On 2023 February 27 at 18:15:55.77 UT, a bright fireball streaked across the sky above northern Sweden. The event offered a valuable opportunity to study the phenomenon using an optical system primarily designed for auroral studies, the Auroral Large Imaging System (ALIS_4D), that captured the event. In this study we show the capability of ALIS_4D to perform observations in support of meteor event analysis. We estimated the trajectory from the recorded data and computed the orbit. In addition, we investigated the origin of the meteoroid searching for its parent body. Fitting the analytical ablation model known as $α$-$β$ to the trajectory as well as incorporating local wind-field data in Monte-Carlo dark-flight simulations, strewn-fields were computed and physical properties of the meteoroid were estimated. Trajectory analyses delineate a strewn field along the border between Kiruna and Gällivare in northern Sweden. Our findings indicate that the meteoroid's parent body was likely an Apollo family object. We performed an orbital similarity analysis to identify candidate parent bodies of the fireball. Our simulations suggest that close approaches with Earth could have disrupted the
Collaboration is expected to play a central role in the transition to a bioeconomy - a central pillar of a green economy. Such collaboration is supposed to connect traditional biomass processing firms with diverse actors in fields where biomass ought to substitute existing or create novel products and processes. This study analyzes the network of technology collaborations among innovating firms in Sweden between 1970 and 2021. The results reveal generally positive associations between direct and indirect ties, with meaningful increases in innovation output for each additional direct collaboration partner. Relationships between brokerage positions and innovation output were statistically insignificant, and cognitive proximity - while following theoretical expectations - materially insignificant. These associations are mostly equal between actors heavily invested in the bioeconomy and those focusing on other innovation areas, indicating that these actors operate under largely similar mechanisms linking collaboration and subsequent innovation output. These results suggest that stimulating collaboration broadly - rather than attempting to optimize collaboration compositions - could res
This paper proposes a preventive congestion management framework with joint Local Flexibility Capacity Market (LFCM) and Local Energy Markets (LEMs). The framework enables Local Energy Communities (LECs) to optimize their flexibility potential across the LEM, LFCM, and heat markets. The LECs utilize their heat and electricity resources to offer flexibility services to Distribution System Operators (DSOs) for congestion relief. In this framework, energy and flexibility are treated as separate variables, each subject to different pricing scheme. Flexibility prices are market-driven, dynamically reflecting the location and severity of congestion. A case study conducted at Chalmers University of Technology, Sweden, shows that the proposed framework can effectively mitigate congestion by trading the LECs flexibility in the LFCM. The study also highlights up to 40% financial benefits for LECs, promoting the LFCM as a viable solution for congestion management in future decentralized energy systems.
Many Swedish benchmarks are translations of US-centric benchmarks and are therefore not suitable for testing knowledge that is particularly relevant, or even specific, to Sweden. We therefore introduce a manually written question-answering benchmark specifically targeted at Sweden-related personalities and events, many of which receive very limited coverage in international media. Our annotators drew inspiration from a popular radio program featuring public figures from culture and media, as well as major sports events in Sweden. The dataset can be used to measure factual recall across models of varying sizes and degrees of Swedish coverage, and allows probing of cross-lingual factual consistency, as it contains English translations. Using the dataset, we find that smaller models with stronger Swedish coverage perform comparably to a multilingual model three times larger in recalling Sweden-related facts. We also observe that continued pre-training on Swedish generally improves factual knowledge but leads to partial forgetting of previously known information. These results demonstrate the dataset's potential as a diagnostic tool for studying language adaptation and knowledge retent
Persistent rural-urban disparities in broadband connectivity remain a major policy challenge, even in digitally advanced countries. This paper examines how these inequalities manifest in northern Finland and Sweden, where sparse populations, long distances, and seasonal variations in demand create persistent gaps in service quality and reliability. Drawing on survey data (n = 148), in-depth interviews, and spatial analysis, the study explores the lived experience of connectivity in Arctic rural communities and introduces a novel Cellular Coverage Inequality (CCI) Index. The index combines measures of rurality and network performance to quantify spatial disparities that are masked by national coverage statistics. Results reveal that headline indicators overstate inclusiveness, while local users report chronic connectivity gaps affecting work, safety, and access to services. Building on these findings, the paper outlines policy reflections in six areas: shared infrastructure and roaming frameworks, spectrum flexibility for rural operators, performance-based Quality-of-Service monitoring, standardized and transparent reporting, temporal and seasonal capacity management, and digital-sk
This is the story of the first Fields Medal awarded to Lars Ahlfors. It was smuggled out of Finland in 1944, pawned in Sweden during World War II, and returned to Helsinki in 2004. This article is based on an interview with Ahlfors' second daughter Vanessa Gruen, and established biographical sources.
This paper examines the development of the Artificial Intelligence (AI) meta-debate in Sweden before and after the release of ChatGPT. From the perspective of agenda-setting theory, we propose that it is an elite outside of party politics that is leading the debate -- i.e. that the politicians are relatively silent when it comes to this rapid development. We also suggest that the debate has become more substantive and risk-oriented in recent years. To investigate this claim, we draw on an original dataset of elite-level documents from the early 2010s to the present, using op-eds published in a number of leading Swedish newspapers. By conducting a qualitative content analysis of these materials, our preliminary findings lend support to the expectation that an academic, rather than a political elite is steering the debate.
