[{"month":"12","publication_identifier":{"eissn":["2329-0501"]},"isi":1,"quality_controlled":"1","project":[{"name":"Microglia action towards neuronal circuit formation and function in health and disease","call_identifier":"H2020","grant_number":"715571","_id":"25D4A630-B435-11E9-9278-68D0E5697425"}],"external_id":{"isi":["000748748500019"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"acknowledged_ssus":[{"_id":"Bio"},{"_id":"LifeSc"},{"_id":"PreCl"}],"language":[{"iso":"eng"}],"doi":"10.1016/j.omtm.2021.09.006","license":"https://creativecommons.org/licenses/by/4.0/","file_date_updated":"2022-01-24T07:43:09Z","ec_funded":1,"publication_status":"published","department":[{"_id":"SaSi"},{"_id":"SiHi"}],"publisher":"Elsevier","acknowledgement":"This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 715571). The research was supported by the Scientific Service Units (SSU) of IST Austria through resources provided by the Bioimaging Facility, the Life Science Facility, and the Pre-Clinical Facility, namely Sonja Haslinger and Michael Schunn for their animal colony management and support. We would also like to thank Chakrabarty Lab for sharing the plasmids for AAV2/6 production. Finally, we would like to thank the Siegert team members for discussion about the manuscript.","year":"2021","date_updated":"2023-11-16T13:12:03Z","date_created":"2022-01-23T23:01:28Z","volume":23,"author":[{"last_name":"Maes","first_name":"Margaret E","orcid":"0000-0001-9642-1085","id":"3838F452-F248-11E8-B48F-1D18A9856A87","full_name":"Maes, Margaret E"},{"last_name":"Wögenstein","first_name":"Gabriele M.","full_name":"Wögenstein, Gabriele M."},{"first_name":"Gloria","last_name":"Colombo","id":"3483CF6C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9434-8902","full_name":"Colombo, Gloria"},{"full_name":"Casado Polanco, Raquel","id":"15240fc1-dbcd-11ea-9d1d-ac5a786425fd","orcid":"0000-0001-8293-4568","first_name":"Raquel","last_name":"Casado Polanco"},{"full_name":"Siegert, Sandra","first_name":"Sandra","last_name":"Siegert","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8635-0877"}],"scopus_import":"1","day":"10","has_accepted_license":"1","article_processing_charge":"Yes","article_type":"original","page":"210-224","publication":"Molecular Therapy - Methods and Clinical Development","citation":{"chicago":"Maes, Margaret E, Gabriele M. Wögenstein, Gloria Colombo, Raquel Casado Polanco, and Sandra Siegert. “Optimizing AAV2/6 Microglial Targeting Identified Enhanced Efficiency in the Photoreceptor Degenerative Environment.” Molecular Therapy - Methods and Clinical Development. Elsevier, 2021. https://doi.org/10.1016/j.omtm.2021.09.006.","short":"M.E. Maes, G.M. Wögenstein, G. Colombo, R. Casado Polanco, S. Siegert, Molecular Therapy - Methods and Clinical Development 23 (2021) 210–224.","mla":"Maes, Margaret E., et al. “Optimizing AAV2/6 Microglial Targeting Identified Enhanced Efficiency in the Photoreceptor Degenerative Environment.” Molecular Therapy - Methods and Clinical Development, vol. 23, Elsevier, 2021, pp. 210–24, doi:10.1016/j.omtm.2021.09.006.","apa":"Maes, M. E., Wögenstein, G. M., Colombo, G., Casado Polanco, R., & Siegert, S. (2021). Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment. Molecular Therapy - Methods and Clinical Development. Elsevier. https://doi.org/10.1016/j.omtm.2021.09.006","ieee":"M. E. Maes, G. M. Wögenstein, G. Colombo, R. Casado Polanco, and S. Siegert, “Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment,” Molecular Therapy - Methods and Clinical Development, vol. 23. Elsevier, pp. 210–224, 2021.","ista":"Maes ME, Wögenstein GM, Colombo G, Casado Polanco R, Siegert S. 2021. Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment. Molecular Therapy - Methods and Clinical Development. 23, 210–224.","ama":"Maes ME, Wögenstein GM, Colombo G, Casado Polanco R, Siegert S. Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment. Molecular Therapy - Methods and Clinical Development. 2021;23:210-224. doi:10.1016/j.omtm.2021.09.006"},"date_published":"2021-12-10T00:00:00Z","type":"journal_article","abstract":[{"lang":"eng","text":"Adeno-associated viruses (AAVs) are widely used to deliver genetic material in vivo to distinct cell types such as neurons or glial cells, allowing for targeted manipulation. Transduction of microglia is mostly excluded from this strategy, likely due to the cells’ heterogeneous state upon environmental changes, which makes AAV design challenging. Here, we established the retina as a model system for microglial AAV validation and optimization. First, we show that AAV2/6 transduced microglia in both synaptic layers, where layer preference corresponds to the intravitreal or subretinal delivery method. Surprisingly, we observed significantly enhanced microglial transduction during photoreceptor degeneration. Thus, we modified the AAV6 capsid to reduce heparin binding by introducing four point mutations (K531E, R576Q, K493S, and K459S), resulting in increased microglial transduction in the outer plexiform layer. Finally, to improve microglial-specific transduction, we validated a Cre-dependent transgene delivery cassette for use in combination with the Cx3cr1CreERT2 mouse line. Together, our results provide a foundation for future studies optimizing AAV-mediated microglia transduction and highlight that environmental conditions influence microglial transduction efficiency.\r\n"}],"title":"Optimizing AAV2/6 microglial targeting identified enhanced efficiency in the photoreceptor degenerative environment","status":"public","ddc":["570"],"intvolume":" 23","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"10655","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"10657","date_updated":"2022-01-24T07:43:09Z","date_created":"2022-01-24T07:43:09Z","checksum":"77dc540e8011c5475031bdf6ccef20a6","success":1,"file_name":"2021_MolTherMethodsClinDev_Maes.pdf","access_level":"open_access","file_size":4794147,"content_type":"application/pdf","creator":"cchlebak"}]},{"intvolume":" 2","status":"public","ddc":["573"],"title":"Minimally invasive protocols and quantification for microglia-mediated perineuronal net disassembly in mouse brain","_id":"10565","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","file":[{"date_updated":"2021-12-20T08:58:40Z","date_created":"2021-12-20T08:58:40Z","checksum":"9ea2501056c5df99e84726b845e9b976","success":1,"relation":"main_file","file_id":"10570","content_type":"application/pdf","file_size":6207060,"creator":"cchlebak","file_name":"2021_STARProt_Venturino.pdf","access_level":"open_access"}],"oa_version":"Published Version","type":"journal_article","issue":"4","abstract":[{"text":"Enzymatic digestion of the extracellular matrix with chondroitinase-ABC reinstates juvenile-like plasticity in the adult cortex as it also disassembles the perineuronal nets (PNNs). The disadvantage of the enzyme is that it must be applied intracerebrally and it degrades the ECM for several weeks. Here, we provide two minimally invasive and transient protocols for microglia-enabled PNN disassembly in mouse cortex: repeated treatment with ketamine-xylazine-acepromazine (KXA) anesthesia and 60-Hz light entrainment. We also discuss how to analyze PNNs within microglial endosomes-lysosomes. For complete details on the use and execution of this protocol, please refer to Venturino et al. (2021).","lang":"eng"}],"article_type":"original","citation":{"ama":"Venturino A, Siegert S. Minimally invasive protocols and quantification for microglia-mediated perineuronal net disassembly in mouse brain. STAR Protocols. 