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Introduction: Research productivity has been linked to a country's intellectual and economic wealth. Further analysis is needed to assess the association between the distribution of research across disciplines and the economic status of countries., Methods: By using 55 years of data, spanning 1962 to 2017, of Elsevier publications across a large set of research disciplines and countries globally, this manuscript explores the relationship and evolution of relative research productivity across different disciplines through a network analysis. It also explores the associations of those with economic productivity categories, as measured by the World Bank economic classification. Additional analysis of discipline similarities is possible by exploring the cross-country evolution of those disciplines., Results: Results show similarities in the relative importance of research disciplines among most high-income countries, with larger idiosyncrasies appearing among the remaining countries. This group of high-income countries shows similarities in the dynamics of the relative distribution of research productivity over time, forming a stable research productivity cluster. Lower income countries form smaller, more independent and evolving clusters, and differ significantly from each other and from higher income countries in the relative importance of their research emphases. Country-based similarities in research productivity profiles also appear to be influenced by geographical proximity., Conclusions: This new form of analyses of research productivity, and its relation to economic status, reveals novel insights to the dynamics of the economic and research structure of countries. This allows for a deeper understanding of the role a country's research structure may play in shaping its economy, and also identification of benchmark resource allocations across disciplines for developing countries., Competing Interests: German Molina owns a private firm called Idalion Capital Group, but nobody else in that company worked on this manuscript. He was part of the project as an independent researcher during his free time, and this work was not performed as part of his work at said company. There are no patents, products in development or marketed products to declare. This does not alter our adherence to all the PLOS ONE policies on sharing data and materials.

The accumulation of knowledge required to produce economic value is a process that often relates to nations economic growth. Some decades ago many authors, in the absence of other available indicators, used to rely on certain measures of human capital such as years of schooling, enrollment rates, or literacy. In this paper, we show that the predictive power of years of education as a proxy for human capital started to dwindle in 1990 when the schooling of nations began to be homogenized. We developed a structural equation model that estimates a metric of human capital that is less sensitive than average years of education and remains as a significant predictor of economic growth when tested with both cross-section data and panel data., Competing Interests: The authors have declared that no competing interests exist.

Computer experiments that mirror the evolutionary dynamics of sexual and asexual organisms as they occur in nature were used to test features proposed to explain the evolution of sexual recombination. Results show that this evolution is better described as a network of interactions between possible sexual forms, including diploidy, thelytoky, facultative sex, assortation, bisexuality, and division of labor between the sexes, rather than a simple transition from parthenogenesis to sexual recombination. Diploidy was shown to be fundamental for the evolution of sex; bisexual reproduction emerged only among anisogamic diploids with a synergistic division of reproductive labor; and facultative sex was more likely to evolve among haploids practicing assortative mating. Looking at the evolution of sex as a complex system through individual-based simulations explains better the diversity of sexual strategies known to exist in nature, compared to classical analytical models.

We argue that making accept/reject decisions on scientific hypotheses, including a recent call for changing the canonical alpha level from p = 0.05 to p = 0.005, is deleterious for the finding of new discoveries and the progress of science. Given that blanket and variable alpha levels both are problematic, it is sensible to dispense with significance testing altogether. There are alternatives that address study design and sample size much more directly than significance testing does; but none of the statistical tools should be taken as the new magic method giving clear-cut mechanical answers. Inference should not be based on single studies at all, but on cumulative evidence from multiple independent studies. When evaluating the strength of the evidence, we should consider, for example, auxiliary assumptions, the strength of the experimental design, and implications for applications. To boil all this down to a binary decision based on a p -value threshold of 0.05, 0.01, 0.005, or anything else, is not acceptable.

Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust a textual description from its original scale of observation to an arbitrarily selected scale, (b) a method to model the structure of any textual description based on the shape of the symbol frequency profiles, and (c) the concept of higher order entropy as the entropy associated with the deviations of a frequency-ranked symbol profile from a perfect Zipfian profile. We call this diversity index the '2nd Order Entropy'. Applying these methods to a variety of musical pieces showed how the space of 'symbolic specific diversity-entropy' and that of '2nd order entropy' captures characteristics that are unique to each music type, style, composer and genre. Some clustering of these properties around each musical category is shown. These methods allow us to visualize a historic trajectory of academic music across this space, from medieval to contemporary academic music. We show that the description of musical structures using entropy, symbol frequency profiles and specific symbolic diversity allows us to characterize traditional and popular expressions of music. These classification techniques promise to be useful in other disciplines for pattern recognition and machine learning.

W.D. Hamilton's Inclusive Fitness Theory explains the conditions that favor the emergence and maintenance of social cooperation. Today we know that these include direct and indirect benefits an agent obtains by its actions, and through interactions with kin and with genetically unrelated individuals. That is, in addition to kin-selection, assortation or homophily, and social synergies drive the evolution of cooperation. An Extended Inclusive Fitness Theory (EIFT) synthesizes the natural selection forces acting on biological evolution and on human economic interactions by assuming that natural selection driven by inclusive fitness produces agents with utility functions that exploit assortation and synergistic opportunities. This formulation allows to estimate sustainable cost/benefit threshold ratios of cooperation among organisms and/or economic agents, using existent analytical tools, illuminating our understanding of the dynamic nature of society, the evolution of cooperation among kin and non-kin, inter-specific cooperation, co-evolution, symbioses, division of labor and social synergies. EIFT helps to promote an interdisciplinary cross fertilization of the understanding of synergy by, for example, allowing to describe the role for division of labor in the emergence of social synergies, providing an integrated framework for the study of both, biological evolution of social behavior and economic market dynamics. Another example is a bio-economic understanding of the motivations of terrorists, which identifies different forms of terrorism.

