GPS Chimera: A Software Profiling Analysis

2020 ◽  
Author(s):  
Micaela Troglia Gamba ◽  
Mario Nicola ◽  
Beatrice Motella
Keyword(s):  
Software Profiling ◽  
Profiling Analysis

scholarly journals Computational Load Analysis of a Galileo OSNMA-Ready Receiver for ARM-Based Embedded Platforms

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 467
Author(s):  
Micaela Troglia Gamba ◽  
Mario Nicola ◽  
Beatrice Motella
Keyword(s):  
Real Time ◽  
Message Authentication ◽  
Software Receiver ◽  
Computational Load ◽  
Navigation Message ◽  
Security And Reliability ◽  
Load Analysis ◽  
Embedded Platforms ◽  
Software Profiling ◽  
Profiling Analysis

Many GNSS applications have been experiencing some constantly growing needs in terms of security and reliability. To address some of them, both GPS and Galileo are proposing evolutions of their legacy civil signals, embedding features of authentication. This paper focuses on the Galileo Open Signal Navigation Message Authentication (OSNMA) and describes its implementation within a real-time software receiver for ARM-based embedded platforms. The innovative contributions of the paper include the software profiling analysis for the OSNMA add on, along with the comparison among performances obtained with different platforms. In addition, specific evaluations on the computational load of the whole receiver complete the analysis. The receiver used for the implementation belongs to the NGene receivers family—real-time fully-software GPS and Galileo receivers, tailored for different platforms and sharing the same core processing. In detail, the paper deals with the introduction of the OSNMA support inside the eNGene, the version of the receiver executable by ARM-based embedded platforms.

Preparation of Salmonella enterica Serovar Typhi Genomic DNA Microarrays for Gene Expression Profiling Analysis*

2009 ◽  
Vol 2009 (2) ◽  
pp. 206-212 ◽  
Author(s):  
Xiu-Mei SHENG ◽  
Xin-Xiang HUANG ◽  
Ling-Xiang MAO ◽  
Chao-Wang ZHU ◽  
Shun-Gao XU ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Salmonella Enterica ◽  
Genomic Dna ◽  
Dna Microarrays ◽  
Profiling Analysis

scholarly journals Comprehensive profiling analysis of the N6-methyladenosine-modified circular RNA transcriptome in cultured cells infected with Marek’s disease virus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Aijun Sun ◽  
Rui Wang ◽  
Shuaikang Yang ◽  
Xiaojing Zhu ◽  
Ying Liu ◽  
...  
Keyword(s):  
Disease Virus ◽  
Cultured Cells ◽  
Circular Rna ◽  
Marek's Disease Virus ◽  
Marek's Disease ◽  
Circular Rnas ◽  
Marek’S Disease Virus ◽  
Marek’S Disease ◽  
Pathway Analyses ◽  
Profiling Analysis

AbstractMarek’s disease virus (MDV) induces severe immunosuppression and lymphomagenesis in the chicken, its natural host, and results in a condition that investigated the pathogenesis of MDV and have begun to focus on the expression profiling of circular RNAs (circRNAs). However, little is known about how the expression of circRNAs is referred to as Marek’s disease. Previous reports have is regulated during MDV replication. Here, we carried out a comprehensive profiling analysis of N6-methyladenosine (m6A) modification on the circRNA transcriptome in infected and uninfected chicken embryonic fibroblast (CEF) cells. Methylated RNA immunoprecipitation sequencing (MeRIP-Seq) revealed that m6A modification was highly conserved in circRNAs. Comparing to the uninfected group, the number of peaks and conserved motifs were not significantly different in cells that were infected with MDV, although reduced abundance of circRNA m6A modifications. However, gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses revealed that the insulin signaling pathway was associated with the regulation of m6A modified circRNAs in MDV infection. This is the first report to describe alterations in the transcriptome-wide profiling of m6A modified circRNAs in MDV-infected CEF cells.

scholarly journals Metabolic profiling analysis of the vitamin B 12 producer Propionibacterium freudenreichii

2021 ◽  
Vol 10 (3) ◽  
Author(s):  
Jiao Liu ◽  
Yongfei Liu ◽  
Jie Wu ◽  
Huan Fang ◽  
Zhaoxia Jin ◽  
...  
Keyword(s):  
Metabolic Profiling ◽  
Vitamin B ◽  
Propionibacterium Freudenreichii ◽  
Metabolic Profiling Analysis ◽  
Vitamin B 12 ◽  
Profiling Analysis

Global transcriptome profiling analysis reveals insight into saliva-responsive genes in alfalfa

2015 ◽  
Vol 35 (3) ◽  
pp. 561-571 ◽  
Author(s):  
Wenxian Liu ◽  
Zhengshe Zhang ◽  
Shuangyan Chen ◽  
Lichao Ma ◽  
Hucheng Wang ◽  
...  
Keyword(s):  
Transcriptome Profiling ◽  
Global Transcriptome ◽  
Profiling Analysis ◽  
Insight Into

scholarly journals In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Joonho Park ◽  
Hyeyoon Kim ◽  
So Yeon Kim ◽  
Yeonjae Kim ◽  
Jee-Soo Lee ◽  
...  
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Good Prognosis ◽  
Severe Illness ◽  
Proteome Profiling ◽  
T Cell Suppression ◽  
Cell Suppression ◽  
Profiling Analysis ◽  
Necrosis Factor

AbstractThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over forty million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed in-depth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.

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