2021;2(4). doi:10.1016/j.xpro.2021.101012","apa":"Venturino, A., & Siegert, S. (2021). Minimally invasive protocols and quantification for microglia-mediated perineuronal net disassembly in mouse brain. STAR Protocols. Elsevier ; Cell Press. https://doi.org/10.1016/j.xpro.2021.101012","ieee":"A. Venturino and S. Siegert, “Minimally invasive protocols and quantification for microglia-mediated perineuronal net disassembly in mouse brain,” STAR Protocols, vol. 2, no. 4. Elsevier ; Cell Press, 2021.","ista":"Venturino A, Siegert S. 2021. Minimally invasive protocols and quantification for microglia-mediated perineuronal net disassembly in mouse brain. STAR Protocols. 2(4), 101012.","short":"A. Venturino, S. Siegert, STAR Protocols 2 (2021).","mla":"Venturino, Alessandro, and Sandra Siegert. “Minimally Invasive Protocols and Quantification for Microglia-Mediated Perineuronal Net Disassembly in Mouse Brain.” STAR Protocols, vol. 2, no. 4, 101012, Elsevier ; Cell Press, 2021, doi:10.1016/j.xpro.2021.101012.","chicago":"Venturino, Alessandro, and Sandra Siegert. “Minimally Invasive Protocols and Quantification for Microglia-Mediated Perineuronal Net Disassembly in Mouse Brain.” STAR Protocols. Elsevier ; Cell Press, 2021. https://doi.org/10.1016/j.xpro.2021.101012."},"publication":"STAR Protocols","date_published":"2021-12-17T00:00:00Z","scopus_import":"1","has_accepted_license":"1","article_processing_charge":"Yes","day":"17","department":[{"_id":"SaSi"}],"publisher":"Elsevier ; Cell Press","publication_status":"published","year":"2021","acknowledgement":"This research was supported by the European Research Council (grant 715571 to S.S.). We thank Rouven Schulz, Michael Schunn, Claudia Gold, Gabriel Krens, Sarah Gorkiewicz, Margaret Maes, Jürgen Siegert, Marco Benevento, and Sara Oakeley for comments on the manuscript and the IST Austria Bioimaging Facility for the technical support.","volume":2,"date_updated":"2023-11-16T13:11:04Z","date_created":"2021-12-19T23:01:32Z","author":[{"full_name":"Venturino, Alessandro","orcid":"0000-0003-2356-9403","id":"41CB84B2-F248-11E8-B48F-1D18A9856A87","last_name":"Venturino","first_name":"Alessandro"},{"last_name":"Siegert","first_name":"Sandra","orcid":"0000-0001-8635-0877","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","full_name":"Siegert, Sandra"}],"article_number":"101012","ec_funded":1,"file_date_updated":"2021-12-20T08:58:40Z","project":[{"_id":"25D4A630-B435-11E9-9278-68D0E5697425","grant_number":"715571","name":"Microglia action towards neuronal circuit formation and function in health and disease","call_identifier":"H2020"}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"Bio"}],"doi":"10.1016/j.xpro.2021.101012","publication_identifier":{"eissn":["2666-1667"]},"month":"12"},{"article_number":"100939","file_date_updated":"2021-11-22T08:23:58Z","ec_funded":1,"year":"2021","acknowledgement":"This research was supported by the Scientific Service Units (SSU) at IST Austria through resources provided by the Bioimaging (BIF) and Preclinical Facilities (PCF). We particularly thank Mohammad Goudarzi for assistance with photography of mouse perfusion and dissection. N.A. received support from FWF Firnberg-Programm (T 1031). This work was also supported by IST Austria institutional funds; FWF SFB F78 to S.H.; and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 725780 LinPro) to S.H.","publication_status":"published","department":[{"_id":"SiHi"}],"publisher":"Cell Press","author":[{"full_name":"Amberg, Nicole","id":"4CD6AAC6-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-3183-8207","first_name":"Nicole","last_name":"Amberg"},{"last_name":"Hippenmeyer","first_name":"Simon","orcid":"0000-0003-2279-1061","id":"37B36620-F248-11E8-B48F-1D18A9856A87","full_name":"Hippenmeyer, Simon"}],"date_updated":"2023-11-16T13:08:03Z","date_created":"2021-11-21T23:01:28Z","volume":2,"month":"11","publication_identifier":{"eissn":["2666-1667"]},"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","project":[{"grant_number":"725780","_id":"260018B0-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Principles of Neural Stem Cell Lineage Progression in Cerebral Cortex Development"},{"_id":"268F8446-B435-11E9-9278-68D0E5697425","grant_number":"T0101031","name":"Role of Eed in neural stem cell lineage progression","call_identifier":"FWF"},{"_id":"059F6AB4-7A3F-11EA-A408-12923DDC885E","grant_number":"F07805","name":"Molecular Mechanisms of Neural Stem Cell Lineage Progression"}],"doi":"10.1016/j.xpro.2021.100939","acknowledged_ssus":[{"_id":"Bio"},{"_id":"PreCl"}],"language":[{"iso":"eng"}],"type":"journal_article","abstract":[{"lang":"eng","text":"Mosaic analysis with double markers (MADM) technology enables the generation of genetic mosaic tissue in mice. MADM enables concomitant fluorescent cell labeling and introduction of a mutation of a gene of interest with single-cell resolution. This protocol highlights major steps for the generation of genetic mosaic tissue and the isolation and processing of respective tissues for downstream histological analysis. For complete details on the use and execution of this protocol, please refer to Contreras et al. (2021)."}],"issue":"4","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"10321","title":"Genetic mosaic dissection of candidate genes in mice using mosaic analysis with double markers","status":"public","ddc":["573"],"intvolume":" 2","oa_version":"Published Version","file":[{"success":1,"checksum":"9e3f6d06bf583e7a8b6a9e9a60500a28","date_updated":"2021-11-22T08:23:58Z","date_created":"2021-11-22T08:23:58Z","file_id":"10329","relation":"main_file","creator":"cchlebak","content_type":"application/pdf","file_size":7309464,"access_level":"open_access","file_name":"2021_STARProtocols_Amberg.pdf"}],"scopus_import":"1","day":"10","has_accepted_license":"1","article_processing_charge":"Yes","publication":"STAR Protocols","citation":{"chicago":"Amberg, Nicole, and Simon Hippenmeyer. “Genetic Mosaic Dissection of Candidate Genes in Mice Using Mosaic Analysis with Double Markers.” STAR Protocols. Cell Press, 2021. https://doi.org/10.1016/j.xpro.2021.100939.","mla":"Amberg, Nicole, and Simon Hippenmeyer. “Genetic Mosaic Dissection of Candidate Genes in Mice Using Mosaic Analysis with Double Markers.” STAR Protocols, vol. 2, no. 4, 100939, Cell Press, 2021, doi:10.1016/j.xpro.2021.100939.","short":"N. Amberg, S. Hippenmeyer, STAR Protocols 2 (2021).","ista":"Amberg N, Hippenmeyer S. 2021. Genetic mosaic dissection of candidate genes in mice using mosaic analysis with double markers. STAR Protocols. 