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Urea is an essential fertilizer needed to meet the global demand for food. Currently, its production rate by reaction of carbon dioxide with ammonia is slow and the energy demand is high. Here we discuss strategies to overcome these challenges. Urea, a crucial nitrogen fertilizer, plays a vital role in meeting global food demand. However, its current production method is energy-intensive and environmentally unfriendly. In this commentary article, the authors propose strategies to address and overcome these challenges.

Ceratopsian dinosaurs underwent great changes, including a shift of locomotion mode, enlarged horns and frills, and increased body size. These changes occur alongside the evolution of endocranial morphology and physiology such as the size and shape of the flocculus, hearing range, olfactory ratio, and the reptile encephalization quotient (REQ). However, the evolution of endocranial structures in early ceratopsians is still unclear because of a lack of information on the earliest ceratopsians. Here, we reconstructed the endocasts of three early-diverging ceratopsians including the Late Jurassic Yinlong, and the Early Cretaceous Liaoceratops and Psittacosaurus. These ceratopsians display obvious flocculi, large and separate olfactory bulbs, long and high anterior semicircular canals, and relatively long cochlear ducts. In the evolution of the earliest ceratopsians to early neoceratopsians, changes include the increasing size of the flocculus (which is reduced or absent in late-diverging ceratopsids), the attenuation of the semicircular canals, and the heightening of the anterior semicircular canal (which is shortened in late-diverging ceratopsids). The endocranial structures suggest early-diverging ceratopsians had a higher olfactory acuity and were adapted to hearing higher frequencies than late-diverging ceratopsians. Furthermore, the REQ suggests that Yinlong and Psittacosaurus were more highly encephalized than late-diverging ceratopsians and most extant reptiles. The angle of the lateral semicircular canal suggests that heads in ceratopsians display a transition from a forward posture to a more downward posture. Our new findings are significant for understanding the physiological changes during ceratopsian evolution and also have implications for the evolution of physiology in extant tetrapods.

Carbon stars play a crucial role in astronomical research and are significant for understanding stellar evolution, measuring cosmic distances, and studying galaxy kinematics. In recent years, identifying carbon stars using machine learning methods and traditional line-index methods has become a research hotspot, but there are still limitations regarding accuracy and automation. In this study, we propose to build a five-class model to identify carbon stars using spectral data from LAMOST DR9. The model achieved 99.45% precision and 91.21% recall on the carbon star testing set. We conducted independent tests using a sample of 1333 known carbon stars that were not used in the training and testing phases, and our model ultimately identified 1199 carbon stars. On this basis, we used this model to screen 11,226,252 spectra of LAMOST DR9 and identified 4383 carbon stars, including 1197 newly discovered carbon stars. To gain a more comprehensive understanding of the characteristics of the 4383 carbon stars obtained, further visual inspection of these spectra was performed to provide more detailed carbon star subtypes.

