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Core-shell-structured La0.8Sr0.2Co0.2Fe0.8O3-δ@Gd0.2Ce0.8O1.9 (LSCF@GDC) composite materials are synthesized and sintered as the SOFC cathodes by screen-printing method. The durability of core-shell-structured LSCF@GDC composite cathodes are evaluated through constant current polarizations (CCP) process at 750 °C and the results indicate that the core-shell-structured LSCF@GDC composite cathode (nanorod, 0.6) possesses an excellent long-term stability. In addition, molecular dynamics (MD) model is developed and applied to simulate the interaction between LSCF and GDC particles. According to the simulation results, compressive stress is generated at the cathode-electrolyte interface by the coated GDC layer. Combining with the X-ray diffraction (XRD) refinement results, it's revealed that the lattice strains are introduced in LSCF lattices because of the compressive stress. Furthermore, XPS results show that the core-shell-structured LSCF@GDC composite cathode (nanorod, 0.6) possess a better inhibition ability for Sr surface segregation. This study provides a possible way to suppress Sr surface segregation.

Oxaliplatin is a promising antitumor drug, but its effectiveness is limited by its side effects in vivo. In this study, we introduced an Oxaliplatin prodrug (Oxa(IV)) self-controlled release strategy, in which Oxa(IV) is encapsulated by TPGS functionalized mesoporous silica nanoparticles (MSNs), and its release is controlled by biological stimuli, such as acidic environments in tumor tissue and high concentrations of reductants in cancer cells. Despite the lack of auxiliary "gatekeepers" to MSNs, this simplified model of Oxa(IV)-MSNs-TPGS could fine-tune the movements of the drug release. Furthermore, we utilized a prodrug approach to avoid the side effects of Oxaliplatin, and we used TPGS groups to reduce multidrug resistance (MDR). Finally, the toxicity of Oxa(IV)-MSNs-TPGS to a human lung adenocarcinoma cell line (A549) in vitro was significantly lower than that of Oxaliplatin. This model demonstrates the considerable potential of a simple self-controlled release system with multiple functions.

In this study, we introduced a targeting polymer poly(ethylene glycol)–folic acid (PEG–FA) on the surface of polydopamine (PDA)-modified mesoporous silica nanoparticles (MSNs) to develop the novel nanoparticles (NPs) MSNs@PDA–PEG–FA, which were employed as a drug delivery system loaded with doxorubicin (DOX) as a model drug for cervical cancer therapy. The chemical structure and properties of these NPs were characterized by transmission electron microscopy, X-ray photoelectron spectroscopy, N2 adsorption/desorption, dynamic light scattering-autosizer, thermogravimetric analysis, and Fourier transform infrared spectroscopy. The pH-sensitive PDA coating served as a gatekeeper. The in vitro drug release experiments showed pH-dependent and sustained drug release profiles that could enhance the therapeutic anticancer effect and minimize potential damage to normal cells due to the acidic microenvironment of the tumor. These MSNs@PDA–PEG–FA achieved significantly high targeting efficiency, which was demonstrated...

Lithium-ion batteries are widely used in electric vehicles (EVs) and hybrid electric vehicles (HEVs), in which proper measures have to be taken to ensure the batteries working with in a suitable temperature range. The air-cooling battery thermal management system (BTMS) is still a widely used solution for this purpose. Based on modeling and numerical simulation method, this paper aims to analyze and improve the cooling effect of the battery cells by optimizing the airflow configuration and layout employed in the U-type air-cooling BTMS. It is found that, for eighteen selected designs in the current study, the best cooling performance can be achieved when the number of both inlet and outlet manifolds is increased to be three. Further analysis is also carried out for the obtained optimum design to confirm its applicability in a wider range of total inlet airflow rates and temperatures.

