--- _id: '12919' abstract: - lang: eng text: We report the visible light photocatalytic cleavage of trityl thioethers or ethers under pH-neutral conditions. The method results in the formation of the respective symmetrical disulfides and alcohols in moderate to excellent yield. The protocol only requires the addition of a suitable photocatalyst and light rendering it orthogonal to several functionalities, including acid labile protective groups. The same conditions can be used to directly convert trityl-protected thiols into unsymmetrical disulfides or selenosulfides, and to cleave trityl resins in solid phase organic synthesis. article_processing_charge: No article_type: original author: - first_name: Sho full_name: Murakami, Sho last_name: Murakami - first_name: Cosima full_name: Brudy, Cosima last_name: Brudy - first_name: Moritz full_name: Bachmann, Moritz last_name: Bachmann - first_name: Yoshiji full_name: Takemoto, Yoshiji last_name: Takemoto - first_name: Bartholomäus full_name: Pieber, Bartholomäus id: 93e5e5b2-0da6-11ed-8a41-af589a024726 last_name: Pieber orcid: 0000-0001-8689-388X citation: ama: Murakami S, Brudy C, Bachmann M, Takemoto Y, Pieber B. Photocatalytic cleavage of trityl protected thiols and alcohols. Synthesis. 2023;55(09):1367-1374. doi:10.1055/a-1979-5933 apa: Murakami, S., Brudy, C., Bachmann, M., Takemoto, Y., & Pieber, B. (2023). Photocatalytic cleavage of trityl protected thiols and alcohols. Synthesis. Georg Thieme Verlag. https://doi.org/10.1055/a-1979-5933 chicago: Murakami, Sho, Cosima Brudy, Moritz Bachmann, Yoshiji Takemoto, and Bartholomäus Pieber. “Photocatalytic Cleavage of Trityl Protected Thiols and Alcohols.” Synthesis. Georg Thieme Verlag, 2023. https://doi.org/10.1055/a-1979-5933. ieee: S. Murakami, C. Brudy, M. Bachmann, Y. Takemoto, and B. Pieber, “Photocatalytic cleavage of trityl protected thiols and alcohols,” Synthesis, vol. 55, no. 09. Georg Thieme Verlag, pp. 1367–1374, 2023. ista: Murakami S, Brudy C, Bachmann M, Takemoto Y, Pieber B. 2023. Photocatalytic cleavage of trityl protected thiols and alcohols. Synthesis. 55(09), 1367–1374. mla: Murakami, Sho, et al. “Photocatalytic Cleavage of Trityl Protected Thiols and Alcohols.” Synthesis, vol. 55, no. 09, Georg Thieme Verlag, 2023, pp. 1367–74, doi:10.1055/a-1979-5933. short: S. Murakami, C. Brudy, M. Bachmann, Y. Takemoto, B. Pieber, Synthesis 55 (2023) 1367–1374. date_created: 2023-05-08T08:25:08Z date_published: 2023-05-01T00:00:00Z date_updated: 2023-05-15T08:43:50Z day: '01' doi: 10.1055/a-1979-5933 extern: '1' intvolume: ' 55' issue: '09' keyword: - Organic Chemistry - Catalysis language: - iso: eng month: '05' oa_version: None page: 1367-1374 publication: Synthesis publication_identifier: eissn: - 1437-210X issn: - 0039-7881 publication_status: published publisher: Georg Thieme Verlag quality_controlled: '1' scopus_import: '1' status: public title: Photocatalytic cleavage of trityl protected thiols and alcohols type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 55 year: '2023' ... --- _id: '13048' abstract: - lang: eng text: In this paper we introduce a pruning of the medial axis called the (λ,α)-medial axis (axλα). We prove that the (λ,α)-medial axis of a set K is stable in a Gromov-Hausdorff sense under weak assumptions. More formally we prove that if K and K′ are close in the Hausdorff (dH) sense then the (λ,α)-medial axes of K and K′ are close as metric spaces, that is the Gromov-Hausdorff distance (dGH) between the two is 1/4-Hölder in the sense that dGH (axλα(K),axλα(K′)) ≲ dH(K,K′)1/4. The Hausdorff distance between the two medial axes is also bounded, by dH (axλα(K),λα(K′)) ≲ dH(K,K′)1/2. These quantified stability results provide guarantees for practical computations of medial axes from approximations. Moreover, they provide key ingredients for studying the computability of the medial axis in the context of computable analysis. acknowledgement: "We are greatly indebted to Erin Chambers for posing a number of questions that eventually led to this paper. We would also like to thank the other organizers of the workshop on ‘Algorithms\r\nfor the medial axis’. We are also indebted to Tatiana Ezubova for helping with the search for and translation of Russian literature. The second author thanks all members of the Edelsbrunner and Datashape groups for the atmosphere in which the research was conducted.