Decision support framework for screening deficient bridges based on statistically-identified key indicators and Monte Carlo simulation

Remediation of ternary heavy metal-polyethylene microplastics co-contaminated soil using co-modified biochar with deep eutectic solvent and warm patch: competitive interactions, mechanistic insights, and microbial community response.

Strategic method development for praziquantel impurity analysis using analytical QbD framework.

A statistical representation of oil spill fate in the Salish Sea (Part 1).

FTIR-based profiling of sinusitis: Stabilized feature selection through Boruta and Monte Carlo methods.

Where rivers meet the sea: Source fingerprinting and health risk mapping of potentially hazardous elements in sediments from the Çanakkale Strait basin (Türkiye).

Intra- and interparticle coating homogeneity and minimum coating amount of hot melt coating products identified by Monte Carlo-Model

Despite its many applications, three-dimensional radical polymerization remains poorly understood. A major challenge is the considerable kinetic slowdown caused by gelation-a liquid-to-solid phase transition that produces a network permeating the entire volume. This rapidly developing structure greatly obscures direct experimental observations of kinetic mechanisms during network formation. Although molecular dynamics (MD) simulations can qualitatively reproduce the gelation process, they are restricted to unrealistically short time scales. To address this limitation, particularly with respect to cycle formation, we propose coarse-grained modeling techniques based on random graphs (RG) and Monte Carlo (MC) simulations, and apply them to the polymerization of (multi)functional acrylates: N-butyl acrylate (NBA), 1,6-hexanediol diacrylate (HDDA), and trimethylolpropane triacrylate (TMPTA). This approach emphasizes the network of monomer units in the polymer rather than representing individual molecules in atomistic detail. In our models, cycles are represented as special types of vertices, depending on their size. The model demonstrates the impact of cycles, such as a delay in the gel point, which varies with cycle size. The number and size of cycles predicted by the coarse-grained models agree well with MD simulations, but they still fail to capture certain structural features, such as overlapping cycles. Typically, in the gel regime, RG and MC models predict structures with many connected cycles essentially in a tree-like pattern.

HetMS-MC: A framework for heterogeneous multiscale Monte Carlo modelling in radiation medicine.

Exploring the effects of impact damage on optical properties of ‘Korla’ pears and Monte Carlo simulation of light propagation in pear tissue

Experimental study of energy-dependent angular broadening of MeV electron beams for high-resolution imaging in thick samples.

Probabilistic exposure assessment and risk characterization of quinolizidine alkaloids and phomopsin A in the Belgian population.

Artificial Intelligence for Simplified Patient-centered Dosimetry in Radiopharmaceutical Therapies.

Impact of physiological transitions during forward processing on Shiga-toxin producing Escherichia coli risks in lettuce.

Definition of a chemical specific adjustment factor for human interindividual differences in kinetics for glutamates (E620-625) following oral intake in the absence and presence of food.

Monte Carlo simulation benefits to healthcare product manufacturers in radiation processing

This study presents the synthesis and characterization of 2,5-bis(2-methyl-1H-benzimidazol-5-yl)-1,3,4-oxadiazole, using 1H NMR, 13C NMR, mass spectrometry and FTIR-ATR infrared spectroscopy. Quantum chemical analysis revealed that P1 possesses a balanced electrophilic–nucleophilic profile, enabling interactions with diverse biological targets. Its HOMO–LUMO gap and electronic stability suggest potential applications in photonic devices. ADMET predictions indicated favorable pharmacokinetics and overall drug-likeness. Molecular docking demonstrated high binding affinities toward anticancer, antibacterial, and antifungal proteins, with P1 reproducing reference ligand binding modes while forming additional stabilizing contacts. Molecular Dynamics simulations captured the thermal motion and conformational flexibility of P1 on the Fe(110) surface, while Monte Carlo simulations identified energy-minimized, compact adsorption conformations. Both approaches confirmed thermodynamically favorable chemisorption, stabilized by direct surface interactions and solvent/ionic contributions. Together, these findings highlight P1 as a dual-purpose scaffold, combining selective biological activity, favorable electronic properties, and strong surface interactions. This integrated computational study supports its potential for both therapeutic development and optoelectronic application.

Identification of priority sources of potentially hazardous elements from public drinking water fountains in Zaječar/East Serbia.

Evaluation of mean composition values, trends and correlations of a 4000km2 north Atlantic area considering data uncertainty: Nutrients, salinity and temperature.

Monte Carlo simulation of the impact on free radical yields under ultra-high dose rate irradiation