov, V., Vogel, S., Voigt, S., Wagner, W., Walther, T., Weiss, P., Wel, M. van der, Werner, I.M., Westerholm, P.J., Westheide, C., Wipplinger, E., Wolf, M., Wolff, C.C.P., Wolk, L., Wong, W.-K., Wrampelmeyer, J., Xia, S., Xiu, D., Xu, K., Xu, C., Yadav, P.K., Yagüe, J., Yan, C., Yang, A., Yoo, W., Yu, W., Yu, S., Yueshen, B.Z., Yuferova, D., Zamojski, M., Zareei, A., Zeisberger, S.M., Zhang, S.S., Zhang, X., Zhong, Z., Zhou, Z.I., Zhou, C., Zhu, X.S., Zoican, M., Zwinkels, R.C.J., Chen, J., Duevski, T., Gao, G., Gemayel, R., Gilder, D. de, Kuhle, P., Pagnotta, E., Pelli, M., Sönksen, J., Zhang, L., Ilczuk, K., Bogoev, D., Qian, Y., Wika, H.C., Yu, Y., Zhao, L., Mi, M., Bao, L., Vaduva, A., Prokopczuk, P., Avetikian, A., Wu, Z.-X., Menkveld, A.J., Dreber, A., Holzmeister, F., Huber, J., Johannesson, M., Kirchler, M., Razen, M., Weitzel, G.U., Abad, D., Abudy, M., Adrian, T., Ait-Sahalia, Y., Akmansoy, O., Alcock, J., Alexeev, V., Aloosh, A., Amato, L., Amaya, D., Angel, J., Bach, A., Baidoo, E., Bakalli, G., Barbon, A., Bashchenko, O., Bindra, P.C., Bjonnes, G.H., Black, J., Black, B.S., Bohorquez, S., Bondarenko, O., Bos, C.S., Bosch-Rosa, C., Bouri, E., Brownlees, C.T., Calamia, A., Cao, V.N., Capelle-Blancard, G., Capera, L., Caporin, M., Carrion, A., Caskurlu, T., Chakrabarty, B., Chernov, M., Cheung, W.M., Chincarini, L.B., Chordia, T., Chow, S.C., Clapham, B., Colliard, J.-E., Comerton-Forde, C., Curran, E., Dao, T., Dare, W., Davies, R.J., Blasis, R. De, Nard, G. De, DeClerck, F., Deev, O., Degryse, H., Deku, S., Desagre, C., Dijk, M.A van, Dim, C., Dimpfl, T., Dong, Y., Drummond, P., Dudda, T., Dumitrescu, A., Dyakov, T., Dyhrberg, A.H., Dzieliński, M., Eksi, A., Kalak, I. El, Ellen, S. ter, Eugster, N., Evans, M.D.D., Farrell, M., Félez-Viñas, E., Ferrara, G., Ferrouhi, E.M., Flori, A., Fluharty-Jaidee, J., Foley, S., Fong, K.Y.L., Foucault, T., Franus, T., Franzoni, F.A., Frijns, B., Frömmel, M., Fu, S., Füllbrunn, S.C., Gan, B., Gehrig, T., Gerritsen, D., Gil-Bazo, J., Glosten, L.R., Gomez, T., Gorbenko, A., Güçbilmez, U., Grammig, J., Gregoire, V., Hagströmer, B., Hambuckers, J., Hapnes, E., Harris, J.H., Harris, L., Hartmann, S., Hasse, J.-B., Hautsch, N., He, X., Heath, D., Hediger, S., Hendershott, T., Hibbert, A.M., Hjalmarsson, E., Hoelscher, S.A., Hoffmann, P., Holden, C.W., Horenstein, A.R., Huang, W., Huang, D., Hurlin, C., Ivashchenko, A., Iyer, S.R., Jahanshahloo, H., Jalkh, N., Jones, C.M., Jurkatis, S., Jylha, P., Kaeck, A., Kaiser, G., Karam, A., Karmaziene, E., Kassner, B., Kaustia, M., Kazak, E., Kearney, F., Kervel, V. van, Khan, S., Khomyn, M., Klein, T., Klein, O., Klos, A., Koetter, M., Krahnen, J.P., Kolokolov, A., Korajczyk, R.A., Kozhan, R., Kwan, A., Lajaunie, Q., Lam, F.E.C., Lambert, M., Langlois, H., Lausen, J., Lauter, T., Leippold, M., Levin, V., Li, Y., Li, H., Liew, C.Y., Lindner, T., Linton, O.B., Liu, J., Liu, A., Llorente, G., Lof, M., Lohr, A., Longstaff, F.A., Lopez-Lira, A., Mankad, S., Mano, N., Marchal, A., Martineau, C., Mazzola, F., Meloso, D., Mihet, R., Mohan, V., Moinas, S., Moore, D., Mu, L., Muravyev, D., Murphy, D., Neszveda, G., Neumeier, C., Nielsson, U., Nimalendran, M., Nolte, S., Norden, L.L., O'Neill, P., Obaid, K., Ødegaard, B.A., Östberg, P., Painter, M., Palan, S., Palit, I., Park, A., Pascual, R., Pasquariello, P., Pastor, L., Patel, V., Patton, A.J., Pearson, N.D., Pelizzon, L., Pelster, M., Pérignon, C., Pfiffer, C., Philip, R., Plíhal, T., Prakash, P., Press, O.-A., Prodromou, T., Putniņš, T.J., Raizada, G., Rakowski, D.A., Ranaldo, A., Regis, L., Reitz, S., Renault, T., Renjie, R.W., Renò, R., Riddiough, S., Rinne, K., Rintamäki, P., Riordan, R., Rittmannsberger, T., Rodríguez-Longarela, I., Rösch, D., Rognone, L., Roseman, B., Rosu, I., Roy, S., Rudolf, N., Rush, S., Rzayev, K., Rzeźnik, A., Sanford, A., Sankaran, H., Sarkar, A., Sarno, L., Scaillet, O., Scharnowski, S., Schenk-Hoppé, K.R., Schertler, A., Schneider, M., Schroeder, F., Schürhoff, N., Schuster, P., Schwarz, M.A., Seasholes, M.S., Seeger, N., Shachar, O., Shkilko, A., Shui, J., Sikic, M., Simion, G., Smales, L.A., Söderlind, P., Sojli, E., Sokolov, K., Spokeviciute, L., Stefanova, D., Subrahmanyam, M.G., Neusüss, S., Szaszi, B., Talavera, O., Tang, Y., Taylor, N., Tham, W.W., Theissen, E., Thimme, J., Tonks, I., Tran, H., Trapin, L., Trolle, A.B., Valente, G., Ness, R.A. Van, Vasquez, A., Verousis, T., Verwijmeren, P., Vilhelmsson, A., Vilkov, G., Vladimirov, V., Vogel, S., Voigt, S., Wagner, W., Walther, T., Weiss, P., Wel, M. van der, Werner, I.M., Westerholm, P.J., Westheide, C., Wipplinger, E., Wolf, M., Wolff, C.C.P., Wolk, L., Wong, W.-K., Wrampelmeyer, J., Xia, S., Xiu, D., Xu, K., Xu, C., Yadav, P.K., Yagüe, J., Yan, C., Yang, A., Yoo, W., Yu, W., Yu, S., Yueshen, B.Z., Yuferova, D., Zamojski, M., Zareei, A., Zeisberger, S.M., Zhang, S.S., Zhang, X., Zhong, Z., Zhou, Z.I., Zhou, C., Zhu, X.S., Zoican, M., Zwinkels, R.C.J., Chen, J., Duevski, T., Gao, G., Gemayel, R., Gilder, D. de, Kuhle, P., Pagnotta, E., Pelli, M., Sönksen, J., Zhang, L., Ilczuk, K., Bogoev, D., Qian, Y., Wika, H.C., Yu, Y., Zhao, L., Mi, M., Bao, L., Vaduva, A., Prokopczuk, P., Avetikian, A., and Wu, Z.-X.
Abstract: Item does not contain fulltext, In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
Published: 2022

