Browse Articles

Performance of GESC and LRESC models for heavy-atom nuclear magnetic shieldings

Some models have been developed recently to calculate and analyze the electronic origin of the nuclear magnetic shielding tensor. We present here the most recent results of calculations performed with the Geometric Elimination of the Small Component (GESC) model, which represents a partial improvement of the Linear Response Elimination of the Small Component (LRESC) model, particularly concerning diamagnetic contributions. We have found that the accuracy of the diamagnetic contributions obtained with the GESC model is higher than the one obtained with the LRESC model for any molecular system. The difference between the LRESC (σdLRESC) and the four-component (σpp) methods is mainly due to the Fermi contact mechanism (σFC,LRESC). In the case of the GESC model, the contribution of such electronic mechanism is lowered by a factor of 5/7 with respect to σpp. Furthermore, the next important mechanism that contributes to the differences between σdLRESC and σpp is known as DiaK (σDiaK), being its values close to half of that due to σFC,LRESC. We analyze here the electronic mechanisms involved in the NMR shielding of halogen atoms of the following family of compounds: HX, IX, and AtX, where X = H, F, Cl, Br, I, At, and the shielding of the central atoms in the following family of molecules: Sn4−iXi and PbH4−iXi with i = 1–4 and X = H, F, Cl, Br, I. The calculations were performed at the LRESC-HF/DFT and GESC-HF/DFT levels of theory together with four-component DHF.

Adaptive control for microgrid frequency stability integrating battery energy storage and photovoltaic

Abstract The integration and control of Microgrid (MG) systems remain critical challenges in the widespread adoption of renewable energy sources, especially photovoltaic (PV). An adaptive control approach is proposed in this work to improve the MG stability in the presence of PV and battery energy storage systems (BESSs). The proposed approach incorporates adaptive centralized secondary control, primary control, and local PV/BESS control. The primary control based on the droop control approach is applied to regulate voltage and frequency in a decentralized manner while ensuring balanced power-sharing among different distributed generators (DGs) in the MG. Besides that, an adaptive coordinated secondary control is implemented to alleviate the deviations of frequency and voltage caused by PV intermittent generation and load variation, which has a central controller that restores nominal setpoints for all DGs. The BESS type used in this study is a lithium-ion battery which is applied to preserve the DC bus voltage approximately constant during various events, enhance system resilience against PV power intermittency, and balance load power demand. The biggest advantage of the proposed control approach is that it dynamically regulates battery charging and discharging to compensate for variations in PV generation and load demand, ensuring stable system operation. In contrast to conventional studies that assume an ideal DC source to represent DGs, this study models PV generation with real-time fluctuations and maximum power point tracking, providing a practical and realistic simulation environment. The robustness and effectiveness of the proposed technique are validated using MATLAB Software. The results obtained signify highly efficient voltage and frequency stability, improved system resilience under dynamic conditions, and optimal power-sharing among DGs. Finally, a comparative analysis with conventional models highlights the superior adaptability and reliability of the proposed approach, making it a viable solution for real-MG applications.

Multimode vibrational activation and energy transfer in single-molecule CO hopping on Pd(111)

We report a vibrationally induced single-molecule hopping of carbon monoxide (CO) on Pd(111) by action spectroscopy with a scanning tunneling microscope (STM-AS). The observed hopping yields reveal vibrational thresholds at 96, 124, 142, and 230 meV, which correspond to high-order overtones of the metal–carbon (M–C) stretch mode and the fundamental C–O stretch mode. Morse potential fitting enables quantitative estimation of anharmonicity and supports overtone-driven activation. Comparison with previous studies on Pd(110) shows that the significantly higher reaction yield on Pd(111) arises from enhanced anharmonic coupling between high-frequency modes and the frustrated translational mode, the reaction coordinate for lateral hopping. This work emphasizes the role of site-dependent anharmonic interactions in energy transfer, with overtone excitations as an available pathway. Our findings offer new insights into multimode vibrational activation mechanisms in surface reactions and highlight a means of manipulating molecular motion at the atomic scale.

