Update of vegetative filter strip scenarios for pesticide risk assessment in Europe.

The g formula is a cornerstone method for estimating causal effects of time-varying treatments using longitudinal observational data in the presence of time-varying confounders that are affected by prior treatment. Standard regression techniques often fail in this setting because adjustment for such covariates can distort the very effects under study. The g-formula addresses this problem by expressing the mean potential outcome under specified static or dynamic treatment regimes as a function of the joint distribution of covariates, treatments and outcomes, which can be approximated via parametric or semi-parametric models and simulation. This review presents the g-formula, emphasizing intuitive explanations. After outlining the causal framework and the core identification assumptions-consistency, sequential exchangeability and positivity-the article describes practical parametric g-formula: model specification for covariate and outcome processes, implementation via forward simulation, and the interpretation of marginal causal contrasts between clinically relevant regimes. The g-formula is then situated within the family of g-methods alongside inverse probability weighting and targeted maximum likelihood estimation, highlighting complementary strengths and limitations. A dedicated section discusses concrete applications, including analyses of highly active antiretroviral therapy and AIDS or death, dynamic 'when to start' antiretroviral strategies in HIV and electronic health record-based evaluations of blood pressure treatment targets. Practical guidance on modelling choices, diagnostics and transparent reporting is provided to support applied researchers considering g-formula in clinical and epidemiological investigations.

High temperature, high vacuum in situ experiments on gold nanoparticles repeatedly reveal an inherently non-equilibrium evolution characterised by surface atom ejection (sublimation), shrinkage, a solid-to-liquid transition (melting) after sufficient mass loss, and evaporation of the resulting droplet until disappearance. Existing theoretical and simulation descriptions of this non-equilibrium sequence rely on the assumptions of homogeneous equilibrium thermodynamics and therefore fail to clearly identify the structural and dynamical changes that accompany the observed transitions. In this work, we establish a molecular dynamics (MD) framework that reproduces both the experimental setup and phase evolution, and identifies where and when sublimation and melting occur. From the generated MD trajectories, we extract: distribution, correlation and displacement functions, density profiles, kind of atomic motion in each nanoparticle shell. This information and the analysis thereof allow the reproduction of the experimental sequence of phase transitions and the determination of both the sublimation onset temperature and the temperature at which the melting process is complete, in quantitative agreement with experiment. The results demonstrate the importance of an appropriate choice of interaction potential and provide a numerical framework that can be extended and applied to other materials.

We present PhotonTracer, a newly developed light-scattering simulation in the geometric-optics limit accelerated on the Graphics Processing Unit (GPU). It is written in CUDA/C++, leveraging the efficient and hardware-accelerated ray-geometry intersection provided by the NVIDIA OptiX™ SDK. It is distributed as a Python package, which makes it accessible to the community. Thanks to the achieved performance, the simulation of light transport and reflectance in highly multiple-scattering semi-infinite media becomes possible on affordable consumer GPUs. A wide range of simulation parameters is accessible through customizable per-ray output buffers. This enables the calculation of many observables relevant to remote sensing, such as albedo, bidirectional reflectance distribution function, scattering phase matrices, or absorption depths. PhotonTracer is validated against two existing simulations. The scattering phase matrix elements for single particles are validated against the ray tracing simulation SIRIS4. The reflectance, transmission and absorption for a layered medium are validated against a Transfer Matrix Method simulation. To illustrate one possible application, the reflectance spectra of semi-infinite particulate ice samples with different mean particle diameters and shapes are simulated and compared to laboratory spectra of well-characterised analogues. We find a good agreement between the simulated and measured spectra, especially for the shape of the water absorption bands. PhotonTracer is well-suited to study the effects of a wide range of medium properties on light scattering. A speedup of 3 to 4 magnitudes over traditional CPU models enables the simulation of highly multiple-scattering systems without the need for simplifying assumptions. This makes it a valuable tool, which enables the inversion of remote sensing and laboratory data and can serve as a reference for analytical models. • A GPU-accelerated light-scattering model in the geometric optics limit is presented. • Highly multiple-scattering systems with negligible absorption can be simulated. • It is distributed as a Python package, making it easily accessible to the community. • A speedup of 5000x was achieved on the GPU over comparable CPU-based models.