23. Joint design of phase shift and transceiver beamforming for intelligent reflecting surface assisted millimeter-wave high-speed railway communications

Author: Chen, C. (Chen), Niu, Y. (Yong), Ai, B. (Bo), He, R. (Ruisi), Han, Z. (Zhu), Zhong, Z. (Zhangdui), Wang, N. (Ning), Su, X. (Xiang), Chen, C. (Chen), Niu, Y. (Yong), Ai, B. (Bo), He, R. (Ruisi), Han, Z. (Zhu), Zhong, Z. (Zhangdui), Wang, N. (Ning), and Su, X. (Xiang)
Abstract: With the emerging demands of new communication services, the contradiction between capacity demand and spectrum shortage of railway communication systems becomes more severe. How to provide broadband communication services has become the key goal of future smart high-speed railway (HSR) systems. Millimeter wave (mm-wave) frequency band has abundant spectrum resources and can provide communication services with large bandwidth. However, due to the high-speed of the train as well as the complexity and dynamics of environments, the communication link may be blocked randomly for a short time and will also lead to frequent handovers. In this paper, we adopt the promising intelligent reflecting surface (IRS) technology for a mm-wave HSR communication system. In order to improve system capacity, IRS is deployed to improve reflection transmission links, and optimization algorithms are designed for transceiver beamforming and IRS phase shift. In addition, given the specificity of the HSR scenario, we also formulate the average system ergodic capacity maximization problem and obtain upper bound on the average system ergodic capacity with statistical channel state information (CSI). Through extensive simulations, we verify that the proposed scheme performs significantly better than the other two baseline schemes in terms of average system throughput and average system ergodic capacity.
Published: 2022

24. Joint Representation Learning and Keypoint Detection for Cross-View Geo-Localization.

Author: Lin, J, Zheng, Z, Zhong, Z, Luo, Z, Li, S, Yang, Y, Sebe, N, Lin, J, Zheng, Z, Zhong, Z, Luo, Z, Li, S, Yang, Y, and Sebe, N
Abstract: In this paper, we study the cross-view geo-localization problem to match images from different viewpoints. The key motivation underpinning this task is to learn a discriminative viewpoint-invariant visual representation. Inspired by the human visual system for mining local patterns, we propose a new framework called RK-Net to jointly learn the discriminative Representation and detect salient Keypoints with a single Network. Specifically, we introduce a Unit Subtraction Attention Module (USAM) that can automatically discover representative keypoints from feature maps and draw attention to the salient regions. USAM contains very few learning parameters but yields significant performance improvement and can be easily plugged into different networks. We demonstrate through extensive experiments that (1) by incorporating USAM, RK-Net facilitates end-to-end joint learning without the prerequisite of extra annotations. Representation learning and keypoint detection are two highly-related tasks. Representation learning aids keypoint detection. Keypoint detection, in turn, enriches the model capability against large appearance changes caused by viewpoint variants. (2) USAM is easy to implement and can be integrated with existing methods, further improving the state-of-the-art performance. We achieve competitive geo-localization accuracy on three challenging datasets, i. e., University-1652, CVUSA and CVACT. Our code is available at https://github.com/AggMan96/RK-Net.
Published: 2022

25. Deep transfer learning enables lesion tracing of circulating tumor cells

Author: Guo, X, Lin, F, Yi, C, Song, J, Sun, D, Lin, L, Zhong, Z, Wu, Z, Wang, X, Zhang, Y, Li, J, Zhang, H, Liu, F, Yang, C, Guo, X, Lin, F, Yi, C, Song, J, Sun, D, Lin, L, Zhong, Z, Wu, Z, Wang, X, Zhang, Y, Li, J, Zhang, H, Liu, F, and Yang, C
Abstract: Liquid biopsy offers great promise for noninvasive cancer diagnostics, while the lack of adequate target characterization and analysis hinders its wide application. Single-cell RNA sequencing (scRNA-seq) is a powerful technology for cell characterization. Integrating scRNA-seq into a CTC-focused liquid biopsy study can perhaps classify CTCs by their original lesions. However, the lack of CTC scRNA-seq data accumulation and prior knowledge hinders further development. Therefore, we design CTC-Tracer, a transfer learning-based algorithm, to correct the distributional shift between primary cancer cells and CTCs to transfer lesion labels from the primary cancer cell atlas to CTCs. The robustness and accuracy of CTC-Tracer are validated by 8 individual standard datasets. We apply CTC-Tracer on a complex dataset consisting of RNA-seq profiles of single CTCs, CTC clusters from a BRCA patient, and two xenografts, and demonstrate that CTC-Tracer has potential in knowledge transfer between different types of RNA-seq data of lesions and CTCs.
Published: 2022

