Polymeric materials with high heat resistance and low dielectric constants are desired for fast communication. To realize this purpose, two kinds of silicon-containing main chain type benzoxazines ...with and without an acetylene group, (ABA-Si-ala)main and (ABA-Si-a)main, were designed and synthesized from polyphenol oligomers, primary amines, and paraformaldehyde. Their chemical structures were characterized and verified by Fourier transform infrared (FTIR) spectra and nuclear magnetic resonance (NMR) spectra. Moreover, their curing behaviors and polymerization reactions were studied by differential scanning calorimetry (DSC) and FTIR spectra, and cross-linking structures were proposed. Furthermore, thermal properties of the two polybenzoxazines were analyzed by dynamic mechanical analysis (DMA) and thermogravimetric analysis (TGA). The results showed that poly(ABA-Si-ala)main exhibited excellent heat resistance and thermal stability, and its T g and char yield at 800 °C under N2 reached as high as 308 °C and 48.5%, respectively, which were higher than those of poly(ABA-Si-a)main. In particular, the existence of the siloxane structure endowed the two polybenzoxazines with good dielectric properties, and the dielectric constants of poly(ABA-Si-ala)main and poly(ABA-Si-a)main were as low as 2.78 and 2.67 at 1 GHz, respectively. Such low dielectric constants will be necessary and vital for signal transmission. Therefore, this work provides a new and effective strategy for designing new polymers with both excellent heat resistance and low dielectric constants.
Hepatocellular carcinoma (HCC) has high relapse and low 5-year survival rates. Single-cell profiling in relapsed HCC may aid in the design of effective anticancer therapies, including ...immunotherapies. We profiled the transcriptomes of ∼17,000 cells from 18 primary or early-relapse HCC cases. Early-relapse tumors have reduced levels of regulatory T cells, increased dendritic cells (DCs), and increased infiltrated CD8+ T cells, compared with primary tumors, in two independent cohorts. Remarkably, CD8+ T cells in recurrent tumors overexpressed KLRB1 (CD161) and displayed an innate-like low cytotoxic state, with low clonal expansion, unlike the classical exhausted state observed in primary HCC. The enrichment of these cells was associated with a worse prognosis. Differential gene expression and interaction analyses revealed potential immune evasion mechanisms in recurrent tumor cells that dampen DC antigen presentation and recruit innate-like CD8+ T cells. Our comprehensive picture of the HCC ecosystem provides deeper insights into immune evasion mechanisms associated with tumor relapse.
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•ScRNA-seq reveals a distinct immune ecosystem in early-relapse HCC•Decreased Tregs, increased DCs, and CD8+ T cells were observed in early-relapse HCC•CD8+ T cells have an innate-like, low cytotoxic, and low clonal expansion phenotype•Recurrent malignant cells mediate the compromised antitumor immune response
Single-cell analysis of primary and relapsed hepatocellular carcinoma tumors from patients reveal innate-like CD8+ T cells with low cytotoxicity and clonal expansion in the latter that may explain the compromised antitumor immunity and poor prognosis associated with liver cancer.
•The adiabatic shear failure process of solids was investigated for the first time by dynamic tests synchronically combined with high-speed photography and infrared temperature measurement.•The key ...characteristics of ASB, such as temperature, critical strain, propagation speed and cooling rate were systematically studied.•The experimental results shows that the apparent temperature rise might have occurred after ASB initiation, indicating it might not be the causation but the consequences of ASB.•The discovery might help to clarify the causality of ASB and serve as the starting point for further physical, mechanistic and mathematic studies of ASB.
One of the most important issues related to dynamic shear localization is the correlation among the stress collapse, temperature elevation and adiabatic shear band (ASB) formation. In this work, the adiabatic shear failure process of pure titanium was investigated by dynamic shear-compression tests synchronically combined with high-speed photography and infrared temperature measurement. The time sequence of important events such as stress collapse, ASB initiation, temperature rise and crack formation was recorded. The key characteristics of ASB, such as width, critical strain, temperature, propagation speed and cooling rate were systematically studied. The maximum propagation velocity of ASB is found in this work to be about 1900 m/s, about 0.6Cs (Cs is the shear wave speed). The maximum temperature within ASB is in the range of 350–650 °C, while the material close to ASB is also heated. The cooling rate of ASB is on the order of 106 °C/s, indicating that it needs a few hundreds of microseconds for the ASB to cool down to the ambient temperature. One important observation is that the apparent temperature rise occurs after ASB initiation, which indicates that it might not be the causation but the consequences of ASB. Further efforts are called for confirmation of this notion because of its significance.
In present work, the abrasive-free jet polishing (AFJP) of bulk single-crystal KDP was first fulfilled, when using a newly-designed low-viscosity microemulsion as the AFJP fluid. The novel AFJP fluid ...shows a typical water-in-oil structure, in which the water cores uniformly distribute in the BmimPF6 IL, with a particle size of about 20-25 nm. What's more, the AFJP fluid is a controllable and selective non-abrasive jet fluid that the shape of the removal function is regular and smooth, presenting a similar Gaussian function, meanwhile, the dispersion coefficient of the removal rate is only 1.9%. Finally, the surface quality of the bulk single-crystal KDP is further improved by AFJP, meanwhile, the subsurface damage is first obviously mitigated.
The containment control is studied for the second-order multiagent systems over a heterogeneous network where the position and velocity interactions are different. We consider three cases that ...multiple leaders are stationary, moving at the same constant speed, and moving at the same time-varying speed, and develop different containment control algorithms for each case. In particular, for the former two cases, we first propose the containment algorithms based on the well-established ones for the homogeneous network, for which the position interaction topology is required to be undirected. Then, we extend the results to the general setting with the directed position and velocity interaction topologies by developing a novel algorithm. For the last case with time-varying velocities, we introduce two algorithms to address the containment control problem under, respectively, the directed and undirected interaction topologies. For most cases, sufficient conditions with regard to the interaction topologies are derived for guaranteeing the containment behavior and, thus, are easy to verify. Finally, six simulation examples are presented to illustrate the validity of the theoretical findings.
