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Additive manufacturing of aluminum (Al) alloys has attracted significant attention in the aerospace industry. However, achieving ultrahigh-strength (>500 MPa) Al alloys remains challenging due to their intrinsic poor printability. Here, we report a novel hybrid additive manufacturing (HAM) approach to process ultrahigh-strength AlMgSc alloy, which combines laser powder bed fusion (LPBF) with interlayer ultrasonic shot peening (USP). The results show that the interlayer ultrasonic shot peening depth reached ∼700 µm, leading to almost full density and residual stress convection from tension to compression. The HAM method promotes equiaxed grain formation and refines grain due to grain recrystallizations. Interestingly, the HAM followed by aging treatment tailors the hierarchically multi-gradient structures, inhibits Mg element intragranular segregation, and promotes the multi-nanoprecipitates (e.g. Al 3 (Sc, Zr) and Al 6 Mn) precipitation. Remarkably, the HAM followed by aging treatment achieves yield strength of 609 MPa and breaks elongation of 7.5%, demonstrating ultrahigh strength and good ductility compared with other Al alloys manufactured by AM and forging as reported in the literature. The strength enhancement mechanisms in this AlMgSc alloy are discussed. The high-density Al 3 (Sc, Zr) precipitates are the main strengthening contributor, and unique hetero-deformation induced (HDI) strengthening (originates from the heterogeneous microstructures) further enhances the strength of the material. This work highlights a novel approach for processing complex-structured ultrahigh strength Al alloy components by hybrid additive manufacturing. Hybrid additive manufacturing for processing ultrahigh strength Al alloy. Hierarchically gradient microstructures involving grain and dislocation gradients. Achieved ultrahigh yield strength (>600 MPa) together with a good elongation of 7.5%. Hybrid additive manufacturing enhances strength without evidently sacrificing ductility.

Crowdsourced trajectory data of ships provide the opportunity for extracting marine lane information. However, extracting useful knowledge from massive amounts of trajectory data is a challenging problem. Trajectory data collected from crowdsourcing can be extremely diverse in different areas and its quality might be very low. Moreover, the density distribution of the crowdsourced trajectory points is quite uneven in different areas. Furthermore, it is necessary to extract marine lanes with high extraction precision in offshore and nearshore water areas, but extraction precision can be lower in the open sea. We propose an adaptive approach for marine lane extraction and refinement based on grid merging and filtering to meet the challenges. In this paper, after pre-processing and clustering the trajectory data based on the density value of grids with a parallel GeoHash encoding algorithm, we propose a parallel grid merging and filtering algorithm based on a QuadTree data structure. The algorithm performs grid merging on the simplified grid data according to the density value of grid, then filters the merged grid data based on a local sliding window mechanism to get the marine lane grid data. Applying the Delaunay Triangulation on the marine lane grid data, the marine lane boundary information can be extracted with adaptive extraction precision. Experimental results show that the proposed approach can extract marine lanes with high extraction precision in offshore and nearshore water area and low extraction precision in open sea area.

The manufacturing process of launch vehicle storage tanks requires urgent simplification, which can be improved by forming the local features after artificial aging. Therefore, a new process of warm flanging aluminum alloys with pre-deformation was proposed to meet this requirement. The mechanical properties of 2219 aluminum alloy with pre-deformation were investigated at different temperatures using thermomechanical property testing. The deformation law of warm flanging was analyzed through simulation. The flanging limit of 2219 aluminum alloy with pre-deformation was obtained through experiments. Results showed that the ductility of 2219 aluminum alloy with pre-deformation increased then decreased with the increasing temperature, a maximum strain of 0.65 was obtained at 200°C. The equivalent strain gradually rose from the corner zone to the straight wall zone during flanging. The maximum equivalent strain is located at the edge of the straight wall, which gradually decreases with the increasing flanging coefficient. A flanging coefficient of 0.60 can be obtained at 200°C without splitting or seriously thinning. These results guide the local flanging of the integral bottom of 2219 aluminum alloy.

