[{"acknowledgement":"MR-V and RS are supported by Fondecyt Grant No. 1220536 and Millennium Science Initiative Program NCN19_170D of ANID, Chile. P.d.C. was supported by Scholarships Nos. 2021/10139-2 and 2022/13872-5 and ICTP-SAIFR Grant No. 2021/14335-0, all granted by São Paulo Research Foundation (FAPESP), Brazil.","quality_controlled":"1","publisher":"Springer Nature","day":"01","publication":"The European Physical Journal E","year":"2023","date_published":"2023-10-01T00:00:00Z","doi":"10.1140/epje/s10189-023-00354-y","date_created":"2023-10-22T22:01:13Z","article_number":"95","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Rojas Vega MN, De Castro P, Soto R. 2023. Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. 46(10), 95.","chicago":"Rojas Vega, Mauricio Nicolas, Pablo De Castro, and Rodrigo Soto. “Mixtures of Self-Propelled Particles Interacting with Asymmetric Obstacles.” The European Physical Journal E. Springer Nature, 2023. https://doi.org/10.1140/epje/s10189-023-00354-y.","ama":"Rojas Vega MN, De Castro P, Soto R. Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. 2023;46(10). doi:10.1140/epje/s10189-023-00354-y","apa":"Rojas Vega, M. N., De Castro, P., & Soto, R. (2023). Mixtures of self-propelled particles interacting with asymmetric obstacles. The European Physical Journal E. Springer Nature. https://doi.org/10.1140/epje/s10189-023-00354-y","short":"M.N. Rojas Vega, P. De Castro, R. Soto, The European Physical Journal E 46 (2023).","ieee":"M. N. Rojas Vega, P. De Castro, and R. Soto, “Mixtures of self-propelled particles interacting with asymmetric obstacles,” The European Physical Journal E, vol. 46, no. 10. Springer Nature, 2023.","mla":"Rojas Vega, Mauricio Nicolas, et al. “Mixtures of Self-Propelled Particles Interacting with Asymmetric Obstacles.” The European Physical Journal E, vol. 46, no. 10, 95, Springer Nature, 2023, doi:10.1140/epje/s10189-023-00354-y."},"title":"Mixtures of self-propelled particles interacting with asymmetric obstacles","author":[{"first_name":"Mauricio Nicolas","id":"441e7207-f91f-11ec-b67c-9e6fe3d8fd6d","full_name":"Rojas Vega, Mauricio Nicolas","last_name":"Rojas Vega"},{"first_name":"Pablo","full_name":"De Castro, Pablo","last_name":"De Castro"},{"last_name":"Soto","full_name":"Soto, Rodrigo","first_name":"Rodrigo"}],"article_processing_charge":"No","external_id":{"pmid":["37819444"]},"pmid":1,"oa_version":"None","abstract":[{"text":"In the presence of an obstacle, active particles condensate into a surface “wetting” layer due to persistent motion. If the obstacle is asymmetric, a rectification current arises in addition to wetting. Asymmetric geometries are therefore commonly used to concentrate microorganisms like bacteria and sperms. However, most studies neglect the fact that biological active matter is diverse, composed of individuals with distinct self-propulsions. Using simulations, we study a mixture of “fast” and “slow” active Brownian disks in two dimensions interacting with large half-disk obstacles. With this prototypical obstacle geometry, we analyze how the stationary collective behavior depends on the degree of self-propulsion “diversity,” defined as proportional to the difference between the self-propulsion speeds, while keeping the average self-propulsion speed fixed. A wetting layer rich in fast particles arises. The rectification current is amplified by speed diversity due to a superlinear dependence of rectification on self-propulsion speed, which arises from cooperative effects. Thus, the total rectification current cannot be obtained from an effective one-component active fluid with the same average self-propulsion speed, highlighting the importance of considering diversity in active matter.","lang":"eng"}],"month":"10","intvolume":" 46","scopus_import":"1","language":[{"iso":"eng"}],"publication_identifier":{"eissn":["1292-895X"],"issn":["1292-8941"]},"publication_status":"published","volume":46,"issue":"10","_id":"14442","status":"public","article_type":"original","type":"journal_article","date_updated":"2023-10-31T11:16:41Z","department":[{"_id":"AnSa"}]},{"title":"Substructures in Latin squares","article_processing_charge":"Yes (in subscription journal)","external_id":{"arxiv":["2202.05088"]},"author":[{"id":"5fca0887-a1db-11eb-95d1-ca9d5e0453b3","first_name":"Matthew Alan","last_name":"Kwan","full_name":"Kwan, Matthew Alan","orcid":"0000-0002-4003-7567"},{"full_name":"Sah, Ashwin","last_name":"Sah","first_name":"Ashwin"},{"last_name":"Sawhney","full_name":"Sawhney, Mehtaab","first_name":"Mehtaab"},{"first_name":"Michael","last_name":"Simkin","full_name":"Simkin, Michael"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Kwan MA, Sah A, Sawhney M, Simkin M. 2023. Substructures in Latin squares. Israel Journal of Mathematics. 256(2), 363–416.","chicago":"Kwan, Matthew Alan, Ashwin Sah, Mehtaab Sawhney, and Michael Simkin. “Substructures in Latin Squares.” Israel Journal of Mathematics. Springer Nature, 2023. https://doi.org/10.1007/s11856-023-2513-9.","ieee":"M. A. Kwan, A. Sah, M. Sawhney, and M. Simkin, “Substructures in Latin squares,” Israel Journal of Mathematics, vol. 256, no. 2. Springer Nature, pp. 363–416, 2023.","short":"M.A. Kwan, A. Sah, M. Sawhney, M. Simkin, Israel Journal of Mathematics 256 (2023) 363–416.","apa":"Kwan, M. A., Sah, A., Sawhney, M., & Simkin, M. (2023). Substructures in Latin squares. Israel Journal of Mathematics. Springer Nature. https://doi.org/10.1007/s11856-023-2513-9","ama":"Kwan MA, Sah A, Sawhney M, Simkin M. Substructures in Latin squares. Israel Journal of Mathematics. 2023;256(2):363-416. doi:10.1007/s11856-023-2513-9","mla":"Kwan, Matthew Alan, et al. “Substructures in Latin Squares.” Israel Journal of Mathematics, vol. 256, no. 2, Springer Nature, 2023, pp. 363–416, doi:10.1007/s11856-023-2513-9."},"date_created":"2023-10-22T22:01:14Z","doi":"10.1007/s11856-023-2513-9","date_published":"2023-09-01T00:00:00Z","page":"363-416","publication":"Israel Journal of Mathematics","day":"01","year":"2023","oa":1,"publisher":"Springer Nature","quality_controlled":"1","acknowledgement":"Sah and Sawhney were supported by NSF Graduate Research Fellowship Program DGE-1745302. Sah was supported by the PD Soros Fellowship. Simkin was supported by the Center of Mathematical Sciences and Applications at Harvard University.","department":[{"_id":"MaKw"}],"date_updated":"2023-10-31T11:27:30Z","status":"public","type":"journal_article","article_type":"original","_id":"14444","volume":256,"issue":"2","language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"eissn":["1565-8511"],"issn":["0021-2172"]},"intvolume":" 256","month":"09","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2202.05088","open_access":"1"}],"scopus_import":"1","oa_version":"Preprint","abstract":[{"lang":"eng","text":"We prove several results about substructures in Latin squares. First, we explain how to adapt our recent work on high-girth Steiner triple systems to the setting of Latin squares, resolving a conjecture of Linial that there exist Latin squares with arbitrarily high girth. As a consequence, we see that the number of order- n Latin squares with no intercalate (i.e., no 2×2 Latin subsquare) is at least (e−9/4n−o(n))n2. Equivalently, P[N=0]≥e−n2/4−o(n2)=e−(1+o(1))EN\r\n , where N is the number of intercalates in a uniformly random order- n Latin square. \r\nIn fact, extending recent work of Kwan, Sah, and Sawhney, we resolve the general large-deviation problem for intercalates in random Latin squares, up to constant factors in the exponent: for any constant 0<δ≤1 we have P[N≤(1−δ)EN]=exp(−Θ(n2)) and for any constant δ>0 we have P[N≥(1+δ)EN]=exp(−Θ(n4/3logn)). \r\nFinally, as an application of some new general tools for studying substructures in random Latin squares, we show that in almost all order- n Latin squares, the number of cuboctahedra (i.e., the number of pairs of possibly degenerate 2×2 submatrices with the same arrangement of symbols) is of order n4, which is the minimum possible. As observed by Gowers and Long, this number can be interpreted as measuring ``how associative'' the quasigroup associated with the Latin square is."