[{"language":[{"iso":"eng"}],"quality_controlled":"1","intvolume":"        43","publication_identifier":{"issn":["0730-0301"],"eissn":["1557-7368"]},"has_accepted_license":"1","OA_place":"publisher","date_updated":"2026-04-07T13:02:36Z","corr_author":"1","external_id":{"isi":["001289270900021"]},"file_date_updated":"2025-11-11T09:50:52Z","date_created":"2024-07-10T12:24:00Z","department":[{"_id":"GradSch"},{"_id":"ChWo"}],"article_number":"54","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","short":"CC BY-NC-SA (4.0)","image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)"},"citation":{"short":"P. Synak, A. Kalinov, I.-M. Strugaru, A. Etemadi, H. Yang, C. Wojtan, ACM Transactions on Graphics 43 (2024).","ieee":"P. Synak, A. Kalinov, I.-M. Strugaru, A. Etemadi, H. Yang, and C. Wojtan, “Multi-material mesh-based surface tracking with implicit topology changes,” <i>ACM Transactions on Graphics</i>, vol. 43, no. 4. Association for Computing Machinery, 2024.","ista":"Synak P, Kalinov A, Strugaru I-M, Etemadi A, Yang H, Wojtan C. 2024. Multi-material mesh-based surface tracking with implicit topology changes. ACM Transactions on Graphics. 43(4), 54.","apa":"Synak, P., Kalinov, A., Strugaru, I.-M., Etemadi, A., Yang, H., &#38; Wojtan, C. (2024). Multi-material mesh-based surface tracking with implicit topology changes. <i>ACM Transactions on Graphics</i>. Association for Computing Machinery. <a href=\"https://doi.org/10.1145/3658223\">https://doi.org/10.1145/3658223</a>","mla":"Synak, Peter, et al. “Multi-Material Mesh-Based Surface Tracking with Implicit Topology Changes.” <i>ACM Transactions on Graphics</i>, vol. 43, no. 4, 54, Association for Computing Machinery, 2024, doi:<a href=\"https://doi.org/10.1145/3658223\">10.1145/3658223</a>.","ama":"Synak P, Kalinov A, Strugaru I-M, Etemadi A, Yang H, Wojtan C. Multi-material mesh-based surface tracking with implicit topology changes. <i>ACM Transactions on Graphics</i>. 2024;43(4). doi:<a href=\"https://doi.org/10.1145/3658223\">10.1145/3658223</a>","chicago":"Synak, Peter, Aleksei Kalinov, Irina-Malina Strugaru, Arian Etemadi, Huidong Yang, and Chris Wojtan. “Multi-Material Mesh-Based Surface Tracking with Implicit Topology Changes.” <i>ACM Transactions on Graphics</i>. Association for Computing Machinery, 2024. <a href=\"https://doi.org/10.1145/3658223\">https://doi.org/10.1145/3658223</a>."},"volume":43,"doi":"10.1145/3658223","day":"01","publisher":"Association for Computing Machinery","type":"journal_article","related_material":{"record":[{"relation":"dissertation_contains","id":"19630","status":"public"},{"id":"18301","relation":"dissertation_contains","status":"public"}]},"publication":"ACM Transactions on Graphics","date_published":"2024-07-01T00:00:00Z","scopus_import":"1","abstract":[{"lang":"eng","text":"We introduce a multi-material non-manifold mesh-based surface tracking algorithm that converts self-intersections into topological changes. Our algorithm generalizes prior work on manifold surface tracking with topological changes: it preserves surface features like mesh-based methods, and it robustly handles topological changes like level set methods. Our method also offers improved efficiency and robustness over the state of the art. We demonstrate the effectiveness of the approach on a range of examples, including complex soap film simulations with thousands of interacting bubbles, and boolean unions of non-manifold meshes consisting of millions of triangles."}],"status":"public","OA_type":"hybrid","ddc":["004"],"acknowledgement":"Peter Heiss-Synak helped conceive the project, helped formulate the algorithm structure, contributed ideas and code to Sections 6 & 8, the mesh data structure, algorithm robustness and benchmarks, helped write the paper, and provided supervision and conceptual solutions throughout the project. Aleksei Kalinov contributed ideas and code to Sections 7, 8.5, and 5, the sparse grid data structure, algorithm robustness and benchmarks, optimized the performance, produced all results, most figures, and the supplementary video, helped write the text, and provided conceptual solutions throughout the project. Malina Strugaru helped implement the mesh data structure and designed re-meshing operations for non-manifold triangle meshes. Arian Etemadi developed early prototypes for ideas in Sections 8.1 and 8.3 and helped write the paper. Huidong Yang developed early prototypes for isosurface extraction and visualization. Chris Wojtan helped conceive the project, helped write the paper, and provided supervision, prototype grid data structure code, and conceptual solutions throughout the project. We thank the anonymous reviewers for their helpful comments, the members of the Visual Computing Group at ISTA for their feedback, Christopher Batty for discussions about LosTopos, and SideFX for the Houdini Education software licenses.  