\r\nThe research leading to these results has received funding from the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement No. 339025 GUDHI (Algorithmic Foundations of Geometry Understanding in Higher Dimensions). Supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754411. The Austrian science fund (FWF) M-3073." article_processing_charge: No author: - first_name: André full_name: Lieutier, André last_name: Lieutier - first_name: Mathijs full_name: Wintraecken, Mathijs id: 307CFBC8-F248-11E8-B48F-1D18A9856A87 last_name: Wintraecken orcid: 0000-0002-7472-2220 citation: ama: 'Lieutier A, Wintraecken M. Hausdorff and Gromov-Hausdorff stable subsets of the medial axis. In: Proceedings of the 55th Annual ACM Symposium on Theory of Computing. Association for Computing Machinery; 2023:1768-1776. doi:10.1145/3564246.3585113' apa: 'Lieutier, A., & Wintraecken, M. (2023). Hausdorff and Gromov-Hausdorff stable subsets of the medial axis. In Proceedings of the 55th Annual ACM Symposium on Theory of Computing (pp. 1768–1776). Orlando, FL, United States: Association for Computing Machinery. https://doi.org/10.1145/3564246.3585113' chicago: Lieutier, André, and Mathijs Wintraecken. “Hausdorff and Gromov-Hausdorff Stable Subsets of the Medial Axis.” In Proceedings of the 55th Annual ACM Symposium on Theory of Computing, 1768–76. Association for Computing Machinery, 2023. https://doi.org/10.1145/3564246.3585113. ieee: A. Lieutier and M. Wintraecken, “Hausdorff and Gromov-Hausdorff stable subsets of the medial axis,” in Proceedings of the 55th Annual ACM Symposium on Theory of Computing, Orlando, FL, United States, 2023, pp. 1768–1776. ista: 'Lieutier A, Wintraecken M. 2023. Hausdorff and Gromov-Hausdorff stable subsets of the medial axis. Proceedings of the 55th Annual ACM Symposium on Theory of Computing. STOC: Symposium on Theory of Computing, 1768–1776.' mla: Lieutier, André, and Mathijs Wintraecken. “Hausdorff and Gromov-Hausdorff Stable Subsets of the Medial Axis.” Proceedings of the 55th Annual ACM Symposium on Theory of Computing, Association for Computing Machinery, 2023, pp. 1768–76, doi:10.1145/3564246.3585113. short: A. Lieutier, M. Wintraecken, in:, Proceedings of the 55th Annual ACM Symposium on Theory of Computing, Association for Computing Machinery, 2023, pp. 1768–1776. conference: end_date: 2023-06-23 location: Orlando, FL, United States name: 'STOC: Symposium on Theory of Computing' start_date: 2023-06-20 date_created: 2023-05-22T08:02:02Z date_published: 2023-06-02T00:00:00Z date_updated: 2023-05-22T08:15:19Z day: '02' department: - _id: HeEd doi: 10.1145/3564246.3585113 ec_funded: 1 external_id: arxiv: - '2303.04014' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2303.04014 month: '06' oa: 1 oa_version: Preprint page: 1768-1776 project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships - _id: fc390959-9c52-11eb-aca3-afa58bd282b2 grant_number: M03073 name: Learning and triangulating manifolds via collapses publication: Proceedings of the 55th Annual ACM Symposium on Theory of Computing publication_identifier: isbn: - '9781450399135' publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' status: public title: Hausdorff and Gromov-Hausdorff stable subsets of the medial axis type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '13053' abstract: - lang: eng text: 'Deep neural networks (DNNs) often have to be compressed, via pruning and/or quantization, before they can be deployed in practical settings. In this work we propose a new compression-aware minimizer dubbed CrAM that modifies the optimization step in a principled way, in order to produce models whose local loss behavior is stable under compression operations such as pruning. Thus, dense models trained via CrAM should be compressible post-training, in a single step, without significant accuracy loss. Experimental results on standard benchmarks, such as residual networks for ImageNet classification and BERT models for language modelling, show that CrAM produces dense models