26. Stacked Electron Diffusion Regions and Electron Kelvin-Helmholtz Vortices within the Ion Diffusion Region of Collisionless Magnetic Reconnection

Author: Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., Khotyaintsev, Yu, V, Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., and Khotyaintsev, Yu, V
Abstract: The structure of the electron diffusion region (EDR) is essential for determining how fast the magnetic energy converts to plasma energy during magnetic reconnection. Conventional knowledge of the diffusion region assumes that the EDR is a single layer embedded within the ion diffusion region (IDR). This paper reports the first observation of two EDRs that stack in parallel within an IDR by the Magnetospheric Multiscale mission. The oblique tearing modes can result in these stacked EDRs. Intense electron flow shear in the vicinity of two EDRs induced electron Kelvin-Helmholtz vortices, which subsequently generated kinetic-scale magnetic peak and holes, which may effectively trap electrons. Our analyses show that both the oblique tearing instability and electron Kelvin-Helmholtz instability are important in three-dimensional reconnection since they can control the electron dynamics and structure of the diffusion region through cross-scale coupling.
Published: 2022
Full Text: View/download PDF

27. Joint Representation Learning and Keypoint Detection for Cross-View Geo-Localization.

Author: Lin, J, Zheng, Z, Zhong, Z, Luo, Z, Li, S, Yang, Y, Sebe, N, Lin, J, Zheng, Z, Zhong, Z, Luo, Z, Li, S, Yang, Y, and Sebe, N
Abstract: In this paper, we study the cross-view geo-localization problem to match images from different viewpoints. The key motivation underpinning this task is to learn a discriminative viewpoint-invariant visual representation. Inspired by the human visual system for mining local patterns, we propose a new framework called RK-Net to jointly learn the discriminative Representation and detect salient Keypoints with a single Network. Specifically, we introduce a Unit Subtraction Attention Module (USAM) that can automatically discover representative keypoints from feature maps and draw attention to the salient regions. USAM contains very few learning parameters but yields significant performance improvement and can be easily plugged into different networks. We demonstrate through extensive experiments that (1) by incorporating USAM, RK-Net facilitates end-to-end joint learning without the prerequisite of extra annotations. Representation learning and keypoint detection are two highly-related tasks. Representation learning aids keypoint detection. Keypoint detection, in turn, enriches the model capability against large appearance changes caused by viewpoint variants. (2) USAM is easy to implement and can be integrated with existing methods, further improving the state-of-the-art performance. We achieve competitive geo-localization accuracy on three challenging datasets, i. e., University-1652, CVUSA and CVACT. Our code is available at https://github.com/AggMan96/RK-Net.
Published: 2022

28. Subspace cross representation measure for robust face recognition with few samples

Author: Zhang, J, Qin, X, Xiao, Y, Fei, R, Zang, Q, Xu, S, Bo, L, Li, H, Zhang, H, Zhong, Z, Zhang, J, Qin, X, Xiao, Y, Fei, R, Zang, Q, Xu, S, Bo, L, Li, H, Zhang, H, and Zhong, Z
Abstract: Similarity measure generally exerts a crucial role in face recognition. Recently, regression analysis based similarity measure mechanism has demonstrated significant potential in robust face recognition. Nevertheless, most existing regression methods are far from perfect under few samples due to the poor performance of spanning the individual subspace. Previous works have been noticed that the singular value decomposition (SVD) of facial image can generate a set of complete base of individual subspace. Then we present a novel and efficient image similarity measure model named subspace cross representation (SCR) measure for face recognition with few samples. The power of our proposed SCR stems from the following facts. One is that the complete base can weaken the dependence of linear regression method on the number of labeled samples. The other is the cross linear representation can effectively use two-dimensional geometric features generated by SVD to distinguish facial images. The validity of SCR is tested by a large amount of experiments on AR, CUHK Sketch, Extended Yale B databases, etc. The experimental results demonstrate that SCR achieves satisfactory recognition accuracy compared with other methods, under few sample condition.
Published: 2022

29. Deep transfer learning enables lesion tracing of circulating tumor cells.

Author: Guo, X, Lin, F, Yi, C, Song, J, Sun, D, Lin, L, Zhong, Z, Wu, Z, Wang, X, Zhang, Y, Li, J, Zhang, H, Liu, F, Yang, C, Guo, X, Lin, F, Yi, C, Song, J, Sun, D, Lin, L, Zhong, Z, Wu, Z, Wang, X, Zhang, Y, Li, J, Zhang, H, Liu, F, and Yang, C
Abstract: Liquid biopsy offers great promise for noninvasive cancer diagnostics, while the lack of adequate target characterization and analysis hinders its wide application. Single-cell RNA sequencing (scRNA-seq) is a powerful technology for cell characterization. Integrating scRNA-seq into a CTC-focused liquid biopsy study can perhaps classify CTCs by their original lesions. However, the lack of CTC scRNA-seq data accumulation and prior knowledge hinders further development. Therefore, we design CTC-Tracer, a transfer learning-based algorithm, to correct the distributional shift between primary cancer cells and CTCs to transfer lesion labels from the primary cancer cell atlas to CTCs. The robustness and accuracy of CTC-Tracer are validated by 8 individual standard datasets. We apply CTC-Tracer on a complex dataset consisting of RNA-seq profiles of single CTCs, CTC clusters from a BRCA patient, and two xenografts, and demonstrate that CTC-Tracer has potential in knowledge transfer between different types of RNA-seq data of lesions and CTCs.
Published: 2022

