[{"author":[{"last_name":"Volberg","full_name":"Volberg, Alexander","first_name":"Alexander"},{"full_name":"Zhang, Haonan","id":"D8F41E38-9E66-11E9-A9E2-65C2E5697425","last_name":"Zhang","first_name":"Haonan"}],"acknowledgement":"The research of A.V. is supported by NSF DMS-1900286, DMS-2154402 and by Hausdorff Center for Mathematics. H.Z. is supported by the Lise Meitner fellowship, Austrian Science Fund (FWF) M3337. This work is partially supported by NSF DMS-1929284 while both authors were in residence at the Institute for Computational and Experimental Research in Mathematics in Providence, RI, during the Harmonic Analysis and Convexity program.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"journal_article","corr_author":"1","file_date_updated":"2024-07-22T09:38:15Z","arxiv":1,"_id":"13318","oa":1,"intvolume":" 389","pmid":1,"page":"1657-1676","ddc":["510"],"file":[{"file_size":351796,"relation":"main_file","success":1,"access_level":"open_access","checksum":"56e67756e4c6c97589a8385e15ea2d2a","date_created":"2024-07-22T09:38:15Z","file_id":"17299","creator":"dernst","content_type":"application/pdf","file_name":"2024_MathAnnalen_Volberg.pdf","date_updated":"2024-07-22T09:38:15Z"}],"publication":"Mathematische Annalen","language":[{"iso":"eng"}],"has_accepted_license":"1","status":"public","scopus_import":"1","date_created":"2023-07-30T22:01:03Z","isi":1,"title":"Noncommutative Bohnenblust–Hille inequalities","date_updated":"2025-04-23T07:50:55Z","department":[{"_id":"JaMa"}],"month":"06","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"publisher":"Springer Nature","publication_identifier":{"eissn":["1432-1807"],"issn":["0025-5831"]},"article_processing_charge":"Yes (in subscription journal)","doi":"10.1007/s00208-023-02680-0","publication_status":"published","year":"2024","date_published":"2024-06-01T00:00:00Z","citation":{"ista":"Volberg A, Zhang H. 2024. Noncommutative Bohnenblust–Hille inequalities. Mathematische Annalen. 389, 1657–1676.","ieee":"A. Volberg and H. Zhang, “Noncommutative Bohnenblust–Hille inequalities,” Mathematische Annalen, vol. 389. Springer Nature, pp. 1657–1676, 2024.","mla":"Volberg, Alexander, and Haonan Zhang. “Noncommutative Bohnenblust–Hille Inequalities.” Mathematische Annalen, vol. 389, Springer Nature, 2024, pp. 1657–76, doi:10.1007/s00208-023-02680-0.","short":"A. Volberg, H. Zhang, Mathematische Annalen 389 (2024) 1657–1676.","apa":"Volberg, A., & Zhang, H. (2024). Noncommutative Bohnenblust–Hille inequalities. Mathematische Annalen. Springer Nature. https://doi.org/10.1007/s00208-023-02680-0","ama":"Volberg A, Zhang H. Noncommutative Bohnenblust–Hille inequalities. Mathematische Annalen. 2024;389:1657-1676. doi:10.1007/s00208-023-02680-0","chicago":"Volberg, Alexander, and Haonan Zhang. “Noncommutative Bohnenblust–Hille Inequalities.” Mathematische Annalen. Springer Nature, 2024. https://doi.org/10.1007/s00208-023-02680-0."},"article_type":"original","abstract":[{"lang":"eng","text":"Bohnenblust–Hille inequalities for Boolean cubes have been proven with dimension-free constants that grow subexponentially in the degree (Defant et al. in Math Ann 374(1):653–680, 2019). Such inequalities have found great applications in learning low-degree Boolean functions (Eskenazis and Ivanisvili in Proceedings of the 54th annual ACM SIGACT symposium on theory of computing, pp 203–207, 2022). Motivated by learning quantum observables, a qubit analogue of Bohnenblust–Hille inequality for Boolean cubes was recently conjectured in Rouzé et al. (Quantum Talagrand, KKL and Friedgut’s theorems and the learnability of quantum Boolean functions, 2022. arXiv preprint arXiv:2209.07279). The conjecture was resolved in Huang et al. (Learning to predict arbitrary quantum processes, 2022. arXiv preprint arXiv:2210.14894). In this paper, we give a new proof of these Bohnenblust–Hille inequalities for qubit system with constants that are dimension-free and of exponential growth in the degree. As a consequence, we obtain a junta theorem for low-degree polynomials. Using similar ideas, we also study learning problems of low degree quantum observables and Bohr’s radius phenomenon on quantum Boolean cubes."}],"external_id":{"isi":["001035665500001"],"arxiv":["2210.14468"],"pmid":["38751410"]},"quality_controlled":"1","project":[{"name":"Curvature-dimension in noncommutative analysis","_id":"eb958bca-77a9-11ec-83b8-c565cb50d8d6","grant_number":"M03337"}],"volume":389,"day":"01","oa_version":"Published Version"},{"ddc":["000"],"main_file_link":[{"url":"https://doi.org/10.5281/zenodo.13854760","open_access":"1"}],"abstract":[{"text":"This archive contains all the code and data necessary to reproduce the results presented in the \r\n\"Mapping the attractor landscape of Boolean networks\" paper.","lang":"eng"}],"OA_type":"green","date_created":"2025-06-10T07:10:01Z","status":"public","day":"28","oa_version":"Published Version","has_accepted_license":"1","date_updated":"2025-09-30T12:46:33Z","month":"09","department":[{"_id":"ToHe"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"author":[{"last_name":"trinh","full_name":"trinh, Van Giang","first_name":"Van Giang"},{"full_name":"Park, Kyu Hyong","last_name":"Park","first_name":"Kyu Hyong"},{"orcid":"0000-0003-1993-0331","first_name":"Samuel","last_name":"Pastva","full_name":"Pastva, Samuel","id":"07c5ea74-f61c-11ec-a664-aa7c5d957b2b"},{"full_name":"Rozum, Jordan","last_name":"Rozum","first_name":"Jordan"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","type":"research_data_reference","title":"Mapping the attractor landscape of Boolean networks","related_material":{"record":[{"id":"19796","status":"public","relation":"used_in_publication"}]},"year":"2024","date_published":"2024-09-28T00:00:00Z","oa":1,"citation":{"ista":"trinh VG, Park KH, Pastva S, Rozum J. 2024. Mapping the attractor landscape of Boolean networks, Zenodo, 10.5281/ZENODO.13854759.","mla":"trinh, Van Giang, et al. Mapping the Attractor Landscape of Boolean Networks. Zenodo, 2024, doi:10.5281/ZENODO.13854759.","ieee":"V. G. trinh, K. H. Park, S. Pastva, and J. Rozum, “Mapping the attractor landscape of Boolean networks.” Zenodo, 2024.","apa":"trinh, V. G., Park, K. H., Pastva, S., & Rozum, J. (2024). Mapping the attractor landscape of Boolean networks. Zenodo. https://doi.org/10.5281/ZENODO.13854759","short":"V.G. trinh, K.H. Park, S. Pastva, J. Rozum, (2024).","chicago":"trinh, Van Giang, Kyu Hyong Park, Samuel Pastva, and Jordan Rozum. “Mapping the Attractor Landscape of Boolean Networks.” Zenodo, 2024. https://doi.org/10.5281/ZENODO.13854759.","ama":"trinh VG, Park KH, Pastva S, Rozum J. 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MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models, Zenodo, 10.5281/ZENODO.14213091.","ieee":"E. Frantar, R. Castro, J. Chen, T. Hoefler, and D.-A. Alistarh, “MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models.” Zenodo, 2024.","mla":"Frantar, Elias, et al. MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models. Zenodo, 2024, doi:10.5281/ZENODO.14213091.","short":"E. Frantar, R. Castro, J. Chen, T. Hoefler, D.-A. Alistarh, (2024).","apa":"Frantar, E., Castro, R., Chen, J., Hoefler, T., & Alistarh, D.-A. (2024). MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models. Zenodo. https://doi.org/10.5281/ZENODO.14213091","ama":"Frantar E, Castro R, Chen J, Hoefler T, Alistarh D-A. MARLIN: Mixed-precision auto-regressive parallel inference on Large Language Models. 2024. doi:10.5281/ZENODO.14213091","chicago":"Frantar, Elias, Roberto Castro, Jiale Chen, Torsten Hoefler, and Dan-Adrian Alistarh. “MARLIN: Mixed-Precision Auto-Regressive Parallel Inference on Large Language Models.” Zenodo, 2024. https://doi.org/10.5281/ZENODO.14213091."},"related_material":{"record":[{"status":"public","id":"19877","relation":"used_for_analysis_in"}]},"year":"2024","date_published":"2024-11-24T00:00:00Z","oa":1,"doi":"10.5281/ZENODO.14213091","article_processing_charge":"No","publisher":"Zenodo","OA_place":"repository","_id":"19884","ddc":["000"],"abstract":[{"text":"This is Marlin, a Mixed Auto-Regressive Linear kernel (and the name of one of the planet's fastest fish), an extremely optimized FP16xINT4 matmul kernel aimed at LLM inference that can deliver close to ideal (4x) speedups up to batchsizes of 16-32 tokens (in contrast to the 1-2 tokens of prior work with comparable speedup).\r\n\r\nAdditionally, it includes Sparse-Marlin, an extension of the MARLIN kernels adding support to 2:4 weight sparsity, achieving 5.3x speedups on NVIDIA GPUs (Ampere/Ada).","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/ZENODO.14213091"}],"date_created":"2025-06-24T06:09:18Z","status":"public","day":"24","oa_version":"Published Version","has_accepted_license":"1"},{"date_created":"2025-07-20T22:02:04Z","status":"public","scopus_import":"1","language":[{"iso":"eng"}],"publication":"Nature Mental Health","intvolume":" 2","page":"1134-1137","_id":"20039","issue":"10","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Maja","full_name":"Neidhart, Maja","last_name":"Neidhart"},{"full_name":"Kjelkenes, Rikka","last_name":"Kjelkenes","first_name":"Rikka"},{"first_name":"Karina","full_name":"Jansone, Karina","last_name":"Jansone"},{"last_name":"Rehák Bučková","full_name":"Rehák Bučková, 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Nicholas","first_name":"Nicholas"},{"first_name":"Paul","last_name":"Thompson","full_name":"Thompson, Paul"},{"full_name":"Schwalber, Ameli","last_name":"Schwalber","first_name":"Ameli"},{"full_name":"Liu, Jingyu","last_name":"Liu","first_name":"Jingyu"},{"full_name":"Calhoun, Vince","last_name":"Calhoun","first_name":"Vince"},{"first_name":"Xiao","full_name":"Chang, Xiao","last_name":"Chang"},{"full_name":"Xia, Yunman","last_name":"Xia","first_name":"Yunman"},{"last_name":"Gong","full_name":"Gong, Yanting","first_name":"Yanting"},{"first_name":"Tianye","last_name":"Jia","full_name":"Jia, Tianye"},{"first_name":"Paul","full_name":"Renner, Paul","last_name":"Renner"},{"last_name":"Hese","full_name":"Hese, Sören","first_name":"Sören"},{"last_name":"Giner","full_name":"Giner, Arantxa","first_name":"Arantxa"},{"full_name":"Sanchez, Mavi","last_name":"Sanchez","first_name":"Mavi"},{"first_name":"Elena","last_name":"Alvarez","full_name":"Alvarez, Elena"},{"full_name":"Spanlang, 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Lena","first_name":"Lena"},{"id":"3E57A680-F248-11E8-B48F-1D18A9856A87","full_name":"Novarino, Gaia","last_name":"Novarino","orcid":"0000-0002-7673-7178","first_name":"Gaia"},{"first_name":"Sarah Jane","full_name":"Böttger, Sarah Jane","last_name":"Böttger"},{"first_name":"Mira","last_name":"Tschorn","full_name":"Tschorn, Mira"},{"first_name":"Michael","full_name":"Rapp, Michael","last_name":"Rapp"},{"last_name":"Ask","full_name":"Ask, Helga","first_name":"Helga"},{"last_name":"Fernandez","full_name":"Fernandez, Sara","first_name":"Sara"},{"first_name":"Dennis","full_name":"Van Der Meer, Dennis","last_name":"Van Der Meer"},{"first_name":"Lars T.","full_name":"Westlye, Lars T.","last_name":"Westlye"},{"first_name":"Ole A.","last_name":"Andreassen","full_name":"Andreassen, Ole A."},{"first_name":"Rieke","last_name":"Aden","full_name":"Aden, Rieke"},{"last_name":"Seefried","full_name":"Seefried, Beke","first_name":"Beke"},{"first_name":"Sebastian","full_name":"Siehl, Sebastian","last_name":"Siehl"},{"first_name":"Frauke","last_name":"Nees","full_name":"Nees, Frauke"},{"first_name":"Argyris","last_name":"Stringaris","full_name":"Stringaris, Argyris"},{"full_name":"Tost, Heike","last_name":"Tost","first_name":"Heike"},{"first_name":"Andreas","full_name":"Meyer-Lindenberg, Andreas","last_name":"Meyer-Lindenberg"},{"first_name":"Nina","last_name":"Christmann","full_name":"Christmann, Nina"},{"first_name":"Jamie","full_name":"Banks, Jamie","last_name":"Banks"},{"first_name":"Kerstin","last_name":"Schepanski","full_name":"Schepanski, Kerstin"},{"full_name":"Schütz, Tatjana","last_name":"Schütz","first_name":"Tatjana"},{"first_name":"Ulrike Helene","full_name":"Taron, Ulrike Helene","last_name":"Taron"},{"full_name":"Eils, Roland","last_name":"Eils","first_name":"Roland"},{"first_name":"Jean Charles","full_name":"Roy, Jean Charles","last_name":"Roy"},{"first_name":"Tristram A.","last_name":"Lett","full_name":"Lett, Tristram A."},{"first_name":"Hedi","full_name":"Kebir, Hedi","last_name":"Kebir"},{"first_name":"Elli","last_name":"Polemiti","full_name":"Polemiti, Elli"},{"last_name":"Hitchen","full_name":"Hitchen, Esther","first_name":"Esther"},{"first_name":"Marcel","full_name":"Jentsch, Marcel","last_name":"Jentsch"},{"last_name":"Serin","full_name":"Serin, Emin","first_name":"Emin"},{"first_name":"Antoine","full_name":"Bernas, Antoine","last_name":"Bernas"},{"last_name":"Vaidya","full_name":"Vaidya, Nilakshi","first_name":"Nilakshi"},{"first_name":"Sven","full_name":"Twardziok, Sven","last_name":"Twardziok"},{"first_name":"Markus","full_name":"Ralser, Markus","last_name":"Ralser"},{"first_name":"Andreas","last_name":"Heinz","full_name":"Heinz, Andreas"}],"acknowledgement":"Funded by the European Union. Complementary funding was received by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (10041392 and 10038599). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union, the European Health and Digital Executive Agency (HADEA) or UKRI. The European Union, HADEA or UKRI cannot be held responsible for them. This work received support from the Chinese Ministry for Science and Technology (MOST), the Horizon 2020-funded European Research Council advanced grant ‘STRATIFY’ (695313); the German Research Foundation (COPE; 675346; NE 1383/15-1 and BA 2088/7-1 (CoviDrug)), the National Natural Science Foundation of China grant 82150710554, the Hector II foundation and the German Center for Mental Health (DZPG) (01EE2301A, 01EE2304A, 01EE2301D).","day":"01","volume":2,"oa_version":"None","quality_controlled":"1","abstract":[{"text":"This Comment presents a high-level protocol for data harmonization within large cohorts, in which it postulates four main steps including (1) expert review, (2) pre-statistical harmonization, (3) statistical harmonization, and (4) validation.","lang":"eng"}],"article_type":"comment","OA_type":"closed access","citation":{"chicago":"Neidhart, Maja, Rikka Kjelkenes, Karina Jansone, Barbora Rehák Bučková, Nathalie Holz, Frauke Nees, Henrik Walter, et al. “A Protocol for Data Harmonization in Large Cohorts.