Browse Articles

The influence of packing protocol, size ratio, and pore structure on fractal exponents in dense polydisperse packings

We study fractal properties of systems of densely and randomly packed disks, obeying a power-law distribution of radii, which is generated by using various protocols: Delaunay triangulation (DT) and constant pressure (CP) protocols and the generalized Apollonian packing. The power-law exponents of the mass-radius relation and structure factor are obtained numerically for various values of the size ratio of the distribution, defined as the largest-to-smallest radius ratio. We show that the size ratio is an important control parameter responsible for the consistency of the fractal properties of the system: the larger the ratio, the less pronounced the finite-size effects and the better the agreement between the exponents. For the DT protocol, all three exponents coincide even at moderate values of the size ratio. For the CP protocol, the exponents are different for both moderate and large size ratios. The suppression of the exponent of the structure factor in the CP packing is explained by the specific behavior of pores, which contain relatively large cavities. We develop an algorithm for calculating the pore size distribution and show that it is related to the exponent of the structure factor. We argue that the presence of the cavities lowers the configurational entropy and, thus, reduces the randomness of the CP packing. Thus, the cavities reduce both packing fraction and randomness of the CP packings. Nevertheless, there is a tendency for the exponents to converge as the size ratio increases, suggesting that all the exponents become equal in the limit of an infinite size ratio.

Unveiling climate transformations in the northwestern Caucasus: the Middle Holocene divergence of landscape evolution

Interference effects on the x-ray emission spectra of liquid water and analysis of an attosecond pump-probe model

We report a detailed investigation of the importance of vibrational direct and interference effects in x-ray emission applied to water. We use the full Kramers–Heisenberg (KH) expression on a 2D grid with the two OH-stretches of a central water molecule as coordinates and solve for the relevant vibrational states, providing direct and interference terms. For two pentamer models, we show close agreement between high-level adiabatic diagrammatic construction and time-dependent density functional theory results, and apply to four larger 32-molecule clusters representing high- (HDL) and low-density liquid (LDL) and two intermediate structures. We find for HDL and LDL an initial split (without dynamics) of 0.6 eV, which is increased to 0.7 eV using the full KH expression, i.e., the observed split is dominated by the initial H-bonding. The importance of direct and interference contributions is different for HDL and LDL structures, where for HDL, the full spectrum is well represented by the direct contribution, while for LDL, the 3a1 is strongly enhanced in the direct spectrum, and the 1b1 has large interference contributions. In a recent attosecond x-ray pump/x-ray probe spectrum, only one 1b1 peak was observed together with a significantly increased intensity in the 3a1 region. We reassign the features due to molecules in asymmetric H-bond situations (1b1 peak) and molecules in tetrahedral H-bonding (3a1 intensity) in this experiment, where only direct terms contribute. To eliminate the need for precomputed potential energy surfaces, we show that a semi-classical approximation to the KH formalism gives excellent agreement, including vibrational fine-structure, with the full KH spectra for the four 32-molecule clusters.

Physical synchronisation for anomaly detection in epidemic blockchain consensus

Abstract Gossip protocols propagate information through peer-to-peer networks analogously to epidemic spreading, yet this analogy has remained informal. Here, we formalise it for blockchain consensus by means of a phase-encoding under which the dynamics reduce, at leading order and in a weak-coupling regime, to coupled-oscillator synchronisation on complex networks. Block preferences correspond to oscillator phases, communication latencies to natural frequencies, and network topology to the coupling graph. The resulting order parameter (a synchronisation measure from statistical physics) tracks simulated network consensus with a correlation of $$\rho =0.997$$ and represents it as a phase transition. Consensus disruptions then appear as phase-coherence disturbances, providing candidate anomaly signals for node isolation, network partitions, and block withholding (three typical attacks on blockchains). On real blockchain data, where continuous phase dynamics are not observable, we construct a static phase proxy from per-pool block-attribution statistics; applied to Bitcoin, this proxy-based detector identifies the 2013 chain fork at $$5.1\sigma$$ significance on unmodified data. Validation on a second protocol family confirms that the phenomenology generalises. This framework expands physicists’ reach into adversarial systems, provides epidemic modellers with an empirical testbed, and offers blockchain operators a complementary, consensus-layer anomaly signal.