High-temperature polymorphs of hafnia (HfO2) are of significant interest in electronics and fuel-cell applications, and stabilization at ambient conditions can be achieved by aliovalent substitution and nanosize effects. Y3+ stabilization of hafnia (YSH) introduces local cation disorder around charge-compensating oxygen-ion vacancies, and here we establish both the average and local structure of YSH nanoparticles using synchrotron powder X-ray diffraction (PXRD) and pair distribution function (PDF) analysis. A range of phase-pure crystalline nanoparticles of Hf1-xYxO2-x/2 were prepared via continuous flow solvothermal synthesis and subsequent high-temperature annealing, and full stabilization of the cubic phase is achieved already at 13 at% Y3+. The average structure conforms to the cubic fluorite phase of HfO2, but local displacive disorder caused by electrostatic attraction of neighbouring oxygen ions and repulsion of neighbouring metal ions by the net-positive oxygen-ion vacancies is established. The well-known Zr3Y4O12 structure, which incorporates such relaxation motifs, provides a good proxy description of YSH. In situ X-ray total scattering experiments provide insight into the formation mechanism of the YSH nanoparticles and initial precipitation of an atomically mixed amorphous phase is followed by crystallization over several minutes. The crystallization rate increases with higher reaction temperature, whereas an increased doping level results in slower crystallization.

Recently, numerous novel phase-space distributions have been proposed by combining the linear canonical transform (LCT) and the Wigner distribution function (WDF), known as the linear canonical Wigner distributions (LCWDs). Among them, the closed-form instantaneous cross-correlation function type of Wigner distribution (CICFWD) has been proven to provide better flexibility for non-stationary signal processing and detection, due to its additional free parameters. Currently, the discrete CICFWD is only defined under a specific LCT parameter constraint and lacks a sampling theorem. This limits its applicability, since in numerical simulations, experiments, and practical optical systems, continuous fields or signals are discretized through digital sampling processes. In this paper, we will develop a general discrete CICFWD formulation without limitations, propose a numerical calculation algorithm, and a corresponding sampling theorem. We will also demonstrate their correctness by comparing the analytical CICFWDs of continuous test signals with their numerically approximated counterparts. Our results will enable more efficient and accurate numerical simulations using CICFWDs, which will be useful in applying them to problems, including optical measurements based on Newton’s rings, numerical optical signal processing, partial coherence, broadband communication and radar systems.

Lung injury risk curves for behind armor blunt trauma using the abbreviated injury scoring system.

We present a classical density functional theory (DFT) study of liquid water in which bridge functions arising from triplet correlations are explicitly incorporated beyond the hypernetted-chain (HNC) approximation. Starting from a third-order density expansion of the Helmholtz free energy functional, we construct a tractable DFT-RISM (reference interaction site model) framework in which three-body direct correlations are included through a physically motivated factorization scheme. Particular attention is paid to the oxygen-oxygen (O-O) radial distribution function, whose second peak at around 4.5 Å is a hallmark of local tetrahedral ordering. We show that this structural feature can be generated within an integral equation framework by introducing an effective bridge function with appropriate inter-particle correlation contributions. Comparison with molecular dynamics data demonstrates that the inclusion of triplet correlations significantly improves the description of the O-O correlations beyond the HNC level, while maintaining reasonable agreement for O-H and H-H correlations. These results provide a physically transparent route to understanding the origin of tetrahedral ordering in liquid water and highlight the essential role of three-body correlations in molecular liquids, particularly in hydrogen-bonded systems.

In the previous articles in this series, it was shown how the use of the Patterson map as a priori information significantly improves the estimation of triplet invariants and makes possible the ab initio solution of macromolecular structures with data resolutions up to 2.2 Å, provided that heavy atoms are present in the unit cell. For the above estimation, the position and intensity of the most representative Patterson peaks were used. No effort towards Patterson deconvolution is necessary. Triplet invariants, however, depend not only on individual Patterson peaks, but also on pairs of interatomic vectors that start or converge on the same atom. Such pairs presuppose the presence of a third interatomic vector, and therefore in this article we legitimately speak of Patterson peak triples. The new mathematical formulation allows their algebra to be described: the informative contribution coming from them has been incorporated into the technique of joint probability distribution functions, and the result is a concentration factor that significantly improves the estimation of triplet invariants. Experimental tests on proteins and nucleic acids show that structural complexity and non-atomic resolution are no longer an unsurpassable obstacle for crystal structure solution.

