Disease control can induce both demographic and evolutionary responses in host-parasite systems. Foreseeing the outcome of control therefore requires knowledge of the eco-evolutionary feedback between control and system. Previous work has assumed that control strategies have a homogeneous effect on the parasite population. However, this is not true when control targets those traits that confer to the parasite heterogeneous levels of resistance, which can additionally be related to other key parasite traits, through evolutionary trade-offs. In this work, we develop a minimal model coupling epidemiological and evolutionary dynamics to explore possible trait-dependent effects of control strategies. Particularly, we consider a parasite expressing continuous levels of a trait determining resource exploitation, and a control treatment that can be either positively or negatively correlated with that trait. We demonstrate the potential of trait-dependent control by considering that the decision maker may want to minimise both the damage caused by the disease and the use of treatment, due to possible environmental or economic costs. We identify efficient strategies showing that the optimal type of treatment depends on the amount applied. Our results pave the way for the study of control strategies based on evolutionary constraints, such as collateral sensitivity and resistance costs, which are receiving increasing attention for both public health and agricultural purposes.

Cylindrical interfaces occur in sheared or deformed emulsions and as biological or technological lipid monolayer or bilayer tubules. Like the corresponding spherical droplets and vesicles, these cylinderlike surfaces may host orientational order with n-fold rotational symmetry, for example in the positions of lipid molecules or of spherical nanoparticles. We examine how that order interacts with and induces shape modulations of cylindrical interfaces. While on spherical droplets 2n topological defects necessarily exist and can induce icosahedral droplet shapes, the cylindrical topology is compatible with a defect-free patterning. Nevertheless, once a modulation is introduced by a mechanism such as spontaneous curvature, nontrivial patterns of order, including ones with excess defects, emerge and have nonlinear effects on the shape of the tube. By examining the equilibrium energetics of the system analytically and with a lattice-based Markov chain Monte Carlo simulation, we predict low-temperature morphologies of modulated cylindrical interfaces hosting orientational order. A shape modulation induces a banded pattern of alternatingly isotropic and ordered interfacial material. Furthermore, cylindrical systems can be divided into type I, without defects, and type II, which go through a spectrum of defect states with up to 4n excess defects. The character of the curvature-induced shape transition from unmodulated to modulated cylinders is continuous or discontinuous accordingly.

9 Optimising the use of chemical pesticide is required in order to reduce the inevitable environmental and economic costs related to it. The consequences of chemical control are particularly tricky to foresee in the presence of pathogens, displaying heterogeneous traits involved in their life cycle, because its effect will likely differ across the population. In this work, we investigate the effects of trait-dependent pesticide on heterogeneous plant pathogens, by means of a minimal model connecting evolutionary and agricultural states of the system. We model a pathogen population displaying continuous levels of virulence and transmission. Control strategies are modelled by the quantity of pesticide released and its degree of correlation with the pathogen’s heterogeneous traits. We show that the pathogen population can adapt towards opposite evolutionary states, that may be reversed by chemical control due to its heterogeneous selective pressure. This dual behaviour triggers saturating effects in yield production, with respect to pesticide use. As a consequence, we show that maximising yield production and minimising pesticide application are conflicting objectives. We identify Pareto-efficient solutions, where the optimal pesticide type depends on the applied quantity. Our results provide a theoretical framework to explore how to harness heterogeneity in pathogen populations to our advantage. 10 Crop pathogens and pests (P&Ps) are responsible for reduction in the yield and quality of agricultural production. They 11 cause important economic losses and reduce food security at household, national and global level1. Nowadays, although 12 alternative practices to protect crops are gaining scientific support2, 3, the use of chemical pesticides is still the primary means 13 to control P&Ps and faces an increasing food demand worldwide4. Although the use of pesticides, among other practices, has 14 led to a greater than twofold increase in food production during the last century5, worldwide surveys have documented the 15 contamination and impact of pesticide residues in soils, terrestrial and aquatic ecosystems, and their toxic effects on humans 16 and nonhuman biota5, 6. A reduction in the use of pesticide is sought worldwide and demanded by the EU pesticide Regulation 17 N 1107/2009. A report on pesticide residues in food is due every year by the European Food Security Agency (EFSA)7. Recent 18 works suggest that pesticide use could be reduced, without impacting crop productivity and profitability, through the adoption 19 of new production strategies and optimisation; this is particularly true in those cases with high pesticide use2, 5. 20 Mathematical modelling provides an excellent tool, in addition to field and lab experiments, to assess the efficacy of different 21 control strategies8–10. Significant attention has been devoted to design and explore different strategies to overcome the 22 problem of pesticide resistance11. Models are often framed in terms of sensitive versus resistant pathogen strains12–14, and 23 aim at understanding optimal spatial15, 16, and temporal17, 18 patterns of pesticide release. Foreseeing the consequences of 24 a prolonged use of pesticide is particularly tricky when the pathogen displays a more general heterogeneity, i.e. when the 25 composition of the pathogen population is more complex than simply resistant versus sensitive. In these populations, individuals 26 characterised by genetically related variants, may differ from each other by phenotype traits possibly involved in the pathogen’s 27 virulence, transmission, viability etc. This phenomenon is ubiquitous in plant pathogens, including viruses19, bacteria20, 21, 28 fungi22–24. When such heterogeneity is maintained (rather than transient), the population is then trait-structured. In such 29 populations, the overall effect of a control strategy will depend on the trait distribution of the heterogeneous pathogen, which in 30 turn will be affected by the control’s selective pressure25, 26. Ultimately, the performance of any management scenario will 31 result from the complex interplay between the epidemiological plant-pathogen interactions, and the pathogen’s evolutionary 32 dynamics. However, despite few exceptions (e.g. see Shaw et al.27), in the context of pest management, heterogeneous pathogen 33 populations are modelled only rarely. 34 In this work, we move away from the sensitive/resistant duality, and investigate the role of continuous heterogeneity in pest 35 control. In the framework of a classical type SIS model, we consider a trait-structured pathogen population and we investigate 36 the evolutionary dynamics of its trait distribution28. The trait variable might determine the pathogen levels of virulence, 37 transmission and the pesticide sensitivity. This framework will allow to account for the transmission-virulence trade-off, as 38 well as to possible heterogeneous pesticide effects. The transmission-virulence trade-off hypothesis, introduced to explain the 39 evolution of intermediate levels of virulence29, 30, assumes a positive correlation between the two traits, so that an increase in 40

