251 research outputs found

    Static and Dynamic Analysis of Piezoelectric Laminated Composite Beams and Plates

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    In this chapter, the mechanical behavior analysis of piezoelectric laminated composite beams and plates is influenced subjected to static, dynamic, and aerodynamic loads. Algorithm for dynamic, stability problem analysis and vibration control of laminated composite beams and plates with piezoelectric layers is presented. In addition, numerical calculations, considering the effect of factors on static, dynamic, and stability response of piezoelectric laminated composite beams and plates are also clearly presented. The content of this chapter can equip readers with the knowledge used to calculate the static, dynamic, and vibration control of composite beams, panels made of piezoelectric layers applied in the field different techniques

    Investigation of Sodium Manganese Oxide Nanowires Synthesized by Hydrothermal Method for Alkaline Ion Battery

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    Sodium Manganese Oxide (NaxMnO2) has attracted much attention as cathode materials for alkaline ion battery due to the ability of fast charge and discharge ion Na+, in particular in nanoscale. We report on the synthesis of NaxMnO2 nanowires via hydrothermal synthesis route from Mn2O3 and NaOH solution. The morphological observation indicates that the obtained Na0.44MnO2 nanowires with diameters of about 20-30 nm, length up to several micrometers were formed by this process. The electrochemical properties of fabricated materials were investigated by means of cyclic voltammetry technique and show that Sodium Manganese Oxide (NaxMnO2) is a promising material in the field of research and fabrication alkaline ion battery

    Two plant-associated Bacillus velezensis strains selected after genome analysis, metabolite profiling, and with proved biocontrol potential, were enhancing harvest yield of coffee and black pepper in large field trials

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    Elimination of chemically synthesized pesticides, such as fungicides and nematicides, in agricultural products is a key to successful practice of the Vietnamese agriculture. We describe here the route for developing successful biostimulants based on members of the Bacillus subtilis species complex. A number of endospore-forming Gram-positive bacterial strains with antagonistic action against plant pathogens were isolated from Vietnamese crop plants. Based on their draft genome sequence, thirty of them were assigned to the Bacillus subtilis species complex. Most of them were assigned to the species Bacillus velezensis. Whole genome sequencing of strains BT2.4 and BP1.2A corroborated their close relatedness to B. velezensis FZB42, the model strain for Gram-positive plant growth-promoting bacteria. Genome mining revealed that at least 15 natural product biosynthesis gene clusters (BGCs) are well conserved in all B. velezensis strains. In total, 36 different BGCs were identified in the genomes of the strains representing B. velezensis, B. subtilis, Bacillus tequilensis, and Bacillus. altitudinis. In vitro and in vivo assays demonstrated the potential of the B. velezensis strains to enhance plant growth and to suppress phytopathogenic fungi and nematodes. Due to their promising potential to stimulate plant growth and to support plant health, the B. velezensis strains TL7 and S1 were selected as starting material for the development of novel biostimulants, and biocontrol agents efficient in protecting the important Vietnamese crop plants black pepper and coffee against phytopathogens. The results of the large-scale field trials performed in the Central Highlands in Vietnam corroborated that TL7 and S1 are efficient in stimulating plant growth and protecting plant health in large-scale applications. It was shown that treatment with both bioformulations resulted in prevention of the pathogenic pressure exerted by nematodes, fungi, and oomycetes, and increased harvest yield in coffee, and pepper.Peer Reviewe

    Prototyping of DSSDs for Particle Tracking and Spectroscopy within the EXL Project at Fair

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    Prototype double-sided silicon strip detectors (DSSDss) of 300 μ\mu m thickness produced at PTI St. Petersburg (Russia) were tested for the use as position sensitive, ΔE\Delta E and E detectors for tracking and particle identification in the EXL (EXotic nuclei studied in Light-ion induced reactions at the NESR storage ring) setup at the FAIR (Facility for Antiproton and Ion Research) project at GSI. We describe the characteristics of detectors with 16×16,  64×6416 \times 16,\;64\times 64 and 64×1664\times 16 strips, respectively. The response of these detectors for 241^{241}Am α\alpha particles injected either from the p or n side was examined. The test measurements were performed partially at GSI and the University of Edinburgh. A first in-beam test with a proton beam of 50 MeV with the latter two DSSDs and two 6.5 mm thick Si(Li) detectors was also done at KVI Groningen, the Netherlands. The results reveal good spectroscopic properties of these detectors

    Insulin signaling and its application

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    The discovery of insulin in 1921 introduced a new branch of research into insulin activity and insulin resistance. Many discoveries in this field have been applied to diagnosing and treating diseases related to insulin resistance. In this mini-review, the authors attempt to synthesize the updated discoveries to unravel the related mechanisms and inform the development of novel applications. Firstly, we depict the insulin signaling pathway to explain the physiology of insulin action starting at the receptor sites of insulin and downstream the signaling of the insulin signaling pathway. Based on this, the next part will analyze the mechanisms of insulin resistance with two major provenances: the defects caused by receptors and the defects due to extra-receptor causes, but in this study, we focus on post-receptor causes. Finally, we discuss the recent applications including the diseases related to insulin resistance (obesity, cardiovascular disease, Alzheimer’s disease, and cancer) and the potential treatment of those based on insulin resistance mechanisms

    A Methodology to Characterize Riverine Macroplastic Emission Into the Ocean

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    Land-based macroplastic is considered one of the major sources of marine plastic debris. However, estimations of plastic emission from rivers into the oceans remain scarce and uncertain, mainly due to a severe lack of standardized observations. To properly assess global plastic fluxes, detailed information on spatiotemporal variation in river plastic quantities and composition are urgently needed. In this paper, we present a new methodology to characterize riverine macroplastic dynamics. The proposed methodology was applied to estimate the plastic emission from the Saigon River, Vietnam. During a 2-week period, hourly cross-sectional profiles of plastic transport were made across the river width. Simultaneously, sub-hourly samples were taken to determine the weight, size and composition of riverine macroplastics (>5 cm). Finally, extrapolation of the observations based on available hydrological data yielded new estimates of daily, monthly and annual macroplastic emission into the ocean. Our results suggest that plastic emissions from the Saigon River are up to four times higher than previously estimated. Importantly, our flexible methodology can be adapted to local hydrological circumstances and data availability, thus enabling a consistent characterization of macroplastic dynamics in rivers worldwide. Such data will provide crucial knowledge for the optimization of future mediation and recycling efforts

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

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    Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts
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