Diagrammatic multiplet-sum method (MSM) density-functional theory (DFT). III. Inclusion of relaxation and application to LiH

Ideal density-functional approximations (DFAs) should account for dynamic, static, and nondynamic correlation. While common DFAs struggle with the latter two, the Ziegler–Rauk–Baerends–Daul multiplet sum method (MSM) provides a pragmatic way to include static correlation. In this article, we use diagrammatic MSM density-functional theory (diag MSM DFT) using the two-orbital two-electron model to extend MSM DFT to include nondynamic correlation without relying on symmetry arguments. Building on previous formulations [Ponra et al., J. Chem. Phys. 159, 244306 (2023) and Casida et al., J. Chem. Phys. 162, 144317 (2025)] that lacked relaxation effects, this article incorporates relaxation via nonorthogonal configuration interaction. We demonstrate that this modified diag MSM DFT produces an accurate ground-state potential energy curve for lithium hydride, even at the ionic-to-open-shell-singlet avoided crossing characterized by significant charge transfer. This encouraging result suggests that the model can be extended to (at least) other singly and multiply bonded diatomic molecules, while providing insight into a novel way to include strong correlation in DFT.

Intelligent optimization of personalized learning path based on transformer and reinforcement learning

The interfacial thermal resistance at liquid–vapor interfaces and the role of intrinsic surface analysis

A jump in temperature across the liquid–vapor interface has been observed in both experiments and non-equilibrium molecular dynamics (NEMD) simulations. If capillary fluctuations are removed by evaluating properties in simulations relative to the intrinsic surface, a small peak in the intrinsic density profile—referred to as an adsorbed layer—appears on the vapor side of the interface next to the temperature jump. It has been proposed that this adsorbed layer introduces a resistance to heat transfer that causes the temperature jump. We revisit this explanation by simulating liquid–vapor systems of Lennard-Jones spline particles and analyzing properties relative to the intrinsic surface at both equilibrium and non-equilibrium. We find that the intrinsic density profiles with the same liquid-phase temperature are nearly identical at equilibrium and non-equilibrium, and that the adsorbed layer is very similar in both cases. We show that, when transforming the density to time-averaged coordinates, the particles in the adsorbed layer spread across most of the interfacial region, while the large gradient in temperature is located outside the interfacial region. The reported linear correlation between vapor-side adsorption of the intrinsic density and interfacial thermal conductance is also observed using an alternative definition of adsorption based on time-averaged NEMD profiles, even though the latter contains only about 12% adsorbed particles. We argue that this correlation arises because both quantities increase with interfacial width. Although intrinsic surface analysis provides valuable insight in many contexts, we do not find evidence that the molecular origin of interfacial thermal resistance at vapor–liquid interfaces is governed by the adsorbed layer.

Topical mosquito repellency of a Litsea cubeba essential oil spray against Aedes aegypti, Anopheles dirus, and Culex quinquefasciatus

Abstract Mosquito-borne diseases remain an important global public health concern, and increasing insecticide resistance has strengthened interest in complementary personal protection tools. This study evaluated the short-term dermal tolerability and laboratory repellency of MosShield, a ready-to-use topical spray formulated with 6% w/w Litsea cubeba essential oil. Non-confidential formulation quality-control parameters, including appearance, homogeneity, pH, density, and apparent viscosity, were recorded to support formulation consistency before testing. Short-term dermal tolerability was assessed using a human skin-patch test in 48 healthy volunteers, with no visible skin reactions observed up to 96 h after application. Repellency assays were conducted following the World Health Organization arm-in-cage protocol against three medically important mosquito species: Aedes aegypti , Anopheles dirus , and Culex quinquefasciatus . The formulation showed species-dependent repellency, achieving median complete protection times of 225 min against Cx. quinquefasciatus and 120 min against both Ae. aegypti and An. dirus. These findings provide product-relevant laboratory evidence supporting further evaluation of the 6% L. cubeba essential oil spray as a plant-based topical mosquito repellent under semi-field and field conditions.

Generation of robust entanglement in plasmonically coupled quantum dots driven by quantum squeezed light

Can quantum light reliably generate entanglement in systems with dissipation? Our cavity quantum electrodynamics calculations demonstrate that a single-mode squeezed light source can robustly generate steady-state entanglement between a plasmonically coupled pair of quantum dots. The strong coupling of plasmons to the light source and the pairwise nature of squeezed photon generation enable entanglement between quantum dots. This entanglement, measured as concurrence, can be improved by replacing an entangled photon-pair pulsed source of light with continuous pumping of squeezed photons. Unlike previously introduced schemes, the concurrence is robust against variations in the system parameters. Specifically, the generation of entanglement does not rely on fine-tuning of the plasmon–quantum dot coupling. These results provide a new perspective for robust entangled-state preparation in open quantum systems.

