A social hierarchy is an ordered ranking of individuals that arises through their interactions and governs relative access to resources and social influence. This form of social organization is pervasive across animal species and has a crucial role in shaping survival and reproductive outcomes. Across species, the routes to high status vary widely. As social groups become more complex, the basis of hierarchy shifts from simple residency rules to fighting-based dominance and finally to alliance-based systems. In this Review, we first examine the neuroendocrine and subcortical mechanisms that support status transitions in residency-based hierarchies. We then discuss plasticity within hypothalamic and mesolimbic circuits that underlie fighting-outcome-based social learning, through which fighting-based hierarchies emerge. Finally, we explore alliance-based hierarchies in cognitively complex species, in which individuals attain status through coalition formation, cooperation and reputation. We review evidence that cortical regions encode information about the strengths, emotions, experiences and intentions of other individuals and use this to navigate complex social interactions and attain status. As social hierarchies have shifted from primarily fighting-based to increasingly alliance-based strategies over evolutionary time, neural control of status has, thus, transitioned from subcortical social behaviour circuits to a more elaborated cortical network in humans.

Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze. STATEMENT OF SIGNIFICANCE: Eurasian mammoths evolved progressively thinner enamel and more complex enamel crests which have been hypothesized to reduce whole-tooth wear and extend dental longevity as grazing intensified, but this idea has not yet been directly tested. Here, we test this long-standing hypothesis using mechanical testing and in-silico wear models on fossil Woolly mammoth and modern Indian Elephant molars. We demonstrate that wear relevant material properties can be preserved in fossil dentitions and show that the addition of enamel plates through evolutionary time does not decrease whole-tooth wear rate as previously hypothesized, but rather topological shifts facilitate the emergence of a regular, low-relief, occlusal surface with an increasing number of triturating crests that likely improved mastication capacity of fibrous, lower nutrient graze.

Energy minimization is regarded to be a fundamental characteristic of legged locomotion, yet the influence of life history on the energy cost of locomotion has not been widely studied. We tested the hypothesis that growth-period limb loading minimizes the energy cost of walking in mature animals. We found that limb-loaded animals that chronically carried approximately 4% of their body mass on their distal right limb for 14 weeks (LL group) moved this mass with much less energy (22% less) than control animals (CON group) (p < 0.05). Furthermore, the majority of LL animals had a lower cost of walking with the limb load compared to walking without it. On average, LL animals did not use more energy walking with the limb load compared to CON animals walking unloaded. This remarkable limb-load carrying economy is, to our knowledge, the lowest reported for legged animal locomotion. Notably, we also found that CON and LL animals used the same amount of energy during unloaded walking, despite this being a novel condition for the LL group. These data suggest that energy minimization is critical not only across evolutionary and acute behavioural time frames, but also drives adaptation during the growth span.

Shake-gels—mixed suspensions of silica nanoparticles and poly(ethylene oxide)—exhibit reversible sol-gel transitions, which are triggered by agitation and reversed by rest. Despite their unique reversibility, the mechanisms governing shake-gel formation and relaxation, as well as the parameters controlling their macroscopic mechanical properties, remain poorly understood. According to the findings of previous studies based on visual observations, the relaxation time of shake-gels exhibits a maximum at an intermediate polymer dose per particle surface area. However, a quantitative rheological characterization of these relaxation behaviors has been lacking. Here, we systematically investigated the time evolution of the storage modulus of shear-induced gels as a function of polymer dose per particle surface area ( C p ) using time-resolved viscoelastic measurements. The initial storage modulus increased with C p and reached a plateau at approximately C p = 0.03 mg/m 2 . Conversely, the relaxation time underwent a precipitous decline above this C p . These results suggest that both high elasticity and prolonged structural stability emerge around the intermediate C p . The observed nonmonotonic dependence on C p persists across different particle concentrations and polymer molecular weights, indicating that normalization by particle surface area provides a useful framework for comparing relaxation behavior across compositions. These results establish a quantitative rheological basis for interpreting previously reported visual observations and offer guidance for the design of tunable, reversible gel systems.