Do different fields of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed two diverging optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in many journals containing a small number of articles. The natural sciences seem to adapt their research strategies to landscapes with large concentrated knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small isolated knowledge clusters. Similar bipolar distributions were obtained when comparing levels of insularity estimated by indicators of international collaboration and levels of country-self citations: researchers in academic areas with many journals such as social sciences, arts and humanities, were the most isolated, and that was true in different regions of the world. The work shows that quantitative measures estimating differences between academic disciplines improve our understanding of different research strategies, eventually helping interdisciplinary research and may be also help improve science policies worldwide.

Scientific productivity of middle income countries correlates stronger with present and future wealth than indices reflecting its financial, social, economic or technological sophistication. We identify the contribution of the relative productivity of different scientific disciplines in predicting the future economic growth of a nation. Results show that rich and poor countries differ in the relative proportion of their scientific output in the different disciplines: countries with higher relative productivity in basic sciences such as physics and chemistry had the highest economic growth in the following five years compared to countries with a higher relative productivity in applied sciences such as medicine and pharmacy. Results suggest that the economies of middle income countries that focus their academic efforts in selected areas of applied knowledge grow slower than countries which invest in general basic sciences.

Hymenoptera have haploid males, which produce sperm by cloning. Sperm selection theory predicts that because termites have diploid males that produce genetically diverse sperm, they may profit from a high sperm surplus (large K), whereas Hymenoptera (ants, bees and wasps) should produce few sperm per fertilization (low K). Male reproductive "kings", which continuously provide spermatozoa during the whole life of the queen, allow for a large K. Available empirical evidence confirms the existence of a large difference in K between diploid insects, especially Blattodea (Isoptera) (K > 1,000), and haplo-diploids such as Hymenoptera (K < 10). The available data suggest that sperm selection may be an important evolutionary force for species with diploid, but not haploid males.

Males of Aedes aegypti mosquitoes formed swarms in the laboratory, triggered by the onset of the photophase or by the presence of odors from a rat (which is a potential host for females). The swarm attracted both males and females and increased mating activity. The number of copulas per mosquito was positively correlated with the number of mosquitoes in the swarm and with the duration of the swarm. Swarming and mating activity increased with the presence of a host for females. Young sexually immature males, less than 24 h old, flew but did not swarm nor copulate. Observations using an olfactometer showed that swarming males produced a volatile pheromone that stimulates the flying activity of females at a distance. Females also produce a volatile attractant. The results suggest that males, and possibly also females, produce an aggregation pheromone that attracts males and females towards the swarm. The characteristics of the pheromone-mediated swarm may be described as a 3-dimensional lek. Our results suggest that the development of pheromone-based control systems and/or pheromone traps for the monitoring of vector populations is feasible, adding a new tool to combat this vector of several human pathogens.

Chemical analyses by GC-MS of the metapleural glands (MG) from workers of Solenopsis invicta and S. geminata revealed for the first time the chemical composition of these glands and showed small differences between the two species. The MG of both species contain oleic, stearic, linoleic, and palmitic acid. Both ants, in addition, have small but significant amounts of hydrocarbons in their MG reservoir, which are the same as those found in their postpharyngeal glands (PPG). The PPG of both species contain alkanes, alkenes, and Me-branched alkanes. Each species is characterized by a specific composition of PPG chemicals with some overlap between species. These results suggest that the MG synthesizes mainly palmitic, linoleic, oleic, and stearic acids in these two ants, whereas PPG contains hydrocarbon mixes that widely vary between these two phylogenetically related species.

The concept of altruism is used in very different forms by computer scientists,economists, philosophers, social scientists, psychologists and biologists. Yet, in order to be useful in social simulations, the concept "altruism" requires a more precise meaning. A quantitative formulation is proposed here, based on the cost/benefit analysis of the altruist and of society at large. This formulation is applied in the analysis of the social dynamic working of behaviors that have been called "altruistic punishments", using the agent based computer model Sociodynamica. The simulations suggest that "altruistic punishment" on its own cannot maintain altruistic behaviors. "Altruistic behavior" is sustainable in the long term only if these behaviors trigger synergetic forces in society that eventually make them produce benefits to most individuals. The simulations suggest however that "altruistic punishment" may work as a "social investment", and is thus better called "decentralized social punishment". This behavior is very efficient in enforcing social norms. The efficiency of decentralized social punishment in enforcing norms was dependent on the type of labor structured of the virtual society. I conclude that what is called "altruistic punishment" emerges as a type of social investment that can evolve either through individual and/or group selection, as a successful device for changing or enforcing norms in a society. Social simulations will help us in better understanding the underlying dynamic working of such devices.