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Concept: Complexity


The complexity of chess matches has attracted broad interest since its invention. This complexity and the availability of large number of recorded matches make chess an ideal model systems for the study of population-level learning of a complex system. We systematically investigate the move-by-move dynamics of the white player’s advantage from over seventy thousand high level chess matches spanning over 150 years. We find that the average advantage of the white player is positive and that it has been increasing over time. Currently, the average advantage of the white player is [Formula: see text]0.17 pawns but it is exponentially approaching a value of 0.23 pawns with a characteristic time scale of 67 years. We also study the diffusion of the move dependence of the white player’s advantage and find that it is non-Gaussian, has long-ranged anti-correlations and that after an initial period with no diffusion it becomes super-diffusive. We find that the duration of the non-diffusive period, corresponding to the opening stage of a match, is increasing in length and exponentially approaching a value of 15.6 moves with a characteristic time scale of 130 years. We interpret these two trends as a resulting from learning of the features of the game. Additionally, we find that the exponent [Formula: see text] characterizing the super-diffusive regime is increasing toward a value of 1.9, close to the ballistic regime. We suggest that this trend is due to the increased broadening of the range of abilities of chess players participating in major tournaments.

Concepts: Emergence, Complexity, Systems theory, Trend, Complex number, Complex system, Chess, The Advantage


We present a novel formulation for biochemical reaction networks in the context of protein signal transduction. The model consists of input-output transfer functions, which are derived from differential equations, using stable equilibria. We select a set of “source” species, which are interpreted as input signals. Signals are transmitted to all other species in the system (the “target” species) with a specific delay and with a specific transmission strength. The delay is computed as the maximal reaction time until a stable equilibrium for the target species is reached, in the context of all other reactions in the system. The transmission strength is the concentration change of the target species. The computed input-output transfer functions can be stored in a matrix, fitted with parameters, and even recalled to build dynamical models on the basis of state changes. By separating the temporal and the magnitudinal domain we can greatly simplify the computational model, circumventing typical problems of complex dynamical systems. The transfer function transformation of biochemical reaction systems can be applied to mass-action kinetic models of signal transduction. The paper shows that this approach yields significant novel insights while remaining a fully testable and executable dynamical model for signal transduction. In particular we can deconstruct the complex system into local transfer functions between individual species. As an example, we examine modularity and signal integration using a published model of striatal neural plasticity. The modularizations that emerge correspond to a known biological distinction between calcium-dependent and cAMP-dependent pathways. Remarkably, we found that overall interconnectedness depends on the magnitude of inputs, with higher connectivity at low input concentrations and significant modularization at moderate to high input concentrations. This general result, which directly follows from the properties of individual transfer functions, contradicts notions of ubiquitous complexity by showing input-dependent signal transmission inactivation.

Concepts: Molecular biology, Mathematics, Systems, Emergence, Complexity, Systems theory, Complex system, Transfer function


The proteome of human brain synapses is highly complex and is mutated in over 130 diseases. This complexity arose from two whole-genome duplications early in the vertebrate lineage. Zebrafish are used in modelling human diseases; however, its synapse proteome is uncharacterized, and whether the teleost-specific genome duplication (TSGD) influenced complexity is unknown. We report the characterization of the proteomes and ultrastructure of central synapses in zebrafish and analyse the importance of the TSGD. While the TSGD increases overall synapse proteome complexity, the postsynaptic density (PSD) proteome of zebrafish has lower complexity than mammals. A highly conserved set of ∼1,000 proteins is shared across vertebrates. PSD ultrastructural features are also conserved. Lineage-specific proteome differences indicate that vertebrate species evolved distinct synapse types and functions. The data sets are a resource for a wide range of studies and have important implications for the use of zebrafish in modelling human synaptic diseases.

