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An urban bryophyte hotspot in an industrial city: the case of Ostrava Zoo (Czech Republic)
On the second-order functional structure of the chemical potential in conceptual density functional theory
The second-order functional structure of the chemical potential is examined within conceptual density functional theory by treating μ[N, v(r)] as a functional of the electron number and the external potential. In close analogy with the nonperturbative functional expansion of the total energy introduced by Liu and Parr, the chemical potential admits an explicit functional form up to second order that does not rely on a Taylor expansion about a reference state. This representation organizes established first- and second-order response descriptors into a unified response-theoretical framework, where the linear terms recover the standard hardness and Fukui function contributions, while quadratic terms encode nonlinear charge effects and nonlocal response through the hyperhardness, charge sensitivity, and response kernel. The resulting formulation clarifies the hierarchical organization of response properties associated with the chemical potential and provides a complementary perspective on electronegativity equalization within conceptual density functional theory.
A perturbation-recovery generative autoencoder for heterogeneous graphs with attributes missing
Universal scaling laws in melting thermodynamics of gold nanoparticles: Insights from machine learning molecular dynamics
Understanding the melting behavior at the nanoscale regime serves a fundamental role in both the scientific community and industrial applications. In particular, the melting of nanoparticles (NPs) exhibits behaviors that differ qualitatively from bulk materials due to pronounced size-dependent properties and surface/volume ratio effects, but a unified theoretical understanding remains elusive. Here, by developing a machine-learning interatomic potential applicable across diverse local atomic environments and wide temperature ranges, we systematically investigate the melting thermodynamics of Au NPs spanning from small clusters (102 atoms) to large NPs (105 atoms) through a series of nanosecond-long molecular dynamics simulations. A complete solid–liquid phase diagram of NPs across 1–14 nm diameters is presented, clearly distinguishing the unique surface premelting behavior and complete melting. The size-dependent melting curve follows the Gibbs–Thomson relationship. More importantly, we demonstrate that the melting entropy changes in nanoparticle systems substantially deviate from the empirical Richard’s rule and its generalized form valid for bulk elemental systems. Moreover, we found that all the components of melting entropy follow the same scaling law, based on which we derived a thermodynamic correlation between the NP system and its bulk values. These results bridge the thermodynamic description from the single-atom limit to bulk materials, providing a unique insight for understanding and predicting nanoscale melting thermodynamics.
A logic-based knowledge-driven bidirectional multi-attention GRU framework for fear level classification in humans
Sum-frequency generation spectroscopy of the libration mode at the air/water interface: Electric quadrupole effects
Based on ab initio molecular dynamics simulations and quantum chemistry calculations, we compute the sum-frequency generation (SFG) spectroscopy of the interfacial water libration mode by incorporating the electric dipole, electric quadrupole, and magnetic dipole contributions. The results demonstrate that the electric quadrupole contribution dominates the spectrum, while the magnetic dipole contribution is non-negligible. In contrast, the electric dipole contribution is minimal due to the weak polarizability derivative. These findings are consistent with experimental SFG spectroscopy featuring a prominent peak at 834 cm−1, which can only be accurately reproduced when both the electric quadrupole and magnetic dipole terms are included. The dominance of the electric quadrupole effect is attributed to the delocalized electron density distribution inherent to librational motion, which extends beyond individual water molecules via hydrogen-bonding networks.
A two-stage preprocessing and classification approach for accurate COVID-19 detection in X-ray images
The key role of heteroatom effects in COF separation of SF6/N2: A theoretical study
Sulfur hexafluoride (SF6) is particularly important for purification and recovery in environmental management and resource optimization due to its extremely high global warming potential and widespread industrial applications. In this study, we employed grand canonical Monte Carlo simulations and density functional theory calculations to investigate heteroatom (C, N, and O) functionalization modifications of covalent organic framework (COF)-637, aiming to evaluate its selective adsorption performance for SF6/N2 mixtures. The results indicate that at 298 K and 1 bar, the selectivity values of heterocyclic COF-2O and COF-2N for SF6/N2 (10:90 v:v) mixtures are 400.79 and 353.57, respectively. The introduction of heteroatoms effectively enhances the selective separation performance of the original framework. By analyzing the adsorption isotherms of SF6 in the mixed components within the framework at pressures ranging from 0.1 to 1 bar, it is confirmed that heterocyclic modification can effectively enhance the selective capture of SF6. Further analysis, including charge difference density, Bader charges, and the independent gradient model for weak interactions, reveals the interactions between SF6 and the framework. This study provides theoretical support for understanding the adsorption mechanisms of COFs and for designing highly efficient materials for SF6 purification.