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00315-0.","ama":"Neidhart M, Kjelkenes R, Jansone K, et al. A protocol for data harmonization in large cohorts. Nature Mental Health. 2024;2(10):1134-1137. doi:10.1038/s44220-024-00315-0","apa":"Neidhart, M., Kjelkenes, R., Jansone, K., Rehák Bučková, B., Holz, N., Nees, F., … Heinz, A. (2024). A protocol for data harmonization in large cohorts. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00315-0","short":"M. Neidhart, R. Kjelkenes, K. Jansone, B. Rehák Bučková, N. Holz, F. Nees, H. Walter, G. Schumann, M.A. Rapp, T. Banaschewski, E. Schwarz, A. Marquand, G. Ogoh, B. Stahl, A.H. Young, S. Desrivières, N. Clinton, P. Thompson, A. Schwalber, J. Liu, V. Calhoun, X. Chang, Y. Xia, Y. Gong, T. Jia, P. Renner, S. Hese, A. Giner, M. Sanchez, E. Alvarez, B. Spanlang, C. Pearmund, A.P. Athanasiadis, L. Otten, S. Pitel, S. Petkoski, V. Jirsa, K. Schmitt, J. Wilbertz, M. Patraskaki, P. Sommer, S. Heilmann-Heimbach, C.M. Mathey, A. Miller, I. Claus, M.M. Nöthen, P. Hoffmann, A.J. Forstner, A. Pastor, J. Gallego, F.E. Orosa, G.F. Viapiana, M. Slater, L. Marr, G. Novarino, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, S. Siehl, F. Nees, A. Stringaris, H. Tost, A. Meyer-Lindenberg, N. Christmann, J. Banks, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, Nature Mental Health 2 (2024) 1134–1137.","mla":"Neidhart, Maja, et al. “A Protocol for Data Harmonization in Large Cohorts.” Nature Mental Health, vol. 2, no. 10, Springer Nature, 2024, pp. 1134–37, doi:10.1038/s44220-024-00315-0.","ieee":"M. Neidhart et al., “A protocol for data harmonization in large cohorts,” Nature Mental Health, vol. 2, no. 10. Springer Nature, pp. 1134–1137, 2024.","ista":"Neidhart M, Kjelkenes R, Jansone K, Rehák Bučková B, Holz N, Nees F, Walter H, Schumann G, Rapp MA, Banaschewski T, Schwarz E, Marquand A, Ogoh G, Stahl B, Young AH, Desrivières S, Clinton N, Thompson P, Schwalber A, Liu J, Calhoun V, Chang X, Xia Y, Gong Y, Jia T, Renner P, Hese S, Giner A, Sanchez M, Alvarez E, Spanlang B, Pearmund C, Athanasiadis AP, Otten L, Pitel S, Petkoski S, Jirsa V, Schmitt K, Wilbertz J, Patraskaki M, Sommer P, Heilmann-Heimbach S, Mathey CM, Miller A, Claus I, Nöthen MM, Hoffmann P, Forstner AJ, Pastor A, Gallego J, Orosa FE, Viapiana GF, Slater M, Marr L, Novarino G, Böttger SJ, Tschorn M, Rapp M, Ask H, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Siehl S, Nees F, Stringaris A, Tost H, Meyer-Lindenberg A, Christmann N, Banks J, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A. 2024. A protocol for data harmonization in large cohorts. Nature Mental Health. 2(10), 1134–1137."},"year":"2024","date_published":"2024-10-01T00:00:00Z","publication_status":"published","doi":"10.1038/s44220-024-00315-0","publisher":"Springer Nature","article_processing_charge":"No","publication_identifier":{"eissn":["2731-6076"]},"month":"10","department":[{"_id":"GaNo"}],"date_updated":"2025-07-22T08:59:10Z","title":"A protocol for data harmonization in large cohorts"},{"issue":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Zeng, Guifang","last_name":"Zeng","first_name":"Guifang"},{"first_name":"Qing","full_name":"Sun, Qing","last_name":"Sun"},{"id":"03a7e858-01b1-11ec-8b71-99ae6c4a05bc","full_name":"Horta, Sharona","last_name":"Horta","first_name":"Sharona"},{"first_name":"Shang","full_name":"Wang, Shang","last_name":"Wang"},{"first_name":"Xuan","last_name":"Lu","full_name":"Lu, Xuan"},{"first_name":"Chao Yue","last_name":"Zhang","full_name":"Zhang, Chao Yue"},{"last_name":"Li","full_name":"Li, Jing","first_name":"Jing"},{"last_name":"Li","full_name":"Li, Junshan","first_name":"Junshan"},{"first_name":"Lijie","full_name":"Ci, Lijie","last_name":"Ci"},{"last_name":"Tian","full_name":"Tian, Yanhong","first_name":"Yanhong"},{"first_name":"Maria","orcid":"0000-0001-5013-2843","id":"43C61214-F248-11E8-B48F-1D18A9856A87","full_name":"Ibáñez, Maria","last_name":"Ibáñez"},{"last_name":"Cabot","full_name":"Cabot, Andreu","first_name":"Andreu"}],"type":"other_academic_publication","oa":1,"_id":"20057","OA_place":"publisher","intvolume":" 36","status":"public","date_created":"2025-07-21T08:53:06Z","publication":"Advanced Materials","language":[{"iso":"eng"}],"date_updated":"2025-10-15T07:15:33Z","department":[{"_id":"MaIb"}],"month":"01","article_number":"2470004","title":"A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries","date_published":"2024-01-04T00:00:00Z","year":"2024","citation":{"short":"G. Zeng, Q. Sun, S. Horta, S. Wang, X. Lu, C.Y. Zhang, J. Li, J. Li, L. Ci, Y. Tian, M. Ibáñez, A. Cabot, A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries, Wiley, 2024.","apa":"Zeng, G., Sun, Q., Horta, S., Wang, S., Lu, X., Zhang, C. Y., … Cabot, A. (2024). A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries. Advanced Materials (Vol. 36). Wiley. https://doi.org/10.1002/adma.202470004","ama":"Zeng G, Sun Q, Horta S, et al. A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries. Vol 36. Wiley; 2024. doi:10.1002/adma.202470004","chicago":"Zeng, Guifang, Qing Sun, Sharona Horta, Shang Wang, Xuan Lu, Chao Yue Zhang, Jing Li, et al. A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries. Advanced Materials. Vol. 36. Wiley, 2024. https://doi.org/10.1002/adma.202470004.","ista":"Zeng G, Sun Q, Horta S, Wang S, Lu X, Zhang CY, Li J, Li J, Ci L, Tian Y, Ibáñez M, Cabot A. 2024. A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries, Wiley,p.","ieee":"G. Zeng et al., A layered Bi2Te3@PPy cathode for aqueous Zinc‐Ion batteries: Mechanism and application in printed flexible batteries, vol. 36, no. 1. Wiley, 2024.","mla":"Zeng, Guifang, et al. “A Layered Bi2Te3@PPy Cathode for Aqueous Zinc‐Ion Batteries: Mechanism and Application in Printed Flexible Batteries.” Advanced Materials, vol. 36, no. 1, 2470004, Wiley, 2024, doi:10.1002/adma.202470004."},"publisher":"Wiley","article_processing_charge":"No","publication_identifier":{"issn":["0935-9648"],"eissn":["1521-4095"]},"doi":"10.1002/adma.202470004","publication_status":"published","abstract":[{"lang":"eng","text":"In article number 2305128, Qing Sun, Shang Wang, Yanhong Tian, Andreu Cabot, and co-workers report an investigation of the energy-storage mechanism of a layered Bi2Te3-based cathode for aqueous zinc-ion batteries (ZIBs). They demonstrate that the zinc ion is not inserted into the cathode as previously assumed; in contrast, proton charge-storage dominates the process. They also demonstrate the great application prospects of aqueous ZIBs in flexible electronics via jet printing technology."}],"main_file_link":[{"url":"https://doi.org/10.1002/adma.202470004","open_access":"1"}],"OA_type":"free access","day":"04","oa_version":"Published Version","volume":36,"quality_controlled":"1"},{"day":"18","oa_version":"Published Version","date_created":"2025-08-05T06:49:59Z","status":"public","has_accepted_license":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.5281/zenodo.7137151"}],"abstract":[{"lang":"eng","text":"PyDaddy is an open source package which is a key contribution of the manuscript Nabeel et al, arXiv:2205.02645. The basic scientific premise for this package is to discover the nature of stochasticity in ecological time series datasets. It is well known that the stochasticity can affect the dynamics of ecological systems in counter-intuitive ways. Without understanding the equations (typically, in the form of stochastic differential equations or SDEs, in short) that govern the dynamics of populations or ecosystems, it's challenging to determine the impact of randomness on real datasets. In this manuscript and accompanying package, we introduce a methodology for discovering equations (SDEs) that transforms time series data of state variables into stochastic differential equations. This approach merges traditional stochastic calculus with modern equation-discovery techniques. We showcase the generality of our method through various applications and discuss its limitations and potential pitfalls, offering diagnostic measures to address these challenges."}],"ddc":["570"],"citation":{"short":"A. Nabeel, A. Karichannavar, S. Palathingal, J. Jhawar, D. Brückner, M. Danny Raj, V. Guttal, (2024).","apa":"Nabeel, A., Karichannavar, A., Palathingal, S., Jhawar, J., Brückner, D., Danny Raj, M., & Guttal, V. (2024). PyDaddy: A Python Package for Discovering SDEs from Time Series Data. Zenodo. https://doi.org/10.5281/ZENODO.7137151","ama":"Nabeel A, Karichannavar A, Palathingal S, et al. PyDaddy: A Python Package for Discovering SDEs from Time Series Data. 2024. doi:10.5281/ZENODO.7137151","chicago":"Nabeel, Arshed, Ashwin Karichannavar, Shuaib Palathingal, Jitesh Jhawar, David Brückner, Masila Danny Raj, and Vishwesha Guttal. “PyDaddy: A Python Package for Discovering SDEs from Time Series Data.” Zenodo, 2024. https://doi.org/10.5281/ZENODO.7137151.","ista":"Nabeel A, Karichannavar A, Palathingal S, Jhawar J, Brückner D, Danny Raj M, Guttal V. 2024. PyDaddy: A Python Package for Discovering SDEs from Time Series Data, Zenodo, 10.5281/ZENODO.7137151.","ieee":"A. Nabeel et al., “PyDaddy: A Python Package for Discovering SDEs from Time Series Data.” Zenodo, 2024.","mla":"Nabeel, Arshed, et al. PyDaddy: A Python Package for Discovering SDEs from Time Series Data. Zenodo, 2024, doi:10.5281/ZENODO.7137151."},"oa":1,"year":"2024","date_published":"2024-09-18T00:00:00Z","related_material":{"record":[{"id":"20056","status":"public","relation":"used_for_analysis_in"}]},"_id":"20121","doi":"10.5281/ZENODO.7137151","article_processing_charge":"No","publisher":"Zenodo","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"month":"09","department":[{"_id":"EdHa"}],"date_updated":"2025-09-30T14:14:42Z","title":"PyDaddy: A Python Package for Discovering SDEs from Time Series Data","type":"research_data_reference","author":[{"first_name":"Arshed","last_name":"Nabeel","full_name":"Nabeel, Arshed"},{"last_name":"Karichannavar","full_name":"Karichannavar, Ashwin","first_name":"Ashwin"},{"first_name":"Shuaib","last_name":"Palathingal","full_name":"Palathingal, Shuaib"},{"first_name":"Jitesh","full_name":"Jhawar, Jitesh","last_name":"Jhawar"},{"last_name":"Brückner","id":"e1e86031-6537-11eb-953a-f7ab92be508d","full_name":"Brückner, David","first_name":"David","orcid":"0000-0001-7205-2975"},{"full_name":"Danny Raj, Masila","last_name":"Danny Raj","first_name":"Masila"},{"last_name":"Guttal","full_name":"Guttal, Vishwesha","first_name":"Vishwesha"}],"acknowledgement":"This study was partially funded by Science and Engineering Research Board, Department of Science and Technology, Government of India to Vishwesha Guttal.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"oa_version":"None","volume":2,"day":"01","quality_controlled":"1","article_type":"comment","abstract":[{"lang":"eng","text":"Integrative analyses that incorporate different levels of ‘-omics’ data represent a powerful tool for deciphering the biological mechanisms that underlie environmental influences on mental health and disease. This Comment highlights various aspects of such multi-omics approaches, using the example of the EU-funded environMENTAL project."}],"OA_type":"closed access","year":"2024","date_published":"2024-10-01T00:00:00Z","citation":{"apa":"Desrivières, S., Miller, A., Mathey, C. M., Yu, X., Chen, D., Agunbiade, K., … Walter, H. (2024). Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00317-y","short":"S. Desrivières, A. Miller, C.M. Mathey, X. Yu, D. Chen, K. Agunbiade, S. Heilmann-Heimbach, A.J. Forstner, G. Schumann, P. Hoffmann, M.M. Nöthen, G. Ogoh, B. Stahl, A.H. Young, N. Clinton, P. Thompson, A. Schwalber, J. Liu, V. Calhoun, X. Chang, Y. Xia, Y. Gong, T. Jia, P. Renner, S. Hese, A. Giner, M. Sanchez, E. Alvarez, B. Spanlang, C. Pearmund, A.P. Athanasiadis, L. Otten, S. Pitel, S. Petkoski, V. Jirsa, K. Schmitt, J. Wilbertz, M. Patraskaki, P. Sommer, I. Claus, A. Pastor, J. Gallego, F.E. Orosa, G.F. Viapiana, M. Slater, L. Marr, G. Novarino, A. Marquand, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, R. Kjelkenes, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, S. Siehl, F. Nees, M. Neidhart, A. Stringaris, E. Schwarz, N. Holz, H. Tost, A. Meyer-Lindenberg, N. Christmann, K. Jansone, T. Banaschewski, J. Banks, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, H. Walter, Nature Mental Health 2 (2024) 1131–1133.","chicago":"Desrivières, Sylvane, Abigail Miller, Carina M. Mathey, Xinyang Yu, Di Chen, Kofoworola Agunbiade, Stefanie Heilmann-Heimbach, et al. “Multi-Omics Analyses of the EnvironMENTAL Project Provide Insights into Mental Health and Disease.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00317-y.","ama":"Desrivières S, Miller A, Mathey CM, et al. Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. Nature Mental Health. 2024;2(10):1131-1133. doi:10.1038/s44220-024-00317-y","ista":"Desrivières S, Miller A, Mathey CM, Yu X, Chen D, Agunbiade K, Heilmann-Heimbach S, Forstner AJ, Schumann G, Hoffmann P, Nöthen MM, Ogoh G, Stahl B, Young AH, Clinton N, Thompson P, Schwalber A, Liu J, Calhoun V, Chang X, Xia Y, Gong Y, Jia T, Renner P, Hese S, Giner A, Sanchez M, Alvarez E, Spanlang B, Pearmund C, Athanasiadis AP, Otten L, Pitel S, Petkoski S, Jirsa V, Schmitt K, Wilbertz J, Patraskaki M, Sommer P, Claus I, Pastor A, Gallego J, Orosa FE, Viapiana GF, Slater M, Marr L, Novarino G, Marquand A, Böttger SJ, Tschorn M, Rapp M, Ask H, Kjelkenes R, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Siehl S, Nees F, Neidhart M, Stringaris A, Schwarz E, Holz N, Tost H, Meyer-Lindenberg A, Christmann N, Jansone K, Banaschewski T, Banks J, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A, Walter H. 2024. Multi-omics analyses of the environMENTAL project provide insights into mental health and disease. Nature Mental Health. 2(10), 1131–1133.","mla":"Desrivières, Sylvane, et al. “Multi-Omics Analyses of the EnvironMENTAL Project Provide Insights into Mental Health and Disease.” Nature Mental Health, vol. 2, no. 10, Springer Nature, 2024, pp. 1131–33, doi:10.1038/s44220-024-00317-y.","ieee":"S. Desrivières et al., “Multi-omics analyses of the environMENTAL project provide insights into mental health and disease,” Nature Mental Health, vol. 2, no. 10. Springer Nature, pp. 1131–1133, 2024."