30. Grow-up of a Filament Channel by Intermittent Small-scale Magnetic Reconnection

Author: Li, H. T., Cheng, X., Guo, J. H., Yan, X. L., Wang, L. F., Zhong, Z., Li, C., Ding, M. D., Li, H. T., Cheng, X., Guo, J. H., Yan, X. L., Wang, L. F., Zhong, Z., Li, C., and Ding, M. D.
Abstract: Filament channel (FC), a plasma volume where the magnetic field is primarily aligned with the polarity inversion line, is believed to be the pre-eruptive configuration of coronal mass ejections. Nevertheless, evidence for how the FC is formed is still elusive. In this paper, we present a detailed study on the build-up of a FC to understand its formation mechanism. The New Vacuum Solar Telescope of Yunnan Observatories and Optical and Near-Infrared Solar Eruption Tracer of Nanjing University, as well as the AIA and HMI on board Solar Dynamics Observatory are used to study the grow-up process of the FC. Furthermore, we reconstruct the non-linear force-free field (NLFFF) of the active region using the regularized Biot-Savart laws (RBSL) and magnetofrictional method to reveal three-dimension (3D) magnetic field properties of the FC. We find that partial filament materials are quickly transferred to longer magnetic field lines formed by small-scale magnetic reconnection, as evidenced by dot-like H{\alpha}/EUV brightenings and subsequent bidirectional outflow jets, as well as untwisting motions. The H{\alpha}/EUV bursts appear repeatedly at the same location and are closely associated with flux cancellation, which occurs between two small-scale opposite polarities and is driven by shearing and converging motions. The 3D NLFFF model reveals that the reconnection takes place in a hyperbolic flux tube that is located above the flux cancellation site and below the FC. The FC is gradually built up toward a twisted flux rope via series of small-scale reconnection events that occur intermittently prior to the eruption., Comment: 10 pages, 7 figures, 1 table. A&A accepted
Published: 2022
Full Text: View/download PDF

31. Stacked Electron Diffusion Regions and Electron Kelvin-Helmholtz Vortices within the Ion Diffusion Region of Collisionless Magnetic Reconnection

Author: Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., Khotyaintsev, Yu, V, Zhong, Z. H., Zhou, M., Liu, Yi-Hsin, Deng, X. H., Tang, R. X., Graham, Daniel B., Song, L. J., Man, H. Y., Pang, Y., and Khotyaintsev, Yu, V
Abstract: The structure of the electron diffusion region (EDR) is essential for determining how fast the magnetic energy converts to plasma energy during magnetic reconnection. Conventional knowledge of the diffusion region assumes that the EDR is a single layer embedded within the ion diffusion region (IDR). This paper reports the first observation of two EDRs that stack in parallel within an IDR by the Magnetospheric Multiscale mission. The oblique tearing modes can result in these stacked EDRs. Intense electron flow shear in the vicinity of two EDRs induced electron Kelvin-Helmholtz vortices, which subsequently generated kinetic-scale magnetic peak and holes, which may effectively trap electrons. Our analyses show that both the oblique tearing instability and electron Kelvin-Helmholtz instability are important in three-dimensional reconnection since they can control the electron dynamics and structure of the diffusion region through cross-scale coupling.
Published: 2022
Full Text: View/download PDF

32. NTIRE 2019 challenge on image enhancement: Methods and results

Author: Ignatov, A, Timofte, R, Qu, X, Zhou, X, Liu, T, Wan, P, Zamir, S, Arora, A, Khan, S, Khan, F, Shao, L, Park, D, Chun, S, Michelini, P, Liu, H, Zhu, D, Zhong, Z, Liu, X, Jiang, J, Zhao, D, Haris, M, Akita, K, Yoshida, T, Shakhnarovich, G, Ukita, N, Liu, J, Jung, C, Schettini, R, Bianco, S, Cusano, C, Piccoli, F, Liu, P, Zhang, K, Zhang, H, Zuo, W, Bow, N, Wong, L, See, J, Qin, J, Huang, L, Shi, Y, Wei, P, Wen, W, Lin, L, Hui, Z, Wang, X, Gao, X, Kumari, K, Anand, V, Khened, M, Krishnamurthi, G, Ignatov A., Timofte R., Qu X., Zhou X., Liu T., Wan P., Zamir S. W., Arora A., Khan S., Khan F. S., Shao L., Park D., Chun S. Y., Michelini P. N., Liu H., Zhu D., Zhong Z., Liu X., Jiang J., Zhao D., Haris M., Akita K., Yoshida T., Shakhnarovich G., Ukita N., Liu J., Jung C., Schettini R., Bianco S., Cusano C., Piccoli F., Liu P., Zhang K., Zhang H., Zuo W., Bow N. C. N., Wong L. -K., See J., Qin J., Huang L., Shi Y., Wei P., Wen W., Lin L., Hui Z., Wang X., Gao X., Kumari K., Anand V. K., Khened M., Krishnamurthi G., Ignatov, A, Timofte, R, Qu, X, Zhou, X, Liu, T, Wan, P, Zamir, S, Arora, A, Khan, S, Khan, F, Shao, L, Park, D, Chun, S, Michelini, P, Liu, H, Zhu, D, Zhong, Z, Liu, X, Jiang, J, Zhao, D, Haris, M, Akita, K, Yoshida, T, Shakhnarovich, G, Ukita, N, Liu, J, Jung, C, Schettini, R, Bianco, S, Cusano, C, Piccoli, F, Liu, P, Zhang, K, Zhang, H, Zuo, W, Bow, N, Wong, L, See, J, Qin, J, Huang, L, Shi, Y, Wei, P, Wen, W, Lin, L, Hui, Z, Wang, X, Gao, X, Kumari, K, Anand, V, Khened, M, Krishnamurthi, G, Ignatov A., Timofte R., Qu X., Zhou X., Liu T., Wan P., Zamir S. W., Arora A., Khan S., Khan F. S., Shao L., Park D., Chun S. Y., Michelini P. N., Liu H., Zhu D., Zhong Z., Liu X., Jiang J., Zhao D., Haris M., Akita K., Yoshida T., Shakhnarovich G., Ukita N., Liu J., Jung C., Schettini R., Bianco S., Cusano C., Piccoli F., Liu P., Zhang K., Zhang H., Zuo W., Bow N. C. N., Wong L. -K., See J., Qin J., Huang L., Shi Y., Wei P., Wen W., Lin L., Hui Z., Wang X., Gao X., Kumari K., Anand V. K., Khened M., and Krishnamurthi G.
Abstract: This paper reviews the first NTIRE challenge on perceptual image enhancement with the focus on proposed solutions and results. The participating teams were solving a real-world photo enhancement problem, where the goal was to map low-quality photos from the iPhone 3GS device to the same photos captured with Canon 70D DSLR camera. The considered problem embraced a number of computer vision subtasks, such as image denoising, image resolution and sharpness enhancement, image color/contrast/exposure adjustment, etc. The target metric used in this challenge combined PSNR and SSIM scores with solutions' perceptual results measured in the user study. The proposed solutions significantly improved baseline results, defining the state-of-the-art for practical image enhancement.
Published: 2019