that can be more accurate than the standard SGD/Adam-based baselines, but which are stable under weight pruning: specifically, we can prune models in one-shot to 70-80% sparsity with almost no accuracy loss, and to 90% with reasonable (∼1%) accuracy loss, which is competitive with gradual compression methods. Additionally, CrAM can produce sparse models which perform well for transfer learning, and it also works for semi-structured 2:4 pruning patterns supported by GPU hardware. The code for reproducing the results is available at this https URL .' acknowledged_ssus: - _id: ScienComp acknowledgement: "AP, EK, DA received funding from the European Research Council (ERC) under the European\r\nUnion’s Horizon 2020 research and innovation programme (grant agreement No 805223 ScaleML). AV acknowledges the support of the French Agence Nationale de la Recherche (ANR), under grant ANR-21-CE48-0016 (project COMCOPT). We further acknowledge the support from the Scientific Service Units (SSU) of ISTA through resources provided by Scientific Computing (SciComp)-" article_processing_charge: No author: - first_name: Elena-Alexandra full_name: Peste, Elena-Alexandra id: 32D78294-F248-11E8-B48F-1D18A9856A87 last_name: Peste - first_name: Adrian full_name: Vladu, Adrian last_name: Vladu - first_name: Eldar full_name: Kurtic, Eldar id: 47beb3a5-07b5-11eb-9b87-b108ec578218 last_name: Kurtic - first_name: Christoph full_name: Lampert, Christoph id: 40C20FD2-F248-11E8-B48F-1D18A9856A87 last_name: Lampert orcid: 0000-0001-8622-7887 - first_name: Dan-Adrian full_name: Alistarh, Dan-Adrian id: 4A899BFC-F248-11E8-B48F-1D18A9856A87 last_name: Alistarh orcid: 0000-0003-3650-940X citation: ama: 'Peste E-A, Vladu A, Kurtic E, Lampert C, Alistarh D-A. CrAM: A Compression-Aware Minimizer. In: 11th International Conference on Learning Representations .' apa: 'Peste, E.-A., Vladu, A., Kurtic, E., Lampert, C., & Alistarh, D.-A. (n.d.). CrAM: A Compression-Aware Minimizer. In 11th International Conference on Learning Representations . Kigali, Rwanda .' chicago: 'Peste, Elena-Alexandra, Adrian Vladu, Eldar Kurtic, Christoph Lampert, and Dan-Adrian Alistarh. “CrAM: A Compression-Aware Minimizer.” In 11th International Conference on Learning Representations , n.d.' ieee: 'E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, and D.-A. Alistarh, “CrAM: A Compression-Aware Minimizer,” in 11th International Conference on Learning Representations , Kigali, Rwanda .' ista: 'Peste E-A, Vladu A, Kurtic E, Lampert C, Alistarh D-A. CrAM: A Compression-Aware Minimizer. 11th International Conference on Learning Representations . ICLR: International Conference on Learning Representations.' mla: 'Peste, Elena-Alexandra, et al. “CrAM: A Compression-Aware Minimizer.” 11th International Conference on Learning Representations .' short: E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International Conference on Learning Representations , n.d. conference: end_date: 2023-05-05 location: 'Kigali, Rwanda ' name: 'ICLR: International Conference on Learning Representations' start_date: 2023-05-01 date_created: 2023-05-23T11:36:18Z date_published: 2023-05-01T00:00:00Z date_updated: 2023-06-01T12:54:45Z department: - _id: GradSch - _id: DaAl - _id: ChLa ec_funded: 1 external_id: arxiv: - '2207.14200' language: - iso: eng main_file_link: - open_access: '1' url: https://openreview.net/pdf?id=_eTZBs-yedr month: '05' oa: 1 oa_version: Preprint project: - _id: 268A44D6-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '805223' name: Elastic Coordination for Scalable Machine Learning publication: '11th International Conference on Learning Representations ' publication_status: accepted quality_controlled: '1' related_material: record: - id: '13074' relation: dissertation_contains status: public status: public title: 'CrAM: A Compression-Aware Minimizer' type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '13143' abstract: - lang: eng text: "GIMPS and PrimeGrid are large-scale distributed projects dedicated to searching giant prime numbers, usually of special forms like Mersenne and Proth primes. The numbers in the current search-space are millions of digits large and the participating volunteers need to run resource-consuming primality tests. Once a candidate prime N has been found, the only way for another party to independently verify the primality of N used to be by repeating the expensive primality test. To avoid the need for second recomputation of each primality test, these projects have recently adopted certifying mechanisms that enable efficient verification of performed tests. However, the mechanisms presently in place only detect benign errors and there is no guarantee against adversarial behavior: a malicious volunteer can mislead the project to reject a giant prime as being non-prime.