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This study investigates the confined foaming mechanisms and passive cooling performance of Micro-/Nano-Layered (MNL) film/foam alternating structures. These structures consist of solid poly(carbonate) (PC) film layers and foamed poly(methyl methacrylate) (PMMA) layers. We examine the impact of confinement effects, layer thicknesses, and foaming conditions on cell morphology, cell nucleation, growth, and bulk expansion behavior. Samples ranging from 1 to 513 layers were foamed at 20 MPa and temperatures between 70 and 150°C. We identified three distinct cell structures—multiple, double, or single row(s) of cells—in MNL film/foam structures. We observed that cell size decreases and cell nucleation density increases with increasing layer count. The highest cell nucleation density (1.1×1013cells/cm3) and smallest cell size (400 nm) were achieved in a 513-layer sample foamed at 70°C and 20 MPa. MNL samples primarily expand vertically, with the apparent expansion ratio ranging from 2.3 to 11 times as layers increase. Samples with double or single row(s) of cells exhibited tensile strengths (∼30 MPa) comparable to their solid counterparts and thermal conductivities (29.7 mW/m·K) comparable to air. Our samples exhibited high solar radiation reflection (93.5 %) and strong infrared emissivity (91.2 %) in the atmospheric transparent window. Mid-day passive cooling experiments showed an average temperature of 17.7°C lower under our sample than ambient conditions. Given these combined properties and the cost-effective nature of the manufacturing method, our samples are readily applicable for building applications, offering significant energy savings and contributing to the mitigation of global warming.

Nowadays, source camera identification, which aims to identify the source camera of images, is quite important in the field of forensics. There is a problem that cannot be ignored that the existing methods are unreliable and even out of work in the case of the small training sample. To solve this problem, a virtual sample generation-based method is proposed in this paper, combined with the ensemble learning. In this paper, after constructing sub-sets of LBP features, the authors generate a virtual sample-based on the mega-trend-diffusion (MTD) method, which calculates the diffusion range of samples according to the trend diffusion theory, and then randomly generates virtual sample according to uniform distribution within this range. In the aspect of the classifier, an ensemble learning scheme is proposed to train multiple SVM-based classifiers to improve the accuracy of image source identification. The experimental results demonstrate that the proposed method achieves higher average accuracy than the state-of-the-art, which uses a small number of samples as the training sample set.

Aberrant differentiations of bone mesenchymal stem cells (BMSCs) have proved to be associated with the occurrence of senile osteoporosis. However, mechanisms of this phenomenon relative to abnormal lipid metabolism remain unclear. This study was conducted to characterize the lipidomics alterations during BMSC passaging, aiming at uncovering the aging-related lipid metabolism that may play an important role in aberrant differentiations of BMSCs. Principal component analysis presented the sequential lipidomics alterations during BMSC passaging. The majority of glycerophospholipids, including phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerols, as well as sphingolipids, revealed significant elevations, whereas the others, including phosphatidic acids, phosphatidylinositols, and phosphatidylserines, presented decreases in aged cells. Double-bond equivalent versus carbon number plots demonstrated that the changing trends and significances of lipids during passaging were associated with the chain length and the degree of unsaturation. In the correlation networks, the scattering patterns of lipid categories suggested the category-related metabolic independence and potential conversion among phosphatidic acids, phosphatidylinositols, and phosphatidylserines. The lipid–enzyme integrated pathway analysis indicated the activated metabolic conversion from phosphatidic acids to CDP-diacylglycerol to phosphatidylinositols and from sphingosine to ceramides to sphingomyelins with BMSC passaging. The conversions among lipid species described the lipidomics responses that potentially induced the aberrant differentiations during BMSC aging.