Hybrid real-imaginary time evolution for low-depth Hamiltonian simulation in quantum optimization

We study the free energy and dynamics of a closed elastic filament (a one-dimensional curve in two dimensions) coupled to a scalar concentration field representing, for example, an adsorbed species. The density variable has a tendency to phase-separate whereas the local spontaneous curvature is concentration-dependent. We address analytically and by simulation both the free energy landscape and the dynamics (the latter comprising a coupled Willmore flow and Cahn-Hilliard gradient flow on the full differential geometry of a closed filament), addressing issues that previous work typically sidestepped by restricting to the Monge gauge. Specifically, we find that the closure constraint for a deformable filament qualitatively changes the free energy landscape compared with either a rigid closed filament or an open elastic one, admitting metastable and stable states with more than one domain of each type. By numerical global free energy minimization, we explore equilibrium morphologies across a wide range of model parameters. For selected parameter values, we present fully dynamical results, tracking the time evolution of the various contributions to the free energy and confirming the emergence of both metastable and equilibrium multi-domain morphologies.

Substitutional entrenchment arising from epistatic interactions renders previously acceptable amino-acid states unfavorable over evolutionary time and has often been attributed to novel adaptive processes. However, recent simulations based on Potts-Hamiltonian models have suggested that entrenchment may also emerge during protein evolution governed by the neutral theory of molecular evolution (NTME). Here, we re-examine this conclusion by assessing whether substitutions permitted in such simulations are consistent with empirical expectations of NTME. Since Potts models are inferred from a large collection of homologous rather than orthologous sequences, they may allow substitutions that are incompatible with NTME. Our analysis revealed that Potts-based simulations permit amino-acid substitutions whose Hamiltonian energies (PHE, φ) often fall outside empirically derived NTME φ neighborhoods, thus allowing non-neutral evolution of domain sequences. To prevent such transgressions, we implement simulations that impose purifying selection whenever Potts-acceptable substitutions depart from the NTME φ neighborhood. When these substitutions are eliminated, we observed limited substitutional entrenchment, with site-specific amino-acid preferences remaining stable over biologically relevant timescales in neutral protein evolution. We further find that overdispersion of the molecular clock is modest and scales directly with the proportion of evolutionary lineages displaying epistasis-driven among-site rate heterogeneity, independent of entrenchment. These results demonstrate that significantentrenchment is not an inherent property of epistasis during protein evolution consistent with NTME. Our findings establish baseline expectations for neutral evolution with epistasis and suggest that pronounced entrenchment observed in natural protein evolution likely reflects non-neutral evolutionary histories, including adaptation.

ABSTRACT This study delves into the socio-economic landscape of the Kingdom of Poland subsequent to its establishment in 1815 under the auspices of the Congress of Vienna, during which the Napoleonic Code of 1804 prevailed. Despite the legal framework, disparities persisted in property relations, wherein feudal ownership retained practical significance. Over time, societal and economic evolutions catalyzed the emergence of a novel form of real estate ownership, which can be described as pre-factory private property. This paradigm was characterized by a synthesis of feudal vestiges and attributes engendered by the nation's industrialization. Notably, this ownership model found manifestation within so-called factory settlements, which were industrial zones established in some cities.

In this paper, a distributed robust adaptive confined fault-tolerant optimal control method based on deep neural networks is proposed, aiming to solve the complexity and uncertainty problems in human height and weight prediction. Note that the term 'control' in this work refers to feedback regulation of the iterative learning/optimization dynamics of the predictor (iteration domain), rather than controlling the physical time evolution of human height/weight. In the field of public security technology, accurate prediction of individual physiological characteristics has important application value, especially in crime prevention, individual identification, and behavior analysis. Traditional prediction methods often perform erratically in the face of data noise, environmental changes, and outliers. To this end, this paper combines deep learning and fault-tolerant control theory to propose an efficient and reliable prediction framework by optimizing the robustness and adaptive ability of the predictor. By introducing a limited fault-tolerant mechanism, it can maintain high prediction accuracy and stability under various perturbations and incomplete data conditions. Moreover, we evaluate the proposed framework from three complementary dimensions-statistical similarity, overall predictive performance, and minority-class detection ability-and explicitly acknowledge that these criteria may exhibit trade-offs: improved distributional similarity does not necessarily translate into better decision boundaries, and optimizing overall performance can conflict with minority detection (e.g., recall/F1). Simulation and experimental results show that after 2000 rounds of iterative optimization, the normal and fault-tolerant prediction accuracies of human height for finger length of left and right hands are 98.4% and 97.7%, respectively, and the normal and fault-tolerant prediction accuracies of human body weight are 98.2% and 97.5%, respectively, by combining the 372 sets of data with 30% of data loss caused by human. The accuracy of normal and fault-tolerant prediction of human height was 90.8% and 89.2% for the finger length of the left hand, and the accuracy of normal and fault-tolerant prediction of human weight was 85.6% and 83.3%, respectively. The normal and fault-tolerant prediction accuracies of human height for the finger length of the right hand were 96% and 95.3%, and the normal and fault-tolerant prediction accuracies of human weight were 94.4% and 93.5%, respectively. These findings are most directly applicable to small-to-medium tabular datasets with moderate class imbalance and limited minority samples, which matches the regimes evaluated in this study. This study provides a new idea and technical path for biometric prediction and analysis in the field of public security technology, which has important theoretical significance and practical value.

