Engineering最新文献

Practical real-world scenarios such as the Internet, social networks, and biological networks present the challenges of data scarcity and complex correlations, which limit the applications of artificial intelligence. The graph structure is a typical tool used to formulate such correlations, it is incapable of modeling high-order correlations among different objects in systems; thus, the graph structure cannot fully convey the intricate correlations among objects. Confronted with the aforementioned two challenges, hypergraph computation models high-order correlations among data, knowledge, and rules through hyperedges and leverages these high-order correlations to enhance the data. Additionally, hypergraph computation achieves collaborative computation using data and high-order correlations, thereby offering greater modeling flexibility. In particular, we introduce three types of hypergraph computation methods: ① hypergraph structure modeling, ② hypergraph semantic computing, and ③ efficient hypergraph computing. We then specify how to adopt hypergraph computation in practice by focusing on specific tasks such as three-dimensional (3D) object recognition, revealing that hypergraph computation can reduce the data requirement by 80% while achieving comparable performance or improve the performance by 52% given the same data, compared with a traditional data-based method. A comprehensive overview of the applications of hypergraph computation in diverse domains, such as intelligent medicine and computer vision, is also provided. Finally, we introduce an open-source deep learning library, DeepHypergraph (DHG), which can serve as a tool for the practical usage of hypergraph computation.

Microparticles have demonstrated value for regenerative medicine. Attempts in this field tend to focus on the development of intelligent multifunctional microparticles for tissue regeneration. Here, inspired by erythrocytes-associated self-repairing process in damaged tissue, we present novel biomimetic erythrocyte-like microparticles (ELMPs). These ELMPs, which are composed of extracellular matrix-like hybrid hydrogels and the functional additives of black phosphorus, hemoglobin, and growth factors (GFs), are generated by using a microfluidic electrospray. As the resultant ELMPs have the capacity for oxygen delivery and near-infrared-responsive release of both GFs and oxygen, they would have excellent biocompatibility and multifunctional performance when serving as microscaffolds for cell adhesion, stimulating angiogenesis, and adjusting the release profile of cargoes. Based on these features, we demonstrate that the ELMPs can stably overlap to fill a wound and realize controllable cargo release to achieve the desired curative effect of tissue regeneration. Thus, we consider our biomimetic ELMPs with discoid morphology and cargo-delivery capacity to be ideal for tissue engineering.

Strain gradient is a normal phenomenon around a heterostructural interface in ultrathin film, and it is important to determine its effect on magnetic interactions to understand interfacial coupling. In this work, ultrathin Pr_0.67Sr_0.33MnO₃ (PSMO) films on different substrates are studied. For PSMO film under different in-plane strain conditions, the saturated magnetization and Curie temperature can be qualitatively explained by double-exchange interaction and the Jahn–Teller distortion. However, the difference in the saturated magnetization with zero field cooling and 5 T field cooling is proportional to the strain gradient. Strain-gradient-induced structural disorder is proposed to enhance phonon–electron antiferromagnetic interactions and the corresponding antiferromagnetic-to-ferromagnetic phase transition via a strong magnetic field during the field cooling process. A non-monotonous structural transition of the MnO₆ octahedral rotation can enlarge the strain gradient in PSMO film on a SrTiO₃ substrate. This work demonstrates the existence of the flexomagnetic effect in ultrathin manganite film, which should be applicable to other complex oxide systems.

Ice pigging is an emerging technique for pipe cleaning in drinking water distribution systems. However, substantial confusion and controversy exist on the potential impacts of ice pigging on bulk water quality. This study monitored the microstructural features and composition of sediments and microbial community structures in bulk water in eight multimaterial Chinese networks. Chloride concentration analysis demonstrated that separate cleaning of pipes with different materials in complex networks could mitigate the risk of losing ice pigs and degrading water quality. The microstructural and trace element characterization results showed that ice pigs would scarcely disturb the inner surfaces of long-used pipes. The bacterial richness and diversity of bulk water decreased significantly after ice pigging. Furthermore, correlations were established between pipe service age, temperature, and chloride and total iron concentrations, and the 15 most abundant taxa in bulk water, which could be used to guide practical ice pigging operations.

Decarbonization and decontamination of the iron and steel industry (ISI), which contributes up to 15% to anthropogenic CO₂ emissions (or carbon emissions) and significant proportions of air and water pollutant emissions in China, are challenged by the huge demand for steel. Carbon and pollutants often share common emission sources, indicating that emission reduction could be achieved synergistically. Here, we explored the inherent potential of measures to adjust feedstock composition and technological structure and to control the size of the ISI to achieve carbon emission reduction (CER) and pollution emission reduction (PER). We investigated five typical pollutants in this study, namely, petroleum hydrocarbon pollutants and chemical oxygen demand in wastewater, particulate matter, SO₂, and NO_x in off gases, and examined synergies between CER and PER by employing cross elasticity for the period between 2022 and 2035. The results suggest that a reduction of 8.7%–11.7% in carbon emissions and 20%–31% in pollution emissions (except for particulate matter emissions) could be achieved by 2025 under a high steel scrap ratio (SSR) scenario. Here, the SSR and electric arc furnace (EAF) ratio serve critical roles in enhancing synergies between CER and PER (which vary with the type of pollutant). However, subject to a limited volume of steel scrap, a focused increase in the EAF ratio with neglection of the available supply of steel scrap to EAF facilities would lead to an increase carbon and pollution emissions. Although CER can be achieved through SSR and EAF ratio optimization, only when the crude steel production growth rate remains below 2.2% can these optimization measures maintain the emissions in 2030 at a similar level to that in 2021. Therefore, the synergistic effects between PER and CER should be considered when formulating a development route for the ISI in the future.