4,124 research outputs found

    2-[(4,6-Dimeth­oxy­pyrimidin-2-yl)­oxy]benzaldehyde

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    In the title compound, C13H12N2O4, the dihedral angle between the benzene and pyrimidine rings is 55.57 (13)°. The carbonyl group and the two methoxyl groups are approximately coplanar with the benzene ring and pyrimidine ring; the C—C—C—O, C—O—C—N and C—O—C—C torsion angles being −6.1 (5), −4.8 (4) and 179.9 (3)°, respectively. In the crystal, mol­ecules are linked via C—H⋯O inter­actions, forming chains propagating along [110]

    Fourier neural operator for real-time simulation of 3D dynamic urban microclimate

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    Global urbanization has underscored the significance of urban microclimates for human comfort, health, and building/urban energy efficiency. They profoundly influence building design and urban planning as major environmental impacts. Understanding local microclimates is essential for cities to prepare for climate change and effectively implement resilience measures. However, analyzing urban microclimates requires considering a complex array of outdoor parameters within computational domains at the city scale over a longer period than indoors. As a result, numerical methods like Computational Fluid Dynamics (CFD) become computationally expensive when evaluating the impact of urban microclimates. The rise of deep learning techniques has opened new opportunities for accelerating the modeling of complex non-linear interactions and system dynamics. Recently, the Fourier Neural Operator (FNO) has been shown to be very promising in accelerating solving the Partial Differential Equations (PDEs) and modeling fluid dynamic systems. In this work, we apply the FNO network for real-time three-dimensional (3D) urban wind field simulation. The training and testing data are generated from CFD simulation of the urban area, based on the semi-Lagrangian approach and fractional stepping method to simulate urban microclimate features for modeling large-scale urban problems. Numerical experiments show that the FNO model can accurately reconstruct the instantaneous spatial velocity field. We further evaluate the trained FNO model on unseen data with different wind directions, and the results show that the FNO model can generalize well on different wind directions. More importantly, the FNO approach can make predictions within milliseconds on the graphics processing unit, making real-time simulation of 3D dynamic urban microclimate possible

    Causal relationships between blood metabolites and diabetic retinopathy: a two-sample Mendelian randomization study

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    BackgroundDiabetic retinopathy (DR) is a microvascular complication of diabetes, severely affecting patients’ vision and even leading to blindness. The development of DR is influenced by metabolic disturbance and genetic factors, including gene polymorphisms. The research aimed to uncover the causal relationships between blood metabolites and DR.MethodsThe two-sample mendelian randomization (MR) analysis was employed to estimate the causality of blood metabolites on DR. The genetic variables for exposure were obtained from the genome-wide association study (GWAS) dataset of 486 blood metabolites, while the genetic predictors for outcomes including all-stage DR (All DR), non-proliferative DR (NPDR) and proliferative DR (PDR) were derived from the FinnGen database. The primary analysis employed inverse variance weighted (IVW) method, and supplementary analyses were performed using MR-Egger, weighted median (WM), simple mode and weighted mode methods. Additionally, MR-Egger intercept test, Cochran’s Q test, and leave-one-out analysis were also conducted to guarantee the accuracy and robustness of the results. Subsequently, we replicated the MR analysis using three additional datasets from the FinnGen database and conducted a meta-analysis to determine blood metabolites associated with DR. Finally, reverse MR analysis and metabolic pathway analysis were performed.ResultsThe study identified 13 blood metabolites associated with All DR, 9 blood metabolites associated with NPDR and 12 blood metabolites associated with PDR. In summary, a total of 21 blood metabolites were identified as having potential causal relationships with DR. Additionally, we identified 4 metabolic pathways that are related to DR.ConclusionThe research revealed a number of blood metabolites and metabolic pathways that are causally associated with DR, which holds significant importance for screening and prevention of DR. However, it is noteworthy that these causal relationships should be validated in larger cohorts and experiments

    1-(2-Nitro­phen­yl)-3-phenyl­thio­urea

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    The title compound, C13H11N3O2S, was prepared by reaction of 2-nitro­benzenamine, KOH and 1-isothio­cyanato­benzene in an ethanol solution at room temperature. The dihedral angles formed between the thiourea plane and the phenyl rings are 61.9 and 31.0°. The dihedral angle between the two phenyl rings is 78.1°. In the crystal structure, there are weak inter­molecular N—H⋯S and C—H⋯S hydrogen-bonding inter­actions