The biological function of the cell membrane is significantly affected by a disrupted lipid bilayer. Maintaining the structural integrity of the lipid bilayer is hence crucial. In this work, a series of molecular dynamics (MD) simulations were carried out by varying ethanol and glucose concentrations to investigate the counteracting effects of glucose concentration on the ethanol-stressed disorganized hydrated model lipid bilayer, 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC). Our work highlights that the ethanol's concentration-dependent disruptive role affects bilayer integrity, as evidenced by increased lateral diffusion, reduced bilayer thickness, and enhanced disorder in the structural arrangements of the lipids, including the surface curvature order parameter. We observed that the addition of glucose, to some extent, opposes such disorganization. Our investigation reveals that glucose forms substantial hydrogen bonds with lipid headgroups, thereby reducing ethanol-headgroup interaction and promoting tighter lipid packing. The minimum-distance distribution functions suggest that, while water is excluded from the lipid tail, ethanol is found all the way towards the lipid tails, and the terminal methyl groups interact significantly, causing the lipid tails to bend toward the polar regions of the bilayer. This phenomenon however was observed less in the presence of glucose. An inverse relationship between glucose concentration and translational mobility is consistently observed across all ethanol concentrations studied, while higher ethanol content facilitates glucose mobility, regardless of the glucose concentration. This suggests a complex interplay between glucose and ethanol that modulates the diffusive dynamics of the solvent and solute, affecting lipid diffusion and its structural integrity. The computation of the potential of mean force (PMF) using the umbrella sampling technique highlights that the ethanol penetration process is significantly less favored and energetically hindered in the presence of glucose; as a result, lipid diffusion is slowed down. Our findings provide insights into the molecular mechanisms and underscore the protective role of glucose in stabilizing lipid bilayers under alcohol-induced stress. The study is relevant to various pharmaceutical and biomedical applications, as well as the design of biopreservation strategies for cells and tissues.

Micro-structural analysis of aqueous uranyl ions (UO22+) during the course of forward and back extraction in A biphasic system using all atom atomistic simulations.

Diffusion MRI is widely used to characterize tissue microstructure, but standardization remains challenging, particularly for advanced models or regions with crossing fibers. Phantoms provide controlled environments to assess measurement repeatability independent of biological variability. This study evaluated the repeatability of higher-order diffusion tensor metrics using a novel anisotropic diffusion phantom designed to mimic white matter tract geometry. The phantom, containing linear, crossing (30°, 45°, 90°), and bifurcating synthetic fiber bundles, was scanned seven times using a GE Healthcare 3.0 T MRI system. Four acquisition protocols were evaluated: 30-direction DTI (b = 1000s/mm2), 60 and 90-direction High Angular Resolution Diffusion Imaging (HARDI; b = 1300s/mm2), and 30-direction Diffusion Kurtosis Imaging (DKI; b = 250, 500, 750, 1000, 1500, 2000, 2500, 3000 s/mm2). Repeatability was quantified using coefficient of variation (CoV) and intraclass correlation coefficient (ICC) for scalar diffusion metrics across six regions of interest. Fiber orientation distribution functions (fODFs) were analyzed to assess crossing fiber resolution accuracy. DTI-derived metrics demonstrated excellent repeatability, with fractional anisotropy (FA) CoV < 10% and mean, axial, and radial diffusivities < 3%. DKI-derived metrics exhibited greater variability, though kurtosis FA remained stable (CoV ∼7%). Generalized FA showed improved reliability with increased angular resolution (ICC = 0.8445 for 90-direction HARDI). fODFs accurately resolved crossing fibers at 90° (RMSE = 3.49°) and 45° (RMSE = 8.92°) but failed at 30° separation. The phantom provides reliable repeatability for standard DTI metrics and demonstrates utility for quality assurance of advanced diffusion models with high angular resolution protocols.

Insights into the behavior and mechanism of K retention governed by Si-Al network structure during biomass thermal conversion.

BundleParc: Consistent white matter bundle parcellation without tractography.

