Statistics of extinction and survival in Lotka-Volterra systems

We analyze purely competitive many-species Lotka-Volterra systems with random interaction matrices, focusing the attention on statistical properties of their asymptotic states. Generic features of the evolution are outlined from a semiquantitative analysis of the phase-space structure, and extensive numerical simulations are performed to study the statistics of the extinctions. We find that the number of surviving species depends strongly on the statistical properties of the interaction matrix, and that the probability of survival is weakly correlated to specific initial conditions.Comment: Previous version had error in authors. 11 pages, including 5 figure

The 1:1 resonance in Extrasolar Systems: Migration from planetary to satellite orbits

We present families of symmetric and asymmetric periodic orbits at the 1/1 resonance, for a planetary system consisting of a star and two small bodies, in comparison to the star, moving in the same plane under their mutual gravitational attraction. The stable 1/1 resonant periodic orbits belong to a family which has a planetary branch, with the two planets moving in nearly Keplerian orbits with non zero eccentricities and a satellite branch, where the gravitational interaction between the two planets dominates the attraction from the star and the two planets form a close binary which revolves around the star. The stability regions around periodic orbits along the family are studied. Next, we study the dynamical evolution in time of a planetary system with two planets which is initially trapped in a stable 1/1 resonant periodic motion, when a drag force is included in the system. We prove that if we start with a 1/1 resonant planetary system with large eccentricities, the system migrates, due to the drag force, {\it along the family of periodic orbits} and is finally trapped in a satellite orbit. This, in principle, provides a mechanism for the generation of a satellite system: we start with a planetary system and the final stage is a system where the two small bodies form a close binary whose center of mass revolves around the star.Comment: to appear in Cel.Mech.Dyn.Ast

Thermodynamic and Kinetic Parameters for Calcite Nucleation on Peptoid and Model Scaffolds:A Step toward Nacre Mimicry

The production of novel composite materials, assembled using biomimetic polymers known as peptoids (N-substituted glycines) to nucleate CaCO3, can open new pathways for advanced material design. However, a better understanding of the heterogeneous CaCO3 nucleation process is a necessary first step. We determined the thermodynamic and kinetic parameters for calcite nucleation on self-assembled monolayers (SAMs) of nanosheet-forming peptoid polymers and simpler, alkanethiol analogues. We used nucleation rate studies to determine the net interfacial free energy (γ net) for the peptoid-calcite interface and for SAMs terminated with carboxyl headgroups, amine headgroups, or a mix of the two. We compared the results with γ net determined from dynamic force spectroscopy (DFS) and from density functional theory (DFT), using COSMO-RS simulations. Calcite nucleation has a lower thermodynamic barrier on the peptoid surface than on carboxyl and amine SAMs. From the relationship between nucleation rate (J 0) and saturation state, we found that under low-saturation conditions, i.e. <3.3 (pH 9.0), nucleation on the peptoid substrate was faster than that on all of the model surfaces, indicating a thermodynamic drive toward heterogeneous nucleation. When they are taken together, our results indicate that nanosheet-forming peptoid monolayers can serve as an organic template for CaCO3 polymorph growth

The distribution of global tidal marshes from Earth observation data

Aim: Tidal marsh ecosystems are heavily impacted by human activities, highlighting a pressing need to address gaps in our knowledge of their distribution. To better understand the global distribution and changes in tidal marsh extent, and identify opportunities for their conservation and restoration, it is critical to develop a spatial knowledge base of their global occurrence. Here, we develop a globally consistent tidal marsh distribution map for the year 2020 at 10-m resolution. Location: Global. Time period: 2020. Major taxa studied: Tidal marshes. Methods: To map the location of the world's tidal marshes at 10-m resolution, we applied a random forest classification model to Earth observation data from the year 2020. We trained the classification model with a reference dataset developed to support distribution mapping of coastal ecosystems, and predicted the spatial distribution of tidal marshes between 60° N and 60° S. We validated the tidal marsh map using standard accuracy assessment methods, with our final map having an overall accuracy score of 0.85. Results: We estimate the global extent of tidal marshes in 2020 to be 52,880 km2 (95 CI: 32,030 to 59,780 km2) distributed across 120 countries and territories. Tidal marsh distribution is centred in temperate and Arctic regions, with nearly half of the global extent of tidal marshes occurring in the temperate Northern Atlantic (45) region. At the national scale, over a third of the global extent (18,510 km2; CI: 11,200–20,900) occurs within the USA. Main conclusions: Our analysis provides the most detailed spatial data on global tidal marsh distribution to date and shows that tidal marshes occur in more countries and across a greater proportion of the world's coastline than previous mapping studies. Our map fills a major knowledge gap regarding the distribution of the world's coastal ecosystems and provides the baseline needed for measuring changes in tidal marsh extent and estimating their value in terms of ecosystem services. © 2024 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd

Optimal low-thrust trajectories to asteroids through an algorithm based on differential dynamic programming