33. Mixed probability models for aleatoric uncertainty estimation in the context of dense stereo matching

Author: Zhong, Z., Mehltretter, M., Zhong, Z., and Mehltretter, M.
Abstract: The ability to identify erroneous depth estimates is of fundamental interest. Information regarding the aleatoric uncertainty of depth estimates can be, for example, used to support the process of depth reconstruction itself. Consequently, various methods for the estimation of aleatoric uncertainty in the context of dense stereo matching have been presented in recent years, with deep learning-based approaches being particularly popular. Among these deep learning-based methods, probabilistic strategies are increasingly attracting interest, because the estimated uncertainty can be quantified in pixels or in metric units due to the consideration of real error distributions. However, existing probabilistic methods usually assume a unimodal distribution to describe the error distribution while simply neglecting cases in real-world scenarios that could violate this assumption. To overcome this limitation, we propose two novel mixed probability models consisting of Laplacian and Uniform distributions for the task of aleatoric uncertainty estimation. In this way, we explicitly address commonly challenging regions in the context of dense stereo matching and outlier measurements, respectively. To allow a fair comparison, we adapt a common neural network architecture to investigate the effects of the different uncertainty models. In an extensive evaluation using two datasets and two common dense stereo matching methods, the proposed methods demonstrate state-of-the-art accuracy.
Published: 2021

34. Observations of Secondary Magnetic Reconnection in the Turbulent Reconnection Outflow

Author: Zhou, M., Man, H. Y., Deng, X. H., Pang, Y., Khotyaintsev, Yuri V., Lapenta, G., Yi, Y. Y., Zhong, Z. H., Ma, W. Q., Zhou, M., Man, H. Y., Deng, X. H., Pang, Y., Khotyaintsev, Yuri V., Lapenta, G., Yi, Y. Y., Zhong, Z. H., and Ma, W. Q.
Abstract: Magnetic reconnection and turbulence are the two most important energy dissipation processes in plasma. These two processes intertwine with each other and play important roles in their respective dynamic evolution. Here, we present the first evidence that secondary reconnections occur in the turbulent outflow driven by a primary reconnection in the Earth's magnetotail. We have identified 14 secondary reconnections in a large number of current filaments in the turbulent outflow, which persisted for about one and half an hour. Most of these secondary reconnections were electron-only reconnection that has recently been discovered in the magnetosheath. These secondary reconnections entangled the magnetic field lines and dissipated the magnetic energy in the outflow region far away from the primary X line.
Published: 2021
Full Text: View/download PDF

35. Whistler and Broadband Electrostatic Waves in the Multiple X-Line Reconnection at the Magnetopause

Author: Zhong, Z. H., Graham, Daniel B., Khotyaintsev, Yuri V., Zhou, M., Le Contel, O., Tang, R. X., Deng, X. H., Zhong, Z. H., Graham, Daniel B., Khotyaintsev, Yuri V., Zhou, M., Le Contel, O., Tang, R. X., and Deng, X. H.
Abstract: We investigate whistler-mode waves and broadband electrostatic waves (EWs) within an ion diffusion region (IDR) at the magnetopause. The quasi-parallel whistlers are observed in the separatrix regions associated with the electron anisotropy or loss cone, while the oblique whistlers, the Buneman-type waves, and the oblique EWs are observed in the center of the current sheet associated with the accelerated electron or ion beams. The whistlers are linked with Buneman-type waves by the electron Pacman distribution rather than the wave-wave process. The accelerated cold electron beams excite the Buneman-type instabilities and make the anisotropy or loss cone of hot electrons less apparent, which led to the conversion of the whistlers from quasi-parallel to oblique. Additionally, the oblique EWs are associated with the ion beams produced by the multiple X-line reconnection. These results provide a further understanding of the relation between plasma waves and plasma kinetics in the IDR.
Published: 2021
Full Text: View/download PDF

36. Three-Dimensional Electron-Scale Magnetic Reconnection in Earth's Magnetosphere

Author: Zhong, Z. H., Zhou, M., Deng, X. H., Song, L. J., Graham, Daniel B., Tang, R. X., Man, H. Y., Pang, Y., Khotyaintsev, Yuri V., Giles, B. L., Zhong, Z. H., Zhou, M., Deng, X. H., Song, L. J., Graham, Daniel B., Tang, R. X., Man, H. Y., Pang, Y., Khotyaintsev, Yuri V., and Giles, B. L.
Abstract: Two-dimensional Hall reconnection model can explain the fast release of magnetic energy and most of its predictions have been demonstrated by in situ satellite observations. However, the three-dimensional effect to reconnection remains poorly known. Recent numerical simulations have shown that three-dimensional evolution is more complex than two-dimensional in that reconnection occurs in multiple sites that are not necessarily in the primary neutral current sheet. Here, we present the first observational evidence for localized secondary reconnection at the separatrix surface of a magnetic flux rope (MFR). This secondary reconnection occurs between the axial magnetic field of the MFR, which points out-of-plane of the Earth's magnetopause reconnection, and the magnetospheric field. This three-dimensional electron-scale reconnection in the exhaust facilitates the cross-scale energy conversion from the macro-scale down to electron-scale.
Published: 2021
Full Text: View/download PDF

37. Learning to Adapt Invariance in Memory for Person Re-identification.

Author: Zhong, Z, Zheng, L, Luo, Z, Li, S, Yang, Y, Zhong, Z, Zheng, L, Luo, Z, Li, S, and Yang, Y
Abstract: This work considers the problem of unsupervised domain adaptation in person re-identification (re-ID), which aims to transfer knowledge from the source domain to the target domain. Existing methods are primary to reduce the inter-domain shift between the domains, which however usually overlook the relations among target samples. This paper investigates into the intra-domain variations of the target domain and proposes a novel adaptation framework w.r.t three types of underlying invariance, i.e., Exemplar-Invariance, Camera-Invariance, and Neighborhood-Invariance. Specifically, an exemplar memory is introduced to store features of samples, which can effectively and efficiently enforce the invariance constraints over the global dataset. We further present the Graph-based Positive Prediction (GPP) method to explore reliable neighbors for the target domain, which is built upon the memory and is trained on the source samples. Experiments demonstrate that 1) the three invariance properties are complementary and indispensable for effective domain adaptation, 2) the memory plays a key role in implementing invariance learning and improves the performance with limited extra computation cost, 3) GPP can facilitate the invariance learning and thus significantly improves the results, and 4) our approach produces new state-of-the-art adaptation accuracy on three re-ID large-scale benchmarks.
Published: 2021

