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This paper is concerned with the filtering problem in continuous time. Three algorithmic solution approaches for this problem are reviewed: (i) the classical Kalman-Bucy filter, which provides an exact solution for the linear Gaussian problem; (ii) the ensemble Kalman-Bucy filter (EnKBF), which is an approximate filter and represents an extension of the Kalman-Bucy filter to nonlinear problems; and (iii) the feedback particle filter (FPF), which represents an extension of the EnKBF and furthermore provides for a consistent solution in the general nonlinear, non-Gaussian case. The common feature of the three algorithms is the gain times error formula to implement the update step (to account for conditioning due to the observations) in the filter. In contrast to the commonly used sequential Monte Carlo methods, the EnKBF and FPF avoid the resampling of the particles in the importance sampling update step. Moreover, the feedback control structure provides for error correction potentially leading to smaller simulation variance and improved stability properties. The paper also discusses the issue of nonuniqueness of the filter update formula and formulates a novel approximation algorithm based on ideas from optimal transport and coupling of measures. Performance of this and other algorithms is illustrated for a numerical example.
Particle filters (also called sequential Monte Carlo methods) are widely used for state and parameter estimation problems in the context of nonlinear evolution equations. The recently proposed ensemble transform particle filter (ETPF) [S. Reich, SIAM T. Sci. Comput., 35, (2013), pp. A2013-A2014[ replaces the resampling step of a standard particle filter by a linear transformation which allows for a hybridization of particle filters with ensemble Kalman filters and renders the resulting hybrid filters applicable to spatially extended systems. However, the linear transformation step is computationally expensive and leads to an underestimation of the ensemble spread for small and moderate ensemble sizes. Here we address both of these shortcomings by developing second order accurate extensions of the ETPF. These extensions allow one in particular to replace the exact solution of a linear transport problem by its Sinkhorn approximation. It is also demonstrated that the nonlinear ensemble transform filter arises as a special case of our general framework. We illustrate the performance of the second-order accurate filters for the chaotic Lorenz-63 and Lorenz-96 models and a dynamic scene-viewing model. The numerical results for the Lorenz-63 and Lorenz-96 models demonstrate that significant accuracy improvements can be achieved in comparison to a standard ensemble Kalman filter and the ETPF for small to moderate ensemble sizes. The numerical results for the scene-viewing model reveal, on the other hand, that second-order corrections can lead to statistically inconsistent samples from the posterior parameter distribution.
I’m merciful, am I not?
(2017)
Narcissists are said to be particularly unforgiving, yet previous research remains inconclusive. This is likely because most previous studies focused on narcissism as a unitary construct, thereby neglecting its multiple facets. The present study (N = 1101) thus aimed to clarify the nuanced associations between different facets of narcissism and forgiveness, the latter being assessed via self-report and non-self-report measures. The results of a structural equation model (SEM) showed that antagonistic aspects of narcissism were negatively correlated with explicit forgiveness. Importantly, agentic as well as communal aspects of narcissism were positively correlated with explicit forgiveness. Aspects of narcissistic personality were not correlated with implicit forgiveness. Results suggest that not all facets of narcissism are associated with an unforgiving stance.
I can see clearly now
(2017)
Past research has revealed that narcissists lack forgiveness. However, little is known about factors that might either buffer or, more critically, enhance the link between narcissism and lack of forgiveness. To address this gap in the literature, the present studies focused on the moderating role of clarity of transgression-related motivations. In an original and a replication study (Ns = 509 and 532, respectively), participants rated their levels of narcissistic admiration and rivalry and recalled a personal episode in which someone had hurt them. Subsequently, participants reported on their lack of forgiveness toward their transgressor. Response speed to these ratings served as an indirect clarity measure, with faster responses indicating greater clarity. In both studies, narcissistic rivalry (but not admiration) was positively related to lack of forgiveness and this relationship was stronger among individuals who were clear about their transgression-related motivations. Results inform our understanding of socio-emotional factors that contribute to narcissists' lack of forgiveness following interpersonal hurt.
Dieses Buch zeigt Methoden und Instrumente zur Erfassung und Bewertung von gesundheitsrelevanten Merkmalen von Arbeitssituationen. Damit bietet es die Grundlagen für die Ableitung von arbeitsgestalterischen Maßnahmen und personbezogebnen Interventionen, um eingetretene Beeinträchtigungen nachhaltig zu beheben bzw. um diesen vorzubeugen. Die Gesundheitsberichte aller Krankenkassen
weisen aus, dass die durch körperliche Belastungen und Arbeitsumweltbedingungen
verursachten Erkrankungen von Erwerbstätigen rückläufig sind. Zugleich ist eine
Zunahme von durch vorwiegend psychische Belastungen verursachten Erkrankungen
wie psychosomatische Störungen, Depressionen oder Burnout zu verzeichnen. Anhand von Fallbeispielen werden im vorliegenden Buch das methodische Vorgehen zur Datenerhebung,
deren formale Auswertung sowie die aus den Ergebnissen ableitbaren
Schlussfolgerungen für Maßnahmen diskutiert. Es richtet sich vor allem an
jene Experten (Ingenieure, Betriebsärzte, Arbeitspsychologen,
Sicherheitsfachkräfte) die in der betrieblichen Praxis mit der Durchführung von
Gefährdungsanalysen befasst sind.
Introduction: Adequate cognitive function in patients is a prerequisite for successful implementation of patient education and lifestyle coping in comprehensive cardiac rehabilitation (CR) programs. Although the association between cardiovascular diseases and cognitive impairments (CIs) is well known, the prevalence particularly of mild CI in CR and the characteristics of affected patients have been insufficiently investigated so far.
Methods: In this prospective observational study, 496 patients (54.5 ± 6.2 years, 79.8% men) with coronary artery disease following an acute coronary event (ACE) were analyzed. Patients were enrolled within 14 days of discharge from the hospital in a 3-week inpatient CR program. Patients were tested for CI using the Montreal Cognitive Assessment (MoCA) upon admission to and discharge from CR. Additionally, sociodemographic, clinical, and physiological variables were documented. The data were analyzed descriptively and in a multivariate stepwise backward elimination regression model with respect to CI.
Results: At admission to CR, the CI (MoCA score < 26) was determined in 182 patients (36.7%). Significant differences between CI and no CI groups were identified, and CI group was associated with high prevalence of smoking (65.9 vs 56.7%, P = 0.046), heavy (physically demanding) workloads (26.4 vs 17.8%, P < 0.001), sick leave longer than 1 month prior to CR (28.6 vs 18.5%, P = 0.026), reduced exercise capacity (102.5 vs 118.8 W, P = 0.006), and a shorter 6-min walking distance (401.7 vs 421.3 m, P = 0.021) compared to no CI group. The age- and education-adjusted model showed positive associations with CI only for sick leave more than 1 month prior to ACE (odds ratio [OR] 1.673, 95% confidence interval 1.07–2.79; P = 0.03) and heavy workloads (OR 2.18, 95% confidence interval 1.42–3.36; P < 0.01).
Conclusion: The prevalence of CI in CR was considerably high, affecting more than one-third of cardiac patients. Besides age and education level, CI was associated with heavy workloads and a longer sick leave before ACE.