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The scattering formulation of characteristic mode decomposition is utilized to extend modal analysis to lossless scatterers breaking time-reversal symmetry. This enables characteristic modes analysis on devices containing gyrotropic or moving media. The resulting nonreciprocity introduces features not observed in reciprocal scenarios, such as asymmetric phase progression in characteristic far fiel
We present a method for optimal control with respect to a linear cost function for positive linear systems with coupled input constraints. We show that the Bellman equation giving the optimal cost function and resulting sparse state feedback for these systems can be stated explicitly, with the solution given by a linear program. Our framework admits a range of network routing problems with underly
We present an explicit solution to the discrete-time Bellman equation for minimax optimal control of positive systems under unconstrained disturbances. The primary contribution of our result relies on deducing a bound for the disturbance penalty, which characterizes the existence of a finite solution to the problem class. Moreover, this constraint on the disturbance penalty reveals that, in scenar
Network coherence generally refers to the emergence of simple aggregated dynamical behaviors, despite heterogeneity in the dynamics of the subsystems that constitute the network. In this paper, we develop a general frequency domain framework to analyze and quantify the level of network coherence that a system exhibits by relating coherence with a low-rank property of the system's input–output resp
Use of static program analysis tools can be highly beneficial in software development, but usage is hindered by usability issues. One method to better understand these issues is to gather user feedback, but it is challenging to get developers to invest effort in giving user feedback.In this paper, we investigate whether gamification can increase user engagement in feedback collection on static ana
Episodic memory allows the flexible retrieval of commonalities and idiosyncrasies of overlapping life events. For example, seeing a woman in the city with your colleague's daughter may form an integrated memory representation involving the woman and your colleague. However, you may also keep a specific representation of the city event to talk with your colleague about the circumstances of having m
This study explores the potential of utilizing hardware built for Machine Learning (ML) tasks as a platform for solving linear Partial Differential Equations via numerical methods. We examine the feasibility, benefits, and obstacles associated with this approach. Given an Initial Boundary Value Problem (IBVP) and a finite difference method, we directly compute stencil coefficients and assign them
Context Developing compilers and static analysis tools (“language tools”) is a difficult and time-consuming task. We have previously presented property probes, a technique to help the language tool developer build understanding of their tool. A probe presents a live view into the internals of the compiler, enabling the developer to see all the intermediate steps of a compilation or analysis rather
The problem of substructure characteristic modes is developed using a scattering matrix-based formulation, generalizing subregion characteristic mode decomposition to arbitrary computational tools. It is shown that the modes of the scattering formulation are identical to the modes of the classical formulation based on the background Green’s function for lossless systems under conditions where both
In this paper, we propose an approach that combines Vision Language Models (VLMs) and Behavior Trees (BTs) to address failures in robotics. Current robotic systems can handle known failures with pre-existing recovery strategies, but they are often ill-equipped to manage unknown failures or anomalies. We introduce VLMs as a monitoring tool to detect and identify failures during task execution. Addi
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
Standardized Cancer Patient Pathways (CPPs) were introduced in Swedish healthcare starting in 2015 to improve diagnostics for patients with symptoms of cancer, patient satisfaction and equity of care between healthcare providers. An inclusion target and a time target were set. Our primary aim was to visualize the patient population going through CPPs, in terms of investigation time and indications
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
Objective: To investigate the association between female body mass index (BMI) and live birth rates and maternal and perinatal outcomes after in-vitro fertilization (IVF). Methods: We performed a national, population-based cohort study including women undergoing IVF between 2002 and 2020. The cohort included 126,620 fresh cycles and subsequent frozen embryo transfers between 2007 and 2019 (subpopu
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
STUDY QUESTION: Has cumulative live birth rate (CLBR) improved over time and which factors are associated with such an improvement? SUMMARY ANSWER: During an 11-year period, 2007-2017, CLBR per oocyte aspiration increased significantly, from 27.0% to 36.3%, in parallel with an increase in blastocyst transfer and cryopreservation by vitrification. WHAT IS KNOWN ALREADY: While it has been shown that