},"publisher":"Springer Nature","publication_identifier":{"eissn":["2731-6076"]},"article_processing_charge":"No","doi":"10.1038/s44220-024-00317-y","publication_status":"published","date_updated":"2025-08-11T06:44:03Z","month":"10","department":[{"_id":"GaNo"}],"title":"Multi-omics analyses of the environMENTAL project provide insights into mental health and disease","date_created":"2025-08-10T22:01:30Z","scopus_import":"1","status":"public","publication":"Nature Mental Health","language":[{"iso":"eng"}],"intvolume":" 2","page":"1131-1133","_id":"20156","issue":"10","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Sylvane","full_name":"Desrivières, Sylvane","last_name":"Desrivières"},{"full_name":"Miller, Abigail","last_name":"Miller","first_name":"Abigail"},{"full_name":"Mathey, Carina M.","last_name":"Mathey","first_name":"Carina M."},{"first_name":"Xinyang","full_name":"Yu, Xinyang","last_name":"Yu"},{"last_name":"Chen","full_name":"Chen, Di","first_name":"Di"},{"last_name":"Agunbiade","full_name":"Agunbiade, Kofoworola","first_name":"Kofoworola"},{"last_name":"Heilmann-Heimbach","full_name":"Heilmann-Heimbach, Stefanie","first_name":"Stefanie"},{"first_name":"Andreas J.","last_name":"Forstner","full_name":"Forstner, Andreas J."},{"first_name":"Gunter","full_name":"Schumann, Gunter","last_name":"Schumann"},{"full_name":"Hoffmann, Per","last_name":"Hoffmann","first_name":"Per"},{"last_name":"Nöthen","full_name":"Nöthen, Markus M.","first_name":"Markus M."},{"last_name":"Ogoh","full_name":"Ogoh, George","first_name":"George"},{"first_name":"Bernd","full_name":"Stahl, Bernd","last_name":"Stahl"},{"last_name":"Young","full_name":"Young, Allan H.","first_name":"Allan H."},{"first_name":"Nicholas","last_name":"Clinton","full_name":"Clinton, Nicholas"},{"last_name":"Thompson","full_name":"Thompson, Paul","first_name":"Paul"},{"last_name":"Schwalber","full_name":"Schwalber, Ameli","first_name":"Ameli"},{"last_name":"Liu","full_name":"Liu, Jingyu","first_name":"Jingyu"},{"first_name":"Vince","last_name":"Calhoun","full_name":"Calhoun, Vince"},{"full_name":"Chang, Xiao","last_name":"Chang","first_name":"Xiao"},{"first_name":"Yunman","last_name":"Xia","full_name":"Xia, Yunman"},{"full_name":"Gong, Yanting","last_name":"Gong","first_name":"Yanting"},{"full_name":"Jia, Tianye","last_name":"Jia","first_name":"Tianye"},{"full_name":"Renner, Paul","last_name":"Renner","first_name":"Paul"},{"first_name":"Sören","last_name":"Hese","full_name":"Hese, Sören"},{"first_name":"Arantxa","full_name":"Giner, Arantxa","last_name":"Giner"},{"full_name":"Sanchez, Mavi","last_name":"Sanchez","first_name":"Mavi"},{"last_name":"Alvarez","full_name":"Alvarez, Elena","first_name":"Elena"},{"first_name":"Bernhard","full_name":"Spanlang, Bernhard","last_name":"Spanlang"},{"full_name":"Pearmund, Charlie","last_name":"Pearmund","first_name":"Charlie"},{"full_name":"Athanasiadis, Anastasios Polykarpos","last_name":"Athanasiadis","first_name":"Anastasios Polykarpos"},{"first_name":"Lisa","last_name":"Otten","full_name":"Otten, Lisa"},{"first_name":"Séverine","last_name":"Pitel","full_name":"Pitel, Séverine"},{"last_name":"Petkoski","full_name":"Petkoski, Spase","first_name":"Spase"},{"first_name":"Viktor","full_name":"Jirsa, Viktor","last_name":"Jirsa"},{"first_name":"Karen","full_name":"Schmitt, Karen","last_name":"Schmitt"},{"full_name":"Wilbertz, Johannes","last_name":"Wilbertz","first_name":"Johannes"},{"first_name":"Myrto","full_name":"Patraskaki, Myrto","last_name":"Patraskaki"},{"full_name":"Sommer, Peter","last_name":"Sommer","first_name":"Peter"},{"first_name":"Isabelle","full_name":"Claus, Isabelle","last_name":"Claus"},{"first_name":"Alvaro","full_name":"Pastor, Alvaro","last_name":"Pastor"},{"last_name":"Gallego","full_name":"Gallego, Jaime","first_name":"Jaime"},{"full_name":"Orosa, Francisco Eiroa","last_name":"Orosa","first_name":"Francisco Eiroa"},{"first_name":"Guillem Feixas","full_name":"Viapiana, Guillem Feixas","last_name":"Viapiana"},{"first_name":"Mel","full_name":"Slater, Mel","last_name":"Slater"},{"last_name":"Marr","full_name":"Marr, Lena","id":"4406F586-F248-11E8-B48F-1D18A9856A87","first_name":"Lena"},{"last_name":"Novarino","id":"3E57A680-F248-11E8-B48F-1D18A9856A87","full_name":"Novarino, Gaia","orcid":"0000-0002-7673-7178","first_name":"Gaia"},{"first_name":"Andre","last_name":"Marquand","full_name":"Marquand, Andre"},{"full_name":"Böttger, Sarah Jane","last_name":"Böttger","first_name":"Sarah Jane"},{"full_name":"Tschorn, Mira","last_name":"Tschorn","first_name":"Mira"},{"full_name":"Rapp, Michael","last_name":"Rapp","first_name":"Michael"},{"first_name":"Helga","full_name":"Ask, Helga","last_name":"Ask"},{"last_name":"Kjelkenes","full_name":"Kjelkenes, Rikka","first_name":"Rikka"},{"last_name":"Fernandez","full_name":"Fernandez, Sara","first_name":"Sara"},{"first_name":"Dennis","last_name":"Van Der Meer","full_name":"Van Der Meer, Dennis"},{"full_name":"Westlye, Lars T.","last_name":"Westlye","first_name":"Lars T."},{"first_name":"Ole A.","full_name":"Andreassen, Ole A.","last_name":"Andreassen"},{"first_name":"Rieke","last_name":"Aden","full_name":"Aden, Rieke"},{"first_name":"Beke","full_name":"Seefried, Beke","last_name":"Seefried"},{"first_name":"Sebastian","full_name":"Siehl, Sebastian","last_name":"Siehl"},{"first_name":"Frauke","full_name":"Nees, Frauke","last_name":"Nees"},{"first_name":"Maja","last_name":"Neidhart","full_name":"Neidhart, Maja"},{"full_name":"Stringaris, Argyris","last_name":"Stringaris","first_name":"Argyris"},{"last_name":"Schwarz","full_name":"Schwarz, Emanuel","first_name":"Emanuel"},{"last_name":"Holz","full_name":"Holz, Nathalie","first_name":"Nathalie"},{"first_name":"Heike","last_name":"Tost","full_name":"Tost, Heike"},{"last_name":"Meyer-Lindenberg","full_name":"Meyer-Lindenberg, Andreas","first_name":"Andreas"},{"first_name":"Nina","full_name":"Christmann, Nina","last_name":"Christmann"},{"last_name":"Jansone","full_name":"Jansone, Karina","first_name":"Karina"},{"full_name":"Banaschewski, Tobias","last_name":"Banaschewski","first_name":"Tobias"},{"full_name":"Banks, Jamie","last_name":"Banks","first_name":"Jamie"},{"first_name":"Kerstin","full_name":"Schepanski, Kerstin","last_name":"Schepanski"},{"first_name":"Tatjana","last_name":"Schütz","full_name":"Schütz, Tatjana"},{"first_name":"Ulrike Helene","full_name":"Taron, Ulrike Helene","last_name":"Taron"},{"first_name":"Roland","full_name":"Eils, Roland","last_name":"Eils"},{"last_name":"Roy","full_name":"Roy, Jean Charles","first_name":"Jean Charles"},{"first_name":"Tristram A.","full_name":"Lett, Tristram A.","last_name":"Lett"},{"first_name":"Hedi","full_name":"Kebir, Hedi","last_name":"Kebir"},{"full_name":"Polemiti, Elli","last_name":"Polemiti","first_name":"Elli"},{"first_name":"Esther","full_name":"Hitchen, Esther","last_name":"Hitchen"},{"last_name":"Jentsch","full_name":"Jentsch, Marcel","first_name":"Marcel"},{"first_name":"Emin","full_name":"Serin, Emin","last_name":"Serin"},{"first_name":"Antoine","last_name":"Bernas","full_name":"Bernas, Antoine"},{"last_name":"Vaidya","full_name":"Vaidya, Nilakshi","first_name":"Nilakshi"},{"full_name":"Twardziok, Sven","last_name":"Twardziok","first_name":"Sven"},{"first_name":"Markus","full_name":"Ralser, Markus","last_name":"Ralser"},{"first_name":"Andreas","last_name":"Heinz","full_name":"Heinz, Andreas"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"}],"acknowledgement":"This work was supported by the Horizon 2021 (grant 101057429) and UK Research and Innovation (grants 10038599 and 10041392)-funded project environMENTAL. Other funding included the Medical Research Council and Medical Research Foundation (MR/R00465X/, MRF-058-0004-RG-DESRI, ‘ESTRA’- Neurobiological underpinning of eating disorders: integrative biopsychosocial longitudinal analyses in adolescents; and MR/S020306/1, MRF-058-0009-RG-DESR-C0759 ‘ESTRA’-Establishing causal relationships between biopsychosocial predictors and correlates of eating disorders and their mediation by neural pathways), the EU-funded FP6 Integrated Project IMAGEN (reinforcement-related behavior in normal brain function and psychopathology; LSHM-CT- 2007-037286), the Horizon 2020-funded European Research Council advanced grant for STRATIFY (brain network-based stratification of reinforcement-related disorders; 695313) and the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. This paper represents independent research, partly funded by the NIHR Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The authors thank C. Schmäl for proofreading the manuscript.","type":"journal_article"},{"language":[{"iso":"eng"}],"publication":"Nature Mental Health","scopus_import":"1","status":"public","date_created":"2025-08-10T22:01:30Z","intvolume":" 2","_id":"20157","type":"journal_article","author":[{"last_name":"Stahl","full_name":"Stahl, Bernd","first_name":"Bernd"},{"first_name":"George","last_name":"Ogoh","full_name":"Ogoh, George"},{"last_name":"Schumann","full_name":"Schumann, Gunter","first_name":"Gunter"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"},{"full_name":"Stahl, Bernd","last_name":"Stahl","first_name":"Bernd"},{"first_name":"Allan H.","last_name":"Young","full_name":"Young, Allan H."},{"first_name":"Sylvane","last_name":"Desrivières","full_name":"Desrivières, Sylvane"},{"first_name":"Nicholas","last_name":"Clinton","full_name":"Clinton, Nicholas"},{"first_name":"Paul","full_name":"Thompson, Paul","last_name":"Thompson"},{"full_name":"Schwalber, Ameli","last_name":"Schwalber","first_name":"Ameli"},{"first_name":"Jingyu","full_name":"Liu, Jingyu","last_name":"Liu"},{"full_name":"Calhoun, Vince","last_name":"Calhoun","first_name":"Vince"},{"last_name":"Chang","full_name":"Chang, Xiao","first_name":"Xiao"},{"first_name":"Yunman","last_name":"Xia","full_name":"Xia, Yunman"},{"first_name":"Yanting","full_name":"Gong, Yanting","last_name":"Gong"},{"full_name":"Jia, Tianye","last_name":"Jia","first_name":"Tianye"},{"first_name":"Paul","last_name":"Renner","full_name":"Renner, Paul"},{"first_name":"Sören","last_name":"Hese","full_name":"Hese, Sören"},{"first_name":"Arantxa","last_name":"Giner","full_name":"Giner, Arantxa"},{"full_name":"Sanchez, Mavi","last_name":"Sanchez","first_name":"Mavi"},{"first_name":"Elena","full_name":"Alvarez, Elena","last_name":"Alvarez"},{"first_name":"Bernhard","full_name":"Spanlang, Bernhard","last_name":"Spanlang"},{"last_name":"Pearmund","full_name":"Pearmund, Charlie","first_name":"Charlie"},{"last_name":"Athanasiadis","full_name":"Athanasiadis, Anastasios Polykarpos","first_name":"Anastasios Polykarpos"},{"first_name":"Lisa","last_name":"Otten","full_name":"Otten, Lisa"},{"first_name":"Séverine","full_name":"Pitel, Séverine","last_name":"Pitel"},{"first_name":"Spase","full_name":"Petkoski, Spase","last_name":"Petkoski"},{"last_name":"Jirsa","full_name":"Jirsa, Viktor","first_name":"Viktor"},{"full_name":"Schmitt, Karen","last_name":"Schmitt","first_name":"Karen"},{"first_name":"Johannes","last_name":"Wilbertz","full_name":"Wilbertz, Johannes"},{"full_name":"Patraskaki, Myrto","last_name":"Patraskaki","first_name":"Myrto"},{"full_name":"Sommer, Peter","last_name":"Sommer","first_name":"Peter"},{"last_name":"Heilmann-Heimbach","full_name":"Heilmann-Heimbach, Stefanie","first_name":"Stefanie"},{"first_name":"Carina M.","full_name":"Mathey, Carina M.","last_name":"Mathey"},{"first_name":"Abigail","full_name":"Miller, Abigail","last_name":"Miller"},{"first_name":"Isabelle","full_name":"Claus, Isabelle","last_name":"Claus"},{"first_name":"Markus M.","last_name":"Nöthen","full_name":"Nöthen, Markus M."},{"last_name":"Hoffmann","full_name":"Hoffmann, Per","first_name":"Per"},{"full_name":"Forstner, Andreas J.","last_name":"Forstner","first_name":"Andreas J."},{"first_name":"Alvaro","full_name":"Pastor, Alvaro","last_name":"Pastor"},{"last_name":"Gallego","full_name":"Gallego, Jaime","first_name":"Jaime"},{"first_name":"Francisco Eiroa","full_name":"Orosa, Francisco Eiroa","last_name":"Orosa"},{"full_name":"Viapiana, Guillem Feixas","last_name":"Viapiana","first_name":"Guillem Feixas"},{"full_name":"Slater, Mel","last_name":"Slater","first_name":"Mel"},{"id":"4406F586-F248-11E8-B48F-1D18A9856A87","full_name":"Marr, Lena","last_name":"Marr","first_name":"Lena"},{"orcid":"0000-0002-7673-7178","first_name":"Gaia","last_name":"Novarino","full_name":"Novarino, Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Andre","full_name":"Marquand, Andre","last_name":"Marquand"},{"first_name":"Sarah Jane","last_name":"Böttger","full_name":"Böttger, Sarah Jane"},{"first_name":"Mira","last_name":"Tschorn","full_name":"Tschorn, Mira"},{"first_name":"Michael","full_name":"Rapp, Michael","last_name":"Rapp"},{"last_name":"Ask","full_name":"Ask, Helga","first_name":"Helga"},{"full_name":"Kjelkenes, Rikka","last_name":"Kjelkenes","first_name":"Rikka"},{"last_name":"Fernandez","full_name":"Fernandez, Sara","first_name":"Sara"},{"first_name":"Dennis","full_name":"Van Der Meer, Dennis","last_name":"Van Der Meer"},{"first_name":"Lars T.","last_name":"Westlye","full_name":"Westlye, Lars T."},{"full_name":"Andreassen, Ole A.","last_name":"Andreassen","first_name":"Ole A."},{"first_name":"Rieke","full_name":"Aden, Rieke","last_name":"Aden"},{"full_name":"Seefried, Beke","last_name":"Seefried","first_name":"Beke"},{"full_name":"Siehl, Sebastian","last_name":"Siehl","first_name":"Sebastian"},{"first_name":"Frauke","last_name":"Nees","full_name":"Nees, Frauke"},{"first_name":"Maja","full_name":"Neidhart, Maja","last_name":"Neidhart"},{"first_name":"Argyris","last_name":"Stringaris","full_name":"Stringaris, Argyris"},{"last_name":"Schwarz","full_name":"Schwarz, Emanuel","first_name":"Emanuel"},{"first_name":"Nathalie","last_name":"Holz","full_name":"Holz, Nathalie"},{"last_name":"Tost","full_name":"Tost, Heike","first_name":"Heike"},{"first_name":"Andreas","last_name":"Meyer-Lindenberg","full_name":"Meyer-Lindenberg, Andreas"},{"first_name":"Nina","full_name":"Christmann, Nina","last_name":"Christmann"},{"last_name":"Jansone","full_name":"Jansone, Karina","first_name":"Karina"},{"last_name":"Banaschewski","full_name":"Banaschewski, Tobias","first_name":"Tobias"},{"last_name":"Banks","full_name":"Banks, Jamie","first_name":"Jamie"},{"first_name":"Kerstin","last_name":"Schepanski","full_name":"Schepanski, Kerstin"},{"first_name":"Tatjana","full_name":"Schütz, Tatjana","last_name":"Schütz"},{"last_name":"Taron","full_name":"Taron, Ulrike Helene","first_name":"Ulrike Helene"},{"full_name":"Eils, Roland","last_name":"Eils","first_name":"Roland"},{"first_name":"Jean Charles","last_name":"Roy","full_name":"Roy, Jean Charles"},{"first_name":"Tristram A.","last_name":"Lett","full_name":"Lett, Tristram A."