Browse Articles

Structured generative modelling of earthquake response spectra with hierarchical latent variables in hyperbolic geometry

Abstract This study presents a geometry-aware generative modelling framework for earthquake response spectra, leveraging a hierarchical variational autoencoder (HVAE) with latent variables embedded in a Poincaré ball manifold. Predicting complete ground motion response spectra is crucial for seismic hazard analysis and structural performance assessment; however, conventional machine learning models often fail to capture multi-scale physical dependencies and hierarchical uncertainity inherent in earthquake records that arise from event-to-event variablity and spatial variability. The proposed architecture is trained using source and site parameters to regularise the latent space which enables the generation of physically consistent spectral amplitudes while explicitly modelling inter- and intra-event variabilities . By exploiting hyperbolic latent geometry, the HVAE encodes hierarchical relationships into the latent space with an improved representational efficiency. Trained on a curated strong-motion dataset, the model achieves high reconstruction fidelity, with a mean coefficient of determination of 0.961 across all spectral periods. Integration into stochastic ground motion simulation and early warning pipelines demonstrates its practical utility. This work bridges geometric deep learning and seismological modelling, offering a principled, domain-aligned approach to real-time seismic risk mitigation.

Calculating Coulomb interactions in molecular dynamics simulations: The Evjen method revisited

A new way is invented for computing Coulomb interactions in molecular dynamics simulations, which works well for bulk phase and lamina systems. This direct summation (DS) or cell dipole approach is an extension of the “Evjen” method, which was explored in the 1960s. The DS method is the Evjen method with a unit cell dipolar correction and is cast entirely in real space, involving summing the original point charge r−1 interactions, which are truncated on a unit cell basis rather than spherically for the individual point charge interactions. The theory of the DS method is extended to encompass noncubic unit cells periodic in all three Cartesian directions. For moderately sized systems, the DS method performs with comparable accuracy and computational efficiency to that of the Ewald method, both of which are formally exact. The corresponding treatment is made for a lamina system where the charges are in 3D but the unit cells are only periodic in two of the three Cartesian directions. The DS method has no adjustable parameters and is relatively straightforward to implement in existing computer codes that do not include Coulomb interactions, unlike the Ewald method.

Synthesis and biological evaluation, network pharmacology, and molecular docking of 2-benzylidene-1-indanone derivatives as antitumor agents

Density dependence of measured line intensities for O2 transitions

We report predictions and measurements of O2 absorption spectra that exhibit line intensity depletion with increasing gas density. This effect, which is attributed to the finite duration of collisions, alters the line shape by redistributing a portion of the intensity from a relatively narrow spectrum that can be described by an impact-approximation-based profile to a broad pedestal with a width that is inversely related to the collision duration. Using classical molecular dynamics simulations (CMDS), we predicted details regarding this mechanism for O2 with four collision partners: O2, N2, Ar, and He at a temperature of 296 K. These simulations were validated by comparisons with experimental intensity depletion coefficients obtained from absorption spectra of the 1.27 μm band of O2 in air; Ar and He acquired over a wide pressure range up to 120 kPa. All experimental spectra were recorded using high-precision cavity ring-down spectroscopy (CRDS) apparatuses at NIST (United States of America) and LIPhy (France). For air-broadened O2, more specifically, a mean depletion value of ∼0.3% amagat−1 was observed, with almost no resolvable rotational dependence. The temperature dependence of the intensity depletion in this system was also investigated by CMDS at 250 and 296 K and by CRDS spectra of air at 250, 275, and 296 K. The theoretical results suggest a nearly 1/T2 temperature dependence of the intensity-weighted depletion coefficient, which over the limited temperature range considered, was only slightly greater than the measurement precision. Finally, simulations of atmospheric solar absorption spectra were implemented to quantify the impact of neglecting this depletion effect on the retrieved surface pressure, resulting in a negatively biased measurement of ∼0.14%, with a spread of ∼0.02% caused by seasonal variations in gas temperature.