Colloidal nanocrystals are generally regarded as rigid solid entities, rarely exhibiting the structural adaptability observed in molecular cages, such as fullerenes, which can undergo carbon framework reduction and encapsulate guest cations without structural reorganization. Here, by creating two enantiomeric pairs of high-nuclearity copper sulfide nanoclusters with a mixed-valence Cu(II)/Cu(I) configuration, we endow these nanoscale assemblies with an intrinsic capacity for electron uptake under mild reducing conditions. The resulting charge imbalance provides an effective thermodynamic driving force that realizes a positively charged metal ion migrating inward through multiple atomic layers and occupying the cluster core. This system thus represents a rare example of a nanocluster platform that simultaneously combines reduction tolerance and structural robustness, preserving its atomic framework despite the incorporation of a single atom effectively modifying the electronic structure, particularly the local chirality. In situ absorption and circular dichroism spectroscopies establish that the transformation proceeds through a continuous, single-particle process rather than a fragmentation-reconstruction pathway, while ex situ pair distribution function analysis resolves key local steps in the structural evolution, offering mechanistic insights into this unique migration behavior.

Liquid uranium-zirconium (U,Zr) mixtures play a crucial role in the context of nuclear accident scenarios, particularly in the early stages of pressurized-water reactor accidents. In this study, we compare the thermophysical and structural predictions of two interatomic potentials (IAP) for this system, namely a modified-embedded atom model semi-empirical IAP and a spectral neighbor analysis potential (SNAP). Simulations are performed across a temperature range of 2050-2800 K at zero pressure, spanning the full composition range of liquid (U,Zr) mixtures, using simulation cells of 2000 atoms. The predictions of both potentials are benchmarked against experimental data andab initiomolecular dynamics results available in the literature. These models are employed to investigate the relationship between the viscosity, density, and structural properties of liquid (U,Zr) mixtures, and compare their respective predictions. The modified-embedded atom model (MEAM) potential predicts a significant viscosity anomaly at a molar fraction of 70% Zr, where the viscosity is up to approximately 14 times larger than the SNAP prediction at 2200 K, and 7 times larger at 2500 K. The density at this composition is also overestimated by the MEAM potential by 8% relative to the SNAP prediction. A thorough structural analysis leveraging radial distribution functions and structure factors, Voronoi tessellation, average degree of five-fold local symmetry, and common neighbor analysis supports these findings and attributes them to the formation of an icosahedral short-range order, with perfect icosahedral environments 8 times more prevalent at 70% Zr and 2200 K in the MEAM than in the SNAP. In contrast, this structural ordering is not observed with theab initioand SNAP-based computations. Since viscosity is a direct input to corium pool simulation tools such as PROCOR, an overestimation of this magnitude could significantly affect predictions of melt flow and stratification behavior in accident progression simulations. We finally analyze those differences and suggest that the semi-empirical MEAM potential may overestimate effects of short-range ordering in the liquid phase. These new results can play a role in the refinement of nuclear fuel models, improving the available recommendations for in-vessel corium retention simulations aimed at mitigating severe accident scenarios.

Carbon dioxide (CO2) is a major greenhouse gas responsible for global warming/climate change, whereas methane (CH4) is the primary component of natural gas and serves as a comparatively cleaner energy source than coal and oil. Efficient separation of CO2 from CH4- and N2-containing gas mixtures is therefore critical for both environmental mitigation and energy applications. Herein, we investigate the effect of linker functionalization on CO2 adsorption and separation performance in a metal-organic framework we recently developed, UNT-14, using a combined computational approach. Two functionalized analogues, UNT-14-CN and UNT-14-NO2, incorporating cyano (-CN) and nitro (-NO2) groups, respectively, were constructed and systematically analyzed. Grand Canonical Monte Carlo simulations were employed to predict pure-component adsorption isotherms of CO2, CH4, and N2, while density functional theory (DFT) calculations were used to evaluate CO2 binding energies. Both functionalized frameworks exhibit significantly enhanced CO2 uptake relative to parent UNT-14, concomitant with higher Henry's constants (KH) and isosteric heats of adsorption at infinite dilution (Qst0). DFT results corroborate these trends, revealing stronger CO2···framework interactions in the functionalized materials. Radial distribution function analysis reveals preferential CO2 adsorption near the -CN and -NO2 groups in the functionalized structures, in contrast to adsorption near the Cu clusters in parent UNT-14. Ideal adsorbed solution theory calculations further demonstrate improved CO2/CH4 and CO2/N2 separation selectivities under ambient conditions. This suggests that linker functionalization is an effective strategy for tuning the adsorption behavior of UNT-14 toward enhanced CO2 capture and separation, thereby guiding future synthetic efforts.

