Nacre-Inspired,Liquid Metal-Based Ultrasensitive Electronic Skin by Spatially Regulated Cracking Strategy

The realization of liquid metal-based wearable systems will be a milestone toward high-performance, integrated electronic skin. However, despite the revolutionary progress achieved in many other components of electronic skin, liquid metal-based flexible sensors still suffer from poor sensitivity due to the insufficient resistance change of liquid metal to deformation. Herein, a nacre-inspired architecture composed of a biphasic pattern (liquid metal with Cr/Cu underlayer) as “bricks” and strain-sensitive Ag film as “mortar” is developed, which breaks the long-standing sensitivity bottleneck of liquid metal-based electronic skin. With 2 orders of magnitude of sensitivity amplification while maintaining wide (>85%) working range, for the first time, liquid metal-based strain sensors rival the state-of-art counterparts. This liquid metal composite features spatially regulated cracking behavior. On the one hand, hard Cr cells locally modulate the strain distribution, which avoids premature cut-through cracks and prolongs the defect propagation in the adjacent Ag film. On the other hand, the separated liquid metal cells prevent unfavorable continuous liquid-metal paths and create crack-free regions during strain. Demonstrated in diverse scenarios, the proposed design concept may spark more applications of ultrasensitive liquid metal-based electronic skins, and reveals a pathway for sensor development via crack engineering.     

Synthesis of nanopowders with low agglomeration by elaborating Φ values for producing Gd2O3-MgO nanocomposites with extremely fine grain sizes and high mid-infrared transparency

Refining ceramic microstructures to the nanometric range to minimize light scattering provides an interesting methodology for developing novel optical ceramic materials. In this work, we reported the fabrication and properties of a new nanocomposite optical ceramic of Gd₂O₃-MgO. The citric acid sol-gel combustion method was adopted to fabricate Gd₂O₃-MgO nanocomposites with fine-grain sizes, dense microstructures and homogeneous phase domains. Nanopowders with low agglomeration and improved sinterability can be obtained by elaborating Φ values. Further refining of the microstructure of the nanocomposites was achieved by elaborating the hot-pressing conditions. The sample sintered at 65 MPa and 1300 °C showed a quite high hardness value of 14.3 ± 0.2 GPa, a high transmittance of 80.3 %–84.7 % over the 3?6 μm wavelength range, due mainly to its extremely fine-grain size of Gd₂O₃ and MgO (93 and 78 nm, respectively) and high density.     

Magnetically Guidable Proteinaceous Adhesive Microbots for Targeted Locoregional Therapeutics Delivery in the Highly Dynamic Environment of the Esophagus

The esophagus is a tubular-shaped muscular organ where swallowed fluids and muscular contractions constitute a highly dynamic environment. The turbulent, coordinated processes that occur through the oropharyngeal conduit can often compromise targeted administration of therapeutic drugs to a lesion, significantly reducing therapeutic efficacy. Here, magnetically guidable drug vehicles capable of strongly adhering to target sites using a bioengineered mussel adhesive protein (MAP) to achieve localized delivery of therapeutic drugs against the hydrodynamic physiological conditions are proposed. A suite of highly uniform microparticles embedded with iron oxide (IO) nanoparticles (MAP@IO MPs) is microfluidically fabricated using the genipin-mediated covalent cross-linking of bioengineered MAP. The MAP@IO MPs are successfully targeted to a specific region and prolongedly retained in the tubular-structured passageway. In particular, orally administered MAP@IO MPs are effectively captured in the esophagus in vivo in a magnetically guidable manner. Moreover, doxorubicin (DOX)-loaded MAP@IO MPs exhibit a sustainable DOX release profile, effective anticancer therapeutic activity, and excellent biocompatibility. Thus, the magnetically guidable locomotion and robust underwater adhesive properties of the proteinaceous soft microbots can provide an intelligent modular approach for targeted locoregional therapeutics delivery to a specific lesion site in dynamic fluid-associated tubular organs such as the esophagus.     

A Case Report of Germline Compound Heterozygous Mutations in the BRCA1 Gene of an Ovarian and Breast Cancer Patient

The germline carrier of the BRCA1 pathogenic mutation has been well proven to confer an increased risk of breast and ovarian cancer. Despite BRCA1 biallelic pathogenic mutations being extremely rare, they have been reported to be embryonically lethal or to cause Fanconi anemia (FA). Here we describe a patient who was a 48-year-old female identified with biallelic pathogenic mutations of the BRCA1 gene, with no or very subtle FA-features. She was diagnosed with ovarian cancer and breast cancer at the ages of 43 and 44 and had a strong family history of breast and gynecological cancers.     

Highly Efficient Zirconium Based Carbonaceous Solid Acid Catalyst for Selective Synthesis of 5-HMF from Fructose and Glucose in Isopropanol as a Solvent

Catalysis Letters - A new zirconium based carbonaceous solid acid catalyst Zr@CC-PA with both Lewis and Bronsted acidic sites was prepared by simultaneous carbonization and phosphonation of glucose...     

Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Material encapsulation in poly(methyl methacrylate) shell: A review

Material encapsulation is a relatively new technique for coating a micro/nanosize particle or droplet with polymeric or inorganic shell. Encapsulation technology has many applications in various fields including drug delivery, cosmetic, agriculture, thermal energy storage, textile, and self-healing polymers. Poly(methyl methacrylate) (PMMA) is widely used as shell material in encapsulation due to its high chemical stability, biocompatibility, nontoxicity, and good mechanical properties. The main approach for micro/nanoencapsulation of materials using PMMA as shell comprises emulsion-based techniques such as emulsion polymerization and solvent evaporation from oil-in-water emulsion. In the present review, we first focus on the encapsulation techniques of liquid materials with PMMA shell by analyzing the effective processing parameters influencing the preparation of PMMA micro/nanocapsules. We then describe the morphology of PMMA capsules in emulsion systems according to thermodynamic relations. The techniques to investigation of mechanical properties of capsule shell and the release mechanisms of core material from PMMA capsules were also investigated. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48039.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.