2(4), 100939.","apa":"Amberg, N., & Hippenmeyer, S. (2021). Genetic mosaic dissection of candidate genes in mice using mosaic analysis with double markers. STAR Protocols. Cell Press. https://doi.org/10.1016/j.xpro.2021.100939","ieee":"N. Amberg and S. Hippenmeyer, “Genetic mosaic dissection of candidate genes in mice using mosaic analysis with double markers,” STAR Protocols, vol. 2, no. 4. Cell Press, 2021.","ama":"Amberg N, Hippenmeyer S. Genetic mosaic dissection of candidate genes in mice using mosaic analysis with double markers. STAR Protocols. 2021;2(4). doi:10.1016/j.xpro.2021.100939"},"article_type":"original","date_published":"2021-11-10T00:00:00Z"},{"project":[{"name":"Structure and isoform diversity of the Arp2/3 complex","grant_number":"P33367","_id":"9B954C5C-BA93-11EA-9121-9846C619BF3A"},{"call_identifier":"FWF","name":"Protein structure and function in filopodia across scales","grant_number":"M02495","_id":"2674F658-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","isi":1,"external_id":{"isi":["000720259500002"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"ScienComp"},{"_id":"LifeSc"},{"_id":"Bio"},{"_id":"EM-Fac"}],"doi":"10.1016/j.jsb.2021.107808","publication_identifier":{"issn":["1047-8477"]},"month":"11","publisher":"Elsevier ","department":[{"_id":"FlSc"}],"publication_status":"published","acknowledgement":"This research was supported by the Scientific Service Units (SSUs) of IST Austria through resources provided by Scientific Computing (SciComp), the Life Science Facility (LSF), the BioImaging Facility (BIF), and the Electron Microscopy Facility (EMF). We also thank Victor-Valentin Hodirnau for help with cryo-ET data acquisition. The authors acknowledge support from IST Austria and from the Austrian Science Fund (FWF): M02495 to G.D. and Austrian Science Fund (FWF): P33367 to F.K.M.S.","year":"2021","volume":213,"date_created":"2021-11-15T12:21:42Z","date_updated":"2023-11-21T08:36:02Z","related_material":{"record":[{"relation":"software","status":"public","id":"14502"}]},"author":[{"full_name":"Dimchev, Georgi A","id":"38C393BE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8370-6161","first_name":"Georgi A","last_name":"Dimchev"},{"full_name":"Amiri, Behnam","first_name":"Behnam","last_name":"Amiri"},{"full_name":"Fäßler, Florian","id":"404F5528-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7149-769X","first_name":"Florian","last_name":"Fäßler"},{"full_name":"Falcke, Martin","first_name":"Martin","last_name":"Falcke"},{"full_name":"Schur, Florian KM","id":"48AD8942-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4790-8078","first_name":"Florian KM","last_name":"Schur"}],"article_number":"107808","file_date_updated":"2021-11-15T13:11:27Z","article_type":"original","citation":{"ama":"Dimchev GA, Amiri B, Fäßler F, Falcke M, Schur FK. Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data. Journal of Structural Biology. 2021;213(4). doi:10.1016/j.jsb.2021.107808","apa":"Dimchev, G. A., Amiri, B., Fäßler, F., Falcke, M., & Schur, F. K. (2021). Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data. Journal of Structural Biology. Elsevier . https://doi.org/10.1016/j.jsb.2021.107808","ieee":"G. A. Dimchev, B. Amiri, F. Fäßler, M. Falcke, and F. K. Schur, “Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data,” Journal of Structural Biology, vol. 213, no. 4. Elsevier , 2021.","ista":"Dimchev GA, Amiri B, Fäßler F, Falcke M, Schur FK. 2021. Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data. Journal of Structural Biology. 213(4), 107808.","short":"G.A. Dimchev, B. Amiri, F. Fäßler, M. Falcke, F.K. Schur, Journal of Structural Biology 213 (2021).","mla":"Dimchev, Georgi A., et al. “Computational Toolbox for Ultrastructural Quantitative Analysis of Filament Networks in Cryo-ET Data.” Journal of Structural Biology, vol. 213, no. 4, 107808, Elsevier , 2021, doi:10.1016/j.jsb.2021.107808.","chicago":"Dimchev, Georgi A, Behnam Amiri, Florian Fäßler, Martin Falcke, and Florian KM Schur. “Computational Toolbox for Ultrastructural Quantitative Analysis of Filament Networks in Cryo-ET Data.” Journal of Structural Biology. Elsevier , 2021. https://doi.org/10.1016/j.jsb.2021.107808."},"publication":"Journal of Structural Biology","date_published":"2021-11-03T00:00:00Z","keyword":["Structural Biology"],"scopus_import":"1","has_accepted_license":"1","article_processing_charge":"Yes (via OA deal)","day":"03","intvolume":" 213","title":"Computational toolbox for ultrastructural quantitative analysis of filament networks in cryo-ET data","status":"public","ddc":["572"],"_id":"10290","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","file":[{"file_id":"10291","relation":"main_file","date_updated":"2021-11-15T13:11:27Z","date_created":"2021-11-15T13:11:27Z","success":1,"checksum":"6b209e4d44775d4e02b50f78982c15fa","file_name":"2021_JournalStructBiol_Dimchev.pdf","access_level":"open_access","creator":"cchlebak","content_type":"application/pdf","file_size":16818304}],"type":"journal_article","issue":"4","abstract":[{"text":"A precise quantitative description of the ultrastructural characteristics underlying biological mechanisms is often key to their understanding. This is particularly true for dynamic extra- and intracellular filamentous assemblies, playing a role in cell motility, cell integrity, cytokinesis, tissue formation and maintenance. For example, genetic manipulation or modulation of actin regulatory proteins frequently manifests in changes of the morphology, dynamics, and ultrastructural architecture of actin filament-rich cell peripheral structures, such as lamellipodia or filopodia. However, the observed ultrastructural effects often remain subtle and require sufficiently large datasets for appropriate quantitative analysis. The acquisition of such large datasets has been enabled by recent advances in high-throughput cryo-electron tomography (cryo-ET) methods. This also necessitates the development of complementary approaches to maximize the extraction of relevant biological information. We have developed a computational toolbox for the semi-automatic quantification of segmented and vectorized filamentous networks from pre-processed cryo-electron tomograms, facilitating the analysis and cross-comparison of multiple experimental conditions. GUI-based components simplify the processing of data and allow users to obtain a large number of ultrastructural parameters describing filamentous assemblies. We demonstrate the feasibility of this workflow