This research was funded in part by the European Union (ERC-2021-COG 101045083 CoDiNA).","article_type":"original","publication_status":"published","project":[{"name":"Computational Discovery of Numerical Algorithms for Animation and Simulation of Natural Phenomena","grant_number":"101045083","_id":"34bc2376-11ca-11ed-8bc3-9a3b3961a088"}],"license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","author":[{"last_name":"Synak","first_name":"Peter","full_name":"Synak, Peter","id":"331776E2-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Kalinov, Aleksei","id":"44b7120e-eb97-11eb-a6c2-e1557aa81d02","first_name":"Aleksei","orcid":"0000-0003-2189-3904","last_name":"Kalinov"},{"last_name":"Strugaru","id":"2afc607f-f128-11eb-9611-8f2a0dfcf074","full_name":"Strugaru, Irina-Malina","first_name":"Irina-Malina"},{"id":"36cea3aa-f38e-11ec-8ae0-c65ae6f6098f","full_name":"Etemadihaghighi, Arian","first_name":"Arian","last_name":"Etemadihaghighi"},{"last_name":"Yang","full_name":"Yang, Huidong","first_name":"Huidong"},{"id":"3C61F1D2-F248-11E8-B48F-1D18A9856A87","full_name":"Wojtan, Christopher J","first_name":"Christopher J","orcid":"0000-0001-6646-5546","last_name":"Wojtan"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","isi":1,"file":[{"checksum":"1917067d4b52d7729019b03560004e43","success":1,"date_updated":"2024-07-23T06:35:15Z","file_name":"2024_ACMToG_HeissSynak.pdf","access_level":"open_access","creator":"dernst","date_created":"2024-07-23T06:35:15Z","content_type":"application/pdf","file_size":48763368,"relation":"main_file","file_id":"17317"},{"file_name":"sdtopofixer_final.mp4","date_updated":"2024-07-10T12:23:44Z","checksum":"a4f0e293184bfa034c0c585848806b17","success":1,"file_size":48021463,"relation":"main_file","file_id":"17221","date_created":"2024-07-10T12:23:44Z","creator":"akalinov","access_level":"open_access","content_type":"video/mp4"},{"content_type":"application/pdf","creator":"akalinov","date_created":"2025-11-11T09:50:52Z","access_level":"open_access","file_id":"20633","relation":"preprint","file_size":48639581,"checksum":"18fc310a78ec91651148c45a8b89fa44","title":"Authors' version of the text","file_name":"SuperDuperTopoFixer.pdf","date_updated":"2025-11-11T09:50:52Z"}],"oa":1,"_id":"17219","issue":"4","year":"2024","oa_version":"Published Version","keyword":["surface tracking","topology change","non- manifold meshes","multi-material flows","solid modeling"],"title":"Multi-material mesh-based surface tracking with implicit topology changes","article_processing_charge":"Yes (via OA deal)","month":"07"},{"citation":{"ista":"Etemadi A. 2024. Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking. Institute of Science and Technology Austria.","apa":"Etemadi, A. (2024). <i>Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:18301\">https://doi.org/10.15479/at:ista:18301</a>","mla":"Etemadi, Arian. <i>Filling the Holes of Non-Manifold Self-Intersecting Meshes for Implicit Topology Changes in Surface Tracking</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:18301\">10.15479/at:ista:18301</a>.","ieee":"A. Etemadi, “Filling the holes of non-manifold self-intersecting meshes for implicit topology changes in surface tracking,” Institute of Science and Technology Austria, 2024.","short":"A. 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The method in this thesis contributed to Heiss-Synak* and Kalinov* et al. [2024] who devised a non-manifold hybrid surface tracker—a surface tracker that repairs explicit non-manifold triangle meshes with the help of the implicit domain. Specifically, this thesis provides an algorithm for filling the holes that are left after removing problematic parts of the mesh."}],"date_published":"2024-10-15T00:00:00Z","status":"public","ddc":["000"],"degree_awarded":"MS","publication_status":"published","author":[{"last_name":"Etemadihaghighi","first_name":"Arian","full_name":"Etemadihaghighi, Arian","id":"36cea3aa-f38e-11ec-8ae0-c65ae6f6098f"}],"license":"https://creativecommons.org/licenses/by-sa/4.0/","file":[{"checksum":"80fb7923e229ad9d39253d7c8a8083d0","success":1,"date_updated":"2024-10-24T14:34:42Z","file_name":"thesis-arian-etemadi.pdf","access_level":"open_access","creator":"aetemadi","date_created":"2024-10-24T14:34:42Z","content_type":"application/pdf","relation":"main_file","file_size":8914218,"file_id":"18469"},{"date_updated":"2024-10-24T14:34:54Z","file_name":"thesis-arian-etemadi-latex-source.zip","checksum":"1c02586ed7d441d5ec441867650568d1","file_size":9802650,"relation":"source_file","file_id":"18470","access_level":"closed","creator":"aetemadi","date_created":"2024-10-24T14:34:54Z","content_type":"application/x-zip-compressed"}],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","oa":1},{"alternative_title":["ISTA