Recent studies have shown that metal-organic frameworks (MOFs) can enable ultralow rotational barriers for molecular rotors in the solid state. In this near-free-rotor regime, elucidating how molecules behave within an ordered lattice becomes central to both a fundamental understanding and the design of crystalline molecular machines. Here, using a series of structurally simple, isoreticular MOF-5 homologues as a common platform, we present a systematic computational investigation of the rotational dynamics of five highly symmetric, rigid cage-like hydrocarbon rotators─bicyclo[1.1.1]pentane (BCP), cubane (CUB), bicyclo[2.2.2]octane (BCO), barrelene (BAR), and diamantane (DIA)─over a broad temperature range of 30-300 K. We show that under nearly barrierless conditions, these molecular rotators can exhibit inertia-dominated, continuous unidirectional rotations, which we quantify by the frequency of 360° turnover events. Temperature dependence of the 360° turnover frequency reveals clear differences among the rotors in how their dominant dynamical mechanisms transition with temperature. Furthermore, we introduce a Langevin description to quantitatively analyze the time evolution of the mean squared net angular displacement of the rotors in their rotational coordinate. We show that on long time scales all rotors enter the Brownian diffusion regime. The extracted rotational damping coefficients η reveal pronounced differences among the five rotors in both the strength of rotor-lattice coupling and its temperature dependence.

Soft, stimuli-responsive microgels are widely used to stabilize foams and emulsions, yet probing their interfacial properties without perturbing the interface remains a challenge. In this work, we show that acoustic levitation provides a simple and fully contact-free approach to quantify the interfacial properties of poly(N-isopropylacrylamide) microgels at the air-water interface. By monitoring the time evolution of the shape of a levitated droplet and using a neural network trained to interpret droplet geometries, we extract surface tension values for microgels with different cross-linker contents (1, 5, and 10 mol %). Under static levitation, dilute microgel dispersions display a characteristic nonmonotonic shape evolution that reflects the competition between evaporation-induced volume loss and the gradual adsorption and spreading of microgels at the interface. The surface tension values obtained from levitated droplets show excellent agreement with conventional pendant drop measurements, confirming the reliability of this shape-based, contact-free method. Furthermore, this approach enables the study of interfacial kinetics at soft interfaces without physical contact, thereby avoiding potential contamination or perturbation of the sample. In addition, acoustic levitation provides a platform for probing dynamic interfacial properties in future studies. Unlike conventional techniques that impose volume oscillations on the droplet─which can generate internal flows, particularly at higher oscillation frequencies─this method offers the possibility to investigate interfacial dynamics while minimizing flow-induced artifacts. Overall, our results establish acoustic levitation as a powerful platform for probing the interfacial behavior of soft colloids and lay the groundwork for future investigations of dynamic interfacial responses using controlled, volume-preserving droplet deformations.

ABSTRACT The stinkbug Plautia stali harbors essential gut symbiotic bacteria of the genus Pantoea , whose natural strains differ in cultivability and host benefits. Using this system, we evaluated how laboratory-evolved and genetically engineered symbiotic Escherichia coli strains compete against native Pantoea symbionts and how they influence host fitness. In single infection assays, the native uncultivable symbiont Sym A conferred the highest host performance, whereas the evolved (CmL05G13) and artificial (Δ cyaA ) symbiotic E. coli strains supported host survival at levels comparable to cultivable Pantoea symbionts (Sym C–F). In competitive co-infection assays, the symbiotic E. coli strains generally showed unexpectedly strong colonization ability. CmL05G13 outcompeted all the cultivable symbionts Sym C–F and even displaced the native uncultivable symbiont Sym A, whereas Δ cyaA and the nonsymbiotic control E. coli Δ intS were dominated by Sym A at the adult stage. Despite their superior infection competitiveness, the symbiotic E. coli strains provided limited reproductive benefits, behaving as “cheater-like” associates. They were able to invade and dominate the symbiotic organ but failed to match the fitness contributions of native symbionts. These results demonstrate that the experimentally evolved E. coli can rapidly acquire strong colonization ability, surpassing that of the natural symbionts that have coevolved with P. stali in nature. At the same time, the mismatch between infection success and host fitness benefits highlights potential evolutionary conflicts and provides an experimental model for studying the dynamics of cheating, mutualism, and symbiont replacement in vertically transmitted symbioses. IMPORTANCE Understanding how novel symbionts invade and displace long-term mutualists is central to the evolution of symbiosis. This study demonstrates that Escherichia coli , originally a nonsymbiotic bacterium, can rapidly evolve potent colonization ability and even outcompete native Pantoea symbionts of the stinkbug Plautia stali . Meanwhile, these competitive E. coli strains confer markedly lower reproductive benefits compared with the native symbionts that have developed an intimate mutualistic association with the host P. stali over evolutionary time, revealing a striking decoupling between infection success and host fitness. This finding highlights the potential for cheater-like microbes to invade vertically transmitted symbioses and destabilize coevolved partnerships. By combining experimental evolution, controlled co-infections, and quantitative analyses, the P. stali-E. coli experimental symbiotic system provides a powerful model for studying the mechanisms and evolutionary dynamics of mutualism, cheating, and symbiont replacement.