},{"first_name":"Hedi","last_name":"Kebir","full_name":"Kebir, Hedi"},{"full_name":"Polemiti, Elli","last_name":"Polemiti","first_name":"Elli"},{"last_name":"Hitchen","full_name":"Hitchen, Esther","first_name":"Esther"},{"last_name":"Jentsch","full_name":"Jentsch, Marcel","first_name":"Marcel"},{"first_name":"Emin","full_name":"Serin, Emin","last_name":"Serin"},{"first_name":"Antoine","full_name":"Bernas, Antoine","last_name":"Bernas"},{"full_name":"Vaidya, Nilakshi","last_name":"Vaidya","first_name":"Nilakshi"},{"first_name":"Sven","last_name":"Twardziok","full_name":"Twardziok, Sven"},{"first_name":"Markus","last_name":"Ralser","full_name":"Ralser, Markus"},{"first_name":"Andreas","last_name":"Heinz","full_name":"Heinz, Andreas"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"}],"acknowledgement":"Funded provided by the European Union. Complementary funding was received by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee (10131373and 10038599) and Ministry of Science and Technology of China (MOST) National Key Project of ‘Inter-governmental International Scientific and Technological Innovation Cooperation’ (2023YFE0199700).","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"10","quality_controlled":"1","oa_version":"None","day":"01","volume":2,"OA_type":"closed access","article_type":"comment","abstract":[{"lang":"eng","text":"The focus of much of contemporary research ethics is on compliance with established protocols. However, large data-driven neuroscience research raises new ethical concerns that have no agreed-upon solution. Here we reflect on these challenges and propose better integration of public and patient involvement in this evolving landscape."}],"doi":"10.1038/s44220-024-00320-3","article_processing_charge":"No","publication_identifier":{"eissn":["2731-6076"]},"publisher":"Springer Nature","publication_status":"published","citation":{"short":"B. Stahl, G. Ogoh, G. Schumann, H. Walter, B. Stahl, A.H. Young, S. Desrivières, N. Clinton, P. Thompson, A. Schwalber, J. Liu, V. Calhoun, X. Chang, Y. Xia, Y. Gong, T. Jia, P. Renner, S. Hese, A. Giner, M. Sanchez, E. Alvarez, B. Spanlang, C. Pearmund, A.P. Athanasiadis, L. Otten, S. Pitel, S. Petkoski, V. Jirsa, K. Schmitt, J. Wilbertz, M. Patraskaki, P. Sommer, S. Heilmann-Heimbach, C.M. Mathey, A. Miller, I. Claus, M.M. Nöthen, P. Hoffmann, A.J. Forstner, A. Pastor, J. Gallego, F.E. Orosa, G.F. Viapiana, M. Slater, L. Marr, G. Novarino, A. Marquand, S.J. Böttger, M. Tschorn, M. Rapp, H. Ask, R. Kjelkenes, S. Fernandez, D. Van Der Meer, L.T. Westlye, O.A. Andreassen, R. Aden, B. Seefried, S. Siehl, F. Nees, M. Neidhart, A. Stringaris, E. Schwarz, N. Holz, H. Tost, A. Meyer-Lindenberg, N. Christmann, K. Jansone, T. Banaschewski, J. Banks, K. Schepanski, T. Schütz, U.H. Taron, R. Eils, J.C. Roy, T.A. Lett, H. Kebir, E. Polemiti, E. Hitchen, M. Jentsch, E. Serin, A. Bernas, N. Vaidya, S. Twardziok, M. Ralser, A. Heinz, H. Walter, Nature Mental Health 2 (2024).","apa":"Stahl, B., Ogoh, G., Schumann, G., Walter, H., Stahl, B., Young, A. H., … Walter, H. (2024). Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. Nature Mental Health. Springer Nature. https://doi.org/10.1038/s44220-024-00320-3","ama":"Stahl B, Ogoh G, Schumann G, et al. Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. Nature Mental Health. 2024;2(10). doi:10.1038/s44220-024-00320-3","chicago":"Stahl, Bernd, George Ogoh, Gunter Schumann, Henrik Walter, Bernd Stahl, Allan H. Young, Sylvane Desrivières, et al. “Rethinking Ethics in Interdisciplinary and Big Data-Driven Neuroscience Projects.” Nature Mental Health. Springer Nature, 2024. https://doi.org/10.1038/s44220-024-00320-3.","ista":"Stahl B, Ogoh G, Schumann G, Walter H, Stahl B, Young AH, Desrivières S, Clinton N, Thompson P, Schwalber A, Liu J, Calhoun V, Chang X, Xia Y, Gong Y, Jia T, Renner P, Hese S, Giner A, Sanchez M, Alvarez E, Spanlang B, Pearmund C, Athanasiadis AP, Otten L, Pitel S, Petkoski S, Jirsa V, Schmitt K, Wilbertz J, Patraskaki M, Sommer P, Heilmann-Heimbach S, Mathey CM, Miller A, Claus I, Nöthen MM, Hoffmann P, Forstner AJ, Pastor A, Gallego J, Orosa FE, Viapiana GF, Slater M, Marr L, Novarino G, Marquand A, Böttger SJ, Tschorn M, Rapp M, Ask H, Kjelkenes R, Fernandez S, Van Der Meer D, Westlye LT, Andreassen OA, Aden R, Seefried B, Siehl S, Nees F, Neidhart M, Stringaris A, Schwarz E, Holz N, Tost H, Meyer-Lindenberg A, Christmann N, Jansone K, Banaschewski T, Banks J, Schepanski K, Schütz T, Taron UH, Eils R, Roy JC, Lett TA, Kebir H, Polemiti E, Hitchen E, Jentsch M, Serin E, Bernas A, Vaidya N, Twardziok S, Ralser M, Heinz A, Walter H. 2024. Rethinking ethics in interdisciplinary and big data-driven neuroscience projects. Nature Mental Health. 2(10), 1128–1130.","ieee":"B. Stahl et al., “Rethinking ethics in interdisciplinary and big data-driven neuroscience projects,” Nature Mental Health, vol. 2, no. 10. Springer Nature, 2024.","mla":"Stahl, Bernd, et al. “Rethinking Ethics in Interdisciplinary and Big Data-Driven Neuroscience Projects.” Nature Mental Health, vol. 2, no. 10, 1128–1130, Springer Nature, 2024, doi:10.1038/s44220-024-00320-3."},"date_published":"2024-10-01T00:00:00Z","year":"2024","article_number":"1128-1130","title":"Rethinking ethics in interdisciplinary and big data-driven neuroscience projects","department":[{"_id":"GaNo"}],"month":"10","date_updated":"2025-08-11T06:53:55Z"},{"publication_status":"published","doi":"10.1007/978-981-96-0891-1_7","publisher":"Springer Nature","publication_identifier":{"isbn":["9789819608904"],"eissn":["1611-3349"],"issn":["0302-9743"]},"article_processing_charge":"No","citation":{"ama":"Ebrahimi E, Yadav A. Strongly secure universal thresholdizer. In: 30th International Conference on the Theory and Application of Cryptology and Information Security. Vol 15486. Springer Nature; 2024:207-239. doi:10.1007/978-981-96-0891-1_7","chicago":"Ebrahimi, Ehsan, and Anshu Yadav. “Strongly Secure Universal Thresholdizer.” In 30th International Conference on the Theory and Application of Cryptology and Information Security, 15486:207–39. Springer Nature, 2024. https://doi.org/10.1007/978-981-96-0891-1_7.","short":"E. Ebrahimi, A. Yadav, in:, 30th International Conference on the Theory and Application of Cryptology and Information Security, Springer Nature, 2024, pp. 207–239.","apa":"Ebrahimi, E., & Yadav, A. (2024). Strongly secure universal thresholdizer. In 30th International Conference on the Theory and Application of Cryptology and Information Security (Vol. 15486, pp. 207–239). Kolkata, India: Springer Nature. https://doi.org/10.1007/978-981-96-0891-1_7","ieee":"E. Ebrahimi and A. Yadav, “Strongly secure universal thresholdizer,” in 30th International Conference on the Theory and Application of Cryptology and Information Security, Kolkata, India, 2024, vol. 15486, pp. 207–239.","mla":"Ebrahimi, Ehsan, and Anshu Yadav. “Strongly Secure Universal Thresholdizer.” 30th International Conference on the Theory and Application of Cryptology and Information Security, vol. 15486, Springer Nature, 2024, pp. 207–39, doi:10.1007/978-981-96-0891-1_7.","ista":"Ebrahimi E, Yadav A. 2024. Strongly secure universal thresholdizer. 30th International Conference on the Theory and Application of Cryptology and Information Security. ASIACRYPT: Conference on the Theory and Application of Cryptology and Information Security vol. 15486, 207–239."},"date_published":"2024-12-12T00:00:00Z","year":"2024","title":"Strongly secure universal thresholdizer","isi":1,"month":"12","department":[{"_id":"KrPi"}],"date_updated":"2025-09-09T12:00:12Z","external_id":{"isi":["001443889100007"]},"quality_controlled":"1","volume":15486,"oa_version":"Preprint","day":"12","conference":{"start_date":"2024-12-09","location":"Kolkata, India","name":"ASIACRYPT: Conference on the Theory and Application of Cryptology and Information Security","end_date":"2024-12-13"},"OA_type":"green","main_file_link":[{"url":"https://eprint.iacr.org/2024/2078","open_access":"1"}],"abstract":[{"text":"A universalthresholdizer (UT), constructed from a threshold fully homomorphic encryption by Boneh et. al , Crypto 2018, is a general framework for universally thresholdizing many cryptographic schemes. However, their framework is insufficient to construct strongly secure threshold schemes, such as threshold signatures and threshold public-key encryption, etc.\r\n\r\nIn this paper, we strengthen the security definition for a universal thresholdizer and propose a scheme which satisfies our stronger security notion. Our UT scheme is an improvement of Boneh et. al ’s construction at the level of threshold fully homomorphic encryption using a key homomorphic pseudorandom function. We apply our strongly secure UT scheme to construct strongly secure threshold signatures and threshold public-key encryption.","lang":"eng"}],"OA_place":"repository","_id":"18755","oa":1,"type":"conference","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","acknowledgement":"Ehsan Ebrahimi is supported by the Luxembourg National Research Fund under the Junior CORE project QSP (C22/IS/17272217/QSP/Ebrahimi).","author":[{"full_name":"Ebrahimi, Ehsan","last_name":"Ebrahimi","first_name":"Ehsan"},{"full_name":"Yadav, Anshu","id":"dc8f1524-403e-11ee-bf07-9649ad996e21","last_name":"Yadav","first_name":"Anshu"}],"language":[{"iso":"eng"}],"publication":"30th International Conference on the Theory and Application of Cryptology and Information Security","date_created":"2025-01-05T23:01:56Z","status":"public","scopus_import":"1","page":"207-239","intvolume":" 15486"},{"main_file_link":[{"url":"https://eprint.iacr.org/2024/2000","open_access":"1"}],"abstract":[{"lang":"eng","text":"The evasive LWE assumption, proposed by Wee [Eurocrypt’22 Wee] for constructing a lattice-based optimal broadcast encryption, has shown to be a powerful assumption, adopted by subsequent works to construct advanced primitives ranging from ABE variants to obfuscation for null circuits. However, a closer look reveals significant differences among the precise assumption statements involved in different works, leading to the fundamental question of how these assumptions compare to each other. In this work, we initiate a more systematic study on evasive LWE assumptions:\r\n(i) Based on the standard LWE assumption, we construct simple counterexamples against three private-coin evasive LWE variants, used in [Crypto’22 Tsabary, Asiacrypt’22 VWW, Crypto’23 ARYY] respectively, showing that these assumptions are unlikely to hold.\r\n\r\n(ii) Based on existing evasive LWE variants and our counterexamples, we propose and define three classes of plausible evasive LWE assumptions, suitably capturing all existing variants for which we are not aware of non-obfuscation-based counterexamples.\r\n\r\n(iii) We show that under our assumption formulations, the security proofs of [Asiacrypt’22 VWW] and [Crypto’23 ARYY] can be recovered, and we reason why the security proof of [Crypto’22 Tsabary] is also plausibly repairable using an appropriate evasive LWE assumption."}],"OA_type":"green","conference":{"name":"ASIACRYPT: Conference on the Theory and Application of Cryptology and Information Security","end_date":"2024-12-13","location":"Kolkata, India","start_date":"2024-12-09"},"oa_version":"Preprint","day":"13","volume":15487,"alternative_title":["LNCS"],"external_id":{"isi":["001443890800014"]},"quality_controlled":"1","month":"12","department":[{"_id":"KrPi"}],"date_updated":"2025-09-09T12:00:51Z","isi":1,"title":"Evasive LWE assumptions: Definitions, classes, and counterexamples","citation":{"ieee":"C. Brzuska, A. Ünal, and I. K. Y. Woo, “Evasive LWE assumptions: Definitions, classes, and counterexamples,” in 30th International Conference on the Theory and Application of Cryptology and Information Security, Kolkata, India, 2024, vol. 15487, pp. 418–449.","mla":"Brzuska, Chris, et al. “Evasive LWE Assumptions: Definitions, Classes, and Counterexamples.” 30th International Conference on the Theory and Application of Cryptology and Information Security, vol. 15487, Springer Nature, 2024, pp. 418–49, doi:10.1007/978-981-96-0894-2_14.","ista":"Brzuska C, Ünal A, Woo IKY. 2024. Evasive LWE assumptions: Definitions, classes, and counterexamples. 30th International Conference on the Theory and Application of Cryptology and Information Security. ASIACRYPT: Conference on the Theory and Application of Cryptology and Information Security, LNCS, vol. 15487, 418–449.","ama":"Brzuska C, Ünal A, Woo IKY. Evasive LWE assumptions: Definitions, classes, and counterexamples. In: 30th International Conference on the Theory and Application of Cryptology and Information Security. Vol 15487. Springer Nature; 2024:418-449. doi:10.1007/978-981-96-0894-2_14","chicago":"Brzuska, Chris, Akin Ünal, and Ivy K.Y. Woo. “Evasive LWE Assumptions: Definitions, Classes, and Counterexamples.” In 30th International Conference on the Theory and Application of Cryptology and Information Security, 15487:418–49. Springer Nature, 2024. https://doi.org/10.1007/978-981-96-0894-2_14.","short":"C. Brzuska, A. Ünal, I.K.Y. Woo, in:, 30th International Conference on the Theory and Application of Cryptology and Information Security, Springer Nature, 2024, pp. 418–449.","apa":"Brzuska, C., Ünal, A., & Woo, I. K. Y. (2024). Evasive LWE assumptions: Definitions, classes, and counterexamples. In 30th International Conference on the Theory and Application of Cryptology and Information Security (Vol. 15487, pp. 418–449). Kolkata, India: Springer Nature. https://doi.org/10.1007/978-981-96-0894-2_14"},"year":"2024","date_published":"2024-12-13T00:00:00Z","doi":"10.1007/978-981-96-0894-2_14","article_processing_charge":"No","publisher":"Springer Nature","publication_identifier":{"isbn":["9789819608935"],"eissn":["1611-3349"],"issn":["0302-9743"]},"publication_status":"published","page":"418-449","intvolume":" 15487","scopus_import":"1","date_created":"2025-01-05T23:01:56Z","status":"public","language":[{"iso":"eng"}],"publication":"30th International Conference on the Theory and Application of Cryptology and Information Security","type":"conference","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","author":[{"first_name":"Chris","full_name":"Brzuska, Chris","last_name":"Brzuska"},{"last_name":"Ünal","full_name":"Ünal, Akin","id":"f6b56fb6-dc63-11ee-9dbf-f6780863a85a","first_name":"Akin","orcid":"0000-0002-8929-0221"},{"full_name":"Woo, Ivy K.Y.","last_name":"Woo","first_name":"Ivy K.Y."