Programmed cell death （PCD） is of fundamental importance to development and defense in animals and plants. In plants, a well-recognized form of PCD is hypersensitive response （HR） triggered by pathogens, which involves the generation of reactive oxygen species （ROS） and other signaling molecules. While the mitochondrion is a master reg- ulator of PCD in animals, the chloroplast is known to regulate PCD in plants. Arabidopsis Mosaic Death 1 （MOD1）, an enoyl-acyl carrier protein （ACP） reductase essential for fatty acid biosynthesis in chloroplasts, negatively regulates PCD in Arabidopsis. Here we report that PCD in modl results from accumulated ROS and can be suppressed by mu- tations in mitochondrial complex I components, and that the suppression is confirmed by pharmaceutical inhibition of the complex 1-generated ROS. We further show that intact mitochondria are required for full HR and optimum disease resistance to the Pseudomonas syringae bacteria. These findings strongly indicate that the ROS generated in the electron transport chain in mitochondria plays a key role in triggering plant PCD and highlight an important role of the communication between chloroplast and mitochondrion in the control of PCD in plants.

The rear pressure measurement position of V-cone flowmeter is in the complex vortex structure area after fluid around the cone. The non-uniformity of the fluid field will influence the measurement precision of V-cone flowmeter. Large eddy simulation (LES) has been used to study the V-cone flowmeter’s 3-D flow field structure with different Reynolds number in this paper. The better fluid area information can gain by this way. The results show that the values of discharge coefficient (Cd) obtained from LES are more close to the experiment data than the values obtained from k-ε model. Different turbulence intensity with different Reynolds number effects the velocity distribution in the V-cone flowmeter’s flow field. When Reynolds number equals to 20000, the flow field within 8d distance from V-cone tail should keep from being disturbed while the flowmeter under working condition. The non-interfering distance from V-cone tail flow field increases with the Reynolds number raising. These analysis results can offer optimizational information for V-cone flowmeter performance and testing method improvement.

Radiotherapy (RT) is a major treatment for malignant tumors. The latest data show that >70% of patients with malignant tumors need RT at different periods. Skin changes can be experienced by up to 95% of patients who underwent RT. Inflammation and oxidative stress (OS) have been shown to be generally associated with radiation-induced skin reactions (RISRs). Inflammatory response and OS interact and promote each other during RISRs. Severe skin reactions often have a great impact on the progress of RT. The treatment of RISRs is particularly critical because advanced RT technology can also lead to skin reactions. RISRs are classified into acute and chronic reactions. The treatment methods for acute RISRs include steroid treatment, creams, ointments, and hydrocolloid dressings, depending on the reaction grading. Chronic RISRs includes chronic ulcerations, telangiectasias, and fibrosis of the skin, and advanced treatments such as mesenchymal stem cells, hyperbaric oxygen therapy, superoxide dismutase, and low-intensity laser therapy can be considered. Here, we review and summarize the important mechanisms that cause RISRs as well as the standard and advanced treatments for RISRs.

With the continuous growth of global energy demand and the late stage of conventional oilfield exploitation, the demand for developing and utilizing low-permeability heavy oil reservoirs is becoming increasingly urgent. However, the exploitation of low-permeability heavy oil reservoirs faces many challenges due to their high viscosity, low permeability, and complex geological conditions. To overcome these challenges, researchers have gradually introduced SC-CO2 as an oil displacement agent in the exploitation of heavy oil reservoirs. However, the oil displacement mechanism of SC-CO2 in low-permeability heavy oil reservoirs and its improvement mechanism are still not completely understood. The article provides a detailed study and understanding of the oil displacement mechanism of SC-CO2, which involves the expansion of heavy oil volume through SC-CO2 dissolution. This mechanism reduces the capillary resistance and flow resistance during the oil flow process. The permeation of CO2 disrupts the internal structure and arrangement of heavy oil, reducing its viscosity. CO2 extracts both light and heavy components from the heavy oil, reducing the residual oil saturation. In addition, the mechanism of improving the effect of oil displacement agents such as nanoparticles, polymers, and surfactants on SC-CO2 displacement was also explored. By further exploring the mechanisms and improvement mechanisms of SC-CO2 displacement for heavy oil, it can guide the selection and optimization of oil displacement agents. Furthermore, understanding the mechanism can also provide a theoretical basis for engineering practice and technical innovation. While the research on CO2 flooding is analyzed and evaluated, the obstacles and challenges that still exist at this stage are indicated, and future research work on CO2 in low-permeability heavy oil reservoirs is proposed.