Background and purpose Pipeline embolization device (PED) is widely used in intracranial aneurysms, and the scope of applications for the PED, which is frequently used to treat cerebral aneurysms, is also growing. It has some effect on branching vessels as a result of its inherent properties. The effects of PED on the complications rate and branching vessels blockage have not yet been thoroughly investigated. Objective We conducted a systematic review searching reports from multiple databases on PED use for intracranial aneurysms, and analyzed the influence of PED on the occlusion rate of different branching vessels, and the influence of the amount of PED on the occlusion rate of branching vessels by meta-analysis. Methods We searched the literature using PUBMED, Web of Science, and OVID databases until August 2023. Inclusion criteria were that the study used only PED, included at least 10 patients, and recorded branching vessels occlusion rates, mortality, and neurological complications. Results Nine studies were analyzed consisting of 706 patients with 986 side branches. The results of the meta-analysis showed that application of more than one PED did not significantly elevate the rate of branching vessels occlusion compared to application of one PED (OR = 0.70; 95% CI: 0.34 to 1.43; P  = 0.33). In the comparison of branching vessels occlusion rates in the anterior circulation, the anterior cerebral artery (ACA) had a significantly higher occlusion rate compared to the ophthalmic artery (OphA) (OR = 6.54; 95% CI: 3.05 to 14.01; P  < 0.01), ACA also had a higher occlusion rate compared to the anterior choroidal artery (AchA) (OR = 15.44; 95% CI: 4.11 to 57.94 P  < 0.01), ACA versus posterior communicating artery (PcomA) occlusion rate difference was not statistically significant (OR = 2.58; 95% CI: 0.63 to 12.82; P  = 0.17), OphA versus AchA occlusion rate difference was not statistically significant (OR = 2.56; 95% CI: 0.89 to 7.38; P  = 0.08), and the occlusion rate was significantly higher for PcomA compared to AchA (OR = 7.22; 95% CI: 2.49 to 20.95; P  < 0.01) and lower for OphA compared to PcomA (OR = 0.33; 95% CI: 0.19 to 0.55; P  < 0.01). Conclusion The meta-analysis shows that use of multiple PEDs did not significantly increase the occlusion rate of branching vessels, and the larger the diameter of branching vessels covered by PED, the higher the occlusion rate of branching vessels. However, the incidence of complications is low after branching vessels occlusion in anterior circulation, which is related to the collateral circulation compensation of the branching vessels.

The deep integration of digital twins (DT) and agents is expected to open up new collaborative machine intelligence solutions. A new concept, namely, agent‐based digital twins (ADT), is proposed to establish a novel machine intelligence framework with automatic perception, self‐evolution and autonomous collaboration. This short article proposes a new concept of machine intelligence named agent‐based digital twins, which attempts to deeply integrate the digital twins and agents technologies.

This study investigates regional ground-motion characteristics in Yunnan Province using 1,065 recordings from 60 small-to-moderate earthquakes (3.0 ≤  M w ≤ 6.0) at 65 stations. A generalized inversion technique (GIT) using empirical reference site was applied to four tectonically distinct subregions (A–D). The inversion results reveal stress drops (Δ σ ) ranging from 0.3 to 7.34 MPa, with the highest averages in Regions C and D (2.21 MPa), followed by Region A (2.07 MPa) and Region B (1.16 MPa). Δ σ shows no clear dependence on moment magnitude ( M w ) or focal depth but correlates with surface heat flow. Reverse-faulting events exhibit a higher average Δ σ than strike-slip and normal-faulting events. Quality factor models for the four study areas (A–D) are 118.41 f 0.691 , 120.26 f 0.638 , 77.20 f 0.598 and 72.19 f 0.861 , respectively. The eastern regions (C and D) exhibit lower Q 0 and stronger S-wave attenuation, along with higher tectonic activity and lower surface heat flow. The predominant frequencies of average site amplification for GMX-A, GMX-B, GMX-C and GMX-D are 20.00 Hz, 10.83 Hz, 3.97 Hz, and 1.92 Hz, with corresponding amplification factors of 2.84, 4.31, 5.45, and 7.69. Finally, the inversion parameters were validated through stochastic finite-fault simulations of the 2009 M S 6.3 Yao’an mainshock.

The harmonic reducer is an essential kinetic transmission component in the industrial robots. It is easy to be fatigued and resulted in physical malfunction after a long period of operation. Therefore, an accurate in-situ fault diagnosis for the harmonic reducers in an industrial robot is especially important. This paper proposes a fault diagnosis method based on deep learning for the harmonic reducer of industrial robots via consecutive time-domain vibration signals. Considering the sampling signals from industrial robots are long, narrow, and channel-independent, this method combined a 1-dimensional convolutional neural network with matrix kernels (1-D MCNN) adaptive model. By adjusting the size of the convolution kernels, it can concentrate on the contextual feature extraction of consecutive time-domain data while retaining the ability to process the multi-channel fusion data. The proposed method is examined on a physical industrial robot platform, which has achieved a prediction accuracy of 99%. Its performance is appeared to be superior in comparison to the traditional 2-dimensional CNN, deep sparse automatic encoding network (DSAE), multilayer perceptual network (MLP), and support vector machine (SVM).

