dependent observations
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Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 120
Author(s):  
Maximilian Aumiller ◽  
Christian Heckl ◽  
Stefanie Quach ◽  
Herbert Stepp ◽  
Birgit Ertl-Wagner ◽  
...  

In a former study, interstitial photodynamic therapy (iPDT) was performed on patients suffering from newly diagnosed glioblastoma (n = 11; 8/3 male/female; median age: 68, range: 40–76). The procedure includes the application of 5-ALA to selectively metabolize protoporphyrin IX (PpIX) in tumor cells and illumination utilizing interstitially positioned optical cylindrical diffuser fibers (CDF) (2–10 CDFs, 2–3 cm diffusor length, 200 mW/cm, 635 nm, 60 min irradiation). Intraoperative spectral online monitoring (SOM) was employed to monitor treatment light transmission and PpIX fluorescence during iPDT. MRI was used for treatment planning and outcome assessment. Case-dependent observations included intraoperative reduction of treatment light transmission and local intrinsic T1 hyperintensity in non-contrast-enhanced T1-weighted MRI acquired within one day after iPDT. Intrinsic T1 hyperintensity was observed and found to be associated with the treatment volume, which indicates the presence of methemoglobin, possibly induced by iPDT. Based on SOM data, the optical absorption coefficient and its change during iPDT were estimated for the target tissue volumes interjacent between evaluable CDF-pairs at the treatment wavelength of 635 nm. By spatial comparison and statistical analysis, it was found that observed increases of the absorption coefficient during iPDT were larger in or near regions of intrinsic T1 hyperintensity (p = 0.003). In cases where PpIX-fluorescence was undetectable before iPDT, the increase in optical absorption and intrinsic T1 hyperintensity tended to be less. The observations are consistent with in vitro experiments and indicate PDT-induced deoxygenation of hemoglobin and methemoglobin formation. Further investigations are needed to provide more data on the time course of the observed changes, thus paving the way for optimized iPDT irradiation protocols.


Informatics ◽  
2021 ◽  
Vol 18 (3) ◽  
pp. 36-47
Author(s):  
A. Y. Kharin

In the problems of data flows analysis, the problems of statistical decision making on parameters of observed data flows are important. For their solution it is proposed to use sequential statistical decision rules. The rules are constructed for three models of observation flows: sequence of independent homogeneous observations; sequence of observations forming a time series with a trend; sequence of dependent observations forming a homogeneous Markov chain. For each case the situation is considered, where the model describes the observed stochastic data with a distortion. "Outliers" ("contamination") are used as the admissible distortions that adequately describe the majority of situations appear in practice. For such situations the families of sequential decision rules are proposed, and robust decision rules are constructed that allow to reduce influence of distortion to the efficiency characteristics. The results of computer experiments are given to illustrate the constructed decision rules.


2021 ◽  
pp. 147592172110306
Author(s):  
Jannie S Nielsen

A Bayesian approach is often applied when updating a deterioration model using observations from inspections, structural health monitoring, or condition monitoring. The observations are stochastic variables with probability distributions that depend on the damage size. Consecutive observations are usually assumed to be independent of each other, but this assumption does not always hold, especially when using online monitoring systems. Frequent updating using dependent measurements can lead to an over-optimistic assessment of the value of information when the measurements are incorrectly modeled as being independent. This article presents a Bayesian network modeling approach for the inclusion of temporal dependency between measurements through a dependency parameter and presents a generic monitoring model based on the exceedance of thresholds for a damage index. Additionally, the model is implemented in a computational framework for risk-based maintenance planning, developed for maintenance planning for wind turbines. The framework is applied for a numerical experiment, where the expected lifetime costs are found for strategies with monitoring with and without dependency between observations, and also for the case where dependency is present but is neglected when making decisions. The numerical experiment and associated parameter study show that neglecting dependency in the decision model when the observations are in fact dependent can lead to much higher costs than expected and to the selection of non-optimal strategies. Much lower costs (down to one quarter) can be obtained when the dependency is properly modeled. In the case of temporally dependent observations, an advanced decision model using a Bayesian network as a simple digital twin is needed to make monitoring feasible compared to only using inspections.


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Carita Håkansson ◽  
Ulf Leo ◽  
Anna Oudin ◽  
Inger Arvidsson ◽  
Kerstin Nilsson ◽  
...  

Abstract Background Few studies have assessed the mental health of principals, or studied associations with both organizational and social work environment factors and occupational balance. The purpose of the present study was therefore to investigate associations between supporting and demanding organizational and social work environment factors, occupational balance and stress symptoms in principals. Methods A total of 4309 surveys (2316 from the first round, 1992 from the second round), representing 2781 Swedish principals who had responded to at least one of two surveys, were included in the present study. The surveys include questions about socio-demographic factors, occupational balance, overtime work, and supporting and demanding organizational and social work environment factors, as well as questions about personal stress and exhaustion. Generalized Estimating Equations (GEE) models were used to specify a repeated measures model with a dichotomous outcome (binary logistic regression) and multiple independent factors. Data from two surveys were combined, taking into account dependent observations due to the fact that many study subjects had participated in both surveys. Results Associations were found between occupational balance (Q1: OR 2.52, 95% CI 2.03–3.15; Q2: OR 4.95, 95% CI 3.86–6.35; Q3: OR 9.29, 95% CI 6.99–12.34), overtime work (Once a week: OR 1.51, 95% CI 1.10–2.08; Sometimes a week: OR 1.31, 95% CI 1.03–1.66), supportive private life (OR 1.50, 95% CI 1.36–1.66), supportive colleagues at the leadership level (OR 1.24, 95% CI 1.14–1.36), supportive management (OR 1.17, 95% CI 1.07–1.28) and no or negligible stress symptoms. In addition, role demands (OR 0.72, 95% CI 0.63–0.83), having a container function (OR 0.72, 95% CI 0.64–0.82), collaboration with employees (OR 0.77, 95% CI 0.66–0.89), role conflicts (OR 0.75, 95% CI 0.66–0.89) and having a buffer function (OR 0.86, 95% CI 0.77–0.97) were associated with lower likelihood to rate no or negligible stress symptoms. Conclusions The occupational balance of principals is strongly associated with no or negligible stress symptoms, and thus is a promising venue for promoting well-being. Improvements should be made to several factors in the organizational and social work environments to improve principals’ chances of having occupational balance, and therefore better mental health.


GPS Solutions ◽  
2020 ◽  
Vol 25 (1) ◽  
Author(s):  
Hao Wang ◽  
Noboru Noguchi

AbstractWe present a pure data-driven method to estimate vehicle dynamics from the measurements of sideslip and yaw rate in the use of GPS and inertial navigation system. The GPS and INS configuration provides vehicle position, velocity vector, vehicle orientation, and yaw rate observations. A new dynamic mode decomposition with control (DMDc) method denoises the state observations by adopting the total least-squares algorithm. The total least-squares DMD with control (tlsDMDc) helps discover the underlying dynamics with the time-dependent observations of states and external control. The experiments of a simulated linear dynamic model with synthetic Gaussian noise illustrate that the solutions of tlsDMDc are more accurate than the standard DMDc to characterize underlying dynamics with imperfect measurements. We additionally investigate how the algorithm performs on vehicle motion deduction and sensor bias correction. It has been shown that the tlsDMDc-based state estimator with the couple of GPS and inertial sensor measurements provides accurate and robust observation in the presence of model error and measurement noise.


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