Phylogenetic comparative methods have been used in recent literature to work with laws and test for regularities (evolutionary associations of quantitative features) and evolutionary singularities (features that evolved in a single taxon). We analyzed these uses epistemologically, taking the evolution of red-blood-cell mean corpuscular volume (MCV) in mammals as a case study. For this, we considered three hypotheses: (i) in the absence of natural selection, other forces or constraints acting on the variation of MCV, MCV variance increases with evolutionary time, as predicted by biology's first law. Our results show that MCV evolves following Brownian motion which, according to Donsker's theorem, is the limit of the random walks on which the law is based on; (ii) MCV decreases as mass-independent basal-metabolic-rate increases, probably because smaller red-blood-cells are more efficient than larger ones at delivering oxygen in tissues. We show evidence for such evolutionary association so we are facing a regularity; (iii) outliers to the latter regularity (extreme MCV values) are evolutionary singularities. We show evidence for a significant difference between the value predicted by an inference model and that observed in Tragulus javanicus. Although at first sight laws and regularities have more in common with each other than with evolutionary singularities, they are fundamentally different: "biology's first law" is based on a priori, mathematical reasoning, whereas the regularity hypothesis is based on empirical data. Regularities and evolutionary singularities are two sides of the same coin, the latter appearing as the exceptions that, so to say, prove the rule.

We explore how the dissipative geometric phase evolves within the spin-boson model, focusing specifically on coupling to an Ohmic bath in the weakly coherent regime. To determine the non-unitary time evolution of the system's reduced density matrix, we employ the non-interacting blip approximation (NIBA). For the localized pure initial state used throughout, we derive a compact Bloch-sphere expression showing that the mixed-state geometric phase is a weighted azimuthal winding of the dissipative trajectory. We then map geometric-phase accumulation across various system-bath coupling strengths, temperatures, static biases, and bath cutoff frequencies. Benchmarking representative results against the numerically exact time-evolving matrix product operator (TEMPO) technique shows that NIBA reproduces the population dynamics almost indistinguishably. It also captures the geometric phase quantitatively and qualitatively, although TEMPO reveals a clearer trend in the stationary coherence. Our results show that quantum dissipation suppresses the geometric phase through two complementary mechanisms: thermal noise reduces the state's purity, while static bias localizes the dynamics and reduces the accessible geometric area.

While flocking together, living organisms follow their neighbors. The Vicsek model [T. Vicsek etal., Phys. Rev. Lett. 75, 1226 (1995)] for living systems, where individuals follow their neighbors within a spherically symmetric neighborhood with local velocity alignment rule in the presence of noise, provides a minimal framework to explore their collective dynamics. Associating limited vision angle to an individual provides a minimal description for cognitive perception. This breaks the spherical symmetry of its neighborhood and implements non-reciprocity within the interaction among themselves. Here, we show that in the low noise regime, with decreasing vision angle, the polar order parameter decreases from ≈1 to a much lower value, indicating a transition from a state with global coherent motion of large clusters to a state with small, locally ordered, fragmented clusters. These clusters can spontaneously merge and split among themselves hindering any significant large scale coherent motion in this state. However, we show that at small vision angles, even though the fragmentation restricts formation of larger sized clusters, particles exhibit strong short-range correlations within the small local clusters. In the high-noise regime, as the vision angle decreases, the local ordering observed for full vision angle (spherically symmetric neighborhood) gradually disappears, producing a homogeneous, disordered, steady state. Here, we probe the steady-state properties by analyzing the distributions and spatial correlations of velocities as well as their related fluctuations and also calculate the cluster size distributions for various sets of vision angle and noise strengths. The time evolution of these quantities helps in characterizing the emergence of the corresponding steady states.