During the COVID-19 pandemic, governments faced the challenge of managing population behavior to prevent their healthcare systems from collapsing. Sweden adopted a strategy centered on voluntary sanitary recommendations while Belgium resorted to mandatory measures. Their consequences on pandemic progression and associated economic impacts remain insufficiently understood. This study leverages the divergent policies of Belgium and Sweden during the COVID-19 pandemic to relax the unrealistic -- but persistently used -- assumption that social contacts are not influenced by an epidemic's dynamics. We develop an epidemiological-economic co-simulation model where pandemic-induced behavioral changes are a superposition of voluntary actions driven by fear, prosocial behavior or social pressure, and compulsory compliance with government directives. Our findings emphasize the importance of early responses, which reduce the stringency of measures necessary to safeguard healthcare systems and minimize ensuing economic damage. Voluntary behavioral changes lead to a pattern of recurring epidemics, which should be regarded as the natural long-term course of pandemics. Governments should carefully
Activity-based models in transport are crucial for providing a comprehensive and realistic understanding of individuals' activity-travel patterns. Traditionally, travel surveys have been used to develop these models, but they are often costly and have small sample sizes. Mobile phone application data, one example of emerging data sources, offers an alternative with wider population coverage over extended periods for developing activity-based models. However, the challenges of using these data include sampling biases in the population coverage and individual-level data sparsity due to intermittent and irregular data collection. To synthesise activity-travel plans, we propose a novel model that combines mobile phone application data with travel survey data, addressing their limitations. Our generative model simulates multiple average weekday activity schedules for over 263,000 individuals living in Sweden, approximately 2.6% of Sweden's population. We also introduce a temporal-score approach to improve home and work location identification approaches. We assess the model's performance against an existing large-scale agent-based model of Sweden (SySMo) and a dummy model using only mob
Forest canopies embody a dynamic set of ecological factors, acting as a pivotal interface between the Earth and its atmosphere. They are not only the result of an ecosystem's ability to maintain its inherent ecological processes, structures, and functions but also a reflection of human disturbance. This study introduces a methodology for extracting a comprehensive and human-interpretable set of features from the Canopy Height Model (CHM), which are then analyzed to identify reliable indicators for the degree of naturalness of forests in Southern Sweden. Utilizing these features, machine learning models - specifically, the perceptron, logistic regression, and decision trees - are applied to predict forest naturalness with an accuracy spanning from 89% to 95%, depending on the area of the region of interest. The predictions of the proposed method are easy to interpret, something that various stakeholders may find valuable.
This study showcases the digitalization of Löfstad Castle in Sweden to contribute to preserving its heritage values. The castle and its collections are deteriorating due to an inappropriate indoor climate. To address this, thirteen cloud-connected sensor boxes, equipped with 84 sensors, were installed throughout the main building, from the basement to the attic, to continuously monitor various indoor environmental parameters. The collected extensive multi-parametric data form the basis for creating a parametric digital twin of the building. The digital twin and detailed data analytics offer a deeper understanding of indoor climate and guide the adoption of appropriate heating and ventilation strategies. The results revealed the need to address high humidity problems in the basement and on the ground floor, such as installing vapor barriers. Opportunities for adopting energy-efficient heating and ventilation strategies on the upper floors were also highlighted. The digitalization solution and findings are not only applicable to Löfstad Castle but also provide valuable guidance for the conservation of other historic buildings facing similar challenges.
The assessment of the origin of the anthropogenic contamination in marine regions impacted by other sources than global fallout is a challenge. This is the case of the west coast of Sweden, influenced by the liquid effluents released by the European Nuclear Reprocessing Plants through North Sea currents and by Baltic Sea local and regional sources, among others. This work focused on the study of anthropogenic actinides (${}^{236}$U, ${}^{237}$Np and ${}^{239,240}$Pu) in seawater and biota from a region close to Gothenburg where radioactive wastes with an unknown composition were dumped in 1964. To this aim, a radiochemical procedure for the sequential extraction of U, Np and Pu from biota samples and the subsequent analysis of ${}^{236}$U, ${}^{237}$Np, ${}^{239}$Pu and ${}^{240}$Pu by Accelerator Mass Spectrometry was developed. The method was validated through the study of two reference materials provided by the International Atomic Energy Agency (IAEA): IAEA-446 (Baltic Sea seaweed) and IAEA-437 (Mediterranean Sea mussels). The ${}^{233}$U$/{}^{236}$U atom ratio was also studied in the seawater samples. The obtained results indicate that the North Sea currents and global fallout
Economic growth in Sweden during the early 20th Century was largely driven by industry. A significant contributor to this growth was the installation of different kinds of engines used to power factories. We use newly digitized data on engines and their energy source by industry sector, and combine this with municipality-level data of workers per industry sector to construct a new variable reflecting economic output using dirty engines. In turn, we assess the average externality of dirty output on mortality in the short-run, as defined by deaths over the population in the baseline year. Our results show substantial increases of up to 17% higher mortality in cities where large increases to dirty engine installations occurred, which is largely driven by the elderly. We also run a placebo test using clean powered industry and find no effect on mortality.
Applications of learning analytics (LA) can raise concerns from students about their privacy in higher education contexts. Developing effective privacy-enhancing practices requires a systematic understanding of students' privacy concerns and how they vary across national and cultural dimensions. We conducted a survey study with established instruments to measure privacy concerns and cultural values for university students in five countries (Germany, South Korea, Spain, Sweden, and the United States; N = 762). The results show that students generally trusted institutions with their data and disclosed information as they perceived the risks to be manageable even though they felt somewhat limited in their ability to control their privacy. Across the five countries, German and Swedish students stood out as the most trusting and least concerned, especially compared to US students who reported greater perceived risk and less control. Students in South Korea and Spain responded similarly on all five privacy dimensions (perceived privacy risk, perceived privacy control, privacy concerns, trusting beliefs, and non-self-disclosure behavior), despite their significant cultural differences. Cu
This paper estimates how electricity price divergence within Sweden has affected incentives to invest in photovoltaic (PV) generation between 2016 and 2022 based on a synthetic control approach. Sweden is chosen as the research subject since it is together with Italy the only EU country with multiple bidding zones and is facing dramatic divergence in electricity prices between low-tariff bidding zones in Northern and high-tariff bidding zones in Southern Sweden since 2020. The results indicate that PV uptake in municipalities located north of the bidding zone border is reduced by 40.9-48% compared to their Southern counterparts. Based on these results, the creation of separate bidding zones within countries poses a threat to the expansion of PV generation and other renewables since it disincentivizes investment in areas with low electricity prices.
The FREIA Laboratory at Uppsala University, Sweden, has completed the evaluation of 13 double-spoke cavity cryomodules for ESS. This is the first time double-spoke cavities will be deployed in a real machine. This paper summarizes testing procedures and statistics of the results and lessons learned.
The spread of COVID-19 disease affected people's lives worldwide, particularly their travel behaviours and how they performed daily activities. During the first wave of the pandemic, spring 2020, countries adopted different strategies to contain the spread of the virus. The aim of this paper is to analyse the changes in mobility behaviours, focusing on the sustainability level of modal choices caused by the pandemic in two countries with different containment policies in place: Italy and Sweden. Survey data uncovered which transport means was the most used for three different trip purposes (grocery shopping, non-grocery shopping and commuting) both before and during the first wave of the pandemic. The variation in the sustainability level of modal choices was then observed through descriptive statistics and significance tests. By estimating three multinomial logistic regression models, one for each trip purpose, we tried to identify which factors, beyond the country, affected the variation in the sustainability level of the modal choice with the beginning of the pandemic. Results show a greater reduction in mobility among the Italian sample compared to the Swedish one, especially f
Even though many of the experiments leading to the standard model of particle physics were done at large accelerator laboratories in the US and at CERN[1] many exciting developments happened in smaller national facilities all over the world. In this report we highlight the history of accelerator facilities in Sweden which was home to the highest-energy cyclotron in Europe for some time in the early 1950s. [1] For a brief history of this story see: V. Ziemann, Beams -- the Story of Particle Accelerators and the Science they Discover, Copernicus books, Springer 2024.
Scholars have not asked why so many governments created ad hoc scientific advisory bodies (ahSABs) to address the Covid-19 pandemic instead of relying on existing public health infrastructure. We address this neglected question with an exploratory study of the US, UK, Sweden, Italy, Poland, and Uganda. Drawing on our case studies and the blame-avoidance literature, we find that ahSABs are created to excuse unpopular policies and take the blame should things go wrong. Thus, membership typically represents a narrow range of perspectives. An ahSAB is a good scapegoat because it does little to reduce government discretion and has limited ability to deflect blame back to government. Our explanation of our deviant case of Sweden, that did not create and ahSAB, reinforces our general principles. We draw the policy inference that ahSAB membership should be vetted by the legislature to ensure broad membership.
The real-time analysis of infectious disease surveillance data, e.g., in the form of a time-series of reported cases or fatalities, is essential in obtaining situational awareness about the current dynamics of an adverse health event such as the COVID-19 pandemic. This real-time analysis is complicated by reporting delays that lead to underreporting of the number of events for the most recent time points (e.g., days or weeks). This can lead to misconceptions by the interpreter, e.g., the media or the public, as was the case with the time-series of reported fatalities during the COVID-19 pandemic in Sweden. Nowcasting methods provide real-time estimates of the complete number of events using the incomplete time-series of currently reported events by using information about the reporting delays from the past. Here, we consider nowcasting the number of COVID-19-related fatalities in Sweden. We propose a flexible Bayesian approach, extending existing nowcasting methods by incorporating regression components to accommodate additional information provided by leading indicators such as time-series of the number of reported cases and ICU admissions. By a retrospective evaluation, we show t