Search Results (7,129)

Sparganium stoloniferum tubers (SL), known medicinally as Sparganii Rhizoma, are commonly considered superior at the winter-harvest stage, when they show the traditional quality traits of heavy weight and firm texture. However, the developmental basis of this quality phenotype remains insufficiently understood. This study aimed to determine how tissue organization, cell-wall architecture, starch deposition, and related transcriptional patterns are associated with winter-harvest quality in SL. By comparing SL at different developmental stages, we found that maturation was accompanied by reduced moisture content, increased tuber density, higher parenchyma cell density, progressive cell-wall thickening, and marked starch accumulation. Laser scanning confocal microscopy (LSCM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) observations further revealed thickened multilamellar cell walls and abundant clustered or compound-like starch bodies in mature SL. Starch isolated from mature SL displayed an A-type crystalline pattern, short-range order, and high gelatinization and pasting temperatures, indicating an ordered and thermally stable starch matrix. Cell-wall Fourier-transform infrared spectroscopy (FTIR) and solid-state nuclear magnetic resonance (NMR) analyses showed a predominantly polysaccharide-rich framework with subtle maturation-associated changes in aromatic- and methoxy-associated wall signals. Transcript-guided pathway analysis, supported by reverse transcription quantitative polymerase chain reaction (RT–qPCR)validation, suggested developmental shifts in carbohydrate metabolism, lipid-related metabolism, and gibberellin-associated transcriptional patterns. Together, these findings indicate that winter-harvest quality in SL is associated with coordinated tissue consolidation, cell-wall maturation, starch deposition, and transcriptional reprogramming, providing a structural and molecular framework for understanding the traditional firm-texture trait of S. stoloniferum. Full article

CeO₂ is widely used as a non-radioactive surrogate for UO₂ because of its fluorite crystal structure and similar thermophysical characteristics. In this study, an FIB-assisted specimen preparation route combined with high-temperature nanoindentation was used to evaluate the micromechanical behavior of CeO₂ from room temperature to 400 °C. Hardness and Young’s modulus were experimentally measured at room temperature, 100 °C, 200 °C, 300 °C, and 400 °C. The load–displacement curves were smooth, and no obvious pop-in events were observed within the tested load range. From 100 °C to 400 °C, both Young’s modulus and hardness decreased approximately linearly with increasing temperature, and linear fitting was used to describe their temperature dependence. The measured Young’s modulus decreased from 191.3 ± 14.0 GPa at 100 °C to 136.7 ± 9.5 GPa at 400 °C, while the hardness decreased from 6.79 ± 0.58 GPa to 5.08 ± 0.48 GPa. The obtained temperature-dependent trend is consistent with previously reported high-temperature nanoindentation data for fluorite-structured oxides. These results provide useful micromechanical data and methodological support for elevated-temperature small-scale mechanical characterization of ceramic nuclear fuel surrogate materials. Full article

Tensor completion is commonly formulated by minimizing a convex combination of nuclear norms of mode-wise unfolding matrices. Although effective, the non-negative weight constraint can limit the flexibility of mode balancing, especially when different modes contribute unequally to the reconstruction. In this paper, we propose a tensor completion model based on a linear combination of nuclear norms, where the weights are allowed to take signed values under a normalization constraint. To implement this model, we develop an ADMM-based algorithm, termed FlexHaLRTC, which extends the standard singular value thresholding update to handle both shrinkage for positive weights and expansion for negative weights. Experiments on color image inpainting and video completion show that the proposed method achieves competitive PSNR, SSIM, and RSE results, with more noticeable gains in high-missing-rate settings. Full article

