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Ancient burial mounds detection in the Altai Mountains with high-resolution satellite images
No full textThe Altai Mountains rank among the world’s most notable and valuable archaeological regions. Within the sprawling Altai Mountains area, burial mounds (kurgans) of past civilizations, which are sometimes well preserved in permafrost, are a particularly precious trove of archaeological insights. This study investigates the application of deep learning-based object detection techniques for automatic kurgan identification in high-resolution satellite imagery. We compare the performance of various object detection methods utilizing both convolutional neural network and Transformer backbones. Our results validate the effectiveness of different approaches, especially with larger models, in the challenging task of detecting small archaeological structures. Techniques addressing the class imbalance can further improve performance of off-the-shelf methods. These findings demonstrate the feasibility of employing deep learning techniques to automate kurgan identification, which can improve archaeological surveying processes. It suggests the potential of deep learning technology for constructing a comprehensive inventory of Altai Mountain kurgans, particularly relevant in the context of global warming and archaeological site preservation.1. Introduction 2. Study Areas and Image Data 2.1. Study Sites 2.2. Image Data 3. Methodology Machine-Learning Method 4. Experimental Results 4.1. Accuracy Validation 4.2. Discovering Kurgans in Unexplored Regions 5. Discussion 6. Conclusion
P2X purinergic receptors are required for correct cortical development in human brain organoids
No full textThe human neocortex represents a crucial evolutionary advance, the formation of which requires the tight and precise orchestration of both intracellular and extracellular signals. Structures grown in three-dimensional cultures, specifically human-induced pluripotent stem cells (hIPSCs)-derived cerebral organoids (COs), have been fundamental to study the signals that regulate the formation of the cortex, overcoming the limitations of 2D cultures. Amongst these, purinergic signaling driven by extracellular ATP and other nucleotides may encode crucial intercellular communications that govern central nervous system (CNS) development. The ATP that accumulates in the extracellular milieu can interact with both ionotropic P2X and metabotropic P2Y receptors on cells to exert its modulating effects. Although widely studied in different animal models, little is known about the expression and function of this signaling system in the human cortex. Thus, here we analyzed the expression of P2X receptor subunits comprehensively throughout the entire process of CO development, confirming that P2X receptors are functional in ventricular structures of the human cortex. Specifically, we detected the expression of P2X1, P2X4, and P2X6 in CO, showing distinct distributions in Nestin+ radial glial cells and/or DCX+ newborn neurons. Significantly, we also show how prolonged pharmacological inhibition of P2X activity affects CO development, resulting in smaller organoids with fewer and less well-organized cortical ventricles. Altogether, our findings point to a relevant role of purinergic signaling during the formation of the human cerebral cortex
Continuous phase hydrophobicity exerts substantial influence on the surface functional group prevalence in protein nanocapsules synthesized in inverse miniemulsion
No full textSystematic Parameterization of Flory–Huggins Models from Molecular Dynamics Simulations for Ternary Lipid Mixtures
No full textTernary lipid mixtures with saturated and unsaturated lipids and cholesterol serve as widely used model systems to study coexisting liquid-ordered (Lo) and liquid-disordered (Ld) domains in biomembranes. Despite advances in both experiments and simulations, a computationally efficient systematic approach to extract effective pairwise lipid–lipid and lipid–cholesterol interactions from molecular dynamics (MD) simulations for mesoscale models remains limited. Moreover, parametrizing Flory–Huggins (FH) or lattice Monte Carlo (MC) models becomes especially challenging for multicomponent systems due to the size and complexity of the pairwise interaction matrix. To address this, we aim to bridge molecular-level interactions and continuum mean-field models by implementing a multiscale framework that integrates coarse-grained (CG-MD) and all-atom (AA-MD) simulations with FH theory and lattice MC models. Pairwise interaction energies (wij) are extracted from radial distribution functions using the reversible work theorem and formulated into FH interaction parameters (χij). We apply this multiscale framework to determine phase count and analyze tie-line and bistable phase behavior of (Ld/Lo) domains for ternary lipid mixtures, specifically using the FH model. The extracted χij values from MD reproduce domain formation in both MC and FH models. Comparisons across AA-MD, CG-MD, MC, and FH frameworks reveal both quantitative differences and similarities, as well as conserved trends in phase separation behavior. This study establishes a systematic approach to parametrize mesoscale models for multicomponent lipid membranes directly from MD simulations. Furthermore, our approach can serve as a tool for system-specific mesoscale biomembrane modeling studies that embed molecular-level detail and bridge top-down and bottom-up perspectives for future studies