Master's Thesis"],"article_processing_charge":"No","month":"08","oa_version":"Published Version","_id":"17368","year":"2024","keyword":["Epigenetics","Multi-omics","Bayesian regression"],"title":"Bayesian linear regression for analyzing general omics data with time-to-event phenotypes","author":[{"last_name":"Villanueva Marijuan","first_name":"Ariadna","id":"e0ae4864-133f-11ed-8f02-adaa8dd27540","full_name":"Villanueva Marijuan, Ariadna"}],"publication_status":"published","oa":1,"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","file":[{"embargo":"2025-02-14","date_updated":"2025-02-14T23:30:03Z","file_name":"Masters_thesis_AriadnaVillanueva.pdf","checksum":"0c2daa174609f0c00919dccc5701d375","file_id":"17433","file_size":13052436,"relation":"main_file","content_type":"application/pdf","access_level":"open_access","date_created":"2024-08-14T11:51:24Z","creator":"avillanu"},{"file_id":"17434","file_size":45642547,"relation":"source_file","content_type":"application/zip","creator":"avillanu","date_created":"2024-08-14T11:51:57Z","access_level":"closed","embargo_to":"open_access","file_name":"Masters thesis-AriadnaVillanueva.zip","date_updated":"2025-02-14T23:30:03Z","checksum":"e9ed4465dfa539ac4c3a8d4d0b6271a1"}],"status":"public","abstract":[{"lang":"eng","text":"Recent advancements in molecular diagnostic techniques have enabled the collection of\r\nmultiple types of omics data from patients, including genomics, epigenomics, proteomics,\r\nand transcriptomics. However, we lack effective methods for integrating all these different\r\ndata types and combining them with clinical outcomes to study the molecular mechanisms\r\nthat govern pathological phenotypes. We present multi-omics BayesW, a penalized Bayesian\r\nregression method that can handle general omics data for survival analysis of time-to-event\r\nphenotypes. Our method can: (1) accommodate incomplete data by allowing censored\r\nindividuals, (2) use continuous time-to-event data to test associations of markers with a\r\nphenotype and (3) estimate effects jointly while allowing for independent groups of biological\r\nmarkers. Extensive simulations using planted signals on real data demonstrate that our model\r\naccurately retrieves the true parameters of the model while controlling for false discoveries\r\nand maintaining the expected prediction accuracy. We address data correlations by estimating\r\nthe effects jointly, even between omic groups, while also estimating the individual variance\r\nexplained by each group. We apply our model to two datasets. Using 18,000 individuals from\r\nthe Generation Scotland study we model the association of time at onset of Type 2 Diabetes,\r\nStroke, Ischemic Disease, and Osteoarthritis from baseline study entry, with 831,724 CpG\r\nmethylation probes. We find that large proportions of variation in disease onset times can\r\nbe attributed to methylation as measured in whole blood at baseline in individuals without\r\ndisease symptoms. We then apply our model to The Cancer Genome Atlas (TCGA) pan-cancer\r\ndataset, in which we use 5 types of omics: copy number variation, epigenetics, somatic\r\nmutations, miRNA, and gene expression. For cancer survival age-at-onset we find that, when\r\nfitting the 5 groups together, almost all variation attributable to \"omics\" data is explained by\r\nDNA methylation. When considering progression times, both methylation and gene expression\r\nexplain a large part of the variance. We found 2 genes that are significantly associated (95%\r\nposterior inclusion probability) with cancer survival time, conditional on all other genome-wide\r\nomics data variation. Owing to the vast variability of mechanisms characterizing different\r\ncancers, there are likely few specific genes with a strong signal in a pan-cancer setting. Taken\r\ntogether, we showed the applicability of our multi-omics BayesW model to a wide-range of\r\nbiological questions in multi-omics data.\r\n"}],"date_published":"2024-08-13T00:00:00Z","degree_awarded":"MS","ddc":["610"],"citation":{"chicago":"Villanueva Marijuan, Ariadna. “Bayesian Linear Regression for Analyzing General Omics Data with Time-to-Event Phenotypes.” Institute of Science and Technology Austria, 2024. <a href=\"https://doi.org/10.15479/at:ista:17368\">https://doi.org/10.15479/at:ista:17368</a>.","ama":"Villanueva Marijuan A. Bayesian linear regression for analyzing general omics data with time-to-event phenotypes. 