A design for a small chloride salt fast reactor (sm-MCFR) is presented through the integration of molten salt reactor and small reactor technologies, targeting efficient transmutation of transuranic (TRU) elements in spent nuclear fuel and rapid reactor deployment. The feasibility exploration and research on the design boundaries of sm-MCFR will be conducted in this article. The core adopts a dual-fluid configuration, in which the fuel salt and coolant circulate independently. Chloride salt is selected as the fuel carrier due to its high solubility for heavy metal nuclides and the low neutron absorption cross-section of chlorine, which help to form a hard fast-neutron spectrum and thereby enhance transmutation efficiency. The cooling system employs a direct supercritical carbon dioxide (s-CO₂) cycle, simplifying the overall layout. For the neutronics design, simulations were carried out using the TMCBurnup (TRITON MODEC Coupled Burnup Code). By adjusting the core geometry, fuel salt composition, and reprocessing strategy, the sm-MCFR achieves a hard fast-neutron spectrum but also demonstrates good potential for fuel utilization. In terms of thermal–hydraulic design, the heat exchange effect of the reactor core can be improved by adjusting the proportion of the coolant and the flow direction. The sm-MCFR is expected to become a promising candidate for advanced small reactors that have potential applications in nuclear waste transmutation and distributed energy generation. Full article

During the life of a nuclear reactor, there are changes to the in-core components that are a function of operating environment and time. It is important to know how the properties of critical core components change, which can be assessed through materials surveillance programs. It is also desirable to characterize materials behaviour long before the end of the reactor design life. Therefore, experiments to characterize materials for in-core applications are performed in test reactors that typically have higher total neutron fluxes than power reactors. The extensive in-core materials irradiation programs that supported the validation of long-term material behaviour in CANDU (CANada Deuterium Uranium) reactors used various irradiation facilities, both domestic and international, are summarized in this paper. However, these test reactor facilities are aging and in some cases are closing, including NRU, which ceased operations in 2018. As Canada contemplates a new domestic high-flux test reactor to support both existing and potential new power reactors, this paper provides a review of the facilities and approaches that were implemented to successfully research CANDU reactor materials and can serve as a basis to define future facility requirements. Full article

To address the scientific challenges associated with complex microscopic pore structures and the unclear mechanisms of miscible gas injection in typical low-permeability carbonate reservoirs in the Middle East, online nuclear magnetic resonance (NMR) imaging experiments were conducted during water-alternating-CO₂ miscible flooding. The microscopic oil mobilization mechanisms were quantitatively investigated for different pore structure types and at various displacement stages. The results indicate that water-alternating-CO₂ miscible flooding achieves a relatively high degree of oil mobilization in large and medium pore–throat structures. This behavior is likely associated with Jamin-type flow resistance effects and flow regulation induced by gas–water alternating slugs. Differences in microscopic oil mobilization are mainly observed in mesopores (0.3–1.5 μm). The recovery degrees of mesopores in Cores 1, 2, and 3 reach 89%, 94.2%, and 78%, respectively, contributing 93.7%, 80.6%, and 50.9% to the total oil recovery. The degree of microscopic heterogeneity controls the distribution of remaining oil in core slices after breakthrough of the displacement front. In Core 1, the signal amplitude exhibits a gradual and uniform decline, indicating that gas–water alternating injection suppresses gas channeling and improves mobility control. In Core 2, the signal amplitude decreases more rapidly with increasing heterogeneity. In Core 3, the signal disparity continues to intensify, leading to the formation of dominant gas–water channeling pathways, while low-permeability pore–throat structures evolve into typical bypassed oil zones. As the CO₂–oil contact front progressively advances toward the outlet end, the swept volume gradually decreases due to the development of preferential flow channels. Consequently, significant remaining oil accumulation occurs near the outlet region. Full article

Interpretation of pharmacometabolomics results, aiming particularly at biomarker (sets) discovery for drug exposure, remains a major challenge. The metabotyping of drug exposure depends on resolution of specific metabolomics techniques and comprises individual metabolic phenotypes (“metabotypes”), disease-, drug- and microbiome-specific patterns, as well as conditional metabolic states (e. g. fasting). In this clinical trial with 16 healthy participants, an exploratory objective was to evaluate the untargeted urinary metabolomics of voriconazole, administered in four single doses, using proton nuclear magnetic resonance (¹H-NMR) spectroscopy. Voriconazole is a second-generation triazole and a potent inhibitor of drug-metabolizing enzymes such as cytochrome P450 (CYP) isozymes CYP3A4 and CYP2C19. Therefore, identification of metabolites reflecting acute CYP3A4 inhibition was of particular interest. On two treatment days without and with voriconazole (with background microdosed midazolam and omeprazole administration for CYP3A4 and CYP2C19 phenotyping, respectively), spot urine was collected after overnight fasting (predose) and 4 h later (postdose fasting). In the postdose versus predose fingerprints, most changes at the annotated metabolite level were attributable to fasting metabolomics or potential confounders. ¹H-NMR spectroscopy identified neither a short-term voriconazole-specific signature nor patterns or metabolites potentially reflecting acute CYP3A4 inhibition. Our study emphasizes crucial significance of strict standardization of fasting time and minimization of confounder influences by clinical trial design as well as selection of adequate baselines and high-resolution analytical techniques in pharmacometabolomics research, especially for biomarker discovery. Full article