}],"acknowledgement":"The authors thank the anonymous reviewers for insightful comments which very much improved this work, in particular, sharing with us the counterexamples against a prior version of Hiding Evasive LWE, and against public-coin Evasive LWE when the sampler inputs B. Chris Brzuska and Ivy K. Y. Woo are supported by Research Council of Finland grant 358950. We thank Russell W. F. Lai and Hoeteck Wee for helpful discussions.","oa":1,"OA_place":"repository","_id":"18756"},{"language":[{"iso":"eng"}],"publication":"eLife","has_accepted_license":"1","date_created":"2025-01-05T23:01:57Z","status":"public","scopus_import":"1","pmid":1,"intvolume":" 13","ddc":["570"],"file":[{"content_type":"application/pdf","file_name":"2024_eLife_Last.pdf","date_updated":"2025-01-08T08:51:45Z","creator":"dernst","file_id":"18774","checksum":"a4f0f906e4d5c1078208b317e78699d1","date_created":"2025-01-08T08:51:45Z","file_size":7445664,"relation":"main_file","success":1,"access_level":"open_access"}],"DOAJ_listed":"1","OA_place":"publisher","_id":"18757","oa":1,"type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","acknowledgement":"We thank A Koster and M Barcena for helpful discussions and kindly sharing the coronaviral replication organelle datasets. We are also grateful to van den Hoek et al., 2022 and Wu et al., 2023, for uploading the data that we used for Figure 5 onto EMPIAR and EMDB, as well as to the authors of various other datasets uploaded to these databases that are not discussed in this manuscript but that were useful for testing the software. We also thank the reviewers, whose comments were very helpful in improving the manuscript and the software. Finally, we are grateful the early Ais users who provided us with feedback on the software and reported issues. This research was supported by the following grants to THS: European Research Council H202 Grant 759517; European Union’s Horizon Europe Program IMAGINE grant 101094250, and the Netherlands Organization for Scientific Research Grant VI.Vidi.193.014.","author":[{"full_name":"Last, Mart G.F.","last_name":"Last","first_name":"Mart G.F."},{"last_name":"Abendstein","full_name":"Abendstein, Leoni","id":"14f1f051-cd9d-11ef-9c94-8b942a882560","orcid":"0000-0001-7634-5353","first_name":"Leoni"},{"full_name":"Voortman, Lenard M.","last_name":"Voortman","first_name":"Lenard M."},{"first_name":"Thomas H.","full_name":"Sharp, Thomas H.","last_name":"Sharp"}],"file_date_updated":"2025-01-08T08:51:45Z","external_id":{"pmid":["39704648"]},"quality_controlled":"1","day":"20","volume":13,"oa_version":"Published Version","OA_type":"gold","article_type":"original","abstract":[{"text":"Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET.","lang":"eng"}],"doi":"10.7554/eLife.98552","publication_identifier":{"eissn":["2050-084X"]},"publisher":"eLife Sciences Publications","article_processing_charge":"Yes","publication_status":"published","citation":{"short":"M.G.F. Last, L. Abendstein, L.M. Voortman, T.H. Sharp, ELife 13 (2024).","apa":"Last, M. G. F., Abendstein, L., Voortman, L. M., & Sharp, T. H. (2024). Streamlining segmentation of cryo-electron tomography datasets with Ais. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.98552","ama":"Last MGF, Abendstein L, Voortman LM, Sharp TH. Streamlining segmentation of cryo-electron tomography datasets with Ais. eLife. 2024;13. doi:10.7554/eLife.98552","chicago":"Last, Mart G.F., Leoni Abendstein, Lenard M. Voortman, and Thomas H. Sharp. “Streamlining Segmentation of Cryo-Electron Tomography Datasets with Ais.” ELife. eLife Sciences Publications, 2024. https://doi.org/10.7554/eLife.98552.","ista":"Last MGF, Abendstein L, Voortman LM, Sharp TH. 2024. Streamlining segmentation of cryo-electron tomography datasets with Ais. eLife. 13, 98552.","ieee":"M. G. F. Last, L. Abendstein, L. M. Voortman, and T. H. Sharp, “Streamlining segmentation of cryo-electron tomography datasets with Ais,” eLife, vol. 13. eLife Sciences Publications, 2024.","mla":"Last, Mart G. F., et al. “Streamlining Segmentation of Cryo-Electron Tomography Datasets with Ais.” ELife, vol. 13, 98552, eLife Sciences Publications, 2024, doi:10.7554/eLife.98552."},"date_published":"2024-12-20T00:00:00Z","year":"2024","article_number":"98552","title":"Streamlining segmentation of cryo-electron tomography datasets with Ais","department":[{"_id":"FlPr"}],"month":"12","date_updated":"2025-01-08T08:52:51Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"}},{"related_material":{"record":[{"relation":"later_version","status":"public","id":"19603"}]},"oa":1,"arxiv":1,"_id":"18758","OA_place":"publisher","corr_author":"1","file_date_updated":"2025-01-08T09:14:59Z","acknowledgement":"Kalina Petrova: Swiss National Science Foundation, grant no. CRSII5 173721. This project\r\nhas received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101034413.\r\nSimon Weber: Swiss National Science Foundation under project no. 204320","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"full_name":"Lill, Jonas","last_name":"Lill","first_name":"Jonas"},{"first_name":"Kalina H","full_name":"Petrova, Kalina H","id":"554ff4e4-f325-11ee-b0c4-a10dbd523381","last_name":"Petrova"},{"first_name":"Simon","full_name":"Weber, Simon","last_name":"Weber"}],"type":"conference","scopus_import":"1","date_created":"2025-01-05T23:01:57Z","status":"public","publication":"19th International Symposium on Parameterized and Exact Computation","language":[{"iso":"eng"}],"has_accepted_license":"1","ddc":["500"],"file":[{"date_updated":"2025-01-08T09:14:59Z","file_name":"2024_LIPIcs_Lill.pdf","content_type":"application/pdf","creator":"dernst","file_id":"18775","date_created":"2025-01-08T09:14:59Z","checksum":"a64b9a0e41f7b867d25cb155825ccd53","access_level":"open_access","success":1,"relation":"main_file","file_size":927326}],"intvolume":" 321","year":"2024","date_published":"2024-12-05T00:00:00Z","citation":{"ista":"Lill J, Petrova KH, Weber S. 2024. Linear-time MaxCut in multigraphs parameterized above the Poljak-Turzík bound. 19th International Symposium on Parameterized and Exact Computation. IPEC: Symposium on Parameterized and Exact Computation, LIPIcs, vol. 321, 2.","mla":"Lill, Jonas, et al. “Linear-Time MaxCut in Multigraphs Parameterized above the Poljak-Turzík Bound.” 19th International Symposium on Parameterized and Exact Computation, vol. 321, 2, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024, doi:10.4230/LIPIcs.IPEC.2024.2.","ieee":"J. Lill, K. H. Petrova, and S. Weber, “Linear-time MaxCut in multigraphs parameterized above the Poljak-Turzík bound,” in 19th International Symposium on Parameterized and Exact Computation, Egham, United Kingdom, 2024, vol. 321.","apa":"Lill, J., Petrova, K. H., & Weber, S. (2024). Linear-time MaxCut in multigraphs parameterized above the Poljak-Turzík bound. In 19th International Symposium on Parameterized and Exact Computation (Vol. 321). Egham, United Kingdom: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.IPEC.2024.2","short":"J. Lill, K.H. Petrova, S. Weber, in:, 19th International Symposium on Parameterized and Exact Computation, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024.","chicago":"Lill, Jonas, Kalina H Petrova, and Simon Weber. “Linear-Time MaxCut in Multigraphs Parameterized above the Poljak-Turzík Bound.” In 19th International Symposium on Parameterized and Exact Computation, Vol. 321. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024. https://doi.org/10.4230/LIPIcs.IPEC.2024.2.","ama":"Lill J, Petrova KH, Weber S. Linear-time MaxCut in multigraphs parameterized above the Poljak-Turzík bound. In: 19th International Symposium on Parameterized and Exact Computation. Vol 321. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2024. doi:10.4230/LIPIcs.IPEC.2024.2"},"publication_identifier":{"isbn":["9783959773539"],"issn":["1868-8969"]},"article_processing_charge":"Yes","publisher":"Schloss Dagstuhl - Leibniz-Zentrum für Informatik","doi":"10.4230/LIPIcs.IPEC.2024.2","publication_status":"published","date_updated":"2026-01-05T13:46:07Z","department":[{"_id":"MaKw"}],"month":"12","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_number":"2","isi":1,"title":"Linear-time MaxCut in multigraphs parameterized above the Poljak-Turzík bound","ec_funded":1,"oa_version":"Published Version","volume":321,"day":"05","alternative_title":["LIPIcs"],"quality_controlled":"1","external_id":{"arxiv":["2407.01071"],"isi":["001534851900002"]},"project":[{"grant_number":"101034413","name":"IST-BRIDGE: International postdoctoral program","_id":"fc2ed2f7-9c52-11eb-aca3-c01059dda49c","call_identifier":"H2020"}],"abstract":[{"text":"MaxCut is a classical NP-complete problem and a crucial building block in many combinatorial algorithms. The famous Edwards-Erdős bound states that any connected graph on n vertices with m edges contains a cut of size at least m/2+(n-1)/4. Crowston, Jones and Mnich [Algorithmica, 2015] showed that the MaxCut problem on simple connected graphs admits an FPT algorithm, where the parameter k is the difference between the desired cut size c and the lower bound given by the Edwards-Erdős bound. This was later improved by Etscheid and Mnich [Algorithmica, 2017] to run in parameterized linear time, i.e., f(k)⋅ O(m). We improve upon this result in two ways: Firstly, we extend the algorithm to work also for multigraphs (alternatively, graphs with positive integer weights). Secondly, we change the parameter; instead of the difference to the Edwards-Erdős bound, we use the difference to the Poljak-Turzík bound. The Poljak-Turzík bound states that any weighted graph G has a cut of size at least (w(G))/2+(w_MSF(G))/4, where w(G) denotes the total weight of G, and w_MSF(G) denotes the weight of its minimum spanning forest. In connected simple graphs the two bounds are equivalent, but for multigraphs the Poljak-Turzík bound can be larger and thus yield a smaller parameter k. Our algorithm also runs in parameterized linear time, i.e., f(k)⋅ O(m+n).","lang":"eng"}],"OA_type":"gold","conference":{"end_date":"2024-09-06","name":"IPEC: Symposium on Parameterized and Exact Computation","start_date":"2024-09-04","location":"Egham, United Kingdom"}},{"external_id":{"isi":["001364636000001"],"arxiv":["2310.06887"]},"quality_controlled":"1","volume":976,"oa_version":"Published Version","day":"01","OA_type":"gold","article_type":"letter_note","abstract":[{"text":"With the remarkable sensitivity and resolution of JWST in the infrared, measuring rest-optical kinematics of galaxies at z > 5 has become possible for the first time. This study pilots a new method for measuring galaxy dynamics for highly multiplexed, unbiased samples by combining FRESCO NIRCam grism spectroscopy and JADES medium-band imaging. Here we present one of the first JWST kinematic measurements for a galaxy at z > 5. We find a significant velocity gradient, which, if interpreted as rotation, yields Vrot = 305 ± 70 km s−1, and we hence refer to this galaxy as Twister-z5. With a rest-frame optical effective radius of re = 2.25 kpc, the high rotation velocity in this galaxy is not due to a compact size, as may be expected in the early Universe, but rather to a high total mass, (math formula). This is a factor of roughly 10× higher than the stellar mass within re. We also observe that the radial Hα equivalent width profile and the specific star formation rate map from resolved stellar population modeling are centrally depressed by a factor of ∼1.5 from the center to re. Combined with the morphology of the line-emitting gas in comparison to the continuum, this centrally suppressed star formation is consistent with a star-forming disk surrounding a bulge growing inside out. While large, rapidly rotating disks are common to z ∼ 2, the existence of one after only 1 Gyr of cosmic time, shown for the first time in ionized gas, adds to the growing evidence that some galaxies matured earlier than expected in the history of the Universe.","lang":"eng"}],"article_processing_charge":"Yes","publication_identifier":{"issn":["2041-8205"],"eissn":["2041-8213"]},"publisher":"IOP Publishing","doi":"10.3847/2041-8213/ad7b17","publication_status":"published","year":"2024","date_published":"2024-12-01T00:00:00Z","citation":{"chicago":"Nelson, Erica, Gabriel Brammer, Clara Giménez-Arteaga, Pascal A. Oesch, Rohan P. Naidu, Hannah Übler, Jasleen Matharu, et al. “Ionized Gas Kinematics with FRESCO: An Extended, Massive, Rapidly Rotating Galaxy at z = 5.4.” Astrophysical Journal Letters. IOP Publishing, 2024. https://doi.org/10.3847/2041-8213/ad7b17.","ama":"Nelson E, Brammer G, Giménez-Arteaga C, et al. Ionized gas kinematics with FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4. Astrophysical Journal Letters. 2024;976(2). doi:10.3847/2041-8213/ad7b17","apa":"Nelson, E., Brammer, G., Giménez-Arteaga, C., Oesch, P. A., Naidu, R. P., Übler, H., … Witstok, J. (2024). Ionized gas kinematics with FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4. Astrophysical Journal Letters. IOP Publishing. https://doi.org/10.3847/2041-8213/ad7b17","short":"E. Nelson, G. Brammer, C. Giménez-Arteaga, P.A. Oesch, R.P. Naidu, H. Übler, J. Matharu, A.E. Shapley, K.E. Whitaker, E. Wisnioski, N.M. Förster Schreiber, R. Smit, P. Van Dokkum, J. Chisholm, R. Endsley, A.I. Hartley, J. Gibson, E. Giovinazzo, G. Illingworth, I. Labbe, M.V. Maseda, J.J. Matthee, A. Covelo Paz, S.H. Price, N.A. Reddy, I. Shivaei, A. Weibel, S. Wuyts, M. Xiao, S. Alberts, W.M. Baker, A.J. Bunker, A.J. Cameron, S. Charlot, D.J. Eisenstein, A. De Graaff, Z. Ji, B.D. Johnson, G.C. Jones, R. Maiolino, B. Robertson, L. Sandles, K.A. Suess, S. Tacchella, C.C. Williams, J. Witstok, Astrophysical Journal Letters 976 (2024).","mla":"Nelson, Erica, et al. “Ionized Gas Kinematics with FRESCO: An Extended, Massive, Rapidly Rotating Galaxy at z = 5.4.” Astrophysical Journal Letters, vol. 976, no. 2, L27, IOP Publishing, 2024, doi:10.3847/2041-8213/ad7b17.","ieee":"E. Nelson et al., “Ionized gas kinematics with FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4,” Astrophysical Journal Letters, vol. 976, no. 2. IOP Publishing, 2024.","ista":"Nelson E, Brammer G, Giménez-Arteaga C, Oesch PA, Naidu RP, Übler H, Matharu J, Shapley AE, Whitaker KE, Wisnioski E, Förster Schreiber NM, Smit R, Van Dokkum P, Chisholm J, Endsley R, Hartley AI, Gibson J, Giovinazzo E, Illingworth G, Labbe I, Maseda MV, Matthee JJ, Covelo Paz A, Price SH, Reddy NA, Shivaei I, Weibel A, Wuyts S, Xiao M, Alberts S, Baker WM, Bunker AJ, Cameron AJ, Charlot S, Eisenstein DJ, De Graaff A, Ji Z, Johnson BD, Jones GC, Maiolino R, Robertson B, Sandles L, Suess KA, Tacchella S, Williams CC, Witstok J. 2024. Ionized gas kinematics with FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4. Astrophysical Journal Letters. 