Chitosan from shrimp shell waste as a carrier for frankincense nanoparticles with enhanced antimicrobial activity

Abstract This study focuses on the sustainable extraction of chitosan from shrimp shell waste and its application in developing frankincense-loaded chitosan nanoparticles with enhanced antimicrobial efficacy. Chitosan was extracted through demineralization with 4% HCl, deproteinization using 8% NaOH at 70 °C, and deacetylation with 40% NaOH under shaking for 48 h, yielding 3.4 g (22.51%) from 15 g of shrimp shell powder. Frankincense ethanolic extract was incorporated into chitosan nanoparticles using sodium tripolyphosphate as a crosslinker, followed by ultrasonication and dropwise addition of chitosan to form a stable nanocomposite. Characterization confirmed a semi-crystalline structure (XRD), typical thermal degradation (TGA), and strong molecular interaction between chitosan and frankincense (FTIR). TEM and SEM showed well-dispersed, amorphous nanoparticles with smoother surfaces, while DLS revealed an average particle size of 149.4 nm, PDI 0.26, and zeta potential + 12.0 mV, indicating moderate stability. Antimicrobial activity was evaluated using two methods: the well diffusion and microplate reader assays against Staphylococcus aureus , Streptococcus mutans , Escherichia coli , Salmonella typhi , and Candida albicans . Results showed that nanoparticles significantly enhanced inhibition of S. mutans , S. typhi , and C. albicans compared to the extract. These findings highlight chitosan–frankincense nanoparticles as a promising natural antimicrobial system for pharmaceutical and food preservation applications.

Two-state reaction path search using a quantum Monte Carlo-inspired approach

We present an algorithm for finding chemical reaction pathways using a Monte Carlo transition state search (MCTSS) scheme. Our strategy is a bidirectional two-state approach that simultaneously drives two Monte Carlo trajectories from reactants to products, and vice versa, until the trajectories meet. The trajectories are driven in a Metropolis-like procedure with transition probabilities based on the real-space diffusion Monte Carlo algorithm. A computationally inexpensive structure preselection procedure is used to guide the two trajectories toward each other. We performed a proof-of-principle demonstration of the MCTSS algorithm for the model two-dimensional double-well potential and for the halogen anion SN2-substitution in halogenated methane. The MCTSS approach presented here is expected to be particularly useful when employing electronic structure methods that do not provide analytic gradients.

Transcriptomic analysis of preimplantation mouse embryos exposed to nanoplastics using RNA sequencing

X-ray emission spectroscopy in liquid jets: A effective tool to probe valence and <i>p</i> -shells in organometallics and the influence of the solvation

In this combined experimental and theoretical work, we present state-of-the-art liquid jet experiments based on x-ray emission spectroscopy of the [Fe(CN)6]4− and [Fe(CN)6]3− molecular ions in the hard-x-ray energy range. The ab initio simulations of the valence-to-core and Kβ spectra reveal insights into the valence and metal’s d-shells, respectively. These results open new perspectives for applying spectroscopy to organometallic complexes in order to disentangle and probe various environmental effects, including solvent interactions, pH variations, and ligand field influences and dynamical processes, such as charge transfer or photoinduced ligand exchange reactions such as photoaquation in solution.

Correction: Comprehensive analysis of the PLXNA3 gene on prognosis and immune characteristics in breast cancer

Modeling the behavior of concentrated aqueous HNO3 using machine learning interatomic potentials

We develop two multi-defect machine learning interatomic potentials (MLIPs) trained at the BLYP-D2 and PBE-D3 density functional theories using the DeepMD-kit, allowing for the investigation of structural and thermodynamic properties of nitric acid over a wide range of concentrations via molecular dynamics (MD) simulations. We directly compute the degree of dissociation, α, and pKa from MD simulations, revealing that HNO3 behaves as a weaker acid at higher concentrations, noting that our standard-state pKa value is in excellent agreement with the experimental one. In general, good agreement is observed with experimental results such as α and density outside the training dataset, with only modest deviations at low-to-medium concentrations. We benchmark our custom multi-defect DeepMD MLIPs against foundational models MACE-MP0 and MACE-OFF23. The foundation models capture some aspects of HNO3/NO3− solvation in concentrated nitric acid but show noticeable density errors and miss subtle structural features relevant to spectroscopy, whereas the bespoke DeepMD MLIPs yield more compact solvation shells, reproduce density-concentration trends, and run ∼12–15× faster than MACE-MP0. Although classical FFs are still more efficient and match experimental densities better, they lack chemical reactivity and thus cannot predict α or pKa, underscoring the need for system-specific reactive MLIPs beyond universal MLIPs.

