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  • 1. Bar-Dolev, Maya
    et al.
    Celik, Yeliz
    Wettlaufer, John S.
    Stockholms universitet, Nordiska institutet för teoretisk fysik (Nordita).
    Davies, Peter L.
    Braslavsky, Ido
    New insights into ice growth and melting modifications by antifreeze proteins2012Inngår i: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 9, nr 77, s. 3249-3259Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Antifreeze proteins (AFPs) evolved in many organisms, allowing them to survive in cold climates by controlling ice crystal growth. The specific interactions of AFPs with ice determine their potential applications in agriculture, food preservation and medicine. AFPs control the shapes of ice crystals in a manner characteristic of the particular AFP type. Moderately active AFPs cause the formation of elongated bipyramidal crystals, often with seemingly defined facets, while hyperactive AFPs produce more varied crystal shapes. These different morphologies are generally considered to be growth shapes. In a series of bright light and fluorescent microscopy observations of ice crystals in solutions containing different AFPs, we show that crystal shaping also occurs during melting. In particular, the characteristic ice shapes observed in solutions of most hyperactive AFPs are formed during melting. We relate these findings to the affinities of the hyperactive AFPs for the basal plane of ice. Our results demonstrate the relation between basal plane affinity and hyperactivity and show a clear difference in the ice-shaping mechanisms of most moderate and hyperactive AFPs. This study provides key aspects associated with the identification of hyperactive AFPs.

  • 2.
    Bottinelli, Arianna
    et al.
    Stockholms universitet, Nordiska institutet för teoretisk fysik (Nordita).
    Gherardi, Marco
    Barthelemy, Marc
    Efficiency and shrinking in evolving networks2019Inngår i: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 16, nr 154, artikkel-id 20190101Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Characterizing the spatio-temporal evolution of networks is a central topic in many disciplines. While network expansion has been studied thoroughly, less is known about how empirical networks behave when shrinking. For transportation networks, this is especially relevant on account of their connection with the socio-economical substrate, and we focus here on the evolution of the French railway network from its birth in 1840 to 2000, in relation to the country's demographic dynamics. The network evolved in parallel with technology (e.g. faster trains) and under strong constraints, such as preserving a good population coverage and balancing cost and efficiency. We show that the shrinking phase that started in 1930 decreased the total length of the network while preserving efficiency and population coverage: efficiency and robustness remained remarkably constant while the total length of the network shrank by 50% between 1930 and 2000, and the total travel time and time-diameter decreased by more than 75% during the same period. Moreover, shrinking the network did not affect the overall accessibility with an average travel time that decreases steadily since its formation. This evolution leads naturally to an increase in transportation multimodality (such as a massive use of cars) and shows the importance of considering together transportation modes acting at different spatial scales. More generally, our results suggest that shrinking is not necessarily associated with a decay in performance and functions but can be beneficial in terms of design goals and can be part of the natural evolution of an adaptive network.

  • 3.
    Britton, Tom
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Tomba, Gianpaolo Scalia
    Estimation in emerging epidemics: biases and remedies2019Inngår i: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 16, nr 150, artikkel-id 20180670Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    When analysing new emerging infectious disease outbreaks, one typically has observational data over a limited period of time and several parameters to estimate, such as growth rate, the basic reproduction number R-0, the case fatality rate and distributions of serial intervals, generation times, latency and incubation times and times between onset of symptoms, notification, death and recovery/discharge. These parameters form the basis for predicting a future outbreak, planning preventive measures and monitoring the progress of the disease outbreak. We study inference problems during the emerging phase of an outbreak, and point out potential sources of bias, with emphasis on: contact tracing backwards in time, replacing generation times by serial intervals, multiple potential infectors and censoring effects amplified by exponential growth. These biases directly affect the estimation of, for example, the generation time distribution and the case fatality rate, but can then propagate to other estimates such as R-0 and growth rate. We propose methods to remove or at least reduce bias using statistical modelling. We illustrate the theory by numerical examples and simulations.

  • 4.
    Leung, Ka Yin
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Ball, Frank
    Sirl, David
    Britton, Tom
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Individual preventive social distancing during an epidemic may have negative population-level outcomes2018Inngår i: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 15, nr 145, artikkel-id 20180296Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The outbreak of an infectious disease in a human population can lead to individuals responding with preventive measures in an attempt to avoid getting infected. This leads to changes in contact patterns. However, as we show in this paper, rational behaviour at the individual level, such as social distancing from infectious contacts, may not always be beneficial for the population as a whole. We use epidemic network models to demonstrate the potential negative consequences at the population level. We take into account the social structure of the population through several network models. As the epidemic evolves, susceptible individuals may distance themselves from their infectious contacts. Some individuals replace their lost social connections by seeking new ties. If social distancing occurs at a high rate at the beginning of an epidemic, then this can prevent an outbreak from occurring. However, we show that moderate social distancing can worsen the disease outcome, both in the initial phase of an outbreak and the final epidemic size. Moreover, the same negative effect can arise in real-world networks. Our results suggest that one needs to be careful when targeting behavioural changes as they could potentially worsen the epidemic outcome. Furthermore, network structure crucially influences the way that individual-level measures impact the epidemic at the population level. These findings highlight the importance of careful analysis of preventive measures in epidemic models.

  • 5. Marais, Adriana
    et al.
    Adams, Betony
    Ringsmuth, Andrew K.
    VU University Amsterdam, The Netherlands; The University of Queensland, Australia.
    Ferretti, Marco
    Gruber, J. Michael
    Hendrikx, Ruud
    Schuld, Maria
    Smith, Samuel L.
    Sinayskiy, Ilya
    Krüger, Tjaart P. J.
    Petruccione, Francesco
    van Grondelle, Rienk
    The future of quantum biology2018Inngår i: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 15, nr 148, artikkel-id 20180640Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Biological systems are dynamical, constantly exchanging energy and matter with the environment in order to maintain the non-equilibrium state synonymous with living. Developments in observational techniques have allowed us to study biological dynamics on increasingly small scales. Such studies have revealed evidence of quantum mechanical effects, which cannot be accounted for by classical physics, in a range of biological processes. Quantum biology is the study of such processes, and here we provide an outline of the current state of the field, as well as insights into future directions.

  • 6.
    Trapman, Pieter
    et al.
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Ball, Frank
    Dhersin, Jean-Stephane
    Viet, Chi
    Wallinga, Jacco
    Britton, Tom
    Stockholms universitet, Naturvetenskapliga fakulteten, Matematiska institutionen.
    Inferring R-0 in emerging epidemics-the effect of common population structure is small2016Inngår i: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 13, nr 121, artikkel-id 20160288Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    When controlling an emerging outbreak of an infectious disease, it is essential to know the key epidemiological parameters, such as the basic reproduction number R-0 and the control effort required to prevent a large outbreak. These parameters are estimated from the observed incidence of new cases and information about the infectious contact structures of the population in which the disease spreads. However, the relevant infectious contact structures for new, emerging infections are often unknown or hard to obtain. Here, we show that, for many common true underlying heterogeneous contact structures, the simplification to neglect such structures and instead assume that all contacts are made homogeneously in the whole population results in conservative estimates for R-0 and the required control effort. This means that robust control policies can be planned during the early stages of an outbreak, using such conservative estimates of the required control effort.

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