\r\nIn this paper, we propose a practical, cryptographically-sound mechanism for certifying the non-primality of Proth numbers. That is, a volunteer can – parallel to running the primality test for N – generate an efficiently verifiable proof at a little extra cost certifying that N is not prime. The interactive protocol has statistical soundness and can be made non-interactive using the Fiat-Shamir heuristic.\r\nOur approach is based on a cryptographic primitive called Proof of Exponentiation (PoE) which, for a group G, certifies that a tuple (x,y,T)∈G2×N satisfies x2T=y (Pietrzak, ITCS 2019 and Wesolowski, J. Cryptol. 2020). In particular, we show how to adapt Pietrzak’s PoE at a moderate additional cost to make it a cryptographically-sound certificate of non-primality." acknowledgement: 'We are grateful to Pavel Atnashev for clarifying via e-mail several aspects of the primality tests implementated in the PrimeGrid project. Pavel Hubáček is supported by the Czech Academy of Sciences (RVO 67985840), the Grant Agency of the Czech Republic under the grant agreement no. 19-27871X, and by the Charles University project UNCE/SCI/004. Chethan Kamath is supported by Azrieli International Postdoctoral Fellowship, ISF grants 484/18 and 1789/19, and ERC StG project SPP: Secrecy Preserving Proofs.' alternative_title: - LNCS article_processing_charge: No author: - first_name: Charlotte full_name: Hoffmann, Charlotte id: 0f78d746-dc7d-11ea-9b2f-83f92091afe7 last_name: Hoffmann - first_name: Pavel full_name: Hubáček, Pavel last_name: Hubáček - first_name: Chethan full_name: Kamath, Chethan last_name: Kamath - first_name: Krzysztof Z full_name: Pietrzak, Krzysztof Z id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87 last_name: Pietrzak orcid: 0000-0002-9139-1654 citation: ama: 'Hoffmann C, Hubáček P, Kamath C, Pietrzak KZ. Certifying giant nonprimes. In: Public-Key Cryptography - PKC 2023. Vol 13940. Springer Nature; 2023:530-553. doi:10.1007/978-3-031-31368-4_19' apa: 'Hoffmann, C., Hubáček, P., Kamath, C., & Pietrzak, K. Z. (2023). Certifying giant nonprimes. In Public-Key Cryptography - PKC 2023 (Vol. 13940, pp. 530–553). Atlanta, GA, United States: Springer Nature. https://doi.org/10.1007/978-3-031-31368-4_19' chicago: Hoffmann, Charlotte, Pavel Hubáček, Chethan Kamath, and Krzysztof Z Pietrzak. “Certifying Giant Nonprimes.” In Public-Key Cryptography - PKC 2023, 13940:530–53. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-31368-4_19. ieee: C. Hoffmann, P. Hubáček, C. Kamath, and K. Z. Pietrzak, “Certifying giant nonprimes,” in Public-Key Cryptography - PKC 2023, Atlanta, GA, United States, 2023, vol. 13940, pp. 530–553. ista: 'Hoffmann C, Hubáček P, Kamath C, Pietrzak KZ. 2023. Certifying giant nonprimes. Public-Key Cryptography - PKC 2023. PKC: Public-Key Cryptography, LNCS, vol. 13940, 530–553.' mla: Hoffmann, Charlotte, et al. “Certifying Giant Nonprimes.” Public-Key Cryptography - PKC 2023, vol. 13940, Springer Nature, 2023, pp. 530–53, doi:10.1007/978-3-031-31368-4_19. short: C. Hoffmann, P. Hubáček, C. Kamath, K.Z. Pietrzak, in:, Public-Key Cryptography - PKC 2023, Springer Nature, 2023, pp. 530–553. conference: end_date: 2023-05-10 location: Atlanta, GA, United States name: 'PKC: Public-Key Cryptography' start_date: 2023-05-07 date_created: 2023-06-18T22:00:47Z date_published: 2023-05-02T00:00:00Z date_updated: 2023-06-19T08:03:37Z day: '02' department: - _id: KrPi doi: 10.1007/978-3-031-31368-4_19 intvolume: ' 13940' language: - iso: eng main_file_link: - open_access: '1' url: https://eprint.iacr.org/2023/238 month: '05' oa: 