Michael Nosonovsky

We investigate the relationship between the graphical symmetry of symbols and their frequency of occurrence in culturally evolved symbolic systems and compare the observed tendencies with those found in physical structures. Capital letters of the English and Russian alphabets were classified according to their invariance under vertical reflection, horizontal reflection, and rotation through 180°. The graphical symmetry of numerical figures was analyzed across four numeral systems. Symmetry was examined for 1000 Japanese Kanji arranged into frequency-ranked groups. Spearman’s and Kendall’s rank-correlation tests revealed positive symmetry–frequency tendencies in both alphabets, although the associations did not reach conventional statistical significance. A strong and statistically significant positive association was obtained for the average symmetry of the numerical figures and their leading-digit frequencies predicted by Benford’s law. The Japanese Kanji produced the strongest statistical result. Despite their different cultural origins and graphical organization, the investigated alphabets and numeral systems exhibited surprisingly similar symmetry-class entropies, suggesting a possible common balance between graphical regularity and symbol distinguishability. For comparison, seven-bond and eight-bond colloidal clusters demonstrated the opposite tendency, with asymmetric configurations occurring more frequently and dominating their symmetry-class distributions.

The language used to describe wine poorly corresponds to its chemical composition hypothesized a narrow bottleneck formed by a low-dimensional perceptual layer between a chemical sensometabolome and a descriptive language.

This study investigates seeding and cultivation of C2C12 myoblast cells on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (P3HBV) films synthesized at four polymer concentrations, yielding films with progressively increasing lateral thickness and diverse surface topographies. Cell attachment was evaluated after 24 h, alongside correlations between surface topography and cellular behavior. Surface characteristics across films at each thickness were quantified using atomic force microscopy (AFM), scanning electron microscopy (SEM), advanced topological data analysis (TDA), and threshold relief analysis. C2C12 myoblast growth was imaged via fluorescence microscopy, with quantitative metrics extracted using the Cellpose Plus toolbox. Statistical modeling revealed correlations between surface features and cell morphology. SEM imaging further corroborated pore characteristics against cell growth metrics. Results demonstrate a linear relationship between surface topography and cellular responses, underscoring the critical role of substrate morphology in modulating cell behavior, where films synthesized at high polymer concentrations (5–7% w/v) exhibit enhanced cell attachment. The 85:15 P3HBV copolymer was selected for its favorable thermomechanical properties, high biocompatibility, and cost-effectiveness for large-scale biosynthesis. Our work presents a reproducible data-driven pipeline for analyzing cell–surface interactions, combining TDA and image segmentation metrics to explore the behavior of surface morphology under varying material conditions.

Molecular inventories of astronomical sources are usually compared through composition, abundance, excitation, and reaction chemistry. Here we introduce a complementary group-theoretical approach in which molecular symmetry is treated as a statistical descriptor of astronomical molecular populations. Three chemically and physically distinct molecular corpora are analysed: 75 main-isotopic species from the GOTHAM inventory of the cold dark cloud TMC-1, 39 molecular species detected in the Herschel/HIFI survey of Orion KL, and 23 distinct main species obtained by collapsing isotopologues in a recent 3-mm survey of the carbon-rich circumstellar envelope IRC+10216. Each molecular carrier is assigned a point group using an equilibrium-structure, species-level convention. The resulting symmetry distributions are strongly uneven: a small number of symmetry classes and, in particular, reflection and proper axial symmetry dominate all three molecular corpora. Under the adopted classification, every species in all three corpora possesses at least one mirror plane, making reflection symmetry the most universal structural feature identified in the present census. Proper axial symmetry is likewise exceptionally prevalent: the fractions of species possessing a nontrivial proper rotational axis increase from 65.3% in TMC-1 to 79.5% in Orion KL and 95.7% in IRC+10216. Linear molecules alone constitute 44.0%, 51.3%, and 78.3% of the three corpora, respectively. Thus, the observed molecular symmetry landscape is far from uniform: mirror and axial symmetries occupy an exceptional position, whereas other symmetry types are comparatively weakly represented or absent. The persistence of reflection symmetry across a cold dark cloud, a hot high-mass star-forming region, and a radially stratified carbon-rich circumstellar envelope demonstrates that its prevalence cannot be attributed to low temperature alone. In contrast, the strong source-to-source variation of linear symmetry points to environmental chemistry and reaction-network topology as major controlling factors, with IRC+10216 providing a particularly clear example of carbon-chain growth that constructs and preserves linear molecular skeletons. We therefore propose that the strongly nonuniform symmetry distribution of an astronomical molecular inventory, and especially the exceptional prevalence of mirror and axial symmetry, can serve as a compact structural descriptor of its chemical formation history. Rotational-spectroscopic selection and conformer populations remain important limitations, and the reported distributions characterize detected molecular corpora rather than complete, bias-free molecular populations.