In this paper, we aim to investigate the optimal synchronization problem for a group of generic linear systems with input saturation. To seek the optimal controller, Hamilton-Jacobi-Bellman (HJB) ...equations involving nonquadratic input energy terms in coupled forms are established. The solutions to these coupled HJB equations are further proven to be optimal and the induced controllers constitute interactive Nash equilibrium. Due to the difficulty to analytically solve HJB equations, especially in coupled forms, and the possible lack of model information of the systems, we apply the data-based off-policy reinforcement learning algorithm to learn the optimal control policies. A byproduct of this off-policy algorithm is shown that it is insensitive to probing noise that is exerted to the system to maintain persistence of excitation condition. In order to implement this off-policy algorithm, we employ actor and critic neural networks to approximate the controllers and the cost functions. Furthermore, the estimated control policies obtained by this presented implementation are proven to converge to the optimal ones under certain conditions. Finally, an illustrative example is provided to verify the effectiveness of the proposed algorithm.
Limited by the shape-fixed kernels, convolutional neural networks (CNNs) are usually difficult to model difform land covers in hyperspectral images (HSIs), leading to inadequate land use. Recently, ...benefiting from the ability to conduct shape-adaptive convolutions and model complex patterns in graph-structured data, graph convolutional networks (GCNs) have been applied to HSI classification. However, due to the massive computation in GCNs, HSI is usually pretreated into a graph based on a specific superpixel segmentation, which limits the modeling of spatial topologies to the same scale. To break this limitation, we propose a multilevel superpixel structured graph U-Net (MSSGU) to learn multiscale features on multilevel graphs. Specifically, we construct several hierarchical segmentations from fine to coarse by progressively merging adjacent superpixels and then convert them into multilevel graphs. Meanwhile, based on the merging relations between hierarchical superpixels, we establish the pooling and unpooling functions to transfer features from one graph to another, thereby enabling different-level graphs to collaborate in a single network. Different from concatenating different-scale features straightforwardly in the feature fusion stage, MSSGU fuses them in a coarse-to-fine progressive manner, which can generate subtler fusion features adaptive to the pixelwise classification task. Moreover, we use a CNN instead of GCN to extract and fuse the pixel-level features, which greatly reduces the computation. Such a hybrid U-Net can exploit features of HSIs from a multiscale hierarchical perspective, and its performance has been proven competitive with other deep-learning-based methods by extensive experiments on three benchmark datasets.
The concentrations of SDS from a to d increase in turn.
•There exists moderate SDS concentration for the most stable SiO2/SDS foam.•The enhanced viscoelasticity of air–liquid surface improves the ...foam stability.•The SiO2/SDS foam mitigates the viscous fingering instability in sandpack.
Although foam has been widely used in petroleum industry, its instability is still a problem during its applications. Here, partially hydrophobic modified SiO2 nanoparticles were used with sodium dodecyl sulfate (SDS) to increase the foam stability. Surface tension, interfacial dilational viscoelasticity, and ζ potential of SiO2/SDS aqueous dispersion had been determined and correlated with foam stability and plugging ability in porous media. The experimental results showed that SiO2 nanoparticle had a synergetic effect on foam stability with SDS at proper concentrations, and more stable foam could be obtained from SiO2/SDS dispersion compared to SDS solution. It is deduced that SDS molecules help the nanoparticles to move to air–liquid interface at moderate concentration, and thus the dilational viscoelasticity increased consequently. SiO2/SDS foam showed a good plugging performance in the sandpack flooding experiment. Foam stability was enhanced with nanoparticles adsorbed on the surface of liquid film, so bubbles did not rupture easily in porous media. As a result, more gas was trapped in the sandpack to prevent gas breakthrough. These fundamental results may guide the application of nanoparticle-stabilized foams in oil field.
In this technical note, we investigate the H ∞ group consensus for networks of agents modeled by single-integrator with model uncertainty and external disturbance. By developing tools from algebraic ...graph theory, matrix analysis as well as Lyapunov stability theory, we are able to derive some sufficient conditions in terms of the structure and strength of the couplings among agents so as to guarantee the group consensus with desired H ∞ performance. Such conditions are structural and easy to check. Furthermore, some adaptation laws are proposed to address the coupling strength problem arising from the consideration that the theoretical value is usually much larger than expected in practice. Finally, some simulation examples are presented to demonstrate the efficiency of the theoretical findings.
Extensive grape pomace from red-winemaking may seriously pollute the environment and cause the waste of resources. Cellulose after fermentation in grape pomace is suitable as the source of extract ...outstanding cellulose nanocrystals (CNCs). Herein, CNCs were successfully extracted from grape pomace with an eco-friendly and facile deep eutectic solvent (DES). The green DES with the composition of lactic acid/choline chloride (the molar ratio was 2:1), were used to fabricate CNCs. Importantly, the obtained CNCs as a robust nanocomposite can be successfully utilized to prepare the self-healing nanocomposite hydrogels. After added of Fe(III) and borax, the excellent self-healing performance of the guar gum-based hydrogels were achieved by the reversible noncovalent bonding interaction. Specifically, the hydrogels showed good mechanical properties (the stress was about 0.95 MPa, the strain was about 170%) and self-healing ability (the self-healing efficiency was about 90.0%). These biologically self-healing nanocomposite hydrogels can greatly broaden the recycling and utilization of grape pomace.
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