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Devising an efficient exploration of the search space is one of the key challenges in the design of combinatorial optimization algorithms. Here, we introduce the Generator-Enhanced Optimization (GEO) strategy: a framework that leverages any generative model (classical, quantum, or quantum-inspired) to solve optimization problems. We focus on a quantum-inspired version of GEO relying on tensor-network Born machines, and referred to hereafter as TN-GEO. To illustrate our results, we run these benchmarks in the context of the canonical cardinality-constrained portfolio optimization problem by constructing instances from the S&P 500 and several other financial stock indexes, and demonstrate how the generalization capabilities of these quantum-inspired generative models can provide real value in the context of an industrial application. We also comprehensively compare state-of-the-art algorithms and show that TN-GEO is among the best; a remarkable outcome given the solvers used in the comparison have been fine-tuned for decades in this real-world industrial application. Also, a promising step toward a practical advantage with quantum-inspired models and, subsequently, with quantum generative models Solving combinatorial optimization problems using quantum or quantum-inspired machine learning models would benefit from strategies able to work with arbitrary objective functions. Here, the authors use the power of generative models to realise such a black-box solver, and show promising performances on some portfolio optimization examples.

The vibrational NH stretching transitions in secondary amines with intramolecular NH···O hydrogen bonds were investigated by experimental and theoretical methods, considering a large number of compounds and covering a wide range of stretching wavenumbers. The assignment of the NH stretching transitions in the experimental IR spectra was, in several instances, supported by measurement of the corresponding ND wavenumbers and by correlation with the observed NH proton chemical shifts. The observed wavenumbers were correlated with theoretical wavenumbers predicted with B3LYP density functional theory, using the basis sets 6-311++G(d,p) and 6-31G(d) and considering the harmonic as well as the anharmonic VPT2 approximation. Excellent correlations were established between observed wavenumbers and calculated harmonic values. However, the correlations were non-linear, in contrast to the results of previous investigations of the corresponding OH···O systems. The anharmonic VPT2 wavenumbers were found to be linearly related to the corresponding harmonic values. The results provide correlation equations for the prediction of NH stretching bands on the basis of standard B3LYP/6-311++G(d,p) and B3LYP/6-31G(d) harmonic analyses, with standard deviations close to 38 cm−1. This is significant because the full anharmonic VPT2 analysis tends to be impractical for large molecules, requiring orders of magnitude more computing time than the harmonic analysis.

Clean fuel production and pollutant removal are critical industrial challenges. This study presents a model for CO 2 adsorption, focusing on non-metallic, biocompatible catalysts. We demonstrate the potential of chalcogen-doped graphene nanoflake modified with pyridinic nitrogen atoms as biocompatible catalysts for hydrogenating CO 2 to formic acid and methanol. Using dispersion-corrected density functional theory, the catalytic hydrogenation and electrochemical reduction of CO 2 over single chalcogen atoms (Se, Te) embedded in nitrogen-doped graphene nanoflake were analyzed. High hybridization between Se/Te and N states near the Fermi level stabilizes the chalcogen atoms on the graphene nanoflake. Se-doped nitrogen-containing graphene nanoflake exhibits lower energy barriers and higher catalytic performance than Te, facilitating CO 2 conversion to formic acid and methanol with improved stability. Migration barriers, electronic structures, and adsorption energies highlight Se-doped nitrogen-containing graphene nanoflake as an efficient catalyst for CO 2 hydrogenation and electrochemical reduction at room temperature. In particular, Se doping not only stabilizes the material but also improves catalytic performance for the selective production of CO/CH 3 OH. This work introduces Se-doped nitrogen-containing graphene nanoflake as a promising non-metal biocompatible catalyst.

The interaction between the graphene sheet and adsorbing molecules is investigated as a considerable potential in graphene sensors. The decoration of graphene by chalcogen atoms has improved the CO2 and C2H2 storage capacity via density functional theory calculations, which determine the significant and suitable gas sensor. The distinction of capture and separation of C2H2 from CO2 via absorbents is a great challenge due to the high similarity in kinetic diameters and boiling points, and reactive properties. The obtained results reveal that the C2H2 adsorption energy on the Te-decorated graphene sheet is higher than CO2, which could be corresponded to nonmetal tellurium sensitivity on the modified graphene surface. Additionally, the CO2 adsorption energy on the Te-decorated graphene sheet is the highest in comparison with pristine graphene and Se-decorated graphene. The orbital analysis, such as the density of states as well as frontier molecular orbital, has been studied for indicating the kind of interaction (physisorption or chemisorption). The electron density difference and electron localization function and localized orbital locator analyses assign apparent changes in the distribution of electrons about pristine graphene, Se-decorated graphene, and Te-decorated graphene in the presence of gas molecules adsorption. To the best of our knowledge, this is the first time the quantum chemistry methods are used to find the positive effect of nonmetal (Se, Te) atoms for C2H2 capture. Ultimately, Te-decorated graphene has been detected as the best adsorbent in sensing C2H2 gas.