In this paper an optimisation algorithm based on Differential Dynamic Programming is applied to the design of rendezvous and fly-by trajectories to near Earth objects. Differential dynamic programming is a successive approximation technique that computes a feedback control law in correspondence of a fixed number of decision times. In this way the high dimensional problem characteristic of low-thrust optimisation is reduced into a series of small dimensional problems. The proposed method exploits the stage-wise approach to incorporate an adaptive refinement of the discretisation mesh within the optimisation process. A particular interpolation technique was used to preserve the feedback nature of the control law, thus improving robustness against some approximation errors introduced during the adaptation process. The algorithm implements global variations of the control law, which ensure a further increase in robustness. The results presented show how the proposed approach is capable of fully exploiting the multi-body dynamics of the problem; in fact, in one of the study cases, a fly-by of the Earth is scheduled, which was not included in the first guess solution

The influence of gene expression time delays on Gierer-Meinhardt pattern formation systems

There are numerous examples of morphogen gradients controlling long range signalling in developmental and cellular systems. The prospect of two such interacting morphogens instigating long range self-organisation in biological systems via a Turing bifurcation has been explored, postulated, or implicated in the context of numerous developmental processes. However, modelling investigations of cellular systems typically neglect the influence of gene expression on such dynamics, even though transcription and translation are observed to be important in morphogenetic systems. In particular, the influence of gene expression on a large class of Turing bifurcation models, namely those with pure kinetics such as the Gierer–Meinhardt system, is unexplored. Our investigations demonstrate that the behaviour of the Gierer–Meinhardt model profoundly changes on the inclusion of gene expression dynamics and is sensitive to the sub-cellular details of gene expression. Features such as concentration blow up, morphogen oscillations and radical sensitivities to the duration of gene expression are observed and, at best, severely restrict the possible parameter spaces for feasible biological behaviour. These results also indicate that the behaviour of Turing pattern formation systems on the inclusion of gene expression time delays may provide a means of distinguishing between possible forms of interaction kinetics. Finally, this study also emphasises that sub-cellular and gene expression dynamics should not be simply neglected in models of long range biological pattern formation via morphogens

Effect of the Surface on the Electron Quantum Size Levels and Electron g-Factor in Spherical Semiconductor Nanocrystals

The structure of the electron quantum size levels in spherical nanocrystals is studied in the framework of an eight--band effective mass model at zero and weak magnetic fields. The effect of the nanocrystal surface is modeled through the boundary condition imposed on the envelope wave function at the surface. We show that the spin--orbit splitting of the valence band leads to the surface--induced spin--orbit splitting of the excited conduction band states and to the additional surface--induced magnetic moment for electrons in bare nanocrystals. This additional magnetic moment manifests itself in a nonzero surface contribution to the linear Zeeman splitting of all quantum size energy levels including the ground 1S electron state. The fitting of the size dependence of the ground state electron g factor in CdSe nanocrystals has allowed us to determine the appropriate surface parameter of the boundary conditions. The structure of the excited electron states is considered in the limits of weak and strong magnetic fields.Comment: 11 pages, 4 figures, submitted to Phys. Rev.

Differential influences of early growth and social factors on young children's cognitive performance in four low-and-middle-income birth cohorts (Brazil, Guatemala, Philippines, and South Africa)

Background: Studies relating childhood cognitive development to poor linear growth seldom take adequate account of social conditions related to both, leading to a focus on nutrition interventions. We aimed to assess the roles of both biological and social conditions in determining early childhood cognition, mediated by birthweight and early linear growth. Methods: After exploratory structural equation modelling to identify determining factors, we tested direct and indirect paths to cognitive performance through birthweight and child height-for-age at 2 years, assessed between 4 and 8.5 years of age among 2448 children in four birth cohort studies in low-and-middle-income countries (Brazil, Guatemala, Philippines and South Africa). Determinants were compared across the cohorts. Findings: Three factors yielded excellent fit, comprising birth endowment (primarily maternal age and birth order), household resources (crowding, dependency) and parental capacity (parental education). We estimated their strength together with maternal height in determining cognitive performance. Percentage shares of total effects of the four determinants show a marked transition from mainly biological determinants of birth weight (birth endowment 34%) and maternal height (30%) compared to household resources (25%) and parental capacity (11%), through largely economic determinants of height at 2 years (household resources (60%) to cognitive performance being predominantly determined by parental capacity (64%) followed by household resources (29%). The largely biological factor, birth endowment (maternal age and birth order) contributed only 7% to childhood cognitive performance and maternal height was insignificant. In summary, the combined share of social total effects (household resources and parental capacity) rises from 36∙2% on birth weight, to 78∙2% on height for age at 24 m, and 93∙4% on cognitive functioning. Interpretation: Across four low- and middle-income contexts, cognition in childhood is influenced more by the parental capacity of families and their economic resources than by birth weight and early linear growth. Improving children's cognitive functioning requires multi-sectoral interventions to improve parental education and enhance their economic wellbeing, interventions that are known to improve also early childhood growth