Realistic fitness landscapes generally display a redundancy-fitness trade-off: highly fit trait configurations are inevitably rare, while less fit trait configurations are expected to be more redundant. The resulting sub-optimal patterns in the fitness distribution are typically described by means of effective formulations, where redundancy provided by the presence of neutral contributions is modelled implicitly, e.g. with a bias of the mutation process. However, the extent to which effective formulations are compatible with explicitly redundant landscapes is yet to be understood, as well as the consequences of a potential miss-match. Here we investigate the effects of such trade-off on the evolution of phenotype-structured populations, characterised by continuous quantitative traits. We consider a typical replication-mutation dynamics, and we model redundancy by means of two dimensional landscapes displaying both selective and neutral traits. We show that asymmetries of the landscapes will generate neutral contributions to the marginalised fitness-level description, that cannot be described by effective formulations, nor disentangled by the full trait distribution. Rather, they appear as effective sources, whose magnitude depends on the geometry of the landscape. Our results highlight new important aspects on the nature of sub-optimality. We discuss practical implications for rapidly mutant populations such as pathogens and cancer cells, where the qualitative knowledge of their trait and fitness distributions can drive disease management and intervention policies.

Patterns can form when the uniform state of any system is unstable so that some non-uniform motif grows in amplitude. Here, we identify an alternative way to form non-trivial structures, which we call "ghost-patterns". Ghost-patterns emerge from noisy initial conditions when all non-uniform modes decay in amplitude except for one non-trivial motif which fails to decay. Hence, in seeking structured states, it is not necessary to find positive growth rates. We demonstrate ghost-patterns in an idealized non-equilibrium model intended to emulate draining thin-film suspensions.

All organisms descend from populations with limited resources, so it is clear why evolution should select strategies that win resources at the expense of competitors. Less obvious is how altruistic behaviours evolve, whereby an individual helps others despite expense to itself. Modelling simple agents using evolutionary game theory, it is shown that steady states of extreme altruism can evolve when pay-offs are very rare compared with death. In these states, agents give away most of their wealth. A new theorem for general evolutionary models shows that, when pay-offs are rare, evolution no longer selects strategies to maximize income (average pay-off), but to minimize the risk of missing-out entirely on a rare resource. Principles revealed by the model are widely applicable, where the game represents rare life-changing events: disasters or gluts.