38. Learning to Adapt Invariance in Memory for Person Re-identification.

Author: Zhong, Z, Zheng, L, Luo, Z, Li, S, Yang, Y, Zhong, Z, Zheng, L, Luo, Z, Li, S, and Yang, Y
Abstract: This work considers the problem of unsupervised domain adaptation in person re-identification (re-ID), which aims to transfer knowledge from the source domain to the target domain. Existing methods are primary to reduce the inter-domain shift between the domains, which however usually overlook the relations among target samples. This paper investigates into the intra-domain variations of the target domain and proposes a novel adaptation framework w.r.t three types of underlying invariance, i.e., Exemplar-Invariance, Camera-Invariance, and Neighborhood-Invariance. Specifically, an exemplar memory is introduced to store features of samples, which can effectively and efficiently enforce the invariance constraints over the global dataset. We further present the Graph-based Positive Prediction (GPP) method to explore reliable neighbors for the target domain, which is built upon the memory and is trained on the source samples. Experiments demonstrate that 1) the three invariance properties are complementary and indispensable for effective domain adaptation, 2) the memory plays a key role in implementing invariance learning and improves the performance with limited extra computation cost, 3) GPP can facilitate the invariance learning and thus significantly improves the results, and 4) our approach produces new state-of-the-art adaptation accuracy on three re-ID large-scale benchmarks.
Published: 2021

39. OpenMix: Reviving Known Knowledge for Discovering Novel Visual Categories in an Open World

Author: Zhong, Z, Zhu, L, Luo, Z, Li, S, Yang, Y, Sebe, N, Zhong, Z, Zhu, L, Luo, Z, Li, S, Yang, Y, and Sebe, N
Abstract: In this paper, we tackle the problem of discovering new classes in unlabeled visual data given labeled data from disjoint classes. Existing methods typically first pre-train a model with labeled data, and then identify new classes in unlabeled data via unsupervised clustering. However, the labeled data that provide essential knowledge are often underexplored in the second step. The challenge is that the labeled and unlabeled examples are from non-overlapping classes, which makes it difficult to build a learning relationship between them. In this work, we introduce Open-Mix to mix the unlabeled examples from an open set and the labeled examples from known classes, where their non-overlapping labels and pseudo-labels are simultaneously mixed into a joint label distribution. OpenMix dynamically compounds examples in two ways. First, we produce mixed training images by incorporating labeled examples with unlabeled examples. With the benefit of unique prior knowledge in novel class discovery, the generated pseudo-labels will be more credible than the original unlabeled predictions. As a result, OpenMix helps preventing the model from overfitting on unlabeled samples that may be assigned with wrong pseudo-labels. Second, the first way encourages the unlabeled examples with high class-probabilities to have considerable accuracy. We introduce these examples as reliable anchors and further integrate them with un-labeled samples. This enables us to generate more combinations in unlabeled examples and exploit finer object relations among the new classes. Experiments on three classification datasets demonstrate the effectiveness of the proposed OpenMix, which is superior to state-of-the-art methods in novel class discovery.
Published: 2021

40. Observations of Electron-Only Magnetic Reconnection Associated With Macroscopic Magnetic Flux Ropes

Author: Man, H. Y., Zhou, M., Yi, Y. Y., Zhong, Z. H., Tian, A. M., Deng, X. H., Khotyaintsev, Yuri V., Russell, C. T., Giles, B. L., Man, H. Y., Zhou, M., Yi, Y. Y., Zhong, Z. H., Tian, A. M., Deng, X. H., Khotyaintsev, Yuri V., Russell, C. T., and Giles, B. L.
Abstract: We report a Magnetospheric Multiscale (MMS) mission observation of magnetic reconnection occurring at the edge of a large-scale magnetic flux rope (MFR), the cross-section of which was about 2 R-E. The MFR was observed at the duskside in the Earth's magnetotail and was highly oblique with its axis approximately along theX(GSM)direction. We find an electron-scale current sheet near the edge of this MFR. The Hall magnetic and electric field, super-Alfvenic electron outflow, parallel electric field, and positive energy dissipation were observed associated with the current sheet, which indicates that MMS detected a reconnecting current sheet with a large guide field. Interestingly, ions were not coupled in this reconnection, akin to the electron-only reconnection observed in the turbulent magnetosheath. We further find that the electron-only reconnection is commonly associated with a macroscopic MFR. This result will shed new light on understanding the multiscale coupling associated with an MFR in space plasmas.
Published: 2020
Full Text: View/download PDF

41. Extension of the Electron Diffusion Region in a Guide Field Magnetic Reconnection at Magnetopause

Author: Zhong, Z. H., Zhou, M., Tang, R. X., Deng, X. H., Khotyaintsev, Yuri V., Giles, B. L., Paterson, W. R., Pang, Y., Man, H. Y., Russell, C. T., Burch, J. L., Zhong, Z. H., Zhou, M., Tang, R. X., Deng, X. H., Khotyaintsev, Yuri V., Giles, B. L., Paterson, W. R., Pang, Y., Man, H. Y., Russell, C. T., and Burch, J. L.
Abstract: The structure of the electron diffusion region (EDR) in different plasma regimes is an outstanding question related to magnetic reconnection. Here we report a long EDR that extended at least 20 ion inertial lengths downstream of an X line at the Earth's magnetopause, which was observed by the Magnetospheric Multiscale mission. This EDR was detected in the exhaust of an asymmetric magnetic reconnection with a moderate guide field, the reconnection rate of which was similar to 0.1. It corresponds to strong positive energy dissipation (J . E' > 0) and enhancement of electron nongyrotropy. The energy dissipation was contributed by the electron jet and non-ideal electric field along the outflow direction, which suggests that the EDR probably plays more important roles in the energy conversion in magnetic reconnection than previously thought. Our result could be a significant step toward fully understanding the structure of the EDR.
Published: 2020
Full Text: View/download PDF

