The Ecotoxicity of Iron Oxide Nanoparticles : Acute, Chronic and Mixture Effects on Daphnia magna

This PhD thesis focuses on the investigation of iron oxide nanoparticles (IONP). Due to the increasing application of iron nanomaterials (NM) in environmental remediation of contaminated sites, tons of these NM will consequently be released to the environment with unknown risks to biota. For assessing effects of IONP, Daphnia magna was used since there are several standardized test protocols available. Due to its sensitivity against most pollutants and its filter-feeding way of life Daphnia is a preferred organism for testing NM in aquatic ecotoxicology. The presented studies show the influence of coating materials and colloidal properties on the effects of IONP on Daphnia in acute and chronic tests. In a further study, the use of IONP for remediation applications and the risk/benefit for the environment from this technique was studied in combinatory exposure acute tests. Furthermore, the Daphnia acute test was critically revised and possible miniaturizations and prolongations are shown

On the relationship between stochastic turnpike and dissipativity notions

In this paper, we introduce and study different dissipativity notions and different turnpike properties for discrete-time stochastic nonlinear optimal control problems. The proposed stochastic dissipativity notions extend the classic notion of Jan C. Willems to $L^r$ random variables and to probability measures. Our stochastic turnpike properties range from a formulation for random variables via turnpike phenomena in probability and in probability measures to the turnpike property for the moments. Moreover, we investigate how different metrics (such as Wasserstein or L\'evy-Prokhorov) can be leveraged in the analysis. Our results are built upon stationarity concepts in distribution and in random variables and on the formulation of the stochastic optimal control problem as a finite-horizon Markov decision process. We investigate how the proposed dissipativity notions connect to the various stochastic turnpike properties and we work out the link between these two different forms of dissipativity

Exploring Turn Signal Usage Patterns in Lane Changes: A Bayesian Hierarchical Modelling Analysis of Realistic Driving Data

Using turn signals to convey a driver's intention to change lanes provides a direct and unambiguous way of communicating with nearby drivers. Nonetheless, past research has indicated that drivers may not always use their turn signals prior to starting a lane change. In this study, we analyze realistic driving data to investigate turn signal usage during lane changes on highways in and around Gothenburg, Sweden. We examine turn signal usage and identify factors that have an influence on it by employing Bayesian hierarchical modelling (BHM). The results showed that a turn signal was used in approximately 60% of cases before starting a lane change, while it was only used after the start of a lane change in 33% of cases. In 7% of cases, a turn signal was not used at all. Additionally, the BHM results reveal that various factors influence turn signal usage. The study concludes that understanding the factors that affect turn signal usage is crucial for improving traffic safety through policy-making and designing algorithms for autonomous vehicles for future mixed traffic

Pathwise turnpike and dissipativity results for discrete-time stochastic linear-quadratic optimal control problems

We investigate pathwise turnpike behavior of discrete-time stochastic linear-quadratic optimal control problems. Our analysis is based on a novel strict dissipativity notion for such problems, in which a stationary stochastic process replaces the optimal steady state of the deterministic setting. The analytical findings are illustrated by a numerical example

Turnpike and dissipativity in generalized discrete-time stochastic linear-quadratic optimal control

We investigate different turnpike phenomena of generalized discrete-time stochastic linear-quadratic optimal control problems. Our analysis is based on a novel strict dissipativity notion for such problems, in which a stationary stochastic process replaces the optimal steady state of the deterministic setting. We show that from this time-varying dissipativity notion, we can conclude turnpike behaviors concerning different objects like distributions, moments, or sample paths of the stochastic system and that the distributions of the stationary pair can be characterized by a stationary optimization problem. The analytical findings are illustrated by numerical simulations

Towards Causal Inference for Spatio-Temporal Data: Conflict and Forest Loss in Colombia

In many data scientific problems, we are interested not only in modeling the behaviour of a system that is passively observed, but also in inferring how the system reacts to changes in the data generating mechanism. Given knowledge of the underlying causal structure, such behaviour can be estimated from purely observational data. To do so, one typically assumes that the causal structure of the data generating mechanism can be fully specified. Furthermore, many methods assume that data are generated as independent replications from that mechanism. Both of these assumptions are usually hard to justify in practice: datasets often have complex dependence structures, as is the case for spatio-temporal data, and the full causal structure between all involved variables is hardly known. Here, we present causal models that are adapted to the characteristics of spatio-temporal data, and which allow us to define and quantify causal effects despite incomplete causal background knowledge. We further introduce a simple approach for estimating causal effects, and a non-parametric hypothesis test for these effects being zero. The proposed methods do not rely on any distributional assumptions on the data, and allow for arbitrarily many latent confounders, given that these confounders do not vary across time (or, alternatively, they do not vary across space). Our theoretical findings are supported by simulations and code is available online. This work has been motivated by the following real-world question: how has the Colombian conflict influenced tropical forest loss? There is evidence for both enhancing and reducing impacts, but most literature analyzing this problem is not using formal causal methodology. When applying our method to data from 2000 to 2018, we find a reducing but insignificant causal effect of conflict on forest loss. Regionally, both enhancing and reducing effects can be identified.Comment: 29 pages, 8 figure