976(2), L27."},"isi":1,"article_number":"L27","title":"Ionized gas kinematics with FRESCO: An extended, massive, rapidly rotating galaxy at z = 5.4","date_updated":"2025-09-09T11:58:02Z","department":[{"_id":"JoMa"}],"month":"12","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"publication":"Astrophysical Journal Letters","language":[{"iso":"eng"}],"has_accepted_license":"1","scopus_import":"1","date_created":"2025-01-05T23:01:58Z","status":"public","intvolume":" 976","ddc":["520"],"file":[{"file_name":"2024_AstrophysicalJour_Nelson.pdf","date_updated":"2025-01-08T08:18:39Z","content_type":"application/pdf","file_id":"18771","creator":"dernst","date_created":"2025-01-08T08:18:39Z","checksum":"5c7320196586b4340e55f215d8737185","success":1,"access_level":"open_access","file_size":1822989,"relation":"main_file"}],"arxiv":1,"DOAJ_listed":"1","_id":"18760","OA_place":"publisher","oa":1,"author":[{"full_name":"Nelson, Erica","last_name":"Nelson","first_name":"Erica"},{"first_name":"Gabriel","last_name":"Brammer","full_name":"Brammer, Gabriel"},{"full_name":"Giménez-Arteaga, Clara","last_name":"Giménez-Arteaga","first_name":"Clara"},{"first_name":"Pascal A.","last_name":"Oesch","full_name":"Oesch, Pascal A."},{"first_name":"Rohan P.","full_name":"Naidu, Rohan P.","last_name":"Naidu"},{"first_name":"Hannah","full_name":"Übler, Hannah","last_name":"Übler"},{"last_name":"Matharu","full_name":"Matharu, Jasleen","first_name":"Jasleen"},{"last_name":"Shapley","full_name":"Shapley, Alice E.","first_name":"Alice E."},{"last_name":"Whitaker","full_name":"Whitaker, Katherine E.","first_name":"Katherine E."},{"last_name":"Wisnioski","full_name":"Wisnioski, Emily","first_name":"Emily"},{"first_name":"Natascha M.","full_name":"Förster Schreiber, Natascha M.","last_name":"Förster Schreiber"},{"last_name":"Smit","full_name":"Smit, Renske","first_name":"Renske"},{"first_name":"Pieter","last_name":"Van Dokkum","full_name":"Van Dokkum, Pieter"},{"last_name":"Chisholm","full_name":"Chisholm, John","first_name":"John"},{"full_name":"Endsley, Ryan","last_name":"Endsley","first_name":"Ryan"},{"first_name":"Abigail I.","full_name":"Hartley, Abigail I.","last_name":"Hartley"},{"first_name":"Justus","last_name":"Gibson","full_name":"Gibson, Justus"},{"first_name":"Emma","full_name":"Giovinazzo, Emma","last_name":"Giovinazzo"},{"first_name":"Garth","full_name":"Illingworth, Garth","last_name":"Illingworth"},{"first_name":"Ivo","last_name":"Labbe","full_name":"Labbe, Ivo"},{"first_name":"Michael V.","full_name":"Maseda, Michael V.","last_name":"Maseda"},{"orcid":"0000-0003-2871-127X","first_name":"Jorryt J","full_name":"Matthee, Jorryt J","id":"7439a258-f3c0-11ec-9501-9df22fe06720","last_name":"Matthee"},{"first_name":"Alba","last_name":"Covelo Paz","full_name":"Covelo Paz, Alba"},{"full_name":"Price, Sedona H.","last_name":"Price","first_name":"Sedona H."},{"first_name":"Naveen A.","last_name":"Reddy","full_name":"Reddy, Naveen A."},{"last_name":"Shivaei","full_name":"Shivaei, Irene","first_name":"Irene"},{"full_name":"Weibel, Andrea","last_name":"Weibel","first_name":"Andrea"},{"full_name":"Wuyts, Stijn","last_name":"Wuyts","first_name":"Stijn"},{"first_name":"Mengyuan","last_name":"Xiao","full_name":"Xiao, Mengyuan"},{"last_name":"Alberts","full_name":"Alberts, Stacey","first_name":"Stacey"},{"first_name":"William M.","last_name":"Baker","full_name":"Baker, William M."},{"first_name":"Andrew J.","full_name":"Bunker, Andrew J.","last_name":"Bunker"},{"first_name":"Alex J.","full_name":"Cameron, Alex J.","last_name":"Cameron"},{"full_name":"Charlot, Stephane","last_name":"Charlot","first_name":"Stephane"},{"first_name":"Daniel J.","full_name":"Eisenstein, Daniel J.","last_name":"Eisenstein"},{"full_name":"De Graaff, Anna","last_name":"De Graaff","first_name":"Anna"},{"full_name":"Ji, Zhiyuan","last_name":"Ji","first_name":"Zhiyuan"},{"last_name":"Johnson","full_name":"Johnson, Benjamin D.","first_name":"Benjamin D."},{"last_name":"Jones","full_name":"Jones, Gareth C.","first_name":"Gareth C."},{"full_name":"Maiolino, Roberto","last_name":"Maiolino","first_name":"Roberto"},{"last_name":"Robertson","full_name":"Robertson, Brant","first_name":"Brant"},{"last_name":"Sandles","full_name":"Sandles, Lester","first_name":"Lester"},{"first_name":"Katherine A.","last_name":"Suess","full_name":"Suess, Katherine A."},{"first_name":"Sandro","full_name":"Tacchella, Sandro","last_name":"Tacchella"},{"full_name":"Williams, Christina C.","last_name":"Williams","first_name":"Christina C."},{"full_name":"Witstok, Joris","last_name":"Witstok","first_name":"Joris"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","acknowledgement":"We thank the reviewer and editorial staff for their excellent feedback and effort—the manuscript is much stronger as a result. Support for this work was provided by NASA through grant JWST-GO-01895 awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS 5-26555. H.Ü. gratefully acknowledges support by the Isaac Newton Trust and by the Kavli Foundation through a Newton-Kavli Junior Fellowship. This work has received funding from the Swiss State Secretariat for Education, Research and Innovation (SERI) under contract No. MB22.00072, as well as from the Swiss National Science Foundation (SNSF) through project grant 200020_207349. The Cosmic Dawn Center (DAWN) is funded by the Danish National Research Foundation under grant No. 140. R.S. acknowledges an STFC Ernest Rutherford Fellowship (ST/S004831/1). R.P.N. acknowledges support for this work provided by NASA through the NASA Hubble Fellowship grant HST-HF2-51515.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS5-26555. M.V.M. acknowledges support from the National Science Foundation via AAG grant 2205519 and the Wisconsin Alumni Research Foundation via grant MSN251397. R.M. also acknowledges funding from a research professorship from the Royal Society. A.J.B., A.J.C., and G.C.J. acknowledge funding from the \"FirstGalaxies\" Advanced Grant from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No. 789056). I.L. acknowledges support by the Australian Research Council through Future Fellowship FT220100798. D.J.E. is supported as a Simons Investigator and by a JWST/NIRCam contract to the University of Arizona, NAS5-02015. R.M., J.W., L.S., and W.B. acknowledge support by the Science and Technology Facilities Council (STFC), the ERC through advanced grant 695671 \"QUENCH,\" and the UKRI Frontier Research grant RISEandFALL. B.E.R. acknowledges support from the NIRCam Science Team contract to the University of Arizona, NAS5-02015. The research of C.C.W. is supported by NOIRLab, which is managed by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. The HST and JWST image mosaics of the FRESCO fields are released at MAST as a High Level Science Product (P. Oesch & D. Magee 2023).","type":"journal_article","issue":"2","file_date_updated":"2025-01-08T08:18:39Z"},{"article_type":"original","abstract":[{"text":"Termites, together with cockroaches, belong to the Blattodea. They possess an XX/XY sex determination system which has evolved from an XX/X0 system present in other Blattodean species, such as cockroaches and wood roaches. Little is currently known about the sex chromosomes of termites, their gene content, or their evolution. We here investigate the X chromosome of multiple termite species and compare them with the X chromosome of cockroaches using genomic and transcriptomic data. We find that the X chromosome of the termite Macrotermes natalensis is large and differentiated showing hall marks of sex chromosome evolution such as dosage compensation, while this does not seem to be the case in the other two termite species investigated here where sex chromosomes may be evolutionary younger. Furthermore, the X chromosome in M. natalensis is different from the X chromosome found in the cockroach Blattella germanica indicating that sex chromosome turn-over events may have happened during termite evolution.","lang":"eng"}],"OA_type":"gold","volume":16,"oa_version":"Published Version","day":"01","project":[{"grant_number":"M02484","call_identifier":"FWF","name":"Sex Determination in Termites","_id":"26641CAC-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","external_id":{"isi":["001380841100001"],"pmid":["39658246"]},"month":"12","department":[{"_id":"BeVi"}],"date_updated":"2025-09-09T11:58:41Z","tmp":{"image":"/images/cc_by_nc.png","legal_code_url":"https://creativecommons.org/licenses/by-nc/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)","short":"CC BY-NC (4.0)"},"license":"https://creativecommons.org/licenses/by-nc/4.0/","isi":1,"article_number":"evae265","title":"Evidence for a novel X chromosome in termites","citation":{"ista":"Fraser R, Moraa R, Djolai A, Meisenheimer N, Laube S, Vicoso B, Huylmans AK. 2024. Evidence for a novel X chromosome in termites. Genome Biology and Evolution. 16(12), evae265.","ieee":"R. Fraser et al., “Evidence for a novel X chromosome in termites,” Genome Biology and Evolution, vol. 16, no. 12. Oxford University Press, 2024.","mla":"Fraser, Roxanne, et al. “Evidence for a Novel X Chromosome in Termites.” Genome Biology and Evolution, vol. 16, no. 12, evae265, Oxford University Press, 2024, doi:10.1093/gbe/evae265.","short":"R. Fraser, R. Moraa, A. Djolai, N. Meisenheimer, S. Laube, B. Vicoso, A.K. Huylmans, Genome Biology and Evolution 16 (2024).","apa":"Fraser, R., Moraa, R., Djolai, A., Meisenheimer, N., Laube, S., Vicoso, B., & Huylmans, A. K. (2024). Evidence for a novel X chromosome in termites. Genome Biology and Evolution. Oxford University Press. https://doi.org/10.1093/gbe/evae265","ama":"Fraser R, Moraa R, Djolai A, et al. Evidence for a novel X chromosome in termites. Genome Biology and Evolution. 2024;16(12). doi:10.1093/gbe/evae265","chicago":"Fraser, Roxanne, Ruth Moraa, Annika Djolai, Nils Meisenheimer, Sophie Laube, Beatriz Vicoso, and Ann K Huylmans. “Evidence for a Novel X Chromosome in Termites.” Genome Biology and Evolution. Oxford University Press, 2024. https://doi.org/10.1093/gbe/evae265."},"date_published":"2024-12-01T00:00:00Z","year":"2024","doi":"10.1093/gbe/evae265","article_processing_charge":"Yes","publisher":"Oxford University Press","publication_identifier":{"eissn":["1759-6653"]},"publication_status":"published","ddc":["570"],"file":[{"checksum":"9cf8fd14580dd694dd810ccca808ad0e","date_created":"2025-01-08T08:28:07Z","file_size":795106,"relation":"main_file","access_level":"open_access","success":1,"content_type":"application/pdf","file_name":"2024_GBE_Fraser.pdf","date_updated":"2025-01-08T08:28:07Z","creator":"dernst","file_id":"18772"}],"intvolume":" 16","pmid":1,"scopus_import":"1","status":"public","date_created":"2025-01-05T23:01:58Z","language":[{"iso":"eng"}],"publication":"Genome Biology and Evolution","acknowledged_ssus":[{"_id":"ScienComp"}],"has_accepted_license":"1","issue":"12","corr_author":"1","file_date_updated":"2025-01-08T08:28:07Z","type":"journal_article","acknowledgement":"urthermore, we thank all lab members and collaborators for feedback on the project. Specifically, Dino McMahon provided R. flavipes males and females, Judith Korb provided C. secundus males and females, gave feedback on the project and discussed questions on termite reproduction, Mireille Vasseur-Cognet provided M. natalensis males and females, Ariana Macon performed the lab work for sequencing and the Vicoso group gave critical feedback on the project. We furthermore thank the HPC group at IST Austria and Christian Meesters at JGU Mainz for their technical support.\r\nThis work was supported by a Österreichischer Wissenschaftsfonds (FWF) grant of the Meitner Programme to A.K.H. (project number M 2484), funding by the Deutsche Forschungsgemeinschaft (DFG) of the Research Training Group GenEvo (project number 407023052) to A.K.H., R.F., and A.D., and funding of the DFG within the Schwerpunktprogramm Gevol to A.K.H. and R.M. (project number 503256468).","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","author":[{"first_name":"Roxanne","last_name":"Fraser","full_name":"Fraser, Roxanne"},{"last_name":"Moraa","full_name":"Moraa, Ruth","first_name":"Ruth"},{"full_name":"Djolai, Annika","last_name":"Djolai","first_name":"Annika"},{"last_name":"Meisenheimer","full_name":"Meisenheimer, Nils","first_name":"Nils"},{"first_name":"Sophie","full_name":"Laube, Sophie","last_name":"Laube"},{"first_name":"Beatriz","orcid":"0000-0002-4579-8306","last_name":"Vicoso","full_name":"Vicoso, Beatriz","id":"49E1C5C6-F248-11E8-B48F-1D18A9856A87"},{"id":"4C0A3874-F248-11E8-B48F-1D18A9856A87","full_name":"Huylmans, Ann K","last_name":"Huylmans","first_name":"Ann K","orcid":"0000-0001-8871-4961"}],"oa":1,"DOAJ_listed":"1","OA_place":"publisher","_id":"18761"},{"abstract":[{"text":"Consider the random variable $\\mathrm{Tr}( f_1(W)A_1\\dots f_k(W)A_k)$ where $W$ is an $N\\times N$ Hermitian Wigner matrix, $k\\in\\mathbb{N}$, and choose (possibly $N$-dependent) regular functions $f_1,\\dots, f_k$ as well as bounded deterministic matrices $A_1,\\dots,A_k$. We give a functional central limit theorem showing that the fluctuations around the expectation are Gaussian. Moreover, we determine the limiting covariance structure and give explicit error bounds in terms of the scaling of $f_1,\\dots,f_k$ and the number of traceless matrices among $A_1,\\dots,A_k$, thus extending the results of [Cipolloni, Erdős, Schröder 2023] to products of arbitrary length $k\\geq2$. As an application, we consider the fluctuation of $\\mathrm{Tr}(\\mathrm{e}^{\\mathrm{i} tW}A_1\\mathrm{e}^{-\\mathrm{i} tW}A_2)$ around its thermal value $\\mathrm{Tr}(A_1)\\mathrm{Tr}(A_2)$ when $t$ is large and give an explicit formula for the variance.","lang":"eng"}],"article_type":"original","OA_type":"gold","oa_version":"Published Version","day":"20","volume":29,"ec_funded":1,"quality_controlled":"1","external_id":{"isi":["001381599200001"],"arxiv":["2307.11028"]},"project":[{"_id":"62796744-2b32-11ec-9570-940b20777f1d","call_identifier":"H2020","name":"Random matrices beyond Wigner-Dyson-Mehta","grant_number":"101020331"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"date_updated":"2025-09-09T11:59:15Z","month":"12","department":[{"_id":"LaEr"}],"title":"Multi-point functional central limit theorem for Wigner matrices","article_number":"191","isi":1,"year":"2024","date_published":"2024-12-20T00:00:00Z","citation":{"ama":"Reker J. Multi-point functional central limit theorem for Wigner matrices. Electronic Journal of Probability. 