42. Direct Evidence for Electron Acceleration Within Ion-Scale Flux Rope

Author: Zhong, Z. H., Zhou, M., Tang, R. X., Deng, X. H., Turner, D. L., Cohen, I. J., Pang, Y., Man, H. Y., Russell, C. T., Giles, B., Paterson, W. R., Khotyaintsev, Yuri V., Burch, J. L., Zhong, Z. H., Zhou, M., Tang, R. X., Deng, X. H., Turner, D. L., Cohen, I. J., Pang, Y., Man, H. Y., Russell, C. T., Giles, B., Paterson, W. R., Khotyaintsev, Yuri V., and Burch, J. L.
Abstract: Energetic electrons have frequently been observed in small-scale flux ropes. However, whether these energetic electrons were energized directly within the flux rope or not is unknown. In this paper, we present concrete evidence provided by the Magnetospheric Multiscale mission that a secondary flux rope provided strong acceleration for electrons expelled by the reconnection X line. We find that the energetic electron fluxes inside the ion-scale flux rope were larger than those outside the flux rope. Electrons were adiabatically accelerated by betatron and Fermi mechanisms inside the flux rope. The highest energy electrons (>100 keV) were produced by betatron acceleration, whereas Fermi acceleration was unable to accelerate the electrons to high energy probably due to the finite distance of the acceleration region along the field-aligned direction. These results confirm the essential role of ion-scale flux ropes in producing energetic electrons.
Published: 2020
Full Text: View/download PDF

43. Multi-wavelength observations of the BL Lac object Fermi J1544-0649: one year after its awakening

Author: Tam, P. H. T., Pal, P. S., Cui, Y. D., Jiang, N., Sotnikova, Y., Yang, C. W., Wang, L. Z., Tang, B. T., Li, Y. B., Mao, J., Kong, A. K. H., Zhong, Z. H., Ding, J., Mufakharov, T., Fan, J. F., Dou, L. M., Shen, R. F., Ai, Y. L., Tam, P. H. T., Pal, P. S., Cui, Y. D., Jiang, N., Sotnikova, Y., Yang, C. W., Wang, L. Z., Tang, B. T., Li, Y. B., Mao, J., Kong, A. K. H., Zhong, Z. H., Ding, J., Mufakharov, T., Fan, J. F., Dou, L. M., Shen, R. F., and Ai, Y. L.
Abstract: We report observations of a transient source \fermi\ from radio to \grs. \fermi\ was discovered by the {\it Fermi-LAT} in May 2017. Follow-up {\it Swift-XRT} observations revealed three flaring episodes through March 2018, and the peak X-ray flux is about $10^3$ higher than the {\it ROSAT all-sky survey (RASS)} flux upper limit. Optical spectral measurements taken by the {\it Magellan 6.5-m telescope} and the {\it Lick-Shane telescope} both show a largely featureless spectrum, strengthening the BL Lac interpretation first proposed by \citet{Bruni18}. The optical and mid-infrared (MIR) emission goes to a higher state in 2018, when the flux in high energies goes down to a lower level. Our {\it RATAN-600m} measurements at 4.8~GHz and 8.2~GHz do not indicate any significant radio flux variation over the monitoring seasons in 2017 and 2018, nor deviate from the archival {\it NVSS} flux level. During GeV flaring times, the spectrum is very hard ($\Gamma_\gamma\sim$1.7) in the GeV band and at times also very hard (($\Gamma_{\rm X}\lesssim2$) in the X-rays, similar to a high-synchrotron-peak (or even an extreme) BL Lac object, making \fermi\ a good target for ground-based {\it Cherenkov telescopes}., Comment: Submitted in Journal of High Energy Astrophysics
Published: 2020
Full Text: View/download PDF

44. Random Erasing Data Augmentation

Author: Zhong, Z, Zheng, L, Kang, G, Li, S, Yang, Y, Zhong, Z, Zheng, L, Kang, G, Li, S, and Yang, Y
Published: 2020

45. Random Erasing Data Augmentation

Author: Zhong, Z, Zheng, L, Kang, G, Li, S, Yang, Y, Zhong, Z, Zheng, L, Kang, G, Li, S, and Yang, Y
Published: 2020

46. Multi-wavelength observations of the BL Lac object Fermi J1544-0649: one year after its awakening

Author: Tam, P. H. T., Pal, P. S., Cui, Y. D., Jiang, N., Sotnikova, Y., Yang, C. W., Wang, L. Z., Tang, B. T., Li, Y. B., Mao, J., Kong, A. K. H., Zhong, Z. H., Ding, J., Mufakharov, T., Fan, J. F., Dou, L. M., Shen, R. F., Ai, Y. L., Tam, P. H. T., Pal, P. S., Cui, Y. D., Jiang, N., Sotnikova, Y., Yang, C. W., Wang, L. Z., Tang, B. T., Li, Y. B., Mao, J., Kong, A. K. H., Zhong, Z. H., Ding, J., Mufakharov, T., Fan, J. F., Dou, L. M., Shen, R. F., and Ai, Y. L.
Abstract: We report observations of a transient source \fermi\ from radio to \grs. \fermi\ was discovered by the {\it Fermi-LAT} in May 2017. Follow-up {\it Swift-XRT} observations revealed three flaring episodes through March 2018, and the peak X-ray flux is about $10^3$ higher than the {\it ROSAT all-sky survey (RASS)} flux upper limit. Optical spectral measurements taken by the {\it Magellan 6.5-m telescope} and the {\it Lick-Shane telescope} both show a largely featureless spectrum, strengthening the BL Lac interpretation first proposed by \citet{Bruni18}. The optical and mid-infrared (MIR) emission goes to a higher state in 2018, when the flux in high energies goes down to a lower level. Our {\it RATAN-600m} measurements at 4.8~GHz and 8.2~GHz do not indicate any significant radio flux variation over the monitoring seasons in 2017 and 2018, nor deviate from the archival {\it NVSS} flux level. During GeV flaring times, the spectrum is very hard ($\Gamma_\gamma\sim$1.7) in the GeV band and at times also very hard (($\Gamma_{\rm X}\lesssim2$) in the X-rays, similar to a high-synchrotron-peak (or even an extreme) BL Lac object, making \fermi\ a good target for ground-based {\it Cherenkov telescopes}., Comment: Submitted in Journal of High Energy Astrophysics
Published: 2020
Full Text: View/download PDF