2024. doi:<a href=\"https://doi.org/10.15479/at:ista:17368\">10.15479/at:ista:17368</a>","ieee":"A. Villanueva Marijuan, “Bayesian linear regression for analyzing general omics data with time-to-event phenotypes,” Institute of Science and Technology Austria, 2024.","apa":"Villanueva Marijuan, A. (2024). <i>Bayesian linear regression for analyzing general omics data with time-to-event phenotypes</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:17368\">https://doi.org/10.15479/at:ista:17368</a>","mla":"Villanueva Marijuan, Ariadna. <i>Bayesian Linear Regression for Analyzing General Omics Data with Time-to-Event Phenotypes</i>. Institute of Science and Technology Austria, 2024, doi:<a href=\"https://doi.org/10.15479/at:ista:17368\">10.15479/at:ista:17368</a>.","ista":"Villanueva Marijuan A. 2024. Bayesian linear regression for analyzing general omics data with time-to-event phenotypes. Institute of Science and Technology Austria.","short":"A. Villanueva Marijuan, Bayesian Linear Regression for Analyzing General Omics Data with Time-to-Event Phenotypes, Institute of Science and Technology Austria, 2024."},"type":"dissertation","doi":"10.15479/at:ista:17368","day":"13","publisher":"Institute of Science and Technology Austria","page":"60","department":[{"_id":"GradSch"},{"_id":"MaRo"}],"file_date_updated":"2025-02-14T23:30:03Z","date_created":"2024-08-02T10:52:40Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","short":"CC BY-NC-SA (4.0)","image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)"},"publication_identifier":{"issn":["2791-4585"]},"language":[{"iso":"eng"}],"corr_author":"1","supervisor":[{"last_name":"Robinson","orcid":"0000-0001-8982-8813","id":"E5D42276-F5DA-11E9-8E24-6303E6697425","full_name":"Robinson, Matthew Richard","first_name":"Matthew Richard"}],"has_accepted_license":"1","OA_place":"publisher","date_updated":"2026-04-07T13:03:41Z"},{"ddc":["004"],"acknowledgement":"This work is graciously supported by FWF Lise Meitner (Grant M 3319). Kang Liao sincerely thank Emiliano Luci, Chunyu Lin, and Yao Zhao for their huge support.","conference":{"location":"London, United Kingdom","end_date":"2023-06-02","name":"ICRA: International Conference on Robotics and Automation","start_date":"2023-05-29"},"status":"public","scopus_import":"1","date_published":"2023-07-04T00:00:00Z","abstract":[{"text":"3D printing based on continuous deposition of materials, such as filament-based 3D printing, has seen widespread adoption thanks to its versatility in working with a wide range of materials. An important shortcoming of this type of technology is its limited multi-material capabilities. While there are simple hardware designs that enable multi-material printing in principle, the required software is heavily underdeveloped. A typical hardware design fuses together individual materials fed into a single chamber from multiple inlets before they are deposited. This design, however, introduces a time delay between the intended material mixture and its actual deposition. In this work, inspired by diverse path planning research in robotics, we show that this mechanical challenge can be addressed via improved printer control. We propose to formulate the search for optimal multi-material printing policies in a reinforcement\r\nlearning setup. We put forward a simple numerical deposition model that takes into account the non-linear material mixing and delayed material deposition. To validate our system we focus on color fabrication, a problem known for its strict requirements for varying material mixtures at a high spatial frequency. We demonstrate that our learned control policy outperforms state-of-the-art hand-crafted algorithms.","lang":"eng"}],"oa":1,"isi":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"success":1,"checksum":"daeaa67124777d88487f933ea3f77164","file_name":"Liao2023.pdf","date_updated":"2023-05-16T09:12:05Z","content_type":"application/pdf","date_created":"2023-05-16T09:12:05Z","creator":"mpiovarc","access_level":"open_access","file_id":"12977","file_size":5367986,"relation":"main_file"}],"author":[{"last_name":"Liao","first_name":"Kang","full_name":"Liao, Kang"},{"first_name":"Thibault","full_name":"Tricard, Thibault","last_name":"Tricard"},{"last_name":"Piovarci","orcid":"0000-0002-5062-4474","first_name":"Michael","full_name":"Piovarci, Michael","id":"62E473F4-5C99-11EA-A40E-AF823DDC885E"},{"full_name":"Seidel, Hans-Peter","first_name":"Hans-Peter","last_name":"Seidel"},{"last_name":"Babaei","full_name":"Babaei, Vahid","first_name":"Vahid"}],"publication_status":"published","project":[{"_id":"eb901961-77a9-11ec-83b8-f5c883a62027","grant_number":"M03319","name":"Perception-Aware Appearance Fabrication"}],"keyword":["reinforcement learning","deposition","control","color","multi-filament"],"title":"Learning deposition policies for fused multi-material 3D printing","oa_version":"Submitted Version","_id":"12976","year":"2023","month":"07","article_processing_charge":"No","external_id":{"isi":["001048371104068"]},"has_accepted_license":"1","date_updated":"2025-04-15T07:43:52Z","publication_identifier":{"eisbn":["9798350323658"],"issn":["1050-4729"]},"quality_controlled":"1","language":[{"iso":"eng"}],"intvolume":"      2023","department":[{"_id":"BeBi"}],"date_created":"2023-05-16T09:14:09Z","file_date_updated":"2023-05-16T09:12:05Z","type":"conference","publisher":"IEEE","day":"04","doi":"10.1109/ICRA48891.2023.10160465","page":"12345-12352","volume":2023,"citation":{"short":"K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, V. Babaei, in:, 2023 IEEE International Conference on Robotics and Automation, IEEE, 2023, pp. 12345–12352.","ieee":"K. Liao, T. Tricard, M. Piovarci, H.