Exploring the chemodiversity of antimicrobial minalemines from Didemnum granulatum by neutral loss graph

Abstract In this study, we report on the identification of the active antimicrobial principles from the tunicate Didemnum granulatum . Two new natural products, minalemines G ( 1 ) and H ( 2 ), were isolated and their structures were elucidated. Both compounds showed potent antibacterial activity, with compound 1 showing sub-microgram inhibition against Staphylococcus aureus . Moreover, we also report a new mass spectrometry-based approach, named neutral loss graph, developed to explore minor metabolites from complex mixtures. This approach was applied here to reveal twelve additional minalemine analogues in the organic extract of D. granulatum .

An 8-dimensional symmetry-adapted neural network potential energy surface for H2 dissociative chemisorption on hexagonal boron nitride <i>ortho</i> site with explicit surface atom motion

We developed an 8D, site-specific, reduced-dimensionality potential energy surface (PES) for H2 dissociation at the ortho site of hexagonal BN, treating two surface atom degrees of freedom explicitly. To our knowledge, this is the first PES for gas-phase dissociation on a covalent surface with explicit treatment of surface atom motion and symmetry in a reduced-dimensionality approach. The PES was fitted to 16 164 PBE+D3 DFT data points with a mean absolute error of 17.00 meV using a symmetry-aware neural network incorporating atom permutational invariance and lattice space group symmetry. Convergence was validated via 2D site vibrational Schrödinger equation integration and classical MD trajectory prediction uncertainty analysis. Comparison of site-specific vibrations with the surface phonon spectrum revealed the limitations of the phonon approximation for covalent PES generation using EAM-thermal averaging methods. Classical trajectory analysis reveals that H–H bond elongation beyond 1.5 Å occurs at incident energies as low as 2.25 eV, which is below the 2.664 eV chemisorption barrier, suggesting BN surface mobility facilitates pre-dissociation. Our 8D model reproduces the barrier with 17% error (0.387 eV) compared to the full 108-dimensional model, while providing at least four orders of magnitude computational speedup compared to other surface models, enabling wavepacket dynamics calculations. This methodology provides a framework for future quantum dynamics studies on covalent 2D materials, using site vibrations to construct efficient discrete-variable representation basis sets.

Tolerance driven lightweight design and interface robustness of multi material aircraft horizontal tail structures

Vibrational spectra of the radiation-induced cationic species resulting from phosphine monomers and dimers: A matrix isolation and CCSD(T) study

Phosphine (PH3) is the simplest phosphorus compound detected in the extrasolar and planetary environments, where it can be subjected to ionizing radiation. In this study, we first report the vibrational spectra of the ionized molecules resulting from phosphine monomer and dimer in solid noble gas matrices upon X-ray irradiation. The assignment was based on the comparative studies using electron paramagnetic resonance and Fourier transform infrared spectroscopy, complemented by the quantum-chemical calculations at the valence-correlated spin unrestricted coupled cluster single-double and perturbative triple [UCCSD(T)] level of theory. We were able to observe three fundamentals of PH3+• and four fundamentals of P2H6+•. The spectroscopic data were also obtained for PD3+•, P2D6+•, and [PH3-PD3]+• radical cations. PH3+• demonstrates a large blue shift of the most intense infrared (IR) absorption related to the P–H stretching vibration (ν1) with respect to the corresponding vibration in the parent neutral. For the P2H6+• radical cation, the most intense IR absorption corresponds to a low-frequency deformational vibration. It was found that the P2H6+• radical cation reveals a photochromic behavior: it decays under the action of light with λ ≤ 400 nm and can be partially recovered after subsequent photolysis at λ = 445–525 nm. The observed transformations were attributed to the interconversion between P2H6+• and the PH4+…PH2• complex. The dynamics of these transformations was discussed using the data obtained for mixed P2H3D3+• species. The obtained results may be useful for future searches for the manifestations of such species in extraterrestrial environments and studies of the radiation-induced transformations of phosphine in icy media.

Ancient genomes reveal early-stage admixture and genetic diversity in the Northwestern Kyushu Yayoi