Unternehmerische Führung in Sozialen Organisationen

Sozialunternehmen mit einer ausgeprägt unternehmerischen Führung sind erfolgreicher als solche, die weniger stark veränderungs- und marktorientiert ausgerichtet sind, weniger Risiken eingehen, und ihre Mitarbeitenden weniger stark einbeziehen. Das zeigen die Ergebnisse einer Befragung von 257 Sozialen Organisationen aus der ganzen Schweiz, die im Bereich der Integration Wohn-, Arbeits-, Bildungs- oder Beratungsdienstleistungen für Klienten anbie-ten und sich dabei noch überwiegend über Leistungsverträge oder andere öffentliche Gelder (z.B. Kostengutsprachen) finanzieren. Der Organisationserfolg wurde dabei mit Bezug auf die Stakeholderzufriedenheit, die Mitarbeiterfluktuation, das Orga-nisationswachstum und die Veränderung in der Marktfinanzierung gemessen. Das letztgenannte Erfolgsmass spielt angesichts knapper werdender öf-fentlicher Finanzmittel eine zunehmend wichtige Rolle. Die relevanten Erfolgsfaktoren unterscheiden sich dabei je nach Erfolgsmass. Neben einer unter-nehmerischen Führung spielen auch die Wertekongruenz zwischen der haupt- und der ehrenamtlichen Leitung, die Verankerung der Organisationsstrategie, die organisationsinterne Kommunikation und die Organisationsstruktur eine entscheidende Rolle für die Zielerreichung

Electro‐Olefination—A Catalyst Free Stereoconvergent Strategy for the Functionalization of Alkenes

Conventional methods carrying out C(sp2)−C(sp2) bond formations are typically mediated by transition‐metal‐based catalysts. Herein, we conceptualize a complementary avenue to access such bonds by exploiting the potential of electrochemistry in combination with organoboron chemistry. We demonstrate a transition metal catalyst‐free electrocoupling between (hetero)aryls and alkenes through readily available alkenyl‐tri(hetero)aryl borate salts (ATBs) in a stereoconvergent fashion. This unprecedented transformation was investigated theoretically and experimentally and led to a library of functionalized alkenes. The concept was then carried further and applied to the synthesis of the natural product pinosylvin and the derivatization of the steroidal dehydroepiandrosterone (DHEA) scaffold

Growth Histories in Bimetric Massive Gravity

We perform cosmological perturbation theory in Hassan-Rosen bimetric gravity for general homogeneous and isotropic backgrounds. In the de Sitter approximation, we obtain decoupled sets of massless and massive scalar gravitational fluctuations. Matter perturbations then evolve like in Einstein gravity. We perturb the future de Sitter regime by the ratio of matter to dark energy, producing quasi-de Sitter space. In this more general setting the massive and massless fluctuations mix. We argue that in the quasi-de Sitter regime, the growth of structure in bimetric gravity differs from that of Einstein gravity.Comment: 28 pages + appendix, 11 figure

Improving Efficiency of Human-Robot Coexistence While Guaranteeing Safety: Theory and User Study

Guaranteeing safety for humans in shared workspaces is not trivial. Not only must all possible situations be provably safe, but the human must feel safe as well. While robots are gradually leaving their cages, due to strict safety requirements, engineers often only replace physical cages with static safety zones - when the safety zone is entered, the robot is forced to stop. This can lead to excessive robot downtime. We present a concept for guaranteeing non-collision between humans and robots whilst maximising robot uptime and staying on-path. We evaluate how users react to this approach, in a trial over three non-consecutive days, compared to a control approach of static safety zones. We measure working efficiency as well as human factors such as trust, understanding of the robot, and perceived safety. Using our approach, the robot is indeed more efficient compared to static safety zones and the effect persists over multiple trials on separate days. We also observed that understanding of the robot's movement increased for our method over the course of trials, and the perceived safety of the robot increased for both our method and the control