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In linguistics, there is little consensus on how to define, measure, and compare complexity across languages. We propose to take the diversity of viewpoints as a given, and to capture the complexity of a language by a vector of measurements, rather than a single value. We then assess the statistical support for two controversial hypotheses: the trade-off hypothesis and the equi-complexity hypothesis. We furnish meta-analyses of 28 complexity metrics applied to texts written in overall 80 typologically diverse languages. The trade-off hypothesis is partially supported, in the sense that around one third of the significant correlations between measures are negative. The equi-complexity hypothesis, on the other hand, is largely confirmed. While we find evidence for complexity differences in the domains of morphology and syntax, the overall complexity vectors of languages turn out virtually indistinguishable.

Pollen monitoring has traditionally been carried out using manual methods first developed in the early 1950s. Although this technique has been recently standardised, it suffers from several drawbacks, notably data usually only being available with a delay of 3–9 days and usually delivered at a daily resolution. Several automatic instruments have come on to the market over the past few years, with more new devices also under development. This paper provides a comprehensive overview of all available and developing automatic instruments, how they measure, how they identify airborne pollen, what impacts measurement quality, as well as what potential there is for further advancement in the field of bioaerosol monitoring.

Standards for manual pollen and fungal spore monitoring have been established based on several decades of experience, tests, and research. New technological and methodological advancements have led to the development of a range of different automatic instruments for which no standard yet exist. This paper aims to provide an overview of aspects that need to be considered for automatic pollen and fungal spore monitoring, including a set of guidelines and recommendations. It covers issues relevant to developing an automatic monitoring network, from the instrument design and calibration through algorithm development to site selection criteria. Despite no official standard yet existing, it is essential that all aspects of the measurement chain are carried out in a manner that is as standardised as possible to ensure high-quality data and information can be provided to end-users.

Pollen exposure weakens the immunity against certain seasonal respiratory viruses by diminishing the antiviral interferon response. Here we investigate whether the same applies to the pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is sensitive to antiviral interferons, if infection waves coincide with high airborne pollen concentrations. Our original hypothesis was that more airborne pollen would lead to increases in infection rates. To examine this, we performed a cross-sectional and longitudinal data analysis on SARS-CoV-2 infection, airborne pollen, and meteorological factors. Our dataset is the most comprehensive, largest possible worldwide from 130 stations, across 31 countries and five continents. To explicitly investigate the effects of social contact, we additionally considered population density of each study area, as well as lockdown effects, in all possible combinations: without any lockdown, with mixed lockdown?no lockdown regime, and under complete lockdown. We found that airborne pollen, sometimes in synergy with humidity and temperature, explained, on average, 44% of the infection rate variability. Infection rates increased after higher pollen concentrations most frequently during the four previous days. Without lockdown, an increase of pollen abundance by 100 pollen/m3 resulted in a 4% average increase of infection rates. Lockdown halved infection rates under similar pollen concentrations. As there can be no preventive measures against airborne pollen exposure, we suggest wide dissemination of pollen?virus coexposure dire effect information to encourage high-risk individuals to wear particle filter masks during high springtime pollen concentrations. © 2021 National Academy of Sciences. All rights reserved., 1.1.1.2/VIAA/2/18/283; European Cooperation in Science and Technology, COST: CA18226; Academy of Finland, AKA: 318194, PS4A; Ministerio de Educación, Cultura y Deporte, MECD: FPU15/01668; Department of the Environment, Australian Government; Lietuvos Mokslo Taryba; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, MPNTR: 451-03-68/2020-14/200358; European Social Fund, ESF: 09.3.3-LMT-K-712-01-0066; Helmholtz Association; Christine Kühne – Center for Allergy Research and Education, CK-CARE, ACKNOWLEDGMENTS. We thank Mr. Luis-Leopold Moelter and Mr. Mehmet Gökkaya for assistance in overall data curation. The study was partly implemented in the frame of the European Cooperation in Science and Technology (EU-COST) program, "New approaches in detection of pathogens and aeroallergens (ADOPT)," Grant CA18226 (EU Framework Program Horizon 2020). D.B. and C.T.-H. were supported by the Helmholtz Climate Initiative (HI-CAM), Mitigation and Adaptation. A.Ch. and D.V. were supported by the Municipality of Thessaloniki, Greece (Directorate for the Management of the Urban Environment, Department of Environment). This research has been partly supported by the European Social Fund (Project 09.3.3-LMT-K-712-01-0066) under grant agreement with the Research Council of Lithuania (LMTLT). The study was also partly conducted within the frame of the project of the European Community European Regional Development Fund (EC ERDF) and PostDoc Latvia (Grant 1.1.1.2/VIAA/2/18/283). M.S. acknowledges the Academy of Finland (Project PS4A, Grant 318194). We thank the Department of Health and Rehabilitation of Vinnytsia Regional Council, Ukraine, for providing the numbers of COVID-19 cases. A.H.A. acknowledges Angel Chaves and the Government of Navarra: Institute of Public and Labor Health of Navarra, within LIFE-IP NAdatpa-CC (LIFE16 IPC/ES/000001). A.P. was supported by a predoctoral grant financed by the Ministry of Education, Culture and Sports of Spain, in the Program for the Promotion of Talent and its Employability (Grant FPU15/01668). B.S. acknowledges the Ministry of Education, Science, and Technological Development of the Republic of Serbia (Grant 451-03-68/2020-14/200358). C.T.H. acknowledges the Christine Kühne–Center for Allergy Research and Education (CK-CARE), and The Initiative and Networking Fund of the Helmholtz Association (Immunology & Inflammation). We thank Jan Bumberger, Marcus Karsten, Paul Remmler, Jan C. Simon, and Regina Treudler for data provision and curation from Leipzig, Germany. We thank Claudia Langford Brown and Dana Flanders for statistical advice and scientific discussions. We thank Penelope Jones, Edith Bucher, Reyhan Gumusburun, Haydar Soydaner Karakus, Su Ozgur, and Asli Tetik Vardarli for data curation.