by analyzing cryo-ET data of untreated and chemically perturbed branched actin filament networks and that of parallel actin filament arrays. In principle, the computational toolbox presented here is applicable for data analysis comprising any type of filaments in regular (i.e. parallel) or random arrangement. We show that it can ease the identification of key differences between experimental groups and facilitate the in-depth analysis of ultrastructural data in a time-efficient manner.","lang":"eng"}]},{"year":"2021","publication_status":"published","publisher":"IEEE","department":[{"_id":"KrPi"}],"author":[{"full_name":"Pietrzak, Krzysztof Z","id":"3E04A7AA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-9139-1654","first_name":"Krzysztof Z","last_name":"Pietrzak"},{"full_name":"Salem, Iosif","first_name":"Iosif","last_name":"Salem"},{"full_name":"Schmid, Stefan","first_name":"Stefan","last_name":"Schmid"},{"id":"2D82B818-F248-11E8-B48F-1D18A9856A87","last_name":"Yeo","first_name":"Michelle X","full_name":"Yeo, Michelle X"}],"related_material":{"record":[{"id":"14506","relation":"dissertation_contains","status":"public"}]},"date_created":"2021-08-29T22:01:16Z","date_updated":"2023-11-30T10:54:50Z","ec_funded":1,"external_id":{"isi":["000853016800008"],"arxiv":["2104.04293"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2104.04293"}],"oa":1,"quality_controlled":"1","isi":1,"project":[{"name":"Teaching Old Crypto New Tricks","call_identifier":"H2020","_id":"258AA5B2-B435-11E9-9278-68D0E5697425","grant_number":"682815"}],"conference":{"end_date":"2021-06-24","location":"Espoo and Helsinki, Finland","start_date":"2021-06-21","name":"2021 IFIP Networking Conference (IFIP Networking)"},"doi":"10.23919/IFIPNetworking52078.2021.9472205","language":[{"iso":"eng"}],"month":"06","publication_identifier":{"eissn":["1861-2288"],"isbn":["978-1-6654-4501-6"],"eisbn":["978-3-9031-7639-3"]},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"9969","title":"LightPIR: Privacy-preserving route discovery for payment channel networks","status":"public","oa_version":"Submitted Version","type":"conference","abstract":[{"lang":"eng","text":"Payment channel networks are a promising approach to improve the scalability of cryptocurrencies: they allow to perform transactions in a peer-to-peer fashion, along multihop routes in the network, without requiring consensus on the blockchain. However, during the discovery of cost-efficient routes for the transaction, critical information may be revealed about the transacting entities. This paper initiates the study of privacy-preserving route discovery mechanisms for payment channel networks. In particular, we present LightPIR, an approach which allows a client to learn the shortest (or cheapest in terms of fees) path between two nodes without revealing any information about the endpoints of the transaction to the servers. The two main observations which allow for an efficient solution in LightPIR are that: (1) surprisingly, hub labelling algorithms – which were developed to preprocess “street network like” graphs so one can later efficiently compute shortest paths – also perform well for the graphs underlying payment channel networks, and that (2) hub labelling algorithms can be conveniently combined with private information retrieval. LightPIR relies on a simple hub labeling heuristic on top of existing hub labeling algorithms which leverages the specific topological features of cryptocurrency networks to further minimize storage and bandwidth overheads. In a case study considering the Lightning network, we show that our approach is an order of magnitude more efficient compared to a privacy-preserving baseline based on using private information retrieval on a database that stores all pairs shortest paths."}],"citation":{"ama":"Pietrzak KZ, Salem I, Schmid S, Yeo MX. LightPIR: Privacy-preserving route discovery for payment channel networks. In: IEEE; 2021. doi:10.23919/IFIPNetworking52078.2021.9472205","ieee":"K. Z. Pietrzak, I. Salem, S. Schmid, and M. X. Yeo, “LightPIR: Privacy-preserving route discovery for payment channel networks,” presented at the 2021 IFIP Networking Conference (IFIP Networking), Espoo and Helsinki, Finland, 2021.","apa":"Pietrzak, K. Z., Salem, I., Schmid, S., & Yeo, M. X. (2021). LightPIR: Privacy-preserving route discovery for payment channel networks. Presented at the 2021 IFIP Networking Conference (IFIP Networking), Espoo and Helsinki, Finland: IEEE. https://doi.org/10.23919/IFIPNetworking52078.2021.9472205","ista":"Pietrzak KZ, Salem I, Schmid S, Yeo MX. 2021. LightPIR: Privacy-preserving route discovery for payment channel networks. 2021 IFIP Networking Conference (IFIP Networking).","short":"K.Z. Pietrzak, I. Salem, S. Schmid, M.X. Yeo, in:, IEEE, 2021.","mla":"Pietrzak, Krzysztof Z., et al. LightPIR: Privacy-Preserving Route Discovery for Payment Channel Networks. IEEE, 2021, doi:10.23919/IFIPNetworking52078.2021.9472205.","chicago":"Pietrzak, Krzysztof Z, Iosif Salem, Stefan Schmid, and Michelle X Yeo. “LightPIR: Privacy-Preserving Route Discovery for Payment Channel Networks.” IEEE, 2021. https://doi.org/10.23919/IFIPNetworking52078.2021.9472205."},"date_published":"2021-06-21T00:00:00Z","scopus_import":"1","day":"21","article_processing_charge":"No"},{"related_material":{"record":[{"id":"14539","relation":"dissertation_contains","status":"public"}]},"author":[{"full_name":"Chatterjee, Krishnendu","last_name":"Chatterjee","first_name":"Krishnendu","orcid":"0000-0002-4561-241X","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Goharshady, Ehsan Kafshdar","last_name":"Goharshady","first_name":"Ehsan Kafshdar"},{"full_name":"Novotný, Petr","id":"3CC3B868-F248-11E8-B48F-1D18A9856A87","last_name":"Novotný","first_name":"Petr"},{"last_name":"Zikelic","first_name":"Dorde","orcid":"0000-0002-4681-1699","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87","full_name":"Zikelic, Dorde"}],"date_updated":"2023-11-30T10:55:37Z","date_created":"2021-07-11T22:01:17Z","year":"2021","acknowledgement":"We thank the anonymous reviewers for their helpful comments. This research was partially supported by the ERCCoG 863818 (ForM-SMArt) and the Czech Science Foundation grant No. GJ19-15134Y.","publisher":"Association for Computing Machinery","department":[{"_id":"KrCh"}],"publication_status":"published","ec_funded":1,"doi":"10.1145/3453483.3454093","conference":{"name":"PLDI: Programming Language Design and Implementation","location":"Online","start_date":"2021-06-20","end_date":"2021-06-26"},"language":[{"iso":"eng"}],"oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/2104.01189","open_access":"1"}],"external_id":{"arxiv":["2104.01189"],"isi":["000723661700067"]},"project":[{"_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818","name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020"}],"quality_controlled":"1","isi":1,"publication_identifier":{"isbn":["9781450383912"]},"month":"06","oa_version":"Preprint","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"9644","status":"public","title":"Proving