It was shown in [PRL 114, 138301 (2015)] that a remarkably simple dynamical model exhibits many of the complex flow regimes and non-equilibrium phase transitions characteristic of complex fluids. By removing extraneous detail, this simplest microscopic model of non-Newtonian flow can reveal the universal physics relevant to all complex fluids. Here we present more detailed results and a full derivation of the model's compact mean-field constitutive relation, with great potential scope for insights into universality and tractable mathematics. By enforcing local conservation of angular momentum, the one-dimensional (1D) XY-model (originally used for equilibrium magnetic systems) can be driven into various flow regimes, including simple Newtonian behaviour, shear banding, solid-liquid coexistence and slip-plane motion. The model demonstrates that the phenomenon of shear banding does not rely on details of tensorial stress fields, but can exist in 1D.

We consider biased ensembles of trajectories associated with large deviations of currents in equilibrium systems. The biased ensembles are characterised by non-zero currents and lack the time-reversal symmetry of the equilibrium state. In cases where the equilibrium system has an inversion symmetry which is broken by the bias, we show that the biased ensembles retain a generalised time-reversal symmetry, involving a spatial transformation that inverts the current. This means that these ensembles lack dissipation. Hence, they differ significantly from non-equilibrium steady states where currents are induced by external forces. One consequence of this result is that maximum entropy assumptions (MaxEnt/MaxCal), widely used for modelling thermal systems away from equilibrium, have quite unexpected implications, including apparent superfluid behaviour in a classical model of shear flow.

We find that the classical one-dimensional $XY$ model, with angular-momentum-conserving Langevin dynamics, mimics the non-Newtonian flow regimes characteristic of soft matter when subjected to counterrotating boundaries. An elaborate steady-state phase diagram has continuous and first-order transitions between states of uniform flow, shear-banding, solid-fluid coexistence and slip planes. Results of numerical studies and a concise mean-field constitutive relation offer a paradigm for diverse nonequilibrium complex fluids.

We dynamically simulate fractionation (partitioning of particle species) during spinodal gas-liquid separation of a size-polydisperse colloid, using polydispersity up to ~40% and a skewed parent size distribution. We introduce a novel coarse-grained Voronoi method to minimise size bias in measuring local volume fraction, along with a variety of spatial correlation functions which detect fractionation without requiring a clear distinction between the phases. These can be applied whether or not a system is phase separated, to determine structural correlations in particle size, and generalise easily to other kinds of polydispersity (charge, shape, etc.). We measure fractionation in both mean size and polydispersity between the phases, its direction differing between model interaction potentials which are identical in the monodisperse case. These qualitative features are predicted by a perturbative theory requiring only a monodisperse reference as input. The results show that intricate fractionation takes place almost from the start of phase separation, so can play a role even in nonequilibrium arrested states. The methods for characterisation of inhomogeneous polydisperse systems could in principle be applied to experiment as well as modelling.

We investigate the correspondence between a nonequilibrium ensemble defined via the distribution of phase-space paths of a Hamiltonian system and a system driven into a steady state by nonequilibrium boundary conditions. To discover whether the nonequilibrium path ensemble adequately describes the physics of a driven system, we measure transition rates in a simple one-dimensional model of rotors with Newtonian dynamics and purely conservative interactions. We compare those rates with known properties of the nonequilibrium path ensemble. In doing so, we establish effective protocols for the analysis of transition rates in nonequilibrium quasisteady states. Transition rates between potential wells and also between phase-space elements are studied and found to exhibit distinct properties, the more coarse-grained potential wells being effectively further from equilibrium. In all cases the results from the boundary-driven system are close to the path-ensemble predictions, but the question of equivalence of the two remains open.

We investigate the effect of metastable gas-liquid (G-L) separation on crystal growth in a system of either monodisperse or slightly size-polydisperse square well particles, using a simulation setup that allows us to focus on the growth of a single crystal. Our system parameters are such that, inside the metastable G-L binodal, a macroscopic layer of the gas phase "coats" the crystal as it grows, consistent with experiment and theoretical free energy considerations. Crucially, the effect of this metastable G-L separation on the crystal growth rate depends qualitatively on whether the system is polydisperse. We measure reduced polydispersity and qualitatively different local size ordering in the crystal relative to the fluid, proposing that the required fractionation is dynamically facilitated by the gas layer. Our results show that polydispersity and metastability, both ubiquitous in soft matter, must be considered in tandem if their dynamical effects are to be understood.

Within the Free-Volume Asakura-Oosawa-Vrij (FVAO) theory of colloid-polymer mixtures, we show that unphysical gas-liquid binodals predicted in the regime of small attraction range (i.e. polymer size) are caused in part by the use of the Carnahan-Starling (CS) hard sphere (HS) reference free energy. Replacement of the CS expression with an alternative dramatically affects predicted phase behaviour and, for polydisperse colloid, the resultant fractionation predictions. Although short-range attractions render FVAO, as a perturbative HS-based theory, less accurate anyway, we argue that the particular effects of CS in this regime are an important consideration -- usually ignored -- in the evaluation of such theories. We refer to a variety of literature exhibiting similarly inaccurate gas-liquid binodals, and suggest CS's status as the de facto choice of hard sphere reference should be carefully considered where short-range attractions are present.