This paper reviews recent progress in modeling collective behaviors in myxobacteria using lattice gas cellular automata approach (LGCA). Myxobacteria are social bacteria that swarm, glide on surfaces and feed cooperatively. When starved, tens of thousands of cells change their movement pattern from outward spreading to inward concentration; they form aggregates that become fruiting bodies. Cells inside fruiting bodies differentiate into round, nonmotile, environmentally resistant spores. Traditionally, cell aggregation has been considered to imply chemotaxis, a long-range cell interaction. However, myxobacteria aggregation is the consequence of direct cell-contact interactions, not chemotaxis. In this paper, we review biological LGCA models based on local cell–cell contact signaling that have reproduced the rippling, streaming, aggregating and sporulation stages of the fruiting body formation in myxobacteria.

Myxobacteria provide one of the simplest models of cell–cell interaction and organized cell movement leading to cellular differentiation. When starved, tens of thousands of cells change their movement pattern from outward spreading to inward concentration; they form aggregates that become fruiting bodies. Cells inside fruiting bodies differentiate into round, nonmotile, environmentally resistant spores. Traditionally, cell aggregation has been considered to imply chemotaxis; a long-range cell interaction. However, myxobacterial aggregation is the consequence of direct cell-contact interactions, not chemotaxis. We present here a 3D stochastic lattice-gas cellular automata model of cell aggregation based on local cell–cell contact, and no chemotaxis. We demonstrate that a 3D discrete stochastic model can simulate two stages of cell aggregation. First, a “traffic jam” forms embedded in a field of motile cells. The jam then becomes an aggregation center that accumulates more cells. We show that, at high cell density, cells stream around the traffic jam, generating a 3D hemispherical mound. Later, when the nuclear traffic jam dissolves, the aggregation center becomes a 3D ring of streaming cells.

Myxobacterial cells are social; they swarm by gliding on surfaces as they feed cooperatively. When they sense starvation, tens of thousands of cells change their movement pattern from outward spreading to inward concentration and form aggregates that become fruiting bodies. Cells inside fruiting bodies differentiate into round, nonmotile, environmentally resistant spores. Traditionally, cell aggregation has been considered to imply chemotaxis, a long-range cell interaction that shares many features of chemical reaction–diffusion dynamics. The biological evidence, however, suggests that Myxococcus xanthus aggregation is the consequence of direct cell-contact interactions that are different from chemotaxis. To test whether local interactions suffice to explain the formation of fruiting bodies and the differentiation of spores within them, we have simulated the process. In this article, we present a unified 3D model that reproduces in one continuous simulation all the stages of fruiting-body formation that have been experimentally observed: nonsymmetric initial aggregates (traffic jams), streams, formation of toroidal aggregates, hemispherical 3D mounds, and finally sporulation within the fruiting body.