The Sample Environment and Characterization (SEC) group of the European X‐ray Free‐Electron Laser (EuXFEL) develops sample delivery systems for the various scientific instruments, including systems for the injection of liquid samples that enable serial femtosecond X‐ray crystallography (SFX) and single‐particle imaging (SPI) experiments, among others. For rapid prototyping of various device types and materials, sub‐micrometre precision 3D printers are used to address the specific experimental conditions of SFX and SPI by providing a large number of devices with reliable performance. This work presents the current pool of 3D printed liquid sample delivery devices, based on the two‐photon polymerization (2PP) technique. These devices encompass gas dynamic virtual nozzles (GDVNs), mixing‐GDVNs, high‐viscosity extruders (HVEs) and electrospray conical capillary tips (CCTs) with highly reproducible geometric features that are suitable for time‐resolved SFX and SPI experiments at XFEL facilities. Liquid sample injection setups and infrastructure on the Single Particles, Clusters, and Biomolecules and Serial Femtosecond Crystallography (SPB/SFX) instrument are described, this being the instrument which is designated for biological structure determination at the EuXFEL. Presented here are 3D printed sample delivery devices for precise control over fluids and the generation of micrometre‐sized gas‐focused liquid jets, high‐viscosity streams and near‐monodisperse droplets suitable for X‐ray scattering experiments on X‐ray free‐electron laser (XFEL) instruments.

In this study, the electronic transport properties of 11- Cis and Trans retinal, components of rhodopsin, were investigated as optical molecular switches using the nonequilibrium Green’s function (NEGF) formalism combined with first-principles density functional theory (DFT). These isomers, which can be reversibly converted into each other, were examined in detail. The structural and spectroscopic properties, including infrared (IR), Raman, nuclear magnetic resonance (NMR), and ultraviolet (UV) spectra, were analyzed using the hybrid B3LYP/6–311 +  + G** level of theory. Complete vibrational assignments were performed for both forms utilizing the scaled quantum mechanical force field (SQMFF) methodology. To evaluate the conductivity of these molecules, we utilized current–voltage (I-V) characteristics, transmission spectra, molecular projected self-consistent Hamiltonian (MPSH), HOMO–LUMO gap, and second-order interaction energies (E 2 ). The trendline extrapolation of the current–voltage plots confirmed our findings. We investigated the effect of different electrodes (Ag, Au, Pt) and various connection sites (hollow, top, bridge) on conductivity. The Ag electrode with the hollow site exhibited the highest efficiency. Our results indicate that the Cis form has higher conductivity than the Trans form.

Nowadays, one of the most distinguished subjects is the incrementation of CO2 concentration that causes climate change. Based on the density functional theory analysis, structure, electronic, optical, and thermodynamic properties of four organic di-chalcogenide compounds such as C11H12NO3Se–SeC11H12NO3, C9H10NO2Te–TeC9H10NO2, C12H12NTe–TeC12H12N, and C12H12NSe–SeC12H12N, as candidates for carbon dioxide absorption, are investigated scientifically. The effect of different temperatures and various substitutions on the catalytic activity of the di-chalcogenide compounds in the capture and release of CO2 has been investigated. The absorption spectrum of the di-chalcogen compounds has been obtained via the Ultraviolet–Visible optical spectra analysis. By the quantum theory of atoms in molecules and natural bond orbital analysis, the interaction between chalcogenide compounds and CO2 has been evaluated. The positive effect of di-selenides compounds for capturing and releasing CO2 has been represented in our investigation. The catalytic cycle of CO2 capture and release is independent of the thermal effect. In contrast, the various substitutions of di-chalcogenide compounds directly influence the catalytic cycle of CO2 capture and release.

