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In order to prepare a high-bandwidth absorbing material with both mechanical properties and electromagnetic absorption properties, a nano-particle modification and physical blending method were used to design and prepare a carbonyl iron room temperature vulcanized silicone rubber composite material based on polydimethylsiloxane. The mechanical properties and wave absorbing properties of the composite material were systematically analyzed. The results show that when the mass fraction of white carbon black is 3%, the composite material has the best comprehensive mechanical properties and is convenient for material processing; the composite material is a magnetic loss type wave absorbing material, and the attenuation constant of the material is positively correlated with the carbonyl iron content and frequency. According to simulation calculations, the absorption peak of electromagnetic waves gradually shifts to low frequency as the thickness of the composite material and the content of carbonyl iron are increased at 2-18 GHz. When the thickness of the composite material is 1.5 mm and the mass fraction of carbonyl iron is 75%, the effective absorption bandwidth of the absorbing material can reach 9.07 GHz, accounting for 56.68% of the target bandwidth. In practical applications, the formula can be optimized and the thickness of the material can be controlled according to the needs of the application scenario to achieve the best absorbing effect.

Cell therapy based on mesenchymal stem cells (MSCs) alleviate muscle atrophy caused by diabetes and aging; however, the impact of human umbilical cord mesenchymal stem cells on muscle atrophy following nerve injury and the underlying mechanisms remain unclear. In this study, we evaluated the therapeutic efficacy of human umbilical cord MSCs (hucMSCs) and hucMSC-derived exosomes (hucMSC-EXOs) for muscle atrophy following nerve injury and identified the underlying molecular mechanisms. Sciatic nerve crush injury in rats and the induction of myotubes in L6 cells were used to determine the ameliorating effect of hucMSCs and hucMSC-EXOs on muscle atrophy. Q-PCR and Western blot analyses were used to measure the expression of muscle-specific ubiquitin ligases Fbxo32 (Atrogin1, MAFbx) and Trim63 (MuRF-1). Dual-luciferase reporter gene experiments were conducted to validate the direct binding of miRNAs to their target genes. Local injection of hucMSCs and hucMSC-EXOs mitigated atrophy in the rat gastrocnemius muscle following sciatic nerve crush injury. In vitro, hucMSC-EXOs alleviated atrophy in L6 myotubes. Mechanistic analysis indicated the upregulation of miR-23b-3p levels in L6 myotubes following hucMSC-EXOs treatment. MiR-23b-3p significantly inhibited the expression of its target genes, Fbxo32 and Trim63, and suppressed myotube atrophy. Notably, an miR-23b-3p inhibitor reversed the inhibitory effect of miR-23b-3p on myotube atrophy in vitro. These results suggest that hucMSCs and their exosomes alleviate muscle atrophy following nerve injury. MiR-23b-3p in exosomes secreted by hucMSCs contributes to this mechanism by inhibiting the muscle-specific ubiquitination ligases Fbxo32 and Trim63. [ABSTRACT FROM AUTHOR]

Increasing porosity is one of the most direct ways to improve the thermal insulation and dielectric properties of materials. Until now, many wet methods for preparing Si3N4 ceramic foams usually face the problems of complex rheology, long period, and expensive cost, and the reported pore sizes of Si3N4 ceramic foams are typically micron-grade, resulting in a lack of competitiveness in thermal insulation and wave-transparent applications. In this paper, the Si3N4@SiO2 ceramic foams were prepared using an efficient dry-method, which combined three processes of low temperature chemical vapor deposition (LTCVD), template, and isostatic pressing. The method has the advantages of simple operation and short preparation period, and can realize near-net size molding and mass production. In addition, the evolution mechanisms of honeycomb microstructure and composition of Si3N4@SiO2 ceramic foam during sintering were studied by chemical reaction thermodynamics. The as-prepared Si3N4@SiO2 ceramic foam possesses low density (0.377 g·cm−3), high compressive strength (7.5 MPa), low thermal conductivity (0.0808 W·m−1·K−1), and excellent dielectric properties (ε < 1.32, tan δ < 0.009) in the frequency range of 8–18 GHz, and its maximum working temperature in air can reach up to 1100 °C. It will be recommended to be applied in the interlayer of Si3N4 ceramic radome to improve its thermal insulation and electromagnetic wave transparency performances. [ABSTRACT FROM AUTHOR]

Simple Summary: The research of this paper can be applied in the compaction parameter prediction of soil-filling materials, which can significantly reduce the amount of laboratory work and improve the efficiency of optimizing design for soil resource utilization in engineering construction. Maximum Dry Density (MDD) and Optimum Moisture Content (OMC) are two important parameters of soil filling, which affect the soil stability and bearing capacity, and thus the reliability and durability of facilities such as highways and bridges. Therefore, it is important to make reasonable predictions of OMC and MDD. Four machine learning algorithms, namely, Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), and Extreme Gradient Boosting Tree (XGBoost), are adopted in this paper to establish MDD and OMC prediction models. After training and testing, the best models of the four algorithms are compared. The results show that, as an ensemble learning algorithm, XGBoost is the best model for predicting MDD and OMC, with an R2 of 0.9234 for OMC, and an R2 of 0.9098 for MDD. Finally, the feature importance analysis concludes that the plastic limit (PL) and the liquid limit (LL) are the two features that affect OMC and MDD the most. The prediction of soil compaction parameters using machine learning models, especially ensemble learning, can significantly reduce the amount of laboratory work and improve the efficiency of optimizing design for soil resource utilization in engineering construction. [ABSTRACT FROM AUTHOR]