2024;29. doi:10.1214/24-EJP1247","chicago":"Reker, Jana. “Multi-Point Functional Central Limit Theorem for Wigner Matrices.” Electronic Journal of Probability. Institute of Mathematical Statistics, 2024. https://doi.org/10.1214/24-EJP1247.","short":"J. Reker, Electronic Journal of Probability 29 (2024).","apa":"Reker, J. (2024). Multi-point functional central limit theorem for Wigner matrices. Electronic Journal of Probability. Institute of Mathematical Statistics. https://doi.org/10.1214/24-EJP1247","ieee":"J. Reker, “Multi-point functional central limit theorem for Wigner matrices,” Electronic Journal of Probability, vol. 29. Institute of Mathematical Statistics, 2024.","mla":"Reker, Jana. “Multi-Point Functional Central Limit Theorem for Wigner Matrices.” Electronic Journal of Probability, vol. 29, 191, Institute of Mathematical Statistics, 2024, doi:10.1214/24-EJP1247.","ista":"Reker J. 2024. Multi-point functional central limit theorem for Wigner matrices. Electronic Journal of Probability. 29, 191."},"publication_status":"published","article_processing_charge":"Yes","publication_identifier":{"eissn":["1083-6489"]},"publisher":"Institute of Mathematical Statistics","doi":"10.1214/24-EJP1247","file":[{"file_id":"18773","creator":"dernst","content_type":"application/pdf","file_name":"2024_ElectrJournProbability_Reker.pdf","date_updated":"2025-01-08T08:44:03Z","relation":"main_file","file_size":812428,"success":1,"access_level":"open_access","checksum":"67178feaa8630a332599d3037a3fe70e","date_created":"2025-01-08T08:44:03Z"}],"ddc":["510"],"intvolume":" 29","date_created":"2025-01-05T23:01:58Z","status":"public","scopus_import":"1","has_accepted_license":"1","publication":"Electronic Journal of Probability","language":[{"iso":"eng"}],"file_date_updated":"2025-01-08T08:44:03Z","corr_author":"1","author":[{"full_name":"Reker, Jana","id":"e796e4f9-dc8d-11ea-abe3-97e26a0323e9","last_name":"Reker","first_name":"Jana"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","acknowledgement":"I am very grateful to László Erdős for suggesting the topic and many valuable discussions during my work on the project. I would also like to thank the two anonymous referees for their careful reading of the manuscript and detailed feedback.\r\nPartially supported by ERC Advanced Grants “RMTBeyond” No. 101020331 and “LDRaM” No. 884584.","type":"journal_article","related_material":{"record":[{"status":"public","id":"17173","relation":"earlier_version"}]},"oa":1,"_id":"18762","OA_place":"publisher","DOAJ_listed":"1","arxiv":1},{"ddc":["570"],"file":[{"content_type":"application/pdf","file_name":"2024_eLife_David.pdf","date_updated":"2025-01-08T13:33:05Z","file_id":"18780","creator":"dernst","checksum":"1d64265f62a3bf14550b4f5c684f1782","date_created":"2025-01-08T13:33:05Z","relation":"main_file","file_size":9992462,"success":1,"access_level":"open_access"}],"intvolume":" 12","date_created":"2025-01-08T13:25:45Z","scopus_import":"1","status":"public","language":[{"iso":"eng"}],"publication":"eLife","has_accepted_license":"1","file_date_updated":"2025-01-08T13:33:05Z","type":"journal_article","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Csaba","full_name":"Dávid, Csaba","last_name":"Dávid"},{"last_name":"Giber","full_name":"Giber, Kristóf","first_name":"Kristóf"},{"last_name":"Szigeti","id":"44F4BDC0-F248-11E8-B48F-1D18A9856A87","full_name":"Szigeti, Margit Katalin","orcid":"0000-0001-9500-8758","first_name":"Margit Katalin"},{"full_name":"Köllő, Mihály","last_name":"Köllő","first_name":"Mihály"},{"first_name":"Zoltan","last_name":"Nusser","full_name":"Nusser, Zoltan"},{"last_name":"Acsady","full_name":"Acsady, Laszlo","first_name":"Laszlo"}],"acknowledgement":"This research was supported by the Wellcome Trust (ZN, LA). In addition, LA was supported by an ERC Advanced Grant (FRONTHAL, 742595) and the European Union project RRF-2.3.1-\r\n21-2022-00004 within the framework of the Artificial Intelligence National Laboratory and Lendület_2023_90. ZN is the recipient of a Hungarian Academy of Sciences Momentum Grant (Lendület, LP2012-29) and an ERC Advanced Grant (293681). We thank the Light Microscopy Center at Institute of Experimental Medicine for kindly providing microscopy support. Authors would like to express their deepest gratitude to Prof Luc Anselin (Center for Spatial Data Science, University of Chicago) and Dr Szabolcs Káli (Instiute of Experimental Medicine, Budapest) for the valuable discussion about analysis of spatial association, and to Krisztina Faddi for the excellent technical assistance. ","oa":1,"DOAJ_listed":"1","OA_place":"publisher","_id":"18779","article_type":"original","abstract":[{"text":"Unsupervised segmentation in biological and non-biological images is only partially resolved. Segmentation either requires arbitrary thresholds or large teaching datasets. Here, we propose a spatial autocorrelation method based on Local Moran’s I coefficient to differentiate signal, background, and noise in any type of image. The method, originally described for geoinformatics, does not require a predefined intensity threshold or teaching algorithm for image segmentation and allows quantitative comparison of samples obtained in different conditions. It utilizes relative intensity as well as spatial information of neighboring elements to select spatially contiguous groups of pixels. We demonstrate that Moran’s method outperforms threshold-based method in both artificially generated as well as in natural images especially when background noise is substantial. This superior performance can be attributed to the exclusion of false positive pixels resulting from isolated, high intensity pixels in high noise conditions. To test the method’s power in real situation, we used high power confocal images of the somatosensory thalamus immunostained for Kv4.2 and Kv4.3 (A-type) voltage-gated potassium channels in mice. Moran’s method identified high-intensity Kv4.2 and Kv4.3 ion channel clusters in the thalamic neuropil. Spatial distribution of these clusters displayed strong correlation with large sensory axon terminals of subcortical origin. The unique association of the special presynaptic terminals and a postsynaptic voltage-gated ion channel cluster was confirmed with electron microscopy. These data demonstrate that Moran’s method is a rapid, simple image segmentation method optimal for variable and high noise conditions.","lang":"eng"}],"OA_type":"gold","volume":12,"oa_version":"Published Version","day":"10","quality_controlled":"1","department":[{"_id":"GaNo"}],"month":"12","date_updated":"2025-01-08T13:37:04Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_number":"89361","title":"A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus","citation":{"ieee":"C. Dávid, K. Giber, M. K. Szigeti, M. Köllő, Z. Nusser, and L. Acsady, “A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus,” eLife, vol. 12. eLife Sciences Publications, 2024.","mla":"Dávid, Csaba, et al. “A Novel Image Segmentation Method Based on Spatial Autocorrelation Identifies A-Type Potassium Channel Clusters in the Thalamus.” ELife, vol. 12, 89361, eLife Sciences Publications, 2024, doi:10.7554/elife.89361.","ista":"Dávid C, Giber K, Szigeti MK, Köllő M, Nusser Z, Acsady L. 2024. A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus. eLife. 12, 89361.","ama":"Dávid C, Giber K, Szigeti MK, Köllő M, Nusser Z, Acsady L. A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus. eLife. 2024;12. doi:10.7554/elife.89361","chicago":"Dávid, Csaba, Kristóf Giber, Margit Katalin Szigeti, Mihály Köllő, Zoltan Nusser, and Laszlo Acsady. “A Novel Image Segmentation Method Based on Spatial Autocorrelation Identifies A-Type Potassium Channel Clusters in the Thalamus.” ELife. eLife Sciences Publications, 2024. https://doi.org/10.7554/elife.89361.","short":"C. Dávid, K. Giber, M.K. Szigeti, M. Köllő, Z. Nusser, L. Acsady, ELife 12 (2024).","apa":"Dávid, C., Giber, K., Szigeti, M. K., Köllő, M., Nusser, Z., & Acsady, L. (2024). A novel image segmentation method based on spatial autocorrelation identifies A-type potassium channel clusters in the thalamus. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.89361"},"year":"2024","date_published":"2024-12-10T00:00:00Z","doi":"10.7554/elife.89361","article_processing_charge":"Yes","publisher":"eLife Sciences Publications","publication_identifier":{"issn":["2050-084X"]},"publication_status":"published"},{"status":"public","date_created":"2025-01-14T07:27:26Z","scopus_import":"1","has_accepted_license":"1","language":[{"iso":"eng"}],"publication":"ICML 2024 Workshop AI4Science","file":[{"date_created":"2025-01-27T11:42:24Z","checksum":"beedf05388bbdb7ddda81ec3d5ec7026","success":1,"access_level":"open_access","file_size":4453014,"relation":"main_file","date_updated":"2025-01-27T11:42:24Z","file_name":"2024_ICML_Cadei.pdf","content_type":"application/pdf","file_id":"18896","creator":"dernst"}],"ddc":["000","570"],"intvolume":" 38","oa":1,"related_material":{"link":[{"url":"https://github.com/CausalLearningAI/ISTAnt","relation":"software"}],"record":[{"relation":"research_data","status":"public","id":"18895"},{"relation":"is_continued_by","status":"for_moderation","id":"19509"}]},"OA_place":"publisher","_id":"18847","arxiv":1,"file_date_updated":"2025-01-27T11:42:24Z","corr_author":"1","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","acknowledgement":"We thank Piersilvio De Bartolomeis, and the full Causal Learning and Artificial Intelligence (CLAI) group at ISTA for the extremely helpful discussions. Riccardo Cadei was supported by a Google Research Scholar Award and a Google Initiated Gift to Francesco Locatello. We thank the Social Immunity team at ISTA particularly Michaela Hönigsberger and Wilfrid Jean Louis, for supporting the ecological experiment and Farnaz Beikzadeh Abbasi, Luisa Fiebig and Martin Estermann for annotating ant behavior in ISTAnt.","author":[{"last_name":"Cadei","id":"0fa8b76f-72f0-11ef-b75a-a5da96e5ad6b","full_name":"Cadei, Riccardo","first_name":"Riccardo"},{"first_name":"Lukas","id":"85f0e6d3-06b3-11ec-8982-8c5049fa4455","full_name":"Lindorfer, Lukas","last_name":"Lindorfer"},{"id":"2F64EC8C-F248-11E8-B48F-1D18A9856A87","full_name":"Cremer, Sylvia","last_name":"Cremer","first_name":"Sylvia","orcid":"0000-0002-2193-3868"},{"first_name":"Cordelia","full_name":"Schmid, Cordelia","last_name":"Schmid"},{"orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello","full_name":"Locatello, Francesco","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"}],"volume":38,"oa_version":"Published Version","day":"25","quality_controlled":"1","external_id":{"arxiv":["2405.17151"]},"abstract":[{"text":"Machine Learning and AI have the potential to transform data-driven\r\nscientific discovery, enabling accurate predictions for several scientific\r\nphenomena. As many scientific questions are inherently causal, this paper looks\r\nat the causal inference task of treatment effect estimation, where the outcome\r\nof interest is recorded in high-dimensional observations in a Randomized\r\nControlled Trial (RCT). Despite being the simplest possible causal setting and\r\na perfect fit for deep learning, we theoretically find that many common choices\r\nin the literature may lead to biased estimates. To test the practical impact of\r\nthese considerations, we recorded ISTAnt, the first real-world benchmark for\r\ncausal inference downstream tasks on high-dimensional observations as an RCT\r\nstudying how garden ants (Lasius neglectus) respond to microparticles applied\r\nonto their colony members by hygienic grooming. Comparing 6 480 models\r\nfine-tuned from state-of-the-art visual backbones, we find that the sampling\r\nand modeling choices significantly affect the accuracy of the causal estimate,\r\nand that classification accuracy is not a proxy thereof. We further validated\r\nthe analysis, repeating it on a synthetically generated visual data set\r\ncontrolling the causal model. Our results suggest that future benchmarks should\r\ncarefully consider real downstream scientific questions, especially causal\r\nones. Further, we highlight guidelines for representation learning methods to\r\nhelp answer causal questions in the sciences.","lang":"eng"}],"conference":{"start_date":"2024-07-26","name":"ICML: International Conference on Machine Learning","end_date":"2024-07-26"},"OA_type":"gold","citation":{"ista":"Cadei R, Lindorfer L, Cremer S, Schmid C, Locatello F. 2024. Smoke and mirrors in causal downstream tasks. ICML 2024 Workshop AI4Science. ICML: International Conference on Machine Learning vol. 38.","ieee":"R. Cadei, L. Lindorfer, S. Cremer, C. Schmid, and F. Locatello, “Smoke and mirrors in causal downstream tasks,” in ICML 2024 Workshop AI4Science, 2024, vol. 38.","mla":"Cadei, Riccardo, et al. “Smoke and Mirrors in Causal Downstream Tasks.” ICML 2024 Workshop AI4Science, vol. 38, Curran Associates, 2024.","short":"R. Cadei, L. Lindorfer, S. Cremer, C. Schmid, F. Locatello, in:, ICML 2024 Workshop AI4Science, Curran Associates, 2024.","apa":"Cadei, R., Lindorfer, L., Cremer, S., Schmid, C., & Locatello, F. (2024). Smoke and mirrors in causal downstream tasks. In ICML 2024 Workshop AI4Science (Vol. 38). Curran Associates.","ama":"Cadei R, Lindorfer L, Cremer S, Schmid C, Locatello F. Smoke and mirrors in causal downstream tasks. In: ICML 2024 Workshop AI4Science. Vol 38. Curran Associates; 2024.","chicago":"Cadei, Riccardo, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, and Francesco Locatello. “Smoke and Mirrors in Causal Downstream Tasks.” In ICML 2024 Workshop AI4Science, Vol. 38. Curran Associates, 2024."