This study employs molecular dynamics (MD) simulations to investigate the effects of temperature (600, 650, and 700 K) and annealing time (0-32 ps) on the atomic structure of copper nanorods. The embedded atom method (EAM) potential is used to model interatomic interactions under NPT conditions. Structural evolution is characterized using radial distribution function (RDF), coordination number, common neighbor analysis (CNA), and total energy. Results reveal that increasing temperature induces structural disorder, with a gradual transformation from a highly ordered Face-Centered Cubic (FCC) lattice to a partially amorphous state. Conversely, prolonged annealing promotes atomic rearrangement and recrystallization, stabilizing the structure. At 650 K and ~28 ps, the system achieves optimal stability with the lowest energy and highest FCC fraction. These findings provide atomistic insights into thermal treatment optimization of copper-based materials and contribute to the understanding of thermally induced structural evolution in metallic systems.

Survival for recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) remains low with <20% immunotherapy response. Metformin increases tumor-infiltrating CD8+ T and natural killer (NK) cells, which harbor PD-1. In this Phase 2 clinical trial (NCT04414540), we combined metformin and pembrolizumab to evaluate the overall response rate (ORR) in R/M HNSCC and assess NK cell activity. Eligible patients were randomized 1:1 into two arms: (1) metformin ER dose escalation to 2000 mg over 14 days followed by combination with pembrolizumab 200 mg q3 weeks or (2) pembrolizumab 200 mg q3 weeks followed by combination with metformin ER 2000 mg daily. The primary endpoint was ORR per RECIST 1.1. Nineteen evaluable patients were planned to estimate the proportion of approximately 32% ORR. Safety was evaluated by CTCAE v5.0. The distribution, activation, and cytotoxic function of NK cells was analyzed by flow cytometry. Twenty-one patients were enrolled. 76% were male, 52% smokers, and median age was 64. Ten patients had oropharyngeal tumors, of which 9 were p16 positive. Eighteen patients were evaluable for response, including 4 complete and 5 partial responses for an ORR of 50% (95%CI [29,71]). Combination therapy was well tolerated with no unexpected adverse events (AEs). Five Grade 3 AEs occurred, including nausea, diarrhea, fatigue, and weight loss. Metformin led to increased peripheral NK cell maturation and cytotoxic ability. The combination of metformin and pembrolizumab was well tolerated with mild GI-associated AEs and promising activity warranting further investigation in a randomized trial.

Terahertz (THz) radiation provides an effective means to probe and manipulate collective molecular dynamics in confined water. In this work, nonequilibrium molecular dynamics simulations are employed to investigate the frequency-dependent thermal response and microscopic structure of water confined in armchair-type double-walled carbon nanotubes (DWCNTs). Water encapsulated in (3, 3)@(13, 13), (3, 3)@(18, 18), and (3, 3)@(23, 23) DWCNTs is subjected to linearly polarized THz electric fields applied either parallel or perpendicular to the nanotube axis, and the resulting temperature jump, ΔT, is analyzed over a broad THz frequency range. In comparison with bulk water, confined water exhibits substantially enhanced and highly frequency-selective heating, with a pronounced dependence on field polarization. Under axial polarization, water confined in the narrowest (3, 3)@(13, 13) DWCNT shows a strong resonant response, yielding a maximum temperature increase of ΔT ∼ 370 K, approximately 3.3 times that of bulk water. This enhancement weakens systematically with increasing outer nanotube diameter and higher initial temperature. Analyses of oxygen-oxygen radial distribution functions and transverse density profiles reveal that nanoscale confinement induces pronounced molecular ordering and spatial localization, characterized by ring-like density distributions within the nanotube cross section. These confinement-induced structural features indicate a strong coupling between collective molecular motions and external THz fields, demonstrating that geometric confinement and field polarization jointly regulate resonant energy absorption in nanoscale aqueous systems.