Vitexin induces apoptosis and enhances daunorubicin efficacy in acute leukemia via modulation of the HIF-1α/Bcl-2/caspase-3 pathway

Abstract Acute leukemia is an aggressive hematologic malignancy with limited treatment success owing to drug resistance, severe adverse effects, and high costs. Vitexin, a natural compound, demonstrates promising anticancer properties by modulating multiple pathways and inducing apoptosis, while maintaining favorable toxicity profiles. This study examined the pro-apoptotic effects of vitexin on leukemic cell lines (NB-4 and MOLT-4) and patient-derived bone marrow cells, as well as its combined effect with daunorubicin. Cytotoxicity was evaluated using MTT, apoptosis was assessed via Annexin V/PI flow cytometry, and molecular mechanisms were elucidated through in silico bioinformatic, RT-qPCR, and Western blot analyses. Vitexin decreased cell viability in a dose- and time-dependent manner (48 hours of IC 50 : 901 µM in NB-4, 929 µM in MOLT-4), with minimal toxicity in normal PBMCs. Synergistic interaction with daunorubicin was confirmed through the combination index. Vitexin elevated apoptosis up to 42.82% by downregulating HIF-1α and upregulating caspase-3 at both transcriptional and translational levels. Patient-derived bone marrow cells, the combination treatment induced the highest apoptosis (22.15% AML, 18.82% ALL). Vitexin induces apoptosis via modulation of HIF-1α/Bcl-2/caspase-3 pathway and potentiates efficacy of daunorubicin, thereby supporting potential as an adjunctive therapeutic in acute leukemia. Further in vivo studies are necessary to elucidate pharmacokinetics and clinical applicability.

Exploring nonlinear ion dynamics in polymer electrolytes from the perspective of hopping models

Nonlinear ion transport in polymer electrolytes provides key information about the underlying energy landscape and transport mechanisms. Molecular dynamics simulations are employed to investigate the field-dependent ion dynamics in poly(ethylene oxide)/LiTFSI mixtures over a range of temperatures and salt concentrations. The electric-field dependence of the current and the parallel and orthogonal diffusivities is analyzed in detail. In the weak-field regime, the nonlinear response reflects the degree and character of energetic disorder, while in the high-field regime, effective hopping distances and barrier heights can be extracted. The resulting hopping lengths agree with the typical nearest-neighbor separations from structural analysis and show little dependence on salt concentration. The apparent linear decrease in the effective activation barriers with increasing field accounts for the onset of unbounded ion motion at high fields. Comparison with analytically tractable hopping models in disordered energy landscapes provides a consistent physical interpretation of both the low- and high-field regimes. Overall, the study demonstrates how hopping models can be employed to quantitatively and conceptually rationalize nonlinear ion dynamics in polymer electrolytes.

Entropy measures based on Nirmala coindices for silicon carbide molecular graphs

Artificial thermalization in ring-polymer molecular dynamics: The breakdown of RPMD for gas-phase reactions with pre-reactive complexes and how to fix it

Ring-polymer molecular dynamics (RPMD) has become a popular method for describing chemical reactions due to its ability to simultaneously capture tunneling, zero-point energy, anharmonicity, and recrossing. Here, we highlight that despite its many successes, great care must be taken when applying RPMD to study gas-phase reactions at low pressure. We show that, for bimolecular reactions that proceed via pre-reactive complexes, RPMD predicts spuriously large rates at low temperatures and pressures. Using the rigorous connection between RPMD and semiclassical instanton theory, we demonstrate that this breakdown can be understood in terms of an intrinsic problem with RPMD that we call “artificial thermalization.” In the present context, this opens up reactive channels below the reactant asymptote that should be energetically inaccessible, resulting in erroneously large rates. We discuss practical strategies to overcome this problem by combining the steepest-descent inverse Laplace transform with Bleistein’s uniform approximation to calculate the thermal rate given an appropriate lower energy bound.