Predicting aggressiveness of clear cell renal cell carcinoma via mri using artificial intelligence: implications for surgical planning in a retrospective multicenter study
Catalyst-free activation and conversion of up to seven CO2 by a B6+ monocation
Exploring advanced materials for efficient activation and conversion of CO2 is a crucial approach to mitigate climate change and reduce reliance on fossil fuels. Extensive joint gas-phase mass spectroscopy and kinetic studies performed herein indicate that a mass-selected B6+ monocation can consecutively activate and convert up to seven CO2 to CO under ambient conditions, setting up a record number of CO2 molecules that an isolated cluster can activate in experiments. Detailed theoretical calculations and analyses reveal the ground-state, intermediate, and transition-state geometries as well as CO2-activation and CO-desorption pathways of the concerned species. The catalyst-free CO2-reduction reactions B6+ + nCO2 → B6On+ + nCO (n = 1–7) all appear to be barrier-free in kinetics and thermodynamically favorable at room temperatures, with the calculated exothermicities increasing almost linearly with the number (n) of CO2 molecules activated in the processes. Two electron-deficient periphery B atoms in B6On+ (n = 0–6) are found to serve as active sites to form one effective σ-donation and two weak π-back-donations each in two consecutive steps, with the first site activating a π-bond in O=C=O to form the O≡C–O-adsorption states, while the second site releasing a CO molecule from the CO-desorption states to form the final products, B6On+, unveiling the important role of boron as a honorary transition metal in CO2 activation and conversion.
Cost-effective FRP solutions for enhancing strength and strain of sustainable concrete made with waste tyre rubber
Cu2O/CuInS2/TiO2 double S-scheme heterojunctions for enhanced photocatalytic hydrogen evolution
To address the issues of narrow light absorption range and a high carrier recombination rate of TiO2 in photocatalytic hydrogen evolution, a Cu2O/CuInS2/TiO2 catalyst with double step-scheme (S-scheme) heterojunctions was designed and constructed. The construction of the double S-scheme heterojunctions can promote efficient carrier separation under the action of double electric fields while retaining electrons with strong reducing ability, and it can also enhance the light absorption capability through the synergistic effect of different semiconductors. Furthermore, thanks to the synergistic effects among matched energy band positions, sufficient heterojunction interface coupling, and microstructure, Cu2O/CuInS2/TiO2 exhibits an enhanced photocatalytic hydrogen evolution rate (1610 μmol g−1 h−1), which is 3.8 times higher than that of pristine TiO2. This study provides new insights into the design of double heterojunction photocatalysts and the performance enhancement of wide-bandgap photocatalysts.
A new technique inducing mitral valve regurgitation as an experimental porcine model of volume-overload induced heart failure
Abstract Heart failure (HF) is a common disease resulting in high morbidity, mortality, and healthcare costs. An important cause of HF is mitral valve regurgitation (MR), which induces left ventricular remodeling and volume overload. For HF research, a reproducible and reliable large animal model is crucial. Several MR models have been developed, but they often show high variability in MR severity and MR jet characteristics, as well as an underlying ischemic cardiomyopathy, which may increase the risk of complications during follow-up. We present a straightforward and uniform porcine model of primary MR-induced HF. A custom-made retractor was used to induce severe and uniform MR by chordal rupture. After four weeks, severe MR led to significant left ventricular remodeling compared to the sham group, with a significant increase in left ventricular end-diastolic (+34.5 ± 6.8 ml vs. +8.4 ± 5.3 ml, p = 0.023) and end-systolic volume (+29.9 ± 4.0 ml vs. +4.2 ± 2.9 ml, p = 0.001), a decrease in left ventricular ejection fraction (-11.9 ± 1.9% vs. -0.7 ± 0.9%, p < 0.001) and fractional shortening (-12.2 ± 1.3% vs. -2.2 ± 0.8%, p < 0.001), and a higher amount of left ventricular fibrosis (12.6 ± 1.0% vs. 6.4 ± 0.9%, p = 0.001). This porcine model allows a straightforward and reproducible induction of primary MR-induced HF, with a high success rate. It could be valuable in basic research to study the underlying pathophysiology and in translational research to develop novel diagnostics and therapeutics targeting volume-overload induced HF and/or primary MR.
Publisher’s Note: “Non-thermal acceleration of DNA base pairing by sub-terahertz irradiation” [J. Chem. Phys. 164, 065102 (2026)]
A cloud server centric multifactor lightweight authentication scheme for eHealth systems
Abstract The safety of transmitted data is an essential element of all Cloud-IoT-based electronic healthcare (e-healthcare) systems. Through a review of prior research, we see that there have been several different security frameworks proposed for the protection of communications between the patient, the provider and the cloud server, but most of them have significant weaknesses related to serious attack vectors such as man-in-the-middle, impersonation and denial-of-service attacks. The existence of these vulnerabilities places the sensitive health care information at risk of being compromised in terms of confidentiality and integrity. In recent years, Alzahrani et al. provided a provably secure cloud-centric authentication protocol for use with e-health care systems. It was found through a detailed analysis that their protocol lacked the robust authentication that is required to protect the system from impersonation attacks by attackers on the cloud server or the physician. Therefore, in order to resolve the issues associated with the lack of robustness, this paper provides a cloud-server-centric multi-factor authentication protocol for use in the health care environment. This protocol has the ability to combine the features of one-way hash functions, biometric identification and random number generation to provide increased security in the process of authenticating users to access the e-health care system while mitigating the previously identified vulnerabilities. The correctness and robustness of the protocol were formally analyzed using BAN Logic, the Real-Or-Random Security Model, formal verification using AVISPA Tool and practical implementation analysis. Additionally, the performance of the protocol was measured in terms of computational time, communication overhead and scalability. The results of the security analysis indicate that the proposed protocol can withstand all types of attacks on e-health care systems. Furthermore, the performance analysis demonstrated that the protocol achieved improved efficiencies over the current state-of-the-art protocols in each of the measured performance characteristics. As a result, the proposed protocol has the potential to be used in practice as part of cloud-IoT-based e-healthcare applications.