non-termination by program reversal","abstract":[{"lang":"eng","text":"We present a new approach to proving non-termination of non-deterministic integer programs. Our technique is rather simple but efficient. It relies on a purely syntactic reversal of the program's transition system followed by a constraint-based invariant synthesis with constraints coming from both the original and the reversed transition system. The latter task is performed by a simple call to an off-the-shelf SMT-solver, which allows us to leverage the latest advances in SMT-solving. Moreover, our method offers a combination of features not present (as a whole) in previous approaches: it handles programs with non-determinism, provides relative completeness guarantees and supports programs with polynomial arithmetic. The experiments performed with our prototype tool RevTerm show that our approach, despite its simplicity and stronger theoretical guarantees, is at least on par with the state-of-the-art tools, often achieving a non-trivial improvement under a proper configuration of its parameters."}],"type":"conference","date_published":"2021-06-01T00:00:00Z","citation":{"chicago":"Chatterjee, Krishnendu, Ehsan Kafshdar Goharshady, Petr Novotný, and Dorde Zikelic. “Proving Non-Termination by Program Reversal.” In Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 1033–48. Association for Computing Machinery, 2021. https://doi.org/10.1145/3453483.3454093.","short":"K. Chatterjee, E.K. Goharshady, P. Novotný, D. Zikelic, in:, Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2021, pp. 1033–1048.","mla":"Chatterjee, Krishnendu, et al. “Proving Non-Termination by Program Reversal.” Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2021, pp. 1033–48, doi:10.1145/3453483.3454093.","apa":"Chatterjee, K., Goharshady, E. K., Novotný, P., & Zikelic, D. (2021). Proving non-termination by program reversal. In Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation (pp. 1033–1048). Online: Association for Computing Machinery. https://doi.org/10.1145/3453483.3454093","ieee":"K. Chatterjee, E. K. Goharshady, P. Novotný, and D. Zikelic, “Proving non-termination by program reversal,” in Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation, Online, 2021, pp. 1033–1048.","ista":"Chatterjee K, Goharshady EK, Novotný P, Zikelic D. 2021. Proving non-termination by program reversal. Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation. PLDI: Programming Language Design and Implementation, 1033–1048.","ama":"Chatterjee K, Goharshady EK, Novotný P, Zikelic D. Proving non-termination by program reversal. In: Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation. Association for Computing Machinery; 2021:1033-1048. doi:10.1145/3453483.3454093"},"publication":"Proceedings of the 42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation","page":"1033-1048","article_processing_charge":"No","day":"01","scopus_import":"1"},{"month":"07","publication_identifier":{"eissn":["2521-327X"]},"language":[{"iso":"eng"}],"doi":"10.22331/Q-2021-07-01-491","isi":1,"quality_controlled":"1","project":[{"name":"Non-Ergodic Quantum Matter: Universality, Dynamics and Control","call_identifier":"H2020","_id":"23841C26-32DE-11EA-91FC-C7463DDC885E","grant_number":"850899"}],"external_id":{"isi":["000669830600001"],"arxiv":["2101.05742"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"file_date_updated":"2021-08-06T06:44:31Z","ec_funded":1,"article_number":"491","date_created":"2021-08-01T22:01:21Z","date_updated":"2023-12-13T14:47:25Z","volume":5,"author":[{"full_name":"Sack, Stefan","first_name":"Stefan","last_name":"Sack","id":"dd622248-f6e0-11ea-865d-ce382a1c81a5","orcid":"0000-0001-5400-8508"},{"full_name":"Serbyn, Maksym","last_name":"Serbyn","first_name":"Maksym","orcid":"0000-0002-2399-5827","id":"47809E7E-F248-11E8-B48F-1D18A9856A87"}],"related_material":{"record":[{"id":"14622","relation":"dissertation_contains","status":"public"}]},"publication_status":"published","department":[{"_id":"GradSch"},{"_id":"MaSe"}],"publisher":"Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften","acknowledgement":"We would like to thank D. Abanin and R. Medina for fruitful discussions and A. Smith and I. Kim for valuable feedback on the manuscript. We acknowledge support by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant Agreement No. 850899).","year":"2021","day":"01","has_accepted_license":"1","article_processing_charge":"Yes","scopus_import":"1","date_published":"2021-07-01T00:00:00Z","article_type":"original","publication":"Quantum","citation":{"chicago":"Sack, Stefan, and Maksym Serbyn. “Quantum Annealing Initialization of the Quantum Approximate Optimization Algorithm.” Quantum. Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften, 2021. https://doi.org/10.22331/Q-2021-07-01-491.","mla":"Sack, Stefan, and Maksym Serbyn. “Quantum Annealing Initialization of the Quantum Approximate Optimization Algorithm.” Quantum, vol. 5, 491, Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften, 2021, doi:10.22331/Q-2021-07-01-491.","short":"S. Sack, M. Serbyn, Quantum 5 (2021).","ista":"Sack S, Serbyn M. 2021. Quantum annealing initialization of the quantum approximate optimization algorithm. Quantum. 5, 491.","apa":"Sack, S., & Serbyn, M. (2021). Quantum annealing initialization of the quantum approximate optimization algorithm. Quantum. Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften. https://doi.org/10.22331/Q-2021-07-01-491","ieee":"S. Sack and M. Serbyn, “Quantum annealing initialization of the quantum approximate optimization algorithm,” Quantum, vol. 5. Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften, 2021.","ama":"Sack S, Serbyn M. Quantum annealing initialization of the quantum approximate optimization algorithm. Quantum. 