Nonparametric quantile regression captures regional variability and scaling deviations in Atlantic surfclam length–weight relationships

Solid-angle nearest-neighbor method for size-disperse systems of spheres

Identifying nearest neighbors accurately is essential in particle-based simulations, from analyzing local structure to detecting phase transitions. While parameter-free methods, such as Voronoi tessellation and the solid-angle nearest-neighbor (SANN) algorithm, are effective in monodisperse systems, they become less reliable in mixtures with large size disparities. We introduce SANNR, a generalization of SANN that incorporates particle radii into the solid-angle criterion for robust, size-sensitive neighbor detection. We compare SANNR against Voronoi, Laguerre, and SANN in binary and size-disperse sphere mixtures. Using Wasserstein distance metrics, we show that SANNR closely matches size-aware Laguerre tessellation while preserving the geometric continuity of SANN. Applied to the crystallization of the complex AB13 phase, SANNR improves detection of local bond-orientational order and better captures the emergence of global symmetry. SANNR, thus, offers a smooth, parameter-free, and extensible framework for neighbor detection in polydisperse and multicomponent systems.

Defensive responses of titan triggerfish to tiger sharks at a provisioned reef

Phase behavior of a machine-learning potential trained on stress–strain curves: The case of superionic water ice

We analyze the transferability of a Deep Potential Machine Learning (DP-ML) model trained to reproduce stress–strain curves of high-temperature/high-pressure crystalline phases of water, determining the coexistence lines for the phase transitions between the insulating ice X and the superionic ice XVIII and that between ice XVIII and its melt. Using a set of various free-energy calculation techniques, we find the resulting coexistence lines to be in good agreement with previous data, indicating that the deformation-trained DP-ML model also transfers to thermodynamic properties. This suggests that the inclusion of deformed solid states in training sets may also be a beneficial general strategy in the development of ML interaction models for other condensed-matter systems. Furthermore, the DP-ML model should be useful to investigate other aspects of the considered phase transitions. One of these involves the possible characterization of the XVIII–liquid transition as weakly first-order, with its potentially associated continuous-like behavior. This is an interesting prospect since it might be the first example of such a transition in a three-dimensional structural solid–liquid transformation.

Lactiplantibacillus plantarum from Thai fermented pork with inulin ameliorates metabolic disturbances through proteomic mechanisms

Repetitive proteins that undergo large conformational changes evade structural prediction algorithms

Protein structure prediction algorithms, such as AlphaFold, have accelerated protein design and advanced the understanding of the relationship between amino acid sequence and protein structure. However, these algorithms are limited in their ability to predict the structures of conformationally dynamic, intrinsically disordered, and stimuli-responsive proteins. To evaluate sequence-to-structure predictions of such challenging proteins, we explored a class of conformationally dynamic, repeats-in-toxin (RTX) proteins. RTX proteins adopt intrinsically disordered conformations in the absence of calcium and undergo reversible folding into β-roll structures upon binding to calcium. RTX proteins are characterized by tandem repeats of the sequence GGXGXDXUX, in which X can be any amino acid and U is an aliphatic amino acid. We designed RTX sequence variants with global substitutions of nonconserved amino acids, tandem repeats of consensus sequences GGAGXDTLY, and tandem repeats of scrambled sequences GGAGXDTYL. AlphaFold2 and AlphaFold3 predicted that all of these RTX variants adopt β-roll structures, characteristic of wild-type RTX bound to calcium. However, modeling the predicted structures with molecular dynamics simulations and characterizing the protein variants with circular dichroism spectroscopy, small-angle x-ray scattering, and x-ray crystallography revealed that variants adopt diverse, sequence-dependent structures in the absence and presence of calcium. To better design proteins for applications in biotechnology and sustainability, it is critical to build predictive tools that consider intrinsically disordered protein states and validate these tools with multi-mode, multi-scale experimental data.

