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During video-assisted thoracic surgery, surgical smoke can interfere with the vision and attention of surgeons. In addition, the harmful substances in the surgical smoke also threaten the health of the surgical staff. In practice, we designed an economical and available solution for the smoke in video-assisted thoracic surgery, with satisfactory results. This report introduces the principle and procedure of this solution. [ABSTRACT FROM AUTHOR]

Osteoporosis, which manifests as reduced bone mass and deteriorated bone quality, is common in the elderly population. It is characterized by persistent elevation of macrophage-associated inflammation and active osteoclast bone resorption. Currently, the roles of intracellular metabolism in regulating these processes remain unclear. In this study, we initially performed bioinformatics analysis and observed a significant increase in the proportion of M1 macrophages in bone marrow with aging. Further metabolomics analysis demonstrated a notable reduction in the expression of carnitine metabolites in aged macrophages, while carnitine was not detected in osteoclasts. During the differentiation process, osteoclasts took up carnitine synthesized by macrophages to regulate their own activity. Mechanistically, carnitine enhanced the function of Nrf2 by inhibiting the Keap1-Nrf2 interaction, reducing the proteasome-dependent ubiquitination and degradation of Nrf2. In silico molecular ligand docking analysis of the interaction between carnitine and Keap1 showed that carnitine binds to Keap1 to stabilize Nrf2 and enhance its function. In this study, we found that the decrease in carnitine levels in aging macrophages causes overactivation of osteoclasts, ultimately leading to osteoporosis. A decrease in serum carnitine levels in patients with osteoporosis was found to have good diagnostic and predictive value. Moreover, supplementation with carnitine was shown to be effective in the treatment of osteoporosis. Carnitine activates Nrf2 in macrophage by inhibiting Keap1-Nrf2 protein-protein interaction (PPI), which further exerts anti-osteoporosis effects. In addition, carnitine serves a diagnostic indicator for osteoporosis. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, a marine dual fuel diesel engine fueled with the natural gas (NG: 60%, 70% and 80%) ignited by the biodiesel-diesel blended fuel (25%, 50% and 75% biodiesel by volume) was studied under different conditions. Based on the experiment, a computational fluid dynamics (CFD) model was established, and an improved chemical kinetic mechanism was developed to simulate the fuel spray process and combustion process. The ignition, combustion and emission characteristics of diesel engine fueled with different blended fuels were investigated under different load conditions. In addition, the temperature sensitivity of methane mole fraction with different NG energy fractions was analyzed at the 800 K and 1000 K. The results showed that the additions of NG and biodiesel in the blended fuel had a significant effect on the combustion and emission characteristics of the diesel engine. The starting of combustion (SOC) of the dual fuel engine lagged with the increases of NG and biodiesel content. The maximum enhancement of SOC reached 0.72°CA. The biggest influence on temperature was R122, which was the main reason for the shorter ignition delay during the combustion process. In all cases, NO x , CO and soot emissions decreased with increasing NG energy fraction. The maximum values of NO x , CO and soot emissions reached 1590 ppm, 461 ppm and 1.42 E−07 kg. Considering the combustion and emission characteristics of the engine, the best fuel blending ratio was EF80-B25. • A marine dual fuel diesel engine fueled with the natural gas ignited by the biodiesel-diesel blended fuel is investigated. • An improved 3D model and chemical kinetics mechanism are developed. • The optimum fuel mixture ratio of diesel engine is obtained. • The temperature sensitivity of methane mole fraction with different NG energy fractions is analyzed. [ABSTRACT FROM AUTHOR]