Severe transients in nuclear power plants (NPPs) are strongly coupled and highly nonstationary, which makes reliable short-horizon multivariate forecasting difficult for conventional sequence models. To address this challenge, this study develops a hybrid LSTM-Transformer forecasting framework for severe nuclear accident time series and uses the Sparrow Search Algorithm (SSA) as a task-oriented joint hyperparameter optimization tool for nuclear accident forecasting. In this framework, the self-attention mechanism captures long-range temporal dependencies and cross-variable interactions, while the LSTM component strengthens the modeling of short-term dynamics and local temporal memory. SSA is employed as a task-oriented joint hyperparameter optimization tool to adapt key model settings, including the number of attention heads, encoder depth, model dimension, LSTM hidden units, and dropout rate, for severe nuclear accident forecasting. In addition, a regularized training strategy combining dropout and validation-based early stopping is adopted to alleviate overfitting and improve training stability. The main comparison results are reported as mean ± standard deviation over 20 independent runs with the same data split and different random seeds. Experiments on high-fidelity PCTran/APR1400 simulations covering LOCA, LACP, and SLBIC scenarios, together with a severity-shifted LOCA test, demonstrate strong and statistically stable predictive performance. Across the three representative accident scenarios, the proposed framework achieves mean R² values of 0.943 ± 0.009, 0.951 ± 0.007, and 0.946 ± 0.010, while maintaining about 30% lower mean nRMSE and nMAE than the strongest LSTM-Transformer baseline. A 2 × 2 ablation study shows that regularization mainly improves training efficiency, reducing the required epochs by a range of about 36–41%, whereas SSA primarily improves predictive accuracy through better hyperparameter selection. Their combination provides the best overall generalization. Cross-severity LOCA evaluation further confirms the robustness of the proposed model, yielding mean R² = 0.885 ± 0.017 and mean nRMSE = 0.100 ± 0.010. The model also achieves low inference latency (P50 = 7.6 ms per sample), indicating its computational potential for near-real-time multivariate forecasting in safety-critical transient monitoring. Full article

The electronic properties of high-temperature superconducting cuprates are encoded in NMR data. Without microscopic theory, reliable NMR phenomenologies are in demand. Here we make use of the extensive literature data to develop a different understanding of the cuprates from the shifts of the CuO${}_2$ plane. The Cu shift analysis is based only on the symmetry of the two Cu hyperfine couplings, without assumptions about their size. We use an anisotropic $A_{\alpha }$ and isotropic B, as from atomic Cu orbitals, and find two spin components (A- and B-spins) that explain all the shift data. The components differ in size and temperature dependence according to simple rules. Upon doping the cuprates, metallic B-spin appears above a pseudogap temperature, which is shared with the A-spin. Further doping decreases the pseudogap temperature and increases the B-spin, but less so the A-spin. The apparent linear rate of increase in the density of states of the B-spin with doping is nearly threefold above $x=0.20$, where the pseudogap disappears. The pseudogap temperature is a measure of the coupling between A and B, which suppresses the shifts but not nuclear relaxation. Spin-singlet pairing involves A and B according to three simple condensation rates, which will be discussed. The optimal $T_{\mathrm{c}}$ demands a special match between A and B. However, the shifts do not simply predict the highest $T_{\mathrm{c}}$ of all cuprates, in contrast to nuclear relaxation anisotropy and charge sharing between planar Cu and O. Relations to other probes are discussed. Full article