Highly holographic diffraction efficiency and recording stable macromolecule photopolymer by introducing cross-linker vinyl-POSS
The cross-linked photopolymer vinyl-POSS (Vi-POSS)-phenanthraquinone doped poly methyl methacrylate (PQ/PMMA) was successfully fabricated via a one-pot free radical thermal polymerization technique by incorporating a Vi-POSS cross-linker into PQ/PMMA. The residual C=C bonds on the Vi-POSS branches after cross-linking significantly enhanced the holographic performance, achieving a high diffraction efficiency of 83% and a sensitivity of 0.49 cm J−1, while the cross-linked polymer matrix reduced volume shrinkage to 0.28% (compared to 64%, 0.33 cm J−1, and 0.39% for PQ/PMMA). Moreover, the Vi-POSS-PQ/PMMA sample exhibited excellent stability, with a bit error rate maintained at ∼0.5% over a broad holographic recording time range (3–13 s), demonstrating its suitability for data storage applications by mitigating the effects of laser power fluctuations or system instability. Further experimental analysis confirmed the synthesis of a 3D cross-linked macromolecular network with Vi-POSS as the core. The residual C=C bonds in the Vi-POSS-PQ/PMMA matrix originated primarily from Vi-POSS, and a hexatomic cyclic –C–O–C– structure formed between Vi-POSS and PQ upon beam exposure. In conclusion, this study not only elucidates the microphysical and chemical mechanisms underlying the enhanced holographic performance of Vi-POSS-PQ/PMMA but also proposes a novel strategy to optimize storage stability for holographic data storage applications.
Splicing retention and enhancer divergence govern the evolutionary fate of ohnologues following whole-genome duplication in rainbow trout
Beyond the cutoff: Hybrid ML/MM electrostatics for neural network potentials
Atomistic Neural Network Potentials (NNPs) have been developed to predict molecular properties and electronic ground-state energies of small molecules with kcal/mol accuracy. However, despite their excellent scalability and low computational cost, atomistic NNPs are intrinsically local, making them unreliable for modeling long-range interactions in condensed-phase systems relevant to biological, engineering, and pharmaceutical applications. Recently, we demonstrated how to explicitly incorporate information on long-range interactions into the ANI NNP by retraining it in the presence of electrostatic potentials arising from the molecular environment. Effectively, the introduced embedded ANI/MM model is similar in spirit to quantum mechanics/molecular mechanics. Here, we extend this line of work by developing and training the ANI/MM network to predict binding energies for two protein–ligand complexes. We show that this network predicts forces with an error of less than 1 kcal/mol/Å, opening the possibility of using it for geometry optimizations and molecular dynamics. The resulting ANI/MM NNP outperforms the accurate, ab initio–fitted classical force field Q-Force and exhibits good transferability to new solutes, provided that the training set includes relevant structural fragments of the target molecule. Together, these findings demonstrate that hybrid ML/MM neural architectures offer a promising route toward chemically accurate, scalable modeling of complex molecular systems.
Projected compositional reorganization of Southern plant assemblages in South Korea under climate scenarios using species distribution models
Abstract Understanding how plant communities reorganize under climate change is essential for effective biodiversity conservation and restoration. We developed a spatially explicit, multi-scenario framework to evaluate future dynamics of southern (warm-temperate and subtropical-affiliated) vascular plant assemblages in South Korea. Species distribution models generated projections under three climate scenarios (SSP1–2.6, SSP3–7.0, and SSP5–8.5) across four time periods (1980–2010, 2010–2040, 2040–2070, and 2070–2100). These projections were integrated with spatial environmental clustering, kernel density estimation, and ordination-based trajectory analysis to characterize spatial persistence, compositional change, and directionality. Results revealed strong spatial heterogeneity in community responses. Environmental clusters were classified into stable, transitional, and transformational types based on the magnitude and direction of compositional change and climatic alignment. Multivariate analysis (PERMANOVA) showed that spatial cluster identity explained substantially more variation in community composition than temporal period (R² = 0.364 vs. 0.083). Stable clusters exhibited limited change and strong climatic alignment, whereas transformational clusters showed large shifts and frequent directional misalignment. Transitional clusters displayed intermediate dynamics. By jointly capturing spatial persistence, compositional trajectories, and directional coherence, this framework supports forecasting vegetation responses and climate-resilient conservation planning, with relevance to global biodiversity initiatives such as the Kunming–Montreal Global Biodiversity Framework.