Concepts: DNA, Neuron, Evolution, Species, Complexity, Gene duplication, Vertebrate, Chemical synapse


The external organs of holometabolous insects are generated through two consecutive processes: the development of imaginal primordia and their subsequent transformation into the adult structures. During the latter process, many different phenomena at the cellular level (e.g. cell shape changes, cell migration, folding and unfolding of epithelial sheets) contribute to the drastic changes observed in size and shape. Because of this complexity, the logic behind the formation of the 3D structure of adult external organs remains largely unknown. In this report, we investigated the metamorphosis of the horn in the Japanese rhinoceros beetle Trypoxylus dichotomus. The horn primordia is essentially a 2D epithelial cell sheet with dense furrows. We experimentally unfolded these furrows using three different methods and found that the furrow pattern solely determines the 3D horn structure, indicating that horn formation in beetles occurs by two distinct processes: formation of the furrows and subsequently unfolding them. We postulate that this developmental simplicity offers an inherent advantage to understanding the principles that guide 3D morphogenesis in insects.

Concepts: Insect, Developmental biology, Epithelium, Complexity, Scarabaeidae, Pupa, Japanese rhinoceros beetle, Rhinoceros beetle


Global warming has increased the frequency of extreme climate events, yet responses of biological and human communities are poorly understood, particularly for aquatic ecosystems and fisheries. Retrospective analysis of known outcomes may provide insights into the nature of adaptations and trajectory of subsequent conditions. We consider the 1815 eruption of the Indonesian volcano Tambora and its impact on Gulf of Maine (GoM) coastal and riparian fisheries in 1816. Applying complex adaptive systems theory with historical methods, we analyzed fish export data and contemporary climate records to disclose human and piscine responses to Tambora’s extreme weather at different spatial and temporal scales while also considering sociopolitical influences. Results identified a tipping point in GoM fisheries induced by concatenating social and biological responses to extreme weather. Abnormal daily temperatures selectively affected targeted fish species-alewives, shad, herring, and mackerel-according to their migration and spawning phenologies and temperature tolerances. First to arrive, alewives suffered the worst. Crop failure and incipient famine intensified fishing pressure, especially in heavily settled regions where dams already compromised watersheds. Insufficient alewife runs led fishers to target mackerel, the next species appearing in abundance along the coast; thus, 1816 became the “mackerel year.” Critically, the shift from riparian to marine fisheries persisted and expanded after temperatures moderated and alewives recovered. We conclude that contingent human adaptations to extraordinary weather permanently altered this complex system. Understanding how adaptive responses to extreme events can trigger unintended consequences may advance long-term planning for resilience in an uncertain future.

Concepts: Weather, Complexity, Systems theory, Complex system, Aquatic ecosystem, Global warming, Extreme weather, Complex adaptive system


In this paper we explore the specific role of randomness in financial markets, inspired by the beneficial role of noise in many physical systems and in previous applications to complex socio-economic systems. After a short introduction, we study the performance of some of the most used trading strategies in predicting the dynamics of financial markets for different international stock exchange indexes, with the goal of comparing them to the performance of a completely random strategy. In this respect, historical data for FTSE-UK, FTSE-MIB, DAX, and S & P500 indexes are taken into account for a period of about 15-20 years (since their creation until today).

Concepts: Chaos theory, Economics, Complexity, System, Randomness, Stock market, Stock exchange, Technical analysis


The capacity for groups to exhibit collective intelligence is an often-cited advantage of group living. Previous studies have shown that social organisms frequently benefit from pooling imperfect individual estimates. However, in principle, collective intelligence may also emerge from interactions between individuals, rather than from the enhancement of personal estimates. Here, we reveal that this emergent problem solving is the predominant mechanism by which a mobile animal group responds to complex environmental gradients. Robust collective sensing arises at the group level from individuals modulating their speed in response to local, scalar, measurements of light and through social interaction with others. This distributed sensing requires only rudimentary cognition and thus could be widespread across biological taxa, in addition to being appropriate and cost-effective for robotic agents.