We have studied the magnetic microstates arising from single-shot thermalization processes that occur during growth in artificial square spin ices. The populations of different vertex types can be controlled by the system's lattice constant, as well as by the deposition of different material underlayers. The statistics of these populations are well described by a simple model based on the canonical ensemble, which is used to infer an effective temperature for an arrested microstate. The normalized energy level spacings of the different magnetic vertex configurations are found to be very close to those predicted for a point-dipole model: this is shown to be a very good approximation to energy level spacings calculated for finite-sized cuboid magnetic bodies. States prepared with a rotating field (an athermal method commonly used to lower the energy of these systems) cannot be described by this model, showing that such a method does not induce a near-equilibrium state.

Background and ObjectivesWhile blood donation is traditionally described as a behaviour motivated by pure altruism, the assessment of altruism in the blood donation literature has not been theoretically informed. Drawing on theories of altruism from psychology, economics and evolutionary biology, it is argued that a theoretically derived psychometric assessment of altruism is needed. Such a measure is developed in this study that can be used to help inform both our understanding of the altruistic motives of blood donors and recruitment intervention strategies.Materials and MethodsA cross‐sectional survey (N = 414), with a 1‐month behavioural follow‐up (time 2, N = 77), was designed to assess theoretically derived constructs from psychological, economic and evolutionary biological theories of altruism. Theory of planned behaviour (TPB) variables and co‐operation were also assessed at time 1 and a measure of behavioural co‐operation at time 2.ResultsFive theoretical dimensions (impure altruism, kinship, self‐regarding motives, reluctant altruism and egalitarian warm glow) of altruism were identified through factor analyses. These five altruistic motives differentiated blood donors from non‐donors (donors scored higher on impure altruism and reluctant altruism), showed incremental validity over TPB constructs to predict donor intention and predicted future co‐operative behaviour.ConclusionsThese findings show that altruism in the context of blood donation is multifaceted and complex and, does not reflect pure altruism. This has implication for recruitment campaigns that focus solely on pure altruism.

Within the Free-Volume Asakura-Oosawa-Vrij (FVAO) theory of colloid-polymer mixtures, we show that unphysical gas-liquid binodals predicted in the regime of small attraction range (i.e. polymer size) are caused in part by the use of the Carnahan-Starling (CS) hard sphere (HS) reference free energy. Replacement of the CS expression with an alternative dramatically affects predicted phase behaviour and, for polydisperse colloid, the resultant fractionation predictions. Although short-range attractions render FVAO, as a perturbative HS-based theory, less accurate anyway, we argue that the particular effects of CS in this regime are an important consideration -- usually ignored -- in the evaluation of such theories. We refer to a variety of literature exhibiting similarly inaccurate gas-liquid binodals, and suggest CS's status as the de facto choice of hard sphere reference should be carefully considered where short-range attractions are present.

We present a data analysis procedure that provides the solution to a long-standing issue in microrheology studies, i.e. the evaluation of the fluids' linear viscoelastic properties from the analysis of a finite set of experimental data, describing (for instance) the time-dependent mean-square displacement of suspended probe particles experiencing Brownian fluctuations. We report, for the first time in the literature, the linear viscoelastic response of an optically trapped bead suspended in a Newtonian fluid, over the entire range of experimentally accessible frequencies. The general validity of the proposed method makes it transferable to the majority of microrheology and rheology techniques.

Background: A supply of blood, provided by volunteer donors, is crucial for all health services. Recent epidemiological data suggest that experienced blood donors are motivated by warm-glow (it makes me feel good) and novice donors by a newly identified motivation of reluctant altruism (RA: donating because no-one else will), rather than pure altruism. These new and surprising findings require further investigation. A series of behavioural economic (BE) games to assess warm-glow and psychometric analyses were used to examine the validity of these findings. Methods: Data were gathered from a psychometric experimental study (N = 450) and four lab based economic games (N = 210). Findings: The BE games confirm blood donors are warm-glow givers. Reluctant altruism emerges as a clear factor and the strongest predictor of intentions to donate in non-donors, current and relapsed donors. Discussion: Implications for theories of altruism, blood donation and recruitment of blood donors are discussed.