Diagnosing lung cancer from indeterminate pulmonary nodules (IPLs) remains challenging. In this multi-institutional study involving 2032 participants with IPLs, we integrate the clinical, radiomic with circulating cell-free DNA fragmentomic features in 5-methylcytosine (5mC)-enriched regions to establish a multiomics model (clinic-RadmC) for predicting the malignancy risk of IPLs. The clinic-RadmC yields an area-under-the-curve (AUC) of 0.923 on the external test set, outperforming the single-omics models, and models that only combine clinical features with radiomic, or fragmentomic features in 5mC-enriched regions ( p  < 0.050 for all). The superiority of the clinic-RadmC maintains well even after adjusting for clinic-radiological variables. Furthermore, the clinic-RadmC-guided strategy could reduce the unnecessary invasive procedures for benign IPLs by 10.9% ~ 35%, and avoid the delayed treatment for lung cancer by 3.1% ~ 38.8%. In summary, our study indicates that the clinic-RadmC provides a more effective and noninvasive tool for optimizing lung cancer diagnoses, thus facilitating the precision interventions. Diagnosis of lung cancer from indeterminate pulmonary nodules remains challenging. Here, the authors develop a multi-omics signature to identify oncogenic nodules, and prevent unnecessary procedures.

Background Limited access to genetic information has greatly hindered our understanding of the molecular evolution, phylogeny, and differentiation time of subg. Amygdalus . This study reported complete chloroplast (cp) genome sequences of subg. Amygdalus , which further enriched the available valuable resources of complete cp genomes of higher plants and deepened our understanding of the divergence time and phylogenetic relationships of subg. Amygdalus . Results The results showed that subg. Amygdalus species exhibited a tetrad structure with sizes ranging from 157,736 bp ( P. kansuensis ) to 158,971 bp ( P. davidiana ), a pair of inverted repeat regions (IRa/IRb) that ranged from 26,137–26,467 bp, a large single-copy region that ranged from 85,757–86,608 bp, and a small single-copy region that ranged from 19,020–19,133 bp. The average GC content of the complete cp genomes in the 12 species was 36.80%. We found that the structure of the subg. Amygdalus complete cp genomes was highly conserved, and the 12 subg. Amygdalus species had an rps 19 pseudogene. There was not rearrangement of the complete cp genome in the 12 subg. Amygdalus species. All 12 subg. Amygdalus species clustered into one clade based on both Bayesian inference and maximum likelihood. The divergence time analyses based on the complete cp genome sequences showed that subg. Amygdalus species diverged approximately 15.65 Mya. Conclusion Our results provide data on the genomic structure of subg. Amygdalus and elucidates their phylogenetic relationships and divergence time.

Semi-airborne transient electromagnetics (SATEM) is a geophysical survey tool known for its ability to perform three-dimensional (3D) observations and collect high-density data in large volumes. However, SATEM data processing is presently restricted to 3D model-driven inversion, which is not conducive to detailed surveys. This paper presents a new 3D model- and data-driven inversion algorithm using the particle swarm optimization (PSO) and gradient descent (GD) algorithms. PSO is used to suppress the multiplicity of solutions associated with inverse problems, and the GD algorithm is employed to accelerate the convergence of the inversion process. For the PSO-GD algorithm, a new model-updating equation is established and a cosine probability function is introduced as a weighting term for PSO and GD algorithms to ensure a smooth transition between the two algorithms in the iterative process. The α-trimmed filter function is used as a regularization constraint to smooth the model. The stability and reliability of the PSO-GD algorithm are verified through numerical simulations. Finally, the new algorithm is applied to the processing of SATEM measurements of the Qinshui coal mine in Jincheng, Shanxi Province, China.