Causes, Identification and Repair of loss of Common Ground in coordination in ATM (Air Traffic Management)

Over a century has passed since humans took to commercial flying. Traditional safety practices have worked well but the last decade has seen the need for an updated understanding of ATM safety. The modern safety views are complementary to the traditional ones but are also a new way of understanding and enabling safety practices. This master thesis report presents a comprehensive review of the sources chosen from literature to better understand how a complex sociotechnical system, such as ATM, would operate. Certain selected coordination aspects will be the focus of this master thesis and will be used to model and analyse an ATM case. The ultimate aim of this research project is to add to the growing body of knowledge in the field of ATM safety, to make flying increasingly safer and to enable a complex system to be resilient.Aerospace EngineeringAir Transport Operation

Logistic regression model (<i>R²</i> = 0.12) to predict OM proneness in 653 children.

<p>Only statistically significant results are shown above at P value <0.05.</p>a<p>The inference for the factors of race, IL-1β (−511), and IL-10 (−1082) is a based on a joint hypothesis; thus the degrees of freedom on the chi-square (11.91) is 3, as opposed to 1 on the other inferences.</p>b<p>Wild type genotype.</p>c<p>Either hetero- or homozygous polymorphic genotype.</p>d<p>Homozygous polymorphic genotype.</p

Demographic and clinical characteristics of 653 study children.

a<p>Whites of non-Hispanic ethnicity.</p>b<p>Any duration of breast feeding.</p>c<p>Any duration of exposure to cigarette smoke.</p>d<p>OM susceptibility in immediate family members.</p

Allele and genotype frequencies among 653 study subjects.

<p>RS number = Reference single nucleotide polymorphism (SNP) number.</p><p>CCR5 = C-C chemokine receptor type 5, CX3CR1 = CX3C chemokine receptor 1, ICAM1 = Inter-Cellular Adhesion Molecule 1, IL-1β = Interleukin 1β, IL-2 = Interleukin 2, IL-5 = Interleukin 5, IL-6 = Interleukin 6, IL-8 = Interleukin 8, IL-10 Interleukin 10, IL-12 = Interleukin 12, IL13 = Interleukin 13, IL-18 = Interleukin 18, MBL = Mannose-binding lectin, TGF-β1 = Transforming growth factor β, TLR4 = Toll-like receptor, TNFα = Tumor necrosis factor α.</p

Nasopharyngeal microbiota in infants and changes during viral upper respiratory tract infection and acute otitis media

<div><p>Background</p><p>Interferences between pathogenic bacteria and specific commensals are known. We determined the interactions between nasopharyngeal microbial pathogens and commensals during viral upper respiratory tract infection (URI) and acute otitis media (AOM) in infants.</p><p>Methods</p><p>We analyzed 971 specimens collected monthly and during URI and AOM episodes from 139 infants. The 16S rRNA V4 gene regions were sequenced on the Illumina MiSeq platform.</p><p>Results</p><p>Among the high abundant genus-level nasopharyngeal microbiota were <i>Moraxella</i>, <i>Haemophilus</i>, and <i>Streptococcus</i> (3 otopathogen genera), <i>Corynebacterium</i>, <i>Dolosigranulum</i>, <i>Staphylococcus</i>, <i>Acinetobacter</i>, <i>Pseudomonas</i>, and <i>Bifidobacterium</i>. Bacterial diversity was lower in culture-positive samples for <i>Streptococcus pneumoniae</i>, and <i>Haemophilus influenzae</i>, compared to cultured-negative samples. URI frequencies were positively associated with increasing trend in otopathogen colonization. AOM frequencies were associated with decreasing trend in <i>Micrococcus</i> colonization. During URI and AOM, there were increases in abundance of otopathogen genera and decreases in <i>Pseudomonas</i>, <i>Myroides</i>, <i>Yersinia</i>, <i>and Sphingomonas</i>. Otopathogen abundance was increased during symptomatic viral infection, but not during asymptomatic infection. The risk for AOM complicating URI was reduced by increased abundance of <i>Staphylococcus and Sphingobium</i>.</p><p>Conclusion</p><p>Otopathogen genera played the key roles in URI and AOM occurrences. <i>Staphylococcus</i> counteracts otopathogens thus <i>Staphylococcal</i> colonization may be beneficial, rather than harmful. While <i>Sphingobium</i> may play a role in preventing AOM complicating URI, the commonly used probiotic <i>Bifidobacterium</i> did not play a significant role during URI or AOM. The role of less common commensals in counteracting the deleterious effects of otopathogens requires further studies.</p></div

Relative abundance of microbiota in samples from subjects without and with AOM in the first year.

<p>Relative abundance of microbiota in samples from subjects without and with AOM in the first year.</p

Relative abundance of microbiota in healthy samples compared to sick visit (URI with or without AOM) samples.

<p>Relative abundance of microbiota in healthy samples compared to sick visit (URI with or without AOM) samples.</p

Characteristics of subjects and number of specimens.

<p>Characteristics of subjects and number of specimens.</p

Nasopharyngeal microbiota in infants and changes during viral upper respiratory tract infection and acute otitis media - Fig 2

<p><b>A-B. Shannon diversity index.</b> Fig 2A. Shannon Diversity Index by positive culture for otopathogens. Number in parentheses are number of samples with positive cultures. None = negative culture; S. pneu = <i>Streptococcus pneumoniae</i>; H. influ = <i>Haemophilus influenzae</i>; M. cat = <i>Moraxella catarrhalis</i>; > 1 path = positive culture for more than one of these pathogens. Fig 2B. Shannon Diversity Index by specific time point after antibiotic use. Samples were grouped based on the time of antibiotic use before sample collection: 7 days, 14 days, 1 month, 2 months, 3 months, and 6 months, comparison was made with samples collected after no history of antibiotic use.</p

Relative abundance of microbiota in virus-negative and virus-positive samples.

<p>Relative abundance of microbiota in virus-negative and virus-positive samples.</p