Perceptions of interprofessional education among medical and dental students in the United Arab Emirates: a cross-sectional study

Electron proton-coupled transfers in [NH4][H3N] <i>n</i> ( <i>n</i> = 1, 2) Rydberg clusters: A machine learning-path integral study

Using a combination of path-integral molecular dynamics and machine-learning techniques, we investigate the structure, energetics, and proton-transfer isomerizations in small Rydberg complexes of the form [NH4][NH3]n (n = 1, 2), at temperatures near T = 50 K. In both clusters, the unpaired negative charge resides predominantly outside the molecular framework and is localized near the unit exhibiting the strongest NH4 character. Relative to classical estimates, the combined effects of thermal and nuclear quantum fluctuations shift the computed vertical detachment energies upward, yielding improved agreement with available experimental measurements. Qualitative and quantitative distinctions emerge between the molecular-orbital Rydberg description and solvated electron scenarios in analogous isoelectronic species of the form (NH3)n−. We further characterize proton-transfer-mediated interconversions between isomeric structures. For the dimer, the reactant and product states are equivalent, whereas in the trimer, the rearrangement involves migration of the NH4 radical from a distal to a central position along a hydrogen-bonded chain. Nuclear quantum effects also substantially modify the free energy landscapes associated with proton-transfer isomerizations, most notably through pronounced tunneling induced reductions of the magnitudes of the activation barriers. At the transition states, a strong correlation is registered between the degree of quantum delocalization of the transferring proton and the spatial distribution of the unpaired electron.

Gut microbiome signatures associate with DNA methylation-based biological aging

Reimagining singlet exciton fission: Insights from dimer architectures

Singlet fission (SF) is an ultrafast bimolecular photophysical process in which a high-energy singlet excited state redistributes its energy into two lower-energy unbound triplet states, allowing a theoretical triplet quantum yield of up to 200%. Extensive studies over the past decade and a half have shown that SF proceeds through the formation of a spectroscopically detected correlated triplet–triplet pair (TT) intermediate, which subsequently dissociates to form the requisite two independent triplet excitons. Efficient separation and utilization of these triplets requires a detailed understanding of their generation and extraction in molecular aggregates and thin films. However, limited control over film morphology and intermolecular packing often makes it difficult to systematically tune SF rates. In this perspective, we summarize mechanistic insights gained from steady-state and time-resolved spectroscopic investigations of well-defined dimeric chromophore systems. We highlight the key relaxation and loss pathways that emerge subsequent to formation of the TT state, which can lower the effective triplet yield to less than 100% undoing the opportunities that SF presents. We further discuss strategies to promote the dissociation of TT pair into free triplets rather than undergoing annihilation processes, even within such dimeric architectures. Finally, although triplet extraction from dimers is commonly viewed as inefficient, we outline possible approaches for enabling effective harvesting of triplet excitons in relevant timescales from these molecular architectures.

An opposition based Gooseneck Barnacle Optimizer for energy-efficient UAV path planning in urban low altitude environments

Reentrant phase transition in pH-responsive microgel suspensions

We report here experimental evidence of a reentrant [fluid (liquid-like) to crystal to fluid (liquid-like)] phase transition in pH-responsive poly(N-isopropyl acrylamide)-co-poly(acrylic acid) [PNIPAM-co-PAac] microgel suspensions. Upon increasing the pH (NaOH), a liquid-like ordered PNIPAM-co-PAac microgel suspension changes to crystalline order and reenters into liquid-like order with a further increase in pH (NaOH). The observed reentrant phase behavior is explained in terms of an increase in volume fraction caused by osmotic swelling of microgels as well as an increase in Coulombic repulsion between microgels due to dissociation of acrylic acid groups at the initial pH (NaOH) and then a decrease in the volume fraction caused by osmotic deswelling of microgels along with screening of the Coulombic interactions between microgels by Na+ ions at higher pH (NaOH). Furthermore, as a consequence of reentrant structural transition, PNIPAM-co-PAac microgel suspensions exhibit reentrant viscoelastic properties, i.e., a suspension in a viscoelastic liquid-like state changes to a viscoelastic solid-like state upon increasing pH (NaOH) and reenters into a viscoelastic liquid-like state with further increase of pH (NaOH). Present results are discussed in line with the earlier reported experimental and simulation work on microgels and other charged colloidal suspensions.