},"date_published":"2024-09-25T00:00:00Z","year":"2024","publication_status":"published","publisher":"Curran Associates","article_processing_charge":"No","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"month":"09","department":[{"_id":"SyCr"},{"_id":"FrLo"},{"_id":"GradSch"}],"date_updated":"2025-07-10T11:51:50Z","title":"Smoke and mirrors in causal downstream tasks"},{"oa":1,"related_material":{"link":[{"url":"https://github.com/K4TEL/geo-twitter.git","relation":"software"}]},"_id":"18856","OA_place":"publisher","DOAJ_listed":"1","file_date_updated":"2025-01-20T08:41:10Z","corr_author":"1","issue":"29","user_id":"68b8ca59-c5b3-11ee-8790-cd641c68093d","author":[{"first_name":"Kateryna","full_name":"Lutsai, Kateryna","last_name":"Lutsai"},{"orcid":"0000-0001-8622-7887","first_name":"Christoph","full_name":"Lampert, Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert"}],"acknowledgement":"The authors acknowledge the Institute of Science and Technology (ISTA) for their material support and for granting access to the Twitter database archive, which was essential for the research.","type":"journal_article","date_created":"2025-01-19T23:01:53Z","scopus_import":"1","status":"public","has_accepted_license":"1","publication":"Journal of Spatial Information Science","language":[{"iso":"eng"}],"file":[{"access_level":"open_access","success":1,"file_size":7250655,"relation":"main_file","date_created":"2025-01-20T08:41:10Z","checksum":"b82413f00398ffb5168e8e747571a98d","creator":"dernst","file_id":"18857","date_updated":"2025-01-20T08:41:10Z","file_name":"2024_JourSpatialInfoScience_Lutsai.pdf","content_type":"application/pdf"}],"ddc":["500"],"page":"69-99","year":"2024","date_published":"2024-12-26T00:00:00Z","citation":{"ama":"Lutsai K, Lampert C. Predicting the geolocation of tweets using transformer models on customized data. Journal of Spatial Information Science. 2024;(29):69-99. doi:10.5311/JOSIS.2024.29.295","chicago":"Lutsai, Kateryna, and Christoph Lampert. “Predicting the Geolocation of Tweets Using Transformer Models on Customized Data.” Journal of Spatial Information Science. University of Maine, 2024. https://doi.org/10.5311/JOSIS.2024.29.295.","short":"K. Lutsai, C. Lampert, Journal of Spatial Information Science (2024) 69–99.","apa":"Lutsai, K., & Lampert, C. (2024). Predicting the geolocation of tweets using transformer models on customized data. Journal of Spatial Information Science. University of Maine. https://doi.org/10.5311/JOSIS.2024.29.295","ieee":"K. Lutsai and C. Lampert, “Predicting the geolocation of tweets using transformer models on customized data,” Journal of Spatial Information Science, no. 29. University of Maine, pp. 69–99, 2024.","mla":"Lutsai, Kateryna, and Christoph Lampert. “Predicting the Geolocation of Tweets Using Transformer Models on Customized Data.” Journal of Spatial Information Science, no. 29, University of Maine, 2024, pp. 69–99, doi:10.5311/JOSIS.2024.29.295.","ista":"Lutsai K, Lampert C. 2024. Predicting the geolocation of tweets using transformer models on customized data. Journal of Spatial Information Science. (29), 69–99."},"publication_status":"published","publication_identifier":{"eissn":["1948-660X"]},"article_processing_charge":"Yes","publisher":"University of Maine","doi":"10.5311/JOSIS.2024.29.295","license":"https://creativecommons.org/licenses/by/3.0/","tmp":{"name":"Creative Commons Attribution 3.0 Unported (CC BY 3.0)","short":"CC BY (3.0)","legal_code_url":"https://creativecommons.org/licenses/by/3.0/legalcode","image":"/images/cc_by.png"},"date_updated":"2025-06-05T13:47:12Z","month":"12","department":[{"_id":"ChLa"}],"title":"Predicting the geolocation of tweets using transformer models on customized data","day":"26","oa_version":"Published Version","quality_controlled":"1","abstract":[{"text":"This research is aimed to solve the tweet/user geolocation prediction task and provide a flexible methodology for the geo-tagging of textual big data. The suggested approach implements neural networks for natural language processing (NLP) to estimate the location as coordinate pairs (longitude, latitude) and two-dimensional Gaussian Mixture Models (GMMs). The scope of proposed models has been finetuned on a Twitter dataset using pretrained Bidirectional Encoder Representations from Transformers (BERT) as base models. Performance metrics show a median error of fewer than 30 km on a worldwide-level, and fewer than 15 km on the US-level datasets for the models trained and evaluated on text features of tweets' content and metadata context. Our source code and data are available at https://github.com/K4TEL/geo-twitter.git.","lang":"eng"}],"article_type":"original","OA_type":"gold"},{"OA_type":"gold","conference":{"location":"Vancouver, Canada","start_date":"2024-12-16","end_date":"2024-12-16","name":"NeurIPS: Neural Information Processing Systems"},"abstract":[{"lang":"eng","text":"Current state-of-the-art methods for differentially private model training are based on matrix factorization techniques. However, these methods suffer from high computational overhead because they require numerically solving a demanding optimization problem to determine an approximately optimal factorization prior to the actual model training. In this work, we present a new matrix factorization approach, BSR, which overcomes this computational bottleneck. By exploiting properties of the standard matrix square root, BSR allows to efficiently handle also large-scale problems. For the key scenario of stochastic gradient descent with momentum and weight decay, we even derive analytical expressions for BSR that render the computational overhead negligible. We prove bounds on the approximation quality that hold both in the centralized and in the federated learning setting. Our numerical experiments demonstrate that models trained using BSR perform on par with the best existing methods, while completely avoiding their computational overhead."}],"alternative_title":["Advances in Neural Information Processing Systems"],"quality_controlled":"1","external_id":{"arxiv":["2405.13763"]},"day":"01","oa_version":"Published Version","volume":37,"title":"Banded square root matrix factorization for differentially private model training","month":"12","department":[{"_id":"GradSch"},{"_id":"ChLa"}],"date_updated":"2025-05-14T11:34:20Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_processing_charge":"No","publication_identifier":{"eissn":["1049-5258"]},"publisher":"Neural Information Processing Systems Foundation","publication_status":"published","citation":{"ista":"Kalinin N, Lampert C. 2024. Banded square root matrix factorization for differentially private model training. 38th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","mla":"Kalinin, Nikita, and Christoph Lampert. “Banded Square Root Matrix Factorization for Differentially Private Model Training.” 38th Annual Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.","ieee":"N. Kalinin and C. Lampert, “Banded square root matrix factorization for differentially private model training,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.","apa":"Kalinin, N., & Lampert, C. (2024). Banded square root matrix factorization for differentially private model training. In 38th Annual Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","short":"N. Kalinin, C. Lampert, in:, 38th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","chicago":"Kalinin, Nikita, and Christoph Lampert. “Banded Square Root Matrix Factorization for Differentially Private Model Training.” In 38th Annual Conference on Neural Information Processing Systems, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ama":"Kalinin N, Lampert C. Banded square root matrix factorization for differentially private model training. In: 38th Annual Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024."},"date_published":"2024-12-01T00:00:00Z","year":"2024","intvolume":" 37","ddc":["000"],"file":[{"file_name":"2024_NeurIPS_Nikita.pdf","date_updated":"2025-01-27T09:52:15Z","content_type":"application/pdf","file_id":"18888","creator":"dernst","date_created":"2025-01-27T09:52:15Z","checksum":"a216cab8eddc1fe7840aede0e2c0d41e","access_level":"open_access","success":1,"file_size":1144656,"relation":"main_file"}],"language":[{"iso":"eng"}],"publication":"38th Annual Conference on Neural Information Processing Systems","has_accepted_license":"1","status":"public","scopus_import":"1","date_created":"2025-01-24T17:58:16Z","type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Nikita","full_name":"Kalinin, Nikita","id":"4b14526e-14d2-11ed-ba64-c14c9553d137","last_name":"Kalinin"},{"id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","full_name":"Lampert, Christoph","last_name":"Lampert","first_name":"Christoph","orcid":"0000-0001-8622-7887"}],"corr_author":"1","file_date_updated":"2025-01-27T09:52:15Z","arxiv":1,"OA_place":"publisher","_id":"18875","oa":1},{"volume":37,"oa_version":"Preprint","day":"01","alternative_title":["Advances in Neural Information Processing Systems"],"project":[{"_id":"059876FA-7A3F-11EA-A408-12923DDC885E","name":"Prix Lopez-Loretta 2019 - Marco Mondelli"}],"quality_controlled":"1","external_id":{"arxiv":["2402.13728"]},"main_file_link":[{"url":"https://openreview.net/forum?id=lJ1jdl2K9k","open_access":"1"}],"abstract":[{"lang":"eng","text":"Deep Neural Collapse (DNC) refers to the surprisingly rigid structure of the data representations in the final layers of Deep Neural Networks (DNNs). Though the phenomenon has been measured in a variety of settings, its emergence is typically explained via data-agnostic approaches, such as the unconstrained features model. In this work, we introduce a data-dependent setting where DNC forms due to feature learning through the average gradient outer product (AGOP). The AGOP is defined with respect to a learned predictor and is equal to the uncentered covariance matrix of its input-output gradients averaged over the training dataset. The Deep Recursive Feature Machine (Deep RFM) is a method that constructs a neural network by iteratively mapping the data with the AGOP and applying an untrained random feature map. We demonstrate empirically that DNC occurs in Deep RFM across standard settings as a consequence of the projection with the AGOP matrix computed at each layer. Further, we theoretically explain DNC in Deep RFM in an asymptotic setting and as a result of kernel learning. We then provide evidence that this mechanism holds for neural networks more generally. In particular, we show that the right singular vectors and values of the weights can be responsible for the majority of within-class variability collapse for DNNs trained in the feature learning regime. As observed in recent work, this singular structure is highly correlated with that of the AGOP."}],"OA_type":"green","conference":{"start_date":"2024-12-16","location":"Vancouver, Canada","end_date":"2024-12-16","name":"NeurIPS: Neural Information Processing Systems"},"citation":{"mla":"Beaglehole, Daniel, et al. “Average Gradient Outer Product as a Mechanism for Deep Neural Collapse.” 38th Annual Conference on Neural Information Processing Systems, vol. 37, Neural Information Processing Systems Foundation, 2024.","ieee":"D. Beaglehole, P. Súkeník, M. Mondelli, and M. Belkin, “Average gradient outer product as a mechanism for deep neural collapse,” in 38th Annual Conference on Neural Information Processing Systems, Vancouver, Canada, 2024, vol. 37.","ista":"Beaglehole D, Súkeník P, Mondelli M, Belkin M. 2024. Average gradient outer product as a mechanism for deep neural collapse. 38th Annual Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","chicago":"Beaglehole, Daniel, Peter Súkeník, Marco Mondelli, and Mikhail Belkin. “Average Gradient Outer Product as a Mechanism for Deep Neural Collapse.” In 38th Annual Conference on Neural Information Processing Systems, Vol. 37. Neural Information Processing Systems Foundation, 2024.","ama":"Beaglehole D, Súkeník P, Mondelli M, Belkin M. Average gradient outer product as a mechanism for deep neural collapse. In: 38th Annual Conference on Neural Information Processing Systems. Vol 37. Neural Information Processing Systems Foundation; 2024.","apa":"Beaglehole, D., Súkeník, P., Mondelli, M., & Belkin, M. (2024). Average gradient outer product as a mechanism for deep neural collapse. In 38th Annual Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","short":"D. Beaglehole, P. Súkeník, M. Mondelli, M. Belkin, in:, 38th Annual Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024."},"year":"2024","date_published":"2024-12-01T00:00:00Z","publisher":"Neural Information Processing Systems Foundation","article_processing_charge":"No","publication_identifier":{"eissn":["1049-5258"]},"publication_status":"published","department":[{"_id":"GradSch"},{"_id":"MaMo"}],"month":"12","date_updated":"2025-05-14T11:29:45Z","title":"Average gradient outer product as a mechanism for deep neural collapse","date_created":"2025-01-27T11:11:40Z","scopus_import":"1","status":"public","language":[{"iso":"eng"}],"publication":"38th Annual Conference on Neural Information Processing Systems","intvolume":" 37","oa":1,"arxiv":1,"OA_place":"repository","_id":"18890","corr_author":"1","type":"conference","author":[{"last_name":"Beaglehole","full_name":"Beaglehole, Daniel","first_name":"Daniel"},{"id":"d64d6a8d-eb8e-11eb-b029-96fd216dec3c","full_name":"Súkeník, Peter","last_name":"Súkeník","first_name":"Peter"},{"last_name":"Mondelli","id":"27EB676C-8706-11E9-9510-7717E6697425","full_name":"Mondelli, Marco","first_name":"Marco","orcid":"0000-0002-3242-7020"},{"first_name":"Mikhail","full_name":"Belkin, Mikhail","last_name":"Belkin"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","acknowledgement":"We acknowledge support from the National Science Foundation (NSF) and the Simons Foundation for the Collaboration on the Theoretical Foundations of Deep Learning through awards DMS-2031883 and #814639 as well as the TILOS institute (NSF CCF-2112665). This work used the programs (1) XSEDE (Extreme science and engineering discovery environment) which is supported by NSF grant numbers ACI-1548562, and (2) ACCESS (Advanced cyberinfrastructure coordination ecosystem: services & support) which is supported by NSF grants numbers #2138259, #2138286, #2138307, #2137603, and #2138296. Specifically, we used the resources from SDSC Expanse GPU compute nodes, and NCSA Delta system, via allocations TG-CIS220009. Marco Mondelli is supported by the 2019 Lopez-Loreta prize. We also acknowledge useful feedback from anonymous reviewers. "}]