Extracellular ATP plays a key role in regulating plants stress responses. Here, we aimed to determine whether ATP can alleviate the glyphosate toxicity in maize seedlings under high temperature by regulating antioxidant responses. Foliar spraying with 100 μM glyphosate inhibited the growth of maize seedlings at room temperature (25 °C), leading to an increase in shikimic acid accumulation and oxidative stress (evaluated via lipid peroxidation, free proline, and H 2 O 2 content) in the leaves, all of which were further exacerbated by high temperature (35 °C). The growth inhibition and oxidative stress caused by glyphosate were both alleviated by exogenous ATP. Moreover, the glyphosate-induced antioxidant enzyme activity and antioxidant accumulation were attenuated by high temperature, while ATP treatment reversed this inhibitory effect. Similarly, qPCR data showed that the relative expression levels of antioxidant enzyme-related genes (CAT1 , GR1 , and γ-ECS) in maize leaves were upregulated by ATP before exposure to GLY. Moreover, high temperature-enhanced GLY residue accumulation in maize leaves was reduced by ATP. ATP-induced detoxification was attenuated through NADPH oxidase (NOX) inhibition. Higher NOX activities and O 2 •− production were noted in ATP-treated maize leaves compared to controls prior to GLY treatment, indicating that the extracellular ATP-induced alleviation of GLY toxicity was closely associated with NOX-dependent reactive oxygen species signalling. The current findings present a new approach for reducing herbicide toxicity in crops exposed to high temperatures. [Display omitted] • High temperatures aggravate glyphosate toxicity in maize seedlings. • ATP treatment alleviates glyphosate toxicity in maize seedlings. • ATP triggers the detoxification system in maize leaves. • ATP promotes glyphosate degradation in maize leaves. [ABSTRACT FROM AUTHOR]

Real-world point cloud objects pose great challenges in point cloud classification as objects acquired by scanning devices from real-world scans are often cluttered with background, and are partial due to occlusions as well as reconstruction errors. In the literature, few works tackle the problem of real-world point cloud classification while existing methods require fully point-level annotated training samples. However, large-scale dense point-level foreground–background labeling for real-world point clouds is a labor-intensive and time-consuming job. Leveraging two auxiliary modules, called semi-supervised point-level pseudo labels generation and noise-robust multi-task loss, the framework can integrate well with existing supervised point cloud classification network. A relational graph convolutional network on the local and non-local graph (PointRGCN) is first proposed to predict point-level foreground–background pseudo labels for each object with sparse ground-truth point-level foreground–background labels in training datasets. Then, a weakly supervised classification network, which combines with an auxiliary foreground–background segmentation branch, is employed to classify real-world point clouds. To cope with noise-containing point-level foreground–background labels generated above, a noise-robust multi-task loss is proposed to train the network accurately. Experimental results show that the performance of the proposed framework which is trained with only 1% point-level labels is comparable with many popular or state-of-the-art fully supervised methods. The source code will be available at http://zhiyongsu.github.io. [Display omitted] • A novel weakly supervised framework for real-world point cloud classification. • A local and non-local graph based relational graph convolutional network (PointRGCN). • A noise-robust multi-task loss combining classification and segmentation losses. [ABSTRACT FROM AUTHOR]

[Display omitted] • 3D porous graphene (3DPG) as reinforced additive was investigated in SBS/crumb rubber blend-modified asphalt. • 3DPG can significantly improve high and low-temperature performance and fatigue life of SBS/crumb rubber blend-modified asphalts. • The nanopores in 3DPG can effectively enhance the compatibility of SBS and crumb rubber in asphalt system by virtue of its unique amphiphilicity. • 3DPG as a new synergist presents a promising solution for the critical issue of wide adoption of crumb rubber modified asphalt for high-performance pavement. Styrene-butadiene-styrene (SBS)/crumb rubber (CR) blend-modified asphalt is a desirable binder for pavement engineering with both environmental and economic benefits. However, the inherent incompatibility of SBS and CR in asphalt is still a critical issue. Herein, 3D porous graphene (3DPG) with high surface area and rich micropores as reinforced additive was investigated in SBS/CR blend-modified asphalt for the first time. The experimental results demonstrate that incorporating 3DPG can effectively improve the compatibility of SBS and CR in asphalt and thus significantly enhance the high and low temperature performance and fatigue resistance of the modified asphalt, compared with that without 3DPG. Theoretical calculations further reveal that the nanopores in graphene can endow graphene with electrophilic property, providing a capability of absorbing nonpolar molecules in asphalt while the non-pore part in graphene can interact with polar molecules by conventional π − π stacking. The two forces within graphene can break the original colloidal structures of asphalt, which is conductive to the homogenous formation of SBS network and swelling of CR in asphalt, significantly promoting the pavement performance of the modified asphalt. This work presents the great potential of 3DPG as new additive to solve the inherent incompatibility of SBS/CR blend-modified asphalt for high-grade pavement engineering. [ABSTRACT FROM AUTHOR]