Contrastive learning-based models such as DrugCLIP have recently emerged as scalable tools for structure-based virtual screening by embedding protein structures and small molecules into a shared representation space. While these approaches demonstrate high throughput and competitive screening performance in ligand retrieval tasks, their ability to correctly identify biologically relevant ligand-binding pockets has not been systematically evaluated. Here, we construct a benchmarking dataset comprising 42 pharmacologically diverse human protein targets with experimentally validated drug-bound structures spanning multiple target families. Using this dataset, we evaluate the pocket recognition capability of DrugCLIP and compare its performance with a traditional structure-based workflow (Fpocket combined with ESSA) and a machine learning-based method (P2Rank). DrugCLIP shows robust performance for well-characterized target classes, including kinases (10/10) and nuclear receptors (5/5), but exhibits markedly reduced accuracy for ion channels (1/4), GPCRs (3/5), and transporters (3/5). Notably, pocket prediction accuracy does not strongly correlate with structural data availability, suggesting that intrinsic pocket characteristics rather than training data abundance primarily affect model performance. Across the benchmark, DrugCLIP achieves an overall success rate of 71% (95% CI: 56–83%), compared with 79% (95% CI: 64–88%) for Fpocket+ESSA, and 93% (95% CI: 81–98%) for P2Rank. McNemar’s test showed no significant difference between DrugCLIP and Fpocket+ESSA (p = 0.508), whereas P2Rank significantly outperformed DrugCLIP (p = 0.012). Together, these results provide a quantitative evaluation of pocket recognition by contrastive learning-based models and highlight key limitations of embedding-based approaches for pocket localization. Full article

When the global energy transition is analyzed through economic lenses, the constraints imposed by the laws of thermodynamics are often overlooked. This study addresses the Latecomer’s Dilemma—the predicament of semi-peripheral nations compelled to decarbonize without the capital stock accumulated following the example of the countries of the Global North during their more than two hundred years of industrial development associated with the saturation of the atmosphere with carbon dioxide. A novel phase space model of the Anthropocene is constructed, synthesizing the political concept of ecological debt with the biophysical reality of entropy debt. The application of the laws of systems ecology and non-equilibrium thermodynamics enables the mapping of national development trajectories against the saturated “atmospheric bathtub”. The analysis identifies a critical Injustice Gap—a region of phase space physically foreclosed by historical emissions. Moreover, it has been demonstrated that a circular economy powered by low-density renewables functions as an entropy trap, converting material debt into radiative debt without achieving a closed loop. Consequently, the Polish correction vector is proposed as a stabilization mechanism. This study’s findings indicate that addressing the emerging phenomenon of adaptation apartheid necessitates the implementation of a high-density energy flux, namely Generation IV nuclear reactors, which would be funded by a retroactive ETS3 mechanism. This approach fulfills the thermodynamic condition for material closure, thereby substantiating the notion that energy justice constitutes a physical necessity for planetary stability. This study quantifies the historical radiative debt of a single early-industrialized hub (Manchester) at approximately 142.8 billion EUR. The novelty lies in the synthesis of biophysical laws and the Latecomer’s Dilemma through the proposed ETS3 mechanism. Full article

Nuclear energy offers a zero-carbon solution to emission challenges, yet nuclear power plant design is constrained by spatial limitations and complex nonlinear parameter interactions. This study develops a hybrid genetic multi-objective optimization framework, NHGA-NSGA-II, by integrating refined NHGA strategies with the NSGA-II technique. Applied to a reactor primary loop system, the framework reveals a fundamental trade-off between system miniaturization (mass/volume) and passive safety (natural circulation and MDNBR). Pareto analysis indicates that Optimization Plan 3 corresponds to the most favorable representative trade-off identified under the present modeling assumptions, optimization settings, and constraint framework, achieving a 20% gain in natural circulation capacity and a 5.9% safety improvement with only a 9.2% cost increase, thereby illustrating a balanced relationship among passive safety, compactness, and economic efficiency within the current scope of the study. The proposed framework offers an effective tool for high-dimensional nonlinear optimization in nuclear engineering. Full article