Theoretical simulation of nonadiabatic scattering dynamics involves delicate treatment of both electronic coherence and decoherence all the time. In this study, we investigate the multiconfigurational Ehrenfest (MCE) dynamics with adaptive basis set expansion to capture the growing entanglement between the electronic states and the nuclear degrees of freedom with time, which shares the same features with the well-known overcoherence problem in the traditional Ehrenfest mean field method. Inspired by the decoherence studies in the framework of mixed quantum-classical dynamics, we here propose a decoherence-induced adaptive MCE (DA-MCE) method, which can deal with the coherent propagation and quantum decoherence in nonadiabatic scattering dynamics simultaneously. As demonstrated in the three famous Tully models, DA-MCE can efficiently capture the time evolution of the reduced density matrix, the Stueckelberg interference, and the rapid decoherence. In particular, both the adaptive expansion of the basis set and the form of the variational Ansatz are found to be highly important for the description of complex dynamics. Compared to the multiconfigurational surface hopping method proposed recently, our DA-MCE can also be regarded as a multiconfigurational version of the branching corrected mean field method, which indicates the potential combination of general mixed quantum-classical trajectories with the proposed multiconfigurational approach.

ABSTRACT It is demonstrated that the increase in atmospheric CO2, due to climate change and urbanization, threatens the sustainability of RC structures by accelerating carbonation and corrosion of reinforcement, which reduces structural strength. This study proposes an analysis of the durability of an underground RC water tank, whose space above the dome has been converted into a parking area. A deterministic approach, based on the loss of reinforcement section, is used to quantify uniform corrosion of top ring beam steels. Three carbonation models are compared to evaluate the carbonation progression, and two corrosion current models are applied to analyze the residual area of steel cross-section. A uniform corrosion model is developed to determine the evolution in time of the reinforcements section in different environments. Several parameters influencing corrosion are taken into account. The study concludes that an increase of 10 mm of coating extends the service life by about 20 years, while a higher CO2 concentration accelerates corrosion.

Although ice polymorphs commonly feature orientational order and disorder, it is difficult to grasp the nature of partial order. In this study, we report on the hydrogen ordering of ice V using calorimetry at ambient pressure with an isothermal annealing approach. H2O/D2O isotopic substitution underlines the existence of the partially ordered intermediate state between ice XIII (below 113 K) and ice V (above 120 K), which exhibits a large isotope effect on the enthalpy of hydrogen disordering. Combined with the observation of two-staged time evolution of hydrogen order and the significant deuteration-induced slowdown of the ordering kinetics by a factor of 15-60, we propose that this intermediate state bears dynamic disorder. This reflects mutual conversions of ordered configurations taking place, i.e., domain fluctuations between differently ordered configurations. This finding raises a new perspective to characterize partial order, leading to the potential application toward frustrated functional materials.

Operator-projected variational quantum imaginary time evolution

The properties of aqueous (aq.) salt solutions are consequential to various scientific and technological domains as the ion-water and inter-water interactions modulate their properties. In this study, we studied the vibrational, structural, and molecular dynamics properties and correlations for a wide range of molal concentrations of aq. LiCl and LiNO3 solutions (deuterated; five different concentrations ranging from 1.0 m to ultrahigh concentrations) using classical molecular dynamics simulations and a flexible water model. The more charge-dense Cl- anions induce greater structural rigidity and sluggish dynamics. The time evolution of vibrational frequencies of probe OD modes of dil. HOD/H2O was also investigated. The orientation dynamics of water dominate the slow vibrational spectral diffusions of this mode. The correlations of dynamic properties are more monotonous for aq. LiNO3 solutions across the studied concentrations. In contrast, for aq. LiCl systems, the influence of Cl- became more prominent, leading to more heterogeneous trends. For both anions, the duration of the tethering of water in their solvation strongly correlates linearly with the observed spectral diffusion, contributing to the memory effect. At ultrahigh concentrations, the Cl--water hydrogen bonding directly modulates it, thereby playing a direct role in preserving the vibrational memory of water. In aq. LiNO3, the inter-water interactions appear to determine the timescale of spectral diffusion. When considered together with the strong correlation of its hydration shell, a more subtle influence is observed from NO3- anions.