-P. Seidel, and V. Babaei, “Learning deposition policies for fused multi-material 3D printing,” in <i>2023 IEEE International Conference on Robotics and Automation</i>, London, United Kingdom, 2023, vol. 2023, pp. 12345–12352.","mla":"Liao, Kang, et al. “Learning Deposition Policies for Fused Multi-Material 3D Printing.” <i>2023 IEEE International Conference on Robotics and Automation</i>, vol. 2023, IEEE, 2023, pp. 12345–52, doi:<a href=\"https://doi.org/10.1109/ICRA48891.2023.10160465\">10.1109/ICRA48891.2023.10160465</a>.","apa":"Liao, K., Tricard, T., Piovarci, M., Seidel, H.-P., &#38; Babaei, V. (2023). Learning deposition policies for fused multi-material 3D printing. In <i>2023 IEEE International Conference on Robotics and Automation</i> (Vol. 2023, pp. 12345–12352). London, United Kingdom: IEEE. <a href=\"https://doi.org/10.1109/ICRA48891.2023.10160465\">https://doi.org/10.1109/ICRA48891.2023.10160465</a>","ista":"Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. 2023. Learning deposition policies for fused multi-material 3D printing. 2023 IEEE International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation vol. 2023, 12345–12352.","ama":"Liao K, Tricard T, Piovarci M, Seidel H-P, Babaei V. Learning deposition policies for fused multi-material 3D printing. In: <i>2023 IEEE International Conference on Robotics and Automation</i>. Vol 2023. IEEE; 2023:12345-12352. doi:<a href=\"https://doi.org/10.1109/ICRA48891.2023.10160465\">10.1109/ICRA48891.2023.10160465</a>","chicago":"Liao, Kang, Thibault Tricard, Michael Piovarci, Hans-Peter Seidel, and Vahid Babaei. “Learning Deposition Policies for Fused Multi-Material 3D Printing.” In <i>2023 IEEE International Conference on Robotics and Automation</i>, 2023:12345–52. IEEE, 2023. <a href=\"https://doi.org/10.1109/ICRA48891.2023.10160465\">https://doi.org/10.1109/ICRA48891.2023.10160465</a>."},"publication":"2023 IEEE International Conference on Robotics and Automation"},{"date_created":"2019-05-13T08:58:35Z","file_date_updated":"2021-02-11T11:17:15Z","department":[{"_id":"SyCr"}],"acknowledged_ssus":[{"_id":"Bio"},{"_id":"ScienComp"},{"_id":"M-Shop"},{"_id":"LifeSc"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2663-337X"]},"date_updated":"2026-04-08T14:02:12Z","OA_place":"publisher","has_accepted_license":"1","supervisor":[{"orcid":"0000-0002-2193-3868","last_name":"Cremer","full_name":"Cremer, Sylvia M","id":"2F64EC8C-F248-11E8-B48F-1D18A9856A87","first_name":"Sylvia M"}],"corr_author":"1","citation":{"ama":"Casillas Perez BE. Collective defenses of garden ants against a fungal pathogen. 2019. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:6435\">10.15479/AT:ISTA:6435</a>","chicago":"Casillas Perez, Barbara E. “Collective Defenses of Garden Ants against a Fungal Pathogen.” Institute of Science and Technology Austria, 2019. <a href=\"https://doi.org/10.15479/AT:ISTA:6435\">https://doi.org/10.15479/AT:ISTA:6435</a>.","short":"B.E. Casillas Perez, Collective Defenses of Garden Ants against a Fungal Pathogen, Institute of Science and Technology Austria, 2019.","ieee":"B. E. Casillas Perez, “Collective defenses of garden ants against a fungal pathogen,” Institute of Science and Technology Austria, 2019.","mla":"Casillas Perez, Barbara E. <i>Collective Defenses of Garden Ants against a Fungal Pathogen</i>. Institute of Science and Technology Austria, 2019, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:6435\">10.15479/AT:ISTA:6435</a>.","apa":"Casillas Perez, B. E. (2019). <i>Collective defenses of garden ants against a fungal pathogen</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:6435\">https://doi.org/10.15479/AT:ISTA:6435</a>","ista":"Casillas Perez BE. 2019. Collective defenses of garden ants against a fungal pathogen. Institute of Science and Technology Austria."