Using facile polydopamine (PDA)-based surface modification and a pH-sensitive catechol-boronate binding mechanism, a novel drug delivery system was designed for the treatment of breast cancer. The system was able to achieve the following goals: active targeting, pH responsiveness, in vivo blood circulation for a prolonged period of time, and dual drug loading. After coating with PDA, the docetaxel (DTX)-loaded star-shaped copolymer cholic acid-poly(lactide-co-glycolide) nanoparticles (CA-PLGA@PDA/NPs) were functionalized with amino-poly(ethylene glycol)-folic acid (NH2-PEG-FA) and bortezomib (BTZ) to form the targeting composition, DTX-loaded CA-PLGA@PDA-PEG-FA + BTZ/NPs. The novel NPs exhibited similar drug release characteristics compared to unfunctionalized CA-PLGA/NPs. Meanwhile, the incorporated NH2-PEG-FA contributed to active targeting which was illustrated by cellular uptake experiments and biodistribution studies. Moreover, the pH responsive binding between BTZ and PDA was demonstrated to be effective to release BTZ at the tumor acidic environment for synergistic action with DTX. Both in vitro cytotoxicity and in vivo antitumor studies demonstrated that the novel nanoplatform exhibited the most suitable therapeutic effects. Taken together, the versatile PDA modified DTX-loaded CA-PLGA@PDA-PEG-FA + BTZ/NPs offered a promising chemotherapeutic strategy for enhancing breast cancer treatment.

The design of multifunctional nanocarriers for the co-delivery of anticancer drugs and genetic agents offers an effective and promising strategy to combat multidrug-resistant cancer. Herein, we developed a simple and facile method to fabricate a drug-self-gated and pH-sensitive mesoporous silica vehicle as a "four-in-one" versatile co-delivery system, which possesses targeted chemo and gene therapy capability against multidrug-resistant cancer. P-gp siRNA molecules were loaded into the channels of mesoporous silica nanoparticles. A chemotherapeutic drug (DOX) was employed as a gatekeeper via a pH-sensitive benzoic-imine covalent bond. Folic acid conjugation onto the surface endowed this system with an excellent tumor-targeting effect, which was demonstrated by the cellular and tumor targeting assay. The effective downregulation of P-gp protein by the co-delivered P-gp siRNA was observed by western blotting. Both the in vitro cell viability study and in vivo tumor inhibition assay showed a synergistic effect in suppressing cancer cell proliferation. Therefore, this drug-self-gated nanosystem exhibited great potential for improved multidrug-resistant cancer treatment without any further potential risks of capping agents.

Reversible solid oxide fuel cell (rSOFC) can produce and store energy through dual-mode operating, which is promising for balancing the conflicts between power supply and requirements. One crucial issue is to develop high performance of fuel electrode materials, in terms of materials costs, mechanical strength, mass production in commercialization. The reversible performance of the materials may be enhanced by electrode microstructure optimization in the preparation procedures. It is beneficial to understand the mechanisms of sintering process, in terms of the electrode particle interactions and sintered structure in the molecular/nanoparticle level. Accordingly, a molecular dynamics method is developed to simulate the sintering process for the LST/GDC nanoparticle systems. It is found that a high sintering temperature is beneficial for increasing triple-phase-boundary (TPB) length, but not for the effective surface area of catalyst particles. A mass fraction of 0.5–0.6 is predicted as the optimal LST composition for the TPB length, active surface area, and compatible thermal expansion coefficient. The heat capacity and thermal conductivity increase in the high sintering temperature and high mass fraction of LST conditions. The methodology and findings can provide a guideline on optimization of the sintering conditions for LST/GDC electrodes, which may promote the commercialization of rSOFC technology.