}]},{"status":"public","conference":{"location":"Thessaloniki, Greece","end_date":"2023-10-06","start_date":"2023-10-03","name":"RV: Conference on Runtime Verification"},"type":"conference","_id":"14454","department":[{"_id":"ToHe"}],"date_updated":"2023-10-31T11:48:20Z","intvolume":" 14245","month":"10","main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2308.00341"}],"alternative_title":["LNCS"],"scopus_import":"1","oa_version":"Preprint","abstract":[{"text":"As AI and machine-learned software are used increasingly for making decisions that affect humans, it is imperative that they remain fair and unbiased in their decisions. To complement design-time bias mitigation measures, runtime verification techniques have been introduced recently to monitor the algorithmic fairness of deployed systems. Previous monitoring techniques assume full observability of the states of the (unknown) monitored system. Moreover, they can monitor only fairness properties that are specified as arithmetic expressions over the probabilities of different events. In this work, we extend fairness monitoring to systems modeled as partially observed Markov chains (POMC), and to specifications containing arithmetic expressions over the expected values of numerical functions on event sequences. The only assumptions we make are that the underlying POMC is aperiodic and starts in the stationary distribution, with a bound on its mixing time being known. These assumptions enable us to estimate a given property for the entire distribution of possible executions of the monitored POMC, by observing only a single execution. Our monitors observe a long run of the system and, after each new observation, output updated PAC-estimates of how fair or biased the system is. The monitors are computationally lightweight and, using a prototype implementation, we demonstrate their effectiveness on several real-world examples.","lang":"eng"}],"ec_funded":1,"volume":14245,"language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"eissn":["1611-3349"],"isbn":["9783031442667"],"issn":["0302-9743"]},"project":[{"_id":"62781420-2b32-11ec-9570-8d9b63373d4d","call_identifier":"H2020","grant_number":"101020093","name":"Vigilant Algorithmic Monitoring of Software"}],"title":"Monitoring algorithmic fairness under partial observations","external_id":{"arxiv":["2308.00341"]},"article_processing_charge":"No","author":[{"id":"40876CD8-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas A","orcid":"0000-0002-2985-7724","full_name":"Henzinger, Thomas A","last_name":"Henzinger"},{"id":"8121a2d0-dc85-11ea-9058-af578f3b4515","first_name":"Konstantin","full_name":"Kueffner, Konstantin","orcid":"0000-0001-8974-2542","last_name":"Kueffner"},{"id":"0834ff3c-6d72-11ec-94e0-b5b0a4fb8598","first_name":"Kaushik","last_name":"Mallik","orcid":"0000-0001-9864-7475","full_name":"Mallik, Kaushik"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Henzinger TA, Kueffner K, Mallik K. 2023. Monitoring algorithmic fairness under partial observations. 23rd International Conference on Runtime Verification. RV: Conference on Runtime Verification, LNCS, vol. 14245, 291–311.","chicago":"Henzinger, Thomas A, Konstantin Kueffner, and Kaushik Mallik. “Monitoring Algorithmic Fairness under Partial Observations.” In 23rd International Conference on Runtime Verification, 14245:291–311. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_15.","ama":"Henzinger TA, Kueffner K, Mallik K. Monitoring algorithmic fairness under partial observations. In: 23rd International Conference on Runtime Verification. Vol 14245. Springer Nature; 2023:291-311. doi:10.1007/978-3-031-44267-4_15","apa":"Henzinger, T. A., Kueffner, K., & Mallik, K. (2023). Monitoring algorithmic fairness under partial observations. In 23rd International Conference on Runtime Verification (Vol. 14245, pp. 291–311). Thessaloniki, Greece: Springer Nature. https://doi.org/10.1007/978-3-031-44267-4_15","ieee":"T. A. Henzinger, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness under partial observations,” in 23rd International Conference on Runtime Verification, Thessaloniki, Greece, 2023, vol. 14245, pp. 291–311.","short":"T.A. Henzinger, K. Kueffner, K. Mallik, in:, 23rd International Conference on Runtime Verification, Springer Nature, 2023, pp. 291–311.","mla":"Henzinger, Thomas A., et al. “Monitoring Algorithmic Fairness under Partial Observations.” 