},"page":"183","publisher":"Institute of Science and Technology Austria","day":"07","doi":"10.15479/AT:ISTA:6435","related_material":{"record":[{"id":"1999","relation":"part_of_dissertation","status":"public"}]},"type":"dissertation","ec_funded":1,"project":[{"_id":"2649B4DE-B435-11E9-9278-68D0E5697425","grant_number":"771402","name":"Epidemics in ant societies on a chip","call_identifier":"H2020"}],"publication_status":"published","author":[{"last_name":"Casillas Perez","first_name":"Barbara E","id":"351ED2AA-F248-11E8-B48F-1D18A9856A87","full_name":"Casillas Perez, Barbara E"}],"file":[{"embargo":"2020-05-08","file_name":"tesisDoctoradoBC.pdf","date_updated":"2021-02-11T11:17:15Z","checksum":"6daf2d2086111aa8fd3fbc919a3e2833","file_id":"6438","file_size":3895187,"relation":"main_file","content_type":"application/pdf","date_created":"2019-05-13T09:16:20Z","creator":"casillas","access_level":"open_access"},{"relation":"source_file","file_size":7365118,"file_id":"6439","access_level":"closed","date_created":"2019-05-13T09:16:20Z","creator":"casillas","content_type":"application/zip","date_updated":"2020-07-14T12:47:30Z","file_name":"tesisDoctoradoBC.zip","embargo_to":"open_access","checksum":"3d221aaff7559a7060230a1ff610594f"}],"user_id":"ba8df636-2132-11f1-aed0-ed93e2281fdd","oa":1,"date_published":"2019-05-07T00:00:00Z","abstract":[{"lang":"eng","text":"Social insect colonies tend to have numerous members which function together like a single organism in such harmony that the term ``super-organism'' is often used. In this analogy the reproductive caste is analogous to the primordial germ\r\ncells of a metazoan, while the sterile worker caste corresponds to somatic cells. The worker castes, like tissues, are\r\nin charge of all functions of a living being, besides reproduction. The establishment of new super-organismal units\r\n(i.e. new colonies) is accomplished by the co-dependent castes. The term oftentimes goes beyond a metaphor. We invoke it when we speak about the metabolic rate, thermoregulation, nutrient regulation and gas exchange of a social insect colony. Furthermore, we assert that the super-organism has an immune system, and benefits from ``social immunity''.\r\n\r\nSocial immunity was first summoned by evolutionary biologists to resolve the apparent discrepancy between the expected high frequency of disease outbreak amongst numerous, closely related tightly-interacting hosts, living in stable and microbially-rich environments, against the exceptionally scarce epidemic accounts in natural populations. Social\r\nimmunity comprises a multi-layer assembly of behaviours which have evolved to effectively keep the pathogenic enemies of a colony at bay. The field of social immunity has drawn interest, as it becomes increasingly urgent to stop\r\nthe collapse of pollinator species and curb the growth of invasive pests. In the past decade, several mechanisms of\r\nsocial immune responses have been dissected, but many more questions remain open.\r\n\r\nI present my work in two experimental chapters. In the first, I use invasive garden ants (*Lasius neglectus*) to study how pathogen load and its distribution among nestmates affect the grooming response of the group. Any given group of ants will carry out the same total grooming work, but will direct their grooming effort towards individuals\r\ncarrying a relatively higher spore load. Contrary to expectation, the highest risk of transmission does not stem from grooming highly contaminated ants, but instead, we suggest that the grooming response likely minimizes spore loss to the environment, reducing contamination from inadvertent pickup from the substrate.\r\n\r\nThe second is a comparative developmental approach. I follow black garden ant queens (*Lasius niger*) and their colonies from mating flight, through hibernation for a year. Colonies which grow fast from the start, have a lower chance of survival through hibernation, and those which survive grow at a lower pace later. This is true for colonies of naive\r\nand challenged queens. Early pathogen exposure of the queens changes colony dynamics in an unexpected way: colonies from exposed queens are more likely to grow slowly and recover in numbers only after they survive hibernation.\r\n\r\nIn addition to the two experimental chapters, this thesis includes a co-authored published review on organisational\r\nimmunity, where we enlist the experimental evidence and theoretical framework on which this hypothesis is built,\r\nidentify the caveats and underline how the field is ripe to overcome them. In a final chapter, I describe my part in\r\ntwo collaborative efforts, one to develop an image-based tracker, and the second to develop a classifier for ant\r\nbehaviour."