    Measuring the anomalous quartic gauge couplings in the W+WW+WW^+W^-\to W^+W^- process at muon collider using artificial neural networks

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    The muon collider provides a unique opportunity to study the vector boson scattering processes and dimension-8 operators contributing to anomalous quartic gauge couplings. Because of the cleaner final state, it is easier to decode subprocess and certain operator couplings at a muon collider. We attempt to identify the anomalous WWWWWWWW coupling in WWWWWW\to WW scattering in this paper. The vector boson scattering process corresponding to the anomalous WWWWWWWW coupling is μ+μνννˉνˉ+\mu^+\mu^-\to \nu\nu\bar{\nu}\bar{\nu}\ell^+\ell^-, with four (anti-)neutrinos in the final state, which pose difficulties for phenomenological studies. In this paper, the machine learning method is used to tackle this problem. We find that, the artificial neural network can be used to extract the W+WW+WW^+W^-\to W^+W^- contribution, and is useful to reconstruct the center of mass energy of the subprocess which is important in the study of the Standard Model effective field theory. The sensitivities and the expected constraints on the dimension-8 operators at the muon collider with s=30\sqrt{s}=30 TeV are presented. The artificial neural networks exhibit great potential in the phenomenological study of processes with multiple neutrinos in the final state.Comment: 26 pages, 11 figures, 7 table

    Comparative Transcriptomics of Strawberries (Fragaria spp.) Provides Insights into Evolutionary Patterns

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    Multiple closely related species with genomic sequences provide an ideal system for studies on comparative and evolutionary genomics, as well as the mechanism of speciation. The whole genome sequences of six strawberry species (Fragaria spp.) have been released, which provide one of the richest genomic resources of any plant genus. In this study, we first generated seven transcriptome sequences of Fragaria species de novo, with a total of 48,557–82,537 unigenes per species. Combined with 13 other species genomes in Rosales, we reconstructed a phylogenetic tree at the genomic level. The phylogenic tree shows that Fragaria closed grouped with Rubus and the Fragaria clade is divided into three subclades. East Asian species appeared in every subclade, suggesting that the genus originated in this area at ∼7.99 Mya. Four species found in mountains of Southwest China originated at ∼3.98 Mya, suggesting that rapid speciation occurred to adapt to changing environments following the uplift of the Qinghai–Tibet Plateau. Moreover, we identified 510 very significantly positively selected genes in the cultivated species F. × ananassa genome. This set of genes was enriched in functions related to specific agronomic traits, such as carbon metabolism and plant hormone signal transduction processes, which are directly related to fruit quality and flavor. These findings illustrate comprehensive evolutionary patterns in Fragaria and the genetic basis of fruit domestication of cultivated strawberry at the genomic/transcriptomic level

    Acute and subacute toxicity study of Aucklandia lappa Decne seed oil

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    Purpose: To investigate the acute and subacute toxicity of Aucklandia lappa Decne. seed oil (ALDO) in mice and rats.Methods: A single dose of 10 g ALDO/kg was administered to Kunming mice in an acute oral toxicity experiment. Their weight and feed consumption were recorded for 14 days to observe whether they had symptoms of poisoning and mortality. Sprague-Dawley (SD) rats were administered 0.89, 1.77 and 3.54 g/kg for 28 days, and symptoms of poisoning and mortality were monitored daily. Body weight, feedconsumption, hematology, serum biochemical parameters, relative organ weight, and histopathology of the experimental and control groups were compared.Results: The acute oral toxicity study revealed that there was no significant difference in the macroscopic results, including mortality, feed consumption and weight growth between the group dosed with 10 g ALDO/kg (p > 0.05) and the control group. In the subacute toxicity test, SD rats had a higher weight growth rate and feed utilization after doses of 0.89 g ALDO/kg (p < 0.01). However, compared with the control group (p > 0.05), there was also no significant difference in biochemical and hematological parameters, relative organ weight, or in macroscopic and histological features of both animal types. The electrolyte concentrations of Na and Cl increased at the doses of 1.77 and 3.54 g/kg (p < 0.01).Conclusion: These results suggest that ALDO is relatively safe when administered orally to rats and provide a theoretical basis for the development of new food resources
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