Concepts: Fungus, Interaction, Sociology, Emergence, Complexity, Vector space, Problem solving, Domain


The ability to probe symmetry-breaking transitions on their natural time scales is one of the key challenges in nonequilibrium physics. Stripe ordering represents an intriguing type of broken symmetry, where complex interactions result in atomic-scale lines of charge and spin density. Although phonon anomalies and periodic distortions attest the importance of electron-phonon coupling in the formation of stripe phases, a direct time-domain view of vibrational symmetry breaking is lacking. We report experiments that track the transient multi-terahertz response of the model stripe compound La1.75Sr0.25NiO4, yielding novel insight into its electronic and structural dynamics following an ultrafast optical quench. We find that although electronic carriers are immediately delocalized, the crystal symmetry remains initially frozen-as witnessed by time-delayed suppression of zone-folded Ni-O bending modes acting as a fingerprint of lattice symmetry. Longitudinal and transverse vibrations react with different speeds, indicating a strong directionality and an important role of polar interactions. The hidden complexity of electronic and structural coupling during stripe melting and formation, captured here within a single terahertz spectrum, opens new paths to understanding symmetry-breaking dynamics in solids.

Concepts: Crystal, Optics, Fundamental physics concepts, Condensed matter physics, Symmetry, Complexity, Solid, The Hidden


A new synthesis of (8-quinolyl)-5-methoxysalicylaldimine (Hqsal-5-OMe) is reported and its crystal structure is presented. Two Fe(III) complexes, [Fe(qsal-5-OMe)(2) ]Cl⋅solvent (solvent=2 MeOH⋅0.5 H(2) O (1) and MeCN⋅H(2) O (2)) have been prepared and their structural, electronic and magnetic properties studied. [Fe(qsal-5-OMe)(2) ] Cl⋅2 MeOH⋅0.5 H(2) O (1) exhibits rare crystallographically independent high-spin and low-spin Fe(III) centres at 150 K, whereas [Fe(qsal-5-OMe)(2) ]Cl⋅ MeCN⋅H(2) O (2) is low spin at 100 K. In both structures there are extensive π-π and CH⋅⋅⋅π interactions. SQUID magnetometry of 2 reveals an unusual abrupt stepped-spin crossover with T(½) =245 K and 275 K for steps 1 and 2, respectively, with a slight hysteresis of 5 K in the first step and a plateau of 15 K between the steps. In contrast, 1 is found to undergo an abrupt half-spin crossover also with a hysteresis of 10 K. The two compounds are the first Fe(III) complexes of a substituted qsal ligand to exhibit abrupt spin crossover. These conclusions are supported by (57) Fe Mössbauer spectroscopy. Both complexes exhibit reversible reduction to Fe(II) at -0.18 V and irreversible oxidation of the coordinated qsal-5-OMe ligand at +1.10 V.

Concepts: Magnetic field, Iron, Structure, Redox, Magnetism, Complex, Complexity, Exhibition


The thorium(iv) tetraiodide complex ThI(4)(DME)(2) () (DME = 1,2-dimethoxyethane) has been prepared in high yield by reacting the corresponding chloride complex ThCl(4)(DME)(2) with an excess of trimethylsilyl iodide (Me(3)SiI) in toluene. This new route avoids the use of thorium metal as a reagent. ThI(4)(DME)(2) () exhibits excellent thermal stability compared to ThI(4)(THF)(4) (), which undergoes rapid ring-opening of THF at ambient temperature to yield the iodobutoxide complex ThI(3)[O(CH(2))(4)I](THF)(3) (). Subsequent ligand-exchange between and DME affords ThI(3)[O(CH(2))(4)I](DME)(2) (), which can be converted to with Me(3)SiI. Salt metathesis between and K(L(Me)) (L(Me) = (2,6-(i)Pr(2)C(6)H(3))NC(Me)CHC(Me)N(2,6-(i)Pr(2)C(6)H(3))) cleanly gives (L(Me))ThI(2)[O(CH(2))(4)I](THF) (), which is a rare example of a thorium β-diketiminate complex. Complexes , , and represent the first reported examples of THF ring-opening mediated by thorium. The synthetic utility of ThI(4)(DME)(2) () is demonstrated by preparation of thorium(iv) alkoxide, amide, and organometallic compounds.

Concepts: Olefin metathesis, Complex, Complexity, Solvent, Chloride, Tetrahydrofuran, Organometallic chemistry, Thorium