Electrical Transport Properties of Multilayered Single-Walled Carbon Nanotube Films

An improved layer-by-layer vacuum filtration method was adopted for the fabrication of single-walled carbon nanotube (SWCNT) films aiming at a series of SWCNT films with controllable thickness and density. The electrical transport properties of the multilayered SWCNT films have been investigated. With the constant film density, the decrease of the layer number of the SWCNT film results in an increase of the temperature coefficient of resistance (TCR). SWCNT film with 95% metallic nanotubes has shown a lower TCR than that of the SWCNT films with a low percentage of metallic nanotubes. The effect of thermal annealing and subsequent acid (HNO3) treatment on the electrical properties of the SWCNT films has also been investigated

A deep-neural-network-based hybrid method for semi-supervised classification of polarimetric SAR data

This paper proposes a deep-neural-network-based semi-supervised method for polarimetric synthetic aperture radar (PolSAR) data classification. The proposed method focuses on achieving a well-trained deep neural network (DNN) when the amount of the labeled samples is limited. In the proposed method, the probability vectors, where each entry indicates the probability of a sample associated with a category, are first evaluated for the unlabeled samples, leading to an augmented training set. With this augmented training set, the parameters in the DNN are learned by solving the optimization problem, where the log-likelihood cost function and the class probability vectors are used. To alleviate the “salt-and-pepper” appearance in the classification results of PolSAR images, the spatial interdependencies are incorporated by introducing a Markov random field (MRF) prior in the prediction step. The experimental results on two realistic PolSAR images demonstrate that the proposed method effectively incorporates the spatial interdependencies and achieves the good classification accuracy with a limited number of labeled samples

Quorum sensing LuxS/autoinducer-2 inhibits Enterococcus faecalis biofilm formation ability

Objective:  To investigate the relation between biofilm formation ability and quorum sensing gene LuxS/AI-2. Materials and Methods: Enterococcus faecalis (E. faecalis) standard strain ATCC 29212 was used in the study. Long flanking homology polymerase chain reaction method was used to build the LuxS gene knockout strain. Sequential culture turbidity measurement and CFU counting were used to assess the proliferation ability of E. faecalis after the depletion of LuxS. 96-well plate assay was used to quantify the biofilm formation ability; CLSM was used to observe the attached bacteria areas, while scanning electron microscopy (SEM) was performed to observe biofilm microstructure conditions. Results: LuxS gene knockout strains were successfully constructed and identified. The results showed that proliferation ability of E. faecalis was not affected by the depletion of the luxS gene, and the biofilm formation ability of ΔLuxS 29212 significantly decreased (P<0.05). Conclusions: Collectively, our studies provide the LuxS gene's key role in controlling biofilm formation of E. faecalis, which presented a negative regulation, and furthermore, providing us a possible way to conquer the persistent apical periodontitis

CD44ICD promotes breast cancer stemness via PFKFB4-mediated glucose metabolism.

CD44 is a single-pass cell surface glycoprotein that is distinguished as the first molecule used to identify cancer stem cells in solid tumors based on its expression. In this regard, the CD44high cell population demonstrates not only the ability to regenerate a heterogeneous tumor, but also the ability to self-regenerate when transplanted into immune-deficient mice. However, the exact role of CD44 in cancer stem cells remains unclear in part because CD44 exists in various isoforms due to alternative splicing. Methods: Gain- and loss-of-function methods in different models were used to investigate the effects of CD44 on breast cancer stemness. Cancer stemness was analyzed by detecting SOX2, OCT4 and NANOG expression, ALDH activity, side population (SP) and sphere formation. Glucose consumption, lactate secretion and reactive oxygen species (ROS) levels were detected to assess glycolysis. Western blot, immunohistochemical staining, ELISA and TCGA dataset analysis were performed to determine the association of CD44ICD and PFKFB4 with clinical cases. A PFKFB4 inhibitor, 5MPN, was used in a xenograft model to inhibit breast cancer development. Results: In this report, we found that the shortest CD44 isoform (CD44s) inhibits breast cancer stemness, whereas the cleaved product of CD44 (CD44ICD) promotes breast cancer stemness. Furthermore, CD44ICD interacts with CREB and binds to the promoter region of PFKFB4, thereby regulating PFKFB4 transcription and expression. The resultant PFKFB4 expression facilitates the glycolysis pathway (vis-à-vis oxidative phosphorylation) and promotes stemness of breast cancer. In addition, we found that CD44ICD and PFKFB4 expressions are generally up-regulated in the tumor portion of breast cancer patient samples. Most importantly, we found that 5MPN (a selective inhibitor of PFKFB4) suppresses CD44ICD-induced tumor development. Conclusion: CD44ICD promotes breast cancer stemness via PFKFB4-mediated glycolysis, and therapies that target PFKFB4 (e.g., 5MPN therapy) may lead to improved outcomes for cancer patients

Designing leakage-resilient password entry on head-mounted smart wearable glass devices

AXA Research Fun

Solvothermal Synthesis, Structure and Optical Property of Nanosized CoSb3 Skutterudite

Binary skutterudite CoSb3 nanoparticles were synthesized by solvothermal method. The nanostructuring of CoSb3 material was achieved by the inclusion of various kinds of additives. X-ray diffraction examination indicated the formation of the cubic phase of CoSb3. Structural analysis by transmission electron microscopy analysis further confirmed the formation of crystalline CoSb3 nanoparticles with high purity. With the assistance of additives, CoSb3 nanoparticles with size as small as 10 nm were obtained. The effect of the nanostructure of CoSb3 on the UV–visible absorption and luminescence was studied. The nanosized CoSb3 skutterudite may find application in developing thermoelectric devices with better efficiency

Solvothermal Synthesis, Structure and Optical Property of Nanosized CoSb3 Skutterudite

Binary skutterudite CoSb3 nanoparticles were synthesized by solvothermal method. The nanostructuring of CoSb3 material was achieved by the inclusion of various kinds of additives. X-ray diffraction examination indicated the formation of the cubic phase of CoSb3. Structural analysis by transmission electron microscopy analysis further confirmed the formation of crystalline CoSb3 nanoparticles with high purity. With the assistance of additives, CoSb3nanoparticles with size as small as 10 nm were obtained. The effect of the nanostructure of CoSb3on the UV–visible absorption and luminescence was studied. The nanosized CoSb3 skutterudite may find application in developing thermoelectric devices with better efficiency.

Semi-supervised classification of polarimetric SAR images using Markov random field and two-level Wishart mixture model

In this work, we propose a semi-supervised method for classification of polarimetric synthetic aperture radar (PolSAR) images. In the proposed method, a 2-level mixture model is constructed by associating each component density with a unique Wishart mixture model (instead of a single Wishart distribution as that in the conventional Wishart mixture model). This modeling scheme facilitates the accurate description of data for the categories, each of which includes multiple subcategories. The learning algorithm for the proposed model is developed based on variational inference and all the update equations are obtained in closed form. In the learning algorithm, the spatial interdependencies are incorporated by imposing a Markov random field prior on the indicator variable to alleviate the speckle effect on the classification results. The experimental results demonstrate the improved performance of the proposed method compared with the unsupervised version and supervised version of the proposed model as well as an existing method for semi-supervised classification