}],"status":"public","ddc":["570","006","578","592"],"degree_awarded":"PhD","alternative_title":["ISTA Thesis"],"article_processing_charge":"No","month":"05","year":"2019","_id":"6435","oa_version":"Published Version","title":"Collective defenses of garden ants against a fungal pathogen","keyword":["Social Immunity","Sanitary care","Social Insects","Organisational Immunity","Colony development","Multi-target tracking"]},{"file_date_updated":"2020-07-14T12:47:03Z","date_created":"2018-12-12T12:31:32Z","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"Bio"}],"license":"https://creativecommons.org/publicdomain/zero/1.0/","datarep_id":"53","author":[{"full_name":"Bergmiller, Tobias","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","last_name":"Bergmiller","orcid":"0000-0001-5396-4346"},{"full_name":"Andersson, Anna M","id":"2B8A40DA-F248-11E8-B48F-1D18A9856A87","first_name":"Anna M","last_name":"Andersson","orcid":"0000-0003-2912-6769"},{"orcid":"0000-0003-3768-877X","last_name":"Tomasek","first_name":"Kathrin","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87","full_name":"Tomasek, Kathrin"},{"last_name":"Balleza","full_name":"Balleza, Enrique","first_name":"Enrique"},{"first_name":"Daniel","full_name":"Kiviet, Daniel","last_name":"Kiviet"},{"last_name":"Hauschild","orcid":"0000-0001-9843-3522","first_name":"Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","full_name":"Hauschild, Robert"},{"full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gasper","orcid":"0000-0002-6699-1455","last_name":"Tkacik"},{"first_name":"Calin C","full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","orcid":"0000-0001-6220-2052"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"checksum":"d77859af757ac8025c50c7b12b52eaf3","file_name":"IST-2017-53-v1+1_Data_MDE.zip","date_updated":"2020-07-14T12:47:03Z","content_type":"application/zip","date_created":"2018-12-12T13:02:38Z","creator":"system","access_level":"open_access","file_id":"5603","file_size":6773204,"relation":"main_file"}],"tmp":{"image":"/images/cc_0.png","name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"},"oa":1,"abstract":[{"lang":"eng","text":"This repository contains the data collected for the manuscript \"Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity\".\r\nThe data is compressed into a single archive. Within the archive, different folders correspond to figures of the main text and the SI of the related publication.\r\nData is saved as plain text, with each folder containing a separate readme file describing the format. Typically, the data is from fluorescence microscopy measurements of single cells growing in a microfluidic \"mother machine\" device, and consists of relevant values (primarily arbitrary unit or normalized fluorescence measurements, and division times / growth rates) after raw microscopy images have been processed, segmented, and their features extracted, as described in the methods section of the related publication."}],"date_published":"2017-03-10T00:00:00Z","status":"public","has_accepted_license":"1","date_updated":"2025-09-11T07:05:03Z","ddc":["571"],"article_processing_charge":"No","month":"03","citation":{"ama":"Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. 2017. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:53\">10.15479/AT:ISTA:53</a>","chicago":"Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza, Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity.” Institute of Science and Technology Austria, 2017. <a href=\"https://doi.org/10.15479/AT:ISTA:53\">https://doi.org/10.15479/AT:ISTA:53</a>.","short":"T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild, G. Tkačik, C.C. Guet, (2017).","mla":"Bergmiller, Tobias, et al. <i>Biased Partitioning of the Multi-Drug Efflux Pump AcrAB-TolC Underlies Long-Lived Phenotypic Heterogeneity</i>. Institute of Science and Technology Austria, 2017, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:53\">10.15479/AT:ISTA:53</a>.","apa":"Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild, R., … Guet, C. C. (2017). Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:53\">https://doi.org/10.15479/AT:ISTA:53</a>","ista":"Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik G, Guet CC. 2017. Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:53\">10.15479/AT:ISTA:53</a>.","ieee":"T. Bergmiller <i>et al.</i>, “Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity.” Institute of Science and Technology Austria, 2017."