Association between silymarin and age-related macular degeneration in patients with liver dysfunction: a nationwide cohort study

Freezing under motion: How surface vibrations suppress ice nucleation in water nanofilms

Suppressing ice nucleation in interfacial water nanofilms is critical for preventing macroscopic icing in a wide range of natural and engineered systems. Surface vibrations have been proposed as a promising, energy-efficient anti-icing strategy, yet the molecular mechanisms by which surface vibrations inhibit ice nucleation remain poorly understood. Here, we use molecular dynamics simulations to investigate how harmonic surface vibrations influence heterogeneous ice nucleation in supercooled water nanofilms. We identify two distinct and complementary mechanisms. First, surface vibrations induce acoustothermal heating in the adjacent liquid, reducing the degree of supercooling and thereby lowering nucleation rates. Beyond this thermal effect, we uncover a separate (non-thermal) kinetic mechanism: surface vibrations disrupt the interfacial water structure by increasing molecular mobility and dispersing the spatial arrangement of water molecules near the surface, thereby hindering the formation of stable pre-nucleation structures. Vibrations significantly reduce nucleation rates, indicating that kinetic disruption alone can suppress freezing even when liquid temperature is held constant. Direct structural analysis confirms this kinetic mechanism: both the population of ice-like clusters and the tetrahedral order of interfacial water decrease under vibration. By mapping vibration-induced structural changes onto an effective surface temperature, we show that relatively small reductions in interfacial water density correspond to substantial increases in the free-energy barrier for nucleation near the freezing limit. These results provide molecular-level insight into vibration-mediated control of ice formation and highlight surface vibrations as a powerful strategy for suppressing ice nucleation at its nanoscale origin.

Insight into cytotoxic and molecular mechanisms of bee venom and its nanoemulsion against West Nile virus in vitro

Abstract West Nile virus (WNV) causes West Nile fever and is primarily transmitted by Culex spp. mosquitoes. The primary hosts of WNV are birds, while humans and horses can also develop illness following infection. Currently, no specific antiviral therapy exists for WNV, and vaccination remains the only effective preventive measure. This study aimed to evaluate the efficiency of the crude bee venom (BV) and its nanoemulsion (NE) on WNV by determining in vitro Vero cells cytotoxicity and viral titer by RT-qPCR. We also conducted BV peptides-envelope glycoprotein of WNV interactions by molecular docking analysis. The NE of BV was characterized by dynamic light scattering (DLS) and zeta potential analyses. The DLS revealed that the size of NE was greater than that of BV. Also, the DLS showed that the polydispersity index of NE was less than that of BV (0.349 and 0.557, respectively). Zeta potential analysis of NE was slightly less than that of BV (23.0 and 23.7 mV, respectively). Both treatments showed low cytopathic effects on Vero cells compared to positive control infected with WNV. RT-qPCR revealed that the titer of WNV was lower in cells treated with BV and its NE than in controls. Molecular docking revealed BV peptides-envelope glycoprotein of WNV interactions, with binding energy of − 5.2, − 4.5, − 13.0, − 10.8, and − 5.1 kcal/mol for the peptides apamin, tertiapin, melittin, mast cell degranulating peptide, and secapin-2 peptide, respectively. BV-NE demonstrated preliminary in vitro anti-WNV activity requiring mechanistic, toxicological, and in vivo validation.

Data-efficient multidimensional free energy estimation via physics-informed score learning

Many biological processes involve numerous coupled degrees of freedom, yet free-energy estimation is often restricted to one-dimensional profiles to mitigate the high computational cost of multidimensional sampling. In this work, we extend Fokker–Planck Score Learning (FPSL) to efficiently reconstruct two-dimensional free-energy landscapes from non-equilibrium molecular dynamics simulations using different types of collective variables. We show that explicitly modeling orthogonal degrees of freedom reveals insights hidden in one-dimensional projections at negligible computational overhead. Additionally, exploiting symmetries in the underlying landscape enhances reconstruction accuracy, while regularization techniques ensure numerical robustness in sparsely sampled regions. We validate our approach on three distinct systems: the conformational dynamics of alanine dipeptide, as well as coarse-grained and all-atom models of solute permeation through lipid bilayers. We demonstrate that, because FPSL learns a smooth score function rather than histogram-based densities, it overcomes the exponential scaling of grid-based methods, establishing it as a data-efficient and scalable tool for multidimensional free-energy estimation.

The optimization model and empirical analysis of teaching resource allocation and business collaboration under the background of higher education informatization