• The development of higher alcohols of modern automobile engines is listed. • The improvements of higher alcohols characteristic are discussed. • Optimization applications in diesel engine are investigated. • Improvement suggestions for performance enhancement of diesel engine are proposed. The application of oxygenated alternative fuels in diesel engines is an effective way to solve the energy crisis and environmental pollution. Higher alcohols (butanol and pentanol), as oxygenated and renewable fuels, are considered as new promising alternative fuels for diesel engine due to their good physicochemical properties and excellent combustion and emission characteristics in engines. The combustion is a complex process and has a significant impact on performance and emission characteristics of compression ignition (CI) engines. There are complicated relationships among CI engine, environment and fuel physicochemical properties, which interacts with each other. Therefore, it is important to investigate the synergistic effects of alternative fuels and their additives on CI engines. In recent years, the research on the advanced alcohols and its additives had made great progress. However, few people have reviewed the synergistic effect of higher alcohols and its additives on diesel engines. Therefore, this paper takes the combustion, performance and emission aspects of higher alcohols and its additives on the diesel engine as a starting point. Firstly, the physicochemical properties and preparations of higher alcohols are described, and their advantages are highlighted. Then, the effects of higher alcohols and its additives on the combustion, performance and emission characteristics of CI engines are summarized in terms of neat fuel, dual-fuel injection and multi-fuel blends, exhaust gas recirculation (EGR), injection strategy and advanced combustion mode. Finally, some important conclusions and discussions on the future development and experimental research direction are put forward, which will be helpful for the research on the use of higher alcohol in CI engines. [ABSTRACT FROM AUTHOR]

[Display omitted] • Multi-crosslinked Flexible CNC/PVAGMA/TA nanocomposite hydrogel fibers was prepared. • The CNC/PVAGMA/TA nanocomposite hydrogels exhibited excellent tensile strengths as well as high-water content of 70 %. • The hydrogel fibers can be easily knitted into various complex geometries or integral textiles. Hydrogel fibers with excellent mechanical properties are requested for biomedical applications, especially for flexible and wearable devices. However, it remains a challenge to fabricate hydrogel fibers with both enough strength and high water content. Herein, we prepare cellulose nanocrystal/polyvinyl alcohol nanocomposite hydrogels by rapid covalent crosslinking and the subsequent strong hydrogen bonding interaction derived from tannic acid. The multi-crosslinked skeletal structure endows the hydrogels with excellent tensile strengths as well as high water content, compared to the polyvinyl alcohol-glycidylmethacrylate hydrogels. Notably, P10C5T15 hydrogel can lift loads to 4.375 kg, which is approximately 2353 times its weight. Subsequently, the flexible and mechanically stable hydrogel fibers are fabricated with a tensile strength of 7.3 MPa and a breaking elongation of 123.8 %. Furthermore, the fabricated hydrogel fibers can be easily knitted into various complex geometries or integral textiles, suggesting their great potential for woven smart devices. [ABSTRACT FROM AUTHOR]

Point cloud denoising is a crucial and fundamental step in geometry processing, which has achieved significant progress in the last two decades. Denoising real-world noisy point clouds is a very challenging problem since it is hard to describe the complex real-world noise by simple distributions such as Gaussian distribution. Furthermore, existing methods may suffer from performance degradation when dealing with real-world noisy point clouds with complex structures, which contain not only sharp features (sharp edges, sharp corners, etc.) but also smooth features, fine features, etc. To solve the above-mentioned problems, we propose a novel structure-aware denoising approach by exploiting the prior information in both external clean point clouds and the given noisy point cloud. We first group nonlocal self-similarity (NSS) patches from a set of external clean point clouds. Then, we employ the Gaussian Mixture Model (GMM) learning algorithm to learn external NSS priors over patch groups. Next, the internal priors are learned from the given noisy point cloud in the same way to refine the prior model. We integrate both the learned external and internal priors into a set of orthogonal dictionaries to efficiently estimate point normals. Finally, we propose a feature-aware point updating method through adaptive neighborhood selection to reposition points to match the estimated normals. Extensive experiments show that our approach achieves favorable comprehensive performance compared with many popular or state-of-the-art methods in terms of both objective and visual perception. The source code can be found at https://zhiyongsu.github.io. • A structure-aware denoising method is proposed for real-world noisy point clouds. • The proposed method jointly learns external and internal priors for denoising. • A feature-aware point updating method is proposed. [ABSTRACT FROM AUTHOR]