The integration of various therapy strategies into a single nanoplatform for synergistic cancer treatment has presented a great prospect. Herein, docetaxel (DTX)-loaded poly lactic-co-glycolic acid (PLGA)-coated polydopamine modified with d-α-tocopherol polyethylene glycol 1000 succinate (TPGS) was synthesized for chemo-photothermal synergistic therapy against cancer. Firstly, the DTX-loaded PLGA NPs were prepared by a facile and robust nanoprecipitation method. Then, they were coated with dopamine to achieve the photothermal effects and to be further modified with TPGS, which can inhibit the P-glycoprotein-mediated multidrug resistance (MDR). The near-infrared (NIR) laser irradiation triggered DTX release from DTX-loaded PLGA NPs@PDA-TPGS, and then the chemo-photothermal therapy effect could be enhanced. The in vitro experimental results illustrated that DTX-loaded PLGA NPs@PDA-TPGS exhibits excellent photothermal conservation properties and remarkable cell-killing efficiency. In vivo antitumor studies further confirmed that DTX-loaded PLGA NPs@PDA-TPGS could present an outstanding synergistic antitumor efficacy compared with any monotherapy. This work exhibits a novel nanoplatform, which could not only load chemotherapy drugs efficiently, but could also improve the therapeutic effect of chemotherapy drugs by overcoming MDR and light-mediated photothermal cancer therapy.

In this paper we propose a multi-view method to recognize hand gestures using point cloud. The main idea of this paper is to project point cloud into view images and hand gestures are described by extracting and fusing features in view images. The conversion of feature space increases the inner-class similarity and meanwhile reduces the inter-class similarity. The features of view images are extracted in parallel so the scale of each feature extractor can be reduced to converge easily. In our method we perform a refined hand segmentation to segment hand form background firstly. Then the segmented hand point cloud is projected into different view planes to form view images. Next we use convolutional neural networks as feature extractors to extract features of view images. The extracted view image features are fused to form the features of hand gestures. Finally a SVM is trained for hand gesture recognition. The experimental results show that our multiview method achieves higher recognition rate and more robust to the challenging rotation changes especially out-plane rotations.

Twenty-two species shorebirds were recorded on mangrove wetlands surrounding Leizhou Peninsula, Guangdong Province, China. One recorded species, Spoon-billed Sandpiper (Eurynorhynchus pygmeus), is listed as endangered in the IUCN Red List (World Conservation Union) and this was the first record of the species at Leizhou in this study. Most recorded species are listed in the Sino-Japan or Sino-Australia Agreement on Conservation of Migratory Birds. Dunlin (Calidris alpina), Kentish Plover (Charadrius alexandrinus), and Greater Sand Plover (Charadrius leschenaultii) were dominant, accounting for 34%, 32%, and 12% of total individuals, respectively. Five survey sites were designated by habitat type. There was no significant difference in species, but total abundance differed significantly among survey sites. More species were recorded in winter and spring than in summer. One hundred and sixty-five species of benthos were recorded. Total mean biomass and density of benthos was 223.3 ± 74.8 g/m2 (±S.E.), density 210.97 ± 67.6 ind./m2, respectively. Mollusks accounted for 83.4% of total biomass, and 75.6% of total density. Both biomass and density of benthos varied significantly among survey sites. There was no significant difference between spring and autumn on biomass or density of benthos. There was a significant and negative correlation between number of shorebirds and densities of polychaetes on mudflats. Shorebird species richness (F1,3 = 13.14, p = 0.036) and abundance (F1,3 = 12.59, p = 0.037) were significantly and positively correlated with mudflat area. Stopping losses of mangrove habitat and tidal flats is the top priority measure for shorebird conservation. Reducing the impacts of human disturbance on both habitats and birds is an urgent necessity for mangrove wetland conservation management.

In this paper we propose a novel method to detect fingertip using depth data. The first step of our method is to segment hand from depth map precisely. Then a two layer hand model is constructed to detect self-occlusion and mitigate its impact. In the next step an extended graph model of hand is built to locate and label finger bases. Then we generate heat maps of finger bases to detect finger regions even fingers are closed or adhesion occurs. Finally fingertips are located on fingers by geodesic paths. Experiments on different finger motions and hand rotations show that our framework performs accurately when hand pose and rotation change. Compared with other approaches our method shows less errors and robust to depth noise.