2021;5. doi:10.22331/Q-2021-07-01-491"},"abstract":[{"text":"The quantum approximate optimization algorithm (QAOA) is a prospective near-term quantum algorithm due to its modest circuit depth and promising benchmarks. However, an external parameter optimization required in the QAOA could become a performance bottleneck. This motivates studies of the optimization landscape and search for heuristic ways of parameter initialization. In this work we visualize the optimization landscape of the QAOA applied to the MaxCut problem on random graphs, demonstrating that random initialization of the QAOA is prone to converging to local minima with suboptimal performance. We introduce the initialization of QAOA parameters based on the Trotterized quantum annealing (TQA) protocol, parameterized by the Trotter time step. We find that the TQA initialization allows to circumvent\r\nthe issue of false minima for a broad range of time steps, yielding the same performance as the best result out of an exponentially scaling number of random initializations. Moreover, we demonstrate that the optimal value of the time step coincides with the point of proliferation of Trotter errors in quantum annealing. Our results suggest practical ways of initializing QAOA protocols on near-term quantum devices and reveal new connections between QAOA and quantum annealing.","lang":"eng"}],"type":"journal_article","oa_version":"Published Version","file":[{"creator":"cchlebak","file_size":2312482,"content_type":"application/pdf","file_name":"2021_Quantum_Sack.pdf","access_level":"open_access","date_created":"2021-08-06T06:44:31Z","date_updated":"2021-08-06T06:44:31Z","checksum":"9706c2bb8e748e9b5b138381995a7f6f","file_id":"9774","relation":"main_file"}],"ddc":["530"],"title":"Quantum annealing initialization of the quantum approximate optimization algorithm","status":"public","intvolume":" 5","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"9760"},{"date_published":"2021-11-10T00:00:00Z","page":"619-639","citation":{"chicago":"Chatterjee, Krishnendu, Ehsan Kafshdar Goharshady, Petr Novotný, Jiří Zárevúcky, and Dorde Zikelic. “On Lexicographic Proof Rules for Probabilistic Termination.” In 24th International Symposium on Formal Methods, 13047:619–39. Springer Nature, 2021. https://doi.org/10.1007/978-3-030-90870-6_33.","short":"K. Chatterjee, E.K. Goharshady, P. Novotný, J. Zárevúcky, D. Zikelic, in:, 24th International Symposium on Formal Methods, Springer Nature, 2021, pp. 619–639.","mla":"Chatterjee, Krishnendu, et al. “On Lexicographic Proof Rules for Probabilistic Termination.” 24th International Symposium on Formal Methods, vol. 13047, Springer Nature, 2021, pp. 619–39, doi:10.1007/978-3-030-90870-6_33.","apa":"Chatterjee, K., Goharshady, E. K., Novotný, P., Zárevúcky, J., & Zikelic, D. (2021). On lexicographic proof rules for probabilistic termination. In 24th International Symposium on Formal Methods (Vol. 13047, pp. 619–639). Virtual: Springer Nature. https://doi.org/10.1007/978-3-030-90870-6_33","ieee":"K. Chatterjee, E. K. Goharshady, P. Novotný, J. Zárevúcky, and D. Zikelic, “On lexicographic proof rules for probabilistic termination,” in 24th International Symposium on Formal Methods, Virtual, 2021, vol. 13047, pp. 619–639.","ista":"Chatterjee K, Goharshady EK, Novotný P, Zárevúcky J, Zikelic D. 2021. On lexicographic proof rules for probabilistic termination. 24th International Symposium on Formal Methods. FM: Formal Methods, LNCS, vol. 13047, 619–639.","ama":"Chatterjee K, Goharshady EK, Novotný P, Zárevúcky J, Zikelic D. On lexicographic proof rules for probabilistic termination. In: 24th International Symposium on Formal Methods. Vol 13047. Springer Nature; 2021:619-639. doi:10.1007/978-3-030-90870-6_33"},"publication":"24th International Symposium on Formal Methods","article_processing_charge":"No","day":"10","scopus_import":"1","oa_version":"Preprint","intvolume":" 13047","title":"On lexicographic proof rules for probabilistic termination","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"10414","abstract":[{"lang":"eng","text":"We consider the almost-sure (a.s.) termination problem for probabilistic programs, which are a stochastic extension of classical imperative programs. Lexicographic ranking functions provide a sound and practical approach for termination of non-probabilistic programs, and their extension to probabilistic programs is achieved via lexicographic ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous work have a limitation that impedes their automation: all of their components have to be non-negative in all reachable states. This might result in LexRSM not existing even for simple terminating programs. Our contributions are twofold: First, we introduce a generalization of LexRSMs which allows for some components to be negative. This standard feature of non-probabilistic termination proofs was hitherto not known to be sound in the probabilistic setting, as the soundness proof requires a careful analysis of the underlying stochastic process. Second, we present polynomial-time algorithms using our generalized LexRSMs for proving a.s. termination in broad classes of linear-arithmetic programs."}],"alternative_title":["LNCS"],"type":"conference","language":[{"iso":"eng"}],"doi":"10.1007/978-3-030-90870-6_33","conference":{"end_date":"2021-11-26","start_date":"2021-11-20","location":"Virtual","name":"FM: Formal Methods"},"project":[{"name":"Formal Methods for Stochastic Models: Algorithms and Applications","call_identifier":"H2020","_id":"0599E47C-7A3F-11EA-A408-12923DDC885E","grant_number":"863818"},{"_id":"2564DBCA-B435-11E9-9278-68D0E5697425","grant_number":"665385","name":"International IST Doctoral Program","call_identifier":"H2020"}],"isi":1,"quality_controlled":"1","oa":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2108.02188"}],"external_id":{"arxiv":["2108.02188"],"isi":["000758218600033"]},"publication_identifier":{"issn":["0302-9743"],"eisbn":["978-3-030-90870-6"],"eissn":["1611-3349"],"isbn":["9-783-0309-0869-0"]},"month":"11","volume":13047,"date_updated":"2024-01-17T08:19:41Z","date_created":"2021-12-05T23:01:45Z","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"14539"},{"id":"14778","status":"public","relation":"later_version"}]},"author":[{"full_name":"Chatterjee, Krishnendu","first_name":"Krishnendu","last_name":"Chatterjee","id":"2E5DCA20-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4561-241X"},{"full_name":"Goharshady, Ehsan Kafshdar","first_name":"Ehsan Kafshdar","last_name":"Goharshady"},{"last_name":"Novotný","first_name":"Petr","id":"3CC3B868-F248-11E8-B48F-1D18A9856A87","full_name":"Novotný, Petr"},{"full_name":"Zárevúcky, Jiří","last_name":"Zárevúcky","first_name":"Jiří"},{"full_name":"Zikelic, Dorde","last_name":"Zikelic","first_name":"Dorde","orcid":"0000-0002-4681-1699","id":"294AA7A6-F248-11E8-B48F-1D18A9856A87"}],"department":[{"_id":"KrCh"}],"publisher":"Springer Nature","publication_status":"published","acknowledgement":"This research was partially supported by the ERC CoG 863818 (ForM-SMArt), the Czech Science Foundation grant No. GJ19-15134Y, and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.","year":"2021","ec_funded":1},{"doi":"10.3866/PKU.WHXB202108017","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.3866/PKU.WHXB202108017"}],"oa":1,"quality_controlled":"1","publication_identifier":{"issn":["1001-4861"]},"month":"10","author":[{"id":"9E331C2E-9F27-11E9-AE48-5033E6697425","orcid":"0000-0002-9515-4277","first_name":"Cheng","last_name":"Chang","full_name":"Chang, Cheng"},{"full_name":"Chen, Wei","first_name":"Wei","last_name":"Chen"},{"full_name":"Chen, Ye","first_name":"Ye","last_name":"Chen"},{"full_name":"Chen, Yonghua","first_name":"Yonghua","last_name":"Chen"},{"last_name":"Chen","first_name":"Yu","full_name":"Chen, Yu"},{"full_name":"Ding, Feng","last_name":"Ding","first_name":"Feng"},{"last_name":"Fan","first_name":"Chunhai","full_name":"Fan, Chunhai"},{"full_name":"Fan, Hong