},"_id":"5560","year":"2017","oa_version":"Published Version","day":"10","doi":"10.15479/AT:ISTA:53","publisher":"Institute of Science and Technology Austria","type":"research_data","keyword":["single cell microscopy","mother machine microfluidic device","AcrAB-TolC pump","multi-drug efflux","Escherichia coli"],"title":"Biased partitioning of the multi-drug efflux pump AcrAB-TolC underlies long-lived phenotypic heterogeneity","related_material":{"record":[{"status":"public","relation":"research_paper","id":"665"}]}},{"month":"02","article_processing_charge":"No","type":"research_data","keyword":["multi-electrode recording","retinal ganglion cells"],"related_material":{"record":[{"id":"2257","relation":"used_in_publication","status":"public"}]},"title":"Multi-electrode array recording from salamander retinal ganglion cells","day":"27","doi":"10.15479/AT:ISTA:61","publisher":"Institute of Science and Technology Austria","oa_version":"Published Version","citation":{"chicago":"Marre, Olivier, Gašper Tkačik, Dario Amodei, Elad Schneidman, William Bialek, and Michael Berry. “Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells.” Institute of Science and Technology Austria, 2017. <a href=\"https://doi.org/10.15479/AT:ISTA:61\">https://doi.org/10.15479/AT:ISTA:61</a>.","ama":"Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. Multi-electrode array recording from salamander retinal ganglion cells. 2017. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:61\">10.15479/AT:ISTA:61</a>","apa":"Marre, O., Tkačik, G., Amodei, D., Schneidman, E., Bialek, W., &#38; Berry, M. (2017). Multi-electrode array recording from salamander retinal ganglion cells. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:61\">https://doi.org/10.15479/AT:ISTA:61</a>","ista":"Marre O, Tkačik G, Amodei D, Schneidman E, Bialek W, Berry M. 2017. Multi-electrode array recording from salamander retinal ganglion cells, Institute of Science and Technology Austria, <a href=\"https://doi.org/10.15479/AT:ISTA:61\">10.15479/AT:ISTA:61</a>.","mla":"Marre, Olivier, et al. <i>Multi-Electrode Array Recording from Salamander Retinal Ganglion Cells</i>. Institute of Science and Technology Austria, 2017, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:61\">10.15479/AT:ISTA:61</a>.","ieee":"O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, and M. Berry, “Multi-electrode array recording from salamander retinal ganglion cells.” Institute of Science and Technology Austria, 2017.","short":"O. Marre, G. Tkačik, D. Amodei, E. Schneidman, W. Bialek, M. Berry, (2017)."},"_id":"5562","year":"2017","oa":1,"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","tmp":{"image":"/images/cc_0.png","name":"Creative Commons Public Domain Dedication (CC0 1.0)","short":"CC0 (1.0)","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode"},"file":[{"checksum":"e620eff260646f57b479a69492c8b765","date_updated":"2020-07-14T12:47:03Z","file_name":"IST-2017-61-v1+1_bint_fishmovie32_100.mat","content_type":"application/octet-stream","access_level":"open_access","date_created":"2018-12-12T13:03:04Z","creator":"system","file_id":"5622","relation":"main_file","file_size":1336936},{"relation":"main_file","file_size":1897543,"file_id":"5623","date_created":"2018-12-12T13:03:05Z","creator":"system","access_level":"open_access","content_type":"application/zip","file_name":"IST-2017-61-v1+2_bint_fishmovie32_100.zip","date_updated":"2020-07-14T12:47:03Z","checksum":"de83f9b81ea0aae3cddfc3ed982e0759"}],"department":[{"_id":"GaTk"}],"author":[{"full_name":"Marre, Olivier","first_name":"Olivier","last_name":"Marre"},{"orcid":"0000-0002-6699-1455","last_name":"Tkacik","first_name":"Gasper","full_name":"Tkacik, Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Amodei","first_name":"Dario","full_name":"Amodei, Dario"},{"last_name":"Schneidman","first_name":"Elad","full_name":"Schneidman, Elad"},{"full_name":"Bialek, William","first_name":"William","last_name":"Bialek"},{"full_name":"Berry, Michael","first_name":"Michael","last_name":"Berry"}],"datarep_id":"61","date_created":"2018-12-12T12:31:33Z","file_date_updated":"2020-07-14T12:47:03Z","ddc":["570"],"has_accepted_license":"1","date_updated":"2025-09-29T11:14:05Z","status":"public","date_published":"2017-02-27T00:00:00Z","abstract":[{"text":"This data was collected as part of the study [1]. It consists of preprocessed multi-electrode array recording from 160 salamander retinal ganglion cells responding to 297 repeats of a 19 s natural movie. The data is available in two formats: (1) a .mat file containing an array with dimensions “number of repeats” x “number of neurons” x “time in a repeat”; (2) a zipped .txt file containing the same data represented as an array with dimensions “number of neurons” x “number of samples”, where the number of samples is equal to the product of the number of repeats and timebins within a repeat. The time dimension is divided into 20 ms time windows, and the array is binary indicating whether a given cell elicited at least one spike in a given time window during a particular repeat. See the reference below for details regarding collection and preprocessing:\r\n\r\n[1] Tkačik G, Marre O, Amodei D, Schneidman E, Bialek W, Berry MJ II. Searching for Collective Behavior in a Large Network of Sensory Neurons. PLoS Comput Biol. 2014;10(1):e1003408.","lang":"eng"}]}]