Global Well-Posedness and Long Time Decay of Fractional Navier-Stokes Equations in Fourier-Besov Spaces

We study the Cauchy problem of the fractional Navier-Stokes equations in critical Fourier-Besov spaces FB˙p,q1-2β+3/p′. Some properties of Fourier-Besov spaces have been discussed, and we prove a general global well-posedness result which covers some recent works in classical Navier-Stokes equations. Particularly, our result is suitable for the critical case β=1/2. Moreover, we prove the long time decay of the global solutions in Fourier-Besov spaces

Nano-Porous Light-Emitting Silicon Chip as a Potential Biosensor Platform

Nano-porous silicon (PS) offers a potential platform for biosensors with benefits both in terms of light emission and the large functional surface area. A light emitting PS chip with a stable and functional surface was fabricated in our laboratory. When protein was deposited on it, the light emission was reduced in proportion to the protein concentration. Based on this property, we developed a rudimentary demonstration of a label-free sensor to detect bovine serum albumin (BSA). A serial concentration of BSA was applied to the light chip and the reduction in light emission was measured. The reduction of the light intensity was linearly related to the concentration of the BSA at concentrations below 10-5 M. The detection limit was 8×10-9 M

Highly Stable Garnet Fe2Mo3O12 Cathode Boosts the Lithium–Air Battery Performance Featuring a Polyhedral Framework and Cationic Vacancy Concentrated Surface

Lithium–air batteries (LABs), owing to their ultrahigh theoretical energy density, are recognized as one of the next-generation energy storage techniques. However, it remains a tricky problem to find highly active cathode catalyst operating within ambient air. In this contribution, a highly active Fe2Mo3O12 (FeMoO) garnet cathode catalyst for LABs is reported. The experimental and theoretical analysis demonstrate that the highly stable polyhedral framework, composed of FeO octahedrons and MO tetrahedrons, provides a highly effective air catalytic activity and long-term stability, and meanwhile keeps good structural stability. The FeMoO electrode delivers a cycle life of over 1800 h by applying a simple half-sealed condition in ambient air. It is found that surface-rich Fe vacancy can act as an O2 pump to accelerate the catalytic reaction. Furthermore, the FeMoO catalyst exhibits a superior catalytic capability for the decomposition of Li2CO3. H2O in the air can be regarded as the main contribution to the anode corrosion and the deterioration of LAB cells could be attributed to the formation of LiOH·H2O at the end of cycling. The present work provides in-depth insights to understand the catalytic mechanism in air and constitutes a conceptual breakthrough in catalyst design for efficient cell structure in practical LABs

Weighted Gene Co-expression Network Analysis for RNA-Sequencing Data of the Varicose Veins Transcriptome

ObjectiveVaricose veins are a common problem worldwide and can cause significant impairments in health-related quality of life, but the etiology and pathogenesis remain not well defined. This study aims to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes.MethodsWe harvested great saphenous veins (GSV) from patients who underwent coronary artery bypass grafting (CABG) and varicose veins from conventional stripping surgery. RNA-Sequencing (RNA-Seq) technique was used to obtain the complete transcriptomic data of both GSVs from CABG patients and varicose veins. Weighted Gene Co-expression network analysis (WGCNA) and further analyses were then carried out with the aim to elucidate transcriptomic regulations of varicose veins by detecting differentially expressed genes, pathways and regulator genes.ResultsFrom January 2015 to December 2016, 7 GSVs from CABG patients and 13 varicose veins were obtained. WGCNA identified 4 modules. In the brown module, gene ontology (GO) analysis showed that the biological processes were focused on response to stimulus, immune response and inflammatory response, etc. Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis showed that the biological processes were focused on cytokine-cytokine receptor interaction and TNF signaling pathway, etc. In the gray module, GO analysis showed that the biological processes were skeletal myofibril assembly related. The immunohistochemistry staining showed that the expression of ASC, Caspase-1 and NLRP3 were increased in GSVs from CABG patients compared with varicose veins. Histopathological analysis showed that in the varicose veins group, the thickness of vascular wall, tunica intima, tunica media and collagen/smooth muscle ratio were significantly increased, and that the elastic fiber/internal elastic lamina ratio was decreased.ConclusionThis study shows that there are clear differences in transcriptomic information between varicose veins and GSVs from CABG patients. Some inflammatory RNAs are down-regulated in varicose veins compared with GSVs from CABG patients. Skeletal myofibril assembly pathway may play a crucial role in the pathogenesis of varicose veins. Characterization of these RNAs may provide new targets for understanding varicose veins diagnosis, progression, and treatment

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

A new dynamic K-best SD algorithm for MIMO detection

Multiple Input Multiple Output (MIMO) system is considered as an unalterable technology in wireless communication for its advantages in the spectral efficiency. Among the detection algorithms, maximum likelihood (ML) detection can achieve the best bit error rate performance, but the computational complexity of ML detection is too huge to be acceptable. In order to solve this problem, numbers of algorithms have been proposed. The K-Best SD sphere decoding (K-Best SD) algorithm is one of them. As K increase, the K-Best SD algorithm will approach the bit error rate of ML detection. However, if the K is large, the computational complexity will be unacceptable. In this paper, we propose a modified K-Best SD algorithm, in which the difference between the partial Euclidean distance of best and second best solution at each level of the tree search can be used to calculate the dynamic K, which can reduce the computational complexity considerably with a negligible BER performance loss. ? 2014 IEEE.EICPCI-S(ISTP)