Jin","first_name":"Hong Jin","last_name":"Fan"},{"full_name":"Fan, Zhanxi","first_name":"Zhanxi","last_name":"Fan"},{"last_name":"Gong","first_name":"Cheng","full_name":"Gong, Cheng"},{"full_name":"Gong, Yongji","last_name":"Gong","first_name":"Yongji"},{"first_name":"Qiyuan","last_name":"He","full_name":"He, Qiyuan"},{"last_name":"Hong","first_name":"Xun","full_name":"Hong, Xun"},{"last_name":"Hu","first_name":"Sheng","full_name":"Hu, Sheng"},{"first_name":"Weida","last_name":"Hu","full_name":"Hu, Weida"},{"first_name":"Wei","last_name":"Huang","full_name":"Huang, Wei"},{"full_name":"Huang, Yuan","last_name":"Huang","first_name":"Yuan"},{"full_name":"Ji, Wei","last_name":"Ji","first_name":"Wei"},{"first_name":"Dehui","last_name":"Li","full_name":"Li, Dehui"},{"full_name":"Li, Lain Jong","last_name":"Li","first_name":"Lain Jong"},{"full_name":"Li, Qiang","first_name":"Qiang","last_name":"Li"},{"full_name":"Lin, Li","last_name":"Lin","first_name":"Li"},{"first_name":"Chongyi","last_name":"Ling","full_name":"Ling, Chongyi"},{"last_name":"Liu","first_name":"Minghua","full_name":"Liu, Minghua"},{"full_name":"Liu, Nan","last_name":"Liu","first_name":"Nan"},{"last_name":"Liu","first_name":"Zhuang","full_name":"Liu, Zhuang"},{"first_name":"Kian Ping","last_name":"Loh","full_name":"Loh, Kian Ping"},{"last_name":"Ma","first_name":"Jianmin","full_name":"Ma, Jianmin"},{"last_name":"Miao","first_name":"Feng","full_name":"Miao, Feng"},{"full_name":"Peng, Hailin","last_name":"Peng","first_name":"Hailin"},{"full_name":"Shao, Mingfei","last_name":"Shao","first_name":"Mingfei"},{"full_name":"Song, Li","last_name":"Song","first_name":"Li"},{"first_name":"Shao","last_name":"Su","full_name":"Su, Shao"},{"full_name":"Sun, Shuo","last_name":"Sun","first_name":"Shuo"},{"full_name":"Tan, Chaoliang","last_name":"Tan","first_name":"Chaoliang"},{"first_name":"Zhiyong","last_name":"Tang","full_name":"Tang, Zhiyong"},{"first_name":"Dingsheng","last_name":"Wang","full_name":"Wang, Dingsheng"},{"full_name":"Wang, Huan","last_name":"Wang","first_name":"Huan"},{"first_name":"Jinlan","last_name":"Wang","full_name":"Wang, Jinlan"},{"last_name":"Wang","first_name":"Xin","full_name":"Wang, Xin"},{"full_name":"Wang, Xinran","first_name":"Xinran","last_name":"Wang"},{"full_name":"Wee, Andrew T.S.","first_name":"Andrew T.S.","last_name":"Wee"},{"full_name":"Wei, Zhongming","first_name":"Zhongming","last_name":"Wei"},{"first_name":"Yuen","last_name":"Wu","full_name":"Wu, Yuen"},{"first_name":"Zhong Shuai","last_name":"Wu","full_name":"Wu, Zhong Shuai"},{"full_name":"Xiong, Jie","last_name":"Xiong","first_name":"Jie"},{"first_name":"Qihua","last_name":"Xiong","full_name":"Xiong, Qihua"},{"full_name":"Xu, Weigao","first_name":"Weigao","last_name":"Xu"},{"first_name":"Peng","last_name":"Yin","full_name":"Yin, Peng"},{"full_name":"Zeng, Haibo","first_name":"Haibo","last_name":"Zeng"},{"last_name":"Zeng","first_name":"Zhiyuan","full_name":"Zeng, Zhiyuan"},{"last_name":"Zhai","first_name":"Tianyou","full_name":"Zhai, Tianyou"},{"full_name":"Zhang, Han","first_name":"Han","last_name":"Zhang"},{"first_name":"Hui","last_name":"Zhang","full_name":"Zhang, Hui"},{"first_name":"Qichun","last_name":"Zhang","full_name":"Zhang, Qichun"},{"full_name":"Zhang, Tierui","first_name":"Tierui","last_name":"Zhang"},{"full_name":"Zhang, Xiang","first_name":"Xiang","last_name":"Zhang"},{"last_name":"Zhao","first_name":"Li Dong","full_name":"Zhao, Li Dong"},{"full_name":"Zhao, Meiting","first_name":"Meiting","last_name":"Zhao"},{"last_name":"Zhao","first_name":"Weijie","full_name":"Zhao, Weijie"},{"full_name":"Zhao, Yunxuan","last_name":"Zhao","first_name":"Yunxuan"},{"first_name":"Kai Ge","last_name":"Zhou","full_name":"Zhou, Kai Ge"},{"first_name":"Xing","last_name":"Zhou","full_name":"Zhou, Xing"},{"full_name":"Zhou, Yu","first_name":"Yu","last_name":"Zhou"},{"last_name":"Zhu","first_name":"Hongwei","full_name":"Zhu, Hongwei"},{"full_name":"Zhang, Hua","first_name":"Hua","last_name":"Zhang"},{"full_name":"Liu, Zhongfan","first_name":"Zhongfan","last_name":"Liu"}],"volume":37,"date_created":"2024-01-14T23:00:58Z","date_updated":"2024-01-17T11:29:33Z","year":"2021","publisher":"Peking University","department":[{"_id":"MaIb"}],"publication_status":"published","article_number":"2108017","date_published":"2021-10-13T00:00:00Z","citation":{"chicago":"Chang, Cheng, Wei Chen, Ye Chen, Yonghua Chen, Yu Chen, Feng Ding, Chunhai Fan, et al. “Recent Progress on Two-Dimensional Materials.” Acta Physico-Chimica Sinica. Peking University, 2021. https://doi.org/10.3866/PKU.WHXB202108017.","short":"C. Chang, W. Chen, Y. Chen, Y. Chen, Y. Chen, F. Ding, C. Fan, H.J. Fan, Z. Fan, C. Gong, Y. Gong, Q. He, X. Hong, S. Hu, W. Hu, W. Huang, Y. Huang, W. Ji, D. Li, L.J. Li, Q. Li, L. Lin, C. Ling, M. Liu, N. Liu, Z. Liu, K.P. Loh, J. Ma, F. Miao, H. Peng, M. Shao, L. Song, S. Su, S. Sun, C. Tan, Z. Tang, D. Wang, H. Wang, J. Wang, X. Wang, X. Wang, A.T.S. Wee, Z. Wei, Y. Wu, Z.S. Wu, J. Xiong, Q. Xiong, W. Xu, P. Yin, H. Zeng, Z. Zeng, T. Zhai, H. Zhang, H. Zhang, Q. Zhang, T. Zhang, X. Zhang, L.D. Zhao, M. Zhao, W. Zhao, Y. Zhao, K.G. Zhou, X. Zhou, Y. Zhou, H. Zhu, H. Zhang, Z. Liu, Acta Physico-Chimica Sinica 37 (2021).","mla":"Chang, Cheng, et al. “Recent Progress on Two-Dimensional Materials.” Acta Physico-Chimica Sinica, vol. 37, no. 12, 2108017, Peking University, 2021, doi:10.3866/PKU.WHXB202108017.","ieee":"C. Chang et al., “Recent progress on two-dimensional materials,” Acta Physico-Chimica Sinica, vol. 37, no. 12. Peking University, 2021.","apa":"Chang, C., Chen, W., Chen, Y., Chen, Y., Chen, Y., Ding, F., … Liu, Z. (2021). Recent progress on two-dimensional materials. Acta Physico-Chimica Sinica. Peking University. https://doi.org/10.3866/PKU.WHXB202108017","ista":"Chang C, Chen W, Chen Y, Chen Y, Chen Y, Ding F, Fan C, Fan HJ, Fan Z, Gong C, Gong Y, He Q, Hong X, Hu S, Hu W, Huang W, Huang Y, Ji W, Li D, Li LJ, Li Q, Lin L, Ling C, Liu M, Liu N, Liu Z, Loh KP, Ma J, Miao F, Peng H, Shao M, Song L, Su S, Sun S, Tan C, Tang Z, Wang D, Wang H, Wang J, Wang X, Wang X, Wee ATS, Wei Z, Wu Y, Wu ZS, Xiong J, Xiong Q, Xu W, Yin P, Zeng H, Zeng Z, Zhai T, Zhang H, Zhang H, Zhang Q, Zhang T, Zhang X, Zhao LD, Zhao M, Zhao W, Zhao Y, Zhou KG, Zhou X, Zhou Y, Zhu H, Zhang H, Liu Z. 2021. Recent progress on two-dimensional materials. Acta Physico-Chimica Sinica. 37(12), 2108017.","ama":"Chang C, Chen W, Chen Y, et al. Recent progress on two-dimensional materials. Acta Physico-Chimica Sinica. 