Aiming to investigate the unclear lower limit of microscopic pore mobilization during CO₂ pre-fracturing in the shale oil reservoirs of the Ma51X well block, this study integrates high-temperature and high-pressure (110 °C 70 MPa) CO₂ huff-n-puff with nuclear magnetic resonance (NMR) experiments. The results demonstrate the following: (1) under high-temperature (110 °C) and ultra-high-pressure (70 MPa) conditions, the lower limit of mobilizable pores for CO₂ to displace reservoir crude oil reaches 1.7~2.2 nm; (2) the dominant mobilized pore range for CO₂ is 5.1~38.5 nm, and macropore abundance directly dictates the macroscopic sweep coverage of CO₂; (3) the modification effect of CO₂ on pore structure is primarily concentrated within the mesopore-to-macropore systems, and with an increase in huff-n-puff cycles, crude oil in mesopores progressively migrates toward macropores; and (4) multi-cycle CO₂ huff-n-puff exhibits a cyclic performance pattern characterized by dominance in the initial cycle and subsequent attenuation. This study precisely delineates the lower limit of mobilizable pores for crude oil in the shale oil reservoirs of the Ma51X well block, providing a robust theoretical foundation for the efficient development of this formation and analogous ultra-low permeability reservoirs. Full article

Driven by global climate change and carbon reduction targets, nuclear energy has gained increasing prominence as a clean baseload power source. Enhancing the energy efficiency of key equipment in nuclear power plants is essential for achieving a low-carbon transition. This study addresses the trade-off between separation efficiency and pressure drop under multi-parameter coupling in hooked corrugated plate separators by proposing a multi-objective optimization strategy that integrates automated numerical simulation with data-driven optimization. An automated CFD framework was developed to efficiently generate a comprehensive dataset covering inlet velocity, droplet diameter, plate spacing, and hook length. A multilayer perceptron (MLP) surrogate model was then constructed, achieving high predictive accuracy with coefficients of determination (R²) of 0.95 for separation efficiency and 0.91 for pressure drop. Using the trained surrogate model, the NSGA-II algorithm was employed for multi-objective optimization, and the TOPSIS method was applied to identify the optimal compromise solutions. The results show that for representative droplet diameters of 5, 10, and 15 μm, the optimized structures improve separation efficiency by 25.71–29.14%. The integrated automated CFD–surrogate model–multi-objective optimization framework established in this study provides an efficient and generalizable approach for the design of gas–liquid separation equipment, contributing to energy consumption reduction in nuclear and process industries and supporting the realization of global carbon neutrality goals. Full article

Background/Objectives: Achillea millefolium is a well-known plant used in traditional medicine for the treatment of inflammation, gastrointestinal disorders, respiratory diseases, hypertension, and diabetes, among others. These effects are attributed to the metabolite content of flavonoids and terpenes such as achillin (1) and leucodin (2). Thus, the current investigation aims to standardize the extracts from A. millefollium based on the presence of 1 and 2 and relate them to their relaxant effect in ex vivo assays. Methods: A validated High-Performance Liquid Chromatography (HPLC) method was used to determine the concentration of the main compounds, employing standard molecules previously isolated from the same species and characterized by nuclear magnetic resonance (NMR) and X-ray diffraction. Also, the relaxant effects of both compounds and their combinations were assayed on aortic and tracheal rat rings in an organ bath. Results: Compounds (1) and (2) are the main compounds in hexane, dichloromethane, and hydroalcoholic extracts, present in different proportions. The relaxant effects in ex vivo models of the aorta and trachea showed that the sesquiterpene lactones achillin (1) [Trachea, maximum effect (Emax): 67.67 ± 5.01%, medium effective concentration (EC50): 304.44 ± 2.61 µM; Aorta: Emax: 63.94 ± 6.28%, EC50: 225.73 ± 4.49 µM)] and leucodin (2) (Trachea: Emax: 76.71 ± 4.73%, EC50: 266.40 ± 2.05 µM; Aorta, Emax: 72.96 ± 1.73%, EC50: 163.29 ± 2.99 µM) are responsible for the relaxant effects shown by the extracts. The observed effect is proportional to the concentration of these molecules, with hexane extracts being more active. Additionally, we demonstrate the safety of molecules 1 and 2 through toxicological studies recommended by the OECD. Conclusions: The isolated compounds achillin and leucodin are the primary constituents in the flowers of A. millefolium, with higher concentrations found in hexane extracts, particularly of achillin, which shows a correlation of 2.33 with respect to leucodin. This correlation is closely related to their relaxant effect, as these compounds are the main contributors to the relaxant response in the trachea and aorta, being more effective when used together. Full article