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Herein, oriented boron nitride (BN)/alumina (Al2O3)/polydimethylsiloxane (PDMS) composites were obtained by filler orientation due to the shear-inducing effect via 3-D printing. The oriented BN platelets acted as a rapid highway for heat transfer in the matrix and resulted in a significant increase in the thermal conductivity along the orientation direction. Extra addition of spherical Al2O3 enhanced the fillers networks and resulted in the dramatic growth of slurry viscosity. This, together with filler orientation induced the synergism and provided large increases in the thermal conductivity. A high orientation degree of 90.65% and in-plane thermal conductivity of 3.64 W/(m∙K) were realized in the composites with oriented 35 wt% BN and 30 wt% Al2O3 hybrid fillers. We attributed the influence of filler orientation and hybrid fillers on the thermal conductivity to the decrease of thermal interface resistance of composites and proposed possible theoretical models for the thermal conductivity enhancement mechanisms.

As a promising alternative anode material, silicon (Si) presents a larger capacity than the commercial anode to achieve large capacity lithium-ion batteries. However, the application of pure Si as anode is hampered by limitations such as volume expansion, low conductivity and unstable solid electrolyte interphase. To break through these limitations, the core-shell Si@Li4Ti5O12 nanocomposite, which was prepared via in-situ self-assembly reaction and decompressive boiling fast concentration method, was proposed in this work. This anode combines the advantages of nano-sized Si particle and pure Li4Ti5O12 (LTO) coating layer, improving the performance of the lithium-ion batteries. The Si@Li4Ti5O12 anode displays a high initial discharge/charge specific capacity of 1756/1383 mAh g−1 at 500 mA g−1 (representing high initial coulombic efficiency of 78.8%), a large rate capability (specific capacity of 620 mAh g−1 at 4000 mA g−1), an outstanding cycling stability (reversible specific capacity of 883 mAh g−1 after 150 cycles) and a low volume expansion rate (only 3.3% after 150 cycles). Moreover, the synthesis process shows the merits of efficiency, simplicity, and economy, providing a reliable method to fabricate large capacity Si@Li4Ti5O12 nanocomposite anode materials for practical lithium-ion batteries.

Smart activity sensing has gained more and more attention with the development of sensing devices and recognition techniques. For multi-modal sensing scenarios like smart home, fusing results of multiple models brings opportunities to achieve more comprehensive and accurate recognition, as well as challenges to coordinate a collection of models under strict resource limitations. In this paper, we firstly model the multi-modal sensing problem with strict orthogonal resource constraints. Then, for scenarios with fixed and changeable resource limitations, we propose two online decision methods correspondingly to optimize recognition accuracy through dynamically selecting models and fusing their predictions, given a pre-trained model library. Specifically, by utilizing reward feedback based on an actor-critic scheme, we deal with fixed resources and accuracy optimization in one shot. Furthermore, for changeable resources, we decouple resource allocation and model evaluation to support model portability with comparable accuracy. Three types of sensing devices and nine recognition models have been investigated in our work. Experiments show that our method improves the recognition accuracy compared to that achieved by a single-modality model, and also achieves higher accuracy with less resource costs compared to the end-to-end multi-modal model.

Apoptosis of gastric mucosa epithelial cells caused by the abuse of alcohol produces injury to the gastric mucosa and acute or chronic gastritis. In recent years, it has been demonstrated that endoplasmic reticulum stress (ERS) is involved in mediating apoptosis, and that autophagy has a protective effect on survival of cells. Rebamipide is a gastric mucosal protectant used to treat gastritis and stomach ulcers. In this study, ethanol was used to overstimulate gastric mucosal epithelial cells and gavage mice. It was found that 400 mmol/L ethanol overstimulation could activate ERS and induce apoptosis (control vs ethanol treatment: 15.24 ± 1.10% vs 33.80 ± 1.47%, P 0.001); but could not activate the autophagy pathway. Rebamipide intervention can reduce apoptosis rate (20.78 ± 1.63%), and significantly inhibit the activation of ERS and the active ERS-related downstream NF-κB signaling pathway. Additionally, rebamipide can activate the expression of autophagy-related pathway proteins and increase the expression of p-ERK and p-p38. In addition, rebamipide relieved oxidative stress after an ethanol insult. In the present study, molecular evidence of rebamipide inhibition of ERS and regulation of the protein expression of autophagy pathway components were produced using an acute alcoholic gastric mucosal injury model. This model provides a new approach for investigating the effects of rebamipide treatment on alcohol-induced gastric mucosal damage.

The combination of various fillers can improve the thermal conductivity of polymer composites, because an efficient heat conduction network synergistically formed in matrix. The synergistic effect of two fillers, carbon fiber and alumina particle, in polydimethylsiloxane (PDMS) is investigated in this work. A filler combination results in higher thermally conductive composite than any of the single filler. The volume ratio of 4:1 shows the greatest thermal conductivity. The thermal conductivity of PDMS composite filled with 24 vol% carbon fiber and 6 vol% alumina reaches 7.91 W m−1K−1, which was 34% higher than that of 30 vol% CF/PDMS. The combined filler composite also shown better process performance due to the lower viscosity. The synergy is attributed to the optimized heat transfer network and reduced interfacial thermal resistance. Therefore, a combined filler achieved better thermally conductive performance and better process performance with cost-effective source materials.

One of the major challenges for fully enjoying the power of machine learning is the need for the high-quality labelled data. To tap-in the gold-mine of data generated by IoT devices with unprecedented volume and value, we discover and leverage the hidden connections among the multimodal data collected by various sensing devices. Different modal data can complete and learn from each other, but it is challenging to fuse multimodal data without knowing their perception (and thus the correct labels). In this work, we propose MultiSense, a paradigm for automatically mining potential perception, cross-labelling each modal data, and then improving the learning models over the set of multimodal data. We design innovative solutions for segmenting, aligning, and fusing multimodal data from different sensors. We implement our framework and conduct comprehensive evaluations on a rich set of data. Our results demonstrate that MultiSense significantly improves the data usability and the power of the learning models.

In this work, we report a fabrication of oriented carbon fibres/alumina/silicon rubber composites by 3-D printing. The 3-D printed composites possess higher thermal conductivity up to 7.36 W/m K at 12 vol% CFs and 30 vol% alumina loading than that of cast composites (4.22 W/m K) at the same components. The orientation caused by 3-D printing produces a synergism of the thermal conductivity enhancement for CFs and alumina hybrid filled composites. We attribute the synergism to the decrease of thermal interface resistance, while the reduction of thermal interface resistance has a bigger effect on thermal conductivity of CASR composites. This study provides a novel way to obtain thermal conductive composites with orientation, which has a great significance for the development of high-performance thermal conductive products.

BackgroundThe mechanisms of macrophages/monocytes in autoimmune hepatitis (AIH) remain unclear. We investigated the role of receptor-interacting protein kinase 3 (RIP3), a key inflammatory signal a...