Michaelbisgaard4431

There is a strong and growing interest in using the large amount of high-quality operational data available within an airline. One reason for this is the push by regulators to use data to demonstrate safety performance by monitoring the outputs of Safety Performance Indicators relative to targeted goals. However, the current exceedance-based approaches alone do not provide sufficient operational risk information to support managers and operators making proximate real-time data-driven decisions. The purpose of this study was to develop and test a set of metrics which can complement the current exceedance-based methods. The approach was to develop two construct variables that were designed with the aim to (1) create an aggregate construct variable that can differentiate between normal and abnormal landings (row_mean); and (2) determine if temporal sequence patterns can be detected within the data set that can differentiate between the two landing groups (row_sequence). To assess the differentiation ability of the aggregate constructs, a set of both statistical and visual tests were run in order to detect quantitative and qualitative differences between the data series representing two landing groups prior to touchdown. The result, verified with a time series k-means cluster analysis, show that the composite constructs seem to differentiate normal and abnormal landings by capturing time-varying importance of individual variables in the final 300 seconds before touchdown. Together the approaches discussed in this article present an interesting and complementary way forward that should be further pursued.This contribution focuses on complex [Mo2 (H)2 (μ-AdDipp2 )2 ] (1) and tetrahydrofuran and pyridine adducts [Mo2 (H)2 (μ-AdDipp2 )2 (L)2 ] (1⋅thf and 1⋅py), which contain a trans-(H)Mo≣Mo(H) core (AdDipp2 =HC(NDipp2 )2 ; Dipp=2,6-iPr2 C6 H3 ). Computational studies provide insights into the coordination and electronic characteristics of the central trans-Mo2 H2 unit of 1, with four-coordinate, fourteen-electron Mo atoms and ϵ-agostic interactions with Dipp methyl groups. Small size C- and N-donors give rise to related complexes 1⋅L but only one molecule of P-donors, for example, PMe3 , can bind to 1, causing one of the hydrides to form a three-centered, two-electron (3c-2e) Mo-H→Mo bond (2⋅PMe3 ). A DFT analysis of the terminal and bridging hydride coordination to the Mo≣Mo bond is also reported, along with reactivity studies of the Mo-H bonds of these complexes. Reactions investigated include oxidation of 1⋅thf by silver triflimidate, AgNTf2 , to afford a monohydride [Mo2 (μ-H)(μ-NTf2 )(μ-AdDipp2 )2 ] (4), with an O,O'-bridging triflimidate ligand.Although much is known about the development of physical aggression across the lifespan, far less is known about the developmental pattern of indirect aggression from childhood to adulthood. Accordingly, we examined the self-reported use of indirect aggression from age 10 to 22 in a randomly drawn sample of 704 Canadians. A person-centered approach was used to capture intraindividual change and heterogeneity in development. Four childhood (age 10-18) indirect aggression trajectories were identified (1) a very low decreasing group (64.8%), (2) a low decreasing group (26.0%), (3) a low-to-moderate increasing group (5.1%), and (4) a moderate increasing group (4.1%). There were more girls than boys in the moderate increasing group (75.9% vs. selleckchem 24.1%). Two adulthood (age 19-22) indirect aggression trajectory groups were also identified (1) a low decreasing group (82.6%), and (2) a moderate stable group (17.4%). No sex differences were found among adults' use across the two trajectories. When we examined the prediction of indirect aggression use in adulthood from indirect aggression use in childhood, we found that children who followed a moderate increasing trajectory from age 10 to 18 were nine times more likely to follow a moderate stable trajectory from age 19 to 22, while children who followed a low-to-moderate increasing trajectory across childhood were 14 times more likely to follow a moderate stable trajectory across adulthood (compared to the very low decreasing group). Given the negative impact indirect aggression has on others, intervening early to derail this pattern of abuse is justified.Antibody-Mediated Rejection (AMR) due to donor-specific antibodies (DSA) is associated with poor outcomes after lung transplantation. Currently, there are no guidelines regarding the selection of treatment protocols. We studied how DSA characteristics including titers, C1q, and mean fluorescence intensity (MFI) values in undiluted and diluted sera may predict a response to therapeutic plasma exchange (TPE) and inform patient prognosis after treatment. Among 357 patients consecutively transplanted without detectable pre-existing DSAs between 01/01/16 and 12/31/18, 10 patients were treated with a standardized protocol of five TPE sessions with IVIG. Based on DSA characteristics after treatment, all patients were divided into three groups as responders, partial responders, and nonresponders. Kaplan-Meier Survival analyses showed a statistically significant difference in patient survival between those groups (P = 0.0104). Statistical analyses showed that MFI in pre-TPE 116 diluted sera was predictive of a response to standardized protocol (R2 = 0.9182) and patient survival (P = 0.0098). Patients predicted to be nonresponders who underwent treatment with a more aggressive protocol of eight TPE sessions with IVIG and bortezomib showed improvements in treatment response (P = 0.0074) and patient survival (P = 0.0253). Dilutions may guide clinicians as to which patients would be expected to respond to a standards protocol or require more aggressive treatment.Geographically dependent individual level models (GD-ILMs) are a class of statistical models that can be used to study the spread of infectious disease through a population in discrete-time in which covariates can be measured both at individual and area levels. The typical ILMs to illustrate spatial data are based on the distance between susceptible and infectious individuals. A key feature of GD-ILMs is that they take into account the spatial location of the individuals in addition to the distance between susceptible and infectious individuals. As a motivation of this article, we consider tuberculosis (TB) data which is an infectious disease which can be transmitted through individuals. It is also known that certain areas/demographics/communities have higher prevalent of TB (see Section 4 for more details). It is also of interest of policy makers to identify those areas with higher infectivity rate of TB for possible preventions. Therefore, we need to analyze this data properly to address those concerns. In this article, the expectation conditional maximization algorithm is proposed for estimating the parameters of GD-ILMs to be able to predict the areas with the highest average infectivity rates of TB.