This study investigates Interpenetrating Phase Composites (IPCs) based on Gyroid Triply Periodic Minimal Surface (TPMS) architectures for multifunctional aerospace and automotive applications. Hybrid IPCs were developed by infiltrating 3D‐printed Gyroid lattices with moisture‐curing polyurethane foam. The research evaluates frequency‐dependent sound absorption and quasi‐static mechanical properties using experimental measurements and JCALP numerical modeling. The results demonstrate that reducing unit cell size enhances both stiffness and high‐frequency absorption. A critical synergy is identified at a 6 mm cell size, where foam infiltration increases sound absorption by 12.4% and shifts peaks toward lower frequencies. Mechanically, the IPC configuration provides a confinement effect that stabilizes the Gyroid struts against buckling. For the G04 architecture, Young’s modulus and specific energy absorption increased by up to 24.6% and 15.3%, respectively, relative to an equivalent‐mass unfilled Gyroid lattice with the same 4 mm unit‐cell size. Foam infiltration modified the acoustic response depending on the Gyroid unit‐cell size. Optical observations suggest a wall‐induced variation in foam cell morphology. The combined results demonstrate that changing unit‐cell size under constant wall thickness changes the overall architecture, including porosity and relative density, which collectively influence the acoustic and mechanical response, providing practical design guidelines for multifunctional lightweight structures.

We introduce a comprehensive computational framework for quantifying the dynamics of levitating droplets in a cluster during controlled cooling from 50 to 46 °C. This framework integrates state-of-the-art Computer Vision and Machine Learning techniques such as YOLO-based detection and robust multiobject tracking, to extract kinematic and energetic metrics: estimated velocity, acceleration, kinetic energy, and spatial uniformity. Directional statistics of droplet motion are analyzed through circular statistics, specifically, Mean Resultant Length (MRL) and the Hermans–Rasson (HR) test, to explain temperature-driven changes in trajectory orientation. In addition, we study the efficiency of trajectories defined as the ratio of the straight-line Euclidean displacement to the actual path length. This metric enables objective classification of droplets into high- and low-efficiency groups. Our analysis reveals a dynamical transition at 47 °C. Below this critical temperature, the angular distributions evolve from multimodal to isotropic (uniform/random) behavior, accompanied by a marked reorganization of both MRL and HR values. These findings establish a quantitative link between thermal conditions and collective droplet motion, providing fundamental insights into the stability and self-organization of levitated liquid ensembles.

The dimensionality of the taste dataspace formed by bitter and umami ligands interacting with T1R1 and T2R receptors determined D = 3 for the tastes.

We investigate the asymptotic maximum value and convergence of the Voronoi Entropy (VE) for a 2D random point process (S = 1.690 ± 0.001) and point sets with long-range order characterized by hyperuniformity. We find that for the number of polygons of about n > 100, the VE range is between S = 0 (ordered set of seed points) and S = 1.69 (random set of seed points). For circular regions with the dimensionless radius R normalized by the average distance between points, we identify two limits: Limit-1 (R = 2.5, 16 ± 6 points) is the minimum radius, for which it is possible to construct a Voronoi diagram, and Limit-2 (R = 5.5, 96 ± 6 points) at which the VE reaches the saturation level. We also discuss examples of seed point patterns for which the values of VE exceed the asymptotic value of S > 1.69. While the VE accounts only for neighboring polygons, covering the 2D plane imposes constraints on the number of polygons and the number of edges in polygons. Consequently, unlike the conventional Shannon Entropy, the VE captures some long-range order properties of the system. We calculate the VE for several hyperuniform sets of points and compare it with the values of exponents of collective density variables characterizing long-range correlations in the system. We show that the VE correlates with the latter up to a certain saturation level, after which the value of the VE falls to S = 0, and we explain this phenomenon.