1 oa_version: Submitted Version page: 530-553 publication: Public-Key Cryptography - PKC 2023 publication_identifier: eissn: - 1611-3349 isbn: - '9783031313677' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Certifying giant nonprimes type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13940 year: '2023' ... --- _id: '13142' abstract: - lang: eng text: Reinforcement learning has received much attention for learning controllers of deterministic systems. We consider a learner-verifier framework for stochastic control systems and survey recent methods that formally guarantee a conjunction of reachability and safety properties. Given a property and a lower bound on the probability of the property being satisfied, our framework jointly learns a control policy and a formal certificate to ensure the satisfaction of the property with a desired probability threshold. Both the control policy and the formal certificate are continuous functions from states to reals, which are learned as parameterized neural networks. While in the deterministic case, the certificates are invariant and barrier functions for safety, or Lyapunov and ranking functions for liveness, in the stochastic case the certificates are supermartingales. For certificate verification, we use interval arithmetic abstract interpretation to bound the expected values of neural network functions. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. alternative_title: - LNCS article_processing_charge: No author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic citation: ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework for neural network controllers and certificates of stochastic systems. In: Tools and Algorithms for the Construction and Analysis of Systems . Vol 13993. Springer Nature; 2023:3-25. doi:10.1007/978-3-031-30823-9_1' apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). A learner-verifier framework for neural network controllers and certificates of stochastic systems. In Tools and Algorithms for the Construction and Analysis of Systems (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_1' chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1. ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier framework for neural network controllers and certificates of stochastic systems,” in Tools and Algorithms for the Construction and Analysis of Systems , Paris, France, 2023, vol. 13993, pp. 3–25. ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier framework for neural network controllers and certificates of stochastic systems. Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993, 3–25.' mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network Controllers and Certificates of Stochastic Systems.” Tools and Algorithms for the Construction and Analysis of Systems , vol. 13993, Springer Nature, 2023, pp. 3–25, doi:10.1007/978-3-031-30823-9_1. short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25. conference: end_date: 2023-04-27 location: Paris, France name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems' start_date: 2023-04-22 date_created: 2023-06-18T22:00:47Z date_published: 2023-04-22T00:00:00Z date_updated: 2023-06-19T08:30:54Z day: '22' ddc: - '000' department: - _id: KrCh - _id: ToHe doi: 10.1007/978-3-031-30823-9_1 ec_funded: 1 file: - access_level: open_access checksum: 3d8a8bb24d211bc83360dfc2fd744307 content_type: application/pdf creator: dernst date_created: 2023-06-19T08:29:30Z date_updated: 2023-06-19T08:29:30Z file_id: '13150' file_name: 2023_LNCS_Chatterjee.pdf file_size: 528455 relation: main_file success: 1 file_date_updated: 2023-06-19T08:29:30Z has_accepted_license: '1' intvolume: ' 13993' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '04' oa: 1 oa_version: Published Version page: 3-25 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: 'Tools and Algorithms for the Construction and Analysis of Systems ' publication_identifier: eissn: - 1611-3349 isbn: - '9783031308222' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: A learner-verifier framework for neural network controllers and certificates of stochastic systems tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13993 year: '2023' ...