Abstract The demographic history of the Japanese archipelago was shaped by major episodes of migration and admixture, most notably the transition approximately 3,000 years ago from the Jomon period, a long-established hunter-gatherer tradition, to the Yayoi period, when migrants from the Eurasian continent introduced agriculture and new technologies. However, the timing, extent, and regional variability of the admixture between continental migrants and indigenous Jomon populations remain poorly understood. Northwestern Kyushu has drawn particular attention because skeletal analyses have indicated that Yayoi individuals from this region retain Jomon-like morphological features. However, their genetic background remains unclear. Here, we report whole genome sequences from four Northwestern Kyushu Yayoi individuals excavated from Nagasaki Prefecture, Japan. The two individuals retained nearly full Jomon ancestry, demonstrating that unadmixed Jomon descendants persisted alongside the admixed populations until the transitional phase between the Early and Middle Yayoi periods. The other two individuals showed clear evidence of an admixture, and genetic analyses indicated that gene flow between migrants and the indigenous Jomon population had already begun in this region approximately 2.5–2.6 kya. These findings suggest that the admixture in northwestern Kyushu occurred gradually rather than through a single large-scale migration event at the onset of the Yayoi period, offering new insights into the complex demographic dynamics that shaped the genetic landscape of ancient Japan.

Unraveling vibronic interactions in molecules functionalized with optical cycling centers

We report detailed characterization of the vibronic interactions between the first two electronically excited states, à and B̃, in SrOPh (Ph = phenyl, –C6H5) and its deuterated counterpart, SrOPh-d5 (-C6D5). The vibronic interactions, which arise due to non-adiabatic coupling between the two electronic states, mix the B̃,ν0 state with the energetically close vibronic level, Ã,ν21ν33, resulting in extra transition probability into the latter state. This state mixing is more prominent in the deuterated molecule because of the smaller energy gap between the interacting states. We model the mixing of the à and B̃ states using the Köppel–Domcke–Cederbaum (KDC) Hamiltonian parameterized in the diabatic framework of Ichino, Gauss, and Stanton on the basis of equation-of-motion coupled-cluster calculations. The simulation attributes the observed mixing to a second-order effect mediated by linear quasi-diabatic couplings between the ÖC̃ and B̃–C̃ states. Based on the measured spectra, we deduce an effective coupling strength of ∼0.5 cm−1. Non-adiabatic couplings between different electronic states are an important factor that should be considered in the design of laser-cooling protocols for complex molecules.

Rab43 mitigates the inflammatory response in acute lung injury via MyD88 ubiquitination

Water adsorption on a GaP(110) surface: A UHV study

The interaction of molecular water with the GaP(110) surface has been studied under ultrahigh vacuum conditions with a combination of x-ray photoelectron spectroscopy (XPS), scanning tunneling microscopy (STM), low-energy electron diffraction (LEED), and temperature-programmed desorption (TPD) methods. An adlayer of water at 1 ML coverage (referenced to the number of undercoordinated Ga surface atoms) desorbs from the GaP(110) surface over the temperature range of 250–370 K in TPD experiments. This water monolayer exhibited a c(2 × 2) surface structure, observed with both LEED and STM, consisting of alternating OH and H2O surface-bound species, as determined by XPS data. However, at water coverages below 1 ML, the surface concentrations of OH species were higher than that of molecular H2O, and in the 0–0.75 ML surface coverage range, the (OH:H2O) ratio was constant at 2:1. We also observed another stable surface adlayer at 4/3 ML water coverage that exhibited quasi-ordering with a c(3 × 2) LEED pattern. TPD spectra showed that this extra 1/3 ML desorbed near 210 K before the onset of the desorption of the 1 ML coverage.

Abnormal epigenetic aging of epigenetic outliers in normal colon mucosa from colorectal cancer patients

Effects of basis sets and tight d-functions in quantum Monte Carlo and CCSD(T) calculations with pseudopotentials

The diffusion Monte Carlo (DMC) method is generally considered less sensitive to basis set incompleteness than conventional electronic structure approaches. Its performance for systems containing second-row elements in high oxidation states—where tight d-functions play an essential role—remains insufficiently explored. In this work, we investigate the influence of basis sets and high-exponent d-functions on atomization energies of molecules containing first- and second-row elements using both DMC and CCSD(T) with correlation-consistent effective core potentials. Tight d-functions are found to significantly affect the nodal structure of the trial wave functions, particularly for molecules containing second-row elements in high oxidation states, thereby impacting the DMC energies. For molecules containing second-row elements, at least the a(T+d)Z or aQZ basis set is required to obtain accurate results, whereas molecules containing second-row elements in high oxidation states demand even larger sets such as a(Q+d)Z or a5Z. Moreover, basis set effects on DMC energies are approximately half those observed at the HF level, with a strong correlation between the two, suggesting that HF calculations can provide useful guidance for basis set selection in DMC. These findings highlight the critical role of tight d-functions in ensuring reliable DMC predictions for chemically challenging systems.