A comparative study of perturbative and nonequilibrium Green's function approaches for Floquet sidebands in periodically driven quantum systems
No full textWe compare two complementary theoretical approaches to compute and interpret Floquet sidebands in periodically driven quantum materials: a first-order perturbative approach (first-order perturbative Born approximation, PB1) and time-dependent nonequilibrium Green's functions (tdNEGF). Using graphene as a model Dirac system, we disentangle in pump-probe setups Floquet-dressed initial states, Volkov-dressed final states (also known as laser-assisted photoelectric effect, LAPE), and their interference. We quantify how photoemission matrix elements, polarization, incidence angle, and near-surface screening shape the momentum-resolved sideband intensity observed in tr-ARPES. PB1 yields an analytical expression for the momentum-dependent sideband intensity, and for graphene it captures the correct symmetry trends, such as the magnitude of the intensities when considering the interference between the Floquet and Volkov states and photoemission matrix elements. tdNEGF reproduces the full energy-momentum-resolved spectra, including hybridization gaps and spectral-weight redistribution. We find qualitative agreement between PB1 and tdNEGF once matrix elements are included; quantitative differences arise near hybridization regions and at specific angles where higher-order processes and self-energies are essential. Thus, for systems with simple band structures and away from these regions, the two approaches can be used in a complementary way
Kernels, lax algebras, décalage, and supercoherence
No full textWe prove that a pointed category has kernels if and only if it is a lax algebra for the arrow 2-monad, and that this holds if and only if it is the décalage of a supercoherent structure. We will then interpret categories with kernels as the sought-after weak version of unary operadic categories
Classifying Causal Nonlinear Electrodynamics via -Parity and Irrelevant Deformations
No full textWe investigate the classification of self-dual nonlinear electrodynamic (NED) theories based on their analyticity properties, which are directly linked to invariance under a discrete -parity transformation. This classification is expressed through the structure of the irrelevant -like deformations that generate the theories from a Maxwell seed. Using both closed-form and perturbative methods within the Courant-Hilbert (CH) and Russo-Townsend auxiliary field formalisms, we demonstrate a precise correspondence: -parity-invariant, analytic theories are generated by irrelevant deformations built from integer powers of the energy-momentum tensor scalars, . Conversely, -parity-violating, non-analytic theories require deformations involving both integer and half-integer powers, . We prove this result in generality via a perturbative CH framework, showing that -parity invariance imposes specific constraints on the expansion coefficients of the CH function which, in turn, force all half-integer powers in the deformation to vanish. The classification is explicitly verified for known closed-form theories: the analytic generalized Born-Infeld model and the non-analytic examples of the -deformed and "no -maximum" theories. Furthermore, we show how the -parity transformation is consistently generalized in the presence of a marginal root- coupling , and we derive the corresponding marginal and irrelevant flow equations for the studied theories
Stabilization of 5-HMF in highly alkaline electrolytes through acetalization for the selective electrooxidation to FFCA
No full textThe oxidation products of 5-hydroxymethylfurfural (HMF) and its derivatives are promising monomers for the production of renewable polymers. However, the stability of HMF during electrooxidation in alkaline electrolytes remains challenging due to its degradation into humins, which reduces the carbon yield. To increase HMF stability in alkaline media, a protection strategy based on acetalization of the formyl group is plausible, but it has not yet been evaluated for electrochemical processes. In this study, we successfully transferred this protection strategy to the electrochemical oxidation of HMF in alkaline media. We demonstrate that acetal-protected HMF is highly stable in alkaline electrolytes, even at elevated concentrations and temperatures. Furthermore, we show that the overall selectivity of the electrooxidation shifts from 2,5-furandicarboxylic acid (FDCA) to 5-formyl-2-furancarboxylic acid (FFCA), which is typically not obtained during the alkaline electrooxidation of HMF. High yields (95%) and faradaic efficiencies (87%) of FFCA were achieved, even at elevated substrate concentrations (250 mM) in 5 M KOH. The carbon balance remained closed throughout the electrooxidation, demonstrating that acetalization of HMF effectively suppresses degradation into humins