23rd International Conference on Runtime Verification, vol. 14245, Springer Nature, 2023, pp. 291–311, doi:10.1007/978-3-031-44267-4_15."},"oa":1,"quality_controlled":"1","publisher":"Springer Nature","acknowledgement":"This work is supported by the European Research Council under Grant No.: ERC-2020-AdG 101020093.","date_created":"2023-10-29T23:01:15Z","date_published":"2023-10-01T00:00:00Z","doi":"10.1007/978-3-031-44267-4_15","page":"291-311","publication":"23rd International Conference on Runtime Verification","day":"01","year":"2023"},{"_id":"14446","tmp":{"short":"CC BY-NC-ND (4.0)","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png"},"article_type":"original","type":"journal_article","status":"public","date_updated":"2023-10-31T12:12:47Z","ddc":["510"],"file_date_updated":"2023-10-31T12:07:23Z","department":[{"_id":"ChLa"}],"abstract":[{"lang":"eng","text":"Recent work has paid close attention to the first principle of Granger causality, according to which cause precedes effect. In this context, the question may arise whether the detected direction of causality also reverses after the time reversal of unidirectionally coupled data. Recently, it has been shown that for unidirectionally causally connected autoregressive (AR) processes X → Y, after time reversal of data, the opposite causal direction Y → X is indeed detected, although typically as part of the bidirectional X↔ Y link. As we argue here, the answer is different when the measured data are not from AR processes but from linked deterministic systems. When the goal is the usual forward data analysis, cross-mapping-like approaches correctly detect X → Y, while Granger causality-like approaches, which should not be used for deterministic time series, detect causal independence X → Y. The results of backward causal analysis depend on the predictability of the reversed data. Unlike AR processes, observables from deterministic dynamical systems, even complex nonlinear ones, can be predicted well forward, while backward predictions can be difficult (notably when the time reversal of a function leads to one-to-many relations). To address this problem, we propose an approach based on models that provide multiple candidate predictions for the target, combined with a loss function that consideres only the best candidate. The resulting good forward and backward predictability supports the view that unidirectionally causally linked deterministic dynamical systems X → Y can be expected to detect the same link both before and after time reversal."}],"oa_version":"Published Version","scopus_import":"1","intvolume":" 23","month":"08","publication_status":"published","publication_identifier":{"eissn":["1335-8871"]},"language":[{"iso":"eng"}],"file":[{"creator":"dernst","date_updated":"2023-10-31T12:07:23Z","file_size":2639783,"date_created":"2023-10-31T12:07:23Z","file_name":"2023_MeasurementScienceRev_Jakubik.pdf","access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"b069cc10fa6a7c96b2bc9f728165f9e6","file_id":"14476","success":1}],"license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","issue":"4","volume":23,"citation":{"apa":"Jakubík, J., Phuong, M., Chvosteková, M., & Krakovská, A. (2023). Against the flow of time with multi-output models. Measurement Science Review. Sciendo. https://doi.org/10.2478/msr-2023-0023","ama":"Jakubík J, Phuong M, Chvosteková M, Krakovská A. Against the flow of time with multi-output models. Measurement Science Review. 2023;23(4):175-183. doi:10.2478/msr-2023-0023","ieee":"J. Jakubík, M. Phuong, M. Chvosteková, and A. Krakovská, “Against the flow of time with multi-output models,” Measurement Science Review, vol. 23, no. 4. Sciendo, pp. 175–183, 2023.","short":"J. Jakubík, M. Phuong, M. Chvosteková, A. Krakovská, Measurement Science Review 23 (2023) 175–183.","mla":"Jakubík, Jozef, et al. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review, vol. 23, no. 4, Sciendo, 2023, pp. 175–83, doi:10.2478/msr-2023-0023.","ista":"Jakubík J, Phuong M, Chvosteková M, Krakovská A. 2023. Against the flow of time with multi-output models. Measurement Science Review. 