47. Thorax disease classification with attention guided convolutional neural network

Author: Guan, Q, Huang, Y, Zhong, Z, Zheng, Z, Zheng, L, Yang, Y, Guan, Q, Huang, Y, Zhong, Z, Zheng, Z, Zheng, L, and Yang, Y
Abstract: © 2019 Elsevier B.V. This paper considers the task of thorax disease diagnosis on chest X-ray (CXR) images. Most existing methods generally learn a network with global images as input. However, thorax diseases usually happen in (small) localized areas which are disease specific. Thus training CNNs using global images may be affected by the (excessive) irrelevant noisy areas. Besides, due to the poor alignment of some CXR images, the existence of irregular borders hinders the network performance. For addressing the above problems, we propose to integrate the global and local cues into a three-branch attention guided convolution neural network (AG-CNN) to identify thorax diseases. An attention guided mask inference based cropping strategy is proposed to avoid noise and improve alignment in the global branch. AG-CNN also integrates the global cues to compensate the lost discriminative cues by the local branch. Specifically, we first learn a global CNN branch using global images. Then, guided by the attention heatmap generated from the global branch, we infer a mask to crop a discriminative region from the global image. The local region is used for training a local CNN branch. Lastly, we concatenate the last pooling layers of both the global and local branches for fine-tuning the fusion branch. Experiments on the ChestX-ray14 dataset demonstrate that after integrating the local cues with the global information, the average AUC scores are improved by AG-CNN.
Published: 2020

48. Sub-ion-scale Dynamics of the Ion Diffusion Region in the Magnetotail : MMS Observations

Author: Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Pang, Y., Huang, S. Y., Khotyaintsev, Yuri V., Russell, C. T., Giles, B., Zhou, M., Man, H. Y., Zhong, Z. H., Deng, X. H., Pang, Y., Huang, S. Y., Khotyaintsev, Yuri V., Russell, C. T., and Giles, B.
Abstract: This paper reports magnetospheric multiscale (MMS) observations of the sub-ion-scale dynamics within the ion diffusion region (IDR) in the Earth's magnetotail. MMS crossed the IDR from the southern to the northern hemisphere, at about two ion inertial length earthward of the X line with a small guide field. Electrons were anisotropic in the inflow region of the IDR and turned into isotropic within the IDR. The isotropization of the electrons was probably due to the pitch angle scattering in highly curved magnetic field lines. We suggest that the thickness of the electron isotropic region strongly depends on the horizontal distance to the X line. The out-of-plane current bifurcated in the IDR. It peaked at the boundaries between the inflow and outflow electrons around the separatrices. Magnetic energy conversion and dissipation predominantly occurred at the peak of the out-of-plane current instead of at the neutral sheet center where B-L = 0. Both the energy dissipation and normal electric field E-N exhibited evident asymmetry with respect to the neutral sheet. The energy dissipation was larger around the northern separatrix than around the southern separatrix. The electric field E-N showed a tripolar variation across the neutral sheet, that is, a unipolar E-N around the southern separatrix and a bipolar E-N around the northern separatrix. The reasons and implications of these asymmetries are discussed.
Published: 2019
Full Text: View/download PDF

49. Energy Conversion and Dissipation at Dipolarization Fronts : A Statistical Overview

Author: Zhong, Z. H., Deng, X. H., Zhou, M., Ma, W. Q., Tang, R. X., Khotyaintsev, Yuri V., Giles, B. L., Russell, C. T., Burch, J. L., Zhong, Z. H., Deng, X. H., Zhou, M., Ma, W. Q., Tang, R. X., Khotyaintsev, Yuri V., Giles, B. L., Russell, C. T., and Burch, J. L.
Abstract: Dipolarization fronts (DFs) are important for energy conversion, particle acceleration, and flux transport in the magnetotail. The partition of energy conversion between ions and electrons and the energy dissipation at DFs are not well understood. In this paper, we present a statistical study of energy conversion and dissipation of 122 DFs observed by Magnetospheric Multiscale mission in the magnetotail. Statistically, electromagnetic energy transfers to plasma at DF. The released energy is mainly transferred to ions rather than electrons. On average, ions gain energy across the whole DF, while electrons gain energy at the leading part but lose energy at the trailing part of DFs. Joule dissipation J center dot (E+v(e) x B) can be either positive or negative at DFs, and its average value is very small. The kinetic energy dissipation parameter Pi - D does not exhibit clear signatures at the DFs; hence, it is not suitable for quantifying the energy dissipation at DF.
Published: 2019
Full Text: View/download PDF

50. Electron-scale Vertical Current Sheets in a Bursty Bulk Flow in the Terrestrial Magnetotail

Author: Zhou, M., Huang, J., Man, H. Y., Deng, X. H., Zhong, Z. H., Russell, C. T., Paterson, W. R., Giles, B. L., Lindqvist, P-A, Khotyaintsev, Yuri V., Burch, J. L., Zhou, M., Huang, J., Man, H. Y., Deng, X. H., Zhong, Z. H., Russell, C. T., Paterson, W. R., Giles, B. L., Lindqvist, P-A, Khotyaintsev, Yuri V., and Burch, J. L.
Abstract: We report Magnetospheric Multiscale observations of multiple vertical current sheets (CSs) in a bursty bulk flow in the near-Earth magnetotail. Two of the CSs were fine structures of a dipolarization front (DF) at the leading edge of the flow. The other CSs were a few Earth radii tailward of the DF; that is, in the wake of the DF. Some of these vertical CSs were a few electron inertial lengths thick and were converting energy from magnetic field to plasma. The currents of the CSs in the DF wake were carried by electrons that formed flow shear layers. These electron-scale CSs were probably formed during the turbulent evolution of the bursty bulk flow and are important for energy conversion associated with fast flows.
Published: 2019
Full Text: View/download PDF

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Publication Year Range

Publication Type

Journal

Database

Publisher

226 results on '"Zhong, Z."'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources