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The electrification of long-haul freight transport is essential for reducing emissions and achieving sustainable mobility. However, battery-electric trucks (BETs) face significant barriers, including limited range, high battery weight, and prolonged charging times, which hinder their widespread adoption for long-distance travel. Electric Road Systems (ERS) offer a compelling solution by providing
Collaborating with highly skilled professionals in participatory design of machine learning (ML) and visualization tools presents unique challenges. This paper reflects on interdisciplinary projects involving medicine, biology, and the social sciences, where ML was introduced to support complex data analysis and segmentation tasks, sometimes from the outset and other times as a later addition. Des
We perform a validation analysis on the multipolar model of opinion dynamics. A general methodology for using the model on datasets of two correlated variables is proposed and tested using data on the relationship between COVID-19 vaccination rates and political participation in Sweden. The model is shown to successfully capture the opinion segregation demonstrated by the data and spatial correlat
The anesthetic drug propofol is commonly used to control hypnotic depth (suppression of awareness) in patients undergoing surgery or intensive care. In addition to manual titration, a model-based open-loop feed-forward strategy called target-controlled infusion (TCI) has attained some clinical popularity. Research on closed-loop control, with awareness estimates derived from an electroencephalogra
This work investigates the cryogenic performance of InAs-based vertical nanowire ferroelectric field-effect transistors (VNW-FeFETs) with hafnium zirconium oxide (HZO) as the ferroelectric gate dielectric. Measurements at 300 K and 14 K reveal a 25% increase in memory window, from 560 mV at room temperature to 700 mV at 14 K, indicating enhanced polarization stability at low temperatures while als
Sparse tensor computations suffer from irregular memory access patterns that degrade cache performance. While software prefetching can mitigate this, existing compiler approaches lack the semantic insight needed for effective optimization. We present ASaP, an automatic software prefetching framework integrated within MLIR’s sparse tensor dialect. By leveraging semantic information-tensor formats a
We present a general technique for efficient computation of second order information for optimization functionals involving many variables of different nature, frequently appearing in modern applications. This technique relies on the bilinear Hessian, and while the main tools for this task have been published elsewhere, we here focus on the problem of how to organize the computations in the multi-
The purpose of this study was to investigate the supervision of non-smoking school yards in Sweden. Smoking costs Swedish society an estimated 30 billion SEK annually in cost for healthcare, production losses and sick leave. Smoking among adolescents has declined in recent years, but it is still 24 % in high school's grade 2, which categorized as smokers. The supervision of the schoolyard is t
In the software industry, the drive to add new features often overshadows the need to improve existing code. Large Language Models (LLMs) offer a new approach to improving codebases at an unprecedented scale through AI-assisted refactoring. However, LLMs come with inherent risks such as braking changes and the introduction of security vulnerabilities. We advocate for encapsulating the interaction
This study evaluates the design choices of a two-day, industry-collaborative case competition at Campus Helsingborg and their effect on student motivation and engagement. Using pre and post Self-Determination Theory surveys, observations, and interviews we observed very high intrinsic (4.82/5) and extrinsic motivation (4.33/5). The perceived value of competition elements increased consistently aft
The introduction of electric heavy trucks will lead to new charging power requirements on the power grid. This study examines how much charging power is required for the public fast charging of a fully electrified long-haul truck fleet. Probabilistic truck charging profiles are created using agent-based simulations, based on fully representative long-haul goods transport data from the study area.
Post-compression of (sub)-picosecond laser pulses down to sub-100 fs durations has become a standard approach for high-peak-power sources at a high average power [1]. Here, we propose a new post-compression geometry suited for extreme temporal compression of energetic narrowband lasers, such as diode or electrically pumped four-level systems which can deliver kW-average powers [2], but typically e
We introduce Thalassa, a framework designed to convert nonlinear systems of partial differential equations (PDEs) with a time-like component into tensor programs that solve these equations. These programs can run on GPUs as well as machine learning (ML) acceleration hardware, enabling scientific computing fields such as computational fluid dynamics, astrophysics, mechanics and biology to utilize a
As a prominent category of side-channel attacks (SCAs), plaintext-checking (PC) oracle-based SCAs offer the advantages of generality and operational simplicity on a targeted device. At TCHES 2023, Rajendran et al. and Tanaka et al. independently proposed the multiple-valued (MV) PC oracle, significantly reducing the required number of queries (a.k.a., traces) in the PC oracle. However, in practice
The theory of optimal control on positive cones has recently identified several new problem classes where the Bellman equation can be solved explicitly, in analogy with classical linear quadratic control. In this paper, the idea is extended to minimax adaptive control, yielding exact solutions to instances of the Bellman equation for dual control. In particular, this allows for optimization of the
Future wireless communications will rely on multiple-input multiple-output (MIMO) beamforming operating at millimeter wave (mmWave) frequency bands to deliver high data rates. To support flexible spatial processing and meet the demands of latency-critical applications, it is essential to use fully digital mmWave MIMO beamforming, which relies on accurate channel estimation. However, ensuring power