Investigating the influence of astringent compounds on oral lubrication and the protective role of proline-rich proteins

Abstract Astringency, characterized by dryness and roughness in the mouth, is a major challenge for the acceptance of plant-based protein-rich foods. The mechanisms behind this sensation, particularly the role of mucins and the oral epithelium, remain unclear. This study investigates the impact of tannins, specifically epigallocatechin gallate (EgCG), on oral lubrication and examines the role of MUC1 protein in the lubrification and potentially in the astringency perception. The protective effect of proline-rich proteins (PRPs) is also explored. In vitro tribological tests were performed on four oral epithelial models expressing different MUC1 isoforms, using a reconstructed mucosal pellicle. A homemade biotribometer measured friction and dissipated energy to assess tannin-mucin interactions. Results confirm that EgCG disrupts epithelial lubrication, increasing frictional forces. However, MUC1 expression, particularly its structure, reduces these effects by preventing tannin aggregation and preserving lubrication. PRPs also enhance lubrication by binding tannins, limiting their interaction with mucins. This study highlights the roles of MUC1 and PRPs in oral lubrication in the presence of tannins.

Quantum hierarchical Fokker–Planck equations with U(1) gauge fields [U(1)-QHFPE]: A computational framework for Aharonov–Bohm effects

We present a software package that solves the quantum Fokker–Planck equation with gauge fields, formulated within the hierarchical equations of motion framework [U(1)-QHFPE]. The framework rigorously preserves gauge invariance and rotational symmetry under non-Markovian and non-perturbative system–bath (S–B) interactions, enabling accurate simulations of transport phenomena such as the Aharonov–Bohm effect under thermal environments. In a strong S–B coupling regime, quantum S–B entanglement emerges naturally. The demonstration programs perform calculations of response functions in Aharonov–Bohm ring geometries with a mechanical potential that may induce quantum tunneling, thereby illustrating the software’s capability to resolve topological quantum interference in dissipative open systems. Written in C++, the code includes a central processing unit version with highly readable OpenMP directives and a graphics processing unit version tailored for high-performance computing.

FireCastNet: earth-as-a-graph for seasonal fire prediction

Calculating excitonic interactions using transition currents with application to PTCDA

We consider assemblies of molecules where the electronic wavefunctions of different molecules do not overlap. Typically, the interaction Hamiltonian between two molecules is then described by their Coulomb interaction, and matrix-elements between products of single-molecule energy eigenstates are calculated using the corresponding (transition) charge densities. In the present work, we compare this approach with one based on (transition) current densities. As an example, we perform calculations for 3,4,9,10-perylenetetracarboxylicacid-dianhydride (PTCDA) molecules in different arrangements. We find that for exact molecular wavefunctions, both methods agree, but there are marked differences for the wavefunctions that we obtained from electronic-structure theory. The main difference can be attributed to the error in the molecular transition energy and results in an arrangement-independent ratio between the interactions calculated with the two approaches. At small separations between the molecules, additional deviations occur, which we trace back to the quality of the molecular electronic wavefunctions. Within both approaches, we calculate interactions for the arrangement of PTCDA on KCl and NaCl surfaces and compare to the ones obtained using the point–dipole approximation. Finally, we provide a simple algorithm that allows fast and accurate calculations of the involved integrals.

Constructing a prognostic signature of tumor-associated B lymphocytes in hepatocellular carcinoma via machine learning integration

Revisiting the access conductance of a nanopore in a charged membrane

Electric-field-driven electrolyte transport through nanoporous membranes is important for applications including osmotic power generation, sensing, and iontronics. We derive an analytical equation in the Debye–Hückel regime and a semi-analytical equation for arbitrary surface potentials for the electric-field-driven electric current through a pore in an ultrathin membrane, which predict scaling with fractional powers of the pore size and Debye length. We show that our theory for arbitrary electric potentials accurately quantifies the ionic conductance through an ultrathin membrane in finite-element method numerical simulations for a wide range of parameters and generalizes a widely used theory for the access electrical conductance of a membrane nanopore to a broader range of conditions. Our theory predicts that fractional power-law scaling of the ionic conductance with electrolyte concentration at low concentrations is an intrinsic property of charged ultrathin membranes and also occurs for thicker membranes for which the access contribution to the conductance dominates, which could help to explain experimental observations of this widely debated phenomenon.

Anatomical and anthropometric predictors of femoral and saphenous nerve location for ultrasound guided procedures