23(4), 175–183.","chicago":"Jakubík, Jozef, Mary Phuong, Martina Chvosteková, and Anna Krakovská. “Against the Flow of Time with Multi-Output Models.” Measurement Science Review. Sciendo, 2023. https://doi.org/10.2478/msr-2023-0023."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"Yes","author":[{"last_name":"Jakubík","full_name":"Jakubík, Jozef","first_name":"Jozef"},{"first_name":"Phuong","id":"3EC6EE64-F248-11E8-B48F-1D18A9856A87","full_name":"Bui Thi Mai, Phuong","last_name":"Bui Thi Mai"},{"first_name":"Martina","last_name":"Chvosteková","full_name":"Chvosteková, Martina"},{"first_name":"Anna","last_name":"Krakovská","full_name":"Krakovská, Anna"}],"title":"Against the flow of time with multi-output models","acknowledgement":"The work was supported by the Scientific Grant Agency of the Ministry of Education of the Slovak Republic and the Slovak Academy of Sciences, projects APVV-21-0216, VEGA2-0096-21 and VEGA 2-0023-22.","oa":1,"quality_controlled":"1","publisher":"Sciendo","year":"2023","has_accepted_license":"1","publication":"Measurement Science Review","day":"01","page":"175-183","date_created":"2023-10-22T22:01:15Z","doi":"10.2478/msr-2023-0023","date_published":"2023-08-01T00:00:00Z"},{"type":"journal_article","article_type":"review","status":"public","_id":"14443","department":[{"_id":"GaNo"}],"date_updated":"2023-10-31T12:17:20Z","scopus_import":"1","intvolume":" 80","month":"10","abstract":[{"lang":"eng","text":"Importance Climate change, pollution, urbanization, socioeconomic inequality, and psychosocial effects of the COVID-19 pandemic have caused massive changes in environmental conditions that affect brain health during the life span, both on a population level as well as on the level of the individual. How these environmental factors influence the brain, behavior, and mental illness is not well known.\r\nObservations A research strategy enabling population neuroscience to contribute to identify brain mechanisms underlying environment-related mental illness by leveraging innovative enrichment tools for data federation, geospatial observation, climate and pollution measures, digital health, and novel data integration techniques is described. This strategy can inform innovative treatments that target causal cognitive and molecular mechanisms of mental illness related to the environment. An example is presented of the environMENTAL Project that is leveraging federated cohort data of over 1.5 million European citizens and patients enriched with deep phenotyping data from large-scale behavioral neuroimaging cohorts to identify brain mechanisms related to environmental adversity underlying symptoms of depression, anxiety, stress, and substance misuse.\r\nConclusions and Relevance This research will lead to the development of objective biomarkers and evidence-based interventions that will significantly improve outcomes of environment-related mental illness."}],"oa_version":"None","pmid":1,"volume":80,"issue":"10","publication_status":"published","publication_identifier":{"eissn":["2168-6238"]},"language":[{"iso":"eng"}],"article_processing_charge":"No","external_id":{"pmid":["37610741"]},"author":[{"first_name":"Gunter","last_name":"Schumann","full_name":"Schumann, Gunter"},{"last_name":"Andreassen","full_name":"Andreassen, Ole A.","first_name":"Ole A."},{"last_name":"Banaschewski","full_name":"Banaschewski, Tobias","first_name":"Tobias"},{"first_name":"Vince D.","last_name":"Calhoun","full_name":"Calhoun, Vince D."},{"full_name":"Clinton, Nicholas","last_name":"Clinton","first_name":"Nicholas"},{"first_name":"Sylvane","last_name":"Desrivieres","full_name":"Desrivieres, Sylvane"},{"full_name":"Brandlistuen, Ragnhild Eek","last_name":"Brandlistuen","first_name":"Ragnhild Eek"},{"first_name":"Jianfeng","full_name":"Feng, Jianfeng","last_name":"Feng"},{"first_name":"Soeren","full_name":"Hese, Soeren","last_name":"Hese"},{"first_name":"Esther","full_name":"Hitchen, Esther","last_name":"Hitchen"},{"first_name":"Per","last_name":"Hoffmann","full_name":"Hoffmann, Per"},{"last_name":"Jia","full_name":"Jia, Tianye","first_name":"Tianye"},{"first_name":"Viktor","last_name":"Jirsa","full_name":"Jirsa, Viktor"},{"first_name":"Andre F.","last_name":"Marquand","full_name":"Marquand, Andre F."