2021;37(12). doi:10.3866/PKU.WHXB202108017"},"publication":"Acta Physico-Chimica Sinica","article_type":"review","article_processing_charge":"No","day":"13","scopus_import":"1","oa_version":"Submitted Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14800","intvolume":" 37","title":"Recent progress on two-dimensional materials","status":"public","issue":"12","abstract":[{"text":"Research on two-dimensional (2D) materials has been explosively increasing in last seventeen years in varying subjects including condensed matter physics, electronic engineering, materials science, and chemistry since the mechanical exfoliation of graphene in 2004. Starting from graphene, 2D materials now have become a big family with numerous members and diverse categories. The unique structural features and physicochemical properties of 2D materials make them one class of the most appealing candidates for a wide range of potential applications. In particular, we have seen some major breakthroughs made in the field of 2D materials in last five years not only in developing novel synthetic methods and exploring new structures/properties but also in identifying innovative applications and pushing forward commercialisation. In this review, we provide a critical summary on the recent progress made in the field of 2D materials with a particular focus on last five years. After a brief background introduction, we first discuss the major synthetic methods for 2D materials, including the mechanical exfoliation, liquid exfoliation, vapor phase deposition, and wet-chemical synthesis as well as phase engineering of 2D materials belonging to the field of phase engineering of nanomaterials (PEN). We then introduce the superconducting/optical/magnetic properties and chirality of 2D materials along with newly emerging magic angle 2D superlattices. Following that, the promising applications of 2D materials in electronics, optoelectronics, catalysis, energy storage, solar cells, biomedicine, sensors, environments, etc. are described sequentially. Thereafter, we present the theoretic calculations and simulations of 2D materials. Finally, after concluding the current progress, we provide some personal discussions on the existing challenges and future outlooks in this rapidly developing field. ","lang":"eng"}],"type":"journal_article"},{"place":"Cham","ec_funded":1,"publication_status":"published","publisher":"Springer Nature","department":[{"_id":"ToHe"}],"acknowledgement":"We thank Christoph Lampert and Alex Greengold for fruitful discussions. This research was supported in part by the Simons Institute for the Theory of Computing, the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 754411.","year":"2021","date_created":"2021-10-31T23:01:31Z","date_updated":"2024-01-30T12:06:56Z","volume":"12974 ","author":[{"full_name":"Lukina, Anna","first_name":"Anna","last_name":"Lukina","id":"CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425"},{"full_name":"Schilling, Christian","id":"3A2F4DCE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-3658-1065","first_name":"Christian","last_name":"Schilling"},{"first_name":"Thomas A","last_name":"Henzinger","id":"40876CD8-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2985-7724","full_name":"Henzinger, Thomas A"}],"related_material":{"record":[{"id":"13234","status":"public","relation":"extended_version"}]},"month":"10","publication_identifier":{"eissn":["1611-3349"],"isbn":["9-783-0308-8493-2"],"eisbn":["978-3-030-88494-9"],"issn":["0302-9743"]},"quality_controlled":"1","isi":1,"project":[{"name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020","_id":"260C2330-B435-11E9-9278-68D0E5697425","grant_number":"754411"},{"name":"The Wittgenstein Prize","call_identifier":"FWF","_id":"25F42A32-B435-11E9-9278-68D0E5697425","grant_number":"Z211"}],"oa":1,"external_id":{"arxiv":["2009.06429"],"isi":["000719383800003"]},"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2009.06429"}],"language":[{"iso":"eng"}],"conference":{"name":"RV: Runtime Verification","location":"Virtual","start_date":"2021-10-11","end_date":"2021-10-14"},"doi":"10.1007/978-3-030-88494-9_3","alternative_title":["LNCS"],"type":"conference","abstract":[{"text":"Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. The typical approach is to detect inputs from novel classes and retrain the classifier on an augmented dataset. However, not only the classifier but also the detection mechanism needs to adapt in order to distinguish between newly learned and yet unknown input classes. To address this challenge, we introduce an algorithmic framework for active monitoring of a neural network. A monitor wrapped in our framework operates in parallel with the neural network and interacts with a human user via a series of interpretable labeling queries for incremental adaptation. In addition, we propose an adaptive quantitative monitor to improve precision. An experimental evaluation on a diverse set of benchmarks with varying numbers of classes confirms the benefits of our active monitoring framework in dynamic scenarios.","lang":"eng"}],"title":"Into the unknown: active monitoring of neural networks","status":"public","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"10206","oa_version":"Preprint","keyword":["monitoring","neural networks","novelty detection"],"scopus_import":"1","day":"06","article_processing_charge":"No","page":"42-61","publication":"21st International Conference on Runtime Verification","citation":{"short":"A. Lukina, C. Schilling, T.A. Henzinger, in:, 21st International Conference on Runtime Verification, Springer Nature, Cham, 2021, pp. 42–61.","mla":"Lukina, Anna, et al. “Into the Unknown: Active Monitoring of Neural Networks.” 21st International Conference on Runtime Verification, vol. 12974, Springer Nature, 2021, pp. 42–61, doi:10.1007/978-3-030-88494-9_3.","chicago":"Lukina, Anna, Christian Schilling, and Thomas A Henzinger. “Into the Unknown: Active Monitoring of Neural Networks.” In 21st International Conference on Runtime Verification, 12974:42–61. Cham: Springer Nature, 2021. https://doi.org/10.1007/978-3-030-88494-9_3.","ama":"Lukina A, Schilling C, Henzinger TA. Into the unknown: active monitoring of neural networks. In: 21st International Conference on Runtime Verification. Vol 12974. Cham: Springer Nature; 2021:42-61. doi:10.1007/978-3-030-88494-9_3","ieee":"A. Lukina, C. Schilling, and T. A. Henzinger, “Into the unknown: active monitoring of neural networks,” in 21st International Conference on Runtime Verification, Virtual, 2021, vol. 12974, pp. 42–61.","apa":"Lukina, A., Schilling, C., & Henzinger, T. A. (2021). Into the unknown: active monitoring of neural networks. In 21st International Conference on Runtime Verification (Vol. 12974, pp. 42–61). Cham: Springer Nature. https://doi.org/10.1007/978-3-030-88494-9_3","ista":"Lukina A, Schilling C, Henzinger TA. 2021. Into the unknown: active monitoring of neural networks. 21st International Conference on Runtime Verification. RV: Runtime Verification, LNCS, vol. 12974, 42–61."},"date_published":"2021-10-06T00:00:00Z"}]