Beyond aridification: multiple explanations for the elevated diversification of cacti in the New World Succulent Biome

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106989/1/nph12752.pd

Positivity of the English language

Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is broadly invariant with respect to frequency of word use.Comment: Manuscript: 9 pages, 3 tables, 5 figures; Supplementary Information: 12 pages, 3 tables, 8 figure

Learning and innovative elements of strategy adoption rules expand cooperative network topologies

Cooperation plays a key role in the evolution of complex systems. However, the level of cooperation extensively varies with the topology of agent networks in the widely used models of repeated games. Here we show that cooperation remains rather stable by applying the reinforcement learning strategy adoption rule, Q-learning on a variety of random, regular, small-word, scale-free and modular network models in repeated, multi-agent Prisoners Dilemma and Hawk-Dove games. Furthermore, we found that using the above model systems other long-term learning strategy adoption rules also promote cooperation, while introducing a low level of noise (as a model of innovation) to the strategy adoption rules makes the level of cooperation less dependent on the actual network topology. Our results demonstrate that long-term learning and random elements in the strategy adoption rules, when acting together, extend the range of network topologies enabling the development of cooperation at a wider range of costs and temptations. These results suggest that a balanced duo of learning and innovation may help to preserve cooperation during the re-organization of real-world networks, and may play a prominent role in the evolution of self-organizing, complex systems.Comment: 14 pages, 3 Figures + a Supplementary Material with 25 pages, 3 Tables, 12 Figures and 116 reference

Emergence of metapopulations and echo chambers in mobile agents

Multi-agent models often describe populations segregated either in the physical space, i.e. subdivided in metapopulations, or in the ecology of opinions, i.e. partitioned in echo chambers. Here we show how the interplay between homophily and social influence controls the emergence of both kinds of segregation in a simple model of mobile agents, endowed with a continuous opinion variable. In the model, physical proximity determines a progressive convergence of opinions but differing opinions result in agents moving away from each others. This feedback between mobility and social dynamics determines to the onset of a stable dynamical metapopulation scenario where physically separated groups of like-minded individuals interact with each other through the exchange of agents. The further introduction of confirmation bias in social interactions, defined as the tendency of an individual to favor opinions that match his own, leads to the emergence of echo chambers where different opinions can coexist also within the same group. We believe that the model may be of interest to researchers investigating the origin of segregation in the offline and online world

Modeling and Inferring Cleavage Patterns in Proliferating Epithelia

The regulation of cleavage plane orientation is one of the key mechanisms driving epithelial morphogenesis. Still, many aspects of the relationship between local cleavage patterns and tissue-level properties remain poorly understood. Here we develop a topological model that simulates the dynamics of a 2D proliferating epithelium from generation to generation, enabling the exploration of a wide variety of biologically plausible cleavage patterns. We investigate a spectrum of models that incorporate the spatial impact of neighboring cells and the temporal influence of parent cells on the choice of cleavage plane. Our findings show that cleavage patterns generate “signature” equilibrium distributions of polygonal cell shapes. These signatures enable the inference of local cleavage parameters such as neighbor impact, maternal influence, and division symmetry from global observations of the distribution of cell shape. Applying these insights to the proliferating epithelia of five diverse organisms, we find that strong division symmetry and moderate neighbor/maternal influence are required to reproduce the predominance of hexagonal cells and low variability in cell shape seen empirically. Furthermore, we present two distinct cleavage pattern models, one stochastic and one deterministic, that can reproduce the empirical distribution of cell shapes. Although the proliferating epithelia of the five diverse organisms show a highly conserved cell shape distribution, there are multiple plausible cleavage patterns that can generate this distribution, and experimental evidence suggests that indeed plants and fruitflies use distinct division mechanisms

Quantum Gravity in 2+1 Dimensions: The Case of a Closed Universe

In three spacetime dimensions, general relativity drastically simplifies, becoming a ``topological'' theory with no propagating local degrees of freedom. Nevertheless, many of the difficult conceptual problems of quantizing gravity are still present. In this review, I summarize the rather large body of work that has gone towards quantizing (2+1)-dimensional vacuum gravity in the setting of a spatially closed universe.Comment: 61 pages, draft of review for Living Reviews; comments, criticisms, additions, missing references welcome; v2: minor changes, added reference

Coupled Information Diffusion–Pest Dynamics Models Predict Delayed Benefits of Farmer Cooperation in Pest Management Programs

Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' “diffusion of innovation theory”. In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations

Simian virus 40 vectors for pulmonary gene therapy

<p>Abstract</p> <p>Background</p> <p>Sepsis remains the leading cause of death in critically ill patients. One of the primary organs affected by sepsis is the lung, presenting as the Acute Respiratory Distress Syndrome (ARDS). Organ damage in sepsis involves an alteration in gene expression, making gene transfer a potential therapeutic modality. This work examines the feasibility of applying simian virus 40 (SV40) vectors for pulmonary gene therapy.</p> <p>Methods</p> <p>Sepsis-induced ARDS was established by cecal ligation double puncture (2CLP). SV40 vectors carrying the luciferase reporter gene (SV/<it>luc) </it>were administered intratracheally immediately after sepsis induction. Sham operated (SO) as well as 2CLP rats given intratracheal PBS or adenovirus expressing luciferase served as controls. Luc transduction was evaluated by <it>in vivo </it>light detection, immunoassay and luciferase mRNA detection by RT-PCR in tissue harvested from septic rats. Vector abundance and distribution into alveolar cells was evaluated using immunostaining for the SV40 VP1 capsid protein as well as by double staining for VP1 and for the surfactant protein C (proSP-C). Immunostaining for T-lymphocytes was used to evaluate the cellular immune response induced by the vector.</p> <p>Results</p> <p>Luc expression measured by <it>in vivo </it>light detection correlated with immunoassay from lung tissue harvested from the same rats. Moreover, our results showed vector presence in type II alveolar cells. The vector did not induce significant cellular immune response.</p> <p>Conclusion</p> <p>In the present study we have demonstrated efficient uptake and expression of an SV40 vector in the lungs of animals with sepsis-induced ARDS. These vectors appear to be capable of <it>in vivo </it>transduction of alveolar type II cells and may thus become a future therapeutic tool.</p