With the increasing incidence of thoracic tumors, radiation therapy (RT) has become an important component of comprehensive treatment. RT improves survival in many cancers, but it involves some inevitable complications. Radiation-induced heart disease (RIHD) is one of the most serious complications. RIHD comprises a spectrum of heart disease including cardiomyopathy, pericarditis, coronary artery disease, valvular heart disease and conduction system abnormalities. There are numerous clinical manifestations of RIHD, such as chest pain, palpitation, and dyspnea, even without obvious symptoms. Based on previous studies, the pathogenesis of RIHD is related to the production and effects of various cytokines caused by endothelial injury, inflammatory response, and oxidative stress (OS). Therefore, it is of great importance for clinicians to identify the mechanism and propose interventions for the prevention of RIHD.

The bandgap of two-dimensional (2D) materials plays an important role in their applications to various devices. For instance, the gapless nature of graphene limits the use of this material to semiconductor device applications, whereas the indirect bandgap of molybdenum disulfide is suitable for electrical and photo-device applications. Therefore, predicting the bandgap rapidly and accurately for a given 2D material structure has great scientific significance in the manufacturing of semiconductor devices. Compared to the extremely high computation cost of conventional first-principles calculations, machine learning (ML) based on statistics may be a promising alternative to predicting bandgaps. Although ML algorithms have been used to predict the properties of materials, they have rarely been used to predict the properties of 2D materials. In this study, we apply four ML algorithms to predict the bandgaps of 2D materials based on the computational 2D materials database (C2DB). Gradient boosted decision trees and random forests are more effective in predicting bandgaps of 2D materials with an R 2 >90% and root-mean-square error (RMSE) of ~0.24 eV and 0.27 eV, respectively. By contrast, support vector regression and multi-layer perceptron show that R 2 is >70% with RMSE of ~0.41 eV and 0.43 eV, respectively. Finally, when the bandgap calculated without spin-orbit coupling (SOC) is used as a feature, the RMSEs of the four ML models decrease greatly to 0.09 eV, 0.10 eV, 0.17 eV, and 0.12 eV, respectively. The R 2 of all the models is >94%. These results show that the properties of 2D materials can be rapidly obtained by ML prediction with high precision.

Radiotherapy (RT) is currently one of the leading treatments for various cancers; however, it may cause damage to healthy tissue, with both short-term and long-term side effects. Severe radiation-induced normal tissue damage (RINTD) frequently has a significant influence on the progress of RT and the survival and prognosis of patients. The redox system has been shown to play an important role in the early and late effects of RINTD. Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are the main sources of RINTD. The free radicals produced by irradiation can upregulate several enzymes including nicotinamide adenine dinucleotide phosphate oxidase (NADPH oxidase), lipoxygenases (LOXs), nitric oxide synthase (NOS), and cyclooxygenases (COXs). These enzymes are expressed in distinct ways in various cells, tissues, and organs and participate in the RINTD process through different regulatory mechanisms. In recent years, several studies have demonstrated that epigenetic modulators play an important role in the RINTD process. Epigenetic modifications primarily contain noncoding RNA regulation, histone modifications, and DNA methylation. In this article, we will review the role of oxidative stress and epigenetic mechanisms in radiation damage, and explore possible prophylactic and therapeutic strategies for RINTD.