In this study, the electronic transport properties of 2-amino-4,5-bis(2,5-dimethylthiophen-3-yl)furan-3-carbonitrile (as a diarylethene) and its 3 derivatives in R position (R = H, –NH2, and –NO2) have been studied by non-equilibrium green’s function joint with density functional theory. This molecule can be converted from closed form to open form by ultraviolet radiation or visible light. Several parameters, including different molecular geometries, the influence of electrode constituents (Pt, Au, and Ag) and adsorption types (bridge, hollow, and top), I–V characteristics, on–off ratio, HOMO–LUMO gaps, and electronic transmission coefficients T(E), have been investigated. The results showed that as the molecule changes from closed form to open form (closed → open), conductivity changes from on state (high conductivity) to off state (low conductivity).

Background Polymorphisms in the XRCC3 gene, a key component of homologous recombination repair, have been studied for their potential role in thyroid cancer susceptibility. However, published findings remain inconsistent across populations and genetic variants. This meta-analysis aimed to clarify the associations between XRCC3 polymorphisms and thyroid cancer risk, with emphasis on variant- and ethnicity-specific effects. Methods A systematic search of PubMed, EMBASE, Scopus, CNKI, and other databases up to July 10, 2025 identified case–control studies reporting genotype distributions of XRCC3 polymorphisms in thyroid cancer. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were calculated under fixed- or random-effects models. Subgroup analyses by ethnicity, sensitivity tests, and publication bias assessments (Egger’s and Begg’s tests) were performed. Results Twenty-four eligible studies were included: 14 for rs861539, six for rs1799796, and four for rs1799794, comprising 4,502 cases and 6,048 controls. For rs861539, no significant association with thyroid cancer risk was observed in the overall population (T vs. C: OR = 1.089, 95% CI = 0.908–1.306, p  = 0.358), with consistent null results across Asian and Caucasian subgroups. For rs1799796, no overall association was detected (G vs. A: OR = 0.970, 95% CI = 0.875–1.075, p  = 0.558), but a protective effect emerged in Asian populations (GA vs. AA: OR = 0.835, 95% CI = 0.701–0.995, p  = 0.043). For rs1799794, significant associations were found under recessive models (GG vs. AA: OR = 1.371, 95% CI = 1.066–1.762, p  = 0.014; GG vs. GA + AA: OR = 1.316, 95% CI = 1.037–1.669, p  = 0.024). Considerable heterogeneity was observed (I² = 42.2–93.3%), and eight studies deviated from Hardy–Weinberg equilibrium. Conclusions XRCC3 rs1799794 polymorphism is associated with increased thyroid cancer risk, particularly under recessive genetic models. The rs1799796 variant may confer a protective effect in Asian populations, whereas rs861539 shows no significant association. These results highlight population-specific genetic effects and underscore the importance of considering ethnicity in genetic association studies. Further large, well-designed investigations are warranted to confirm these findings and to explore potential gene–environment interactions.

BackgroundIn especially, low and middle-income nations (LMICs), where healthcare access may be restricted, high blood pressure (BP) is a major risk factor for cardiovascular disease and stroke, both of which can even lead to death. Altering one's lifestyle, in conjunction with medical therapy, has been demonstrated to be effective in lowering BP. Recent research has shown that physical activity (PA), in a variety of guises and to varying degrees, can be an effective means of lowering BP.ObjectiveThe purpose of this meta-analysis and systematic review was to evaluate the impact that PA plays in the development of hypertension in LMICs nations.MethodsAn exhaustive search of the available research was carried out in order to locate studies that were pertinent. We searched a number of online databases, such as SCOPUS, Medline, and Web of Science, looking for clinical trials that were published before March of 2023. Studies were only considered for inclusion if they were randomized controlled trials (RCTs), reported on the association between PA and BP, and were carried out in LMICs countries.ResultsThis meta-analysis incorporated a comprehensive collection of 60 studies, encompassing a total of 11,002 people, consisting of 5,630 cases and 5372 controls. The findings indicate that engaging in PA had a notable impact on decreasing systolic blood pressure (SBP), as seen by a weighted mean difference (WMD) of -7.70 mmHg, with a 95% confidence interval (CI) ranging from -9.50 to -5.91 (p < 0.001). Additionally, PA was found to have a significant influence on reducing diastolic blood pressure (DBP), as indicated by a WMD of -3.60 mmHg, with a 95% CI ranging from -4.48to -2.73(p < 0.001). The findings from subgroup analysis indicate that the observed results remained statistically significant when considering individuals with baseline SBP of 120 mmHg or lower and DBP of 80 mmHg or lower.ConclusionThe incorporation of PA can significantly contribute to the mitigation of high BP within LMICs nations. Additional investigation is required to ascertain the most effective form and amount of PA in order to mitigate BP levels within these specific individuals.