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Iron centeredN-heterocyclic carbene (Fe-NHC) complexes have shown long-lived excited states with charge transfer character useful for light harvesting applications. Understanding the nature of the metal-ligand bond is of fundamental importance to rationally tailor the properties of transition metal complexes. The high-energy-resolution fluorescence detected X-ray absorption near edge structure (HE
A new generation of octahedral iron(ii)-N-heterocyclic carbene (NHC) complexes, employing different tridentate C^N^C ligands, has been designed and synthesized as earth-abundant photosensitizers for dye sensitized solar cells (DSSCs) and related solar energy conversion applications. This work introduces a linearly aligned push-pull design principle that reaches from the ligand having nitrogen-base
This paper examines the local exponential stability (LES) of trajectories for nonlinear systems on Riemannian manifolds. We present necessary and sufficient conditions for LES of a trajectory on a Riemannian manifold by analyzing the complete lift of the system along the given trajectory. These conditions are coordinate-free which reveal fundamental relationships between exponential stability and
The need for autonomous robot systems in both the service and the industrial domain is larger than ever. In the latter, the transition to small batches or even “batch size 1” in production created a need for robot control system architectures that can provide the required flexibility. Such architectures must not only have a sufficient knowledge integration framework. It must also support autonomou
Background: Artificial intelligence (AI) systems can potentially aid the diagnostic pathway of prostate cancer by alleviating the increasing workload, preventing overdiagnosis, and reducing the dependence on experienced radiologists. We aimed to investigate the performance of AI systems at detecting clinically significant prostate cancer on MRI in comparison with radiologists using the Prostate Im
Control of network systems with uncertain local dynamics has remained an open problem for a long time. In this paper, a distributed minimax adaptive control algorithm is proposed for such networks whose local dynamics has an uncertain parameter possibly taking finite number of values. To hedge against this uncertainty, each node in the network collects the historical data of its neighbouring nodes
This work concerns reduction of the peak flow rate of a district heating grid,a key system property which is bounded by pipe dimensions and pumpingcapacity. The peak flow rate constrains the number of additional consumersthat can be connected, and may be a limiting factor in reducing supplytemperatures when transitioning to the 4th generation of district heating.We evaluate a full year of operatio
The process of constructing, maintaining, and reconstructing episodic memories is closely linked to the temporal dynamics of visual exploration through sequences of eye movements (Johansson et al., 2022; Nikolaev et al., 2023). However, the neural mechanisms that mediate relational memory across eye movements are not yet fully understood. This study presented participants with a series of visuospa
We present a tool for modeling conflict situations that enables simulation and testing of situation awareness in shared autonomy, in this case in an autonomous driving scenario. The flexibility of the tool allows definition of new conflict situations, integration with various control and conflict detection systems, as well as customization of Takeover Request (TOR) signals and different means of c
Research in community ecology has tended to focus on trophic interactions (e.g., predation, resource competition) as driving forces of community dynamics, and sexual interactions have often been overlooked. Here we discuss how sexual interactions can affect community dynamics, especially focusing on frequency-dependent dynamics of horizontal communities (i.e., communities of competing species in a
We present an online learning analysis of minimax adaptive control for the case where the uncertainty includes a finite set of linear dynamical systems. Precisely, for each system inside the uncertainty set, we define the model-based regret by comparing the state and input trajectories from the minimax adaptive controller against that of an optimal controller in hindsight that knows the true dynam
The transition to agile manufacturing, Industry 4.0, and high-mix-low-volume tasks require robot programming solutions that are flexible. However, most deployed robot solutions are still statically programmed and use stiff position control, which limit their usefulness. In this paper, we show how a single robot skill that utilizes knowledge representation, task planning, and automatic selection of
We present a novel class of minimax optimal control problems with positive dynamics, linear objective function and homogeneous constraints. The proposed problem class can be analyzed with dynamic programming and an explicit solution to the Bellman equation can be obtained, revealing that the optimal control policy (among all possible policies) is linear. This policy can in turn be computed through
Sex-limited morphs can provide profound insights into the evolution and genomic architecture of complex phenotypes. Inter-sexual mimicry is one particular type of sex-limited polymorphism in which a novel morph resembles the opposite sex. While inter-sexual mimics are known in both sexes and a diverse range of animals, their evolutionary origin is poorly understood. Here, we investigated the genom
The AI Act’s (AIA) requirements for high-risk AI systems affect many aspects of modern software systems. Knowing which AIA-related technical challenges are relevant to different companies is essential to focus compliance-oriented research on the aspects that matter. We therefore conducted an interview study in collaboration with a case company that specializes in network video solutions within the
In this paper, we provide the following simple equivalent condition for a nonsymmetric Algebraic Riccati Equation to admit a stabilizing cone-preserving solution: an associated coefficient matrix must be stable. The result holds under the assumption that said matrix be cross-positive on a proper cone, and it both extends and completes a corresponding sufficient condition for nonnegative matrices i
Research efforts to push the integration density of circuits with technologies that transcend Moore's law have gained significant attention in recent years. This study investigates the silicon area gains of Sequential 3D technology, utilizing the third dimension of integrated circuits by accommodating nMOS and pMOS transistors in two stacked tiers with high-density and low-pitch 3D vias. The effic
When deploying deep neural networks on robots or other physical systems, the learned model should reliably quantify predictive uncertainty. A reliable uncertainty allows downstream modules to reason about the safety of its actions. In this work, we address metrics for uncertainty quantification. Specifically, we focus on regression tasks, and investigate Area Under Sparsification Error (AUSE), Cal