},{"full_name":"Nees, Frauke","last_name":"Nees","first_name":"Frauke"},{"last_name":"Nöthen","full_name":"Nöthen, Markus M.","first_name":"Markus M."},{"last_name":"Novarino","full_name":"Novarino, Gaia","orcid":"0000-0002-7673-7178","first_name":"Gaia","id":"3E57A680-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Polemiti, Elli","last_name":"Polemiti","first_name":"Elli"},{"first_name":"Markus","full_name":"Ralser, Markus","last_name":"Ralser"},{"first_name":"Michael","last_name":"Rapp","full_name":"Rapp, Michael"},{"first_name":"Kerstin","last_name":"Schepanski","full_name":"Schepanski, Kerstin"},{"first_name":"Tamara","last_name":"Schikowski","full_name":"Schikowski, Tamara"},{"first_name":"Mel","last_name":"Slater","full_name":"Slater, Mel"},{"first_name":"Peter","full_name":"Sommer, Peter","last_name":"Sommer"},{"first_name":"Bernd Carsten","last_name":"Stahl","full_name":"Stahl, Bernd Carsten"},{"full_name":"Thompson, Paul M.","last_name":"Thompson","first_name":"Paul M."},{"first_name":"Sven","last_name":"Twardziok","full_name":"Twardziok, Sven"},{"full_name":"Van Der Meer, Dennis","last_name":"Van Der Meer","first_name":"Dennis"},{"full_name":"Walter, Henrik","last_name":"Walter","first_name":"Henrik"},{"first_name":"Lars","last_name":"Westlye","full_name":"Westlye, Lars"}],"title":"Addressing global environmental challenges to mental health using population neuroscience: A review","citation":{"mla":"Schumann, Gunter, et al. “Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience: A Review.” JAMA Psychiatry, vol. 80, no. 10, American Medical Association, 2023, pp. 1066–74, doi:10.1001/jamapsychiatry.2023.2996.","apa":"Schumann, G., Andreassen, O. A., Banaschewski, T., Calhoun, V. D., Clinton, N., Desrivieres, S., … Westlye, L. (2023). Addressing global environmental challenges to mental health using population neuroscience: A review. JAMA Psychiatry. American Medical Association. https://doi.org/10.1001/jamapsychiatry.2023.2996","ama":"Schumann G, Andreassen OA, Banaschewski T, et al. Addressing global environmental challenges to mental health using population neuroscience: A review. JAMA Psychiatry. 2023;80(10):1066-1074. doi:10.1001/jamapsychiatry.2023.2996","short":"G. Schumann, O.A. Andreassen, T. Banaschewski, V.D. Calhoun, N. Clinton, S. Desrivieres, R.E. Brandlistuen, J. Feng, S. Hese, E. Hitchen, P. Hoffmann, T. Jia, V. Jirsa, A.F. Marquand, F. Nees, M.M. Nöthen, G. Novarino, E. Polemiti, M. Ralser, M. Rapp, K. Schepanski, T. Schikowski, M. Slater, P. Sommer, B.C. Stahl, P.M. Thompson, S. Twardziok, D. Van Der Meer, H. Walter, L. Westlye, JAMA Psychiatry 80 (2023) 1066–1074.","ieee":"G. Schumann et al., “Addressing global environmental challenges to mental health using population neuroscience: A review,” JAMA Psychiatry, vol. 80, no. 10. American Medical Association, pp. 1066–1074, 2023.","chicago":"Schumann, Gunter, Ole A. Andreassen, Tobias Banaschewski, Vince D. Calhoun, Nicholas Clinton, Sylvane Desrivieres, Ragnhild Eek Brandlistuen, et al. “Addressing Global Environmental Challenges to Mental Health Using Population Neuroscience: A Review.” JAMA Psychiatry. American Medical Association, 2023. https://doi.org/10.1001/jamapsychiatry.2023.2996.","ista":"Schumann G, Andreassen OA, Banaschewski T, Calhoun VD, Clinton N, Desrivieres S, Brandlistuen RE, Feng J, Hese S, Hitchen E, Hoffmann P, Jia T, Jirsa V, Marquand AF, Nees F, Nöthen MM, Novarino G, Polemiti E, Ralser M, Rapp M, Schepanski K, Schikowski T, Slater M, Sommer P, Stahl BC, Thompson PM, Twardziok S, Van Der Meer D, Walter H, Westlye L. 2023. Addressing global environmental challenges to mental health using population neuroscience: A review. JAMA Psychiatry. 80(10), 1066–1074."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"American Medical Association","quality_controlled":"1","page":"1066-1074","date_created":"2023-10-22T22:01:14Z","doi":"10.1001/jamapsychiatry.2023.2996","date_published":"2023-10-01T00:00:00Z","year":"2023","publication":"JAMA Psychiatry","day":"01"}]